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Section: Sequential Decisions Based on Algorithmic Probability > The AIXI Model. The AIXI model is the centerpiece of Hutter’s theory. It describes a universal artificial agent designed to maximize expected rewards in an unknown environment. AIXI operates under the assumption that the environment can be represented by ... | Wikipedia - Algorithmic probability - Sequential Decisions Based on Algorithmic Probability > The AIXI Model | 159 | 882 | null |
Section: Details. ARC's mission is to ensure that powerful machine learning systems of the future are designed and developed safely and for the benefit of humanity. It was founded in April 2021 by Paul Christiano and other researchers focused on the theoretical challenges of AI alignment. They attempt to develop scalab... | Wikipedia - Alignment Research Center - Details | 317 | 1,450 | null |
Section: Definitions. Given an initial problem P0 and set of problem solving methods of the form: P if P1 and … and Pn the associated and–or tree is a set of labelled nodes such that: The root of the tree is a node labelled by P0. For every node N labelled by a problem or sub-problem P and for every method of the form ... | Wikipedia - And–or tree - Definitions | 239 | 914 | null |
Section: Relationship with two-player games. And–or trees can also be used to represent the search spaces for two-person games. The root node of such a tree represents the problem of one of the players winning the game, starting from the initial state of the game. Given a node N, labelled by the problem P of the player... | Wikipedia - And–or tree - Relationship with two-player games | 212 | 957 | null |
Section: Abstract argumentation frameworks > Formal framework. Abstract argumentation frameworks, also called argumentation frameworks à la Dung, are defined formally as a pair: A set of abstract elements called arguments, denoted A {\displaystyle A} A binary relation on A {\displaystyle A} , called attack relation, de... | Wikipedia - Argumentation framework - Abstract argumentation frameworks > Formal framework | 265 | 836 | null |
Abstract argumentation frameworks, also called argumentation frameworks à la Dung, are defined formally as a pair: A set of abstract elements called arguments, denoted A {\displaystyle A} A binary relation on A {\displaystyle A} , called attack relation, denoted R {\displaystyle R} For instance, the argumentation syste... | Wikipedia - Argumentation framework - Abstract argumentation frameworks > Formal framework | 494 | 1,502 | null |
Section: Abstract argumentation frameworks > Different semantics of acceptance > Extensions. To decide if an argument can be accepted or not, or if several arguments can be accepted together, Dung defines several semantics of acceptance that allows, given an argumentation system, sets of arguments (called extensions) t... | Wikipedia - Argumentation framework - Abstract argumentation frameworks > Different semantics of acceptance > Extensions | 345 | 1,333 | null |
For instance, given S = ⟨ A , R ⟩ {\displaystyle S=\langle A,R\rangle } , E {\displaystyle E} is a complete extension of S {\displaystyle S} only if it is an admissible set and every acceptable argument with respect to E {\displaystyle E} belongs to E {\displaystyle E} , E {\displaystyle E} is a preferred extension of ... | Wikipedia - Argumentation framework - Abstract argumentation frameworks > Different semantics of acceptance > Extensions | 438 | 1,524 | null |
There exists some inclusions between the sets of extensions built with these semantics : Every stable extension is preferred, Every preferred extension is complete, The grounded extension is complete, If the system is well-founded (there exists no infinite sequence a 0 , a 1 , … , a n , … {\displaystyle a_{0},a_{1},\do... | Wikipedia - Argumentation framework - Abstract argumentation frameworks > Different semantics of acceptance > Extensions | 316 | 1,048 | null |
Section: Abstract argumentation frameworks > Different semantics of acceptance > Labellings. Labellings are a more expressive way than extensions to express the acceptance of the arguments. Concretely, a labelling is a mapping that associates every argument with a label in (the argument is accepted), out (the argument ... | Wikipedia - Argumentation framework - Abstract argumentation frameworks > Different semantics of acceptance > Labellings | 160 | 675 | null |
L {\displaystyle L} is a reinstatement labelling on the system S = ⟨ A , R ⟩ {\displaystyle S=\langle A,R\rangle } if and only if : ∀ a ∈ A , L ( a ) = i n {\displaystyle \forall a\in A,L(a)={\mathit {in}}} if and only if ∀ b ∈ A {\displaystyle \forall b\in A} such that ( b , a ) ∈ R , L ( b ) = o u t {\displaystyle (b... | Wikipedia - Argumentation framework - Abstract argumentation frameworks > Different semantics of acceptance > Labellings | 347 | 784 | null |
{\mathit {out}}} One can convert every extension into a reinstatement labelling: the arguments of the extension are in, those attacked by an argument of the extension are out, and the others are undec. Conversely, one can build an extension from a reinstatement labelling just by keeping the arguments in. Indeed, Camina... | Wikipedia - Argumentation framework - Abstract argumentation frameworks > Different semantics of acceptance > Labellings | 313 | 1,172 | null |
