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Gender bias is thus "hard-coded" into technology. Companies often cite research showing that customers want their digital assistants to sound like women, justifying the choice with the profit motive. However, research on the topic is mixed, with studies showing that in some contexts male choices may be preferred. For e... | Wikipedia - Gender digital divide - Female gendering of AI technologies > Digital assistants > Feminization of voice assistants | 173 | 920 | null |
Article: Generative AI Copyright Disclosure Act. The Generative AI Copyright Disclosure Act is a piece of legislation introduced by California Representative Adam Schiff in the United States Congress on April 9, 2024. It concerns the transparency of companies regarding their use of copyrighted work to train their gener... | Wikipedia - Generative AI Copyright Disclosure Act - Summary | 278 | 1,406 | null |
Article: Gödel machine. A Gödel machine is a hypothetical self-improving computer program that solves problems in an optimal way. It uses a recursive self-improvement protocol in which it rewrites its own code when it can prove the new code provides a better strategy. The machine was invented by Jürgen Schmidhuber (fir... | Wikipedia - Gödel machine - Summary | 225 | 1,126 | null |
Section: Variables of interest. There are three variables that are particularly useful in the run time of the Gödel machine. At some time t {\displaystyle t} , the variable time {\displaystyle {\text{time}}} will have the binary equivalent of t {\displaystyle t} . This is incremented steadily throughout the run time of... | Wikipedia - Gödel machine - Variables of interest | 236 | 912 | null |
At any given time t {\displaystyle t} , where ( 1 ≤ t ≤ T ) {\displaystyle (1\leq t\leq T)} , the goal is to maximize future success or utility. A typical utility function follows the pattern u ( s , E n v ) : S × E → R {\displaystyle u(s,\mathrm {Env} ):S\times E\rightarrow \mathbb {R} } : u ( s , E n v ) = E μ [ ∑ τ ... | Wikipedia - Gödel machine - Variables of interest | 386 | 1,149 | null |
A typical utility function follows the pattern u ( s , E n v ) : S × E → R {\displaystyle u(s,\mathrm {Env} ):S\times E\rightarrow \mathbb {R} } : u ( s , E n v ) = E μ [ ∑ τ = time T r ( τ ) ∣ s , E n v ] {\displaystyle u(s,\mathrm {Env} )=E_{\mu }{\Bigg [}\sum _{\tau ={\text{time}}}^{T}r(\tau )\mid s,\mathrm {Env} {\... | Wikipedia - Gödel machine - Variables of interest | 356 | 1,115 | null |
Section: Instructions used by proof techniques > get-axiom(n). Appends the n-th axiom as a theorem to the current theorem sequence. Below is the initial axiom scheme: Hardware Axioms formally specify how components of the machine could change from one cycle to the next. Reward Axioms define the computational cost of ha... | Wikipedia - Gödel machine - Instructions used by proof techniques > get-axiom(n) | 201 | 1,033 | null |
Section: Language. A GOLOG interpreter automatically maintains a direct characterization of the dynamic world being modeled, on the basis of user supplied axioms about preconditions, effects of actions and the initial state of the world. This allows the application to reason about the condition of the world and conside... | Wikipedia - GOLOG - Language | 283 | 1,560 | null |
Section: Planning and scripting. In contrast to the Planning Domain Definition Language, Golog supports planning and scripting as well. Planning means that a goal state in the world model is defined, and the solver brings a logical system into this state. Behavior scripting implements reactive procedures, which are run... | Wikipedia - GOLOG - Planning and scripting | 191 | 937 | null |
Section: History. It was announced during Google's "Made By Google" event on October 4, 2017. It was released for sale on January 27, 2018. With a flashing light emitting diode (LED) that indicates it is recording, Google Clips automatically captures video clips at moments its machine learning algorithms determine to b... | Wikipedia - Google Clips - History | 167 | 826 | null |
Article: Grammar systems theory. Grammar systems theory is a field of theoretical computer science that studies systems of finite collections of formal grammars generating a formal language. Each grammar works on a string, a so-called sequential form that represents an environment. Grammar systems can thus be used as a... | Wikipedia - Grammar systems theory - Summary | 338 | 1,196 | null |
The behavior of A {\displaystyle \mathbb {A} } is then described by this grammar. Suppose the A {\displaystyle \mathbb {A} } has a subsumption architecture; each component of this architecture can be then represented as a formal grammar, too, and the final behavior of the agent is then described by this system of gramm... | Wikipedia - Grammar systems theory - Summary | 306 | 1,512 | null |
Section: History > 1970s. Arcade system boards have used specialized graphics circuits since the 1970s. In early video game hardware, RAM for frame buffers was expensive, so video chips composited data together as the display was being scanned out on the monitor. A specialized barrel shifter circuit helped the CPU anim... | Wikipedia - Graphics processing unit - History > 1970s | 295 | 1,368 | null |
