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AGI is defined as AI that can perform at or beyond human capability across a wide range of cognitive tasks, unlike narrow AI which is task-specific.
Artificial general intelligence (AGI) is a hypothetical type of AI that matches or surpasses human capabilities across virtually all cognitive tasks. Unlike narrow AI (ANI), which is limited to well-defined tasks, an AGI system would be able to generalize knowledge, transfer skills between domains, and solve novel problems without task-specific reprogramming. Beyond AGI, artificial superintelligence (ASI) is envisioned as AI that outperforms the best human abilities across every domain by a wide margin. The scope of AGI is often described through its expected capabilities and the lack of a single universally agreed definition of “intelligence” for computers. Commonly cited intelligence traits include reasoning and strategy under uncertainty, representing knowledge (including common sense), planning, learning, and communicating in natural language, with the ability to integrate these skills to achieve goals. Additional desirable “physical” traits may include sensing (e.g., seeing or hearing) and acting (e.g., moving, manipulating objects, and responding to hazards). Because no definitive definition exists, researchers also discuss tests aimed at human-level intelligence—such as the Turing test, the Ikea test, and other practical benchmarks—and debate how well these measures capture true AGI.
AGI is defined as AI that can perform at or beyond human capability across a wide range of cognitive tasks, unlike narrow AI which is task-specific.
AGI’s scope includes both cognitive abilities (reasoning, planning, learning, language, knowledge representation) and potentially physical abilities (sensing and acting).
There is no single agreed-upon definition of computer intelligence, so AGI is often evaluated using proposed human-level tests and debated criteria.
A hypothetical AI system that matches or surpasses human capabilities across virtually all cognitive tasks.
AI whose competence is confined to specific, well-defined tasks rather than broad generalization.
A hypothetical form of AGI that would outperform the best human abilities across every domain by a wide margin.
A test of machine intelligence where a human judge converses with both a human and a machine, and the machine “passes” if it convinces the judge it is human often enough.
A benchmark where an AI controls a robot to assemble furniture from parts and instructions, demonstrating real-world generalization and autonomy.
A problem believed to require AGI (or equivalent general intelligence) because it cannot be solved by a purpose-specific algorithm alone.
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