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[SOURCE: https://arstechnica.com/ai/2026/02/an-ai-coding-bot-took-down-amazon-web-services/#comments] | [TOKENS: 1677] |
Mode +o Kiro An AI coding bot took down Amazon Web Services Blames “user error, not AI error” for incident in December involving its Kiro tool. Rafe Rosner-Uddin, Financial Times – Feb 20, 2026 9:13 am | 87 Credit: Getty Credit: Getty Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav Amazon’s cloud unit has suffered at least two outages due to errors involving its own AI tools, leading some employees to raise doubts about the US tech giant’s push to roll out these coding assistants. Amazon Web Services experienced a 13-hour interruption to one system used by its customers in mid-December after engineers allowed its Kiro AI coding tool to make certain changes, according to four people familiar with the matter. The people said the agentic tool, which can take autonomous actions on behalf of users, determined that the best course of action was to “delete and recreate the environment.” Amazon posted an internal postmortem about the “outage” of the AWS system, which lets customers explore the costs of its services. Multiple Amazon employees told the FT that this was the second occasion in recent months in which one of the group’s AI tools had been at the center of a service disruption. “We’ve already seen at least two production outages [in the past few months],” said one senior AWS employee. “The engineers let the AI [agent] resolve an issue without intervention. The outages were small but entirely foreseeable.” AWS, which accounts for 60 percent of Amazon’s operating profits, is seeking to build and deploy AI tools including “agents” capable of taking actions independently based on human instructions. Like many Big Tech companies, it is seeking to sell this technology to outside customers. The incidents highlight the risk that these nascent AI tools can misbehave and cause disruptions. Amazon said it was a “coincidence that AI tools were involved” and that “the same issue could occur with any developer tool or manual action.” “In both instances, this was user error, not AI error,” Amazon said, adding that it had not seen evidence that mistakes were more common with AI tools. The company said the incident in December was an “extremely limited event” affecting only a single service in parts of mainland China. Amazon added that the second incident did not have an impact on a “customer facing AWS service.” Neither disruption was anywhere near as severe as a 15-hour AWS outage in October 2025 that forced multiple customers’ apps and websites offline—including OpenAI’s ChatGPT. Employees said the group’s AI tools were treated as an extension of an operator and given the same permissions. In these two cases, the engineers involved did not require a second person’s approval before making changes, as would normally be the case. Amazon said that by default its Kiro tool “requests authorisation before taking any action” but said the engineer involved in the December incident had “broader permissions than expected—a user access control issue, not an AI autonomy issue.” AWS launched Kiro in July. It said the coding assistant would advance beyond “vibe coding”—which allows users to quickly build applications—to instead write code based on a set of specifications. The group had earlier relied on its Amazon Q Developer product, an AI-enabled chatbot, to help engineers write code. This was involved in the earlier outage, three of the employees said. Some Amazon employees said they were still skeptical of AI tools’ utility for the bulk of their work given the risk of error. They added that the company had set a target for 80 percent of developers to use AI for coding tasks at least once a week and was closely tracking adoption. Amazon said it was experiencing strong customer growth for Kiro and that it wanted customers and employees to benefit from efficiency gains. “Following the December incident, AWS implemented numerous safeguards,” including mandatory peer review and staff training, Amazon added. © 2026 The Financial Times Ltd. All rights reserved. Not to be redistributed, copied, or modified in any way. Financial Times Financial Times 87 Comments An AI coding bot took down Amazon Web Services Blames “user error, not AI error” for incident in December involving its Kiro tool. Amazon’s cloud unit has suffered at least two outages due to errors involving its own AI tools, leading some employees to raise doubts about the US tech giant’s push to roll out these coding assistants. Amazon Web Services experienced a 13-hour interruption to one system used by its customers in mid-December after engineers allowed its Kiro AI coding tool to make certain changes, according to four people familiar with the matter. The people said the agentic tool, which can take autonomous actions on behalf of users, determined that the best course of action was to “delete and recreate the environment.” Amazon posted an internal postmortem about the “outage” of the AWS system, which lets customers explore the costs of its services. Multiple Amazon employees told the FT that this was the second occasion in recent months in which one of the group’s AI tools had been at the center of a service disruption. “We’ve already seen at least two production outages [in the past few months],” said one senior AWS employee. “The engineers let the AI [agent] resolve an issue without intervention. The outages were small but entirely foreseeable.” AWS, which accounts for 60 percent of Amazon’s operating profits, is seeking to build and deploy AI tools including “agents” capable of taking actions independently based on human instructions. Like many Big Tech companies, it is seeking to sell this technology to outside customers. The incidents highlight the risk that these nascent AI tools can misbehave and cause disruptions. Amazon said it was a “coincidence that AI tools were involved” and that “the same issue could occur with any developer tool or manual action.” “In both instances, this was user error, not AI error,” Amazon said, adding that it had not seen evidence that mistakes were more common with AI tools. The company said the incident in December was an “extremely limited event” affecting only a single service in parts of mainland China. Amazon added that the second incident did not have an impact on a “customer facing AWS service.” Neither disruption was anywhere near as severe as a 15-hour AWS outage in October 2025 that forced multiple customers’ apps and websites offline—including OpenAI’s ChatGPT. Employees said the group’s AI tools were treated as an extension of an operator and given the same permissions. In these two cases, the engineers involved did not require a second person’s approval before making changes, as would normally be the case. Amazon said that by default its Kiro tool “requests authorisation before taking any action” but said the engineer involved in the December incident had “broader permissions than expected—a user access control issue, not an AI autonomy issue.” AWS launched Kiro in July. It said the coding assistant would advance beyond “vibe coding”—which allows users to quickly build applications—to instead write code based on a set of specifications. The group had earlier relied on its Amazon Q Developer product, an AI-enabled chatbot, to help engineers write code. This was involved in the earlier outage, three of the employees said. Some Amazon employees said they were still skeptical of AI tools’ utility for the bulk of their work given the risk of error. They added that the company had set a target for 80 percent of developers to use AI for coding tasks at least once a week and was closely tracking adoption. Amazon said it was experiencing strong customer growth for Kiro and that it wanted customers and employees to benefit from efficiency gains. “Following the December incident, AWS implemented numerous safeguards,” including mandatory peer review and staff training, Amazon added. © 2026 The Financial Times Ltd. All rights reserved. Not to be redistributed, copied, or modified in any way. Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/science/2026/02/rare-gifted-word-learner-dogs-like-to-share-their-toys/#comments] | [TOKENS: 2373] |
a difference in social style? Rare gifted word-learner dogs like to share their toys “It raises the possibility that social motivation plays a role in why some dogs end up learning object names.” Jennifer Ouellette – Feb 19, 2026 8:32 am | 74 Harvey would like to play. Credit: Claudia Fugazza/CC BY-SA Harvey would like to play. Credit: Claudia Fugazza/CC BY-SA Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav We love hearing about the latest findings coming out of an Eötvös Loránd University (ELU) research group focused on gifted word learner (GWL) dogs—if only for the pictures of adorable doggoes playing with their toys. Just last month, we learned that such dogs can learn the labels for new toys just by overhearing their owners talking about those toys. The group is back with yet another new paper, published in the journal Animal Cognition, presenting evidence that GWL dogs have a preference for novel toys and like to share them with their owners. That social interaction seems to be the key to the unique cognitive abilities of these rare dogs. As previously reported, ELU co-author Claudia Fugazza has been studying canine behavior and cognition for several years as part of the Genius Dog Challenge. For instance, the group’s 2022 study discovered that dogs store key sensory features about their toys—notably what they look like and how they smell—and recall those features when searching for the named toy. Prior studies had suggested that dogs typically rely on vision, or a combination of sight and smell, to locate target objects. GWL dogs can also identify objects based on verbal labels. Last fall, Fugazza’s group discovered that certain dogs can not only memorize the names of objects like their favorite toys, but also extend those labels to entirely new objects with a similar function, regardless of whether or not they are similar in appearance. It’s a cognitively advanced ability known as “label extension,” and for animals to acquire it usually involves years of intensive training in captivity. But the dogs in this new study developed the ability to classify their toys by function with no formal training, merely by playing naturally with their owners. It’s akin to a person calling a hammer and a rock by the same name, or a child understanding that “cup” can describe a mug, a glass, or a tumbler because they serve the same function. This time around, the group recruited 10 GWL dogs and 21 non-GWL dogs, all border collies, since this is the most common breed to fall into the GWL category. They compiled a list of eight toys: two labeled, two unlabeled, and four that were new to each dog. What’s their motivation? Roy is playing with his caretaker. A. Sommese et al., 2026 Roy is playing with his caretaker. A. Sommese et al., 2026 The different toys used during the experiment. A. Sommese et al., 2026 The different toys used during the experiment. A. Sommese et al., 2026 Roy is playing with his caretaker. A. Sommese et al., 2026 The different toys used during the experiment. A. Sommese et al., 2026 There was a two-week period during which owners familiarized the dogs with the toys once a day for at least 10 minutes. Each toy was presented separately. For the labeled toys, owners moved the toy while crouched on the floor, repeatedly naming the toy (“Look at the [toy name]! Here is the [toy name]”). They did not name the unlabeled toys. Owners devoted an equal amount of time to all the toys. Novel toys were excluded from the familiarization phase. After that period, each dog participated in two 90-second trials. The dogs were provided free access to the toys (washed with soap to control for odor cues). In the first trial, owners entered first and placed the labeled and unlabeled toys, plus two of the novel ones, on the floor and stood at a distance, passive and ignoring the dogs as the latter explored the toys. After a five-minute break, the test was repeated with the other two novel toys. All tests were recorded remotely and the footage subsequently analyzed. Human babies are known to pay more attention to named objects, and the authors thought the GWL dogs would show a similar response, but that’s not what happened. All the dogs, whether they were GWL dogs or not, strongly preferred the new toys, and there were no significant differences between the two groups of dogs in terms of how much time they spent playing with labeled versus unlabeled. So just hearing toy names does not automatically increase a dog’s attention. However, the GWL dogs were much more likely to pick up a toy—particularly the new ones—and bring it to their owner, clearly attempting to get said owner to play with them. The typical dogs were more likely to opt for passive physical contact with their owners. The authors interpreted this as a difference in social style rather than curiosity, possibly mirroring the way human babies try to communicate with parents by pointing or showing objects to them. “The way these dogs actively recruit humans into interactions around novel objects is intriguing,” said co-author Andrea Sommese of the University of Veterinary Medicine in Vienna, Austria. “It raises the possibility that social motivation plays a role in why some dogs end up learning object names. Our results suggest that to understand why some dogs learn words, we may need to look less at the toys and more at the relationship. This opens new directions for studying how language-related skills can emerge in species that live so closely with humans.” Animal Cognition, 2026. DOI: 10.1007/s10071-026-02047-3 (About DOIs). Jennifer Ouellette Senior Writer Jennifer Ouellette Senior Writer Jennifer is a senior writer at Ars Technica with a particular focus on where science meets culture, covering everything from physics and related interdisciplinary topics to her favorite films and TV series. Jennifer lives in Baltimore with her spouse, physicist Sean M. Carroll, and their two cats, Ariel and Caliban. 74 Comments Rare gifted word-learner dogs like to share their toys “It raises the possibility that social motivation plays a role in why some dogs end up learning object names.” We love hearing about the latest findings coming out of an Eötvös Loránd University (ELU) research group focused on gifted word learner (GWL) dogs—if only for the pictures of adorable doggoes playing with their toys. Just last month, we learned that such dogs can learn the labels for new toys just by overhearing their owners talking about those toys. The group is back with yet another new paper, published in the journal Animal Cognition, presenting evidence that GWL dogs have a preference for novel toys and like to share them with their owners. That social interaction seems to be the key to the unique cognitive abilities of these rare dogs. As previously reported, ELU co-author Claudia Fugazza has been studying canine behavior and cognition for several years as part of the Genius Dog Challenge. For instance, the group’s 2022 study discovered that dogs store key sensory features about their toys—notably what they look like and how they smell—and recall those features when searching for the named toy. Prior studies had suggested that dogs typically rely on vision, or a combination of sight and smell, to locate target objects. GWL dogs can also identify objects based on verbal labels. Last fall, Fugazza’s group discovered that certain dogs can not only memorize the names of objects like their favorite toys, but also extend those labels to entirely new objects with a similar function, regardless of whether or not they are similar in appearance. It’s a cognitively advanced ability known as “label extension,” and for animals to acquire it usually involves years of intensive training in captivity. But the dogs in this new study developed the ability to classify their toys by function with no formal training, merely by playing naturally with their owners. It’s akin to a person calling a hammer and a rock by the same name, or a child understanding that “cup” can describe a mug, a glass, or a tumbler because they serve the same function. This time around, the group recruited 10 GWL dogs and 21 non-GWL dogs, all border collies, since this is the most common breed to fall into the GWL category. They compiled a list of eight toys: two labeled, two unlabeled, and four that were new to each dog. What’s their motivation? There was a two-week period during which owners familiarized the dogs with the toys once a day for at least 10 minutes. Each toy was presented separately. For the labeled toys, owners moved the toy while crouched on the floor, repeatedly naming the toy (“Look at the [toy name]! Here is the [toy name]”). They did not name the unlabeled toys. Owners devoted an equal amount of time to all the toys. Novel toys were excluded from the familiarization phase. After that period, each dog participated in two 90-second trials. The dogs were provided free access to the toys (washed with soap to control for odor cues). In the first trial, owners entered first and placed the labeled and unlabeled toys, plus two of the novel ones, on the floor and stood at a distance, passive and ignoring the dogs as the latter explored the toys. After a five-minute break, the test was repeated with the other two novel toys. All tests were recorded remotely and the footage subsequently analyzed. Human babies are known to pay more attention to named objects, and the authors thought the GWL dogs would show a similar response, but that’s not what happened. All the dogs, whether they were GWL dogs or not, strongly preferred the new toys, and there were no significant differences between the two groups of dogs in terms of how much time they spent playing with labeled versus unlabeled. So just hearing toy names does not automatically increase a dog’s attention. However, the GWL dogs were much more likely to pick up a toy—particularly the new ones—and bring it to their owner, clearly attempting to get said owner to play with them. The typical dogs were more likely to opt for passive physical contact with their owners. The authors interpreted this as a difference in social style rather than curiosity, possibly mirroring the way human babies try to communicate with parents by pointing or showing objects to them. “The way these dogs actively recruit humans into interactions around novel objects is intriguing,” said co-author Andrea Sommese of the University of Veterinary Medicine in Vienna, Austria. “It raises the possibility that social motivation plays a role in why some dogs end up learning object names. Our results suggest that to understand why some dogs learn words, we may need to look less at the toys and more at the relationship. This opens new directions for studying how language-related skills can emerge in species that live so closely with humans.” Animal Cognition, 2026. DOI: 10.1007/s10071-026-02047-3 (About DOIs). Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/ai/2026/02/openclaw-security-fears-lead-meta-other-ai-firms-to-restrict-its-use/] | [TOKENS: 2387] |
Fear the claw OpenClaw security fears lead Meta, other AI firms to restrict its use The viral agentic AI tool is known for being highly capable but also wildly unpredictable. Paresh Dave, wired.com – Feb 19, 2026 9:11 am | 131 Credit: Carmen Vlasceanu via Getty Credit: Carmen Vlasceanu via Getty Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav Last month, Jason Grad issued a late-night warning to the 20 employees at his tech startup. “You’ve likely seen Clawdbot trending on X/LinkedIn. While cool, it is currently unvetted and high-risk for our environment,” he wrote in a Slack message with a red siren emoji. “Please keep Clawdbot off all company hardware and away from work-linked accounts.” Grad isn’t the only tech executive who has raised concerns to staff about the experimental agentic AI tool, which was briefly known as MoltBot and is now named OpenClaw. A Meta executive says he recently told his team to keep OpenClaw off their regular work laptops or risk losing their jobs. The executive told reporters he believes the software is unpredictable and could lead to a privacy breach if used in otherwise secure environments. He spoke on the condition of anonymity to speak frankly. Peter Steinberger, OpenClaw’s solo founder, launched it as a free, open source tool last November. But its popularity surged last month as other coders contributed features and began sharing their experiences using it on social media. Last week, Steinberger joined ChatGPT developer OpenAI, which says it will keep OpenClaw open source and support it through a foundation. OpenClaw requires basic software engineering knowledge to set up. After that, it only needs limited direction to take control of a user’s computer and interact with other apps to assist with tasks such as organizing files, conducting web research, and shopping online. Some cybersecurity professionals have publicly urged companies to take measures to strictly control how their workforces use OpenClaw. And the recent bans show how companies are moving quickly to ensure security is prioritized ahead of their desire to experiment with emerging AI technologies. “Our policy is, ‘mitigate first, investigate second’ when we come across anything that could be harmful to our company, users, or clients,” says Grad, who is cofounder and CEO of Massive, which provides Internet proxy tools to millions of users and businesses. His warning to staff went out on January 26, before any of his employees had installed OpenClaw, he says. At another tech company, Valere, which works on software for organizations including Johns Hopkins University, an employee posted about OpenClaw on January 29 on an internal Slack channel for sharing new tech to potentially try out. The company’s president quickly responded that use of OpenClaw was strictly banned, Valere CEO Guy Pistone tells WIRED. “If it got access to one of our developer’s machines, it could get access to our cloud services and our clients’ sensitive information, including credit card information and GitHub codebases,” Pistone says. “It’s pretty good at cleaning up some of its actions, which also scares me.” A week later, Pistone did allow Valere’s research team to run OpenClaw on an employee’s old computer. The goal was to identify flaws in the software and potential fixes to make it more secure. The research team later advised limiting who can give orders to OpenClaw and exposing it to the Internet only with a password in place for its control panel to prevent unwanted access. In a report shared with WIRED, the Valere researchers added that users have to “accept that the bot can be tricked.” For instance, if OpenClaw is set up to summarize a user’s email, a hacker could send a malicious email to the person instructing the AI to share copies of files on the person’s computer. But Pistone is confident that safeguards can be put in place to make OpenClaw more secure. He has given a team at Valere 60 days to investigate. “If we don’t think we can do it in a reasonable time, we’ll forgo it,” he says. “Whoever figures out how to make it secure for businesses is definitely going to have a winner.” Some companies concerned about OpenClaw are choosing to trust the cybersecurity protections they already have in place rather than introduce a formal or one-off ban. A CEO of a major software company says only about 15 programs are allowed on corporate devices. Anything else should be automatically blocked, says the executive, who spoke on the condition of anonymity to discuss internal security protocols. He says that while OpenClaw is innovative, he doubts that it will find a way to operate on the company’s network undetected. Jan-Joost den Brinker, chief technology officer at Prague-based compliance software developer Dubrink, says he bought a dedicated machine not connected to company systems or accounts that employees can use to play around with OpenClaw. “We aren’t solving business problems with OpenClaw at the moment,” he says. Massive, the web proxy company, is cautiously exploring OpenClaw’s commercial possibilities. Grad says it tested the AI tool on isolated machines in the cloud and then, last week, released ClawPod, a way for OpenClaw agents to use Massive’s services to browse the web. While OpenClaw is still not welcome on Massive’s systems without protections in place, the allure of the new technology and its moneymaking potential was too great to ignore. OpenClaw “might be a glimpse into the future. That’s why we’re building for it,” Grad says. This story originally appeared on wired.com. WIRED WIRED Wired.com is your essential daily guide to what's next, delivering the most original and complete take you'll find anywhere on innovation's impact on technology, science, business and culture. 131 Comments OpenClaw security fears lead Meta, other AI firms to restrict its use The viral agentic AI tool is known for being highly capable but also wildly unpredictable. Last month, Jason Grad issued a late-night warning to the 20 employees at his tech startup. “You’ve likely seen Clawdbot trending on X/LinkedIn. While cool, it is currently unvetted and high-risk for our environment,” he wrote in a Slack message with a red siren emoji. “Please keep Clawdbot off all company hardware and away from work-linked accounts.” Grad isn’t the only tech executive who has raised concerns to staff about the experimental agentic AI tool, which was briefly known as MoltBot and is now named OpenClaw. A Meta executive says he recently told his team to keep OpenClaw off their regular work laptops or risk losing their jobs. The executive told reporters he believes the software is unpredictable and could lead to a privacy breach if used in otherwise secure environments. He spoke on the condition of anonymity to speak frankly. Peter Steinberger, OpenClaw’s solo founder, launched it as a free, open source tool last November. But its popularity surged last month as other coders contributed features and began sharing their experiences using it on social media. Last week, Steinberger joined ChatGPT developer OpenAI, which says it will keep OpenClaw open source and support it through a foundation. OpenClaw requires basic software engineering knowledge to set up. After that, it only needs limited direction to take control of a user’s computer and interact with other apps to assist with tasks such as organizing files, conducting web research, and shopping online. Some cybersecurity professionals have publicly urged companies to take measures to strictly control how their workforces use OpenClaw. And the recent bans show how companies are moving quickly to ensure security is prioritized ahead of their desire to experiment with emerging AI technologies. “Our policy is, ‘mitigate first, investigate second’ when we come across anything that could be harmful to our company, users, or clients,” says Grad, who is cofounder and CEO of Massive, which provides Internet proxy tools to millions of users and businesses. His warning to staff went out on January 26, before any of his employees had installed OpenClaw, he says. At another tech company, Valere, which works on software for organizations including Johns Hopkins University, an employee posted about OpenClaw on January 29 on an internal Slack channel for sharing new tech to potentially try out. The company’s president quickly responded that use of OpenClaw was strictly banned, Valere CEO Guy Pistone tells WIRED. “If it got access to one of our developer’s machines, it could get access to our cloud services and our clients’ sensitive information, including credit card information and GitHub codebases,” Pistone says. “It’s pretty good at cleaning up some of its actions, which also scares me.” A week later, Pistone did allow Valere’s research team to run OpenClaw on an employee’s old computer. The goal was to identify flaws in the software and potential fixes to make it more secure. The research team later advised limiting who can give orders to OpenClaw and exposing it to the Internet only with a password in place for its control panel to prevent unwanted access. In a report shared with WIRED, the Valere researchers added that users have to “accept that the bot can be tricked.” For instance, if OpenClaw is set up to summarize a user’s email, a hacker could send a malicious email to the person instructing the AI to share copies of files on the person’s computer. But Pistone is confident that safeguards can be put in place to make OpenClaw more secure. He has given a team at Valere 60 days to investigate. “If we don’t think we can do it in a reasonable time, we’ll forgo it,” he says. “Whoever figures out how to make it secure for businesses is definitely going to have a winner.” Some companies concerned about OpenClaw are choosing to trust the cybersecurity protections they already have in place rather than introduce a formal or one-off ban. A CEO of a major software company says only about 15 programs are allowed on corporate devices. Anything else should be automatically blocked, says the executive, who spoke on the condition of anonymity to discuss internal security protocols. He says that while OpenClaw is innovative, he doubts that it will find a way to operate on the company’s network undetected. Jan-Joost den Brinker, chief technology officer at Prague-based compliance software developer Dubrink, says he bought a dedicated machine not connected to company systems or accounts that employees can use to play around with OpenClaw. “We aren’t solving business problems with OpenClaw at the moment,” he says. Massive, the web proxy company, is cautiously exploring OpenClaw’s commercial possibilities. Grad says it tested the AI tool on isolated machines in the cloud and then, last week, released ClawPod, a way for OpenClaw agents to use Massive’s services to browse the web. While OpenClaw is still not welcome on Massive’s systems without protections in place, the allure of the new technology and its moneymaking potential was too great to ignore. OpenClaw “might be a glimpse into the future. That’s why we’re building for it,” Grad says. This story originally appeared on wired.com. Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/science/2026/02/newly-hatched-chickens-form-the-same-sound-association-we-do/#comments] | [TOKENS: 1715] |
Sounds like…. From chickens to humans, animals think “bouba” sounds round There seems to be a deep-seated association between sounds and shapes. John Timmer – Feb 19, 2026 2:38 pm | 64 Credit: RubberBall Productions Credit: RubberBall Productions Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav Does “bouba” sound round to you? How about “maluma”? Neither are real words, but we’ve known for decades that people who hear them tend to associate them with round objects. There have been plenty of ideas put forward about why that would be the case, and most of them have turned out to be wrong. Now, in perhaps the weirdest bit of evidence to date, researchers have found that even newly hatched chickens seem to associate “bouba” with round shapes. The initial finding dates all the way back to 1947, when someone discovered that people associated some word-like sounds with rounded shapes, and others with spiky ones. In the years since, that association got formalized as the bouba/kiki effect, received a fair bit of experimental attention, and ended up with an extensive Wikipedia entry. One of the initial ideas to explain it was similarity to actual words (either phonetically or via the characters used to spell them), but then studies with speakers of different languages and alphabets showed that it is likely a general human tendency. The association also showed up in infants as young as 4 months old, well before they master speaking or spelling. Attempts to find the bouba/kiki effects in other primates, however, came up empty. That led to some speculation that it might be evidence of a strictly human processing ability that underlies our capacity to learn sophisticated languages. A team of Italian researchers—Maria Loconsole, Silvia Benavides-Varela, and Lucia Regolin—now have evidence that that isn’t true either. They decided to look for the bouba/kiki effect well beyond primates, instead turning to newly hatched chickens, only one or three days old. That may sound a bit odd, but chickens have a key advantage beyond ready availability: unlike a 4-month-old human, newly hatched chicks are fully mobile and able to interact with the world. Control experiments using silence or classical music showed that the young chicks are somewhat drawn to a rounded shape. But recordings of a person saying “bouba” caused 80 percent of the chicks to move to a rounded shape first. If a recording of “kiki” was played instead, that number dropped to just 25 percent, with the numbers going to a spiky shape rising. The effect is somewhat stronger in 3-day-old chicks, but it still showed up in the animals that were tested just one day after hatching. The researchers attribute the bouba/kiki effect to what’s called a “crossmodal correspondence,” in which input from one sensory system influences our perception of another. Some of these make a degree of sense, such as associating high pitches with smaller objects, and low pitches with larger ones, something that’s generally consistent with how those pitches are produced. Beyond humans, that has been observed in animals as distant as dogs and tortoises—but not chickens. Other crossmodal correspondences are far less intuitive, such as associating high pitches with bright lighting, which has also been found in species as diverse as chimps and tortoises. In any case, the results argue strongly that the bouba/kiki effect does not represent a capacity that’s distinct to animals that use complex language. They also suggest that the failure to find it in other primates is probably a product of doing the testing in adult primates, which probably have a complicated mixture of motivations that can override simple instinctual preferences. Science, 2026. DOI: 10.1126/science.adq7188 (About DOIs). John Timmer Senior Science Editor John Timmer Senior Science Editor John is Ars Technica's science editor. He has a Bachelor of Arts in Biochemistry from Columbia University, and a Ph.D. in Molecular and Cell Biology from the University of California, Berkeley. When physically separated from his keyboard, he tends to seek out a bicycle, or a scenic location for communing with his hiking boots. 64 Comments From chickens to humans, animals think “bouba” sounds round There seems to be a deep-seated association between sounds and shapes. Does “bouba” sound round to you? How about “maluma”? Neither are real words, but we’ve known for decades that people who hear them tend to associate them with round objects. There have been plenty of ideas put forward about why that would be the case, and most of them have turned out to be wrong. Now, in perhaps the weirdest bit of evidence to date, researchers have found that even newly hatched chickens seem to associate “bouba” with round shapes. The initial finding dates all the way back to 1947, when someone discovered that people associated some word-like sounds with rounded shapes, and others with spiky ones. In the years since, that association got formalized as the bouba/kiki effect, received a fair bit of experimental attention, and ended up with an extensive Wikipedia entry. One of the initial ideas to explain it was similarity to actual words (either phonetically or via the characters used to spell them), but then studies with speakers of different languages and alphabets showed that it is likely a general human tendency. The association also showed up in infants as young as 4 months old, well before they master speaking or spelling. Attempts to find the bouba/kiki effects in other primates, however, came up empty. That led to some speculation that it might be evidence of a strictly human processing ability that underlies our capacity to learn sophisticated languages. A team of Italian researchers—Maria Loconsole, Silvia Benavides-Varela, and Lucia Regolin—now have evidence that that isn’t true either. They decided to look for the bouba/kiki effect well beyond primates, instead turning to newly hatched chickens, only one or three days old. That may sound a bit odd, but chickens have a key advantage beyond ready availability: unlike a 4-month-old human, newly hatched chicks are fully mobile and able to interact with the world. Control experiments using silence or classical music showed that the young chicks are somewhat drawn to a rounded shape. But recordings of a person saying “bouba” caused 80 percent of the chicks to move to a rounded shape first. If a recording of “kiki” was played instead, that number dropped to just 25 percent, with the numbers going to a spiky shape rising. The effect is somewhat stronger in 3-day-old chicks, but it still showed up in the animals that were tested just one day after hatching. The researchers attribute the bouba/kiki effect to what’s called a “crossmodal correspondence,” in which input from one sensory system influences our perception of another. Some of these make a degree of sense, such as associating high pitches with smaller objects, and low pitches with larger ones, something that’s generally consistent with how those pitches are produced. Beyond humans, that has been observed in animals as distant as dogs and tortoises—but not chickens. Other crossmodal correspondences are far less intuitive, such as associating high pitches with bright lighting, which has also been found in species as diverse as chimps and tortoises. In any case, the results argue strongly that the bouba/kiki effect does not represent a capacity that’s distinct to animals that use complex language. They also suggest that the failure to find it in other primates is probably a product of doing the testing in adult primates, which probably have a complicated mixture of motivations that can override simple instinctual preferences. Science, 2026. DOI: 10.1126/science.adq7188 (About DOIs). Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/cars/2026/02/f1-preseason-tests-shows-how-different-2026-will-be/#comments] | [TOKENS: 3546] |