Section: History > 1980s. The NEC μPD7220 was the first implementation of a personal computer graphics display processor as a single large-scale integration (LSI) integrated circuit chip. This enabled the design of low-cost, high-performance video graphics cards such as those from Number Nine Visual Technology. It beca... | Wikipedia - Graphics processing unit - History > 1980s | 349 | 1,561 | null |
for per-scanline palette switches, sprite multiplexing, and hardware windowing), or driving the blitter. In 1986, Texas Instruments released the TMS34010, the first fully programmable graphics processor. It could run general-purpose code but also had a graphics-oriented instruction set. During 1990–1992, this chip beca... | Wikipedia - Graphics processing unit - History > 1980s | 324 | 1,475 | null |
Section: History > 1990s. In 1991, S3 Graphics introduced the S3 86C911, which its designers named after the Porsche 911 as an indication of the performance increase it promised. The 86C911 spawned a variety of imitators: by 1995, all major PC graphics chip makers had added 2D acceleration support to their chips. Fixed... | Wikipedia - Graphics processing unit - History > 1990s | 346 | 1,657 | null |
Another early example is the Super FX chip, a RISC-based on-cartridge graphics chip used in some SNES games, notably Doom and Star Fox. Some systems used DSPs to accelerate transformations. Fujitsu, which worked on the Sega Model 2 arcade system, began working on integrating T&L into a single LSI solution for use in ho... | Wikipedia - Graphics processing unit - History > 1990s | 343 | 1,579 | null |
However, as manufacturing technology continued to progress, video, 2D GUI acceleration, and 3D functionality were all integrated into one chip. Rendition's Verite chipsets were among the first to do this well. In 1997, Rendition collaborated with Hercules and Fujitsu on a "Thriller Conspiracy" project which combined a ... | Wikipedia - Graphics processing unit - History > 1990s | 346 | 1,673 | null |
In that era, OpenGL had no standard driver model for competing hardware accelerators to compete on the basis of support for higher level 3D texturing and lighting functionality. In 1994 Microsoft announced DirectX 1.0 and support for gaming in the forthcoming Windows 95 consumer OS. In 1995 Microsoft announced the acqu... | Wikipedia - Graphics processing unit - History > 1990s | 311 | 1,612 | null |
During this period the same Microsoft team responsible for Direct3D and OpenGL driver standardization introduced their own Microsoft 3D chip design called Talisman. Details of this era are documented extensively in the books "Game of X" v.1 and v.2 by Russel Demaria, "Renegades of the Empire" by Mike Drummond, "Opening... | Wikipedia - Graphics processing unit - History > 1990s | 151 | 692 | null |
Section: History > 2000s. NVIDIA released the GeForce 256, marketed as the world's first GPU, integrating transform and lighting engines for advanced 3D graphics rendering. Nvidia was first to produce a chip capable of programmable shading: the GeForce 3. Each pixel could now be processed by a short program that could ... | Wikipedia - Graphics processing unit - History > 2000s | 345 | 1,659 | null |
Pixel shading is often used for bump mapping, which adds texture to make an object look shiny, dull, rough, or even round or extruded. With the introduction of the Nvidia GeForce 8 series and new generic stream processing units, GPUs became more generalized computing devices. Parallel GPUs are making computational inro... | Wikipedia - Graphics processing unit - History > 2000s | 334 | 1,532 | null |
Section: History > 2010s. In 2010, Nvidia partnered with Audi to power their cars' dashboards, using the Tegra GPU to provide increased functionality to cars' navigation and entertainment systems. Advances in GPU technology in cars helped advance self-driving technology. AMD's Radeon HD 6000 series cards were released ... | Wikipedia - Graphics processing unit - History > 2010s | 349 | 1,563 | null |
They are made using the 16 nm manufacturing process which improves upon previous microarchitectures. Nvidia released one non-consumer card under the new Volta architecture, the Titan V. Changes from the Titan XP, Pascal's high-end card, include an increase in the number of CUDA cores, the addition of tensor cores, and ... | Wikipedia - Graphics processing unit - History > 2010s | 349 | 1,484 | null |
AMD unveiled the Radeon RX 6000 series, its RDNA 2 graphics cards with support for hardware-accelerated ray tracing. The product series, launched in late 2020, consisted of the RX 6800, RX 6800 XT, and RX 6900 XT. The RX 6700 XT, which is based on Navi 22, was launched in early 2021. The PlayStation 5 and Xbox Series X... | Wikipedia - Graphics processing unit - History > 2010s | 325 | 1,470 | null |
Section: Computational functions. Modern GPUs have traditionally used most of their transistors to do calculations related to 3D computer graphics. In addition to the 3D hardware, today's GPUs include basic 2D acceleration and framebuffer capabilities (usually with a VGA compatibility mode). Newer cards such as AMD/ATI... | Wikipedia - Graphics processing unit - Computational functions | 316 | 1,545 | null |
