Reasoning and Adaptability
François discusses the evolving capabilities of deep learning models, particularly their ability to reason and adapt to new situations. He emphasizes the future of programming through input-output pairs, allowing non-technical users to collaborate with AI in creating programs. The conversation also touches on the need for a new architecture to support lifelong distributed learning, enabling AI systems to identify and abstract commonalities across diverse problems.In this clip
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Machine Learning Street Talk (MLST)
Francois Chollet - ARC reflections - NeurIPS 2024
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