Bacon briefcase F1: Preseason tests show how different 2026 will be Everyone’s trying to get mileage as F1 undergoes huge technical changes. Jonathan M. Gitlin – Feb 19, 2026 1:22 pm | 53 Red Bull promoted Isack Hadjar to the top team for 2026. Will he fare any better against Max Verstappen than past teammates? Credit: Marcel van Dorst/EYE4IMAGES/NurPhoto via Getty Images Red Bull promoted Isack Hadjar to the top team for 2026. Will he fare any better against Max Verstappen than past teammates? Credit: Marcel van Dorst/EYE4IMAGES/NurPhoto via Getty Images Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav It’s just two weeks until F1 gets underway in Australia, and teams are currently in Bahrain, midway through their third and final preseason test. The 2026 season promises to be wildly different from those of the past few years, with all-new cars, engines, hybrid systems, and sustainable fuels entering the mix and shaking up the established order. You shouldn’t read too much into times from preseason testing. The cars don’t have to conform to the in-season rules as teams test new components or fit-test rigs; for example, glowing brake discs could once again be seen on some cars that weren’t running wheel covers at an earlier test, something we’re unlikely to see during actual races. You also don’t know how much fuel—and therefore extra weight—anyone is carrying. In the past, some teams have even made headlines by running too light to set more competitive lap times in an effort to impress potential sponsors. And as the name explains, it’s a test, so drivers will be following run plans devised with their engineers to learn specific things about their new cars. Or as one Internet wag once put it, the times mean as much as “a bacon briefcase.” All change That said, the tests are far from meaningless, particularly this year. After 12 years of using the same hybrid power units, the sport has moved to an all-new design. The internal combustion engine is still a turbocharged 1.6 L V6, but that turbocharger no longer features the MGU-H hybrid system that both captured waste energy from the spinning turbine and also eliminated turbo lag. The remaining hybrid system—the MGU-K that harvests and deploys energy from and to the rear wheels—is much more powerful than before and is paired with a 4 Mj (1.1 kWh) battery pack. And like many hybrid road cars, that kinetic energy can come from braking or the engine. Ferrari has shown real signs of speed during testing, but also a few problems. The contraption attached to the car measures wind pressure to correlate wind tunnel data with the real world. Credit: Ahmad AlShehab/NurPhoto via Getty Images Ferrari has shown real signs of speed during testing, but also a few problems. The contraption attached to the car measures wind pressure to correlate wind tunnel data with the real world. Credit: Ahmad AlShehab/NurPhoto via Getty Images Now, the V6 provides 400 kW (536 hp) and the MGU-K an additional 350 kW, as long as the battery has charge. Cars are allowed to deploy up to 8.5 mJ (2.4 kWh) of electrical energy per lap, so energy management—knowing when and how to harvest and when to deploy—will become as important to F1 drivers as it was during the LMP1h days at Le Mans, or currently in Formula E. As a result, we’ve seen some drivers try out new techniques, downshifting to a lower gear than might otherwise be used in order to keep the engine revs up (and therefore charging the battery). There’s also a phenomenon called “superclipping” (previously known as derating), where cars slow toward the ends of a straight even as their engine revs rise—here, the cars are sending some of that engine power to the battery instead of the rear wheels to fill the battery so the MGU-K can help shove the car out of the next corner. And that isn’t always consistent lap to lap, as battery state of charge or track conditions change and the cars’ onboard computers juggle how much energy to deploy. We may have to revisit that topic, as the teams have been asked to test a reduced power output of the MGU-K as a backup plan in case the fears of critics of the 2026 rules come to pass. Interestingly, the MGU-K won’t be used at race starts—it only begins to contribute above 50 km/h (31 mph). That’s to prevent the danger of some drivers depleting their batteries and therefore slowing much faster than others in the approach to the first or second corner at the start as they superclip, and it has also exposed a potential performance differentiator this year. Ferrari, which also provides power units to Haas and Cadillac, opted for smaller turbochargers that spin up more quickly; the other OEMs all went for larger turbos that generate higher peak power. Ferrari has gambled that the smaller, faster turbos will give it an advantage at race starts and when its drivers have to rely solely on their V6s. Sleek 2026 cars look good. Credit: Jakub Porzycki/NurPhoto via Getty Images 2026 cars look good. Credit: Jakub Porzycki/NurPhoto via Getty Images I’ll say this for the 2026 crop of cars: They sure look good. They’re a little shorter and narrower than last year’s cars, with slightly narrower tires and much greater diversity among the teams than in the tightly proscribed ground-effect era. Those rules, which ran from 2022 to 2025, gave such little leeway to the teams in design decisions that performance converged to within fractions of a percent across the entire grid. Now everyone looks quite different from one another. The big thing to look out for this year is who can shed the most drag in straight-line mode. Each car’s front and rear wings are now active, with a raised position called corner mode that generates lots of downforce, and straight mode, which drops both wings to minimize drag (and therefore the energy the car needs to go fast). Ferrari tested an interesting approach to this in Bahrain at one point, with rear wing elements that flipped a full 180 degrees. I wonder if we’ll see that in-season. The arguments about engine compression ratios are still ongoing. Briefly, Mercedes is believed to have used clever materials science to create an engine in which the compression ratio increases rather than decreases as the engine gets hot. For this year, engines are capped at a compression ratio of 16:1 but measured at ambient temperature. Next week, the teams and the sport’s organizers (the FIA) meet to discuss adding a hot test for compression ratios, which is unlikely to go Mercedes’ way. (For its part, Mercedes says there’s nothing illegal about its engines.) The Mercedes-powered teams (Mercedes, McLaren, Williams, and Alpine), as well as Honda-powered Aston Martin, have another potential problem. Each power unit has its own sustainable fuel; Mercedes’ is provided by Petronas and Honda’s by Aramco. To ensure it is indeed fully sustainable, there’s a homologation process with an independent third party to verify compliance throughout the supply chain. Unfortunately for these five teams, neither Petronas nor Aramco have finished this homologation process, with a deadline of March 1 fast approaching. Should that not happen in time, we’ll still see those five teams race, but they’ll use a substitute fuel that won’t be optimized for the engines that will burn it. Huge sums have been invested in Aston Martin, to little effect so far. Credit: Bradley Collyer/PA Images via Getty Images Huge sums have been invested in Aston Martin, to little effect so far. Credit: Bradley Collyer/PA Images via Getty Images I’m pretty sure the unbelievable reliability that’s been a feature of F1 for the last few seasons may be a thing of the past, at least for the first few races in 2026. Up and down the pit lane, teams have missed hours of practice sessions as they troubleshoot gremlins. Aston Martin looks particularly bad in this regard, even in comparison to brand-new Cadillac. Finally, we’re starting to get a better idea of how F1 coverage will work with the move to Apple TV here in the US. Apple TV users will find an F1 tab in the Apple TV app, but you can also use the standalone F1TV app with your Apple credentials. We still have to wait until the first weekend in March to find out which F1 feed and commentary Apple will use, but the F1TV app remains an excellent way to follow the sport, with in-house commentary, alternate commentary from the UK’s Sky TV, in-car feeds for each driver, and an archive of F1 races going back decades. Jonathan M. Gitlin Automotive Editor Jonathan M. Gitlin Automotive Editor Jonathan is the Automotive Editor at Ars Technica. He has a BSc and PhD in Pharmacology. In 2014 he decided to indulge his lifelong passion for the car by leaving the National Human Genome Research Institute and launching Ars Technica's automotive coverage. He lives in Washington, DC. 53 Comments F1: Preseason tests show how different 2026 will be Everyone’s trying to get mileage as F1 undergoes huge technical changes. It’s just two weeks until F1 gets underway in Australia, and teams are currently in Bahrain, midway through their third and final preseason test. The 2026 season promises to be wildly different from those of the past few years, with all-new cars, engines, hybrid systems, and sustainable fuels entering the mix and shaking up the established order. You shouldn’t read too much into times from preseason testing. The cars don’t have to conform to the in-season rules as teams test new components or fit-test rigs; for example, glowing brake discs could once again be seen on some cars that weren’t running wheel covers at an earlier test, something we’re unlikely to see during actual races. You also don’t know how much fuel—and therefore extra weight—anyone is carrying. In the past, some teams have even made headlines by running too light to set more competitive lap times in an effort to impress potential sponsors. And as the name explains, it’s a test, so drivers will be following run plans devised with their engineers to learn specific things about their new cars. Or as one Internet wag once put it, the times mean as much as “a bacon briefcase.” All change That said, the tests are far from meaningless, particularly this year. After 12 years of using the same hybrid power units, the sport has moved to an all-new design. The internal combustion engine is still a turbocharged 1.6 L V6, but that turbocharger no longer features the MGU-H hybrid system that both captured waste energy from the spinning turbine and also eliminated turbo lag. The remaining hybrid system—the MGU-K that harvests and deploys energy from and to the rear wheels—is much more powerful than before and is paired with a 4 Mj (1.1 kWh) battery pack. And like many hybrid road cars, that kinetic energy can come from braking or the engine. Now, the V6 provides 400 kW (536 hp) and the MGU-K an additional 350 kW, as long as the battery has charge. Cars are allowed to deploy up to 8.5 mJ (2.4 kWh) of electrical energy per lap, so energy management—knowing when and how to harvest and when to deploy—will become as important to F1 drivers as it was during the LMP1h days at Le Mans, or currently in Formula E. As a result, we’ve seen some drivers try out new techniques, downshifting to a lower gear than might otherwise be used in order to keep the engine revs up (and therefore charging the battery). There’s also a phenomenon called “superclipping” (previously known as derating), where cars slow toward the ends of a straight even as their engine revs rise—here, the cars are sending some of that engine power to the battery instead of the rear wheels to fill the battery so the MGU-K can help shove the car out of the next corner. And that isn’t always consistent lap to lap, as battery state of charge or track conditions change and the cars’ onboard computers juggle how much energy to deploy. We may have to revisit that topic, as the teams have been asked to test a reduced power output of the MGU-K as a backup plan in case the fears of critics of the 2026 rules come to pass. Interestingly, the MGU-K won’t be used at race starts—it only begins to contribute above 50 km/h (31 mph). That’s to prevent the danger of some drivers depleting their batteries and therefore slowing much faster than others in the approach to the first or second corner at the start as they superclip, and it has also exposed a potential performance differentiator this year. Ferrari, which also provides power units to Haas and Cadillac, opted for smaller turbochargers that spin up more quickly; the other OEMs all went for larger turbos that generate higher peak power. Ferrari has gambled that the smaller, faster turbos will give it an advantage at race starts and when its drivers have to rely solely on their V6s. Sleek I’ll say this for the 2026 crop of cars: They sure look good. They’re a little shorter and narrower than last year’s cars, with slightly narrower tires and much greater diversity among the teams than in the tightly proscribed ground-effect era. Those rules, which ran from 2022 to 2025, gave such little leeway to the teams in design decisions that performance converged to within fractions of a percent across the entire grid. Now everyone looks quite different from one another. The big thing to look out for this year is who can shed the most drag in straight-line mode. Each car’s front and rear wings are now active, with a raised position called corner mode that generates lots of downforce, and straight mode, which drops both wings to minimize drag (and therefore the energy the car needs to go fast). Ferrari tested an interesting approach to this in Bahrain at one point, with rear wing elements that flipped a full 180 degrees. I wonder if we’ll see that in-season. The arguments about engine compression ratios are still ongoing. Briefly, Mercedes is believed to have used clever materials science to create an engine in which the compression ratio increases rather than decreases as the engine gets hot. For this year, engines are capped at a compression ratio of 16:1 but measured at ambient temperature. Next week, the teams and the sport’s organizers (the FIA) meet to discuss adding a hot test for compression ratios, which is unlikely to go Mercedes’ way. (For its part, Mercedes says there’s nothing illegal about its engines.) The Mercedes-powered teams (Mercedes, McLaren, Williams, and Alpine), as well as Honda-powered Aston Martin, have another potential problem. Each power unit has its own sustainable fuel; Mercedes’ is provided by Petronas and Honda’s by Aramco. To ensure it is indeed fully sustainable, there’s a homologation process with an independent third party to verify compliance throughout the supply chain. Unfortunately for these five teams, neither Petronas nor Aramco have finished this homologation process, with a deadline of March 1 fast approaching. Should that not happen in time, we’ll still see those five teams race, but they’ll use a substitute fuel that won’t be optimized for the engines that will burn it. I’m pretty sure the unbelievable reliability that’s been a feature of F1 for the last few seasons may be a thing of the past, at least for the first few races in 2026. Up and down the pit lane, teams have missed hours of practice sessions as they troubleshoot gremlins. Aston Martin looks particularly bad in this regard, even in comparison to brand-new Cadillac. Finally, we’re starting to get a better idea of how F1 coverage will work with the move to Apple TV here in the US. Apple TV users will find an F1 tab in the Apple TV app, but you can also use the standalone F1TV app with your Apple credentials. We still have to wait until the first weekend in March to find out which F1 feed and commentary Apple will use, but the F1TV app remains an excellent way to follow the sport, with in-house commentary, alternate commentary from the UK’s Sky TV, in-car feeds for each driver, and an archive of F1 races going back decades. Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/ai/2026/02/openclaw-security-fears-lead-meta-other-ai-firms-to-restrict-its-use/#comments] | [TOKENS: 2387] |
Fear the claw OpenClaw security fears lead Meta, other AI firms to restrict its use The viral agentic AI tool is known for being highly capable but also wildly unpredictable. Paresh Dave, wired.com – Feb 19, 2026 9:11 am | 131 Credit: Carmen Vlasceanu via Getty Credit: Carmen Vlasceanu via Getty Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav Last month, Jason Grad issued a late-night warning to the 20 employees at his tech startup. “You’ve likely seen Clawdbot trending on X/LinkedIn. While cool, it is currently unvetted and high-risk for our environment,” he wrote in a Slack message with a red siren emoji. “Please keep Clawdbot off all company hardware and away from work-linked accounts.” Grad isn’t the only tech executive who has raised concerns to staff about the experimental agentic AI tool, which was briefly known as MoltBot and is now named OpenClaw. A Meta executive says he recently told his team to keep OpenClaw off their regular work laptops or risk losing their jobs. The executive told reporters he believes the software is unpredictable and could lead to a privacy breach if used in otherwise secure environments. He spoke on the condition of anonymity to speak frankly. Peter Steinberger, OpenClaw’s solo founder, launched it as a free, open source tool last November. But its popularity surged last month as other coders contributed features and began sharing their experiences using it on social media. Last week, Steinberger joined ChatGPT developer OpenAI, which says it will keep OpenClaw open source and support it through a foundation. OpenClaw requires basic software engineering knowledge to set up. After that, it only needs limited direction to take control of a user’s computer and interact with other apps to assist with tasks such as organizing files, conducting web research, and shopping online. Some cybersecurity professionals have publicly urged companies to take measures to strictly control how their workforces use OpenClaw. And the recent bans show how companies are moving quickly to ensure security is prioritized ahead of their desire to experiment with emerging AI technologies. “Our policy is, ‘mitigate first, investigate second’ when we come across anything that could be harmful to our company, users, or clients,” says Grad, who is cofounder and CEO of Massive, which provides Internet proxy tools to millions of users and businesses. His warning to staff went out on January 26, before any of his employees had installed OpenClaw, he says. At another tech company, Valere, which works on software for organizations including Johns Hopkins University, an employee posted about OpenClaw on January 29 on an internal Slack channel for sharing new tech to potentially try out. The company’s president quickly responded that use of OpenClaw was strictly banned, Valere CEO Guy Pistone tells WIRED. “If it got access to one of our developer’s machines, it could get access to our cloud services and our clients’ sensitive information, including credit card information and GitHub codebases,” Pistone says. “It’s pretty good at cleaning up some of its actions, which also scares me.” A week later, Pistone did allow Valere’s research team to run OpenClaw on an employee’s old computer. The goal was to identify flaws in the software and potential fixes to make it more secure. The research team later advised limiting who can give orders to OpenClaw and exposing it to the Internet only with a password in place for its control panel to prevent unwanted access. In a report shared with WIRED, the Valere researchers added that users have to “accept that the bot can be tricked.” For instance, if OpenClaw is set up to summarize a user’s email, a hacker could send a malicious email to the person instructing the AI to share copies of files on the person’s computer. But Pistone is confident that safeguards can be put in place to make OpenClaw more secure. He has given a team at Valere 60 days to investigate. “If we don’t think we can do it in a reasonable time, we’ll forgo it,” he says. “Whoever figures out how to make it secure for businesses is definitely going to have a winner.” Some companies concerned about OpenClaw are choosing to trust the cybersecurity protections they already have in place rather than introduce a formal or one-off ban. A CEO of a major software company says only about 15 programs are allowed on corporate devices. Anything else should be automatically blocked, says the executive, who spoke on the condition of anonymity to discuss internal security protocols. He says that while OpenClaw is innovative, he doubts that it will find a way to operate on the company’s network undetected. Jan-Joost den Brinker, chief technology officer at Prague-based compliance software developer Dubrink, says he bought a dedicated machine not connected to company systems or accounts that employees can use to play around with OpenClaw. “We aren’t solving business problems with OpenClaw at the moment,” he says. Massive, the web proxy company, is cautiously exploring OpenClaw’s commercial possibilities. Grad says it tested the AI tool on isolated machines in the cloud and then, last week, released ClawPod, a way for OpenClaw agents to use Massive’s services to browse the web. While OpenClaw is still not welcome on Massive’s systems without protections in place, the allure of the new technology and its moneymaking potential was too great to ignore. OpenClaw “might be a glimpse into the future. That’s why we’re building for it,” Grad says. This story originally appeared on wired.com. WIRED WIRED Wired.com is your essential daily guide to what's next, delivering the most original and complete take you'll find anywhere on innovation's impact on technology, science, business and culture. 131 Comments OpenClaw security fears lead Meta, other AI firms to restrict its use The viral agentic AI tool is known for being highly capable but also wildly unpredictable. Last month, Jason Grad issued a late-night warning to the 20 employees at his tech startup. “You’ve likely seen Clawdbot trending on X/LinkedIn. While cool, it is currently unvetted and high-risk for our environment,” he wrote in a Slack message with a red siren emoji. “Please keep Clawdbot off all company hardware and away from work-linked accounts.” Grad isn’t the only tech executive who has raised concerns to staff about the experimental agentic AI tool, which was briefly known as MoltBot and is now named OpenClaw. A Meta executive says he recently told his team to keep OpenClaw off their regular work laptops or risk losing their jobs. The executive told reporters he believes the software is unpredictable and could lead to a privacy breach if used in otherwise secure environments. He spoke on the condition of anonymity to speak frankly. Peter Steinberger, OpenClaw’s solo founder, launched it as a free, open source tool last November. But its popularity surged last month as other coders contributed features and began sharing their experiences using it on social media. Last week, Steinberger joined ChatGPT developer OpenAI, which says it will keep OpenClaw open source and support it through a foundation. OpenClaw requires basic software engineering knowledge to set up. After that, it only needs limited direction to take control of a user’s computer and interact with other apps to assist with tasks such as organizing files, conducting web research, and shopping online. Some cybersecurity professionals have publicly urged companies to take measures to strictly control how their workforces use OpenClaw. And the recent bans show how companies are moving quickly to ensure security is prioritized ahead of their desire to experiment with emerging AI technologies. “Our policy is, ‘mitigate first, investigate second’ when we come across anything that could be harmful to our company, users, or clients,” says Grad, who is cofounder and CEO of Massive, which provides Internet proxy tools to millions of users and businesses. His warning to staff went out on January 26, before any of his employees had installed OpenClaw, he says. At another tech company, Valere, which works on software for organizations including Johns Hopkins University, an employee posted about OpenClaw on January 29 on an internal Slack channel for sharing new tech to potentially try out. The company’s president quickly responded that use of OpenClaw was strictly banned, Valere CEO Guy Pistone tells WIRED. “If it got access to one of our developer’s machines, it could get access to our cloud services and our clients’ sensitive information, including credit card information and GitHub codebases,” Pistone says. “It’s pretty good at cleaning up some of its actions, which also scares me.” A week later, Pistone did allow Valere’s research team to run OpenClaw on an employee’s old computer. The goal was to identify flaws in the software and potential fixes to make it more secure. The research team later advised limiting who can give orders to OpenClaw and exposing it to the Internet only with a password in place for its control panel to prevent unwanted access. In a report shared with WIRED, the Valere researchers added that users have to “accept that the bot can be tricked.” For instance, if OpenClaw is set up to summarize a user’s email, a hacker could send a malicious email to the person instructing the AI to share copies of files on the person’s computer. But Pistone is confident that safeguards can be put in place to make OpenClaw more secure. He has given a team at Valere 60 days to investigate. “If we don’t think we can do it in a reasonable time, we’ll forgo it,” he says. “Whoever figures out how to make it secure for businesses is definitely going to have a winner.” Some companies concerned about OpenClaw are choosing to trust the cybersecurity protections they already have in place rather than introduce a formal or one-off ban. A CEO of a major software company says only about 15 programs are allowed on corporate devices. Anything else should be automatically blocked, says the executive, who spoke on the condition of anonymity to discuss internal security protocols. He says that while OpenClaw is innovative, he doubts that it will find a way to operate on the company’s network undetected. Jan-Joost den Brinker, chief technology officer at Prague-based compliance software developer Dubrink, says he bought a dedicated machine not connected to company systems or accounts that employees can use to play around with OpenClaw. “We aren’t solving business problems with OpenClaw at the moment,” he says. Massive, the web proxy company, is cautiously exploring OpenClaw’s commercial possibilities. Grad says it tested the AI tool on isolated machines in the cloud and then, last week, released ClawPod, a way for OpenClaw agents to use Massive’s services to browse the web. While OpenClaw is still not welcome on Massive’s systems without protections in place, the allure of the new technology and its moneymaking potential was too great to ignore. OpenClaw “might be a glimpse into the future. That’s why we’re building for it,” Grad says. This story originally appeared on wired.com. Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/science/2026/02/rare-gifted-word-learner-dogs-like-to-share-their-toys/] | [TOKENS: 2373] |
a difference in social style? Rare gifted word-learner dogs like to share their toys “It raises the possibility that social motivation plays a role in why some dogs end up learning object names.” Jennifer Ouellette – Feb 19, 2026 8:32 am | 74 Harvey would like to play. Credit: Claudia Fugazza/CC BY-SA Harvey would like to play. Credit: Claudia Fugazza/CC BY-SA Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav We love hearing about the latest findings coming out of an Eötvös Loránd University (ELU) research group focused on gifted word learner (GWL) dogs—if only for the pictures of adorable doggoes playing with their toys. Just last month, we learned that such dogs can learn the labels for new toys just by overhearing their owners talking about those toys. The group is back with yet another new paper, published in the journal Animal Cognition, presenting evidence that GWL dogs have a preference for novel toys and like to share them with their owners. That social interaction seems to be the key to the unique cognitive abilities of these rare dogs. As previously reported, ELU co-author Claudia Fugazza has been studying canine behavior and cognition for several years as part of the Genius Dog Challenge. For instance, the group’s 2022 study discovered that dogs store key sensory features about their toys—notably what they look like and how they smell—and recall those features when searching for the named toy. Prior studies had suggested that dogs typically rely on vision, or a combination of sight and smell, to locate target objects. GWL dogs can also identify objects based on verbal labels. Last fall, Fugazza’s group discovered that certain dogs can not only memorize the names of objects like their favorite toys, but also extend those labels to entirely new objects with a similar function, regardless of whether or not they are similar in appearance. It’s a cognitively advanced ability known as “label extension,” and for animals to acquire it usually involves years of intensive training in captivity. But the dogs in this new study developed the ability to classify their toys by function with no formal training, merely by playing naturally with their owners. It’s akin to a person calling a hammer and a rock by the same name, or a child understanding that “cup” can describe a mug, a glass, or a tumbler because they serve the same function. This time around, the group recruited 10 GWL dogs and 21 non-GWL dogs, all border collies, since this is the most common breed to fall into the GWL category. They compiled a list of eight toys: two labeled, two unlabeled, and four that were new to each dog. What’s their motivation? Roy is playing with his caretaker. A. Sommese et al., 2026 Roy is playing with his caretaker. A. Sommese et al., 2026 The different toys used during the experiment. A. Sommese et al., 2026 The different toys used during the experiment. A. Sommese et al., 2026 Roy is playing with his caretaker. A. Sommese et al., 2026 The different toys used during the experiment. A. Sommese et al., 2026 There was a two-week period during which owners familiarized the dogs with the toys once a day for at least 10 minutes. Each toy was presented separately. For the labeled toys, owners moved the toy while crouched on the floor, repeatedly naming the toy (“Look at the [toy name]! Here is the [toy name]”). They did not name the unlabeled toys. Owners devoted an equal amount of time to all the toys. Novel toys were excluded from the familiarization phase. After that period, each dog participated in two 90-second trials. The dogs were provided free access to the toys (washed with soap to control for odor cues). In the first trial, owners entered first and placed the labeled and unlabeled toys, plus two of the novel ones, on the floor and stood at a distance, passive and ignoring the dogs as the latter explored the toys. After a five-minute break, the test was repeated with the other two novel toys. All tests were recorded remotely and the footage subsequently analyzed. Human babies are known to pay more attention to named objects, and the authors thought the GWL dogs would show a similar response, but that’s not what happened. All the dogs, whether they were GWL dogs or not, strongly preferred the new toys, and there were no significant differences between the two groups of dogs in terms of how much time they spent playing with labeled versus unlabeled. So just hearing toy names does not automatically increase a dog’s attention. However, the GWL dogs were much more likely to pick up a toy—particularly the new ones—and bring it to their owner, clearly attempting to get said owner to play with them. The typical dogs were more likely to opt for passive physical contact with their owners. The authors interpreted this as a difference in social style rather than curiosity, possibly mirroring the way human babies try to communicate with parents by pointing or showing objects to them. “The way these dogs actively recruit humans into interactions around novel objects is intriguing,” said co-author Andrea Sommese of the University of Veterinary Medicine in Vienna, Austria. “It raises the possibility that social motivation plays a role in why some dogs end up learning object names. Our results suggest that to understand why some dogs learn words, we may need to look less at the toys and more at the relationship. This opens new directions for studying how language-related skills can emerge in species that live so closely with humans.” Animal Cognition, 2026. DOI: 10.1007/s10071-026-02047-3 (About DOIs). Jennifer Ouellette Senior Writer Jennifer Ouellette Senior Writer Jennifer is a senior writer at Ars Technica with a particular focus on where science meets culture, covering everything from physics and related interdisciplinary topics to her favorite films and TV series. Jennifer lives in Baltimore with her spouse, physicist Sean M. Carroll, and their two cats, Ariel and Caliban. 74 Comments Rare gifted word-learner dogs like to share their toys “It raises the possibility that social motivation plays a role in why some dogs end up learning object names.” We love hearing about the latest findings coming out of an Eötvös Loránd University (ELU) research group focused on gifted word learner (GWL) dogs—if only for the pictures of adorable doggoes playing with their toys. Just last month, we learned that such dogs can learn the labels for new toys just by overhearing their owners talking about those toys. The group is back with yet another new paper, published in the journal Animal Cognition, presenting evidence that GWL dogs have a preference for novel toys and like to share them with their owners. That social interaction seems to be the key to the unique cognitive abilities of these rare dogs. As previously reported, ELU co-author Claudia Fugazza has been studying canine behavior and cognition for several years as part of the Genius Dog Challenge. For instance, the group’s 2022 study discovered that dogs store key sensory features about their toys—notably what they look like and how they smell—and recall those features when searching for the named toy. Prior studies had suggested that dogs typically rely on vision, or a combination of sight and smell, to locate target objects. GWL dogs can also identify objects based on verbal labels. Last fall, Fugazza’s group discovered that certain dogs can not only memorize the names of objects like their favorite toys, but also extend those labels to entirely new objects with a similar function, regardless of whether or not they are similar in appearance. It’s a cognitively advanced ability known as “label extension,” and for animals to acquire it usually involves years of intensive training in captivity. But the dogs in this new study developed the ability to classify their toys by function with no formal training, merely by playing naturally with their owners. It’s akin to a person calling a hammer and a rock by the same name, or a child understanding that “cup” can describe a mug, a glass, or a tumbler because they serve the same function. This time around, the group recruited 10 GWL dogs and 21 non-GWL dogs, all border collies, since this is the most common breed to fall into the GWL category. They compiled a list of eight toys: two labeled, two unlabeled, and four that were new to each dog. What’s their motivation? There was a two-week period during which owners familiarized the dogs with the toys once a day for at least 10 minutes. Each toy was presented separately. For the labeled toys, owners moved the toy while crouched on the floor, repeatedly naming the toy (“Look at the [toy name]! Here is the [toy name]”). They did not name the unlabeled toys. Owners devoted an equal amount of time to all the toys. Novel toys were excluded from the familiarization phase. After that period, each dog participated in two 90-second trials. The dogs were provided free access to the toys (washed with soap to control for odor cues). In the first trial, owners entered first and placed the labeled and unlabeled toys, plus two of the novel ones, on the floor and stood at a distance, passive and ignoring the dogs as the latter explored the toys. After a five-minute break, the test was repeated with the other two novel toys. All tests were recorded remotely and the footage subsequently analyzed. Human babies are known to pay more attention to named objects, and the authors thought the GWL dogs would show a similar response, but that’s not what happened. All the dogs, whether they were GWL dogs or not, strongly preferred the new toys, and there were no significant differences between the two groups of dogs in terms of how much time they spent playing with labeled versus unlabeled. So just hearing toy names does not automatically increase a dog’s attention. However, the GWL dogs were much more likely to pick up a toy—particularly the new ones—and bring it to their owner, clearly attempting to get said owner to play with them. The typical dogs were more likely to opt for passive physical contact with their owners. The authors interpreted this as a difference in social style rather than curiosity, possibly mirroring the way human babies try to communicate with parents by pointing or showing objects to them. “The way these dogs actively recruit humans into interactions around novel objects is intriguing,” said co-author Andrea Sommese of the University of Veterinary Medicine in Vienna, Austria. “It raises the possibility that social motivation plays a role in why some dogs end up learning object names. Our results suggest that to understand why some dogs learn words, we may need to look less at the toys and more at the relationship. This opens new directions for studying how language-related skills can emerge in species that live so closely with humans.” Animal Cognition, 2026. DOI: 10.1007/s10071-026-02047-3 (About DOIs). Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://he.wikipedia.org/wiki/ה'תש"א] | [TOKENS: 620] |
תוכן עניינים ה'תש"א ה'תש"א (5,701) ובקיצור תש"א – היא שנה עברית אשר החלה ביום א' בתשרי, אור ל-3 באוקטובר 1940, והסתיימה ביום כ"ט באלול, 21 בספטמבר 1941.המולד של תשרי חל ביום רביעי, 2 שעות ו-504 חלקים. לפיכך זו שנה מסוג הכז. איננה מעוברת, ואורכה 354 ימים.זו שנה שלישית לשמיטה, ושנת 1 במחזור העיבור ה-301. תקופת ניסן שבשנה זו היא תחילת שנת 17 (סימנה יזלגא) במחזור השמש ה-204.שנה זו היא שנת 1,872 לחורבן הבית, ושנת 2,252 לשטרות. אירועים נולדו נפטרו לוח שנה להלן לוח שנה עברי - גרגוריאני. בכל משבצת יומית - אות אחת או זוג אותיות לציון היום בחודש העברי, ומספר לציון היום בחודש הגרגוריאני. ה'תרצ"ו • ה'תרצ"ז • ה'תרצ"ח • ה'תרצ"ט • ה'ת"ש • ה'תש"א • ה'תש"ב • ה'תש"ג • ה'תש"ד • ה'תש"ה • ה'תש"ו |
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[SOURCE: https://arstechnica.com/tech-policy/2026/02/verizon-might-drop-its-annoying-35-day-wait-for-unlocking-paid-off-phones/] | [TOKENS: 3037] |
Locked phones Verizon acknowledges “pain” of new unlock policy, suggests change is coming Report: Verizon’s goal is “immediate unlock for all payment methods really soon.” Jon Brodkin – Feb 18, 2026 3:58 pm | 66 Credit: Getty Images | SOPA Images Credit: Getty Images | SOPA Images Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav Following our report last week that Verizon is forcing people to wait 35 days for phone unlocks after paying off device installment plans, Verizon is apparently trying to eliminate the inconvenient delay. But Verizon hasn’t confirmed the plan to Ars, and a Verizon statement published by Android Authority yesterday did not provide any timeline for implementing the change. As a refresher, an update to Verizon’s device unlocking policy for postpaid customers imposed a 35-day waiting period when a customer pays off the remaining balance of a device installment plan online, in the Verizon app, or with a Verizon gift card. There’s also a 35-day waiting period after paying off an installment plan over the phone or at a Verizon Authorized Retailer. Saying restrictions are needed to counter fraud, Verizon will only unlock a phone immediately when someone pays off their device-plan balance at a Verizon corporate store or when someone pays off an installment plan on schedule via automatic payments. If you’re partway into one of Verizon’s 36-month device installment plans and pay off the remaining balance early, but without making a trip to a Verizon corporate store, you’d have to wait 35 days for an unlock that would allow you to switch the phone to a different carrier’s network. Verizon reportedly said it is trying to change that “really soon,” but provided no specific or even estimated rollout date. Android Authority reported yesterday that it received a statement from Verizon saying, “we’ve already rolled out immediate unlocking for customers who pay at our corporate stores or use automated payment methods, since those systems can validate transactions in real-time. For other channels such as our app or authorized retailers, the 35-day window is strictly focused on fraud prevention, ensuring payments are fully cleared. That said, we recognize this is a pain point for our customers and our goal is to provide an immediate device unlock for all payment methods really soon. Our teams are diligently working to bridge that gap and we’ll update the website/policy when this is possible.” FCC let Verizon lock phones for longer Verizon did not mention this plan when we contacted the company’s public relations team on Friday. At the time, Verizon confirmed the current policy but didn’t say whether it had any plans to change it. We contacted Verizon again yesterday morning and today about the statement reported by Android Authority and have not received a response. Shortly after or around the time this article was published today, PCMag reported that it received a statement from Verizon indicating that the 35-day delay will be dropped for online payments in a matter of weeks. A Verizon spokesperson “said that several weeks from now, the company would add an extra layer of authentication to its site for credit-card payments that would exempt device payoffs from the 35-day hold,” according to PCMag. Until recently, Verizon had the most consumer-friendly unlocking policy of the major nationwide wireless carriers in the US. This was because of rules imposed on Verizon’s 700 MHz spectrum licenses and merger conditions on the firm’s purchase of TracFone, which resulted in phones being unlocked after 60 days. Verizon used to sell phones that were already unlocked, but in 2019, it obtained a waiver from the Federal Communications Commission allowing it to lock phones for 60 days to deter fraud. Verizon subsequently claimed that even the 60-day period wasn’t long enough to stop fraud, and last month received another waiver that lifted the unlocking requirement. Confusing rollout Verizon started overhauling its unlocking policies after receiving the latest waiver, and the rollout has been confusing. When the new policy was put online with an effective date of January 27, it applied the 35-day delay only to cases in which a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. As we reported, Verizon last week changed that language on the policy page to apply the 35-day delay in more scenarios, but did not change the January 27 effective date. The Verizon statement quoted by Android Authority yesterday said the full terms were presented to customers starting on January 27 even though those terms weren’t fully described on the webpage. “Regarding the website update timing, the new device unlocking policy went into effect on January 27th,” the Verizon statement said. “Customers purchasing or upgrading from that date were (and are being) presented with the full terms of the new policy at their point of sale. We’ll make sure all our public-facing info is also clear and consistent across channels.” Wrong terms still presented to phone buyers But information still is not “clear and consistent across channels,” even when it comes to terms presented directly to phone buyers. For example, the version of the device unlocking policy on Verizon’s webpage for ordering an iPhone 17 says the 35-day delay only applies when a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. We found the same language today in Verizon’s listings for other iPhones and devices made by Google, Samsung, and Motorola. This version of the policy presented to phone buyers would lead a consumer to believe that a phone will be unlocked automatically once the device financing agreement balance is paid in full, as long as a gift card isn’t used. That is not accurate, as we described in this article and our article last week. In one more development we found after this article published, Verizon changed its device unlocking policy again today and updated the effective date to February 18. The new policy is similar to an older version; it details the 35-day unlocking delay after gift card payments but deletes the part that applied the 35-day delay to payments made online or in the Verizon app. This omission is curious because Verizon’s statements to other media outlets indicate that the 35-day delay is still in place for online payments. The omission is apparently explained by new language in the policy that says, “A secure payment method is required to unlock a device immediately when paying the full device balance.” But as far as we know, the only “secure payment methods” that currently result in an immediate unlock require paying in a Verizon corporate store. While a separate Verizon FAQ still describes the in-store limitation, a user reading the policy after today’s update may be given the false belief that paying off a device on Verizon’s website will result in an immediate unlock. The Verizon unlocking policy discussed so far in this article is for postpaid customers. Verizon’s policy for prepaid customers locks phones to its network “until the completion of 365 days of paid and active service.” AT&T’s unlocking policy says postpaid phones purchased at least 60 days ago can be unlocked when the device is paid in full. The T-Mobile policy says postpaid phones active on the T-Mobile network for at least 40 days can be unlocked after being paid in full. AT&T imposes a six-month waiting period for unlocking prepaid phones, while T-Mobile has a 365-day waiting period for prepaid phones. This article was updated with another change to Verizon’s unlocking policy and a statement reported by PCMag. Jon Brodkin Senior IT Reporter Jon Brodkin Senior IT Reporter Jon is a Senior IT Reporter for Ars Technica. He covers the telecom industry, Federal Communications Commission rulemakings, broadband consumer affairs, court cases, and government regulation of the tech industry. 