Section: Computational functions > GPU accelerated video decoding and encoding. Most GPUs made since 1995 support the YUV color space and hardware overlays, important for digital video playback, and many GPUs made since 2000 also support MPEG primitives such as motion compensation and iDCT. This hardware-accelerated vi... | Wikipedia - Graphics processing unit - Computational functions > GPU accelerated video decoding and encoding | 322 | 1,240 | null |
Section: Computational functions > GPU accelerated video decoding and encoding > Video decoding processes that can be accelerated. Video decoding processes that can be accelerated by modern GPU hardware are: Motion compensation (mocomp) Inverse discrete cosine transform (iDCT) Inverse telecine 3:2 and 2:2 pull-down cor... | Wikipedia - Graphics processing unit - Computational functions > GPU accelerated video decoding and encoding > Video decoding processes that can be accelerated | 172 | 837 | null |
Section: GPU forms > Terminology. In the 1970s, the term "GPU" originally stood for graphics processor unit and described a programmable processing unit working independently from the CPU that was responsible for graphics manipulation and output. In 1994, Sony used the term (now standing for graphics processing unit) i... | Wikipedia - Graphics processing unit - GPU forms > Terminology | 237 | 1,079 | null |
Section: GPU forms > Dedicated graphics processing unit. Dedicated graphics processing units uses RAM that is dedicated to the GPU rather than relying on the computer’s main system memory. This RAM is usually specially selected for the expected serial workload of the graphics card (see GDDR). Sometimes systems with ded... | Wikipedia - Graphics processing unit - GPU forms > Dedicated graphics processing unit | 305 | 1,496 | null |
A few graphics cards still use Peripheral Component Interconnect (PCI) slots, but their bandwidth is so limited that they are generally used only when a PCIe or AGP slot is not available. Technologies such as Scan-Line Interleave by 3dfx, SLI and NVLink by Nvidia and CrossFire by AMD allow multiple GPUs to draw images ... | Wikipedia - Graphics processing unit - GPU forms > Dedicated graphics processing unit | 215 | 891 | null |
Section: GPU forms > Integrated graphics processing unit. Integrated graphics processing units (IGPU), integrated graphics, shared graphics solutions, integrated graphics processors (IGP), or unified memory architectures (UMA) use a portion of a computer's system RAM rather than dedicated graphics memory. IGPs can be i... | Wikipedia - Graphics processing unit - GPU forms > Integrated graphics processing unit | 344 | 1,630 | null |
IGPs use system memory with bandwidth up to a current maximum of 128 GB/s, whereas a discrete graphics card may have a bandwidth of more than 1000 GB/s between its VRAM and GPU core. This memory bus bandwidth can limit the performance of the GPU, though multi-channel memory can mitigate this deficiency. Older integrate... | Wikipedia - Graphics processing unit - GPU forms > Integrated graphics processing unit | 225 | 1,120 | null |
Section: GPU forms > Stream processing and general purpose GPUs (GPGPU). It is common to use a general purpose graphics processing unit (GPGPU) as a modified form of stream processor (or a vector processor), running compute kernels. This turns the massive computational power of a modern graphics accelerator's shader pi... | Wikipedia - Graphics processing unit - GPU forms > Stream processing and general purpose GPUs (GPGPU) | 344 | 1,683 | null |
These allow functions called compute kernels to run on the GPU's stream processors. This makes it possible for C programs to take advantage of a GPU's ability to operate on large buffers in parallel, while still using the CPU when appropriate. CUDA was the first API to allow CPU-based applications to directly access th... | Wikipedia - Graphics processing unit - GPU forms > Stream processing and general purpose GPUs (GPGPU) | 242 | 1,319 | null |
Section: GPU forms > External GPU (eGPU). An external GPU is a graphics processor located outside of the housing of the computer, similar to a large external hard drive. External graphics processors are sometimes used with laptop computers. Laptops might have a substantial amount of RAM and a sufficiently powerful cent... | Wikipedia - Graphics processing unit - GPU forms > External GPU (eGPU) | 275 | 1,194 | null |
Section: Overview. A human-built system with complex behavior is often organized as a hierarchy. For example, a command hierarchy has among its notable features the organizational chart of superiors, subordinates, and lines of organizational communication. Hierarchical control systems are organized similarly to divide ... | Wikipedia - Hierarchical control system - Overview | 305 | 1,721 | null |
Section: Applications > Manufacturing, robotics and vehicles. Among the robotic paradigms is the hierarchical paradigm in which a robot operates in a top-down fashion, heavy on planning, especially motion planning. Computer-aided production engineering has been a research focus at NIST since the 1980s. Its Automated Ma... | Wikipedia - Hierarchical control system - Applications > Manufacturing, robotics and vehicles | 201 | 1,077 | null |
