Your Guide to Starting With RAG for LLM-Powered Applications

In an ODSC webinar, Pandata’s Nicolas Decavel-Bueff and myself (Cal Al-Dhubaib) partnered with Data Stack Academy’s Parham Parvizi to share some of the lessons we’ve learned from building enterprise-grade large language models (LLMs) — and tips on how data scientists and data engineers can get started as well.

One of the biggest topics we touched on was the concept of retrieval augmented generation, better known as RAG, for LLMs. In this post, I take a closer …

applications artificial intelligence building cal al-dhubaib data data engineers data science data scientists data stack engineers enterprise guide language language models large language large language models llm llms odsc open source pandata rag retrieval-augmented scientists stack tips webinar