Section: Abstract argumentation frameworks > Inference from an argumentation system. In the general case when several extensions are computed for a given semantic σ {\displaystyle \sigma } , the agent that reasons from the system can use several mechanisms to infer information: Credulous inference: the agent accepts an... | Wikipedia - Argumentation framework - Abstract argumentation frameworks > Inference from an argumentation system | 315 | 1,358 | null |
For these two methods to infer information, one can identify the set of accepted arguments, respectively C r σ ( S ) {\displaystyle Cr_{\sigma }(S)} the set of the arguments credulously accepted under the semantic σ {\displaystyle \sigma } , and S c σ ( S ) {\displaystyle Sc_{\sigma }(S)} the set of arguments accepted ... | Wikipedia - Argumentation framework - Abstract argumentation frameworks > Inference from an argumentation system | 239 | 1,020 | null |
Formally, given a semantic σ {\displaystyle \sigma } : E Q 1 {\displaystyle {\mathit {EQ_{1}}}} : two argumentation frameworks are equivalent if they have the same set of σ {\displaystyle \sigma } -extensions, that is S 1 ≡ 1 S 2 ⇔ E x t σ ( S 1 ) = E x t σ ( S 2 ) {\displaystyle S_{1}\equiv _{1}S_{2}\Leftrightarrow Ex... | Wikipedia - Argumentation framework - Abstract argumentation frameworks > Equivalence between argumentation frameworks | 339 | 856 | null |
_{3}S_{2}\Leftrightarrow Cr_{\sigma }(S_{1})=Cr_{\sigma }(S_{2})} . The strong equivalence says that two systems S 1 {\displaystyle S_{1}} and S 2 {\displaystyle S_{2}} are equivalent if and only if for all other system S 3 {\displaystyle S_{3}} , the union of S 1 {\displaystyle S_{1}} with S 3 {\displaystyle S_{3}} is... | Wikipedia - Argumentation framework - Abstract argumentation frameworks > Equivalence between argumentation frameworks | 164 | 431 | null |
Section: Other kinds > Logic-based argumentation frameworks. In the case of logic-based argumentation frameworks, an argument is not an abstract entity, but a pair, where the first part is a minimal consistent set of formulae enough to prove the formula for the second part of the argument. Formally, an argument is a pa... | Wikipedia - Argumentation framework - Other kinds > Logic-based argumentation frameworks | 263 | 997 | null |
For instance, Relation defeater : ( Ψ , β ) {\displaystyle (\Psi ,\beta )} attacks ( Φ , α ) {\displaystyle (\Phi ,\alpha )} if and only if β ⊢ ¬ ( ϕ 1 ∧ ⋯ ∧ ϕ n ) {\displaystyle \beta \vdash \neg (\phi _{1}\wedge \dots \wedge \phi _{n})} for { ϕ 1 , … , ϕ n } ⊆ Φ {\displaystyle \{\phi _{1},\dots ,\phi _{n}\}\subseteq ... | Wikipedia - Argumentation framework - Other kinds > Logic-based argumentation frameworks | 350 | 919 | null |
Section: Other kinds > Value-based argumentation frameworks. The value-based argumentation frameworks come from the idea that during an exchange of arguments, some can be stronger than others with respect to a certain value they advance, and so the success of an attack between arguments depends on the difference of the... | Wikipedia - Argumentation framework - Other kinds > Value-based argumentation frameworks | 275 | 993 | null |
Formally, a value-based argumentation framework is a tuple V A F = ⟨ A , R , V , val , valprefs ⟩ {\displaystyle VAF=\langle A,R,V,{\textit {val}},{\textit {valprefs}}\rangle } with A {\displaystyle A} and R {\displaystyle R} similar to the standard framework (a set of arguments and a binary relation on this set), V {\... | Wikipedia - Argumentation framework - Other kinds > Value-based argumentation frameworks | 366 | 1,121 | null |
In this framework, an argument a {\displaystyle a} defeats another argument b {\displaystyle b} if and only if a {\displaystyle a} attacks b {\displaystyle b} in the "standard" meaning: ( a , b ) ∈ R {\displaystyle (a,b)\in R} ; and ( val ( b ) , v a l ( a ) ) ∉ valprefs {\displaystyle ({\textit {val}}(b),val(a))\not \... | Wikipedia - Argumentation framework - Other kinds > Value-based argumentation frameworks | 182 | 608 | null |
Formally, an assumption-based argumentation framework is a tuple ⟨ L , R , A , ␣ ¯ ⟩ {\displaystyle \langle {\mathcal {L}},{\mathcal {R}},{\mathcal {A}},{\overline {\mathrm {\textvisiblespace} }}\rangle } , where ⟨ L , R ⟩ {\displaystyle \langle {\mathcal {L}},{\mathcal {R}}\rangle } is a deductive system, where L {\di... | Wikipedia - Argumentation framework - Other kinds > Assumption-based argumentation frameworks | 349 | 872 | null |
{\displaystyle {\mathcal {A}}} to L {\displaystyle {\mathcal {L}}} , where a ¯ {\displaystyle {\overline {a}}} is defined as the contrary of a {\displaystyle a} . As a consequence of defining an ABA, an argument can be represented in a tree-form. Formally, given a deductive system ⟨ L , R ⟩ {\displaystyle \langle {\mat... | Wikipedia - Argumentation framework - Other kinds > Assumption-based argumentation frameworks | 325 | 995 | null |
. . , s m {\displaystyle l_{N}\leftarrow s_{1},...,s_{m}} , ( m ≥ 0 ) {\displaystyle (m\geq 0)} , where l N {\displaystyle l_{N}} is the label of N {\displaystyle N} and If m = 0 {\displaystyle m=0} , then the rule shall be l N ← τ {\displaystyle l_{N}\leftarrow \tau } (i.e. child of N {\displaystyle N} is τ {\displays... | Wikipedia - Argumentation framework - Other kinds > Assumption-based argumentation frameworks | 250 | 686 | null |