Section: Applications > Artificial intelligence. Subsumption architecture is a methodology for developing artificial intelligence that is heavily associated with behavior based robotics. This architecture is a way of decomposing complicated intelligent behavior into many "simple" behavior modules, which are in turn org... | Wikipedia - Hierarchical control system - Applications > Artificial intelligence | 345 | 1,923 | null |
Section: History > Founding and early history. The company was founded by Mark Newman in 2004, then a 20-year-old undergraduate at Westminster College. Newman also served as the company's chief executive officer (CEO). The company is headquartered in South Jordan, Utah, near Salt Lake City. An artificial intelligence c... | Wikipedia - HireVue - History > Founding and early history | 321 | 1,553 | null |
Section: History > Use of artificial intelligence and company growth. In 2013, the company began using artificial intelligence to screen interviewees. Both proprietary voice recognition software and licensed facial recognition software are used by HireVue's Insights program. The company's HireVue Insights program scans... | Wikipedia - HireVue - History > Use of artificial intelligence and company growth | 326 | 1,605 | null |
The company's chief technology officer (CTO) Loren Larsen stated the company experimented with giving candidates limited and unlimited attempts to answer interview questions before moving onto the next, with HireVue ultimately opting to provide unlimited attempts to candidates. Several concerns about HireVue's facial a... | Wikipedia - HireVue - History > Use of artificial intelligence and company growth | 264 | 1,340 | null |
Section: Reception. HireVue's service has received some criticism from interview candidates and AI researchers, particularly for its analysis of "micro-expressions". Commentary on its perceived drawbacks and potential to incite anxiety in interviewees has also been made. In 2015, Fortune writer Katherine Reynolds Lewis... | Wikipedia - HireVue - Reception | 318 | 1,584 | null |
Bloomberg News' Rebecca Greenfield wrote that "with a video interview, human resources staff members only have to review the answers, and can do so on their own schedule, without having to travel for on-campus recruiting," with all this saving money for companies. CNBC's Tonya Riley wrote that HireVue and similar compa... | Wikipedia - HireVue - Reception | 263 | 1,196 | null |
Section: Legal challenges. In November 2019, the Electronic Privacy Information Center filed a complaint to the Federal Trade Commission alleging that HireVue's software caused harm to American workers through its collection of biometric data, bias towards those with different genders, races, sexual orientations and "n... | Wikipedia - HireVue - Legal challenges | 224 | 1,172 | null |
Article: Histogram of oriented displacements. Histogram of oriented displacements (HOD) is a 2D trajectory descriptor. The trajectory is described using a histogram of the directions between each two consecutive points. Given a trajectory T = {P1, P2, P3, ..., Pn}, where Pt is the 2D position at time t. For each pair o... | Wikipedia - Histogram of oriented displacements - Summary | 330 | 1,394 | null |
Article: Hybrid intelligent system. Hybrid intelligent system denotes a software system which employs, in parallel, a combination of methods and techniques from artificial intelligence subfields, such as: Neuro-symbolic systems Neuro-fuzzy systems Hybrid connectionist-symbolic models Fuzzy expert systems Connectionist ... | Wikipedia - Hybrid intelligent system - Summary | 280 | 1,564 | null |
Article: Incremental heuristic search. Incremental heuristic search algorithms combine both incremental and heuristic search to speed up searches of sequences of similar search problems, which is important in domains that are only incompletely known or change dynamically. Incremental search has been studied at least si... | Wikipedia - Incremental heuristic search - Summary | 299 | 1,513 | null |
Section: History. The portal was launched on 30 May 2020, by Ravi Shankar Prasad, the Union Minister for Electronics and IT, Law and Justice and Communications, on the first anniversary of the second tenure of Prime Minister Narendra Modi-led government. A national program for the youth, 'Responsible AI for Youth', was... | Wikipedia - INDIAai - History | 231 | 1,043 | null |
Article: Information space analysis. Within the field of information science, information space analysis is a deterministic method, enhanced by machine intelligence, for locating and assessing resources for team-centric efforts. Organizations need to be able to quickly assemble teams backed by the support services, inf... | Wikipedia - Information space analysis - Summary | 248 | 1,398 | null |
