Memory for LLM applications: Different retrieval techniques for getting the most relevant context, June 8, 2023 @ 9am Pacific

Speaker: Harrison Chase, LangChain
June 8, 2023 @ 9am Pacific
Link: https://bit.ly/41wrVup

About the session

Connecting external data sources to LLMs to give them memory is a crucial part of many LLM applications. This can take the form of connecting to pre-existing large corpora of data, remembering user conversations, or even creating “new memories” by reflection. Underpinning all of all this is retrieval – the process of pulling relevant pieces of information into context.

Join LangChain’s Harrison Chase for a deep dive into retrieval where we dissect the challenges of finding relevant information from a large corpus of data.

You’ll learn

  • What is memory and why is it important
  • Types of memory
  • Basics of semantic search
  • Edge cases of semantic search
  • Generative Agent examples

What you’ll learn:

  • What is vector database
  • What is semantic similarity
  • How to use a vector database to find similar texts

Harrison Chase is the co-founder and CEO of LangChain, a company formed around the open-source Python/Typescript packages that aim to make it easy to develop Language Model applications. Prior to starting LangChain, he led the ML team at Robust Intelligence (an MLOps company focused on testing and validation of machine learning models), led the entity linking team at Kensho (a fintech startup), and studied stats and CS at Harvard.

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