Building Context-Aware Reasoning Applications with LangChain and LangSmith
Speakers

Harrison Chase is the CEO and co-founder 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.

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.
SUMMARY
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.

