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Ep. 19: From Linguistics to Large Language Models with Chris Brousseau i've been wanting to do an episode that really digs into what #LLMs actually are under the hood, and Chris's journey from linguistics into ML made this the perfect conversation to do it 👇 🎧 compiledconversations.com/19/

we start with how a graduate seminar on python and machine translation in 2017 pulled chris from linguistics into NLP. studying how humans create meaning in language for years turns out to be the perfect background for understanding where LLMs shine and where they completely fall apart. 2/5

from there we go deep on the fundamentals - transformers, tokenization, embeddings, context windows, the training pipeline from self-supervised learning through RLHF to fine-tuning. 3/5

he's deployed billion-parameter models at mastercard and jp morgan chase, and co-authored LLMs in Production (which i'm a huge fan of). we dig into the gap between demos and production systems, and the operational challenges that make deploying at scale uniquely hard. 4/5