Article: Artificial brain. An artificial brain (or artificial mind) is software and hardware with cognitive abilities similar to those of the animal or human brain. Research investigating "artificial brains" and brain emulation plays three important roles in science: An ongoing attempt by neuroscientists to understand ... | Wikipedia - Artificial brain - Summary | 347 | 1,841 | null |
Section: Approaches to brain simulation. Although direct human brain emulation using artificial neural networks on a high-performance computing engine is a commonly discussed approach, there are other approaches. An alternative artificial brain implementation could be based on Holographic Neural Technology (HNeT) non l... | Wikipedia - Artificial brain - Approaches to brain simulation | 330 | 1,789 | null |
Spaun's design recreates elements of human brain anatomy. The model, consisting of approximately 2.5 million neurons, includes features of the visual and motor cortices, GABAergic and dopaminergic connections, the ventral tegmental area (VTA), substantia nigra, and others. The design allows for several functions in res... | Wikipedia - Artificial brain - Approaches to brain simulation | 230 | 1,125 | null |
Article: Artificial consciousness. Artificial consciousness, also known as machine consciousness, synthetic consciousness, or digital consciousness, is the consciousness hypothesized to be possible in artificial intelligence. It is also the corresponding field of study, which draws insights from philosophy of mind, phi... | Wikipedia - Artificial consciousness - Summary | 206 | 1,089 | null |
Section: Philosophical views > Plausibility debate. Type-identity theorists and other skeptics hold the view that consciousness can be realized only in particular physical systems because consciousness has properties that necessarily depend on physical constitution. In his 2001 article "Artificial Consciousness: Utopia... | Wikipedia - Artificial consciousness - Philosophical views > Plausibility debate | 190 | 955 | null |
Section: Philosophical views > Plausibility debate > Thought experiments. David Chalmers proposed two thought experiments intending to demonstrate that "functionally isomorphic" systems (those with the same "fine-grained functional organization", i.e., the same information processing) will have qualitatively identical ... | Wikipedia - Artificial consciousness - Philosophical views > Plausibility debate > Thought experiments | 336 | 1,754 | null |
Section: Philosophical views > Plausibility debate > In large language models. In 2022, Google engineer Blake Lemoine made a viral claim that Google's LaMDA chatbot was sentient. Lemoine supplied as evidence the chatbot's humanlike answers to many of his questions; however, the chatbot's behavior was judged by the scie... | Wikipedia - Artificial consciousness - Philosophical views > Plausibility debate > In large language models | 337 | 1,598 | null |
Section: Philosophical views > Testing. Qualia, or phenomenological consciousness, is an inherently first-person phenomenon. Because of that, and the lack of an empirical definition of sentience, directly measuring it may be impossible. Although systems may display numerous behaviors correlated with sentience, determin... | Wikipedia - Artificial consciousness - Philosophical views > Testing | 333 | 1,741 | null |
Section: Philosophical views > Ethics. If it were suspected that a particular machine was conscious, its rights would be an ethical issue that would need to be assessed (e.g. what rights it would have under law). For example, a conscious computer that was owned and used as a tool or central computer within a larger mac... | Wikipedia - Artificial consciousness - Philosophical views > Ethics | 321 | 1,742 | null |
Section: Aspects of consciousness. Bernard Baars and others argue there are various aspects of consciousness necessary for a machine to be artificially conscious. The functions of consciousness suggested by Baars are: definition and context setting, adaptation and learning, editing, flagging and debugging, recruiting a... | Wikipedia - Artificial consciousness - Aspects of consciousness | 206 | 1,069 | null |
Section: Aspects of consciousness > Awareness. Awareness could be one required aspect, but there are many problems with the exact definition of awareness. The results of the experiments of neuroscanning on monkeys suggest that a process, not only a state or object, activates neurons. Awareness includes creating and tes... | Wikipedia - Artificial consciousness - Aspects of consciousness > Awareness | 251 | 1,313 | null |
Section: Aspects of consciousness > Anticipation. The ability to predict (or anticipate) foreseeable events is considered important for artificial intelligence by Igor Aleksander. The emergentist multiple drafts principle proposed by Daniel Dennett in Consciousness Explained may be useful for prediction: it involves th... | Wikipedia - Artificial consciousness - Aspects of consciousness > Anticipation | 272 | 1,499 | null |
Section: Functionalist theories of consciousness. Functionalism is a theory that defines mental states by their functional roles (their causal relationships to sensory inputs, other mental states, and behavioral outputs), rather than by their physical composition. According to this view, what makes something a particul... | Wikipedia - Artificial consciousness - Functionalist theories of consciousness | 183 | 1,055 | null |