Article: Intelligent agent. In artificial intelligence, an intelligent agent is an entity that perceives its environment, takes actions autonomously to achieve goals, and may improve its performance through machine learning or by acquiring knowledge. Leading AI textbooks define artificial intelligence as the "study and... | Wikipedia - Intelligent agent - Summary | 338 | 1,911 | null |
Section: Intelligent agents as the foundation of AI. The concept of intelligent agents provides a foundational lens through which to define and understand artificial intelligence. For instance, the influential textbook Artificial Intelligence: A Modern Approach (Russell & Norvig) describes: Agent: Anything that perceiv... | Wikipedia - Intelligent agent - Intelligent agents as the foundation of AI | 350 | 1,786 | null |
Section: Objective function. An objective function (or goal function) specifies the goals of an intelligent agent. An agent is deemed more intelligent if it consistently selects actions that yield outcomes better aligned with its objective function. In effect, the objective function serves as a measure of success. The ... | Wikipedia - Intelligent agent - Objective function | 339 | 1,792 | null |
In evolutionary systems, a "fitness function" determines which agents are more likely to reproduce. This is analogous to natural selection, where organisms evolve to maximize their chances of survival and reproduction. Some AI systems, such as nearest-neighbor, reason by analogy rather than being explicitly goal-driven... | Wikipedia - Intelligent agent - Objective function | 340 | 1,770 | null |
Sometimes, instead of setting the reward function directly equal to the desired benchmark evaluation function, machine learning programmers use reward shaping to initially give the machine rewards for incremental progress. Yann LeCun stated in 2018, "Most of the learning algorithms that people have come up with essenti... | Wikipedia - Intelligent agent - Objective function | 202 | 1,060 | null |
Section: Agent function. An intelligent agent's behavior can be described mathematically by an agent function. This function determines what the agent does based on what it has seen. A percept refers to the agent's sensory inputs at a single point in time. For example, a self-driving car's percepts might include camera... | Wikipedia - Intelligent agent - Agent function | 350 | 1,533 | null |
Section: Classes of intelligent agents > Russell and Norvig's classification > Simple reflex agents. Simple reflex agents act only on the basis of the current percept, ignoring the rest of the percept history. The agent function is based on the condition-action rule: "if condition, then action". This agent function onl... | Wikipedia - Intelligent agent - Classes of intelligent agents > Russell and Norvig's classification > Simple reflex agents | 173 | 855 | null |
Section: Classes of intelligent agents > Russell and Norvig's classification > Model-based reflex agents. A model-based agent can handle partially observable environments. Its current state is stored inside the agent, maintaining a structure that describes the part of the world which cannot be seen. This knowledge abou... | Wikipedia - Intelligent agent - Classes of intelligent agents > Russell and Norvig's classification > Model-based reflex agents | 178 | 874 | null |
Section: Classes of intelligent agents > Russell and Norvig's classification > Utility-based agents. Goal-based agents only distinguish between goal states and non-goal states. It is also possible to define a measure of how desirable a particular state is. This measure can be obtained through the use of a utility funct... | Wikipedia - Intelligent agent - Classes of intelligent agents > Russell and Norvig's classification > Utility-based agents | 197 | 991 | null |
Section: Classes of intelligent agents > Russell and Norvig's classification > Learning agents. Learning lets agents begin in unknown environments and gradually surpass the bounds of their initial knowledge. A key distinction in such agents is the separation between a "learning element," responsible for improving perfo... | Wikipedia - Intelligent agent - Classes of intelligent agents > Russell and Norvig's classification > Learning agents | 152 | 830 | null |
Section: Alternative definitions and uses. "Intelligent agent" is also often used as a vague term, sometimes synonymous with "virtual personal assistant". Some 20th-century definitions characterize an agent as a program that aids a user or that acts on behalf of a user. These examples are known as software agents, and ... | Wikipedia - Intelligent agent - Alternative definitions and uses | 190 | 947 | null |
Section: Alternative definitions and uses > Agentic AI. In the context of generative artificial intelligence, AI agents (also referred to as compound AI systems) are a class of intelligent agents distinguished by their ability to operate autonomously in complex environments. Agentic AI tools prioritize decision-making ... | Wikipedia - Intelligent agent - Alternative definitions and uses > Agentic AI | 341 | 1,681 | null |
Software frameworks for addressing agent reliability include AgentSpec, ToolEmu, GuardAgent, Agentic Evaluations, and predictive models from H2O.ai. In February 2025, Hugging Face released Open Deep Research, an open source version of OpenAI Deep Research. Hugging Face also released a free web browser agent, similar to... | Wikipedia - Intelligent agent - Alternative definitions and uses > Agentic AI | 192 | 955 | null |
