Large language models (LLMs) like Llama 2 are the must-have technology of the year. Unfortunately, LLMs can't accurately answer questions about your business because they lack enough domain knowledge. The solution is to combine the LLM with a vector database like Chroma—a technique known as retrieval augmented generation (RAG). Beyond this, incorporating AI into products is best done with an AI application framework, like LlamaIndex.
In this session you'll learn how to get started with Chroma and perform Q&A on some documents using Llama 2, the RAG technique, and LlamaIndex.
Presenter Bio
Dan BeckerChief Generative AI Architect at Straive; Founder at Build Great AI
Dan Becker is one of the top thought leaders on machine learning and AI. He's the Chief Generative AI Architect at Straive, building AI solutions for content technology. He also runs the Build Great AI consultancy, and was previously VP of ML Development Tools at DataRobot. Dan is also a successful Kaggle competitor, the author of "Automated Machine Learning for Business", and the DataCamp course "Introduction to Deep Learning in Python".
