Feynman on Artificial Intelligence and Machine Learning, with Updates
This is an incremental historical analysis for AI researchers and historians, offering retrospective insights without new technical contributions.
The paper revisits Richard Feynman's 1980s ideas on AI and neural networks, assessing their alignment with modern advances and identifying unresolved challenges in computational science and symbolic methods.
I present my recollections of Richard Feynman's mid-1980s interest in artificial intelligence and neural networks, set in the technical context of the physics-related approaches to neural networks of that time. I attempt to evaluate his ideas in the light of the substantial advances in the field since then, and vice versa. There are aspects of Feynman's interests that I think have been largely achieved and others that remain excitingly open, notably in computational science, and potentially including the revival of symbolic methods therein.