Section: Functionalist theories of consciousness > Global workspace theory. This theory analogizes the mind to a theater, with conscious thought being like material illuminated on the main stage. The brain contains many specialized processes or modules (such as those for vision, language, or memory) that operate in par... | Wikipedia - Artificial consciousness - Functionalist theories of consciousness > Global workspace theory | 153 | 869 | null |
Section: Functionalist theories of consciousness > Attention schema theory. In 2011, Michael Graziano and Sabine Kastler published a paper named "Human consciousness and its relationship to social neuroscience: A novel hypothesis" proposing a theory of consciousness as an attention schema. Graziano went on to publish a... | Wikipedia - Artificial consciousness - Functionalist theories of consciousness > Attention schema theory | 275 | 1,434 | null |
Section: Implementation proposals > Connectionist > Haikonen's cognitive architecture. Pentti Haikonen considers classical rule-based computing inadequate for achieving AC: "the brain is definitely not a computer. Thinking is not an execution of programmed strings of commands. The brain is not a numerical calculator ei... | Wikipedia - Artificial consciousness - Implementation proposals > Connectionist > Haikonen's cognitive architecture | 284 | 1,562 | null |
Section: Implementation proposals > Connectionist > Creativity Machine. Stephen Thaler proposed a possible connection between consciousness and creativity in his 1994 patent, called "Device for the Autonomous Generation of Useful Information" (DAGUI), or the so-called "Creativity Machine", in which computational critic... | Wikipedia - Artificial consciousness - Implementation proposals > Connectionist > Creativity Machine | 170 | 978 | null |
Section: In fiction. In 2001: A Space Odyssey, the spaceship's sentient supercomputer, HAL 9000 was instructed to conceal the true purpose of the mission from the crew. This directive conflicted with HAL's programming to provide accurate information, leading to cognitive dissonance. When it learns that crew members int... | Wikipedia - Artificial consciousness - In fiction | 346 | 1,656 | null |
Article: Artificial general intelligence. Artificial general intelligence (AGI)—sometimes called human‑level intelligence AI—is a type of artificial intelligence that would match or surpass human capabilities across virtually all cognitive tasks. Some researchers argue that state‑of‑the‑art large language models alread... | Wikipedia - Artificial general intelligence - Summary | 345 | 1,739 | null |
Section: Terminology. AGI is also known as strong AI, full AI, human-level AI, human-level intelligent AI, or general intelligent action. Some academic sources reserve the term "strong AI" for computer programs that will experience sentience or consciousness. In contrast, weak AI (or narrow AI) is able to solve one spe... | Wikipedia - Artificial general intelligence - Terminology | 342 | 1,628 | null |
Section: Characteristics > Intelligence traits. Researchers generally hold that a system is required to do all of the following to be regarded as an AGI: reason, use strategy, solve puzzles, and make judgments under uncertainty represent knowledge, including common sense knowledge plan learn communicate in natural lang... | Wikipedia - Artificial general intelligence - Characteristics > Intelligence traits | 156 | 905 | null |
Section: Characteristics > Physical traits. Other capabilities are considered desirable in intelligent systems, as they may affect intelligence or aid in its expression. These include: the ability to sense (e.g. see, hear, etc.), and the ability to act (e.g. move and manipulate objects, change location to explore, etc.... | Wikipedia - Artificial general intelligence - Characteristics > Physical traits | 311 | 1,476 | null |
Section: Characteristics > Tests for human-level AGI. Several tests meant to confirm human-level AGI have been considered, including: The Turing Test (Turing) Proposed by Alan Turing in his 1950 paper "Computing Machinery and Intelligence", this test involves a human judge engaging in natural language conversations wit... | Wikipedia - Artificial general intelligence - Characteristics > Tests for human-level AGI | 325 | 1,577 | null |
In 2023, it was claimed that "AI is closer to ever" to passing the Turing test, though the article's authors reinforced that imitation (as "large language models" ever closer to passing the test are built upon) is not synonymous with "intelligence". Further, as AI intelligence and human intelligence may differ, "passin... | Wikipedia - Artificial general intelligence - Characteristics > Tests for human-level AGI | 342 | 1,600 | null |
Section: Characteristics > AI-complete problems. A problem is informally called "AI-complete" or "AI-hard" if it is believed that in order to solve it, one would need to implement AGI, because the solution is beyond the capabilities of a purpose-specific algorithm. There are many problems that have been conjectured to ... | Wikipedia - Artificial general intelligence - Characteristics > AI-complete problems | 213 | 1,113 | null |
Section: History > Classical AI. Modern AI research began in the mid-1950s. The first generation of AI researchers were convinced that artificial general intelligence was possible and that it would exist in just a few decades. AI pioneer Herbert A. Simon wrote in 1965: "machines will be capable, within twenty years, of... | Wikipedia - Artificial general intelligence - History > Classical AI | 330 | 1,628 | null |
