What is AGI? Some Definitions from Experts
(1) Generalizable
(2) Marches or exceeds top human experts
(3) Can invent knowledge
Schmidt, February 26, 2025, Mr. Schmidt was CEO of Google, (2001-11) and executive chairman of Google and its successor, Alphabet Inc. (2011-17), Wall Street Journal, AI Could Usher In a New Renaissance, https://www.wsj.com/opinion/agi-could-usher-in-a-new-renaissance-physics-math-econ-advancement-ed71a02a?mod=Searchresults_pos1&page=1
Schmidt, February 26, 2025, Mr. Schmidt was CEO of Google, (2001-11) and executive chairman of Google and its successor, Alphabet Inc. (2011-17), Wall Street Journal, AI Could Usher In a New Renaissance, https://www.wsj.com/opinion/agi-could-usher-in-a-new-renaissance-physics-math-econ-advancement-ed71a02a?mod=Searchresults_pos1&page=1
The idea of artificial general intelligence captivated thinkers for decades before it came anywhere near being realized. The concept still conjures popular visions out of science fiction, from C-3PO to Skynet.
Even as the interest has grown, AGI has defied a concise, universally accepted definition. In 1950, Alan Turing proposed the Turing Test to assess machine intelligence. Rather than trying to determine whether machines truly think (a question he deemed intractable), Turing focused on behavior: Could a machine’s actions be indistinguishable from those of a human?
Remarkably, some of today’s AI models pass the Turing Test, in the sense that they produce complex responses that imitate human intelligence. But as the technology has advanced, so has the bar for achieving AGI. Some believe that AGI will be realized when AI moves beyond narrow, focused tasks, growing to possess a generalized ability to understand, learn and perform any intellectual task a human can do. Others define AGI more ambitiously, as intelligence that matches or exceeds the top human minds across domains. Demis Hassabis, CEO of DeepMind Technologies, calls AGI-level reasoning the ability to invent relativity with only the knowledge that Einstein had at the time.
These differing definitions create a moving target for AGI, making it both elusive and tantalizing. To sort through all this, it’s helpful to say what AGI isn’t. It isn’t an infallible intelligence; like other intelligent systems, mistakes can be useful for its learning process. Neither is AGI a singular source of truth—our knowledge of the world is probabilistic and complex, notably at subatomic and intergalactic scales, but also in everyday life. Multiple AGI systems could emerge, each with a distinct capability and way of understanding the world.
Even without a consensus about a precise definition, the contours of an AGI future are beginning to take shape. AI systems capable of performing at the intellectual level of the world’s top scientists are arriving soon—likely by the end of the decade.
A key marker of the shift to AGI will be AI’s ability to produce knowledge based on its own findings, not merely retrieval and recombination of human-generated information. AGI will then move beyond the current limits of knowledge. Glimpses
