Opšta veštačka inteligencija

Opšta veštačka inteligencija (AGI) is a type of artificial intelligence (AI) that can perform as well or better than humans on a wide range of cognitive tasks, as opposed to narrow AI, which is designed for specific tasks. It is one of various definitions of strong AI.

Creating AGI is a primary goal of AI research and of companies such as OpenAI, DeepMind, and Anthropic. A 2020 survey identified 72 active AGI R&D projects spread across 37 countries.

The timeline for AGI development remains a subject of ongoing debate among researchers and experts. Ажурирано: 2023., some argue that it may be possible in years or decades; others maintain it might take a century or longer; and a minority believe it may never be achieved. There is debate on the exact definition of AGI, and regarding whether modern large language models (LLMs) such as GPT-4 are early, incomplete forms of AGI. AGI is a common topic in science fiction and futures studies.

Contention exists over the potential for AGI to pose a threat to humanity; for example, OpenAI claims to treat it as an existential risk, while others find the development of AGI to be too remote to present a risk.

Terminologija

AGI is also known as strong AI, full AI, human-level AI or general intelligent action. However, some academic sources reserve the term "strong AI" for computer programs that experience sentience or consciousness. In contrast, weak AI (or narrow AI) is able to solve one specific problem, but lacks general cognitive abilities. Some academic sources use "weak AI" to refer more broadly to any programs that neither experience consciousness nor have a mind in the same sense as humans.

Related concepts include artificial superintelligence and transformative AI. An artificial superintelligence (ASI) is a hypothetical type of AGI that is much more generally intelligent than humans, while the notion of transformative AI relates to AI having a large impact on society, for example, similar to the agricultural or industrial revolution.

Literatura

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• Hanna, Alex, and Emily M. Bender, "Theoretical AI Harms Are a Distraction: Fearmongering about artificial intelligence's potential to end humanity shrouds the real harm it already causes", Scientific American, vol 330, no. 2 (February 2024), pp. 69–70. "[H]ype [about "existential risks"] surrounds many AI firms, but their technology already enables myriad harms, including... discrimination in housing, criminal justice, and health care, as well as the spread of hate speech and misinformation... Large language models extrude... fluent... coherent-seeming text but have no understanding of what the text means, let alone the ability to reason.... (p. 69.) [T]hat output... becomes a noxious... insidious pollutant of our information ecosystem.... [T]oo many... publications [about] AI come from corporate labs or... academic groups that receive... industry funding. Many of these publications are based on junk science [that] is nonreproducible... is full of hype, and uses evaluation methods that do not measure what they purport to... Meanwhile 'AI doomers' cite this junk science... to [misdirect] attention [to] the fantasy of all-powerful machines possibly going rogue and destroying humanity." (p. 70.)
• Hughes-Castleberry, Kenna, "A Murder Mystery Puzzle: The literary puzzle Cain's Jawbone, which has stumped humans for decades, reveals the limitations of natural-language-processing algorithms", Scientific American, vol. 329, no. 4 (November 2023), pp. 81–82. "This murder mystery competition has revealed that although NLP (natural-language processing) models are capable of incredible feats, their abilities are very much limited by the amount of context they receive. This [...] could cause [difficulties] for researchers who hope to use them to do things such as analyze ancient languages. In some cases, there are few historical records on long-gone civilizations to serve as training data for such a purpose." (p. 82.)
• Immerwahr, Daniel, "Your Lying Eyes: People now use A.I. to generate fake videos indistinguishable from real ones. How much does it matter?", The New Yorker, 20 November 2023, pp. 54–59. "If by 'deepfakes' we mean realistic videos produced using artificial intelligence that actually deceive people, then they barely exist. The fakes aren't deep, and the deeps aren't fake. [...] A.I.-generated videos are not, in general, operating in our media as counterfeited evidence. Their role better resembles that of cartoons, especially smutty ones." (p. 59.)
• Marcus, Gary, "Am I Human?: Researchers need new ways to distinguish artificial intelligence from the natural kind", Scientific American, vol. 316, no. 3 (March 2017), pp. 61–63. Marcus points out a so far insuperable stumbling block to artificial intelligence: an incapacity for reliable disambiguation. "[V]irtually every sentence [that people generate] is ambiguous, often in multiple ways. Our brain is so good at comprehending language that we do not usually notice." A prominent example is the "pronoun disambiguation problem" ("PDP"): a machine has no way of determining to whom or what a pronoun in a sentence—such as "he", "she" or "it"—refers.
• Marcus, Gary, "Artificial Confidence: Even the newest, buzziest systems of artificial general intelligence are stymmied by the same old problems", Scientific American, vol. 327, no. 4 (October 2022), pp. 42–45.
• Press, Eyal, "In Front of Their Faces: Does facial-recognition technology lead police to ignore contradictory evidence?", The New Yorker, 20 November 2023, pp. 20–26.
• Roivainen, Eka, "AI's IQ: ChatGPT aced a [standard intelligence] test but showed that intelligence cannot be measured by IQ alone", Scientific American, vol. 329, no. 1 (July/August 2023), p. 7. "Despite its high IQ, ChatGPT fails at tasks that require real humanlike reasoning or an understanding of the physical and social world.... ChatGPT seemed unable to reason logically and tried to rely on its vast database of... facts derived from online texts."

Spoljašnje veze

• The AGI portal maintained by Pei Wang