Question

Artificial general intelligence (AGI) is a kind of synthetic intelligence (AI) that matches or surpasses human cognitive capabilities throughout a wide variety of cognitive jobs. This contrasts with narrow AI, which is restricted to specific jobs. [1] Artificial superintelligence (ASI), on the other hand, refers to AGI that considerably goes beyond human cognitive abilities. AGI is considered among the definitions of strong AI.

Creating AGI is a main goal of AI research study and of business such as OpenAI [2] and Meta. [3] A 2020 study recognized 72 active AGI research study and advancement tasks throughout 37 countries. [4]

The timeline for attaining AGI remains a subject of continuous debate among researchers and professionals. As of 2023, some argue that it might be possible in years or years; others keep it might take a century or accc.rcec.sinica.edu.tw longer; a minority think it may never be accomplished; and another minority claims that it is already here. [5] [6] Notable AI scientist Geoffrey Hinton has expressed issues about the rapid development towards AGI, recommending it might be accomplished earlier than many anticipate. [7]

There is debate on the exact definition of AGI and relating to whether contemporary big language models (LLMs) such as GPT-4 are early types of AGI. [8] AGI is a common subject in science fiction and futures research studies. [9] [10]

Contention exists over whether AGI represents an existential threat. [11] [12] [13] Many professionals on AI have stated that mitigating the risk of human termination positioned by AGI must be a global top priority. [14] [15] Others discover the advancement of AGI to be too remote to present such a risk. [16] [17]

Terminology

AGI is also known as strong AI, [18] [19] complete AI, [20] human-level AI, [5] human-level intelligent AI, wiki.rrtn.org or basic intelligent action. [21]

Some academic sources reserve the term "strong AI" for computer system programs that experience life or awareness. [a] On the other hand, weak AI (or narrow AI) has the ability to fix one specific problem however lacks general cognitive abilities. [22] [19] Some academic sources utilize "weak AI" to refer more broadly to any programs that neither experience consciousness nor have a mind in the same sense as human beings. [a]

Related ideas consist of artificial superintelligence and transformative AI. An artificial superintelligence (ASI) is a hypothetical type of AGI that is far more usually intelligent than people, [23] while the idea of transformative AI connects to AI having a big impact on society, for instance, similar to the agricultural or industrial transformation. [24]

A structure for categorizing AGI in levels was proposed in 2023 by Google DeepMind researchers. They define five levels of AGI: emerging, proficient, specialist, virtuoso, and superhuman. For instance, a qualified AGI is specified as an AI that surpasses 50% of competent adults in a wide variety of non-physical jobs, and a superhuman AGI (i.e. an artificial superintelligence) is similarly specified however with a threshold of 100%. They think about large language designs like ChatGPT or LLaMA 2 to be circumstances of emerging AGI. [25]

Characteristics

Various popular meanings of intelligence have actually been proposed. Among the leading proposals is the Turing test. However, there are other widely known meanings, and some researchers disagree with the more popular techniques. [b]

Intelligence traits

Researchers generally hold that intelligence is required to do all of the following: [27]

reason, use technique, fix puzzles, and make judgments under unpredictability
represent knowledge, including good sense knowledge
plan
find out
- interact in natural language
- if necessary, integrate these skills in conclusion of any offered goal


Many interdisciplinary approaches (e.g. cognitive science, computational intelligence, and choice making) consider extra traits such as creativity (the capability to form unique psychological images and concepts) [28] and autonomy. [29]

Computer-based systems that show a lot of these capabilities exist (e.g. see computational imagination, forum.kepri.bawaslu.go.id automated thinking, decision support group, robotic, evolutionary computation, intelligent representative). There is debate about whether contemporary AI systems have them to an appropriate degree.

Physical qualities

Other capabilities are thought about preferable in intelligent systems, as they might impact intelligence or aid in its expression. These include: [30]

- the capability to sense (e.g. see, hear, and so on), and
- the capability to act (e.g. relocation and manipulate items, modification place to explore, etc).


This consists of the capability to find and react to risk. [31]

Although the capability to sense (e.g. see, hear, users.atw.hu etc) and the ability to act (e.g. move and control items, modification location to check out, and so on) can be preferable for some intelligent systems, [30] these physical capabilities are not strictly required for an entity to certify as AGI-particularly under the thesis that big language models (LLMs) may already be or end up being AGI. Even from a less optimistic point of view on LLMs, there is no company requirement for an AGI to have a human-like kind; being a silicon-based computational system suffices, offered it can process input (language) from the external world in location of human senses. This interpretation aligns with the understanding that AGI has never been proscribed a particular physical embodiment and thus does not require a capacity for mobility or traditional "eyes and ears". [32]

Tests for human-level AGI

Several tests suggested to verify human-level AGI have been thought about, consisting of: [33] [34]

The concept of the test is that the machine needs to try and pretend to be a male, by addressing questions put to it, and it will just pass if the pretence is reasonably persuading. A significant part of a jury, who should not be expert about makers, must be taken in by the pretence. [37]

AI-complete problems

An issue is informally called "AI-complete" or "AI-hard" if it is thought that in order to fix it, one would require to execute AGI, because the option is beyond the capabilities of a purpose-specific algorithm. [47]

There are many issues that have been conjectured to need basic intelligence to fix along with human beings. Examples include computer vision, natural language understanding, and handling unexpected circumstances while fixing any real-world issue. [48] Even a particular job like translation needs a device to check out and compose in both languages, addsub.wiki follow the author's argument (reason), understand the context (knowledge), and consistently recreate the author's initial intent (social intelligence). All of these issues need to be fixed all at once in order to reach human-level maker performance.

However, a number of these jobs can now be carried out by contemporary large language models. According to Stanford University's 2024 AI index, AI has actually reached human-level efficiency on lots of criteria for reading understanding and visual thinking. [49]

History

Classical AI

Modern AI research study began in the mid-1950s. [50] The very first generation of AI scientists were encouraged that artificial basic intelligence was possible and that it would exist in just a few years. [51] AI leader Herbert A. Simon composed in 1965: "machines will be capable, within twenty years, of doing any work a male can do." [52]

Their predictions were the motivation for Stanley Kubrick and Arthur C. Clarke's character HAL 9000, who embodied what AI researchers believed they might create by the year 2001.