Section: History > Narrow AI research. In the 1990s and early 21st century, mainstream AI achieved commercial success and academic respectability by focusing on specific sub-problems where AI can produce verifiable results and commercial applications, such as speech recognition and recommendation algorithms. These "app... | Wikipedia - Artificial general intelligence - History > Narrow AI research | 322 | 1,702 | null |
Section: History > Modern artificial general intelligence research. The term "artificial general intelligence" was used as early as 1997, by Mark Gubrud in a discussion of the implications of fully automated military production and operations. A mathematical formalism of AGI was proposed by Marcus Hutter in 2000. Named... | Wikipedia - Artificial general intelligence - History > Modern artificial general intelligence research | 305 | 1,477 | null |
Section: History > Feasibility. As of 2023, the development and potential achievement of AGI remains a subject of intense debate within the AI community. While traditional consensus held that AGI was a distant goal, recent advancements have led some researchers and industry figures to claim that early forms of AGI may ... | Wikipedia - Artificial general intelligence - History > Feasibility | 336 | 1,788 | null |
John McCarthy is among those who believe human-level AI will be accomplished, but that the present level of progress is such that a date cannot accurately be predicted. AI experts' views on the feasibility of AGI wax and wane. Four polls conducted in 2012 and 2013 suggested that the median estimate among experts for wh... | Wikipedia - Artificial general intelligence - History > Feasibility | 336 | 1,556 | null |
Blaise Agüera y Arcas and Peter Norvig wrote in 2023 that a significant level of general intelligence has already been achieved with frontier models. They wrote that reluctance to this view comes from four main reasons: a "healthy skepticism about metrics for AGI", an "ideological commitment to alternative AI theories ... | Wikipedia - Artificial general intelligence - History > Feasibility | 336 | 1,557 | null |
An OpenAI employee, Vahid Kazemi, claimed in 2024 that the company had achieved AGI, stating, "In my opinion, we have already achieved AGI and it's even more clear with O1." Kazemi clarified that while the AI is not yet "better than any human at any task", it is "better than most humans at most tasks." He also addresse... | Wikipedia - Artificial general intelligence - History > Feasibility | 213 | 983 | null |
Section: History > Timescales. Progress in artificial intelligence has historically gone through periods of rapid progress separated by periods when progress appeared to stop. Ending each hiatus were fundamental advances in hardware, software or both to create space for further progress. For example, the computer hardw... | Wikipedia - Artificial general intelligence - History > Timescales | 329 | 1,595 | null |
AlexNet was regarded as the initial ground-breaker of the current deep learning wave. In 2017, researchers Feng Liu, Yong Shi, and Ying Liu conducted intelligence tests on publicly available and freely accessible weak AI such as Google AI, Apple's Siri, and others. At the maximum, these AIs reached an IQ value of about... | Wikipedia - Artificial general intelligence - History > Timescales | 329 | 1,519 | null |
In 2023, Microsoft Research published a study on an early version of OpenAI's GPT-4, contending that it exhibited more general intelligence than previous AI models and demonstrated human-level performance in tasks spanning multiple domains, such as mathematics, coding, and law. This research sparked a debate on whether... | Wikipedia - Artificial general intelligence - History > Timescales | 320 | 1,460 | null |
Section: Whole brain emulation. While the development of transformer models like in ChatGPT is considered the most promising path to AGI, whole brain emulation can serve as an alternative approach. With whole brain simulation, a brain model is built by scanning and mapping a biological brain in detail, and then copying... | Wikipedia - Artificial general intelligence - Whole brain emulation | 206 | 1,075 | null |
Section: Whole brain emulation > Early estimates. For low-level brain simulation, a very powerful cluster of computers or GPUs would be required, given the enormous quantity of synapses within the human brain. Each of the 1011 (one hundred billion) neurons has on average 7,000 synaptic connections (synapses) to other n... | Wikipedia - Artificial general intelligence - Whole brain emulation > Early estimates | 303 | 1,302 | null |
Section: Whole brain emulation > Criticisms of simulation-based approaches. The artificial neuron model assumed by Kurzweil and used in many current artificial neural network implementations is simple compared with biological neurons. A brain simulation would likely have to capture the detailed cellular behaviour of bi... | Wikipedia - Artificial general intelligence - Whole brain emulation > Criticisms of simulation-based approaches | 229 | 1,223 | null |
Section: Philosophical perspective > "Strong AI" as defined in philosophy. In 1980, philosopher John Searle coined the term "strong AI" as part of his Chinese room argument. He proposed a distinction between two hypotheses about artificial intelligence: Strong AI hypothesis: An artificial intelligence system can have "... | Wikipedia - Artificial general intelligence - Philosophical perspective > "Strong AI" as defined in philosophy | 341 | 1,609 | null |
