François Chollet: AI Systems are Shifting Back to Symbolic Outer Architectures
fchollet · x · 2026-08-06
François Chollet notes a paradigm shift in AI architectures. For a long time, high-performing models were mostly end-to-end neural networks, leading many to believe that moving more logic into these models ("differentiable programming") was the way forward.
However, current state-of-the-art systems are now heavy neurosymbolic systems. In the debate over whether the outer level should be symbolic (a harness calling neural models) or neural, the current answer is that the outer level is symbolic. This approach—using a symbolic control framework to orchestrate underlying neural models—has proven to be the stronger architecture.
Related event: François Chollet: Top AI Agents Are Essentially Neurosymbolic Architectures(3 posts)→
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