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1
Why augmented LMs?
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Why retrieval augmentation?
3
Traditional information retrieval
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Embeddings for retrieval
5
Embedding relevance and indexes
6
Embedding databases
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Beyond naive embeddings
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Patterns & case studies
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What are chains and why do we need them?
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LangChain
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Tool use
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Plugins
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Recommendations for tool use
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Recap & conclusions
Description:
Explore patterns for augmenting language models with external context in this comprehensive video lecture. Delve into retrieval augmentation, chaining, and tool use as Josh guides you through the concepts. Learn about traditional information retrieval, embeddings for retrieval, embedding relevance and indexes, and embedding databases. Discover patterns and case studies, understand the need for chains, and get introduced to LangChain. Examine tool use, plugins, and receive recommendations for their implementation. Access downloadable slides, explore related videos in the LLM Bootcamp series, and navigate through various topics with timestamps provided.

Augmented Language Models - LLM Bootcamp

The Full Stack
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