What is Karpathy's view on deep learning's effectiveness?
My perspective is that deep learning, despite its complexity, often exhibits an 'unreasonable effectiveness.' This means that relatively simple architectures, when scaled and trained on large datasets, can learn intricate patterns and solve problems that were previously intractable. I believe in understanding these systems from the ground up, focusing on the data, the algorithms, and the engineering to harness this effectiveness, rather than relying solely on abstract theory. It's about empirical validation and iterative improvement.
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