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  1. I’ve been thinking about what it actually means to create something “with AI” versus creating something “yourself.”

  2. First stitches: on learning to knit

    I previously learned how to crochet.

  3. A colleague at work asked me for some tips on learning German and her situation and goals were fairly common so I thought I’d write up some notes here.

  4. My niece reached out to me a few days back asking about tips for studying at school.

  5. I love blogging and I’ve benefitted a lot from what it’s done for me ever since I started my first Geocities page in the mid 1990s.

  6. Vermeer at the Rijksmuseum

    [caption id=“” align=“alignnone” width=“768”] Not by Vermeer.

  7. 2022 Readings

    I read 75 books this year (over 22,000 pages), and a few days still remain.

  8. On the interpretability of models

    A common criticism of deep learning models is that they are ‘black boxes’.

  9. FastAI Lesson Zero: video notes

    [These are mainly notes for myself, based off Jeremy Howard’s ‘Lesson 0’ video that was recently posted.

  10. Telling Cats from Dogs

    One of the main ways that using neural networks to train models is different from traditional (imperative) programming can be illustrated with a specific task: let’s say you want to use a computer to tell you whether any particular photo you give it is a…

  11. The use of neural networks / architectures is a powerful pattern, but it’s worth remembering that this pattern is part of the broader category of machine learning.

  12. [This is part of a series on getting out of a language-learning plateau at the intermediate-advanced level.

  13. Small, unexpectedly powerful boxes

    Graphics Processing Units or GPUs are what your computer uses to quickly display your screen.

  14. Rosenblatt’s Mark I Perceptron

    I’ve now read a little about Rosenblatt’s Perceptron in two different places: in the Howard/Gugger Deep Learning book, and also in Cade Metz’ Genius Makers.

  15. Removing Barriers: Deep Learning Edition

    I’ve been re-reading Jeremy Howard & Sylvain Gugger’s Deep Learning for Coders with Fastai and PyTorch and I really appreciate the reminder that a lot of barriers to entry into the Deep Learning space can be productively put to one side.

  16. PDP: a precursor to modern neural networks?

    Parallel Distributed Processing: Explorations in the Microstructure of Cognition, a multi-volume publication by David Rumelhart, James McClelland and the PDP Research Group, was released in 1968 and is recognised as one of the most important works relating

  17. Held back by misunderstanding

    The field of deep learning seems to have had a rough journey into public consciousness and adoption.

  18. Deep Learning: Best in Show?

    Deep Learning is an incredibly powerful technology and there are a number of (focused / specific) areas where it already surpasses human-level abilities.

  19. jQuery and Handlebars are both external to the core functionality of JavaScript.

  20. A basic overview of how to use Handlebars

    Handlebars is a simple templating language that you can use with your JavaScript code.