Building Context-Aware Reasoning Applications with LangChain and LangSmith // Harrison Chase // LLM3

// Abstract
How can companies best build useful and differentiated applications on top of language models? Many of the products and companies built do this by providing the relevant context to LLMs and asking them to reason appropriately. In this talk, Harrison will discuss the different types of context you should be aware of, the different levels of cognitive architectures that are emerging, and how LangChain and LangSmith are built to help with this journey.

// Bio
Harrison Chase is the CEO and co-founder of @LangChain 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.

// Sign up for our Newsletter to never miss an event:
https://mlops.community/join/

// Watch all the conference videos here:
https://home.mlops.community/home/col...

// Check out the MLOps Community podcast: https://open.spotify.com/show/7wZygk3...

// Read our blog:
mlops.community/blog

// Join an in-person local meetup near you:
https://mlops.community/meetups/

// MLOps Swag/Merch:
https://mlops-community.myshopify.com/

// Follow us on Twitter:
  / mlopscommunity  

//Follow us on Linkedin:
  / mlopscommunity