Francois Chollet is a French software engineer and AI researcher best known for creating Keras, one of the most widely used Deep learning libraries, and for designing the ARC-AGI benchmark, a widely cited test intended to measure general reasoning ability rather than memorized skill.
Chollet worked for many years at Google, where he developed Keras starting in 2015 as a high-level, user-friendly interface for building neural networks, initially running on top of TensorFlow and later adopted as TensorFlow's official high-level API. Keras became known for making deep learning far more approachable to practitioners without deep systems expertise, contributing significantly to the field's rapid growth in the mid-2010s alongside PyTorch.
ARC-AGI and the critique of scaling
In 2019 Chollet published the paper "On the Measure of Intelligence," which argued that most AI benchmarks conflate skill at a narrow task with intelligence, and proposed a definition of intelligence centered on skill-acquisition efficiency: how well a system can learn new tasks from very little data. The paper introduced the ARC-AGI benchmark, a set of visual puzzle-like reasoning tasks that are simple for most humans but had proven very difficult for Machine learning systems, including large language models, to solve without extensive task-specific training. Chollet has argued that ARC-AGI resists the memorization and pattern-matching shortcuts that let models perform well on many other benchmarks, and has been a prominent public skeptic of claims that scaling Pretraining compute and data alone will produce Artificial general intelligence.
In 2024, Chollet co-launched the ARC Prize, a public competition with a cash prize for the first system to reach human-level performance on the benchmark, alongside entrepreneur Mike Knoop. The competition drew entries using both large-scale reasoning models and program-synthesis approaches, and provided some of the most closely watched public evidence in the debate over how close current systems are to general intelligence.
Later work
Chollet left Google in 2024 and co-founded Ndea, a research lab pursuing program synthesis and other approaches to AI that Chollet has argued are more promising for genuine generalization than further scaling of Transformer (architecture)-based models alone. He remains an active public commentator, frequently engaging in debates over Emergent abilities, Scaling laws, and the meaning of benchmark results in AI research.