LLMs: Internals, Hallucinations, and Applications | Data Brew | Season 5 | Episode 4

Our fifth season dives into large language models (LLMs), from understanding the internals to the risks of using them and everything in between. While we're at it, we'll be enjoying our morning brew.
In this session, we interviewed Chengyin Eng (Senior Data Scientist, Databricks), Sam Raymond (Senior Data Scientist, Databricks), and Joseph Bradley (Lead Production Specialist - ML, Databricks) on the best practices around LLM use cases, prompt engineering, and how to adapt MLOps for LLMs (i.e., LLMOps).

[@k98killer]

Very interesting. Just getting back into AI/ML starting with genetic algorithms and experimenting with OpenAI. I'll check out that course.