Section: Alternative definitions and uses > Agentic AI > Concerns. Potential concerns include issues of liability, an increased risk of cybercrime, ethical challenges, as well as problems related to AI safety and AI alignment. Other issues involve data privacy. Additional challenges include weakened human oversight, al... | Wikipedia - Intelligent agent - Alternative definitions and uses > Agentic AI > Concerns | 291 | 1,489 | null |
Yoshua Bengio warned at the 2025 World Economic Forum that "all of the catastrophic scenarios with AGI or superintelligence happen if we have agents". In March 2025, Scale AI signed a contract with the United States Department of Defense to work with them, in collaboration with Anduril Industries and Microsoft, to deve... | Wikipedia - Intelligent agent - Alternative definitions and uses > Agentic AI > Concerns | 209 | 1,083 | null |
Section: Applications. The concept of agent-based modeling for self-driving cars was discussed as early as 2003. Hallerbach et al. explored the use of agent-based approaches for developing and validating automated driving systems. Their method involved a digital twin of the vehicle under test and microscopic traffic si... | Wikipedia - Intelligent agent - Applications | 170 | 950 | null |
Section: Overview > Neural network controller. Neural networks have been used to solve problems in almost all spheres of science and technology. Neural network control basically involves two steps: System identification Control It has been shown that a feedforward network with nonlinear, continuous and differentiable a... | Wikipedia - Intelligent control - Overview > Neural network controller | 256 | 1,430 | null |
Article: Intelligent database. Until the 1980s, databases were viewed as computer systems that stored record-oriented and business data such as manufacturing inventories, bank records, and sales transactions. A database system was not expected to merge numeric data with text, images, or multimedia information, nor was ... | Wikipedia - Intelligent database - Summary | 297 | 1,609 | null |
Article: Intelligent decision support system. An intelligent decision support system (IDSS) is a decision support system that makes extensive use of artificial intelligence (AI) techniques. Use of AI techniques in management information systems has a long history – indeed terms such as "Knowledge-based systems" (KBS) a... | Wikipedia - Intelligent decision support system - Summary | 341 | 1,933 | null |
Accuracy and consistency can be comparable to (or even exceed) that of human experts when the decision parameters are well known (e.g. if a common disease is being diagnosed), but performance can be poor when novel or uncertain circumstances arise. Research in AI focused on enabling systems to respond to novelty and un... | Wikipedia - Intelligent decision support system - Summary | 235 | 1,328 | null |
Article: Intelligent word recognition. Intelligent Word Recognition, or IWR, is the recognition of unconstrained handwritten words. IWR recognizes entire handwritten words or phrases instead of character-by-character, like its predecessor, optical character recognition (OCR). IWR technology matches handwritten or print... | Wikipedia - Intelligent word recognition - Summary | 302 | 1,480 | null |
Section: Origins in psychology. The study of intrinsic motivation in psychology and neuroscience began in the 1950s with some psychologists explaining exploration through drives to manipulate and explore, however, this homeostatic view was criticised by White. An alternative explanation from Berlyne in 1960 was the pur... | Wikipedia - Intrinsic motivation (artificial intelligence) - Origins in psychology | 150 | 811 | null |
Section: Types of models > Information-theoretic intrinsic motivation. The quantification of prediction and novelty to drive behaviour is generally enabled through the application of information-theoretic models, where agent state and strategy (policy) over time are represented by probability distributions describing a... | Wikipedia - Intrinsic motivation (artificial intelligence) - Types of models > Information-theoretic intrinsic motivation | 171 | 986 | null |
Section: Intrinsically Motivated Learning. Intrinsically motivated (or curiosity-driven) learning is an emerging research topic in artificial intelligence and developmental robotics that aims to develop agents that can learn general skills or behaviours, that can be deployed to improve performance in extrinsic tasks, s... | Wikipedia - Intrinsic motivation (artificial intelligence) - Intrinsically Motivated Learning | 239 | 1,340 | null |
Section: Background. Rapid progress in AI technology, constituting an AI boom, was brought to widespread public attention in the early 2020s by text-to-image models such as DALL-E, Midjourney, and Stable Diffusion, which were able to generate complex images that convincingly resembled human-made artworks. The prolifera... | Wikipedia - Is This What We Want? - Background | 288 | 1,542 | null |
