A well-known test for artificial general intelligence (AGI) is getting close to being solved, but the test's creators say this points to flaws in the test's design rather than a bonafide breakthrough in research. In 2019, Francois Chollet, a leading figure in the AI world, introduced the ARC-AGI benchmark, short for 'Abstract and Reasoning Corpus for Artificial General Intelligence.' Designed to evaluate whether an AI system can efficiently acquire new skills outside the data it was trained on, ARC-AGI, Francois claims, remains the only AI test to measure progress towards general intelligence (although others have been proposed.) Until this year, the best-performing AI could only solve just under a third of the tasks in ARC-AGI. Chollet blamed the industry's focus on large language models (LLMs), which he believes aren't capable of actual 'reasoning.' To Chollet's point, LLMs are statistical machines. Trained on a lot of examples, they learn patterns in those examples to make...
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