#51 – Jeffrey Quesnelle on Nous Research, large language models, and the human mind
Into the Bytecode
Mathematics of Machine Learning Models
This chapter explores the mathematical foundations of machine learning, focusing on techniques such as discrete cosine transforms and backpropagation. It highlights the complexities of interpreting large language models and emphasizes ongoing efforts in model interpretability and optimizer evolution for improved training efficiency.
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