Article: Joint Artificial Intelligence Center. The Joint Artificial Intelligence Center (JAIC) (pronounced "jake") was an American organization on exploring the usage of Artificial Intelligence (AI) (particularly Edge computing), Network of Networks and AI-enhanced communication for use in actual combat. In February 20... | Wikipedia - Joint Artificial Intelligence Center - Summary | 168 | 873 | null |
Section: History. JAIC was originally proposed to Congress on June 27, 2018; that same month, it was established under the Defense Department's chief information officer (CIO), itself subordinate to the Office of the Secretary of Defense (OSD), to coordinate Department-wide AI efforts. Throughout 2020, JAIC started fin... | Wikipedia - Joint Artificial Intelligence Center - History | 245 | 1,238 | null |
Section: Successor. The first Chief Digital and Artificial Intelligence Office (CDAO) or Chief Digital and Artificial Intelligence Officer was Dr. Craig H. Martell. USAF secretary Frank Kendall has signalled that the CDAO will have an approach to solving the DoD-wide Joint All-Domain Command and Control (JADC2) problem... | Wikipedia - Joint Artificial Intelligence Center - Successor | 183 | 839 | null |
Section: Successor > GIDEs. On 30 January 2023 the CDAO announced a series of global information dominance experiments (GIDEs). GIDE 5 is being held 30 January — 3 February 2023 (Monday—Thursday) at the Pentagon, and at multiple combatant commands (and therefore across the global information grid for JADC2). The experi... | Wikipedia - Joint Artificial Intelligence Center - Successor > GIDEs | 279 | 1,190 | null |
Article: K-line (artificial intelligence). A K-line, or Knowledge-line, is a mental agent which represents an association of a group of other mental agents found active when a subject solves a certain problem or formulates a new idea. These were first described in Marvin Minsky's essay K-lines: A Theory of Memory, publ... | Wikipedia - K-line (artificial intelligence) - Summary | 272 | 1,134 | null |
Article: Knowledge level. In artificial intelligence, knowledge-based agents draw on a pool of logical sentences to infer conclusions about the world. At the knowledge level, we only need to specify what the agent knows and what its goals are; a logical abstraction separate from details of implementation. This notion o... | Wikipedia - Knowledge level - Summary | 235 | 1,241 | null |
Section: Background. Knowledge-based configuration (of complex products and services) has a long history as an artificial intelligence application area, see, e.g. Informally, configuration can be defined as a "special case of design activity, where the artifact being configured is assembled from instances of a fixed se... | Wikipedia - Knowledge-based configuration - Background | 162 | 894 | null |
Section: Configuration systems. Configuration systems, also referred to as configurators or mass customization toolkits, are one of the most successfully applied artificial intelligence technologies. Examples are the automotive industry, the telecommunication industry, the computer industry, and power electric transfor... | Wikipedia - Knowledge-based configuration - Configuration systems | 293 | 1,725 | null |
Section: Configuration process. Core configuration, i.e., guiding the user and checking the consistency of user requirements with the knowledge base, solution presentation and translation of configuration results into bill of materials (BOM) are major tasks to be supported by a configurator. Configuration knowledge bas... | Wikipedia - Knowledge-based configuration - Configuration process | 153 | 901 | null |
Section: Item domains. Knowledge-based recommender systems are well suited to complex domains where items are not purchased very often, such as apartments and cars. Further examples of item domains relevant for knowledge-based recommender systems are financial services, digital cameras, and tourist destinations. Rating... | Wikipedia - Knowledge-based recommender system - Item domains | 160 | 879 | null |
Section: Navigation-based recommendation. In a navigation-based recommender, user feedback is typically provided in terms of "critiques" which specify change requests regarding the item currently recommended to the user. Critiques are then used for the recommendation of the next "candidate" item. An example of a critiq... | Wikipedia - Knowledge-based recommender system - Navigation-based recommendation | 181 | 917 | null |
Section: Components. The knowledge base contains domain-specific facts and rules about a problem domain (rather than knowledge implicitly embedded in procedural code, as in a conventional computer program). In addition, the knowledge may be structured by means of a subsumption ontology, frames, conceptual graph, or log... | Wikipedia - Knowledge-based systems - Components | 151 | 818 | null |
Section: Aspects and development of early systems > Knowledge-based vs. expert systems. The term "knowledge-based system" was often used interchangeably with "expert system", possibly because almost all of the earliest knowledge-based systems were designed for expert tasks. However, these terms tell us about different ... | Wikipedia - Knowledge-based systems - Aspects and development of early systems > Knowledge-based vs. expert systems | 151 | 802 | null |