66 Comments Verizon acknowledges “pain” of new unlock policy, suggests change is coming Report: Verizon’s goal is “immediate unlock for all payment methods really soon.” Following our report last week that Verizon is forcing people to wait 35 days for phone unlocks after paying off device installment plans, Verizon is apparently trying to eliminate the inconvenient delay. But Verizon hasn’t confirmed the plan to Ars, and a Verizon statement published by Android Authority yesterday did not provide any timeline for implementing the change. As a refresher, an update to Verizon’s device unlocking policy for postpaid customers imposed a 35-day waiting period when a customer pays off the remaining balance of a device installment plan online, in the Verizon app, or with a Verizon gift card. There’s also a 35-day waiting period after paying off an installment plan over the phone or at a Verizon Authorized Retailer. Saying restrictions are needed to counter fraud, Verizon will only unlock a phone immediately when someone pays off their device-plan balance at a Verizon corporate store or when someone pays off an installment plan on schedule via automatic payments. If you’re partway into one of Verizon’s 36-month device installment plans and pay off the remaining balance early, but without making a trip to a Verizon corporate store, you’d have to wait 35 days for an unlock that would allow you to switch the phone to a different carrier’s network. Verizon reportedly said it is trying to change that “really soon,” but provided no specific or even estimated rollout date. Android Authority reported yesterday that it received a statement from Verizon saying, “we’ve already rolled out immediate unlocking for customers who pay at our corporate stores or use automated payment methods, since those systems can validate transactions in real-time. For other channels such as our app or authorized retailers, the 35-day window is strictly focused on fraud prevention, ensuring payments are fully cleared. That said, we recognize this is a pain point for our customers and our goal is to provide an immediate device unlock for all payment methods really soon. Our teams are diligently working to bridge that gap and we’ll update the website/policy when this is possible.” FCC let Verizon lock phones for longer Verizon did not mention this plan when we contacted the company’s public relations team on Friday. At the time, Verizon confirmed the current policy but didn’t say whether it had any plans to change it. We contacted Verizon again yesterday morning and today about the statement reported by Android Authority and have not received a response. Shortly after or around the time this article was published today, PCMag reported that it received a statement from Verizon indicating that the 35-day delay will be dropped for online payments in a matter of weeks. A Verizon spokesperson “said that several weeks from now, the company would add an extra layer of authentication to its site for credit-card payments that would exempt device payoffs from the 35-day hold,” according to PCMag. Until recently, Verizon had the most consumer-friendly unlocking policy of the major nationwide wireless carriers in the US. This was because of rules imposed on Verizon’s 700 MHz spectrum licenses and merger conditions on the firm’s purchase of TracFone, which resulted in phones being unlocked after 60 days. Verizon used to sell phones that were already unlocked, but in 2019, it obtained a waiver from the Federal Communications Commission allowing it to lock phones for 60 days to deter fraud. Verizon subsequently claimed that even the 60-day period wasn’t long enough to stop fraud, and last month received another waiver that lifted the unlocking requirement. Confusing rollout Verizon started overhauling its unlocking policies after receiving the latest waiver, and the rollout has been confusing. When the new policy was put online with an effective date of January 27, it applied the 35-day delay only to cases in which a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. As we reported, Verizon last week changed that language on the policy page to apply the 35-day delay in more scenarios, but did not change the January 27 effective date. The Verizon statement quoted by Android Authority yesterday said the full terms were presented to customers starting on January 27 even though those terms weren’t fully described on the webpage. “Regarding the website update timing, the new device unlocking policy went into effect on January 27th,” the Verizon statement said. “Customers purchasing or upgrading from that date were (and are being) presented with the full terms of the new policy at their point of sale. We’ll make sure all our public-facing info is also clear and consistent across channels.” Wrong terms still presented to phone buyers But information still is not “clear and consistent across channels,” even when it comes to terms presented directly to phone buyers. For example, the version of the device unlocking policy on Verizon’s webpage for ordering an iPhone 17 says the 35-day delay only applies when a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. We found the same language today in Verizon’s listings for other iPhones and devices made by Google, Samsung, and Motorola. This version of the policy presented to phone buyers would lead a consumer to believe that a phone will be unlocked automatically once the device financing agreement balance is paid in full, as long as a gift card isn’t used. That is not accurate, as we described in this article and our article last week. In one more development we found after this article published, Verizon changed its device unlocking policy again today and updated the effective date to February 18. The new policy is similar to an older version; it details the 35-day unlocking delay after gift card payments but deletes the part that applied the 35-day delay to payments made online or in the Verizon app. This omission is curious because Verizon’s statements to other media outlets indicate that the 35-day delay is still in place for online payments. The omission is apparently explained by new language in the policy that says, “A secure payment method is required to unlock a device immediately when paying the full device balance.” But as far as we know, the only “secure payment methods” that currently result in an immediate unlock require paying in a Verizon corporate store. While a separate Verizon FAQ still describes the in-store limitation, a user reading the policy after today’s update may be given the false belief that paying off a device on Verizon’s website will result in an immediate unlock. The Verizon unlocking policy discussed so far in this article is for postpaid customers. Verizon’s policy for prepaid customers locks phones to its network “until the completion of 365 days of paid and active service.” AT&T’s unlocking policy says postpaid phones purchased at least 60 days ago can be unlocked when the device is paid in full. The T-Mobile policy says postpaid phones active on the T-Mobile network for at least 40 days can be unlocked after being paid in full. AT&T imposes a six-month waiting period for unlocking prepaid phones, while T-Mobile has a 365-day waiting period for prepaid phones. This article was updated with another change to Verizon’s unlocking policy and a statement reported by PCMag. Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/tech-policy/2026/02/verizon-might-drop-its-annoying-35-day-wait-for-unlocking-paid-off-phones/] | [TOKENS: 3037] |
Locked phones Verizon acknowledges “pain” of new unlock policy, suggests change is coming Report: Verizon’s goal is “immediate unlock for all payment methods really soon.” Jon Brodkin – Feb 18, 2026 3:58 pm | 66 Credit: Getty Images | SOPA Images Credit: Getty Images | SOPA Images Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav Following our report last week that Verizon is forcing people to wait 35 days for phone unlocks after paying off device installment plans, Verizon is apparently trying to eliminate the inconvenient delay. But Verizon hasn’t confirmed the plan to Ars, and a Verizon statement published by Android Authority yesterday did not provide any timeline for implementing the change. As a refresher, an update to Verizon’s device unlocking policy for postpaid customers imposed a 35-day waiting period when a customer pays off the remaining balance of a device installment plan online, in the Verizon app, or with a Verizon gift card. There’s also a 35-day waiting period after paying off an installment plan over the phone or at a Verizon Authorized Retailer. Saying restrictions are needed to counter fraud, Verizon will only unlock a phone immediately when someone pays off their device-plan balance at a Verizon corporate store or when someone pays off an installment plan on schedule via automatic payments. If you’re partway into one of Verizon’s 36-month device installment plans and pay off the remaining balance early, but without making a trip to a Verizon corporate store, you’d have to wait 35 days for an unlock that would allow you to switch the phone to a different carrier’s network. Verizon reportedly said it is trying to change that “really soon,” but provided no specific or even estimated rollout date. Android Authority reported yesterday that it received a statement from Verizon saying, “we’ve already rolled out immediate unlocking for customers who pay at our corporate stores or use automated payment methods, since those systems can validate transactions in real-time. For other channels such as our app or authorized retailers, the 35-day window is strictly focused on fraud prevention, ensuring payments are fully cleared. That said, we recognize this is a pain point for our customers and our goal is to provide an immediate device unlock for all payment methods really soon. Our teams are diligently working to bridge that gap and we’ll update the website/policy when this is possible.” FCC let Verizon lock phones for longer Verizon did not mention this plan when we contacted the company’s public relations team on Friday. At the time, Verizon confirmed the current policy but didn’t say whether it had any plans to change it. We contacted Verizon again yesterday morning and today about the statement reported by Android Authority and have not received a response. Shortly after or around the time this article was published today, PCMag reported that it received a statement from Verizon indicating that the 35-day delay will be dropped for online payments in a matter of weeks. A Verizon spokesperson “said that several weeks from now, the company would add an extra layer of authentication to its site for credit-card payments that would exempt device payoffs from the 35-day hold,” according to PCMag. Until recently, Verizon had the most consumer-friendly unlocking policy of the major nationwide wireless carriers in the US. This was because of rules imposed on Verizon’s 700 MHz spectrum licenses and merger conditions on the firm’s purchase of TracFone, which resulted in phones being unlocked after 60 days. Verizon used to sell phones that were already unlocked, but in 2019, it obtained a waiver from the Federal Communications Commission allowing it to lock phones for 60 days to deter fraud. Verizon subsequently claimed that even the 60-day period wasn’t long enough to stop fraud, and last month received another waiver that lifted the unlocking requirement. Confusing rollout Verizon started overhauling its unlocking policies after receiving the latest waiver, and the rollout has been confusing. When the new policy was put online with an effective date of January 27, it applied the 35-day delay only to cases in which a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. As we reported, Verizon last week changed that language on the policy page to apply the 35-day delay in more scenarios, but did not change the January 27 effective date. The Verizon statement quoted by Android Authority yesterday said the full terms were presented to customers starting on January 27 even though those terms weren’t fully described on the webpage. “Regarding the website update timing, the new device unlocking policy went into effect on January 27th,” the Verizon statement said. “Customers purchasing or upgrading from that date were (and are being) presented with the full terms of the new policy at their point of sale. We’ll make sure all our public-facing info is also clear and consistent across channels.” Wrong terms still presented to phone buyers But information still is not “clear and consistent across channels,” even when it comes to terms presented directly to phone buyers. For example, the version of the device unlocking policy on Verizon’s webpage for ordering an iPhone 17 says the 35-day delay only applies when a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. We found the same language today in Verizon’s listings for other iPhones and devices made by Google, Samsung, and Motorola. This version of the policy presented to phone buyers would lead a consumer to believe that a phone will be unlocked automatically once the device financing agreement balance is paid in full, as long as a gift card isn’t used. That is not accurate, as we described in this article and our article last week. In one more development we found after this article published, Verizon changed its device unlocking policy again today and updated the effective date to February 18. The new policy is similar to an older version; it details the 35-day unlocking delay after gift card payments but deletes the part that applied the 35-day delay to payments made online or in the Verizon app. This omission is curious because Verizon’s statements to other media outlets indicate that the 35-day delay is still in place for online payments. The omission is apparently explained by new language in the policy that says, “A secure payment method is required to unlock a device immediately when paying the full device balance.” But as far as we know, the only “secure payment methods” that currently result in an immediate unlock require paying in a Verizon corporate store. While a separate Verizon FAQ still describes the in-store limitation, a user reading the policy after today’s update may be given the false belief that paying off a device on Verizon’s website will result in an immediate unlock. The Verizon unlocking policy discussed so far in this article is for postpaid customers. Verizon’s policy for prepaid customers locks phones to its network “until the completion of 365 days of paid and active service.” AT&T’s unlocking policy says postpaid phones purchased at least 60 days ago can be unlocked when the device is paid in full. The T-Mobile policy says postpaid phones active on the T-Mobile network for at least 40 days can be unlocked after being paid in full. AT&T imposes a six-month waiting period for unlocking prepaid phones, while T-Mobile has a 365-day waiting period for prepaid phones. This article was updated with another change to Verizon’s unlocking policy and a statement reported by PCMag. Jon Brodkin Senior IT Reporter Jon Brodkin Senior IT Reporter Jon is a Senior IT Reporter for Ars Technica. He covers the telecom industry, Federal Communications Commission rulemakings, broadband consumer affairs, court cases, and government regulation of the tech industry. 66 Comments Verizon acknowledges “pain” of new unlock policy, suggests change is coming Report: Verizon’s goal is “immediate unlock for all payment methods really soon.” Following our report last week that Verizon is forcing people to wait 35 days for phone unlocks after paying off device installment plans, Verizon is apparently trying to eliminate the inconvenient delay. But Verizon hasn’t confirmed the plan to Ars, and a Verizon statement published by Android Authority yesterday did not provide any timeline for implementing the change. As a refresher, an update to Verizon’s device unlocking policy for postpaid customers imposed a 35-day waiting period when a customer pays off the remaining balance of a device installment plan online, in the Verizon app, or with a Verizon gift card. There’s also a 35-day waiting period after paying off an installment plan over the phone or at a Verizon Authorized Retailer. Saying restrictions are needed to counter fraud, Verizon will only unlock a phone immediately when someone pays off their device-plan balance at a Verizon corporate store or when someone pays off an installment plan on schedule via automatic payments. If you’re partway into one of Verizon’s 36-month device installment plans and pay off the remaining balance early, but without making a trip to a Verizon corporate store, you’d have to wait 35 days for an unlock that would allow you to switch the phone to a different carrier’s network. Verizon reportedly said it is trying to change that “really soon,” but provided no specific or even estimated rollout date. Android Authority reported yesterday that it received a statement from Verizon saying, “we’ve already rolled out immediate unlocking for customers who pay at our corporate stores or use automated payment methods, since those systems can validate transactions in real-time. For other channels such as our app or authorized retailers, the 35-day window is strictly focused on fraud prevention, ensuring payments are fully cleared. That said, we recognize this is a pain point for our customers and our goal is to provide an immediate device unlock for all payment methods really soon. Our teams are diligently working to bridge that gap and we’ll update the website/policy when this is possible.” FCC let Verizon lock phones for longer Verizon did not mention this plan when we contacted the company’s public relations team on Friday. At the time, Verizon confirmed the current policy but didn’t say whether it had any plans to change it. We contacted Verizon again yesterday morning and today about the statement reported by Android Authority and have not received a response. Shortly after or around the time this article was published today, PCMag reported that it received a statement from Verizon indicating that the 35-day delay will be dropped for online payments in a matter of weeks. A Verizon spokesperson “said that several weeks from now, the company would add an extra layer of authentication to its site for credit-card payments that would exempt device payoffs from the 35-day hold,” according to PCMag. Until recently, Verizon had the most consumer-friendly unlocking policy of the major nationwide wireless carriers in the US. This was because of rules imposed on Verizon’s 700 MHz spectrum licenses and merger conditions on the firm’s purchase of TracFone, which resulted in phones being unlocked after 60 days. Verizon used to sell phones that were already unlocked, but in 2019, it obtained a waiver from the Federal Communications Commission allowing it to lock phones for 60 days to deter fraud. Verizon subsequently claimed that even the 60-day period wasn’t long enough to stop fraud, and last month received another waiver that lifted the unlocking requirement. Confusing rollout Verizon started overhauling its unlocking policies after receiving the latest waiver, and the rollout has been confusing. When the new policy was put online with an effective date of January 27, it applied the 35-day delay only to cases in which a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. As we reported, Verizon last week changed that language on the policy page to apply the 35-day delay in more scenarios, but did not change the January 27 effective date. The Verizon statement quoted by Android Authority yesterday said the full terms were presented to customers starting on January 27 even though those terms weren’t fully described on the webpage. “Regarding the website update timing, the new device unlocking policy went into effect on January 27th,” the Verizon statement said. “Customers purchasing or upgrading from that date were (and are being) presented with the full terms of the new policy at their point of sale. We’ll make sure all our public-facing info is also clear and consistent across channels.” Wrong terms still presented to phone buyers But information still is not “clear and consistent across channels,” even when it comes to terms presented directly to phone buyers. For example, the version of the device unlocking policy on Verizon’s webpage for ordering an iPhone 17 says the 35-day delay only applies when a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. We found the same language today in Verizon’s listings for other iPhones and devices made by Google, Samsung, and Motorola. This version of the policy presented to phone buyers would lead a consumer to believe that a phone will be unlocked automatically once the device financing agreement balance is paid in full, as long as a gift card isn’t used. That is not accurate, as we described in this article and our article last week. In one more development we found after this article published, Verizon changed its device unlocking policy again today and updated the effective date to February 18. The new policy is similar to an older version; it details the 35-day unlocking delay after gift card payments but deletes the part that applied the 35-day delay to payments made online or in the Verizon app. This omission is curious because Verizon’s statements to other media outlets indicate that the 35-day delay is still in place for online payments. The omission is apparently explained by new language in the policy that says, “A secure payment method is required to unlock a device immediately when paying the full device balance.” But as far as we know, the only “secure payment methods” that currently result in an immediate unlock require paying in a Verizon corporate store. While a separate Verizon FAQ still describes the in-store limitation, a user reading the policy after today’s update may be given the false belief that paying off a device on Verizon’s website will result in an immediate unlock. The Verizon unlocking policy discussed so far in this article is for postpaid customers. Verizon’s policy for prepaid customers locks phones to its network “until the completion of 365 days of paid and active service.” AT&T’s unlocking policy says postpaid phones purchased at least 60 days ago can be unlocked when the device is paid in full. The T-Mobile policy says postpaid phones active on the T-Mobile network for at least 40 days can be unlocked after being paid in full. AT&T imposes a six-month waiting period for unlocking prepaid phones, while T-Mobile has a 365-day waiting period for prepaid phones. This article was updated with another change to Verizon’s unlocking policy and a statement reported by PCMag. Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/cars/2026/02/chevy-bolt-bmw-i3-or-something-else-at-10k-you-have-lots-of-ev-options/] | [TOKENS: 3467] |
$9,999 Chevy Bolt, BMW i3, or something else? At $10K, you have lots of EV options Two of Ars’ favorite electric vehicles are now available for not very much money. Jonathan M. Gitlin – Feb 18, 2026 3:22 pm | 190 Credit: Aurich Lawson | Getty Images Credit: Aurich Lawson | Getty Images Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav 2026 is looking like a pretty good year for affordable electric vehicles. There’s a new Nissan Leaf that starts at a hair under $30,000 (as long as you ignore the destination charge). We’ll soon drive the reborn Chevrolet Bolt—with a new lithium iron phosphate battery, it also has a price tag starting with a two (again, ignoring the destination charge). And the closer you get to $40,000, the more your options expand: the Hyundai Ioniq 5, Chevy Equinox EV, Toyota bZ, Tesla Model 3, Ford Mustang Mach-E, and Subaru Solterra all fall within that price bracket, and some of those are pretty good cars. But what if you only want to spend a fraction of that? Well, you won’t be buying anything new, but then neither do three-quarters of American car buyers, and there’s nothing wrong with that. A few weeks ago, we looked at what passes for the used EV bargain basement—ones that cost $5,000 or less. As long as you’re OK with limited range and slow charging, going electric on a shoestring is possible. But if you’re prepared to spend twice that, it turns out you’ve got plenty of options. As before, we stress that you should have a reliable place to charge an EV if you’re going to buy one, which means at home at night or at work during the day. At this price range, you’re unlikely to find something that DC fast charges quickly, and relying on public AC charging sounds stressful. You’ll probably find a car with some battery degradation, but for the vast majority of models that use active battery cooling, this should be minimal; about 2 percent a year appears to be the average. EVs in the US usually come with an eight-year, 100,000-mile warranty for the battery, although cars in this price range will probably be too old to take advantage of it. If you can, have the car checked out by an independent EV specialist; if not, for some models, there are apps you can use. Even a test drive would work, particularly if you can fully recharge it and see how much range the car reports. Oh, I like those BMW gave the i3 city car a useful battery upgrade in its midlife refresh. Jonathan Gitlin BMW gave the i3 city car a useful battery upgrade in its midlife refresh. Jonathan Gitlin The i3’s cabin looks best in the Giga World trim and its pale eucalyptus bits. Jonathan Gitlin The i3’s cabin looks best in the Giga World trim and its pale eucalyptus bits. Jonathan Gitlin BMW gave the i3 city car a useful battery upgrade in its midlife refresh. Jonathan Gitlin The i3’s cabin looks best in the Giga World trim and its pale eucalyptus bits. Jonathan Gitlin In this price range, you should find plenty of two of Ars’ favorite small EVs: the BMW i3 and the Chevy Bolt. The i3 was one of the first EVs we tested; it appeared on the market around the same time Ars started covering cars. Even now, more than a decade later, there’s some seriously cool stuff in an i3. You’re unlikely to find any other car with a carbon fiber passenger cell for this little money, for one thing. And the interior is still one of the most stylish you’ll find on four wheels. It’s the perfect size for city traffic, and it handles pretty well, too. Of course, it’s not the perfect EV. Its tires are an odd size and expensive to replace. And in this price range, you’re more likely to find earlier cars that came with a 22 kWh pack and a range of 81 miles (130 km), although for model year 2017, that increased to 33 kWh and 114 miles (183 km), making these the ones to look for. But plenty of i3s can also be found with the range extender, a two-cylinder motorbike engine that adds another 60 or 70 miles (97–112 km). And it is a true range extender—the little engine can’t directly drive the rear wheels; purists take note. Similarly, we were smitten with the Chevy Bolt from our very first time behind the wheel at the 2016 Consumer Electronics Show. The following year, the little Bolt hit the market as the first affordable EV to offer more than 200 miles of range on a full battery: 238 miles (383 km) to be precise. That might not sound like a lot in 2026, when people expect a new EV to get 300 miles (482 km) between charges, but back then, it was plenty compared to the likes of the i3 or the compliance cars offered by other OEMs. And Tesla’s Model 3 was still some way away, remember. Nearly a decade ago, Chevy let us autocross the Bolt against a Golf GTI: the Bolt won. Credit: Chevrolet Nearly a decade ago, Chevy let us autocross the Bolt against a Golf GTI: the Bolt won. Credit: Chevrolet The Bolt is efficient, but can also be a hoot to drive, especially if you fit it with tires that prioritize grip over low rolling resistance. Some people find the front seats uncomfortable. And it will only accept DC fast charges at up to 55 kW, but as long as you understand that up front, road trips are more than possible. Early Bolts—the ones in this price range—should have had their battery replaced as part of a $1.8 billion recall. What else? You’ll find lots of Nissan Leafs for less than $10,000, a mix of first- and second-generation models. Unlike the new Leaf, these don’t have active battery cooling, and thus will be subject to more battery degradation and therefore lost range than alternatives. (There’s a smartphone app you can use to interrogate the battery.) The Leaf is competent, but wouldn’t be our first pick over the Bolt. If you’re feeling a bit quirky, consider a compliance car. You’ll find Volkswagen e-Golfs, electric Ford Focuses, Kia Souls, and even some Toyota RAV4s and Mercedes-Benz B-classes, the latter two both using Tesla-supplied powertrains. As all of these are less common, it’s probably worth investigating how easily you can get them fixed if something breaks. And there are quite a few used Teslas within our budget. Mostly these are an older Model S with stratospheric mileages, but friend-of-Ars, the Late Brake Show’s Jonny Smith, bought a Tesla with more than 260,000 miles last year and seems to be doing OK with it. This includes benefiting from free Supercharging, although this does not apply to every Model S. And at this price, everyone will think you bought the car well before Elon took off the mask. Jonathan M. Gitlin Automotive Editor Jonathan M. Gitlin Automotive Editor Jonathan is the Automotive Editor at Ars Technica. He has a BSc and PhD in Pharmacology. In 2014 he decided to indulge his lifelong passion for the car by leaving the National Human Genome Research Institute and launching Ars Technica's automotive coverage. He lives in Washington, DC. 190 Comments Chevy Bolt, BMW i3, or something else? At $10K, you have lots of EV options Two of Ars’ favorite electric vehicles are now available for not very much money. 2026 is looking like a pretty good year for affordable electric vehicles. There’s a new Nissan Leaf that starts at a hair under $30,000 (as long as you ignore the destination charge). We’ll soon drive the reborn Chevrolet Bolt—with a new lithium iron phosphate battery, it also has a price tag starting with a two (again, ignoring the destination charge). And the closer you get to $40,000, the more your options expand: the Hyundai Ioniq 5, Chevy Equinox EV, Toyota bZ, Tesla Model 3, Ford Mustang Mach-E, and Subaru Solterra all fall within that price bracket, and some of those are pretty good cars. But what if you only want to spend a fraction of that? Well, you won’t be buying anything new, but then neither do three-quarters of American car buyers, and there’s nothing wrong with that. A few weeks ago, we looked at what passes for the used EV bargain basement—ones that cost $5,000 or less. As long as you’re OK with limited range and slow charging, going electric on a shoestring is possible. But if you’re prepared to spend twice that, it turns out you’ve got plenty of options. As before, we stress that you should have a reliable place to charge an EV if you’re going to buy one, which means at home at night or at work during the day. At this price range, you’re unlikely to find something that DC fast charges quickly, and relying on public AC charging sounds stressful. You’ll probably find a car with some battery degradation, but for the vast majority of models that use active battery cooling, this should be minimal; about 2 percent a year appears to be the average. EVs in the US usually come with an eight-year, 100,000-mile warranty for the battery, although cars in this price range will probably be too old to take advantage of it. If you can, have the car checked out by an independent EV specialist; if not, for some models, there are apps you can use. Even a test drive would work, particularly if you can fully recharge it and see how much range the car reports. Oh, I like those In this price range, you should find plenty of two of Ars’ favorite small EVs: the BMW i3 and the Chevy Bolt. The i3 was one of the first EVs we tested; it appeared on the market around the same time Ars started covering cars. Even now, more than a decade later, there’s some seriously cool stuff in an i3. You’re unlikely to find any other car with a carbon fiber passenger cell for this little money, for one thing. And the interior is still one of the most stylish you’ll find on four wheels. It’s the perfect size for city traffic, and it handles pretty well, too. Of course, it’s not the perfect EV. Its tires are an odd size and expensive to replace. And in this price range, you’re more likely to find earlier cars that came with a 22 kWh pack and a range of 81 miles (130 km), although for model year 2017, that increased to 33 kWh and 114 miles (183 km), making these the ones to look for. But plenty of i3s can also be found with the range extender, a two-cylinder motorbike engine that adds another 60 or 70 miles (97–112 km). And it is a true range extender—the little engine can’t directly drive the rear wheels; purists take note. Similarly, we were smitten with the Chevy Bolt from our very first time behind the wheel at the 2016 Consumer Electronics Show. The following year, the little Bolt hit the market as the first affordable EV to offer more than 200 miles of range on a full battery: 238 miles (383 km) to be precise. That might not sound like a lot in 2026, when people expect a new EV to get 300 miles (482 km) between charges, but back then, it was plenty compared to the likes of the i3 or the compliance cars offered by other OEMs. And Tesla’s Model 3 was still some way away, remember. The Bolt is efficient, but can also be a hoot to drive, especially if you fit it with tires that prioritize grip over low rolling resistance. Some people find the front seats uncomfortable. And it will only accept DC fast charges at up to 55 kW, but as long as you understand that up front, road trips are more than possible. Early Bolts—the ones in this price range—should have had their battery replaced as part of a $1.8 billion recall. What else? You’ll find lots of Nissan Leafs for less than $10,000, a mix of first- and second-generation models. Unlike the new Leaf, these don’t have active battery cooling, and thus will be subject to more battery degradation and therefore lost range than alternatives. (There’s a smartphone app you can use to interrogate the battery.) The Leaf is competent, but wouldn’t be our first pick over the Bolt. If you’re feeling a bit quirky, consider a compliance car. You’ll find Volkswagen e-Golfs, electric Ford Focuses, Kia Souls, and even some Toyota RAV4s and Mercedes-Benz B-classes, the latter two both using Tesla-supplied powertrains. As all of these are less common, it’s probably worth investigating how easily you can get them fixed if something breaks. And there are quite a few used Teslas within our budget. Mostly these are an older Model S with stratospheric mileages, but friend-of-Ars, the Late Brake Show’s Jonny Smith, bought a Tesla with more than 260,000 miles last year and seems to be doing OK with it. This includes benefiting from free Supercharging, although this does not apply to every Model S. And at this price, everyone will think you bought the car well before Elon took off the mask. SplatMan_DK I was tempted to get a used 3i recently; to delay the purchase of a new EV for a few years. We took a test drive. It handles great and I agree the interior is way better than a car in this class normally is. Our 2014 e-Golf (gen 1) has passed 278,000 km (about 173,000 miles) ) on its original battery, going through a decade of charging it to 100% 5-6 days a week. The battery finally collapsed this winter, with range now so poor I can't get to work without charging on the way. In the end we decided to by a new Toyota bZ4X and not delay the purchase. Seems like one of the better mid-class EVs currently (after they fixed the early problems of the model at least). I am a bit curious though. We have been extremely happy with our Gen 1 e-golf, and we would have kept it even longer if there was a realistic way to replace the battery. Everything but the batteri is still in great shape even after 278K km. We would have spent a decent chunk of money to keep it going. But it's not on the recommended list here. Was it never sold in the US, or is there some flaw with it that's more pronounced in the US market than it is in Europe? February 18, 2026 at 11:39 pm S Stuart Frasier Why the fixation on RWD? I live in central NC now so an inch of snow here is a big deal. And many winters if we see a dusting or none, well that's not unusual. But I also spent 8 years in Pittsburgh, PA with a lot of time in Hartford, CT. 4 feet of snow per year in Pittsburgh and the terrain makes San Francisco look flat. And a big snow or two per winter in CT. I had FWD most of the time in those areas and now in NC. I'm not troubled with how they drive. (But at times miss the ability to drift on old dirt roads.)The main advantage FWD has in snow is that there is more weight on the driven wheels in a front-engine ICE car. Since BEVs tend to have near equal weight distribution, FWD is all downside and no upside. You get a more complicated front suspension, worse handling, and a larger turning circle for no real improvement in traction. FWD BEV cars mostly exist as cost-saving efforts using shared platforms with ICE cars. February 19, 2026 at 6:28 pm Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/tech-policy/2026/02/verizon-might-drop-its-annoying-35-day-wait-for-unlocking-paid-off-phones/] | [TOKENS: 3037] |
