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5 Archetypes of Knowledge-Intensive Applications

It doesn't always have to be RAG.

The current GenAI boom has seen the rise of the Retrieval Augmented Generation (RAG) architecture, which promises to enhance the functionality of chatbots by providing them with context from a knowledge base. In some circles, RAG has become synonymous with LLM-based applications.

I think this is a mistake, and I believe that many of the most valuable use cases that leverage LLM technology will do so without anything that resembles RAG.

A tour through tensorflow with financial data

I present several models ranging in complexity from simple regression to LSTM and policy networks. The series can be used as an educational resource for tensorflow or deep learning, a reference aid, or a source of ideas on how to apply deep learning techniques to problems that are outside of the usual deep learning fields (vision, natural language).

Deep Learning Reading List

There is a lot written online about deep learning and AI. Ignoring the fluff and product-hype articles, you’re left with a huge resource for learning the technical side of the field. I won’t claim to have read everything out there, but here are some of the most useful things that I have found. The purpose of this list is not to be a definitive curriculum, but to recommend some of the high-quality educational material that’s out there. If there is an article that you think belongs on this list send me an email.