On the Measure of Intelligence

Chollet's landmark 2019 paper argues that current AI benchmarks measure crystallized task-specific skill rather than general intelligence. He proposes a formal definition of intelligence as "skill-acquisition efficiency" — how quickly a system can adapt to novel tasks given limited experience — and introduces the Abstraction and Reasoning Corpus (ARC) as a benchmark that measures this efficiency rather than performance on memorized tasks. The paper distinguishes between developer prior, experience, and skill, arguing that a fair test of intelligence must control for all three. This framework directly challenges scaling as the path to AGI: a system that achieves high ARC scores through brute-force training has not demonstrated intelligence in the meaningful sense.