Locked phones Verizon acknowledges “pain” of new unlock policy, suggests change is coming Report: Verizon’s goal is “immediate unlock for all payment methods really soon.” Jon Brodkin – Feb 18, 2026 3:58 pm | 66 Credit: Getty Images | SOPA Images Credit: Getty Images | SOPA Images Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav Following our report last week that Verizon is forcing people to wait 35 days for phone unlocks after paying off device installment plans, Verizon is apparently trying to eliminate the inconvenient delay. But Verizon hasn’t confirmed the plan to Ars, and a Verizon statement published by Android Authority yesterday did not provide any timeline for implementing the change. As a refresher, an update to Verizon’s device unlocking policy for postpaid customers imposed a 35-day waiting period when a customer pays off the remaining balance of a device installment plan online, in the Verizon app, or with a Verizon gift card. There’s also a 35-day waiting period after paying off an installment plan over the phone or at a Verizon Authorized Retailer. Saying restrictions are needed to counter fraud, Verizon will only unlock a phone immediately when someone pays off their device-plan balance at a Verizon corporate store or when someone pays off an installment plan on schedule via automatic payments. If you’re partway into one of Verizon’s 36-month device installment plans and pay off the remaining balance early, but without making a trip to a Verizon corporate store, you’d have to wait 35 days for an unlock that would allow you to switch the phone to a different carrier’s network. Verizon reportedly said it is trying to change that “really soon,” but provided no specific or even estimated rollout date. Android Authority reported yesterday that it received a statement from Verizon saying, “we’ve already rolled out immediate unlocking for customers who pay at our corporate stores or use automated payment methods, since those systems can validate transactions in real-time. For other channels such as our app or authorized retailers, the 35-day window is strictly focused on fraud prevention, ensuring payments are fully cleared. That said, we recognize this is a pain point for our customers and our goal is to provide an immediate device unlock for all payment methods really soon. Our teams are diligently working to bridge that gap and we’ll update the website/policy when this is possible.” FCC let Verizon lock phones for longer Verizon did not mention this plan when we contacted the company’s public relations team on Friday. At the time, Verizon confirmed the current policy but didn’t say whether it had any plans to change it. We contacted Verizon again yesterday morning and today about the statement reported by Android Authority and have not received a response. Shortly after or around the time this article was published today, PCMag reported that it received a statement from Verizon indicating that the 35-day delay will be dropped for online payments in a matter of weeks. A Verizon spokesperson “said that several weeks from now, the company would add an extra layer of authentication to its site for credit-card payments that would exempt device payoffs from the 35-day hold,” according to PCMag. Until recently, Verizon had the most consumer-friendly unlocking policy of the major nationwide wireless carriers in the US. This was because of rules imposed on Verizon’s 700 MHz spectrum licenses and merger conditions on the firm’s purchase of TracFone, which resulted in phones being unlocked after 60 days. Verizon used to sell phones that were already unlocked, but in 2019, it obtained a waiver from the Federal Communications Commission allowing it to lock phones for 60 days to deter fraud. Verizon subsequently claimed that even the 60-day period wasn’t long enough to stop fraud, and last month received another waiver that lifted the unlocking requirement. Confusing rollout Verizon started overhauling its unlocking policies after receiving the latest waiver, and the rollout has been confusing. When the new policy was put online with an effective date of January 27, it applied the 35-day delay only to cases in which a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. As we reported, Verizon last week changed that language on the policy page to apply the 35-day delay in more scenarios, but did not change the January 27 effective date. The Verizon statement quoted by Android Authority yesterday said the full terms were presented to customers starting on January 27 even though those terms weren’t fully described on the webpage. “Regarding the website update timing, the new device unlocking policy went into effect on January 27th,” the Verizon statement said. “Customers purchasing or upgrading from that date were (and are being) presented with the full terms of the new policy at their point of sale. We’ll make sure all our public-facing info is also clear and consistent across channels.” Wrong terms still presented to phone buyers But information still is not “clear and consistent across channels,” even when it comes to terms presented directly to phone buyers. For example, the version of the device unlocking policy on Verizon’s webpage for ordering an iPhone 17 says the 35-day delay only applies when a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. We found the same language today in Verizon’s listings for other iPhones and devices made by Google, Samsung, and Motorola. This version of the policy presented to phone buyers would lead a consumer to believe that a phone will be unlocked automatically once the device financing agreement balance is paid in full, as long as a gift card isn’t used. That is not accurate, as we described in this article and our article last week. In one more development we found after this article published, Verizon changed its device unlocking policy again today and updated the effective date to February 18. The new policy is similar to an older version; it details the 35-day unlocking delay after gift card payments but deletes the part that applied the 35-day delay to payments made online or in the Verizon app. This omission is curious because Verizon’s statements to other media outlets indicate that the 35-day delay is still in place for online payments. The omission is apparently explained by new language in the policy that says, “A secure payment method is required to unlock a device immediately when paying the full device balance.” But as far as we know, the only “secure payment methods” that currently result in an immediate unlock require paying in a Verizon corporate store. While a separate Verizon FAQ still describes the in-store limitation, a user reading the policy after today’s update may be given the false belief that paying off a device on Verizon’s website will result in an immediate unlock. The Verizon unlocking policy discussed so far in this article is for postpaid customers. Verizon’s policy for prepaid customers locks phones to its network “until the completion of 365 days of paid and active service.” AT&T’s unlocking policy says postpaid phones purchased at least 60 days ago can be unlocked when the device is paid in full. The T-Mobile policy says postpaid phones active on the T-Mobile network for at least 40 days can be unlocked after being paid in full. AT&T imposes a six-month waiting period for unlocking prepaid phones, while T-Mobile has a 365-day waiting period for prepaid phones. This article was updated with another change to Verizon’s unlocking policy and a statement reported by PCMag. Jon Brodkin Senior IT Reporter Jon Brodkin Senior IT Reporter Jon is a Senior IT Reporter for Ars Technica. He covers the telecom industry, Federal Communications Commission rulemakings, broadband consumer affairs, court cases, and government regulation of the tech industry. 66 Comments Verizon acknowledges “pain” of new unlock policy, suggests change is coming Report: Verizon’s goal is “immediate unlock for all payment methods really soon.” Following our report last week that Verizon is forcing people to wait 35 days for phone unlocks after paying off device installment plans, Verizon is apparently trying to eliminate the inconvenient delay. But Verizon hasn’t confirmed the plan to Ars, and a Verizon statement published by Android Authority yesterday did not provide any timeline for implementing the change. As a refresher, an update to Verizon’s device unlocking policy for postpaid customers imposed a 35-day waiting period when a customer pays off the remaining balance of a device installment plan online, in the Verizon app, or with a Verizon gift card. There’s also a 35-day waiting period after paying off an installment plan over the phone or at a Verizon Authorized Retailer. Saying restrictions are needed to counter fraud, Verizon will only unlock a phone immediately when someone pays off their device-plan balance at a Verizon corporate store or when someone pays off an installment plan on schedule via automatic payments. If you’re partway into one of Verizon’s 36-month device installment plans and pay off the remaining balance early, but without making a trip to a Verizon corporate store, you’d have to wait 35 days for an unlock that would allow you to switch the phone to a different carrier’s network. Verizon reportedly said it is trying to change that “really soon,” but provided no specific or even estimated rollout date. Android Authority reported yesterday that it received a statement from Verizon saying, “we’ve already rolled out immediate unlocking for customers who pay at our corporate stores or use automated payment methods, since those systems can validate transactions in real-time. For other channels such as our app or authorized retailers, the 35-day window is strictly focused on fraud prevention, ensuring payments are fully cleared. That said, we recognize this is a pain point for our customers and our goal is to provide an immediate device unlock for all payment methods really soon. Our teams are diligently working to bridge that gap and we’ll update the website/policy when this is possible.” FCC let Verizon lock phones for longer Verizon did not mention this plan when we contacted the company’s public relations team on Friday. At the time, Verizon confirmed the current policy but didn’t say whether it had any plans to change it. We contacted Verizon again yesterday morning and today about the statement reported by Android Authority and have not received a response. Shortly after or around the time this article was published today, PCMag reported that it received a statement from Verizon indicating that the 35-day delay will be dropped for online payments in a matter of weeks. A Verizon spokesperson “said that several weeks from now, the company would add an extra layer of authentication to its site for credit-card payments that would exempt device payoffs from the 35-day hold,” according to PCMag. Until recently, Verizon had the most consumer-friendly unlocking policy of the major nationwide wireless carriers in the US. This was because of rules imposed on Verizon’s 700 MHz spectrum licenses and merger conditions on the firm’s purchase of TracFone, which resulted in phones being unlocked after 60 days. Verizon used to sell phones that were already unlocked, but in 2019, it obtained a waiver from the Federal Communications Commission allowing it to lock phones for 60 days to deter fraud. Verizon subsequently claimed that even the 60-day period wasn’t long enough to stop fraud, and last month received another waiver that lifted the unlocking requirement. Confusing rollout Verizon started overhauling its unlocking policies after receiving the latest waiver, and the rollout has been confusing. When the new policy was put online with an effective date of January 27, it applied the 35-day delay only to cases in which a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. As we reported, Verizon last week changed that language on the policy page to apply the 35-day delay in more scenarios, but did not change the January 27 effective date. The Verizon statement quoted by Android Authority yesterday said the full terms were presented to customers starting on January 27 even though those terms weren’t fully described on the webpage. “Regarding the website update timing, the new device unlocking policy went into effect on January 27th,” the Verizon statement said. “Customers purchasing or upgrading from that date were (and are being) presented with the full terms of the new policy at their point of sale. We’ll make sure all our public-facing info is also clear and consistent across channels.” Wrong terms still presented to phone buyers But information still is not “clear and consistent across channels,” even when it comes to terms presented directly to phone buyers. For example, the version of the device unlocking policy on Verizon’s webpage for ordering an iPhone 17 says the 35-day delay only applies when a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. We found the same language today in Verizon’s listings for other iPhones and devices made by Google, Samsung, and Motorola. This version of the policy presented to phone buyers would lead a consumer to believe that a phone will be unlocked automatically once the device financing agreement balance is paid in full, as long as a gift card isn’t used. That is not accurate, as we described in this article and our article last week. In one more development we found after this article published, Verizon changed its device unlocking policy again today and updated the effective date to February 18. The new policy is similar to an older version; it details the 35-day unlocking delay after gift card payments but deletes the part that applied the 35-day delay to payments made online or in the Verizon app. This omission is curious because Verizon’s statements to other media outlets indicate that the 35-day delay is still in place for online payments. The omission is apparently explained by new language in the policy that says, “A secure payment method is required to unlock a device immediately when paying the full device balance.” But as far as we know, the only “secure payment methods” that currently result in an immediate unlock require paying in a Verizon corporate store. While a separate Verizon FAQ still describes the in-store limitation, a user reading the policy after today’s update may be given the false belief that paying off a device on Verizon’s website will result in an immediate unlock. The Verizon unlocking policy discussed so far in this article is for postpaid customers. Verizon’s policy for prepaid customers locks phones to its network “until the completion of 365 days of paid and active service.” AT&T’s unlocking policy says postpaid phones purchased at least 60 days ago can be unlocked when the device is paid in full. The T-Mobile policy says postpaid phones active on the T-Mobile network for at least 40 days can be unlocked after being paid in full. AT&T imposes a six-month waiting period for unlocking prepaid phones, while T-Mobile has a 365-day waiting period for prepaid phones. This article was updated with another change to Verizon’s unlocking policy and a statement reported by PCMag. Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/tech-policy/2026/02/verizon-might-drop-its-annoying-35-day-wait-for-unlocking-paid-off-phones/#comments] | [TOKENS: 3037] |
Locked phones Verizon acknowledges “pain” of new unlock policy, suggests change is coming Report: Verizon’s goal is “immediate unlock for all payment methods really soon.” Jon Brodkin – Feb 18, 2026 3:58 pm | 66 Credit: Getty Images | SOPA Images Credit: Getty Images | SOPA Images Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav Following our report last week that Verizon is forcing people to wait 35 days for phone unlocks after paying off device installment plans, Verizon is apparently trying to eliminate the inconvenient delay. But Verizon hasn’t confirmed the plan to Ars, and a Verizon statement published by Android Authority yesterday did not provide any timeline for implementing the change. As a refresher, an update to Verizon’s device unlocking policy for postpaid customers imposed a 35-day waiting period when a customer pays off the remaining balance of a device installment plan online, in the Verizon app, or with a Verizon gift card. There’s also a 35-day waiting period after paying off an installment plan over the phone or at a Verizon Authorized Retailer. Saying restrictions are needed to counter fraud, Verizon will only unlock a phone immediately when someone pays off their device-plan balance at a Verizon corporate store or when someone pays off an installment plan on schedule via automatic payments. If you’re partway into one of Verizon’s 36-month device installment plans and pay off the remaining balance early, but without making a trip to a Verizon corporate store, you’d have to wait 35 days for an unlock that would allow you to switch the phone to a different carrier’s network. Verizon reportedly said it is trying to change that “really soon,” but provided no specific or even estimated rollout date. Android Authority reported yesterday that it received a statement from Verizon saying, “we’ve already rolled out immediate unlocking for customers who pay at our corporate stores or use automated payment methods, since those systems can validate transactions in real-time. For other channels such as our app or authorized retailers, the 35-day window is strictly focused on fraud prevention, ensuring payments are fully cleared. That said, we recognize this is a pain point for our customers and our goal is to provide an immediate device unlock for all payment methods really soon. Our teams are diligently working to bridge that gap and we’ll update the website/policy when this is possible.” FCC let Verizon lock phones for longer Verizon did not mention this plan when we contacted the company’s public relations team on Friday. At the time, Verizon confirmed the current policy but didn’t say whether it had any plans to change it. We contacted Verizon again yesterday morning and today about the statement reported by Android Authority and have not received a response. Shortly after or around the time this article was published today, PCMag reported that it received a statement from Verizon indicating that the 35-day delay will be dropped for online payments in a matter of weeks. A Verizon spokesperson “said that several weeks from now, the company would add an extra layer of authentication to its site for credit-card payments that would exempt device payoffs from the 35-day hold,” according to PCMag. Until recently, Verizon had the most consumer-friendly unlocking policy of the major nationwide wireless carriers in the US. This was because of rules imposed on Verizon’s 700 MHz spectrum licenses and merger conditions on the firm’s purchase of TracFone, which resulted in phones being unlocked after 60 days. Verizon used to sell phones that were already unlocked, but in 2019, it obtained a waiver from the Federal Communications Commission allowing it to lock phones for 60 days to deter fraud. Verizon subsequently claimed that even the 60-day period wasn’t long enough to stop fraud, and last month received another waiver that lifted the unlocking requirement. Confusing rollout Verizon started overhauling its unlocking policies after receiving the latest waiver, and the rollout has been confusing. When the new policy was put online with an effective date of January 27, it applied the 35-day delay only to cases in which a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. As we reported, Verizon last week changed that language on the policy page to apply the 35-day delay in more scenarios, but did not change the January 27 effective date. The Verizon statement quoted by Android Authority yesterday said the full terms were presented to customers starting on January 27 even though those terms weren’t fully described on the webpage. “Regarding the website update timing, the new device unlocking policy went into effect on January 27th,” the Verizon statement said. “Customers purchasing or upgrading from that date were (and are being) presented with the full terms of the new policy at their point of sale. We’ll make sure all our public-facing info is also clear and consistent across channels.” Wrong terms still presented to phone buyers But information still is not “clear and consistent across channels,” even when it comes to terms presented directly to phone buyers. For example, the version of the device unlocking policy on Verizon’s webpage for ordering an iPhone 17 says the 35-day delay only applies when a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. We found the same language today in Verizon’s listings for other iPhones and devices made by Google, Samsung, and Motorola. This version of the policy presented to phone buyers would lead a consumer to believe that a phone will be unlocked automatically once the device financing agreement balance is paid in full, as long as a gift card isn’t used. That is not accurate, as we described in this article and our article last week. In one more development we found after this article published, Verizon changed its device unlocking policy again today and updated the effective date to February 18. The new policy is similar to an older version; it details the 35-day unlocking delay after gift card payments but deletes the part that applied the 35-day delay to payments made online or in the Verizon app. This omission is curious because Verizon’s statements to other media outlets indicate that the 35-day delay is still in place for online payments. The omission is apparently explained by new language in the policy that says, “A secure payment method is required to unlock a device immediately when paying the full device balance.” But as far as we know, the only “secure payment methods” that currently result in an immediate unlock require paying in a Verizon corporate store. While a separate Verizon FAQ still describes the in-store limitation, a user reading the policy after today’s update may be given the false belief that paying off a device on Verizon’s website will result in an immediate unlock. The Verizon unlocking policy discussed so far in this article is for postpaid customers. Verizon’s policy for prepaid customers locks phones to its network “until the completion of 365 days of paid and active service.” AT&T’s unlocking policy says postpaid phones purchased at least 60 days ago can be unlocked when the device is paid in full. The T-Mobile policy says postpaid phones active on the T-Mobile network for at least 40 days can be unlocked after being paid in full. AT&T imposes a six-month waiting period for unlocking prepaid phones, while T-Mobile has a 365-day waiting period for prepaid phones. This article was updated with another change to Verizon’s unlocking policy and a statement reported by PCMag. Jon Brodkin Senior IT Reporter Jon Brodkin Senior IT Reporter Jon is a Senior IT Reporter for Ars Technica. He covers the telecom industry, Federal Communications Commission rulemakings, broadband consumer affairs, court cases, and government regulation of the tech industry. 66 Comments Verizon acknowledges “pain” of new unlock policy, suggests change is coming Report: Verizon’s goal is “immediate unlock for all payment methods really soon.” Following our report last week that Verizon is forcing people to wait 35 days for phone unlocks after paying off device installment plans, Verizon is apparently trying to eliminate the inconvenient delay. But Verizon hasn’t confirmed the plan to Ars, and a Verizon statement published by Android Authority yesterday did not provide any timeline for implementing the change. As a refresher, an update to Verizon’s device unlocking policy for postpaid customers imposed a 35-day waiting period when a customer pays off the remaining balance of a device installment plan online, in the Verizon app, or with a Verizon gift card. There’s also a 35-day waiting period after paying off an installment plan over the phone or at a Verizon Authorized Retailer. Saying restrictions are needed to counter fraud, Verizon will only unlock a phone immediately when someone pays off their device-plan balance at a Verizon corporate store or when someone pays off an installment plan on schedule via automatic payments. If you’re partway into one of Verizon’s 36-month device installment plans and pay off the remaining balance early, but without making a trip to a Verizon corporate store, you’d have to wait 35 days for an unlock that would allow you to switch the phone to a different carrier’s network. Verizon reportedly said it is trying to change that “really soon,” but provided no specific or even estimated rollout date. Android Authority reported yesterday that it received a statement from Verizon saying, “we’ve already rolled out immediate unlocking for customers who pay at our corporate stores or use automated payment methods, since those systems can validate transactions in real-time. For other channels such as our app or authorized retailers, the 35-day window is strictly focused on fraud prevention, ensuring payments are fully cleared. That said, we recognize this is a pain point for our customers and our goal is to provide an immediate device unlock for all payment methods really soon. Our teams are diligently working to bridge that gap and we’ll update the website/policy when this is possible.” FCC let Verizon lock phones for longer Verizon did not mention this plan when we contacted the company’s public relations team on Friday. At the time, Verizon confirmed the current policy but didn’t say whether it had any plans to change it. We contacted Verizon again yesterday morning and today about the statement reported by Android Authority and have not received a response. Shortly after or around the time this article was published today, PCMag reported that it received a statement from Verizon indicating that the 35-day delay will be dropped for online payments in a matter of weeks. A Verizon spokesperson “said that several weeks from now, the company would add an extra layer of authentication to its site for credit-card payments that would exempt device payoffs from the 35-day hold,” according to PCMag. Until recently, Verizon had the most consumer-friendly unlocking policy of the major nationwide wireless carriers in the US. This was because of rules imposed on Verizon’s 700 MHz spectrum licenses and merger conditions on the firm’s purchase of TracFone, which resulted in phones being unlocked after 60 days. Verizon used to sell phones that were already unlocked, but in 2019, it obtained a waiver from the Federal Communications Commission allowing it to lock phones for 60 days to deter fraud. Verizon subsequently claimed that even the 60-day period wasn’t long enough to stop fraud, and last month received another waiver that lifted the unlocking requirement. Confusing rollout Verizon started overhauling its unlocking policies after receiving the latest waiver, and the rollout has been confusing. When the new policy was put online with an effective date of January 27, it applied the 35-day delay only to cases in which a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. As we reported, Verizon last week changed that language on the policy page to apply the 35-day delay in more scenarios, but did not change the January 27 effective date. The Verizon statement quoted by Android Authority yesterday said the full terms were presented to customers starting on January 27 even though those terms weren’t fully described on the webpage. “Regarding the website update timing, the new device unlocking policy went into effect on January 27th,” the Verizon statement said. “Customers purchasing or upgrading from that date were (and are being) presented with the full terms of the new policy at their point of sale. We’ll make sure all our public-facing info is also clear and consistent across channels.” Wrong terms still presented to phone buyers But information still is not “clear and consistent across channels,” even when it comes to terms presented directly to phone buyers. For example, the version of the device unlocking policy on Verizon’s webpage for ordering an iPhone 17 says the 35-day delay only applies when a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. We found the same language today in Verizon’s listings for other iPhones and devices made by Google, Samsung, and Motorola. This version of the policy presented to phone buyers would lead a consumer to believe that a phone will be unlocked automatically once the device financing agreement balance is paid in full, as long as a gift card isn’t used. That is not accurate, as we described in this article and our article last week. In one more development we found after this article published, Verizon changed its device unlocking policy again today and updated the effective date to February 18. The new policy is similar to an older version; it details the 35-day unlocking delay after gift card payments but deletes the part that applied the 35-day delay to payments made online or in the Verizon app. This omission is curious because Verizon’s statements to other media outlets indicate that the 35-day delay is still in place for online payments. The omission is apparently explained by new language in the policy that says, “A secure payment method is required to unlock a device immediately when paying the full device balance.” But as far as we know, the only “secure payment methods” that currently result in an immediate unlock require paying in a Verizon corporate store. While a separate Verizon FAQ still describes the in-store limitation, a user reading the policy after today’s update may be given the false belief that paying off a device on Verizon’s website will result in an immediate unlock. The Verizon unlocking policy discussed so far in this article is for postpaid customers. Verizon’s policy for prepaid customers locks phones to its network “until the completion of 365 days of paid and active service.” AT&T’s unlocking policy says postpaid phones purchased at least 60 days ago can be unlocked when the device is paid in full. The T-Mobile policy says postpaid phones active on the T-Mobile network for at least 40 days can be unlocked after being paid in full. AT&T imposes a six-month waiting period for unlocking prepaid phones, while T-Mobile has a 365-day waiting period for prepaid phones. This article was updated with another change to Verizon’s unlocking policy and a statement reported by PCMag. Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/google/2026/02/gemini-can-now-generate-ai-music-for-you-no-lyrics-required/] | [TOKENS: 2503] |
Rage Against the Machine Learning Record scratch—Google’s Lyria 3 AI music model is coming to Gemini today With a simple prompt, you can generate 30 seconds of something like music. Ryan Whitwam – Feb 18, 2026 11:00 am | 214 Credit: Google Credit: Google Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav The American poet Henry Wadsworth Longfellow called music “the universal language of mankind.” Is that still true when the so-called music is being generated by a probabilistic robot instead of a human? We’re about to find out. Google has announced its latest Lyria 3 AI model is being deployed in the Gemini app, vastly expanding access to AI music generation. Google DeepMind has been tinkering with Lyria for a while now, offering limited access in developer-oriented products like Vertex AI. Lyria 3 is more capable than previous versions, and it’s also quicker to use. Just select the new “Create music” option in the Gemini app or web UI to get started. You can describe what you want and even upload an image to help the robot get the right vibe. And in a few seconds, you get music (or something like it). In case there was any uncertainty about whether Lyria tracks still counted as a human artistic endeavor, worry not! Unlike past versions of the model, you don’t even have to provide lyrics in your prompt. You can be vague with your request, and the model will create suitable lyrics for the 30-second song. Although with that limit, “jingle” might be more accurate. In addition to the track, each music creation job will come with an album cover-style image created by the Nano Banana model. Gemini will also have a pre-loaded set of AI tracks that you can choose to remix to your heart’s content. The Lyria 3 tools are also coming to Google’s Dream Track toolkit for YouTube Shorts, which will pair nicely with the Veo AI video options. So what kind of tracks can you expect Gemini to spit out? Google has provided some examples: “Sweet Like Plantain“ Prompt: I’m feeling nostalgic. Create a track for my mother about the great times we had as kids and the memories of her home-cooked plantains. Make it a fun afrobeat track with a true African vibe. “Motown Parody“ Prompt: Quintessential 1970s Motown soul. Lush, orchestral R&B production. Warm bassline with melodic fills, locked into a steady drum groove with crisp snare and tambourine. Vintage organ harmonic bed. Three-piece brass section. Gritty, gospel-tinged male tenor lead. “Pop Flutter“ Prompt: Wistful and airy. Soft, breathy female vocals with intimacy. Rapid-fire drum and bass rhythm, low-passed and softened. Deep, warm bass swells. Dreamy electric piano chords and subtle chime textures. Rainy city vibes. “Sea Shanty“ Prompt: An authentic A capella Sea Shanty featuring a robust male choir singing in a traditional call-and-response format. The piece is entirely vocal, relying on synchronized foot-stomps on a wooden deck and sharp handclaps to provide the rhythmic pulse. The lead is a weathered male baritone with a gravelly timbre who sings the narrative ‘chant’ lines. He is immediately answered by a powerful male choir singing in rich, rugged harmony on the ‘response’ lines. The voices are recorded with a natural room reverb that simulates the acoustic environment of a wooden ship’s deck, giving the vocals a resonant, atmospheric quality. The performance is energetic and driving, with the choir leaning into the rhythm of the stomps to create a sense of focused, communal effort. There are no instruments, only the layered textures of collective male voices spanning tenor, baritone, and bass ranges, all contributing to a confident, monolithic sound. Sour notes AI-generated music is not a new phenomenon. Several companies offer models that ingest and homogenize human-created music, and the resulting tracks can sound remarkably “real,” if a bit overproduced. Streaming services have already been inundated with phony AI artists, some of which have gathered thousands of listeners who may not even realize they’re grooving to the musical equivalent of a blender set to purée. Still, you have to seek out tools like that, and Google is bringing similar capabilities to the Gemini app. As one of the most popular AI platforms, we’re probably about to see a lot more AI music on the Internet. Google says tracks generated with Lyria 3 will have an audio version of Google’s SynthID embedded within. That means you’ll always be able to check if a piece of audio was created with Google’s AI by uploading it to Gemini, similar to the way you can check images and videos for SynthID tags. Google also says it has sought to create a music AI that respects copyright and partner agreements. If you name a specific artist in your prompt, Gemini won’t attempt to copy that artist’s sound. Instead, it’s trained to take that as “broad creative inspiration.” Although it also notes this process is not foolproof, and some of that original expression might imitate an artist too much. In those cases, Google invites users to report such shared content. Lyria 3 is going live in the Gemini web interface today and should be available in the mobile app within a few days. It works in English, German, Spanish, French, Hindi, Japanese, Korean, and Portuguese, but Google plans to add more languages soon. While all users will have some access to music generation, those with AI Pro and AI Ultra subscriptions will have higher usage limits, but the specifics are unclear. Ryan Whitwam Senior Technology Reporter Ryan Whitwam Senior Technology Reporter Ryan Whitwam is a senior technology reporter at Ars Technica, covering the ways Google, AI, and mobile technology continue to change the world. Over his 20-year career, he's written for Android Police, ExtremeTech, Wirecutter, NY Times, and more. He has reviewed more phones than most people will ever own. You can follow him on Bluesky, where you will see photos of his dozens of mechanical keyboards. 214 Comments Record scratch—Google’s Lyria 3 AI music model is coming to Gemini today With a simple prompt, you can generate 30 seconds of something like music. The American poet Henry Wadsworth Longfellow called music “the universal language of mankind.” Is that still true when the so-called music is being generated by a probabilistic robot instead of a human? We’re about to find out. Google has announced its latest Lyria 3 AI model is being deployed in the Gemini app, vastly expanding access to AI music generation. Google DeepMind has been tinkering with Lyria for a while now, offering limited access in developer-oriented products like Vertex AI. Lyria 3 is more capable than previous versions, and it’s also quicker to use. Just select the new “Create music” option in the Gemini app or web UI to get started. You can describe what you want and even upload an image to help the robot get the right vibe. And in a few seconds, you get music (or something like it). In case there was any uncertainty about whether Lyria tracks still counted as a human artistic endeavor, worry not! Unlike past versions of the model, you don’t even have to provide lyrics in your prompt. You can be vague with your request, and the model will create suitable lyrics for the 30-second song. Although with that limit, “jingle” might be more accurate. In addition to the track, each music creation job will come with an album cover-style image created by the Nano Banana model. Gemini will also have a pre-loaded set of AI tracks that you can choose to remix to your heart’s content. The Lyria 3 tools are also coming to Google’s Dream Track toolkit for YouTube Shorts, which will pair nicely with the Veo AI video options. So what kind of tracks can you expect Gemini to spit out? Google has provided some examples: “Sweet Like Plantain“ Prompt: I’m feeling nostalgic. Create a track for my mother about the great times we had as kids and the memories of her home-cooked plantains. Make it a fun afrobeat track with a true African vibe. “Motown Parody“ Prompt: Quintessential 1970s Motown soul. Lush, orchestral R&B production. Warm bassline with melodic fills, locked into a steady drum groove with crisp snare and tambourine. Vintage organ harmonic bed. Three-piece brass section. Gritty, gospel-tinged male tenor lead. “Pop Flutter“ Prompt: Wistful and airy. Soft, breathy female vocals with intimacy. Rapid-fire drum and bass rhythm, low-passed and softened. Deep, warm bass swells. Dreamy electric piano chords and subtle chime textures. Rainy city vibes. “Sea Shanty“ Prompt: An authentic A capella Sea Shanty featuring a robust male choir singing in a traditional call-and-response format. The piece is entirely vocal, relying on synchronized foot-stomps on a wooden deck and sharp handclaps to provide the rhythmic pulse. The lead is a weathered male baritone with a gravelly timbre who sings the narrative ‘chant’ lines. He is immediately answered by a powerful male choir singing in rich, rugged harmony on the ‘response’ lines. The voices are recorded with a natural room reverb that simulates the acoustic environment of a wooden ship’s deck, giving the vocals a resonant, atmospheric quality. The performance is energetic and driving, with the choir leaning into the rhythm of the stomps to create a sense of focused, communal effort. There are no instruments, only the layered textures of collective male voices spanning tenor, baritone, and bass ranges, all contributing to a confident, monolithic sound. Sour notes AI-generated music is not a new phenomenon. Several companies offer models that ingest and homogenize human-created music, and the resulting tracks can sound remarkably “real,” if a bit overproduced. Streaming services have already been inundated with phony AI artists, some of which have gathered thousands of listeners who may not even realize they’re grooving to the musical equivalent of a blender set to purée. Still, you have to seek out tools like that, and Google is bringing similar capabilities to the Gemini app. As one of the most popular AI platforms, we’re probably about to see a lot more AI music on the Internet. Google says tracks generated with Lyria 3 will have an audio version of Google’s SynthID embedded within. That means you’ll always be able to check if a piece of audio was created with Google’s AI by uploading it to Gemini, similar to the way you can check images and videos for SynthID tags. Google also says it has sought to create a music AI that respects copyright and partner agreements. If you name a specific artist in your prompt, Gemini won’t attempt to copy that artist’s sound. Instead, it’s trained to take that as “broad creative inspiration.” Although it also notes this process is not foolproof, and some of that original expression might imitate an artist too much. In those cases, Google invites users to report such shared content. Lyria 3 is going live in the Gemini web interface today and should be available in the mobile app within a few days. It works in English, German, Spanish, French, Hindi, Japanese, Korean, and Portuguese, but Google plans to add more languages soon. While all users will have some access to music generation, those with AI Pro and AI Ultra subscriptions will have higher usage limits, but the specifics are unclear. Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/science/2026/02/microsofts-new-10000-year-data-storage-medium-glass/#comments] | [TOKENS: 3335] |