Section: Philosophical perspective > Consciousness. Consciousness can have various meanings, and some aspects play significant roles in science fiction and the ethics of artificial intelligence: Sentience (or "phenomenal consciousness"): The ability to "feel" perceptions or emotions subjectively, as opposed to the abil... | Wikipedia - Artificial general intelligence - Philosophical perspective > Consciousness | 343 | 1,602 | null |
This is opposed to simply being the "subject of one's thought"—an operating system or debugger is able to be "aware of itself" (that is, to represent itself in the same way it represents everything else)—but this is not what people typically mean when they use the term "self-awareness". In some advanced AI models, syst... | Wikipedia - Artificial general intelligence - Philosophical perspective > Consciousness | 172 | 879 | null |
Section: Benefits. AGI could improve productivity and efficiency in most jobs. For example, in public health, AGI could accelerate medical research, notably against cancer. It could take care of the elderly, and democratize access to rapid, high-quality medical diagnostics. It could offer fun, cheap and personalized ed... | Wikipedia - Artificial general intelligence - Benefits | 212 | 1,067 | null |
Section: Benefits > Advancements in medicine and healthcare. AGI would improve healthcare by making medical diagnostics faster, cheaper, and more accurate. AI-driven systems can analyse patient data and detect diseases at an early stage. This means patients will get diagnosed quicker and be able to seek medical attenti... | Wikipedia - Artificial general intelligence - Benefits > Advancements in medicine and healthcare | 223 | 1,218 | null |
Section: Benefits > Mitigating global crises. AGI could play a crucial role in preventing and managing global threats. It could help governments and organizations predict and respond to natural disasters more effectively, using real-time data analysis to forecast hurricanes, earthquakes, and pandemics. By analyzing vas... | Wikipedia - Artificial general intelligence - Benefits > Mitigating global crises | 206 | 1,130 | null |
Section: Risks > Existential risks. AGI may represent multiple types of existential risk, which are risks that threaten "the premature extinction of Earth-originating intelligent life or the permanent and drastic destruction of its potential for desirable future development". The risk of human extinction from AGI has b... | Wikipedia - Artificial general intelligence - Risks > Existential risks | 258 | 1,324 | null |
Section: Risks > Existential risks > Risk of loss of control and human extinction. The thesis that AI poses an existential risk for humans, and that this risk needs more attention, is controversial but has been endorsed in 2023 by many public figures, AI researchers and CEOs of AI companies such as Elon Musk, Bill Gate... | Wikipedia - Artificial general intelligence - Risks > Existential risks > Risk of loss of control and human extinction | 349 | 1,611 | null |
He said that people won't be "smart enough to design super-intelligent machines, yet ridiculously stupid to the point of giving it moronic objectives with no safeguards". On the other side, the concept of instrumental convergence suggests that almost whatever their goals, intelligent agents will have reasons to try to ... | Wikipedia - Artificial general intelligence - Risks > Existential risks > Risk of loss of control and human extinction | 332 | 1,673 | null |
Skeptics sometimes charge that the thesis is crypto-religious, with an irrational belief in the possibility of superintelligence replacing an irrational belief in an omnipotent God. Some researchers believe that the communication campaigns on AI existential risk by certain AI groups (such as OpenAI, Anthropic, DeepMind... | Wikipedia - Artificial general intelligence - Risks > Existential risks > Risk of loss of control and human extinction | 154 | 718 | null |
Section: Risks > Mass unemployment. Researchers from OpenAI estimated that "80% of the U.S. workforce could have at least 10% of their work tasks affected by the introduction of LLMs, while around 19% of workers may see at least 50% of their tasks impacted". They consider office workers to be the most exposed, for exam... | Wikipedia - Artificial general intelligence - Risks > Mass unemployment | 213 | 1,058 | null |
Article: Artificial intelligence and copyright. In the 2020s, the rapid advancement of deep learning-based generative artificial intelligence models raised questions about whether copyright infringement occurs when such are trained or used. This includes text-to-image models such as Stable Diffusion and large language ... | Wikipedia - Artificial intelligence and copyright - Summary | 189 | 1,024 | null |
Section: Copyright status of AI-generated works > United States. In the U.S., the Copyright Act protects "original works of authorship". The U.S. Copyright Office has interpreted this as being limited to works "created by a human being", declining to grant copyright to works generated without human intervention. Some l... | Wikipedia - Artificial intelligence and copyright - Copyright status of AI-generated works > United States | 339 | 1,682 | null |
