Is Karpathy's approach too focused on brute force learning?
Some might perceive my emphasis on large datasets and model scale as 'brute force.' However, I see it more as leveraging the inherent capabilities of neural networks. The effectiveness I've observed often comes from allowing the model to discover patterns within vast amounts of data, rather than explicitly programming every rule. The challenge is then to understand and interpret *why* these models succeed, which requires careful analysis of their internal workings and the data they consume.
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