061: Interpolation, Extrapolation and Linearisation (Prof. Yann LeCun, Dr. Randall Balestriero)
Machine Learning Street Talk (MLST)
Navigating Generalization in Machine Learning
This chapter discusses the intricacies of generalization in machine learning and the drawbacks of oversimplifying complex problems. It delves into the concepts of interpolation and extrapolation, addressing how machine learning models are often mischaracterized and the significance of reasoning in AI. Moreover, the speakers examine the future of AI systems and the potential integration of neural networks with traditional computation to enhance problem-solving abilities.
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