Clear as glass Microsoft’s new 10,000-year data storage medium: glass Femtosecond lasers etch data into a very stable medium. John Timmer – Feb 18, 2026 2:01 pm | 201 Right now, Silica hardware isn't quite ready for commercialization. Credit: Microsoft Research Right now, Silica hardware isn't quite ready for commercialization. Credit: Microsoft Research Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav Archival storage poses lots of challenges. We want media that is extremely dense and stable for centuries or more, and, ideally, doesn’t consume any energy when not being accessed. Lots of ideas have floated around—even DNA has been considered—but one of the simplest is to cut the data into glass. Many forms of glass are very physically and chemically stable, and it’s relatively easy to create features in it. There’s been a lot of preliminary work demonstrating different aspects of a glass-based storage system. But in Wednesday’s issue of Nature, Microsoft Research announced Project Silica, a working demonstration of a system that can read and write data into small slabs of glass with a density of over a Gigabit per cubic millimeter. Writing on glass We tend to think of glass as fragile, prone to shattering, and capable of flowing downward over centuries, although the last claim is a myth. Glass is a category of material, and a variety of chemicals can form glasses. With the right starting chemical, it’s possible to make a glass that is, as the researchers put it, “thermally and chemically stable and is resistant to moisture ingress, temperature fluctuations and electromagnetic interference.” While it would still need to be handled in a way to minimize damage, glass provides the sort of stability we’d want for long-term storage. Putting data into glass is as simple as etching it (to be clear, this is technically not etching, which is a chemical modification of glass’ surface—here, lasers burn features into the interior of the glass). But that’s been one of the challenges, as the writing is typically a slow process. However, the development of femtosecond lasers—lasers that emit pulses that only last 10-15 seconds and can emit millions of them per second—can significantly cut down write times and allow etching to be focused on a very small area, increasing potential data density. To read the data back, there are several options. We’ve already had great success using lasers to read data from optical disks, albeit slowly. But anything that can pick up the small features etched into the glass could conceivably work. With the above considerations in mind, everything was in place on a theoretical level for Project Silica. The big question is how to put them together into a functional system. Microsoft decided that, just to be cautious, it would answer that question twice. A real-world system The difference between these two answers comes down to how an individual unit of data (called a voxel) is written to the glass. One type of voxel they tried was based on birefringence, where refraction of photons depends on their polarization. It’s possible to etch voxels into glass to create birefringence using polarized laser light, producing features smaller than the diffraction limit. In practice, this involved using one laser pulse to create an oval-shaped void, followed by a second, polarized pulse to induce birefringence. The identity of a voxel is based on the orientation of the oval; since we can resolve multiple orientations, it’s possible to save more than one bit in each voxel. The alternative approach involves changing the magnitude of refractive effects by varying the amount of energy in the laser pulse. Again, it’s possible to discern more than two states in these voxels, allowing multiple data bits to be stored in each voxel. The map data from Microsoft Flight Simulator etched onto the Silica storage medium. Credit: Microsoft Research The map data from Microsoft Flight Simulator etched onto the Silica storage medium. Credit: Microsoft Research Reading these in Silica involves using a microscope that can pick up differences in refractive index. (For microscopy geeks, this is a way of saying “they used phase contrast microscopy.”) The microscopy sets the limits on how many layers of voxels can be placed in a single piece of glass. During etching, the layers were separated by enough distance so only a single layer would be in the microscope’s plane of focus at a time. The etching process also incorporates symbols that allow the automated microscope system to position the lens above specific points on the glass. From there, the system slowly changes its focal plane, moving through the stack and capturing images that include different layers of voxels. To interpret these microscope images, Microsoft used a convolutional neural network that combines data from images that are both in and near the plane of focus for a given layer of voxels. This is effective because the influence of nearby voxels changes how a given voxel appears in a subtle way that the AI system can pick up on if given enough training data. The final piece of the puzzle is data encoding. The Silica system takes the raw bitstream of the data it’s storing and adds error correction using a low-density parity-check code (the same error correction used in 5G networks). Neighboring bits are then combined to create symbols that take advantage of the voxels’ ability to store more than one bit. Once a stream of symbols is made, it’s ready to be written to glass. Performance Writing remains a bottleneck in the system, so Microsoft developed hardware that can write a single glass slab with four lasers simultaneously without generating too much heat. That is enough to enable writing at 66 megabits per second, and the team behind the work thinks that it would be possible to add up to a dozen additional lasers. That may be needed, given that it’s possible to store up to 4.84TB in a single slab of glass (the slabs are 12 cm x 12 cm and 0.2 cm thick). That works out to be over 150 hours to fully write a slab. The “up to” aspect of the storage system has to do with the density of data that’s possible with the two different ways of writing data. The method that relies on birefringence requires more optical hardware and only works in high-quality glasses, but can squeeze more voxels into the same volume, and so has a considerably higher data density. The alternative approach can only put a bit over two terabytes into the same slab of glass, but can be done with simpler hardware and can work on any sort of transparent material. Borosilicate glass offers extreme stability; Microsoft’s accelerated aging experiments suggest the data would be stable for over 10,000 years at room temperature. That led Microsoft to declare, “Our results demonstrate that Silica could become the archival storage solution for the digital age.” That may be overselling it just a bit. The Square Kilometer Array telescope, for example, is expected to need to archive 700 petabytes of data each year. That would mean over 140,000 glass slabs would be needed to store the data from this one telescope. Even assuming that the write speed could be boosted by adding significantly more lasers, you’d need over 600 Silica machines operating in parallel to keep up. And the Square Kilometer Array is far from the only project generating enormous amounts of data. That said, there are some features that make Silica a great match for this sort of thing, most notably the complete absence of energy needed to preserve the data, and the fact that it can be retrieved rapidly if needed (a sharp contrast to the days needed to retrieve information from DNA, for example). Plus, I’m admittedly drawn to a system with a storage medium that looks like something right out of science fiction. Nature, 2026. DOI: 10.1038/s41586-025-10042-w (About DOIs). Correction: defined how etching is used here. John Timmer Senior Science Editor John Timmer Senior Science Editor John is Ars Technica's science editor. He has a Bachelor of Arts in Biochemistry from Columbia University, and a Ph.D. in Molecular and Cell Biology from the University of California, Berkeley. When physically separated from his keyboard, he tends to seek out a bicycle, or a scenic location for communing with his hiking boots. 201 Comments Microsoft’s new 10,000-year data storage medium: glass Femtosecond lasers etch data into a very stable medium. Archival storage poses lots of challenges. We want media that is extremely dense and stable for centuries or more, and, ideally, doesn’t consume any energy when not being accessed. Lots of ideas have floated around—even DNA has been considered—but one of the simplest is to cut the data into glass. Many forms of glass are very physically and chemically stable, and it’s relatively easy to create features in it. There’s been a lot of preliminary work demonstrating different aspects of a glass-based storage system. But in Wednesday’s issue of Nature, Microsoft Research announced Project Silica, a working demonstration of a system that can read and write data into small slabs of glass with a density of over a Gigabit per cubic millimeter. Writing on glass We tend to think of glass as fragile, prone to shattering, and capable of flowing downward over centuries, although the last claim is a myth. Glass is a category of material, and a variety of chemicals can form glasses. With the right starting chemical, it’s possible to make a glass that is, as the researchers put it, “thermally and chemically stable and is resistant to moisture ingress, temperature fluctuations and electromagnetic interference.” While it would still need to be handled in a way to minimize damage, glass provides the sort of stability we’d want for long-term storage. Putting data into glass is as simple as etching it (to be clear, this is technically not etching, which is a chemical modification of glass’ surface—here, lasers burn features into the interior of the glass). But that’s been one of the challenges, as the writing is typically a slow process. However, the development of femtosecond lasers—lasers that emit pulses that only last 10-15 seconds and can emit millions of them per second—can significantly cut down write times and allow etching to be focused on a very small area, increasing potential data density. To read the data back, there are several options. We’ve already had great success using lasers to read data from optical disks, albeit slowly. But anything that can pick up the small features etched into the glass could conceivably work. With the above considerations in mind, everything was in place on a theoretical level for Project Silica. The big question is how to put them together into a functional system. Microsoft decided that, just to be cautious, it would answer that question twice. A real-world system The difference between these two answers comes down to how an individual unit of data (called a voxel) is written to the glass. One type of voxel they tried was based on birefringence, where refraction of photons depends on their polarization. It’s possible to etch voxels into glass to create birefringence using polarized laser light, producing features smaller than the diffraction limit. In practice, this involved using one laser pulse to create an oval-shaped void, followed by a second, polarized pulse to induce birefringence. The identity of a voxel is based on the orientation of the oval; since we can resolve multiple orientations, it’s possible to save more than one bit in each voxel. The alternative approach involves changing the magnitude of refractive effects by varying the amount of energy in the laser pulse. Again, it’s possible to discern more than two states in these voxels, allowing multiple data bits to be stored in each voxel. Reading these in Silica involves using a microscope that can pick up differences in refractive index. (For microscopy geeks, this is a way of saying “they used phase contrast microscopy.”) The microscopy sets the limits on how many layers of voxels can be placed in a single piece of glass. During etching, the layers were separated by enough distance so only a single layer would be in the microscope’s plane of focus at a time. The etching process also incorporates symbols that allow the automated microscope system to position the lens above specific points on the glass. From there, the system slowly changes its focal plane, moving through the stack and capturing images that include different layers of voxels. To interpret these microscope images, Microsoft used a convolutional neural network that combines data from images that are both in and near the plane of focus for a given layer of voxels. This is effective because the influence of nearby voxels changes how a given voxel appears in a subtle way that the AI system can pick up on if given enough training data. The final piece of the puzzle is data encoding. The Silica system takes the raw bitstream of the data it’s storing and adds error correction using a low-density parity-check code (the same error correction used in 5G networks). Neighboring bits are then combined to create symbols that take advantage of the voxels’ ability to store more than one bit. Once a stream of symbols is made, it’s ready to be written to glass. Performance Writing remains a bottleneck in the system, so Microsoft developed hardware that can write a single glass slab with four lasers simultaneously without generating too much heat. That is enough to enable writing at 66 megabits per second, and the team behind the work thinks that it would be possible to add up to a dozen additional lasers. That may be needed, given that it’s possible to store up to 4.84TB in a single slab of glass (the slabs are 12 cm x 12 cm and 0.2 cm thick). That works out to be over 150 hours to fully write a slab. The “up to” aspect of the storage system has to do with the density of data that’s possible with the two different ways of writing data. The method that relies on birefringence requires more optical hardware and only works in high-quality glasses, but can squeeze more voxels into the same volume, and so has a considerably higher data density. The alternative approach can only put a bit over two terabytes into the same slab of glass, but can be done with simpler hardware and can work on any sort of transparent material. Borosilicate glass offers extreme stability; Microsoft’s accelerated aging experiments suggest the data would be stable for over 10,000 years at room temperature. That led Microsoft to declare, “Our results demonstrate that Silica could become the archival storage solution for the digital age.” That may be overselling it just a bit. The Square Kilometer Array telescope, for example, is expected to need to archive 700 petabytes of data each year. That would mean over 140,000 glass slabs would be needed to store the data from this one telescope. Even assuming that the write speed could be boosted by adding significantly more lasers, you’d need over 600 Silica machines operating in parallel to keep up. And the Square Kilometer Array is far from the only project generating enormous amounts of data. That said, there are some features that make Silica a great match for this sort of thing, most notably the complete absence of energy needed to preserve the data, and the fact that it can be retrieved rapidly if needed (a sharp contrast to the days needed to retrieve information from DNA, for example). Plus, I’m admittedly drawn to a system with a storage medium that looks like something right out of science fiction. Nature, 2026. DOI: 10.1038/s41586-025-10042-w (About DOIs). Correction: defined how etching is used here. Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/cars/2026/02/chevy-bolt-bmw-i3-or-something-else-at-10k-you-have-lots-of-ev-options/#comments] | [TOKENS: 3467] |
$9,999 Chevy Bolt, BMW i3, or something else? At $10K, you have lots of EV options Two of Ars’ favorite electric vehicles are now available for not very much money. Jonathan M. Gitlin – Feb 18, 2026 3:22 pm | 190 Credit: Aurich Lawson | Getty Images Credit: Aurich Lawson | Getty Images Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav 2026 is looking like a pretty good year for affordable electric vehicles. There’s a new Nissan Leaf that starts at a hair under $30,000 (as long as you ignore the destination charge). We’ll soon drive the reborn Chevrolet Bolt—with a new lithium iron phosphate battery, it also has a price tag starting with a two (again, ignoring the destination charge). And the closer you get to $40,000, the more your options expand: the Hyundai Ioniq 5, Chevy Equinox EV, Toyota bZ, Tesla Model 3, Ford Mustang Mach-E, and Subaru Solterra all fall within that price bracket, and some of those are pretty good cars. But what if you only want to spend a fraction of that? Well, you won’t be buying anything new, but then neither do three-quarters of American car buyers, and there’s nothing wrong with that. A few weeks ago, we looked at what passes for the used EV bargain basement—ones that cost $5,000 or less. As long as you’re OK with limited range and slow charging, going electric on a shoestring is possible. But if you’re prepared to spend twice that, it turns out you’ve got plenty of options. As before, we stress that you should have a reliable place to charge an EV if you’re going to buy one, which means at home at night or at work during the day. At this price range, you’re unlikely to find something that DC fast charges quickly, and relying on public AC charging sounds stressful. You’ll probably find a car with some battery degradation, but for the vast majority of models that use active battery cooling, this should be minimal; about 2 percent a year appears to be the average. EVs in the US usually come with an eight-year, 100,000-mile warranty for the battery, although cars in this price range will probably be too old to take advantage of it. If you can, have the car checked out by an independent EV specialist; if not, for some models, there are apps you can use. Even a test drive would work, particularly if you can fully recharge it and see how much range the car reports. Oh, I like those BMW gave the i3 city car a useful battery upgrade in its midlife refresh. Jonathan Gitlin BMW gave the i3 city car a useful battery upgrade in its midlife refresh. Jonathan Gitlin The i3’s cabin looks best in the Giga World trim and its pale eucalyptus bits. Jonathan Gitlin The i3’s cabin looks best in the Giga World trim and its pale eucalyptus bits. Jonathan Gitlin BMW gave the i3 city car a useful battery upgrade in its midlife refresh. Jonathan Gitlin The i3’s cabin looks best in the Giga World trim and its pale eucalyptus bits. Jonathan Gitlin In this price range, you should find plenty of two of Ars’ favorite small EVs: the BMW i3 and the Chevy Bolt. The i3 was one of the first EVs we tested; it appeared on the market around the same time Ars started covering cars. Even now, more than a decade later, there’s some seriously cool stuff in an i3. You’re unlikely to find any other car with a carbon fiber passenger cell for this little money, for one thing. And the interior is still one of the most stylish you’ll find on four wheels. It’s the perfect size for city traffic, and it handles pretty well, too. Of course, it’s not the perfect EV. Its tires are an odd size and expensive to replace. And in this price range, you’re more likely to find earlier cars that came with a 22 kWh pack and a range of 81 miles (130 km), although for model year 2017, that increased to 33 kWh and 114 miles (183 km), making these the ones to look for. But plenty of i3s can also be found with the range extender, a two-cylinder motorbike engine that adds another 60 or 70 miles (97–112 km). And it is a true range extender—the little engine can’t directly drive the rear wheels; purists take note. Similarly, we were smitten with the Chevy Bolt from our very first time behind the wheel at the 2016 Consumer Electronics Show. The following year, the little Bolt hit the market as the first affordable EV to offer more than 200 miles of range on a full battery: 238 miles (383 km) to be precise. That might not sound like a lot in 2026, when people expect a new EV to get 300 miles (482 km) between charges, but back then, it was plenty compared to the likes of the i3 or the compliance cars offered by other OEMs. And Tesla’s Model 3 was still some way away, remember. Nearly a decade ago, Chevy let us autocross the Bolt against a Golf GTI: the Bolt won. Credit: Chevrolet Nearly a decade ago, Chevy let us autocross the Bolt against a Golf GTI: the Bolt won. Credit: Chevrolet The Bolt is efficient, but can also be a hoot to drive, especially if you fit it with tires that prioritize grip over low rolling resistance. Some people find the front seats uncomfortable. And it will only accept DC fast charges at up to 55 kW, but as long as you understand that up front, road trips are more than possible. Early Bolts—the ones in this price range—should have had their battery replaced as part of a $1.8 billion recall. What else? You’ll find lots of Nissan Leafs for less than $10,000, a mix of first- and second-generation models. Unlike the new Leaf, these don’t have active battery cooling, and thus will be subject to more battery degradation and therefore lost range than alternatives. (There’s a smartphone app you can use to interrogate the battery.) The Leaf is competent, but wouldn’t be our first pick over the Bolt. If you’re feeling a bit quirky, consider a compliance car. You’ll find Volkswagen e-Golfs, electric Ford Focuses, Kia Souls, and even some Toyota RAV4s and Mercedes-Benz B-classes, the latter two both using Tesla-supplied powertrains. As all of these are less common, it’s probably worth investigating how easily you can get them fixed if something breaks. And there are quite a few used Teslas within our budget. Mostly these are an older Model S with stratospheric mileages, but friend-of-Ars, the Late Brake Show’s Jonny Smith, bought a Tesla with more than 260,000 miles last year and seems to be doing OK with it. This includes benefiting from free Supercharging, although this does not apply to every Model S. And at this price, everyone will think you bought the car well before Elon took off the mask. Jonathan M. Gitlin Automotive Editor Jonathan M. Gitlin Automotive Editor Jonathan is the Automotive Editor at Ars Technica. He has a BSc and PhD in Pharmacology. In 2014 he decided to indulge his lifelong passion for the car by leaving the National Human Genome Research Institute and launching Ars Technica's automotive coverage. He lives in Washington, DC. 190 Comments Chevy Bolt, BMW i3, or something else? At $10K, you have lots of EV options Two of Ars’ favorite electric vehicles are now available for not very much money. 2026 is looking like a pretty good year for affordable electric vehicles. There’s a new Nissan Leaf that starts at a hair under $30,000 (as long as you ignore the destination charge). We’ll soon drive the reborn Chevrolet Bolt—with a new lithium iron phosphate battery, it also has a price tag starting with a two (again, ignoring the destination charge). And the closer you get to $40,000, the more your options expand: the Hyundai Ioniq 5, Chevy Equinox EV, Toyota bZ, Tesla Model 3, Ford Mustang Mach-E, and Subaru Solterra all fall within that price bracket, and some of those are pretty good cars. But what if you only want to spend a fraction of that? Well, you won’t be buying anything new, but then neither do three-quarters of American car buyers, and there’s nothing wrong with that. A few weeks ago, we looked at what passes for the used EV bargain basement—ones that cost $5,000 or less. As long as you’re OK with limited range and slow charging, going electric on a shoestring is possible. But if you’re prepared to spend twice that, it turns out you’ve got plenty of options. As before, we stress that you should have a reliable place to charge an EV if you’re going to buy one, which means at home at night or at work during the day. At this price range, you’re unlikely to find something that DC fast charges quickly, and relying on public AC charging sounds stressful. You’ll probably find a car with some battery degradation, but for the vast majority of models that use active battery cooling, this should be minimal; about 2 percent a year appears to be the average. EVs in the US usually come with an eight-year, 100,000-mile warranty for the battery, although cars in this price range will probably be too old to take advantage of it. If you can, have the car checked out by an independent EV specialist; if not, for some models, there are apps you can use. Even a test drive would work, particularly if you can fully recharge it and see how much range the car reports. Oh, I like those In this price range, you should find plenty of two of Ars’ favorite small EVs: the BMW i3 and the Chevy Bolt. The i3 was one of the first EVs we tested; it appeared on the market around the same time Ars started covering cars. Even now, more than a decade later, there’s some seriously cool stuff in an i3. You’re unlikely to find any other car with a carbon fiber passenger cell for this little money, for one thing. And the interior is still one of the most stylish you’ll find on four wheels. It’s the perfect size for city traffic, and it handles pretty well, too. Of course, it’s not the perfect EV. Its tires are an odd size and expensive to replace. And in this price range, you’re more likely to find earlier cars that came with a 22 kWh pack and a range of 81 miles (130 km), although for model year 2017, that increased to 33 kWh and 114 miles (183 km), making these the ones to look for. But plenty of i3s can also be found with the range extender, a two-cylinder motorbike engine that adds another 60 or 70 miles (97–112 km). And it is a true range extender—the little engine can’t directly drive the rear wheels; purists take note. Similarly, we were smitten with the Chevy Bolt from our very first time behind the wheel at the 2016 Consumer Electronics Show. The following year, the little Bolt hit the market as the first affordable EV to offer more than 200 miles of range on a full battery: 238 miles (383 km) to be precise. That might not sound like a lot in 2026, when people expect a new EV to get 300 miles (482 km) between charges, but back then, it was plenty compared to the likes of the i3 or the compliance cars offered by other OEMs. And Tesla’s Model 3 was still some way away, remember. The Bolt is efficient, but can also be a hoot to drive, especially if you fit it with tires that prioritize grip over low rolling resistance. Some people find the front seats uncomfortable. And it will only accept DC fast charges at up to 55 kW, but as long as you understand that up front, road trips are more than possible. Early Bolts—the ones in this price range—should have had their battery replaced as part of a $1.8 billion recall. What else? You’ll find lots of Nissan Leafs for less than $10,000, a mix of first- and second-generation models. Unlike the new Leaf, these don’t have active battery cooling, and thus will be subject to more battery degradation and therefore lost range than alternatives. (There’s a smartphone app you can use to interrogate the battery.) The Leaf is competent, but wouldn’t be our first pick over the Bolt. If you’re feeling a bit quirky, consider a compliance car. You’ll find Volkswagen e-Golfs, electric Ford Focuses, Kia Souls, and even some Toyota RAV4s and Mercedes-Benz B-classes, the latter two both using Tesla-supplied powertrains. As all of these are less common, it’s probably worth investigating how easily you can get them fixed if something breaks. And there are quite a few used Teslas within our budget. Mostly these are an older Model S with stratospheric mileages, but friend-of-Ars, the Late Brake Show’s Jonny Smith, bought a Tesla with more than 260,000 miles last year and seems to be doing OK with it. This includes benefiting from free Supercharging, although this does not apply to every Model S. And at this price, everyone will think you bought the car well before Elon took off the mask. SplatMan_DK I was tempted to get a used 3i recently; to delay the purchase of a new EV for a few years. We took a test drive. It handles great and I agree the interior is way better than a car in this class normally is. Our 2014 e-Golf (gen 1) has passed 278,000 km (about 173,000 miles) ) on its original battery, going through a decade of charging it to 100% 5-6 days a week. The battery finally collapsed this winter, with range now so poor I can't get to work without charging on the way. In the end we decided to by a new Toyota bZ4X and not delay the purchase. Seems like one of the better mid-class EVs currently (after they fixed the early problems of the model at least). I am a bit curious though. We have been extremely happy with our Gen 1 e-golf, and we would have kept it even longer if there was a realistic way to replace the battery. Everything but the batteri is still in great shape even after 278K km. We would have spent a decent chunk of money to keep it going. But it's not on the recommended list here. Was it never sold in the US, or is there some flaw with it that's more pronounced in the US market than it is in Europe? February 18, 2026 at 11:39 pm S Stuart Frasier Why the fixation on RWD? I live in central NC now so an inch of snow here is a big deal. And many winters if we see a dusting or none, well that's not unusual. But I also spent 8 years in Pittsburgh, PA with a lot of time in Hartford, CT. 4 feet of snow per year in Pittsburgh and the terrain makes San Francisco look flat. And a big snow or two per winter in CT. I had FWD most of the time in those areas and now in NC. I'm not troubled with how they drive. (But at times miss the ability to drift on old dirt roads.)The main advantage FWD has in snow is that there is more weight on the driven wheels in a front-engine ICE car. Since BEVs tend to have near equal weight distribution, FWD is all downside and no upside. You get a more complicated front suspension, worse handling, and a larger turning circle for no real improvement in traction. FWD BEV cars mostly exist as cost-saving efforts using shared platforms with ICE cars. February 19, 2026 at 6:28 pm Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/science/2026/02/microsofts-new-10000-year-data-storage-medium-glass/] | [TOKENS: 3335] |
Clear as glass Microsoft’s new 10,000-year data storage medium: glass Femtosecond lasers etch data into a very stable medium. John Timmer – Feb 18, 2026 2:01 pm | 201 Right now, Silica hardware isn't quite ready for commercialization. Credit: Microsoft Research Right now, Silica hardware isn't quite ready for commercialization. Credit: Microsoft Research Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav Archival storage poses lots of challenges. We want media that is extremely dense and stable for centuries or more, and, ideally, doesn’t consume any energy when not being accessed. Lots of ideas have floated around—even DNA has been considered—but one of the simplest is to cut the data into glass. Many forms of glass are very physically and chemically stable, and it’s relatively easy to create features in it. There’s been a lot of preliminary work demonstrating different aspects of a glass-based storage system. But in Wednesday’s issue of Nature, Microsoft Research announced Project Silica, a working demonstration of a system that can read and write data into small slabs of glass with a density of over a Gigabit per cubic millimeter. Writing on glass We tend to think of glass as fragile, prone to shattering, and capable of flowing downward over centuries, although the last claim is a myth. Glass is a category of material, and a variety of chemicals can form glasses. With the right starting chemical, it’s possible to make a glass that is, as the researchers put it, “thermally and chemically stable and is resistant to moisture ingress, temperature fluctuations and electromagnetic interference.” While it would still need to be handled in a way to minimize damage, glass provides the sort of stability we’d want for long-term storage. Putting data into glass is as simple as etching it (to be clear, this is technically not etching, which is a chemical modification of glass’ surface—here, lasers burn features into the interior of the glass). But that’s been one of the challenges, as the writing is typically a slow process. However, the development of femtosecond lasers—lasers that emit pulses that only last 10-15 seconds and can emit millions of them per second—can significantly cut down write times and allow etching to be focused on a very small area, increasing potential data density. To read the data back, there are several options. We’ve already had great success using lasers to read data from optical disks, albeit slowly. But anything that can pick up the small features etched into the glass could conceivably work. With the above considerations in mind, everything was in place on a theoretical level for Project Silica. The big question is how to put them together into a functional system. Microsoft decided that, just to be cautious, it would answer that question twice. A real-world system The difference between these two answers comes down to how an individual unit of data (called a voxel) is written to the glass. One type of voxel they tried was based on birefringence, where refraction of photons depends on their polarization. It’s possible to etch voxels into glass to create birefringence using polarized laser light, producing features smaller than the diffraction limit. In practice, this involved using one laser pulse to create an oval-shaped void, followed by a second, polarized pulse to induce birefringence. The identity of a voxel is based on the orientation of the oval; since we can resolve multiple orientations, it’s possible to save more than one bit in each voxel. The alternative approach involves changing the magnitude of refractive effects by varying the amount of energy in the laser pulse. Again, it’s possible to discern more than two states in these voxels, allowing multiple data bits to be stored in each voxel. The map data from Microsoft Flight Simulator etched onto the Silica storage medium. Credit: Microsoft Research The map data from Microsoft Flight Simulator etched onto the Silica storage medium. Credit: Microsoft Research Reading these in Silica involves using a microscope that can pick up differences in refractive index. (For microscopy geeks, this is a way of saying “they used phase contrast microscopy.”) The microscopy sets the limits on how many layers of voxels can be placed in a single piece of glass. During etching, the layers were separated by enough distance so only a single layer would be in the microscope’s plane of focus at a time. The etching process also incorporates symbols that allow the automated microscope system to position the lens above specific points on the glass. From there, the system slowly changes its focal plane, moving through the stack and capturing images that include different layers of voxels. To interpret these microscope images, Microsoft used a convolutional neural network that combines data from images that are both in and near the plane of focus for a given layer of voxels. This is effective because the influence of nearby voxels changes how a given voxel appears in a subtle way that the AI system can pick up on if given enough training data. The final piece of the puzzle is data encoding. The Silica system takes the raw bitstream of the data it’s storing and adds error correction using a low-density parity-check code (the same error correction used in 5G networks). Neighboring bits are then combined to create symbols that take advantage of the voxels’ ability to store more than one bit. Once a stream of symbols is made, it’s ready to be written to glass. Performance Writing remains a bottleneck in the system, so Microsoft developed hardware that can write a single glass slab with four lasers simultaneously without generating too much heat. That is enough to enable writing at 66 megabits per second, and the team behind the work thinks that it would be possible to add up to a dozen additional lasers. That may be needed, given that it’s possible to store up to 4.84TB in a single slab of glass (the slabs are 12 cm x 12 cm and 0.2 cm thick). That works out to be over 150 hours to fully write a slab. The “up to” aspect of the storage system has to do with the density of data that’s possible with the two different ways of writing data. The method that relies on birefringence requires more optical hardware and only works in high-quality glasses, but can squeeze more voxels into the same volume, and so has a considerably higher data density. The alternative approach can only put a bit over two terabytes into the same slab of glass, but can be done with simpler hardware and can work on any sort of transparent material. Borosilicate glass offers extreme stability; Microsoft’s accelerated aging experiments suggest the data would be stable for over 10,000 years at room temperature. That led Microsoft to declare, “Our results demonstrate that Silica could become the archival storage solution for the digital age.” That may be overselling it just a bit. The Square Kilometer Array telescope, for example, is expected to need to archive 700 petabytes of data each year. That would mean over 140,000 glass slabs would be needed to store the data from this one telescope. Even assuming that the write speed could be boosted by adding significantly more lasers, you’d need over 600 Silica machines operating in parallel to keep up. And the Square Kilometer Array is far from the only project generating enormous amounts of data. That said, there are some features that make Silica a great match for this sort of thing, most notably the complete absence of energy needed to preserve the data, and the fact that it can be retrieved rapidly if needed (a sharp contrast to the days needed to retrieve information from DNA, for example). Plus, I’m admittedly drawn to a system with a storage medium that looks like something right out of science fiction. Nature, 2026. DOI: 10.1038/s41586-025-10042-w (About DOIs). Correction: defined how etching is used here. John Timmer Senior Science Editor John Timmer Senior Science Editor John is Ars Technica's science editor. He has a Bachelor of Arts in Biochemistry from Columbia University, and a Ph.D. in Molecular and Cell Biology from the University of California, Berkeley. When physically separated from his keyboard, he tends to seek out a bicycle, or a scenic location for communing with his hiking boots. 201 Comments Microsoft’s new 10,000-year data storage medium: glass Femtosecond lasers etch data into a very stable medium. Archival storage poses lots of challenges. We want media that is extremely dense and stable for centuries or more, and, ideally, doesn’t consume any energy when not being accessed. Lots of ideas have floated around—even DNA has been considered—but one of the simplest is to cut the data into glass. Many forms of glass are very physically and chemically stable, and it’s relatively easy to create features in it. There’s been a lot of preliminary work demonstrating different aspects of a glass-based storage system. But in Wednesday’s issue of Nature, Microsoft Research announced Project Silica, a working demonstration of a system that can read and write data into small slabs of glass with a density of over a Gigabit per cubic millimeter. Writing on glass We tend to think of glass as fragile, prone to shattering, and capable of flowing downward over centuries, although the last claim is a myth. Glass is a category of material, and a variety of chemicals can form glasses. With the right starting chemical, it’s possible to make a glass that is, as the researchers put it, “thermally and chemically stable and is resistant to moisture ingress, temperature fluctuations and electromagnetic interference.” While it would still need to be handled in a way to minimize damage, glass provides the sort of stability we’d want for long-term storage. Putting data into glass is as simple as etching it (to be clear, this is technically not etching, which is a chemical modification of glass’ surface—here, lasers burn features into the interior of the glass). But that’s been one of the challenges, as the writing is typically a slow process. However, the development of femtosecond lasers—lasers that emit pulses that only last 10-15 seconds and can emit millions of them per second—can significantly cut down write times and allow etching to be focused on a very small area, increasing potential data density. To read the data back, there are several options. We’ve already had great success using lasers to read data from optical disks, albeit slowly. But anything that can pick up the small features etched into the glass could conceivably work. With the above considerations in mind, everything was in place on a theoretical level for Project Silica. The big question is how to put them together into a functional system. Microsoft decided that, just to be cautious, it would answer that question twice. A real-world system The difference between these two answers comes down to how an individual unit of data (called a voxel) is written to the glass. One type of voxel they tried was based on birefringence, where refraction of photons depends on their polarization. It’s possible to etch voxels into glass to create birefringence using polarized laser light, producing features smaller than the diffraction limit. In practice, this involved using one laser pulse to create an oval-shaped void, followed by a second, polarized pulse to induce birefringence. The identity of a voxel is based on the orientation of the oval; since we can resolve multiple orientations, it’s possible to save more than one bit in each voxel. The alternative approach involves changing the magnitude of refractive effects by varying the amount of energy in the laser pulse. Again, it’s possible to discern more than two states in these voxels, allowing multiple data bits to be stored in each voxel. Reading these in Silica involves using a microscope that can pick up differences in refractive index. (For microscopy geeks, this is a way of saying “they used phase contrast microscopy.”) The microscopy sets the limits on how many layers of voxels can be placed in a single piece of glass. During etching, the layers were separated by enough distance so only a single layer would be in the microscope’s plane of focus at a time. The etching process also incorporates symbols that allow the automated microscope system to position the lens above specific points on the glass. From there, the system slowly changes its focal plane, moving through the stack and capturing images that include different layers of voxels. To interpret these microscope images, Microsoft used a convolutional neural network that combines data from images that are both in and near the plane of focus for a given layer of voxels. This is effective because the influence of nearby voxels changes how a given voxel appears in a subtle way that the AI system can pick up on if given enough training data. The final piece of the puzzle is data encoding. The Silica system takes the raw bitstream of the data it’s storing and adds error correction using a low-density parity-check code (the same error correction used in 5G networks). Neighboring bits are then combined to create symbols that take advantage of the voxels’ ability to store more than one bit. Once a stream of symbols is made, it’s ready to be written to glass. Performance Writing remains a bottleneck in the system, so Microsoft developed hardware that can write a single glass slab with four lasers simultaneously without generating too much heat. That is enough to enable writing at 66 megabits per second, and the team behind the work thinks that it would be possible to add up to a dozen additional lasers. That may be needed, given that it’s possible to store up to 4.84TB in a single slab of glass (the slabs are 12 cm x 12 cm and 0.2 cm thick). That works out to be over 150 hours to fully write a slab. The “up to” aspect of the storage system has to do with the density of data that’s possible with the two different ways of writing data. The method that relies on birefringence requires more optical hardware and only works in high-quality glasses, but can squeeze more voxels into the same volume, and so has a considerably higher data density. The alternative approach can only put a bit over two terabytes into the same slab of glass, but can be done with simpler hardware and can work on any sort of transparent material. Borosilicate glass offers extreme stability; Microsoft’s accelerated aging experiments suggest the data would be stable for over 10,000 years at room temperature. That led Microsoft to declare, “Our results demonstrate that Silica could become the archival storage solution for the digital age.” That may be overselling it just a bit. The Square Kilometer Array telescope, for example, is expected to need to archive 700 petabytes of data each year. That would mean over 140,000 glass slabs would be needed to store the data from this one telescope. Even assuming that the write speed could be boosted by adding significantly more lasers, you’d need over 600 Silica machines operating in parallel to keep up. And the Square Kilometer Array is far from the only project generating enormous amounts of data. That said, there are some features that make Silica a great match for this sort of thing, most notably the complete absence of energy needed to preserve the data, and the fact that it can be retrieved rapidly if needed (a sharp contrast to the days needed to retrieve information from DNA, for example). Plus, I’m admittedly drawn to a system with a storage medium that looks like something right out of science fiction. Nature, 2026. DOI: 10.1038/s41586-025-10042-w (About DOIs). Correction: defined how etching is used here. Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/gadgets/2026/02/5-changes-to-know-about-in-apples-latest-ios-macos-and-ipados-betas/] | [TOKENS: 4193] |
