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10min chapter
#381 – Chris Lattner: Future of Programming and AI
Lex Fridman Podcast
Navigating Programming Paradigms for Machine Learning
This chapter examines the evolution of programming in relation to auto-tuning and optimization, highlighting the shift from manual programming to automated systems driven by machine learning. It discusses strategies for improving performance, including caching, vectorization, and kernel fusion, while addressing the challenges posed by memory constraints in larger models. The conversation emphasizes the need for scalable programming frameworks to keep pace with advancements in hardware and the complexities of machine learning tooling.
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