Section: Aspects and development of early systems > Rule-based systems. The first knowledge-based systems were primarily rule-based expert systems. These represented facts about the world as simple assertions in a flat database and used domain-specific rules to reason about these assertions, and then to add to them. On... | Wikipedia - Knowledge-based systems - Aspects and development of early systems > Rule-based systems | 209 | 1,169 | null |
Section: Aspects and development of early systems > Meta-reasoning. Later architectures for knowledge-based reasoning, such as the BB1 blackboard architecture (a blackboard system), allowed the reasoning process itself to be affected by new inferences, providing meta-level reasoning. BB1 allowed the problem-solving pro... | Wikipedia - Knowledge-based systems - Aspects and development of early systems > Meta-reasoning | 164 | 779 | null |
Section: Aspects and development of early systems > Advances driven by enhanced architecture. As knowledge-based systems became more complex, the techniques used to represent the knowledge base became more sophisticated and included logic, term-rewriting systems, conceptual graphs, and frames. Frames, for example, are ... | Wikipedia - Knowledge-based systems - Aspects and development of early systems > Advances driven by enhanced architecture | 150 | 839 | null |
Section: Aspects and development of early systems > Advances in automated reasoning. Another advancement in the 1990s was the development of special purpose automated reasoning systems called classifiers. Rather than statically declare the subsumption relations in a knowledge-base, a classifier allows the developer to ... | Wikipedia - Knowledge-based systems - Aspects and development of early systems > Advances in automated reasoning | 189 | 1,004 | null |
Section: History. LangChain was launched in October 2022 as an open source project by Harrison Chase, while working at machine learning startup Robust Intelligence. The project quickly garnered popularity, with improvements from hundreds of contributors on GitHub, trending discussions on Twitter, lively activity on the... | Wikipedia - LangChain - History | 192 | 913 | null |
Section: Capabilities. LangChain's developers highlight the framework's applicability to use-cases including chatbots, retrieval-augmented generation, document summarization, and synthetic data generation. As of March 2023, LangChain included integrations with systems including Amazon, Google, and Microsoft Azure cloud... | Wikipedia - LangChain - Capabilities | 346 | 1,621 | null |
As of March 2023, LangChain included integrations with systems including Amazon, Google, and Microsoft Azure cloud storage; API wrappers for news, movie information, and weather; Bash for summarization, syntax and semantics checking, and execution of shell scripts; multiple web scraping subsystems and templates; few-sh... | Wikipedia - LangChain - Capabilities | 324 | 1,496 | null |
Section: Overview. As part of a reflection published in 2006, Terry Winograd describes the language-action perspective as resting on two key orienting principles: The first is its focus on linguistic communication as the basis for understanding what occurs in information systems. Ultimately all information is communica... | Wikipedia - Language/action perspective - Overview | 346 | 1,845 | null |
Section: Applications. Insights from related work have been applied over the past two decades. At the LAP 2004 - Conference, Kalle Lyytinen discussed the academic/theoretic success of LAP. Yet, these LAP successes have not found entry into the wider stream of applications. In a sense, LAP is now peripheral to computer ... | Wikipedia - Language/action perspective - Applications | 175 | 852 | null |
Section: Description > Start distance estimates. LPA* maintains two estimates of the start distance g*(n) for each node: g(n), the previously calculated g-value (start distance) as in A* rhs(n), a lookahead value based on the g-values of the node's predecessors (the minimum of all g(n' ) + d(n' , n), where n' is a pred... | Wikipedia - Lifelong Planning A* - Description > Start distance estimates | 227 | 802 | null |
Section: Description > Priority queue. When a node becomes locally inconsistent (because the cost of its predecessor or the edge linking it to a predecessor has changed), it is placed in a priority queue for re-evaluation. LPA* uses a two-dimensional key: k ( n ) = [ k 1 ( n ) k 2 ( n ) ] = [ min ( g ( n ) , r h s ( n ... | Wikipedia - Lifelong Planning A* - Description > Priority queue | 240 | 621 | null |
Section: Description > Node expansion. The top node in the queue is expanded as follows: If the rhs-value of a node equals its g-value, the node is locally consistent and is removed from the queue. If the rhs-value of a node is less than its g-value (known as a locally overconsistent node), the g-value is changed to ma... | Wikipedia - Lifelong Planning A* - Description > Node expansion | 273 | 1,162 | null |
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