FYI 5 changes to know about in Apple’s latest iOS, macOS, and iPadOS betas The 26.3 updates were mostly invisible; these changes are more significant. Andrew Cunningham – Feb 18, 2026 2:28 pm | 132 A collection of iPhones running iOS 26. Credit: Apple A collection of iPhones running iOS 26. Credit: Apple Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav This week, Apple released the first developer betas for iOS 26.4, iPadOS 26.4, macOS 26.4, and its other operating systems. On Tuesday, it followed those up with public beta versions of the same updates. Usually released around the midpoint between one major iOS release and the next, the *.4 updates to its operating system usually include a significant batch of new features and other refinements, and if the first beta is any indication, this year’s releases uphold that tradition. A new “Playlist Playground” feature will let Apple Music subscribers generate playlists with text prompts, and native support for video podcasts is coming to the Podcasts app. The Creator Studio version of the Freeform drawing and collaboration app is also available in the 26.4 updates, allowing subscribers to access stock images from Apple’s Content Hub and to insert AI-generated images. But we’ve spent time digging through the betas to identify some of the more below-the-surface improvements and changes that Apple is testing. Some of these changes won’t come to the public versions of the software until a later release; others may be removed or changed between now and when the 26.4 update is made available to the general public. But generally, Apple’s betas give us a good idea of what the final release will look like. One feature that hasn’t appeared in these betas? The new “more intelligent Siri” that Apple has been promising since the iOS 18 launch in 2024. Apple delayed the feature until sometime in 2026, citing that it wasn’t meeting the company’s standards for quality and reliability. Reports indicated that the company had been planning to make the new Siri part of the 26.4 update, but as of earlier this month, Apple has reportedly decided to push it to the 26.5 release or later; even releasing it as part of iOS 27 in the fall would technically not run afoul of the “2026” promise. Before we begin, the standard warning about installing beta software on hardware you rely on day to day. Although these point updates are generally more stable than the major releases Apple tests in the summer and fall, they can still contain major bugs and may cause your device to behave strangely. The first beta, in particular, tends to be the roughest—more stable versions will be released in the coming weeks, and we should see the final version of the update within the next couple months. Charging limits for MacBooks The macOS 26.4 update includes a slider for manually limiting your Mac’s battery charge percentage. Credit: Andrew Cunningham The macOS 26.4 update includes a slider for manually limiting your Mac’s battery charge percentage. Credit: Andrew Cunningham In macOS 11 Big Sur, Apple added an on-by-default “Optimized Battery Charging” toggle to the operating system that would allow macOS to limit your battery’s charge percentage to 80 percent based on your usage and charging behavior. The idea is to limit the time your battery spends charging while full, something that can gradually reduce its capacity. The macOS 26.4 update adds a new slider similar to the one in iOS, further allowing users to manually specify a maximum charge limit that is always observed, no matter what. It’s adjustable in 5 percent increments from 80 to 100 percent. Anecdotal evidence suggests that limiting your charge percentage can lengthen the useful life of your battery and reduce wear, but there’s nothing that will fully prevent a battery from wearing out and losing capacity over time. It’s up to users to decide whether an immediately noticeable everyday hit to battery life is worth a slightly longer service life. In the current macOS betas, enabling a charge limit manually doesn’t disable the Optimized Battery Charging feature the way it does in iOS. It’s unclear if this is an early bug or an intentional difference in how the feature is implemented in macOS. End-to-end encryption (and other improvements) for non-Apple texting Apple has been infamously slow to adopt support for the Rich Communication Services (RCS) messaging protocol used by most modern Android phones. Apple-to-Apple messaging was handled using iMessage, which supports end-to-end encryption among many other features. But for many years, it stuck by the aging SMS standard for “green bubble” texting between Apple’s platforms and others, to the enduring frustration of anyone with a single Android-using friend in a group chat. Apple finally began supporting RCS messaging for major cellular carriers in iOS 18, and has slowly expanded support to other networks in subsequent releases. But Apple’s implementation still doesn’t support end-to-end encryption, which was added to the RCS standard about a year ago. The 26.4 update is the first to begin testing encryption for RCS messages. But as with the initial RCS rollout, Apple is moving slowly and deliberately: for now, encrypted RCS messaging only works when texting between Apple devices, and not between Apple devices and Android phones. The feature also won’t be included in the final 26.4 release—it’s only included in the betas for testing purposes, and it “will be available to customers in a future software update for iOS, iPadOS, macOS, and watchOS.” Encrypted iMessage and RCS chats will be labeled with a lock icon, much like how most web browsers label HTTPS sites. To support encrypted messaging, Apple will jump from version 2.4 of the RCS Universal Profile to version 3.0. This should also enable support for several improvements in versions 2.5, 2.6, and 2.7 of the RCS standard, including previously iMessage-exclusive things like editing and recalling messages and replying to specific messages inline. The return of the “Compact” Safari tab bar The Compact tab view returns to Safari 26.4 and iPadOS 26.4. Credit: Andrew Cunningham The Compact tab view returns to Safari 26.4 and iPadOS 26.4. Credit: Andrew Cunningham As part of the macOS 12 Monterey/iPadOS 15 beta cycle in 2021, Apple attempted a pretty radical redesign of the Safari browser that combined your tabs and the address bar into one, with the goal of increasing the amount of viewable space on the pages you were viewing. By the time both operating systems were released to the public, Safari’s default design had more or less reverted to its previous state, but the “compact” tab view lived on as an optional view in the settings for those who liked it. Tahoe, the Safari 26 update, and iPadOS 26 all removed that Compact view entirely, though a version of the Compact view became the default for the iPhone version of Safari. The macOS 26.4, Safari 26.4, and iPadOS 26.4 updates restore the Compact tab option to the other versions of Safari. On-by-default Stolen Device Protection Originally introduced in the iOS 17.3 update, Apple’s “Stolen Device Protection” toggle for iPhones added an extra layer of security for users whose phones were stolen by people who had learned their passcodes. With Stolen Device Protection enabled, an iPhone that had been removed from “familiar locations, such as home or work” would require biometric Face ID or Touch ID authentication before accessing stored passwords and credit cards, erasing your phone, or changing Apple Account passwords. Normally, users can enter their passcodes as a fallback; Stolen Device Protection removes that fallback. The iOS 26.4 update will make Stolen Device Protection on by default. Generally, you won’t notice a difference in how your phone behaves, but if you’re traveling or away from places where you regularly use your phone and you can’t use your passcode to access certain information, this is why. It’s possible to switch off Stolen Device protection, but doing so requires biometric authentication, an hour-long wait, and then a second biometric authentication. (This extended wait is also required for disabling Find My, changing your phone’s passcode, or changing Touch ID and Face ID settings.) Rosetta’s end approaches The macOS 26.4 update will add the first user-facing notifications about the end of Rosetta support, currently slated for macOS 28 in 2027. Credit: Andrew Cunningham The macOS 26.4 update will add the first user-facing notifications about the end of Rosetta support, currently slated for macOS 28 in 2027. Credit: Andrew Cunningham Apple’s Rosetta 2 was a crucial support beam in the bridge from the Intel Mac era to the Apple Silicon era, enabling unmodified Intel-native apps to run on the M1 and later processors, with noticeable but manageable performance and responsiveness hits. As with the original Rosetta, it allowed Apple to execute a major CPU architecture switch while keeping it mostly invisible to Mac users, and it bought developers time to release Arm-native versions of their apps so they could take full advantage of the new chips. But now that the transition is complete and the last Intel Macs are fading into the rearview, Apple plans to remove the translation layer from future versions of macOS, with some exceptions for games that rely on the technology. Rosetta 2 won’t be completely removed until macOS 28, but macOS 26.4 will be the first to begin warning users about the end of Rosetta when they launch Intel-native apps. Those notifications link to an Apple support page about identifying and updating Intel-only apps to Apple Silicon-native versions (or universal binaries that support both architectures). Apple has deployed this “adding notifications without removing functionality” approach to deprecating older apps before. Versions 10.13 and 10.14 of macOS would show users pop-ups about the end of support for 32-bit apps for a couple of years before that support was removed in macOS 10.15, for example. Andrew Cunningham Senior Technology Reporter Andrew Cunningham Senior Technology Reporter Andrew is a Senior Technology Reporter at Ars Technica, with a focus on consumer tech including computer hardware and in-depth reviews of operating systems like Windows and macOS. Andrew lives in Philadelphia and co-hosts a weekly book podcast called Overdue. 132 Comments 5 changes to know about in Apple’s latest iOS, macOS, and iPadOS betas The 26.3 updates were mostly invisible; these changes are more significant. This week, Apple released the first developer betas for iOS 26.4, iPadOS 26.4, macOS 26.4, and its other operating systems. On Tuesday, it followed those up with public beta versions of the same updates. Usually released around the midpoint between one major iOS release and the next, the *.4 updates to its operating system usually include a significant batch of new features and other refinements, and if the first beta is any indication, this year’s releases uphold that tradition. A new “Playlist Playground” feature will let Apple Music subscribers generate playlists with text prompts, and native support for video podcasts is coming to the Podcasts app. The Creator Studio version of the Freeform drawing and collaboration app is also available in the 26.4 updates, allowing subscribers to access stock images from Apple’s Content Hub and to insert AI-generated images. But we’ve spent time digging through the betas to identify some of the more below-the-surface improvements and changes that Apple is testing. Some of these changes won’t come to the public versions of the software until a later release; others may be removed or changed between now and when the 26.4 update is made available to the general public. But generally, Apple’s betas give us a good idea of what the final release will look like. One feature that hasn’t appeared in these betas? The new “more intelligent Siri” that Apple has been promising since the iOS 18 launch in 2024. Apple delayed the feature until sometime in 2026, citing that it wasn’t meeting the company’s standards for quality and reliability. Reports indicated that the company had been planning to make the new Siri part of the 26.4 update, but as of earlier this month, Apple has reportedly decided to push it to the 26.5 release or later; even releasing it as part of iOS 27 in the fall would technically not run afoul of the “2026” promise. Before we begin, the standard warning about installing beta software on hardware you rely on day to day. Although these point updates are generally more stable than the major releases Apple tests in the summer and fall, they can still contain major bugs and may cause your device to behave strangely. The first beta, in particular, tends to be the roughest—more stable versions will be released in the coming weeks, and we should see the final version of the update within the next couple months. Charging limits for MacBooks In macOS 11 Big Sur, Apple added an on-by-default “Optimized Battery Charging” toggle to the operating system that would allow macOS to limit your battery’s charge percentage to 80 percent based on your usage and charging behavior. The idea is to limit the time your battery spends charging while full, something that can gradually reduce its capacity. The macOS 26.4 update adds a new slider similar to the one in iOS, further allowing users to manually specify a maximum charge limit that is always observed, no matter what. It’s adjustable in 5 percent increments from 80 to 100 percent. Anecdotal evidence suggests that limiting your charge percentage can lengthen the useful life of your battery and reduce wear, but there’s nothing that will fully prevent a battery from wearing out and losing capacity over time. It’s up to users to decide whether an immediately noticeable everyday hit to battery life is worth a slightly longer service life. In the current macOS betas, enabling a charge limit manually doesn’t disable the Optimized Battery Charging feature the way it does in iOS. It’s unclear if this is an early bug or an intentional difference in how the feature is implemented in macOS. End-to-end encryption (and other improvements) for non-Apple texting Apple has been infamously slow to adopt support for the Rich Communication Services (RCS) messaging protocol used by most modern Android phones. Apple-to-Apple messaging was handled using iMessage, which supports end-to-end encryption among many other features. But for many years, it stuck by the aging SMS standard for “green bubble” texting between Apple’s platforms and others, to the enduring frustration of anyone with a single Android-using friend in a group chat. Apple finally began supporting RCS messaging for major cellular carriers in iOS 18, and has slowly expanded support to other networks in subsequent releases. But Apple’s implementation still doesn’t support end-to-end encryption, which was added to the RCS standard about a year ago. The 26.4 update is the first to begin testing encryption for RCS messages. But as with the initial RCS rollout, Apple is moving slowly and deliberately: for now, encrypted RCS messaging only works when texting between Apple devices, and not between Apple devices and Android phones. The feature also won’t be included in the final 26.4 release—it’s only included in the betas for testing purposes, and it “will be available to customers in a future software update for iOS, iPadOS, macOS, and watchOS.” Encrypted iMessage and RCS chats will be labeled with a lock icon, much like how most web browsers label HTTPS sites. To support encrypted messaging, Apple will jump from version 2.4 of the RCS Universal Profile to version 3.0. This should also enable support for several improvements in versions 2.5, 2.6, and 2.7 of the RCS standard, including previously iMessage-exclusive things like editing and recalling messages and replying to specific messages inline. The return of the “Compact” Safari tab bar As part of the macOS 12 Monterey/iPadOS 15 beta cycle in 2021, Apple attempted a pretty radical redesign of the Safari browser that combined your tabs and the address bar into one, with the goal of increasing the amount of viewable space on the pages you were viewing. By the time both operating systems were released to the public, Safari’s default design had more or less reverted to its previous state, but the “compact” tab view lived on as an optional view in the settings for those who liked it. Tahoe, the Safari 26 update, and iPadOS 26 all removed that Compact view entirely, though a version of the Compact view became the default for the iPhone version of Safari. The macOS 26.4, Safari 26.4, and iPadOS 26.4 updates restore the Compact tab option to the other versions of Safari. On-by-default Stolen Device Protection Originally introduced in the iOS 17.3 update, Apple’s “Stolen Device Protection” toggle for iPhones added an extra layer of security for users whose phones were stolen by people who had learned their passcodes. With Stolen Device Protection enabled, an iPhone that had been removed from “familiar locations, such as home or work” would require biometric Face ID or Touch ID authentication before accessing stored passwords and credit cards, erasing your phone, or changing Apple Account passwords. Normally, users can enter their passcodes as a fallback; Stolen Device Protection removes that fallback. The iOS 26.4 update will make Stolen Device Protection on by default. Generally, you won’t notice a difference in how your phone behaves, but if you’re traveling or away from places where you regularly use your phone and you can’t use your passcode to access certain information, this is why. It’s possible to switch off Stolen Device protection, but doing so requires biometric authentication, an hour-long wait, and then a second biometric authentication. (This extended wait is also required for disabling Find My, changing your phone’s passcode, or changing Touch ID and Face ID settings.) Rosetta’s end approaches Apple’s Rosetta 2 was a crucial support beam in the bridge from the Intel Mac era to the Apple Silicon era, enabling unmodified Intel-native apps to run on the M1 and later processors, with noticeable but manageable performance and responsiveness hits. As with the original Rosetta, it allowed Apple to execute a major CPU architecture switch while keeping it mostly invisible to Mac users, and it bought developers time to release Arm-native versions of their apps so they could take full advantage of the new chips. But now that the transition is complete and the last Intel Macs are fading into the rearview, Apple plans to remove the translation layer from future versions of macOS, with some exceptions for games that rely on the technology. Rosetta 2 won’t be completely removed until macOS 28, but macOS 26.4 will be the first to begin warning users about the end of Rosetta when they launch Intel-native apps. Those notifications link to an Apple support page about identifying and updating Intel-only apps to Apple Silicon-native versions (or universal binaries that support both architectures). Apple has deployed this “adding notifications without removing functionality” approach to deprecating older apps before. Versions 10.13 and 10.14 of macOS would show users pop-ups about the end of support for 32-bit apps for a couple of years before that support was removed in macOS 10.15, for example. F Fred Duck i need a TL;DR on that one, dogCertainly. Let's use Fred Intelligence (FI) to summarise the Arsticle. 1 Charging limits for MacBooks 2 End-to-end encryption (and other improvements) for non-Apple texting 3 The return of the “Compact” Safari tab bar 4 On-by-default Stolen Device Protection 5 Rosetta’s end approaches 6 Apple-shaped products If I can be of further assistance, don't hesitate. February 18, 2026 at 7:49 pm Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/cars/2026/02/chevy-bolt-bmw-i3-or-something-else-at-10k-you-have-lots-of-ev-options/] | [TOKENS: 3467] |
$9,999 Chevy Bolt, BMW i3, or something else? At $10K, you have lots of EV options Two of Ars’ favorite electric vehicles are now available for not very much money. Jonathan M. Gitlin – Feb 18, 2026 3:22 pm | 190 Credit: Aurich Lawson | Getty Images Credit: Aurich Lawson | Getty Images Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav 2026 is looking like a pretty good year for affordable electric vehicles. There’s a new Nissan Leaf that starts at a hair under $30,000 (as long as you ignore the destination charge). We’ll soon drive the reborn Chevrolet Bolt—with a new lithium iron phosphate battery, it also has a price tag starting with a two (again, ignoring the destination charge). And the closer you get to $40,000, the more your options expand: the Hyundai Ioniq 5, Chevy Equinox EV, Toyota bZ, Tesla Model 3, Ford Mustang Mach-E, and Subaru Solterra all fall within that price bracket, and some of those are pretty good cars. But what if you only want to spend a fraction of that? Well, you won’t be buying anything new, but then neither do three-quarters of American car buyers, and there’s nothing wrong with that. A few weeks ago, we looked at what passes for the used EV bargain basement—ones that cost $5,000 or less. As long as you’re OK with limited range and slow charging, going electric on a shoestring is possible. But if you’re prepared to spend twice that, it turns out you’ve got plenty of options. As before, we stress that you should have a reliable place to charge an EV if you’re going to buy one, which means at home at night or at work during the day. At this price range, you’re unlikely to find something that DC fast charges quickly, and relying on public AC charging sounds stressful. You’ll probably find a car with some battery degradation, but for the vast majority of models that use active battery cooling, this should be minimal; about 2 percent a year appears to be the average. EVs in the US usually come with an eight-year, 100,000-mile warranty for the battery, although cars in this price range will probably be too old to take advantage of it. If you can, have the car checked out by an independent EV specialist; if not, for some models, there are apps you can use. Even a test drive would work, particularly if you can fully recharge it and see how much range the car reports. Oh, I like those BMW gave the i3 city car a useful battery upgrade in its midlife refresh. Jonathan Gitlin BMW gave the i3 city car a useful battery upgrade in its midlife refresh. Jonathan Gitlin The i3’s cabin looks best in the Giga World trim and its pale eucalyptus bits. Jonathan Gitlin The i3’s cabin looks best in the Giga World trim and its pale eucalyptus bits. Jonathan Gitlin BMW gave the i3 city car a useful battery upgrade in its midlife refresh. Jonathan Gitlin The i3’s cabin looks best in the Giga World trim and its pale eucalyptus bits. Jonathan Gitlin In this price range, you should find plenty of two of Ars’ favorite small EVs: the BMW i3 and the Chevy Bolt. The i3 was one of the first EVs we tested; it appeared on the market around the same time Ars started covering cars. Even now, more than a decade later, there’s some seriously cool stuff in an i3. You’re unlikely to find any other car with a carbon fiber passenger cell for this little money, for one thing. And the interior is still one of the most stylish you’ll find on four wheels. It’s the perfect size for city traffic, and it handles pretty well, too. Of course, it’s not the perfect EV. Its tires are an odd size and expensive to replace. And in this price range, you’re more likely to find earlier cars that came with a 22 kWh pack and a range of 81 miles (130 km), although for model year 2017, that increased to 33 kWh and 114 miles (183 km), making these the ones to look for. But plenty of i3s can also be found with the range extender, a two-cylinder motorbike engine that adds another 60 or 70 miles (97–112 km). And it is a true range extender—the little engine can’t directly drive the rear wheels; purists take note. Similarly, we were smitten with the Chevy Bolt from our very first time behind the wheel at the 2016 Consumer Electronics Show. The following year, the little Bolt hit the market as the first affordable EV to offer more than 200 miles of range on a full battery: 238 miles (383 km) to be precise. That might not sound like a lot in 2026, when people expect a new EV to get 300 miles (482 km) between charges, but back then, it was plenty compared to the likes of the i3 or the compliance cars offered by other OEMs. And Tesla’s Model 3 was still some way away, remember. Nearly a decade ago, Chevy let us autocross the Bolt against a Golf GTI: the Bolt won. Credit: Chevrolet Nearly a decade ago, Chevy let us autocross the Bolt against a Golf GTI: the Bolt won. Credit: Chevrolet The Bolt is efficient, but can also be a hoot to drive, especially if you fit it with tires that prioritize grip over low rolling resistance. Some people find the front seats uncomfortable. And it will only accept DC fast charges at up to 55 kW, but as long as you understand that up front, road trips are more than possible. Early Bolts—the ones in this price range—should have had their battery replaced as part of a $1.8 billion recall. What else? You’ll find lots of Nissan Leafs for less than $10,000, a mix of first- and second-generation models. Unlike the new Leaf, these don’t have active battery cooling, and thus will be subject to more battery degradation and therefore lost range than alternatives. (There’s a smartphone app you can use to interrogate the battery.) The Leaf is competent, but wouldn’t be our first pick over the Bolt. If you’re feeling a bit quirky, consider a compliance car. You’ll find Volkswagen e-Golfs, electric Ford Focuses, Kia Souls, and even some Toyota RAV4s and Mercedes-Benz B-classes, the latter two both using Tesla-supplied powertrains. As all of these are less common, it’s probably worth investigating how easily you can get them fixed if something breaks. And there are quite a few used Teslas within our budget. Mostly these are an older Model S with stratospheric mileages, but friend-of-Ars, the Late Brake Show’s Jonny Smith, bought a Tesla with more than 260,000 miles last year and seems to be doing OK with it. This includes benefiting from free Supercharging, although this does not apply to every Model S. And at this price, everyone will think you bought the car well before Elon took off the mask. Jonathan M. Gitlin Automotive Editor Jonathan M. Gitlin Automotive Editor Jonathan is the Automotive Editor at Ars Technica. He has a BSc and PhD in Pharmacology. In 2014 he decided to indulge his lifelong passion for the car by leaving the National Human Genome Research Institute and launching Ars Technica's automotive coverage. He lives in Washington, DC. 190 Comments Chevy Bolt, BMW i3, or something else? At $10K, you have lots of EV options Two of Ars’ favorite electric vehicles are now available for not very much money. 2026 is looking like a pretty good year for affordable electric vehicles. There’s a new Nissan Leaf that starts at a hair under $30,000 (as long as you ignore the destination charge). We’ll soon drive the reborn Chevrolet Bolt—with a new lithium iron phosphate battery, it also has a price tag starting with a two (again, ignoring the destination charge). And the closer you get to $40,000, the more your options expand: the Hyundai Ioniq 5, Chevy Equinox EV, Toyota bZ, Tesla Model 3, Ford Mustang Mach-E, and Subaru Solterra all fall within that price bracket, and some of those are pretty good cars. But what if you only want to spend a fraction of that? Well, you won’t be buying anything new, but then neither do three-quarters of American car buyers, and there’s nothing wrong with that. A few weeks ago, we looked at what passes for the used EV bargain basement—ones that cost $5,000 or less. As long as you’re OK with limited range and slow charging, going electric on a shoestring is possible. But if you’re prepared to spend twice that, it turns out you’ve got plenty of options. As before, we stress that you should have a reliable place to charge an EV if you’re going to buy one, which means at home at night or at work during the day. At this price range, you’re unlikely to find something that DC fast charges quickly, and relying on public AC charging sounds stressful. You’ll probably find a car with some battery degradation, but for the vast majority of models that use active battery cooling, this should be minimal; about 2 percent a year appears to be the average. EVs in the US usually come with an eight-year, 100,000-mile warranty for the battery, although cars in this price range will probably be too old to take advantage of it. If you can, have the car checked out by an independent EV specialist; if not, for some models, there are apps you can use. Even a test drive would work, particularly if you can fully recharge it and see how much range the car reports. Oh, I like those In this price range, you should find plenty of two of Ars’ favorite small EVs: the BMW i3 and the Chevy Bolt. The i3 was one of the first EVs we tested; it appeared on the market around the same time Ars started covering cars. Even now, more than a decade later, there’s some seriously cool stuff in an i3. You’re unlikely to find any other car with a carbon fiber passenger cell for this little money, for one thing. And the interior is still one of the most stylish you’ll find on four wheels. It’s the perfect size for city traffic, and it handles pretty well, too. Of course, it’s not the perfect EV. Its tires are an odd size and expensive to replace. And in this price range, you’re more likely to find earlier cars that came with a 22 kWh pack and a range of 81 miles (130 km), although for model year 2017, that increased to 33 kWh and 114 miles (183 km), making these the ones to look for. But plenty of i3s can also be found with the range extender, a two-cylinder motorbike engine that adds another 60 or 70 miles (97–112 km). And it is a true range extender—the little engine can’t directly drive the rear wheels; purists take note. Similarly, we were smitten with the Chevy Bolt from our very first time behind the wheel at the 2016 Consumer Electronics Show. The following year, the little Bolt hit the market as the first affordable EV to offer more than 200 miles of range on a full battery: 238 miles (383 km) to be precise. That might not sound like a lot in 2026, when people expect a new EV to get 300 miles (482 km) between charges, but back then, it was plenty compared to the likes of the i3 or the compliance cars offered by other OEMs. And Tesla’s Model 3 was still some way away, remember. The Bolt is efficient, but can also be a hoot to drive, especially if you fit it with tires that prioritize grip over low rolling resistance. Some people find the front seats uncomfortable. And it will only accept DC fast charges at up to 55 kW, but as long as you understand that up front, road trips are more than possible. Early Bolts—the ones in this price range—should have had their battery replaced as part of a $1.8 billion recall. What else? You’ll find lots of Nissan Leafs for less than $10,000, a mix of first- and second-generation models. Unlike the new Leaf, these don’t have active battery cooling, and thus will be subject to more battery degradation and therefore lost range than alternatives. (There’s a smartphone app you can use to interrogate the battery.) The Leaf is competent, but wouldn’t be our first pick over the Bolt. If you’re feeling a bit quirky, consider a compliance car. You’ll find Volkswagen e-Golfs, electric Ford Focuses, Kia Souls, and even some Toyota RAV4s and Mercedes-Benz B-classes, the latter two both using Tesla-supplied powertrains. As all of these are less common, it’s probably worth investigating how easily you can get them fixed if something breaks. And there are quite a few used Teslas within our budget. Mostly these are an older Model S with stratospheric mileages, but friend-of-Ars, the Late Brake Show’s Jonny Smith, bought a Tesla with more than 260,000 miles last year and seems to be doing OK with it. This includes benefiting from free Supercharging, although this does not apply to every Model S. And at this price, everyone will think you bought the car well before Elon took off the mask. SplatMan_DK I was tempted to get a used 3i recently; to delay the purchase of a new EV for a few years. We took a test drive. It handles great and I agree the interior is way better than a car in this class normally is. Our 2014 e-Golf (gen 1) has passed 278,000 km (about 173,000 miles) ) on its original battery, going through a decade of charging it to 100% 5-6 days a week. The battery finally collapsed this winter, with range now so poor I can't get to work without charging on the way. In the end we decided to by a new Toyota bZ4X and not delay the purchase. Seems like one of the better mid-class EVs currently (after they fixed the early problems of the model at least). I am a bit curious though. We have been extremely happy with our Gen 1 e-golf, and we would have kept it even longer if there was a realistic way to replace the battery. Everything but the batteri is still in great shape even after 278K km. We would have spent a decent chunk of money to keep it going. But it's not on the recommended list here. Was it never sold in the US, or is there some flaw with it that's more pronounced in the US market than it is in Europe? February 18, 2026 at 11:39 pm S Stuart Frasier Why the fixation on RWD? I live in central NC now so an inch of snow here is a big deal. And many winters if we see a dusting or none, well that's not unusual. But I also spent 8 years in Pittsburgh, PA with a lot of time in Hartford, CT. 4 feet of snow per year in Pittsburgh and the terrain makes San Francisco look flat. And a big snow or two per winter in CT. I had FWD most of the time in those areas and now in NC. I'm not troubled with how they drive. (But at times miss the ability to drift on old dirt roads.)The main advantage FWD has in snow is that there is more weight on the driven wheels in a front-engine ICE car. Since BEVs tend to have near equal weight distribution, FWD is all downside and no upside. You get a more complicated front suspension, worse handling, and a larger turning circle for no real improvement in traction. FWD BEV cars mostly exist as cost-saving efforts using shared platforms with ICE cars. February 19, 2026 at 6:28 pm Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/cars/2026/02/chevy-bolt-bmw-i3-or-something-else-at-10k-you-have-lots-of-ev-options/] | [TOKENS: 3467] |
