• Why You Need a Thinking Partner (like this Genius)

    You may not have heard of him, but James Clerk Maxwell wrote down what we now think of as four equations that define ALL of electromagnetics. You can get a T-Shirt with them emblazoned on it. If you want to know how radio waves propagate, or how a radio functions, or how anything running on electricity…

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  • Omni Models Reboot the Whole Game for RAG (GPT-4o)

    “Chat with your documents” already seems so 2023. The new “omni” model can fluently switch among text, audio, still images, and (live) video. RAG, or Retrieval Augmented Generation (see my LinkedIn Learning course for details) is a technique where you pair up a language model with a database to extend it’s capabilities. This includes the…

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  • Free email course: Systems Thinking for the AI Era

    I’m launching a new FREE email course in May, and it’s all about one of the most important skills in this age of layoffs, rapid technological change, and AI: Systems Thinking. This training is specially crafted for software engineers and developers who have mastered basic computer science and are ready to elevate their thinking to…

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  • Running DBRX on your local network

    DataBricks released their DBRX model, and it appears to be quite capable, beating Llama 2, Mistral, and Grok. It uses a slightly novel architecture, so existing tools don’t work with it out of the box, though they are making rapid progress to add support. I haven’t yet been successful in converting this new format into…

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  • FREE Live Training: Generative AI for Technical Professionals

    This Friday, March 22nd, at 4pm Atlanta time, join me for live recording some new training! AI fundamentals for technical professionals. There is no code or math–instead focusing on intuitive explanations of how generative AI works, and how to effectively use it for things we already work on every day–while avoiding pitfalls for the unsuspecting.…

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  • Is Prompt Templating even worth it?

    Check out Sam Witteveen‘s take on Anthropic’s Meta Prompt. (Not the be confused with Meta Corporation). In my LinkedIn Learning course, there’s a lot of necessary discussion about prompt templating. But with approaches like this, how much of that is going to get subsumed into the models themselves? Join the Problem Solver’s Digest for more…

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