A Definition of AGI
The lack of a concrete definition for Artificial General Intelligence (AGI)
obscures the gap between today's specialized AI and human-level cognition. This
paper introduces a quantifiable framework to address this, defining AGI as
matching the cognitive versatility and proficiency of a well-educated adult. To
operationalize this, we ground our methodology in Cattell-Horn-Carroll theory,
the most empirically validated model of human cognition. The framework dissects
general intelligence into ten core cognitive domains-including reasoning,
memory, and perception-and adapts established human psychometric batteries to
evaluate AI systems. Application of this framework reveals a highly "jagged"
cognitive profile in contemporary models. While proficient in
knowledge-intensive domains, current AI systems have critical deficits in
foundational cognitive machinery, particularly long-term memory storage. The
resulting AGI scores (e.g., GPT-4 at 27%, GPT-5 at 58%) concretely quantify
both rapid progress and the substantial gap remaining before AGI.
68f91c1db9b2e4ae0467366b
Dan Hendrycks
68f91c1db9b2e4ae0467366c
Dawn Song
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Christian Szegedy
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Honglak Lee
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Yarin Gal
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Erik Brynjolfsson
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Sharon Li
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Andy Zou
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Lionel Levine
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Bo Han
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Jie Fu
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Ziwei Liu
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Jinwoo Shin
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Kimin Lee
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Mantas Mazeika
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Long Phan
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2025-10-30T14:43:52.714Z
62184306e1ef90f6e56dc116
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Long Phan
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user
justinphan3110
68f91c1db9b2e4ae0467367b
George Ingebretsen
68f91c1db9b2e4ae0467367c
Adam Khoja
68f91c1db9b2e4ae0467367d
Cihang Xie
68f91c1db9b2e4ae0467367e
Olawale Salaudeen
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Matthias Hein
68f91c1db9b2e4ae04673680
Kevin Zhao
68f91c1db9b2e4ae04673681
Alexander Pan
68f91c1db9b2e4ae04673682
David Duvenaud
68f91c1db9b2e4ae04673683
Bo Li
68f91c1db9b2e4ae04673684
Steve Omohundro
68f91c1db9b2e4ae04673685
Gabriel Alfour
68f91c1db9b2e4ae04673686
Max Tegmark
68f91c1db9b2e4ae04673687
Kevin McGrew
68f91c1db9b2e4ae04673688
Gary Marcus
68f91c1db9b2e4ae04673689
Jaan Tallinn
68f91c1db9b2e4ae0467368a
Eric Schmidt
68f91c1db9b2e4ae0467368b
Yoshua Bengio
A Definition of AGI
The lack of a concrete definition for Artificial General Intelligence (AGI)
obscures the gap between today's specialized AI and human-level cognition. This
paper introduces a quantifiable framework to address this, defining AGI as
matching the cognitive versatility and proficiency of a well-educated adult. To
operationalize this, we ground our methodology in Cattell-Horn-Carroll theory,
the most empirically validated model of human cognition. The framework dissects
general intelligence into ten core cognitive domains-including reasoning,
memory, and perception-and adapts established human psychometric batteries to
evaluate AI systems. Application of this framework reveals a highly "jagged"
cognitive profile in contemporary models. While proficient in
knowledge-intensive domains, current AI systems have critical deficits in
foundational cognitive machinery, particularly long-term memory storage. The
resulting AGI scores (e.g., GPT-4 at 27%, GPT-5 at 58%) concretely quantify
both rapid progress and the substantial gap remaining before AGI.
A quantifiable framework based on Cattell-Horn-Carroll theory evaluates AI systems across ten cognitive domains, revealing significant gaps in foundational cognitive abilities like long-term memory.
Cattell-Horn-Carroll theory cognitive domains reasoning memory perception psychometric batteries AGI scores