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@@ -1,10 +1,9 @@
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# AI Session
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-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.
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+The objective is to give a very brief introduction to _DQN_ training using games (just to talk about theory), present _OpenSource Web_ interfaces and create _LLM Embeddings_ to ask questions about given documents.
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Things to cover:
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- Simple theory of Q-learning, with a practical example using the a Taxi game.
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-- Simple thory of Proximal Policy Optimization, with a practical example using a Pong game.
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- _OpenSource Web_ interfaces available for Stable Diffusion, Inference and Embeddings.
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- A practical example on how to create and use _LLMs_ and _Embeddings_ using a _Python_ script.
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