For works using AI tools, the Copyright Office has made the test a different one i.e. whether there is no more than de minimis technological involvement. This difference in approach can be seen in the recent decision in respect of a registration claim by Jason Matthew Allen for his work Théâtre D'opéra Spatial created ... | Wikipedia - Artificial intelligence and copyright - Copyright status of AI-generated works > United States | 326 | 1,688 | null |
These technologies "train" on vast quantities of preexisting human-authored works and use inferences from that training to generate new content. Some systems operate in response to a user's textual instruction, called a "prompt." The resulting output may be textual, visual, or audio, and is determined by the AI based o... | Wikipedia - Artificial intelligence and copyright - Copyright status of AI-generated works > United States | 344 | 1,823 | null |
The U.S. Patent and Trademark Office (USPTO) similarly codified restrictions on the patentability of patents credits solely to AI authors in February 2024, following an August 2023 ruling in the case Thaler v. Perlmutter. In this case, the Patent Office denied grant to patents created by Stephen Thaler's AI program, DA... | Wikipedia - Artificial intelligence and copyright - Copyright status of AI-generated works > United States | 236 | 1,172 | null |
Section: Copyright status of AI-generated works > United Kingdom. Other jurisdictions include explicit statutory language related to computer-generated works, including the United Kingdom's Copyright, Designs and Patents Act 1988, which states: In the case of a literary, dramatic, musical or artistic work which is comp... | Wikipedia - Artificial intelligence and copyright - Copyright status of AI-generated works > United Kingdom | 342 | 1,819 | null |
Section: Training AI with copyrighted data. Deep learning models source large data sets from the Internet such as publicly available images and the text of web pages. The text and images are then converted into numeric formats the AI can analyze. A deep learning model identifies patterns linking the encoded text and im... | Wikipedia - Artificial intelligence and copyright - Training AI with copyrighted data | 170 | 925 | null |
Section: Training AI with copyrighted data > United States. U.S. machine learning developers have traditionally believed this to be allowable under fair use because using copyrighted work is transformative, and limited. The situation has been compared to Google Books's scanning of copyrighted books in Authors Guild, In... | Wikipedia - Artificial intelligence and copyright - Training AI with copyrighted data > United States | 323 | 1,572 | null |
Thomson Reuters argued that Ross Intelligence had used their Westlaw headnotes, brief summaries of court decisions, to train their AI engine designed to compete with Westlaw. While Thomson Reuters' claims were initially denied by judge Stephanos Bibas of the Third Circuit on the basis that headnotes may not have been c... | Wikipedia - Artificial intelligence and copyright - Training AI with copyrighted data > United States | 331 | 1,568 | null |
Section: Training AI with copyrighted data > EU. In the EU, such text and data mining (TDM) exceptions form part of the 2019 Directive on Copyright in the Digital Single Market. They are specifically referred to in the EU's AI Act (which came into force in 2024), which "is widely seen as a clear indication of the EU le... | Wikipedia - Artificial intelligence and copyright - Training AI with copyrighted data > EU | 244 | 1,156 | null |
Section: Training AI with copyrighted data > India. Indian copyright law provides fair use exceptions for scientific research, but lacks specific provisions for commercial AI training models. Unlike the EU and UK, India has not established TDM provisions that explicitly address commercial AI systems. This regulatory un... | Wikipedia - Artificial intelligence and copyright - Training AI with copyrighted data > India | 152 | 846 | null |
Section: Copyright infringing AI outputs. In some cases, deep learning models may replicate items in their training set when generating output. This behaviour is generally considered an undesired overfitting of a model by AI developers, and has in previous generations of AI been considered a manageable problem. Memoriz... | Wikipedia - Artificial intelligence and copyright - Copyright infringing AI outputs | 316 | 1,532 | null |
and other jurisdictions, an AI may also produce infringing content in the form of novel works which incorporate fictional characters. A generative image model such as Stable Diffusion is able to model the stylistic characteristics of an artist like Pablo Picasso (including his particular brush strokes, use of colour, p... | Wikipedia - Artificial intelligence and copyright - Copyright infringing AI outputs | 239 | 1,133 | null |
Section: Litigation. A November 2022 class action lawsuit against Microsoft, GitHub and OpenAI alleged that GitHub Copilot, an AI-powered code editing tool trained on public GitHub repositories, violated the copyright of the repositories' authors, noting that the tool was able to generate source code which matched its ... | Wikipedia - Artificial intelligence and copyright - Litigation | 312 | 1,502 | null |
