During this workshop, you will be able to learn more about features of the MongoDB's Data Platform, including a follow-along, hands-on project to implement an AI application. We will cover various functionalities of MongoDB, as well as useful LLM techniques.

In particular:

Leverage Atlas to build a semantic search using LLMs for pre-summarization and information extraction
Learn how to get started developing your first semantic search app Atlas with a free cluster
Use automatic client side encryption to store user secrets securely (we're going to access users Google Drive Docs!)
Learn about the pre-summarization technique, an alternative to chunking techniques
Store LLM interactions and keep track of model usage and costs using Atlas Charts
Use langchain to compare costs & performance of various models, featuring open-source models, OpenAI, Anthropic, Cohere & Mistral.
Implement access control for vector search
Build a basic RAG pipeline to search across stored facts