$9,999 Chevy Bolt, BMW i3, or something else? At $10K, you have lots of EV options Two of Ars’ favorite electric vehicles are now available for not very much money. Jonathan M. Gitlin – Feb 18, 2026 3:22 pm | 190 Credit: Aurich Lawson | Getty Images Credit: Aurich Lawson | Getty Images Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav 2026 is looking like a pretty good year for affordable electric vehicles. There’s a new Nissan Leaf that starts at a hair under $30,000 (as long as you ignore the destination charge). We’ll soon drive the reborn Chevrolet Bolt—with a new lithium iron phosphate battery, it also has a price tag starting with a two (again, ignoring the destination charge). And the closer you get to $40,000, the more your options expand: the Hyundai Ioniq 5, Chevy Equinox EV, Toyota bZ, Tesla Model 3, Ford Mustang Mach-E, and Subaru Solterra all fall within that price bracket, and some of those are pretty good cars. But what if you only want to spend a fraction of that? Well, you won’t be buying anything new, but then neither do three-quarters of American car buyers, and there’s nothing wrong with that. A few weeks ago, we looked at what passes for the used EV bargain basement—ones that cost $5,000 or less. As long as you’re OK with limited range and slow charging, going electric on a shoestring is possible. But if you’re prepared to spend twice that, it turns out you’ve got plenty of options. As before, we stress that you should have a reliable place to charge an EV if you’re going to buy one, which means at home at night or at work during the day. At this price range, you’re unlikely to find something that DC fast charges quickly, and relying on public AC charging sounds stressful. You’ll probably find a car with some battery degradation, but for the vast majority of models that use active battery cooling, this should be minimal; about 2 percent a year appears to be the average. EVs in the US usually come with an eight-year, 100,000-mile warranty for the battery, although cars in this price range will probably be too old to take advantage of it. If you can, have the car checked out by an independent EV specialist; if not, for some models, there are apps you can use. Even a test drive would work, particularly if you can fully recharge it and see how much range the car reports. Oh, I like those BMW gave the i3 city car a useful battery upgrade in its midlife refresh. Jonathan Gitlin BMW gave the i3 city car a useful battery upgrade in its midlife refresh. Jonathan Gitlin The i3’s cabin looks best in the Giga World trim and its pale eucalyptus bits. Jonathan Gitlin The i3’s cabin looks best in the Giga World trim and its pale eucalyptus bits. Jonathan Gitlin BMW gave the i3 city car a useful battery upgrade in its midlife refresh. Jonathan Gitlin The i3’s cabin looks best in the Giga World trim and its pale eucalyptus bits. Jonathan Gitlin In this price range, you should find plenty of two of Ars’ favorite small EVs: the BMW i3 and the Chevy Bolt. The i3 was one of the first EVs we tested; it appeared on the market around the same time Ars started covering cars. Even now, more than a decade later, there’s some seriously cool stuff in an i3. You’re unlikely to find any other car with a carbon fiber passenger cell for this little money, for one thing. And the interior is still one of the most stylish you’ll find on four wheels. It’s the perfect size for city traffic, and it handles pretty well, too. Of course, it’s not the perfect EV. Its tires are an odd size and expensive to replace. And in this price range, you’re more likely to find earlier cars that came with a 22 kWh pack and a range of 81 miles (130 km), although for model year 2017, that increased to 33 kWh and 114 miles (183 km), making these the ones to look for. But plenty of i3s can also be found with the range extender, a two-cylinder motorbike engine that adds another 60 or 70 miles (97–112 km). And it is a true range extender—the little engine can’t directly drive the rear wheels; purists take note. Similarly, we were smitten with the Chevy Bolt from our very first time behind the wheel at the 2016 Consumer Electronics Show. The following year, the little Bolt hit the market as the first affordable EV to offer more than 200 miles of range on a full battery: 238 miles (383 km) to be precise. That might not sound like a lot in 2026, when people expect a new EV to get 300 miles (482 km) between charges, but back then, it was plenty compared to the likes of the i3 or the compliance cars offered by other OEMs. And Tesla’s Model 3 was still some way away, remember. Nearly a decade ago, Chevy let us autocross the Bolt against a Golf GTI: the Bolt won. Credit: Chevrolet Nearly a decade ago, Chevy let us autocross the Bolt against a Golf GTI: the Bolt won. Credit: Chevrolet The Bolt is efficient, but can also be a hoot to drive, especially if you fit it with tires that prioritize grip over low rolling resistance. Some people find the front seats uncomfortable. And it will only accept DC fast charges at up to 55 kW, but as long as you understand that up front, road trips are more than possible. Early Bolts—the ones in this price range—should have had their battery replaced as part of a $1.8 billion recall. What else? You’ll find lots of Nissan Leafs for less than $10,000, a mix of first- and second-generation models. Unlike the new Leaf, these don’t have active battery cooling, and thus will be subject to more battery degradation and therefore lost range than alternatives. (There’s a smartphone app you can use to interrogate the battery.) The Leaf is competent, but wouldn’t be our first pick over the Bolt. If you’re feeling a bit quirky, consider a compliance car. You’ll find Volkswagen e-Golfs, electric Ford Focuses, Kia Souls, and even some Toyota RAV4s and Mercedes-Benz B-classes, the latter two both using Tesla-supplied powertrains. As all of these are less common, it’s probably worth investigating how easily you can get them fixed if something breaks. And there are quite a few used Teslas within our budget. Mostly these are an older Model S with stratospheric mileages, but friend-of-Ars, the Late Brake Show’s Jonny Smith, bought a Tesla with more than 260,000 miles last year and seems to be doing OK with it. This includes benefiting from free Supercharging, although this does not apply to every Model S. And at this price, everyone will think you bought the car well before Elon took off the mask. Jonathan M. Gitlin Automotive Editor Jonathan M. Gitlin Automotive Editor Jonathan is the Automotive Editor at Ars Technica. He has a BSc and PhD in Pharmacology. In 2014 he decided to indulge his lifelong passion for the car by leaving the National Human Genome Research Institute and launching Ars Technica's automotive coverage. He lives in Washington, DC. 190 Comments Chevy Bolt, BMW i3, or something else? At $10K, you have lots of EV options Two of Ars’ favorite electric vehicles are now available for not very much money. 2026 is looking like a pretty good year for affordable electric vehicles. There’s a new Nissan Leaf that starts at a hair under $30,000 (as long as you ignore the destination charge). We’ll soon drive the reborn Chevrolet Bolt—with a new lithium iron phosphate battery, it also has a price tag starting with a two (again, ignoring the destination charge). And the closer you get to $40,000, the more your options expand: the Hyundai Ioniq 5, Chevy Equinox EV, Toyota bZ, Tesla Model 3, Ford Mustang Mach-E, and Subaru Solterra all fall within that price bracket, and some of those are pretty good cars. But what if you only want to spend a fraction of that? Well, you won’t be buying anything new, but then neither do three-quarters of American car buyers, and there’s nothing wrong with that. A few weeks ago, we looked at what passes for the used EV bargain basement—ones that cost $5,000 or less. As long as you’re OK with limited range and slow charging, going electric on a shoestring is possible. But if you’re prepared to spend twice that, it turns out you’ve got plenty of options. As before, we stress that you should have a reliable place to charge an EV if you’re going to buy one, which means at home at night or at work during the day. At this price range, you’re unlikely to find something that DC fast charges quickly, and relying on public AC charging sounds stressful. You’ll probably find a car with some battery degradation, but for the vast majority of models that use active battery cooling, this should be minimal; about 2 percent a year appears to be the average. EVs in the US usually come with an eight-year, 100,000-mile warranty for the battery, although cars in this price range will probably be too old to take advantage of it. If you can, have the car checked out by an independent EV specialist; if not, for some models, there are apps you can use. Even a test drive would work, particularly if you can fully recharge it and see how much range the car reports. Oh, I like those In this price range, you should find plenty of two of Ars’ favorite small EVs: the BMW i3 and the Chevy Bolt. The i3 was one of the first EVs we tested; it appeared on the market around the same time Ars started covering cars. Even now, more than a decade later, there’s some seriously cool stuff in an i3. You’re unlikely to find any other car with a carbon fiber passenger cell for this little money, for one thing. And the interior is still one of the most stylish you’ll find on four wheels. It’s the perfect size for city traffic, and it handles pretty well, too. Of course, it’s not the perfect EV. Its tires are an odd size and expensive to replace. And in this price range, you’re more likely to find earlier cars that came with a 22 kWh pack and a range of 81 miles (130 km), although for model year 2017, that increased to 33 kWh and 114 miles (183 km), making these the ones to look for. But plenty of i3s can also be found with the range extender, a two-cylinder motorbike engine that adds another 60 or 70 miles (97–112 km). And it is a true range extender—the little engine can’t directly drive the rear wheels; purists take note. Similarly, we were smitten with the Chevy Bolt from our very first time behind the wheel at the 2016 Consumer Electronics Show. The following year, the little Bolt hit the market as the first affordable EV to offer more than 200 miles of range on a full battery: 238 miles (383 km) to be precise. That might not sound like a lot in 2026, when people expect a new EV to get 300 miles (482 km) between charges, but back then, it was plenty compared to the likes of the i3 or the compliance cars offered by other OEMs. And Tesla’s Model 3 was still some way away, remember. The Bolt is efficient, but can also be a hoot to drive, especially if you fit it with tires that prioritize grip over low rolling resistance. Some people find the front seats uncomfortable. And it will only accept DC fast charges at up to 55 kW, but as long as you understand that up front, road trips are more than possible. Early Bolts—the ones in this price range—should have had their battery replaced as part of a $1.8 billion recall. What else? You’ll find lots of Nissan Leafs for less than $10,000, a mix of first- and second-generation models. Unlike the new Leaf, these don’t have active battery cooling, and thus will be subject to more battery degradation and therefore lost range than alternatives. (There’s a smartphone app you can use to interrogate the battery.) The Leaf is competent, but wouldn’t be our first pick over the Bolt. If you’re feeling a bit quirky, consider a compliance car. You’ll find Volkswagen e-Golfs, electric Ford Focuses, Kia Souls, and even some Toyota RAV4s and Mercedes-Benz B-classes, the latter two both using Tesla-supplied powertrains. As all of these are less common, it’s probably worth investigating how easily you can get them fixed if something breaks. And there are quite a few used Teslas within our budget. Mostly these are an older Model S with stratospheric mileages, but friend-of-Ars, the Late Brake Show’s Jonny Smith, bought a Tesla with more than 260,000 miles last year and seems to be doing OK with it. This includes benefiting from free Supercharging, although this does not apply to every Model S. And at this price, everyone will think you bought the car well before Elon took off the mask. SplatMan_DK I was tempted to get a used 3i recently; to delay the purchase of a new EV for a few years. We took a test drive. It handles great and I agree the interior is way better than a car in this class normally is. Our 2014 e-Golf (gen 1) has passed 278,000 km (about 173,000 miles) ) on its original battery, going through a decade of charging it to 100% 5-6 days a week. The battery finally collapsed this winter, with range now so poor I can't get to work without charging on the way. In the end we decided to by a new Toyota bZ4X and not delay the purchase. Seems like one of the better mid-class EVs currently (after they fixed the early problems of the model at least). I am a bit curious though. We have been extremely happy with our Gen 1 e-golf, and we would have kept it even longer if there was a realistic way to replace the battery. Everything but the batteri is still in great shape even after 278K km. We would have spent a decent chunk of money to keep it going. But it's not on the recommended list here. Was it never sold in the US, or is there some flaw with it that's more pronounced in the US market than it is in Europe? February 18, 2026 at 11:39 pm S Stuart Frasier Why the fixation on RWD? I live in central NC now so an inch of snow here is a big deal. And many winters if we see a dusting or none, well that's not unusual. But I also spent 8 years in Pittsburgh, PA with a lot of time in Hartford, CT. 4 feet of snow per year in Pittsburgh and the terrain makes San Francisco look flat. And a big snow or two per winter in CT. I had FWD most of the time in those areas and now in NC. I'm not troubled with how they drive. (But at times miss the ability to drift on old dirt roads.)The main advantage FWD has in snow is that there is more weight on the driven wheels in a front-engine ICE car. Since BEVs tend to have near equal weight distribution, FWD is all downside and no upside. You get a more complicated front suspension, worse handling, and a larger turning circle for no real improvement in traction. FWD BEV cars mostly exist as cost-saving efforts using shared platforms with ICE cars. February 19, 2026 at 6:28 pm Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/gadgets/2026/02/5-changes-to-know-about-in-apples-latest-ios-macos-and-ipados-betas/] | [TOKENS: 4193] |
FYI 5 changes to know about in Apple’s latest iOS, macOS, and iPadOS betas The 26.3 updates were mostly invisible; these changes are more significant. Andrew Cunningham – Feb 18, 2026 2:28 pm | 132 A collection of iPhones running iOS 26. Credit: Apple A collection of iPhones running iOS 26. Credit: Apple Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav This week, Apple released the first developer betas for iOS 26.4, iPadOS 26.4, macOS 26.4, and its other operating systems. On Tuesday, it followed those up with public beta versions of the same updates. Usually released around the midpoint between one major iOS release and the next, the *.4 updates to its operating system usually include a significant batch of new features and other refinements, and if the first beta is any indication, this year’s releases uphold that tradition. A new “Playlist Playground” feature will let Apple Music subscribers generate playlists with text prompts, and native support for video podcasts is coming to the Podcasts app. The Creator Studio version of the Freeform drawing and collaboration app is also available in the 26.4 updates, allowing subscribers to access stock images from Apple’s Content Hub and to insert AI-generated images. But we’ve spent time digging through the betas to identify some of the more below-the-surface improvements and changes that Apple is testing. Some of these changes won’t come to the public versions of the software until a later release; others may be removed or changed between now and when the 26.4 update is made available to the general public. But generally, Apple’s betas give us a good idea of what the final release will look like. One feature that hasn’t appeared in these betas? The new “more intelligent Siri” that Apple has been promising since the iOS 18 launch in 2024. Apple delayed the feature until sometime in 2026, citing that it wasn’t meeting the company’s standards for quality and reliability. Reports indicated that the company had been planning to make the new Siri part of the 26.4 update, but as of earlier this month, Apple has reportedly decided to push it to the 26.5 release or later; even releasing it as part of iOS 27 in the fall would technically not run afoul of the “2026” promise. Before we begin, the standard warning about installing beta software on hardware you rely on day to day. Although these point updates are generally more stable than the major releases Apple tests in the summer and fall, they can still contain major bugs and may cause your device to behave strangely. The first beta, in particular, tends to be the roughest—more stable versions will be released in the coming weeks, and we should see the final version of the update within the next couple months. Charging limits for MacBooks The macOS 26.4 update includes a slider for manually limiting your Mac’s battery charge percentage. Credit: Andrew Cunningham The macOS 26.4 update includes a slider for manually limiting your Mac’s battery charge percentage. Credit: Andrew Cunningham In macOS 11 Big Sur, Apple added an on-by-default “Optimized Battery Charging” toggle to the operating system that would allow macOS to limit your battery’s charge percentage to 80 percent based on your usage and charging behavior. The idea is to limit the time your battery spends charging while full, something that can gradually reduce its capacity. The macOS 26.4 update adds a new slider similar to the one in iOS, further allowing users to manually specify a maximum charge limit that is always observed, no matter what. It’s adjustable in 5 percent increments from 80 to 100 percent. Anecdotal evidence suggests that limiting your charge percentage can lengthen the useful life of your battery and reduce wear, but there’s nothing that will fully prevent a battery from wearing out and losing capacity over time. It’s up to users to decide whether an immediately noticeable everyday hit to battery life is worth a slightly longer service life. In the current macOS betas, enabling a charge limit manually doesn’t disable the Optimized Battery Charging feature the way it does in iOS. It’s unclear if this is an early bug or an intentional difference in how the feature is implemented in macOS. End-to-end encryption (and other improvements) for non-Apple texting Apple has been infamously slow to adopt support for the Rich Communication Services (RCS) messaging protocol used by most modern Android phones. Apple-to-Apple messaging was handled using iMessage, which supports end-to-end encryption among many other features. But for many years, it stuck by the aging SMS standard for “green bubble” texting between Apple’s platforms and others, to the enduring frustration of anyone with a single Android-using friend in a group chat. Apple finally began supporting RCS messaging for major cellular carriers in iOS 18, and has slowly expanded support to other networks in subsequent releases. But Apple’s implementation still doesn’t support end-to-end encryption, which was added to the RCS standard about a year ago. The 26.4 update is the first to begin testing encryption for RCS messages. But as with the initial RCS rollout, Apple is moving slowly and deliberately: for now, encrypted RCS messaging only works when texting between Apple devices, and not between Apple devices and Android phones. The feature also won’t be included in the final 26.4 release—it’s only included in the betas for testing purposes, and it “will be available to customers in a future software update for iOS, iPadOS, macOS, and watchOS.” Encrypted iMessage and RCS chats will be labeled with a lock icon, much like how most web browsers label HTTPS sites. To support encrypted messaging, Apple will jump from version 2.4 of the RCS Universal Profile to version 3.0. This should also enable support for several improvements in versions 2.5, 2.6, and 2.7 of the RCS standard, including previously iMessage-exclusive things like editing and recalling messages and replying to specific messages inline. The return of the “Compact” Safari tab bar The Compact tab view returns to Safari 26.4 and iPadOS 26.4. Credit: Andrew Cunningham The Compact tab view returns to Safari 26.4 and iPadOS 26.4. Credit: Andrew Cunningham As part of the macOS 12 Monterey/iPadOS 15 beta cycle in 2021, Apple attempted a pretty radical redesign of the Safari browser that combined your tabs and the address bar into one, with the goal of increasing the amount of viewable space on the pages you were viewing. By the time both operating systems were released to the public, Safari’s default design had more or less reverted to its previous state, but the “compact” tab view lived on as an optional view in the settings for those who liked it. Tahoe, the Safari 26 update, and iPadOS 26 all removed that Compact view entirely, though a version of the Compact view became the default for the iPhone version of Safari. The macOS 26.4, Safari 26.4, and iPadOS 26.4 updates restore the Compact tab option to the other versions of Safari. On-by-default Stolen Device Protection Originally introduced in the iOS 17.3 update, Apple’s “Stolen Device Protection” toggle for iPhones added an extra layer of security for users whose phones were stolen by people who had learned their passcodes. With Stolen Device Protection enabled, an iPhone that had been removed from “familiar locations, such as home or work” would require biometric Face ID or Touch ID authentication before accessing stored passwords and credit cards, erasing your phone, or changing Apple Account passwords. Normally, users can enter their passcodes as a fallback; Stolen Device Protection removes that fallback. The iOS 26.4 update will make Stolen Device Protection on by default. Generally, you won’t notice a difference in how your phone behaves, but if you’re traveling or away from places where you regularly use your phone and you can’t use your passcode to access certain information, this is why. It’s possible to switch off Stolen Device protection, but doing so requires biometric authentication, an hour-long wait, and then a second biometric authentication. (This extended wait is also required for disabling Find My, changing your phone’s passcode, or changing Touch ID and Face ID settings.) Rosetta’s end approaches The macOS 26.4 update will add the first user-facing notifications about the end of Rosetta support, currently slated for macOS 28 in 2027. Credit: Andrew Cunningham The macOS 26.4 update will add the first user-facing notifications about the end of Rosetta support, currently slated for macOS 28 in 2027. Credit: Andrew Cunningham Apple’s Rosetta 2 was a crucial support beam in the bridge from the Intel Mac era to the Apple Silicon era, enabling unmodified Intel-native apps to run on the M1 and later processors, with noticeable but manageable performance and responsiveness hits. As with the original Rosetta, it allowed Apple to execute a major CPU architecture switch while keeping it mostly invisible to Mac users, and it bought developers time to release Arm-native versions of their apps so they could take full advantage of the new chips. But now that the transition is complete and the last Intel Macs are fading into the rearview, Apple plans to remove the translation layer from future versions of macOS, with some exceptions for games that rely on the technology. Rosetta 2 won’t be completely removed until macOS 28, but macOS 26.4 will be the first to begin warning users about the end of Rosetta when they launch Intel-native apps. Those notifications link to an Apple support page about identifying and updating Intel-only apps to Apple Silicon-native versions (or universal binaries that support both architectures). Apple has deployed this “adding notifications without removing functionality” approach to deprecating older apps before. Versions 10.13 and 10.14 of macOS would show users pop-ups about the end of support for 32-bit apps for a couple of years before that support was removed in macOS 10.15, for example. Andrew Cunningham Senior Technology Reporter Andrew Cunningham Senior Technology Reporter Andrew is a Senior Technology Reporter at Ars Technica, with a focus on consumer tech including computer hardware and in-depth reviews of operating systems like Windows and macOS. Andrew lives in Philadelphia and co-hosts a weekly book podcast called Overdue. 132 Comments 5 changes to know about in Apple’s latest iOS, macOS, and iPadOS betas The 26.3 updates were mostly invisible; these changes are more significant. This week, Apple released the first developer betas for iOS 26.4, iPadOS 26.4, macOS 26.4, and its other operating systems. On Tuesday, it followed those up with public beta versions of the same updates. Usually released around the midpoint between one major iOS release and the next, the *.4 updates to its operating system usually include a significant batch of new features and other refinements, and if the first beta is any indication, this year’s releases uphold that tradition. A new “Playlist Playground” feature will let Apple Music subscribers generate playlists with text prompts, and native support for video podcasts is coming to the Podcasts app. The Creator Studio version of the Freeform drawing and collaboration app is also available in the 26.4 updates, allowing subscribers to access stock images from Apple’s Content Hub and to insert AI-generated images. But we’ve spent time digging through the betas to identify some of the more below-the-surface improvements and changes that Apple is testing. Some of these changes won’t come to the public versions of the software until a later release; others may be removed or changed between now and when the 26.4 update is made available to the general public. But generally, Apple’s betas give us a good idea of what the final release will look like. One feature that hasn’t appeared in these betas? The new “more intelligent Siri” that Apple has been promising since the iOS 18 launch in 2024. Apple delayed the feature until sometime in 2026, citing that it wasn’t meeting the company’s standards for quality and reliability. Reports indicated that the company had been planning to make the new Siri part of the 26.4 update, but as of earlier this month, Apple has reportedly decided to push it to the 26.5 release or later; even releasing it as part of iOS 27 in the fall would technically not run afoul of the “2026” promise. Before we begin, the standard warning about installing beta software on hardware you rely on day to day. Although these point updates are generally more stable than the major releases Apple tests in the summer and fall, they can still contain major bugs and may cause your device to behave strangely. The first beta, in particular, tends to be the roughest—more stable versions will be released in the coming weeks, and we should see the final version of the update within the next couple months. Charging limits for MacBooks In macOS 11 Big Sur, Apple added an on-by-default “Optimized Battery Charging” toggle to the operating system that would allow macOS to limit your battery’s charge percentage to 80 percent based on your usage and charging behavior. The idea is to limit the time your battery spends charging while full, something that can gradually reduce its capacity. The macOS 26.4 update adds a new slider similar to the one in iOS, further allowing users to manually specify a maximum charge limit that is always observed, no matter what. It’s adjustable in 5 percent increments from 80 to 100 percent. Anecdotal evidence suggests that limiting your charge percentage can lengthen the useful life of your battery and reduce wear, but there’s nothing that will fully prevent a battery from wearing out and losing capacity over time. It’s up to users to decide whether an immediately noticeable everyday hit to battery life is worth a slightly longer service life. In the current macOS betas, enabling a charge limit manually doesn’t disable the Optimized Battery Charging feature the way it does in iOS. It’s unclear if this is an early bug or an intentional difference in how the feature is implemented in macOS. End-to-end encryption (and other improvements) for non-Apple texting Apple has been infamously slow to adopt support for the Rich Communication Services (RCS) messaging protocol used by most modern Android phones. Apple-to-Apple messaging was handled using iMessage, which supports end-to-end encryption among many other features. But for many years, it stuck by the aging SMS standard for “green bubble” texting between Apple’s platforms and others, to the enduring frustration of anyone with a single Android-using friend in a group chat. Apple finally began supporting RCS messaging for major cellular carriers in iOS 18, and has slowly expanded support to other networks in subsequent releases. But Apple’s implementation still doesn’t support end-to-end encryption, which was added to the RCS standard about a year ago. The 26.4 update is the first to begin testing encryption for RCS messages. But as with the initial RCS rollout, Apple is moving slowly and deliberately: for now, encrypted RCS messaging only works when texting between Apple devices, and not between Apple devices and Android phones. The feature also won’t be included in the final 26.4 release—it’s only included in the betas for testing purposes, and it “will be available to customers in a future software update for iOS, iPadOS, macOS, and watchOS.” Encrypted iMessage and RCS chats will be labeled with a lock icon, much like how most web browsers label HTTPS sites. To support encrypted messaging, Apple will jump from version 2.4 of the RCS Universal Profile to version 3.0. This should also enable support for several improvements in versions 2.5, 2.6, and 2.7 of the RCS standard, including previously iMessage-exclusive things like editing and recalling messages and replying to specific messages inline. The return of the “Compact” Safari tab bar As part of the macOS 12 Monterey/iPadOS 15 beta cycle in 2021, Apple attempted a pretty radical redesign of the Safari browser that combined your tabs and the address bar into one, with the goal of increasing the amount of viewable space on the pages you were viewing. By the time both operating systems were released to the public, Safari’s default design had more or less reverted to its previous state, but the “compact” tab view lived on as an optional view in the settings for those who liked it. Tahoe, the Safari 26 update, and iPadOS 26 all removed that Compact view entirely, though a version of the Compact view became the default for the iPhone version of Safari. The macOS 26.4, Safari 26.4, and iPadOS 26.4 updates restore the Compact tab option to the other versions of Safari. On-by-default Stolen Device Protection Originally introduced in the iOS 17.3 update, Apple’s “Stolen Device Protection” toggle for iPhones added an extra layer of security for users whose phones were stolen by people who had learned their passcodes. With Stolen Device Protection enabled, an iPhone that had been removed from “familiar locations, such as home or work” would require biometric Face ID or Touch ID authentication before accessing stored passwords and credit cards, erasing your phone, or changing Apple Account passwords. Normally, users can enter their passcodes as a fallback; Stolen Device Protection removes that fallback. The iOS 26.4 update will make Stolen Device Protection on by default. Generally, you won’t notice a difference in how your phone behaves, but if you’re traveling or away from places where you regularly use your phone and you can’t use your passcode to access certain information, this is why. It’s possible to switch off Stolen Device protection, but doing so requires biometric authentication, an hour-long wait, and then a second biometric authentication. (This extended wait is also required for disabling Find My, changing your phone’s passcode, or changing Touch ID and Face ID settings.) Rosetta’s end approaches Apple’s Rosetta 2 was a crucial support beam in the bridge from the Intel Mac era to the Apple Silicon era, enabling unmodified Intel-native apps to run on the M1 and later processors, with noticeable but manageable performance and responsiveness hits. As with the original Rosetta, it allowed Apple to execute a major CPU architecture switch while keeping it mostly invisible to Mac users, and it bought developers time to release Arm-native versions of their apps so they could take full advantage of the new chips. But now that the transition is complete and the last Intel Macs are fading into the rearview, Apple plans to remove the translation layer from future versions of macOS, with some exceptions for games that rely on the technology. Rosetta 2 won’t be completely removed until macOS 28, but macOS 26.4 will be the first to begin warning users about the end of Rosetta when they launch Intel-native apps. Those notifications link to an Apple support page about identifying and updating Intel-only apps to Apple Silicon-native versions (or universal binaries that support both architectures). Apple has deployed this “adding notifications without removing functionality” approach to deprecating older apps before. Versions 10.13 and 10.14 of macOS would show users pop-ups about the end of support for 32-bit apps for a couple of years before that support was removed in macOS 10.15, for example. F Fred Duck i need a TL;DR on that one, dogCertainly. Let's use Fred Intelligence (FI) to summarise the Arsticle. 1 Charging limits for MacBooks 2 End-to-end encryption (and other improvements) for non-Apple texting 3 The return of the “Compact” Safari tab bar 4 On-by-default Stolen Device Protection 5 Rosetta’s end approaches 6 Apple-shaped products If I can be of further assistance, don't hesitate. February 18, 2026 at 7:49 pm Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/gadgets/2026/02/googles-pixel-10a-arrives-on-march-5-for-499-with-specs-and-design-of-yesteryear/] | [TOKENS: 2597] |
Stay the course Google’s Pixel 10a arrives on March 5 for $499 with specs and design of yesteryear Google’s new budget phone is here, but don’t expect a big upgrade. Ryan Whitwam – Feb 18, 2026 10:00 am | 113 Credit: Google Credit: Google Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav It’s that time of year—a new budget Pixel phone is about to hit virtual shelves. The Pixel 10a will be available on March 5, and pre-orders go live today. The 9a will still be on sale for a while, but the 10a will be headlining Google’s store. However, you might not notice unless you keep up with the Pixel numbering scheme. This year’s A-series Pixel is virtually identical to last year’s, both inside and out. Last year’s Pixel 9a was a notable departure from the older design language, but Google made few changes for 2026. We liked that the Pixel 9a emphasized battery capacity and moved to a flat camera bump, and this time, it’s really flat. Google says the camera now sits totally flush with the back panel. This is probably the only change you’ll be able to identify visually. Specs at a glance: Google Pixel 9a vs. Pixel 10a Phone Pixel 9a Pixel 10a SoC Google Tensor G4 Google Tensor G4 Memory 8GB 8GB Storage 128GB, 256GB 128GB, 256GB Display 1080×2424 6.3″ pOLED, 60–120 Hz, Gorilla Glass 3, 2700 nits (peak) 1080×2424 6.3″ pOLED, 60–120 Hz, Gorilla Glass 7i, 3000 nits (peak) Cameras 48 MP primary, f/1.7, OIS; 13 MP ultrawide, f/2.2; 13 MP selfie, f/2.2 48 MP primary, f/1.7, OIS; 13 MP ultrawide, f/2.2; 13 MP selfie, f/2.2 Software Android 15 (at launch), 7 years of OS updates Android 16, 7 years of OS updates Battery 5,100 mAh, 23 W wired charging, 7.5 W wireless charging 5,100 mAh, 30 W wired charging, 10 W wireless charging Connectivity Wi-Fi 6e, NFC, Bluetooth 5.3, sub-6 GHz 5G, USB-C 3.2 Wi-Fi 6e, NFC, Bluetooth 6.0, sub-6 GHz 5G, USB-C 3.2 Measurements 154.7×73.3×8.9 mm; 185 g 153.9×73×9 mm; 183 g Google also says the new Pixel will have a slightly upgraded screen. The resolution, size, and refresh rate are unchanged, but peak brightness has been bumped from 2,700 nits to 3,000 nits (the same as the base model Pixel 10). Plus, the cover glass has finally moved beyond Gorilla Glass 3 to Gorilla Glass 7i, which supposedly has improved scratch and drop protection. Credit: Google Credit: Google Google notes that more of the phone is constructed from recycled material, 100 percent for the aluminum frame and 81 percent for the plastic back. There’s also recycled gold, tungsten, cobalt, and copper inside, amounting to about 36 percent of the phone’s weight. The phone also continues to have a physical SIM slot, which was removed from the Pixel 10 series last year. The device’s USB-C 3.2 port can also charge slightly faster than the 9a (30 W versus 23 W), and wireless charging has gone from 7.5 W to 10 W. There are no Qi2 magnets inside, though. Internally, the Pixel 10a is even more like its predecessor. Unlike past A-series phones, this one doesn’t have the latest Tensor chip—it’s sticking with the same Tensor G4 from the 9a. That’s a bummer, as the G5 was a bigger leap than most of Google’s chip upgrades. The company says it stuck with the G4 to “balance affordability and performance.” In fairness, Google has managed to keep the price steady at $499. With components like RAM and storage in short supply this year, prices could rise for many device refreshes. Why the sidegrade? Google’s position is that the Pixel 10a still offers a good value despite the middling upgrades compared to last year’s phone. It keeps the Pixel camera experience (which is admittedly great) available at a lower price than the flagship phones. While you get better results with the more expensive Pixels, the 9a was still one of the mobile photography options in 2025. With identical camera hardware in 2026, we expect the 10a to be the same. But why not make the Pixel 10a a bigger upgrade? Making a better phone theoretically means you sell more of them, right? There are a few possibilities. By slowing the improvement of the A-series Pixels, Google is making the Pixel 10 look like a better option for buyers. Upgrading the processor and adding features like PixelSnap could make the 10a too appealing compared to the $800 Pixel 10—Google’s A-series phones have been regularly recommended over the flagships due to the lower price and similar capabilities. The Pixel 10’s camera is also less capable than the Pixel 9 was for that generation, making it that much more similar to the A-series. Component prices are also a concern for 2026. While smartphone development cycles can easily range from 18 to 24 months, Google may have decided late in the game to stick with the Tensor G4 in this phone to offset the higher cost of storage and memory. Google has stressed that it wanted to keep the A-series at its traditional $499 price. As a major player in AI, an industry that is vacuuming up all those parts, Google may have had insight into the coming shortage before most. Credit: Google Credit: Google Whatever the reason, the Pixel 10a is looking like a very modest upgrade. If you still think it’s the right phone for you, Google will take your money starting today. The device is at the Google Store for $499 with 128GB of storage, and some carriers should begin offering the phone soon. The 256GB version runs $100 more. The Pixel 10a is available in Lavender, Fog, Obsidian, and the new Berry color. Ryan Whitwam Senior Technology Reporter Ryan Whitwam Senior Technology Reporter Ryan Whitwam is a senior technology reporter at Ars Technica, covering the ways Google, AI, and mobile technology continue to change the world. Over his 20-year career, he's written for Android Police, ExtremeTech, Wirecutter, NY Times, and more. He has reviewed more phones than most people will ever own. You can follow him on Bluesky, where you will see photos of his dozens of mechanical keyboards. 113 Comments Google’s Pixel 10a arrives on March 5 for $499 with specs and design of yesteryear Google’s new budget phone is here, but don’t expect a big upgrade. It’s that time of year—a new budget Pixel phone is about to hit virtual shelves. The Pixel 10a will be available on March 5, and pre-orders go live today. The 9a will still be on sale for a while, but the 10a will be headlining Google’s store. However, you might not notice unless you keep up with the Pixel numbering scheme. This year’s A-series Pixel is virtually identical to last year’s, both inside and out. Last year’s Pixel 9a was a notable departure from the older design language, but Google made few changes for 2026. We liked that the Pixel 9a emphasized battery capacity and moved to a flat camera bump, and this time, it’s really flat. Google says the camera now sits totally flush with the back panel. This is probably the only change you’ll be able to identify visually. Google also says the new Pixel will have a slightly upgraded screen. The resolution, size, and refresh rate are unchanged, but peak brightness has been bumped from 2,700 nits to 3,000 nits (the same as the base model Pixel 10). Plus, the cover glass has finally moved beyond Gorilla Glass 3 to Gorilla Glass 7i, which supposedly has improved scratch and drop protection. Credit: Google Credit: Google Google notes that more of the phone is constructed from recycled material, 100 percent for the aluminum frame and 81 percent for the plastic back. There’s also recycled gold, tungsten, cobalt, and copper inside, amounting to about 36 percent of the phone’s weight. The phone also continues to have a physical SIM slot, which was removed from the Pixel 10 series last year. The device’s USB-C 3.2 port can also charge slightly faster than the 9a (30 W versus 23 W), and wireless charging has gone from 7.5 W to 10 W. There are no Qi2 magnets inside, though. Internally, the Pixel 10a is even more like its predecessor. Unlike past A-series phones, this one doesn’t have the latest Tensor chip—it’s sticking with the same Tensor G4 from the 9a. That’s a bummer, as the G5 was a bigger leap than most of Google’s chip upgrades. The company says it stuck with the G4 to “balance affordability and performance.” In fairness, Google has managed to keep the price steady at $499. With components like RAM and storage in short supply this year, prices could rise for many device refreshes. Why the sidegrade? Google’s position is that the Pixel 10a still offers a good value despite the middling upgrades compared to last year’s phone. It keeps the Pixel camera experience (which is admittedly great) available at a lower price than the flagship phones. While you get better results with the more expensive Pixels, the 9a was still one of the mobile photography options in 2025. With identical camera hardware in 2026, we expect the 10a to be the same. But why not make the Pixel 10a a bigger upgrade? Making a better phone theoretically means you sell more of them, right? There are a few possibilities. By slowing the improvement of the A-series Pixels, Google is making the Pixel 10 look like a better option for buyers. Upgrading the processor and adding features like PixelSnap could make the 10a too appealing compared to the $800 Pixel 10—Google’s A-series phones have been regularly recommended over the flagships due to the lower price and similar capabilities. The Pixel 10’s camera is also less capable than the Pixel 9 was for that generation, making it that much more similar to the A-series. Component prices are also a concern for 2026. While smartphone development cycles can easily range from 18 to 24 months, Google may have decided late in the game to stick with the Tensor G4 in this phone to offset the higher cost of storage and memory. Google has stressed that it wanted to keep the A-series at its traditional $499 price. As a major player in AI, an industry that is vacuuming up all those parts, Google may have had insight into the coming shortage before most. Credit: Google Credit: Google Whatever the reason, the Pixel 10a is looking like a very modest upgrade. If you still think it’s the right phone for you, Google will take your money starting today. The device is at the Google Store for $499 with 128GB of storage, and some carriers should begin offering the phone soon. The 256GB version runs $100 more. The Pixel 10a is available in Lavender, Fog, Obsidian, and the new Berry color. Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/tech-policy/2026/02/lawsuit-epa-revoking-greenhouse-gas-finding-risks-thousands-of-avoidable-deaths/] | [TOKENS: 3540] |
