The Arc Prize Foundation, co-founded by AI expert François Chollet, unveiled ARC-AGI-2, an advanced test designed to evaluate AI general intelligence. Unlike its predecessor, this test emphasizes adaptability, requiring AI models to solve novel, puzzle-like problems rather than relying on brute force computation. Early results show leading AI models score poorly, with reasoning models approximating 1% accuracy. In contrast, a human baseline established by 400 participants achieved a 60% success rate. Chollet asserts that the new test addresses previous flaws by introducing efficiency as a critical metric in measuring AI capabilities.
To effectively measure an AI’s intelligence, we need tests that require adaptability to novel problems rather than relying solely on brute force, computing power.
The ability to interpret patterns on the fly distinguishes true intelligence. ARC-AGI-2 emphasizes efficiency and adaptability in AI's reasoning instead of memorization.
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