061: Interpolation, Extrapolation and Linearisation (Prof. Yann LeCun, Dr. Randall Balestriero)
Machine Learning Street Talk (MLST)
Navigating Neural Network Complexities
This chapter explores the intricate nature of neural networks, highlighting varying perspectives within the machine learning community on their capabilities. It discusses historical techniques that have laid the groundwork for AI, the challenges of training these networks, and the potential for hybrid models that blend symbolic computation with neural architectures. The chapter culminates in a reflection on human cognitive limitations in decision-making and the role of experience in shaping automatic responses.
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