In this episode, we'll take a look at Meta’s ambitious approach to scaling large language models. We'll explore the shift from handling many smaller models for recommendation engines to building colossal generative AI models, and the immense challenges that come with it. From hardware and software optimizations to managing power and dealing with inevitable hardware failures, we'll break down the critical pieces that make Meta's infrastructure tick. What does it take to run systems this large without breaking? Tune in to learn how Meta did it.
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