AI – Rhonabwy

ML Understanding

OpenAI announced the release of GPT-4 a few days ago, with the not-surprisingly flurry of news reports, quite a few hyperbolic, and a few good. I watch RSS feeds (with the amazing open-source NetNewsWire app) of various individuals, forums, and a few online sources for my technology news – so it was a fairly notableContinue reading “ML Understanding”

Large language models and Search

Microsoft’s made an aggressive and delightful splash in the search market by deeply integrating the guts of OpenAI’s large language model ChatGPT with Bing Search. There’s an impressive interview by Joanna Stern on the topic (hat tip to Daring Fireball for the link). There’s a potential there that’s amazing, and others that are truly frightening.Continue reading “Large language models and Search”

Creating Machine Learning Models with CreateML

I have been following the bare outlines of building, and using, machine learning models in Apple’s software ecosystem for a while. Most of my learning and personal research has been with foundational technologies – following some of the frameworks (TensorFlow, PyTorch, SciKit-Learn) and some of the advances in models and their results. Until this holiday,Continue reading “Creating Machine Learning Models with CreateML”

Embodied AI

I’ve thought for quite a while that some of the critical paths forward in building systems that learn need more complexity and variables in their world. A couple of weekends ago a friend passed me an article on Engadget about an AI contest set in Doom. Given the recent exemplary advances of systems learning to play Nintendo games, it’sContinue reading “Embodied AI”