ai-session

AI Session

The objective is to give a very brief introduction to AI training using games (mostly to talk about theory), present OpenSource Web interfaces and create LLM Embeddings to ask questions about given documents.

Things to cover:

• Simple theory of Q-learning, with a practical example using the a Taxi game.
• Simple thory of Proximal Policy Optimization, with a practical example using a Pong game.
• OpenSource Web interfaces available for Stable Diffusion, Inference and Embeddings.
• A practical example on how to create and use LLMs and Embeddings using a Python script.

In no way should any of this be considered as a complete solution, the goal is just to provide enough elements for a start so all participants can grow from there.