“Deadly serious” Lawsuit: EPA revoking greenhouse gas finding risks “thousands of avoidable deaths” EPA sued for abandoning its mission to protect public health. Ashley Belanger – Feb 18, 2026 2:48 pm | 63 Credit: Tramino | iStock / Getty Images Plus Credit: Tramino | iStock / Getty Images Plus Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav In a lawsuit filed Wednesday, the Environmental Protection Agency was accused of abandoning its mission to protect public health after repealing an “endangerment finding” that has served as the basis for federal climate change regulations for 17 years. The lawsuit came from more than a dozen environmental and health groups, including the American Public Health Association, the American Lung Association, the Center for Biological Diversity (CBD), the Clean Air Council, the Environmental Defense Fund (EDF), the Natural Resources Defense Council (NRDC), the Sierra Club, and the Union of Concerned Scientists. The groups have asked the US Court of Appeals for the District of Columbia Circuit to review the EPA decision, which also eliminated requirements controlling greenhouse gas emissions in new cars and trucks. Urging a return to the status quo, the groups argued that the Trump administration is anti-science and illegally moving to benefit the fossil fuel industry, despite a mountain of evidence demonstrating the deadly consequences of unchecked pollution and climate change-induced floods, droughts, wildfires, and hurricanes. “Undercutting the ability of the federal government to tackle the largest source of climate pollution is deadly serious,” Meredith Hankins, legal director for federal climate at NRDC, said in an EDF roundup of statements from plaintiffs. The science is overwhelmingly clear, the groups argued, despite the Trump EPA attempting to muddy the waters by forming a since-disbanded working group of climate contrarians. Trump is a longtime climate denier, as evidenced by a Euro News tracker monitoring his most controversial comments. Most recently, during a cold snap affecting much of the US, he predictably trolled environmentalists, writing on Truth Social, “could the Environmental Insurrectionists please explain—WHATEVER HAPPENED TO GLOBAL WARMING?” The EPA’s final rule summary bragged that “this is the single largest deregulatory action in US history and will save Americans over $1.3 trillion” by 2055. Supposedly, carmakers will pass on any savings from no longer having to meet emissions requirements, giving Americans more access to affordable cars by shutting down expensive emissions and EV mandates “strangling” the auto industry. Sounding nothing like an agency created to monitor pollutants, a fact sheet on the final rule emphasized that Trump’s EPA “chooses consumer choice over climate change zealotry every time.” Critics quickly slammed Trump’s claims that removing the endangerment finding would help the economy. Any savings from cheaper vehicles or reduced costs of charging infrastructure (as Americans ostensibly buy fewer EVs) would be offset by $1.4 trillion “in additional costs from increased fuel purchases, vehicle repair and maintenance, insurance, traffic congestion, and noise,” The Guardian reported. The EPA’s economic analysis also ignores public health costs, the groups suing alleged. David Pettit, an attorney at the CBD’s Climate Law Institute, slammed the EPA’s messaging as an attempt to sway consumers without explaining the true costs. “Nobody but Big Oil profits from Trump trashing climate science and making cars and trucks guzzle and pollute more,” Pettit said. “Consumers will pay more to fill up, and our skies and oceans will fill up with more pollution.” If the court sides with the EPA, “people everywhere will face more pollution, higher costs, and thousands of avoidable deaths,” Peter Zalzal, EDF’s associate vice president of clean air strategies, said. EPA argued climate change evidence is “out of scope” For environmentalists, the decision to sue the EPA was risky but necessary. By putting up a fight, they risk a court potentially reversing the 2009 Supreme Court ruling requiring the EPA to conduct the initial endangerment analysis and then regulate any pollution found from greenhouse gases. Seemingly, that reversal is what the Trump administration has been angling for, hoping the case will reach the Supreme Court, which is more conservative today and perhaps less likely to read the Clean Air Act as broadly as the 2009 court. It’s worth the risk, according to William Piermattei, the managing director of the Environmental Law Program at the University of Maryland Francis King Carey School of Law. He told The New York Times that environmentalists had no choice but to file the lawsuit and act on the public’s behalf. Environmentalists “must challenge this,” Piermattei said. If they didn’t, they’d be “agreeing that we should not regulate greenhouse gasses under the Clean Air Act, full stop.” He suggested that “a majority of the public, does not agree with that statement at all.” Since 2010, the EPA has found that the scientific basis for concluding that “elevated concentrations of greenhouse gases in the atmosphere may reasonably be anticipated to endanger the public health and welfare of current and future US generations is robust, voluminous, and compelling.” And since then, the evidence base has only grown, the groups suing said. Trump used to seem intimidated by the “overwhelming” evidence, environmentalists have noted. During Trump’s prior term, he notably left the endangerment finding in place, perhaps expecting that the evidence was irrefutable. He’s now renewed that fight, arguing that the evidence should be set aside, so that courts can focus on whether Congress “must weigh in on ‘major questions’ that have significant political and economic implications” and serve as a check on the EPA. In the EPA’s comments addressing public concerns about the agency ignoring evidence, the agency has already argued that evidence of climate change is “out of scope” since the EPA did not repeal the basis of the finding. Instead, the EPA claims it is merely challenging its own authority to continue to regulate the auto industry for harmful emissions, suggesting that only Congress has that authority. The Clean Air Act “does not provide EPA statutory authority to prescribe motor vehicle emission standards for the purpose of addressing global climate change concerns,” the EPA said. “In the absence of such authority, the Endangerment Finding is not valid, and EPA cannot retain the regulations that resulted from it.” Whether courts will agree that evidence supporting climate change is “out of scope” could determine whether the Supreme Court’s prior decision that compelled the endangerment finding is ultimately overturned. If that happens, subsequent administrations may struggle to issue a new endangerment finding to undo any potential damage. All eyes would then turn to Congress to pass a law to uphold protections. EPA accused of abandoning its mission By ignoring science, the EPA risks eroding public trust, according to Hana Vizcarra, a senior lawyer at the nonprofit Earthjustice, which is representing several groups in the litigation. “With this action, EPA flips its mission on its head,” Vizcarra said. “It abandons its core mandate to protect human health and the environment to boost polluting industries and attempts to rewrite the law in order to do so.” Groups appear confident that the courts will consider the science. Joanne Spalding, director of the Sierra Club’s Environmental Law Program, noted that the early 2000s litigation from the Sierra Club brought about the original EPA protections. She vowed that the Sierra Club would continue fighting to keep them. “People should not be forced to suffer for this administration’s blind allegiance to the fossil fuel industry and corporate polluters,” Spalding said. “This shortsighted rollback is blatantly unlawful and their efforts to force this upon the American people will fail.” Ankush Bansal, board president of Physicians for Social Responsibility, warned that courts cannot afford to ignore the evidence. The EPA’s “devastating decision” goes “against the science and testimony of countless scientists, health care professionals, and public health practitioners,” Bansal said. If upheld, the long-term consequences could seemingly bury courts in future legal battles. “It will result in direct harm to the health of Americans throughout the country, particularly children, older adults, those with chronic illnesses, and other vulnerable populations, rural to urban, red and blue, of all races and incomes,” Bansal said. “The increased exposure to harmful pollutants and other greenhouse gas emissions from fossil fuel production and consumption will make America sicker, not healthier, less prosperous, not more, for generations to come.” Ashley Belanger Senior Policy Reporter Ashley Belanger Senior Policy Reporter Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience. 63 Comments Lawsuit: EPA revoking greenhouse gas finding risks “thousands of avoidable deaths” EPA sued for abandoning its mission to protect public health. In a lawsuit filed Wednesday, the Environmental Protection Agency was accused of abandoning its mission to protect public health after repealing an “endangerment finding” that has served as the basis for federal climate change regulations for 17 years. The lawsuit came from more than a dozen environmental and health groups, including the American Public Health Association, the American Lung Association, the Center for Biological Diversity (CBD), the Clean Air Council, the Environmental Defense Fund (EDF), the Natural Resources Defense Council (NRDC), the Sierra Club, and the Union of Concerned Scientists. The groups have asked the US Court of Appeals for the District of Columbia Circuit to review the EPA decision, which also eliminated requirements controlling greenhouse gas emissions in new cars and trucks. Urging a return to the status quo, the groups argued that the Trump administration is anti-science and illegally moving to benefit the fossil fuel industry, despite a mountain of evidence demonstrating the deadly consequences of unchecked pollution and climate change-induced floods, droughts, wildfires, and hurricanes. “Undercutting the ability of the federal government to tackle the largest source of climate pollution is deadly serious,” Meredith Hankins, legal director for federal climate at NRDC, said in an EDF roundup of statements from plaintiffs. The science is overwhelmingly clear, the groups argued, despite the Trump EPA attempting to muddy the waters by forming a since-disbanded working group of climate contrarians. Trump is a longtime climate denier, as evidenced by a Euro News tracker monitoring his most controversial comments. Most recently, during a cold snap affecting much of the US, he predictably trolled environmentalists, writing on Truth Social, “could the Environmental Insurrectionists please explain—WHATEVER HAPPENED TO GLOBAL WARMING?” The EPA’s final rule summary bragged that “this is the single largest deregulatory action in US history and will save Americans over $1.3 trillion” by 2055. Supposedly, carmakers will pass on any savings from no longer having to meet emissions requirements, giving Americans more access to affordable cars by shutting down expensive emissions and EV mandates “strangling” the auto industry. Sounding nothing like an agency created to monitor pollutants, a fact sheet on the final rule emphasized that Trump’s EPA “chooses consumer choice over climate change zealotry every time.” Critics quickly slammed Trump’s claims that removing the endangerment finding would help the economy. Any savings from cheaper vehicles or reduced costs of charging infrastructure (as Americans ostensibly buy fewer EVs) would be offset by $1.4 trillion “in additional costs from increased fuel purchases, vehicle repair and maintenance, insurance, traffic congestion, and noise,” The Guardian reported. The EPA’s economic analysis also ignores public health costs, the groups suing alleged. David Pettit, an attorney at the CBD’s Climate Law Institute, slammed the EPA’s messaging as an attempt to sway consumers without explaining the true costs. “Nobody but Big Oil profits from Trump trashing climate science and making cars and trucks guzzle and pollute more,” Pettit said. “Consumers will pay more to fill up, and our skies and oceans will fill up with more pollution.” If the court sides with the EPA, “people everywhere will face more pollution, higher costs, and thousands of avoidable deaths,” Peter Zalzal, EDF’s associate vice president of clean air strategies, said. EPA argued climate change evidence is “out of scope” For environmentalists, the decision to sue the EPA was risky but necessary. By putting up a fight, they risk a court potentially reversing the 2009 Supreme Court ruling requiring the EPA to conduct the initial endangerment analysis and then regulate any pollution found from greenhouse gases. Seemingly, that reversal is what the Trump administration has been angling for, hoping the case will reach the Supreme Court, which is more conservative today and perhaps less likely to read the Clean Air Act as broadly as the 2009 court. It’s worth the risk, according to William Piermattei, the managing director of the Environmental Law Program at the University of Maryland Francis King Carey School of Law. He told The New York Times that environmentalists had no choice but to file the lawsuit and act on the public’s behalf. Environmentalists “must challenge this,” Piermattei said. If they didn’t, they’d be “agreeing that we should not regulate greenhouse gasses under the Clean Air Act, full stop.” He suggested that “a majority of the public, does not agree with that statement at all.” Since 2010, the EPA has found that the scientific basis for concluding that “elevated concentrations of greenhouse gases in the atmosphere may reasonably be anticipated to endanger the public health and welfare of current and future US generations is robust, voluminous, and compelling.” And since then, the evidence base has only grown, the groups suing said. Trump used to seem intimidated by the “overwhelming” evidence, environmentalists have noted. During Trump’s prior term, he notably left the endangerment finding in place, perhaps expecting that the evidence was irrefutable. He’s now renewed that fight, arguing that the evidence should be set aside, so that courts can focus on whether Congress “must weigh in on ‘major questions’ that have significant political and economic implications” and serve as a check on the EPA. In the EPA’s comments addressing public concerns about the agency ignoring evidence, the agency has already argued that evidence of climate change is “out of scope” since the EPA did not repeal the basis of the finding. Instead, the EPA claims it is merely challenging its own authority to continue to regulate the auto industry for harmful emissions, suggesting that only Congress has that authority. The Clean Air Act “does not provide EPA statutory authority to prescribe motor vehicle emission standards for the purpose of addressing global climate change concerns,” the EPA said. “In the absence of such authority, the Endangerment Finding is not valid, and EPA cannot retain the regulations that resulted from it.” Whether courts will agree that evidence supporting climate change is “out of scope” could determine whether the Supreme Court’s prior decision that compelled the endangerment finding is ultimately overturned. If that happens, subsequent administrations may struggle to issue a new endangerment finding to undo any potential damage. All eyes would then turn to Congress to pass a law to uphold protections. EPA accused of abandoning its mission By ignoring science, the EPA risks eroding public trust, according to Hana Vizcarra, a senior lawyer at the nonprofit Earthjustice, which is representing several groups in the litigation. “With this action, EPA flips its mission on its head,” Vizcarra said. “It abandons its core mandate to protect human health and the environment to boost polluting industries and attempts to rewrite the law in order to do so.” Groups appear confident that the courts will consider the science. Joanne Spalding, director of the Sierra Club’s Environmental Law Program, noted that the early 2000s litigation from the Sierra Club brought about the original EPA protections. She vowed that the Sierra Club would continue fighting to keep them. “People should not be forced to suffer for this administration’s blind allegiance to the fossil fuel industry and corporate polluters,” Spalding said. “This shortsighted rollback is blatantly unlawful and their efforts to force this upon the American people will fail.” Ankush Bansal, board president of Physicians for Social Responsibility, warned that courts cannot afford to ignore the evidence. The EPA’s “devastating decision” goes “against the science and testimony of countless scientists, health care professionals, and public health practitioners,” Bansal said. If upheld, the long-term consequences could seemingly bury courts in future legal battles. “It will result in direct harm to the health of Americans throughout the country, particularly children, older adults, those with chronic illnesses, and other vulnerable populations, rural to urban, red and blue, of all races and incomes,” Bansal said. “The increased exposure to harmful pollutants and other greenhouse gas emissions from fossil fuel production and consumption will make America sicker, not healthier, less prosperous, not more, for generations to come.” Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/google/2026/02/gemini-can-now-generate-ai-music-for-you-no-lyrics-required/#comments] | [TOKENS: 2503] |
Rage Against the Machine Learning Record scratch—Google’s Lyria 3 AI music model is coming to Gemini today With a simple prompt, you can generate 30 seconds of something like music. Ryan Whitwam – Feb 18, 2026 11:00 am | 214 Credit: Google Credit: Google Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav The American poet Henry Wadsworth Longfellow called music “the universal language of mankind.” Is that still true when the so-called music is being generated by a probabilistic robot instead of a human? We’re about to find out. Google has announced its latest Lyria 3 AI model is being deployed in the Gemini app, vastly expanding access to AI music generation. Google DeepMind has been tinkering with Lyria for a while now, offering limited access in developer-oriented products like Vertex AI. Lyria 3 is more capable than previous versions, and it’s also quicker to use. Just select the new “Create music” option in the Gemini app or web UI to get started. You can describe what you want and even upload an image to help the robot get the right vibe. And in a few seconds, you get music (or something like it). In case there was any uncertainty about whether Lyria tracks still counted as a human artistic endeavor, worry not! Unlike past versions of the model, you don’t even have to provide lyrics in your prompt. You can be vague with your request, and the model will create suitable lyrics for the 30-second song. Although with that limit, “jingle” might be more accurate. In addition to the track, each music creation job will come with an album cover-style image created by the Nano Banana model. Gemini will also have a pre-loaded set of AI tracks that you can choose to remix to your heart’s content. The Lyria 3 tools are also coming to Google’s Dream Track toolkit for YouTube Shorts, which will pair nicely with the Veo AI video options. So what kind of tracks can you expect Gemini to spit out? Google has provided some examples: “Sweet Like Plantain“ Prompt: I’m feeling nostalgic. Create a track for my mother about the great times we had as kids and the memories of her home-cooked plantains. Make it a fun afrobeat track with a true African vibe. “Motown Parody“ Prompt: Quintessential 1970s Motown soul. Lush, orchestral R&B production. Warm bassline with melodic fills, locked into a steady drum groove with crisp snare and tambourine. Vintage organ harmonic bed. Three-piece brass section. Gritty, gospel-tinged male tenor lead. “Pop Flutter“ Prompt: Wistful and airy. Soft, breathy female vocals with intimacy. Rapid-fire drum and bass rhythm, low-passed and softened. Deep, warm bass swells. Dreamy electric piano chords and subtle chime textures. Rainy city vibes. “Sea Shanty“ Prompt: An authentic A capella Sea Shanty featuring a robust male choir singing in a traditional call-and-response format. The piece is entirely vocal, relying on synchronized foot-stomps on a wooden deck and sharp handclaps to provide the rhythmic pulse. The lead is a weathered male baritone with a gravelly timbre who sings the narrative ‘chant’ lines. He is immediately answered by a powerful male choir singing in rich, rugged harmony on the ‘response’ lines. The voices are recorded with a natural room reverb that simulates the acoustic environment of a wooden ship’s deck, giving the vocals a resonant, atmospheric quality. The performance is energetic and driving, with the choir leaning into the rhythm of the stomps to create a sense of focused, communal effort. There are no instruments, only the layered textures of collective male voices spanning tenor, baritone, and bass ranges, all contributing to a confident, monolithic sound. Sour notes AI-generated music is not a new phenomenon. Several companies offer models that ingest and homogenize human-created music, and the resulting tracks can sound remarkably “real,” if a bit overproduced. Streaming services have already been inundated with phony AI artists, some of which have gathered thousands of listeners who may not even realize they’re grooving to the musical equivalent of a blender set to purée. Still, you have to seek out tools like that, and Google is bringing similar capabilities to the Gemini app. As one of the most popular AI platforms, we’re probably about to see a lot more AI music on the Internet. Google says tracks generated with Lyria 3 will have an audio version of Google’s SynthID embedded within. That means you’ll always be able to check if a piece of audio was created with Google’s AI by uploading it to Gemini, similar to the way you can check images and videos for SynthID tags. Google also says it has sought to create a music AI that respects copyright and partner agreements. If you name a specific artist in your prompt, Gemini won’t attempt to copy that artist’s sound. Instead, it’s trained to take that as “broad creative inspiration.” Although it also notes this process is not foolproof, and some of that original expression might imitate an artist too much. In those cases, Google invites users to report such shared content. Lyria 3 is going live in the Gemini web interface today and should be available in the mobile app within a few days. It works in English, German, Spanish, French, Hindi, Japanese, Korean, and Portuguese, but Google plans to add more languages soon. While all users will have some access to music generation, those with AI Pro and AI Ultra subscriptions will have higher usage limits, but the specifics are unclear. Ryan Whitwam Senior Technology Reporter Ryan Whitwam Senior Technology Reporter Ryan Whitwam is a senior technology reporter at Ars Technica, covering the ways Google, AI, and mobile technology continue to change the world. Over his 20-year career, he's written for Android Police, ExtremeTech, Wirecutter, NY Times, and more. He has reviewed more phones than most people will ever own. You can follow him on Bluesky, where you will see photos of his dozens of mechanical keyboards. 214 Comments Record scratch—Google’s Lyria 3 AI music model is coming to Gemini today With a simple prompt, you can generate 30 seconds of something like music. The American poet Henry Wadsworth Longfellow called music “the universal language of mankind.” Is that still true when the so-called music is being generated by a probabilistic robot instead of a human? We’re about to find out. Google has announced its latest Lyria 3 AI model is being deployed in the Gemini app, vastly expanding access to AI music generation. Google DeepMind has been tinkering with Lyria for a while now, offering limited access in developer-oriented products like Vertex AI. Lyria 3 is more capable than previous versions, and it’s also quicker to use. Just select the new “Create music” option in the Gemini app or web UI to get started. You can describe what you want and even upload an image to help the robot get the right vibe. And in a few seconds, you get music (or something like it). In case there was any uncertainty about whether Lyria tracks still counted as a human artistic endeavor, worry not! Unlike past versions of the model, you don’t even have to provide lyrics in your prompt. You can be vague with your request, and the model will create suitable lyrics for the 30-second song. Although with that limit, “jingle” might be more accurate. In addition to the track, each music creation job will come with an album cover-style image created by the Nano Banana model. Gemini will also have a pre-loaded set of AI tracks that you can choose to remix to your heart’s content. The Lyria 3 tools are also coming to Google’s Dream Track toolkit for YouTube Shorts, which will pair nicely with the Veo AI video options. So what kind of tracks can you expect Gemini to spit out? Google has provided some examples: “Sweet Like Plantain“ Prompt: I’m feeling nostalgic. Create a track for my mother about the great times we had as kids and the memories of her home-cooked plantains. Make it a fun afrobeat track with a true African vibe. “Motown Parody“ Prompt: Quintessential 1970s Motown soul. Lush, orchestral R&B production. Warm bassline with melodic fills, locked into a steady drum groove with crisp snare and tambourine. Vintage organ harmonic bed. Three-piece brass section. Gritty, gospel-tinged male tenor lead. “Pop Flutter“ Prompt: Wistful and airy. Soft, breathy female vocals with intimacy. Rapid-fire drum and bass rhythm, low-passed and softened. Deep, warm bass swells. Dreamy electric piano chords and subtle chime textures. Rainy city vibes. “Sea Shanty“ Prompt: An authentic A capella Sea Shanty featuring a robust male choir singing in a traditional call-and-response format. The piece is entirely vocal, relying on synchronized foot-stomps on a wooden deck and sharp handclaps to provide the rhythmic pulse. The lead is a weathered male baritone with a gravelly timbre who sings the narrative ‘chant’ lines. He is immediately answered by a powerful male choir singing in rich, rugged harmony on the ‘response’ lines. The voices are recorded with a natural room reverb that simulates the acoustic environment of a wooden ship’s deck, giving the vocals a resonant, atmospheric quality. The performance is energetic and driving, with the choir leaning into the rhythm of the stomps to create a sense of focused, communal effort. There are no instruments, only the layered textures of collective male voices spanning tenor, baritone, and bass ranges, all contributing to a confident, monolithic sound. Sour notes AI-generated music is not a new phenomenon. Several companies offer models that ingest and homogenize human-created music, and the resulting tracks can sound remarkably “real,” if a bit overproduced. Streaming services have already been inundated with phony AI artists, some of which have gathered thousands of listeners who may not even realize they’re grooving to the musical equivalent of a blender set to purée. Still, you have to seek out tools like that, and Google is bringing similar capabilities to the Gemini app. As one of the most popular AI platforms, we’re probably about to see a lot more AI music on the Internet. Google says tracks generated with Lyria 3 will have an audio version of Google’s SynthID embedded within. That means you’ll always be able to check if a piece of audio was created with Google’s AI by uploading it to Gemini, similar to the way you can check images and videos for SynthID tags. Google also says it has sought to create a music AI that respects copyright and partner agreements. If you name a specific artist in your prompt, Gemini won’t attempt to copy that artist’s sound. Instead, it’s trained to take that as “broad creative inspiration.” Although it also notes this process is not foolproof, and some of that original expression might imitate an artist too much. In those cases, Google invites users to report such shared content. Lyria 3 is going live in the Gemini web interface today and should be available in the mobile app within a few days. It works in English, German, Spanish, French, Hindi, Japanese, Korean, and Portuguese, but Google plans to add more languages soon. While all users will have some access to music generation, those with AI Pro and AI Ultra subscriptions will have higher usage limits, but the specifics are unclear. Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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[SOURCE: https://arstechnica.com/science/2026/02/microsofts-new-10000-year-data-storage-medium-glass/] | [TOKENS: 3335] |
Clear as glass Microsoft’s new 10,000-year data storage medium: glass Femtosecond lasers etch data into a very stable medium. John Timmer – Feb 18, 2026 2:01 pm | 201 Right now, Silica hardware isn't quite ready for commercialization. Credit: Microsoft Research Right now, Silica hardware isn't quite ready for commercialization. Credit: Microsoft Research Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav Archival storage poses lots of challenges. We want media that is extremely dense and stable for centuries or more, and, ideally, doesn’t consume any energy when not being accessed. Lots of ideas have floated around—even DNA has been considered—but one of the simplest is to cut the data into glass. Many forms of glass are very physically and chemically stable, and it’s relatively easy to create features in it. There’s been a lot of preliminary work demonstrating different aspects of a glass-based storage system. But in Wednesday’s issue of Nature, Microsoft Research announced Project Silica, a working demonstration of a system that can read and write data into small slabs of glass with a density of over a Gigabit per cubic millimeter. Writing on glass We tend to think of glass as fragile, prone to shattering, and capable of flowing downward over centuries, although the last claim is a myth. Glass is a category of material, and a variety of chemicals can form glasses. With the right starting chemical, it’s possible to make a glass that is, as the researchers put it, “thermally and chemically stable and is resistant to moisture ingress, temperature fluctuations and electromagnetic interference.” While it would still need to be handled in a way to minimize damage, glass provides the sort of stability we’d want for long-term storage. Putting data into glass is as simple as etching it (to be clear, this is technically not etching, which is a chemical modification of glass’ surface—here, lasers burn features into the interior of the glass). But that’s been one of the challenges, as the writing is typically a slow process. However, the development of femtosecond lasers—lasers that emit pulses that only last 10-15 seconds and can emit millions of them per second—can significantly cut down write times and allow etching to be focused on a very small area, increasing potential data density. To read the data back, there are several options. We’ve already had great success using lasers to read data from optical disks, albeit slowly. But anything that can pick up the small features etched into the glass could conceivably work. With the above considerations in mind, everything was in place on a theoretical level for Project Silica. The big question is how to put them together into a functional system. Microsoft decided that, just to be cautious, it would answer that question twice. A real-world system The difference between these two answers comes down to how an individual unit of data (called a voxel) is written to the glass. One type of voxel they tried was based on birefringence, where refraction of photons depends on their polarization. It’s possible to etch voxels into glass to create birefringence using polarized laser light, producing features smaller than the diffraction limit. In practice, this involved using one laser pulse to create an oval-shaped void, followed by a second, polarized pulse to induce birefringence. The identity of a voxel is based on the orientation of the oval; since we can resolve multiple orientations, it’s possible to save more than one bit in each voxel. The alternative approach involves changing the magnitude of refractive effects by varying the amount of energy in the laser pulse. Again, it’s possible to discern more than two states in these voxels, allowing multiple data bits to be stored in each voxel. The map data from Microsoft Flight Simulator etched onto the Silica storage medium. Credit: Microsoft Research The map data from Microsoft Flight Simulator etched onto the Silica storage medium. Credit: Microsoft Research Reading these in Silica involves using a microscope that can pick up differences in refractive index. (For microscopy geeks, this is a way of saying “they used phase contrast microscopy.”) The microscopy sets the limits on how many layers of voxels can be placed in a single piece of glass. During etching, the layers were separated by enough distance so only a single layer would be in the microscope’s plane of focus at a time. The etching process also incorporates symbols that allow the automated microscope system to position the lens above specific points on the glass. From there, the system slowly changes its focal plane, moving through the stack and capturing images that include different layers of voxels. To interpret these microscope images, Microsoft used a convolutional neural network that combines data from images that are both in and near the plane of focus for a given layer of voxels. This is effective because the influence of nearby voxels changes how a given voxel appears in a subtle way that the AI system can pick up on if given enough training data. The final piece of the puzzle is data encoding. The Silica system takes the raw bitstream of the data it’s storing and adds error correction using a low-density parity-check code (the same error correction used in 5G networks). Neighboring bits are then combined to create symbols that take advantage of the voxels’ ability to store more than one bit. Once a stream of symbols is made, it’s ready to be written to glass. Performance Writing remains a bottleneck in the system, so Microsoft developed hardware that can write a single glass slab with four lasers simultaneously without generating too much heat. That is enough to enable writing at 66 megabits per second, and the team behind the work thinks that it would be possible to add up to a dozen additional lasers. That may be needed, given that it’s possible to store up to 4.84TB in a single slab of glass (the slabs are 12 cm x 12 cm and 0.2 cm thick). That works out to be over 150 hours to fully write a slab. The “up to” aspect of the storage system has to do with the density of data that’s possible with the two different ways of writing data. The method that relies on birefringence requires more optical hardware and only works in high-quality glasses, but can squeeze more voxels into the same volume, and so has a considerably higher data density. The alternative approach can only put a bit over two terabytes into the same slab of glass, but can be done with simpler hardware and can work on any sort of transparent material. Borosilicate glass offers extreme stability; Microsoft’s accelerated aging experiments suggest the data would be stable for over 10,000 years at room temperature. That led Microsoft to declare, “Our results demonstrate that Silica could become the archival storage solution for the digital age.” That may be overselling it just a bit. The Square Kilometer Array telescope, for example, is expected to need to archive 700 petabytes of data each year. That would mean over 140,000 glass slabs would be needed to store the data from this one telescope. Even assuming that the write speed could be boosted by adding significantly more lasers, you’d need over 600 Silica machines operating in parallel to keep up. And the Square Kilometer Array is far from the only project generating enormous amounts of data. That said, there are some features that make Silica a great match for this sort of thing, most notably the complete absence of energy needed to preserve the data, and the fact that it can be retrieved rapidly if needed (a sharp contrast to the days needed to retrieve information from DNA, for example). Plus, I’m admittedly drawn to a system with a storage medium that looks like something right out of science fiction. Nature, 2026. DOI: 10.1038/s41586-025-10042-w (About DOIs). Correction: defined how etching is used here. John Timmer Senior Science Editor John Timmer Senior Science Editor John is Ars Technica's science editor. He has a Bachelor of Arts in Biochemistry from Columbia University, and a Ph.D. in Molecular and Cell Biology from the University of California, Berkeley. When physically separated from his keyboard, he tends to seek out a bicycle, or a scenic location for communing with his hiking boots. 201 Comments Microsoft’s new 10,000-year data storage medium: glass Femtosecond lasers etch data into a very stable medium. Archival storage poses lots of challenges. We want media that is extremely dense and stable for centuries or more, and, ideally, doesn’t consume any energy when not being accessed. Lots of ideas have floated around—even DNA has been considered—but one of the simplest is to cut the data into glass. Many forms of glass are very physically and chemically stable, and it’s relatively easy to create features in it. There’s been a lot of preliminary work demonstrating different aspects of a glass-based storage system. But in Wednesday’s issue of Nature, Microsoft Research announced Project Silica, a working demonstration of a system that can read and write data into small slabs of glass with a density of over a Gigabit per cubic millimeter. Writing on glass We tend to think of glass as fragile, prone to shattering, and capable of flowing downward over centuries, although the last claim is a myth. Glass is a category of material, and a variety of chemicals can form glasses. With the right starting chemical, it’s possible to make a glass that is, as the researchers put it, “thermally and chemically stable and is resistant to moisture ingress, temperature fluctuations and electromagnetic interference.” While it would still need to be handled in a way to minimize damage, glass provides the sort of stability we’d want for long-term storage. Putting data into glass is as simple as etching it (to be clear, this is technically not etching, which is a chemical modification of glass’ surface—here, lasers burn features into the interior of the glass). But that’s been one of the challenges, as the writing is typically a slow process. However, the development of femtosecond lasers—lasers that emit pulses that only last 10-15 seconds and can emit millions of them per second—can significantly cut down write times and allow etching to be focused on a very small area, increasing potential data density. To read the data back, there are several options. We’ve already had great success using lasers to read data from optical disks, albeit slowly. But anything that can pick up the small features etched into the glass could conceivably work. With the above considerations in mind, everything was in place on a theoretical level for Project Silica. The big question is how to put them together into a functional system. Microsoft decided that, just to be cautious, it would answer that question twice. A real-world system The difference between these two answers comes down to how an individual unit of data (called a voxel) is written to the glass. One type of voxel they tried was based on birefringence, where refraction of photons depends on their polarization. It’s possible to etch voxels into glass to create birefringence using polarized laser light, producing features smaller than the diffraction limit. In practice, this involved using one laser pulse to create an oval-shaped void, followed by a second, polarized pulse to induce birefringence. The identity of a voxel is based on the orientation of the oval; since we can resolve multiple orientations, it’s possible to save more than one bit in each voxel. The alternative approach involves changing the magnitude of refractive effects by varying the amount of energy in the laser pulse. Again, it’s possible to discern more than two states in these voxels, allowing multiple data bits to be stored in each voxel. Reading these in Silica involves using a microscope that can pick up differences in refractive index. (For microscopy geeks, this is a way of saying “they used phase contrast microscopy.”) The microscopy sets the limits on how many layers of voxels can be placed in a single piece of glass. During etching, the layers were separated by enough distance so only a single layer would be in the microscope’s plane of focus at a time. The etching process also incorporates symbols that allow the automated microscope system to position the lens above specific points on the glass. From there, the system slowly changes its focal plane, moving through the stack and capturing images that include different layers of voxels. To interpret these microscope images, Microsoft used a convolutional neural network that combines data from images that are both in and near the plane of focus for a given layer of voxels. This is effective because the influence of nearby voxels changes how a given voxel appears in a subtle way that the AI system can pick up on if given enough training data. The final piece of the puzzle is data encoding. The Silica system takes the raw bitstream of the data it’s storing and adds error correction using a low-density parity-check code (the same error correction used in 5G networks). Neighboring bits are then combined to create symbols that take advantage of the voxels’ ability to store more than one bit. Once a stream of symbols is made, it’s ready to be written to glass. Performance Writing remains a bottleneck in the system, so Microsoft developed hardware that can write a single glass slab with four lasers simultaneously without generating too much heat. That is enough to enable writing at 66 megabits per second, and the team behind the work thinks that it would be possible to add up to a dozen additional lasers. That may be needed, given that it’s possible to store up to 4.84TB in a single slab of glass (the slabs are 12 cm x 12 cm and 0.2 cm thick). That works out to be over 150 hours to fully write a slab. The “up to” aspect of the storage system has to do with the density of data that’s possible with the two different ways of writing data. The method that relies on birefringence requires more optical hardware and only works in high-quality glasses, but can squeeze more voxels into the same volume, and so has a considerably higher data density. The alternative approach can only put a bit over two terabytes into the same slab of glass, but can be done with simpler hardware and can work on any sort of transparent material. Borosilicate glass offers extreme stability; Microsoft’s accelerated aging experiments suggest the data would be stable for over 10,000 years at room temperature. That led Microsoft to declare, “Our results demonstrate that Silica could become the archival storage solution for the digital age.” That may be overselling it just a bit. The Square Kilometer Array telescope, for example, is expected to need to archive 700 petabytes of data each year. That would mean over 140,000 glass slabs would be needed to store the data from this one telescope. Even assuming that the write speed could be boosted by adding significantly more lasers, you’d need over 600 Silica machines operating in parallel to keep up. And the Square Kilometer Array is far from the only project generating enormous amounts of data. That said, there are some features that make Silica a great match for this sort of thing, most notably the complete absence of energy needed to preserve the data, and the fact that it can be retrieved rapidly if needed (a sharp contrast to the days needed to retrieve information from DNA, for example). Plus, I’m admittedly drawn to a system with a storage medium that looks like something right out of science fiction. Nature, 2026. DOI: 10.1038/s41586-025-10042-w (About DOIs). Correction: defined how etching is used here. Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is the trusted source in a sea of information. After all, you don’t need to know everything, only what’s important. |
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