Taoism notes 🔗Introduction 🔗Taoism is a practical self consistent personal philosophy that despite its ancient roots fits nicely with modern scientific thought. This including concepts such as the block universe, recursive structures, quantum theory, fuzzy logic and non-monotonic reasoning. It provides best in class guidance for several practical areas including how to generally conduct oneself, how to interact with others, and quite brilliantly how to think about the universe holistically. No stone is left unturned by the broadness of it’s reach.

This is a bit different to the usual technical stuff I write. I want to talk about LLMs. Whilst an amazing piece of technology (magic), they do play heavily into the hands of large corporations. I suppose this stuff is quite obvious but I thought I’d write it anyhow! Why is this? They commodify skill and knowledge such that it is centralised, and no longer distributed amongst a variety of places and humans, like the internet.

This short post is a call to arms for Tsetlin Machines (TMs), a somewhat academic outsider’s view of what the community has and what is missing. The discourse is biased to commercial usages of the technology, a vital step forward in establishing the true value of the algorithms discussed in this blog post.. Introduction 🔗Tsetlin Machines are a new class of classifier that have significant usability and performance benefits over both standard classifiers, and most interestingly over existing deep learning (DL) systems.

Hi All! I recently delivered a talk about polars at PyDataLondon23. Here’s the slides data and notebook. Hope you find them useful! This data has ben created as an open data set by CitizenMe as part of their 360° Data Lab initiative.

The ability to perform accurate repetitive computation has been central to a large number of scientific and technological advances in the last seventy years. At the heart of this commercially is Moore’s Law, which states that computational power provided by traditional computer central processing units will double year-on-year for the foreseeable future. Unfortunately, several factors have compounded to make this less likely to continue. Heat dissipation, atomic and quantum effects provide practical limits to the miniaturisation and packing of transistors, and the limited bandwidth between CPU and memory limits computation speed.