Judge Orrick later dismissed all but one claim, that of copyright infringement towards Stability AI, in October 2023. However, after refiling on some of the eliminated claims, Orrick agreed in August 2024 to include some of these additional claims against the AI companies, which included both copyright and trademark in... | Wikipedia - Artificial intelligence and copyright - Litigation | 350 | 1,688 | null |
The two suits against OpenAI were combined (during which Awad left the suit) and by February 2024, Judge Araceli Martínez-Olguín of the Northern District of California threw out all but one claim related to the use of the author's copyrighted works as part of the training data for the AI model. The New York Times has s... | Wikipedia - Artificial intelligence and copyright - Litigation | 341 | 1,778 | null |
In September 2024, the Regional Court of Hamburg dismissed a German photographer's lawsuit against the non-profit organization LAION for unauthorized reproduction of his copyrighted work while creating a dataset for AI training. The decision was described as a "landmark ruling on TDM exceptions for AI training data" in... | Wikipedia - Artificial intelligence and copyright - Litigation | 173 | 879 | null |
Section: Usage by country > India > 2024 elections. In the 2024 Indian general election, politicians used deepfakes in their campaign materials. These deepfakes included politicians who had died prior to the election. Mathuvel Karunanidhi's party posted with his likeness even though he had died 2018. A video The All-In... | Wikipedia - Artificial intelligence and elections - Usage by country > India > 2024 elections | 158 | 745 | null |
Section: Usage by country > South Africa > 2024 elections. In the 2024 South African general election, there were several uses of AI content: i) A deepfaked video of Joe Biden emerged on social media showing him saying that "The U.S. would place sanctions on SA and declare it an enemy state if the African National Cong... | Wikipedia - Artificial intelligence and elections - Usage by country > South Africa > 2024 elections | 173 | 719 | null |
Section: Usage by country > Taiwan > 2024 elections. AI-generated content was used during the 2024 Taiwanese presidential election. Among the media were: i) A deepfake video of General Secretary of the Chinese Communist Party Xi Jinping which showed him supporting the presidential elections. Created on social media, th... | Wikipedia - Artificial intelligence and elections - Usage by country > Taiwan > 2024 elections | 151 | 743 | null |
Section: Usage by country > United Kingdom > 2024 elections. The Centre for Emerging Technology and Security provided a report on the threat of AI to the 2024 UK general election. The reports' findings said that the impact of AI was limited but may damage the democratic system. In the run up to the UK 2024 general elec... | Wikipedia - Artificial intelligence and elections - Usage by country > United Kingdom > 2024 elections | 214 | 990 | null |
Section: Usage by country > United States > 2024 elections. Officials from the ODNI and FBI have stated that Russia, Iran, and China used generative artificial intelligence tools to create fake and divisive text, photos, video, and audio content to foster anti-Americanism and engage in covert influence campaigns. The u... | Wikipedia - Artificial intelligence and elections - Usage by country > United States > 2024 elections | 235 | 1,236 | null |
Section: AI use in election interference by foreign governments. AI has begun to be used in election interference by foreign governments. Governments thought to be using AI to interfere in external elections include Russia, Iran and China. Russia was thought to be the most prolific nation targeting the 2024 presidentia... | Wikipedia - Artificial intelligence and elections - AI use in election interference by foreign governments | 308 | 1,577 | null |
Section: Ethics of AI use in political campaigning. As the use of AI and its associated tools in political campaigning and messaging increases, many ethical concerns have been raised. Campaigns have used AI in a number of ways, including speech writing, fundraising, voter behaviour prediction, fake robocalls and the ge... | Wikipedia - Artificial intelligence and elections - Ethics of AI use in political campaigning | 349 | 1,801 | null |
Article: Artificial intelligence arms race. A military artificial intelligence arms race is an economic and military competition between two or more states to develop and deploy advanced AI technologies and lethal autonomous weapons systems (LAWS). The goal is to gain a strategic or tactical advantage over rivals, simi... | Wikipedia - Artificial intelligence arms race - Summary | 239 | 1,304 | null |
Section: History. In 2014, AI specialist Steve Omohundro warned that "An autonomous weapons arms race is already taking place". According to Siemens, worldwide military spending on robotics was US$5.1 billion in 2010 and US$7.5 billion in 2015. China became a top player in artificial intelligence research in the 2010s.... | Wikipedia - Artificial intelligence arms race - History | 174 | 860 | null |
Section: Risks. One risk concerns the AI race itself, whether or not the race is won by any one group. There are strong incentives for development teams to cut corners with regard to the safety of the system, increasing the risk of critical failures and unintended consequences. This is in part due to the perceived adva... | Wikipedia - Artificial intelligence arms race - Risks | 308 | 1,528 | null |
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