• https://simonwillison.net
  Simon Willison updates his blog frequently with easy to read, yet insightful posts, mostly on large language models.

Pelican tea party by Simon Willison

• https://sebastianraschka.com/blog
  Sebastian Raschka is a prolific author of articles, books, and courses. Currently seems to be focused on various methods of tuning large language models.

Some older pages we (used to) occasionaly read:

• http://www.inference.vc
  Ferenc Huszar has been going strong for a while now.

• http://colah.github.io
  Christopher Olah, a titan of neural networks visualization.

• https://raberrytv.wordpress.com
  This site is a source of information on recommendation systems, NLP, transformers, and more.

• http://deliprao.com
  Delip Rao on machine learning and all sorts of other topics.

• http://benanne.github.io
  Sander Dieleman’s blog might have become more theoretical over the years.

• http://hunch.net
  John Langford is the father of Vowpal Wabbit, so to speak. He has 110 pages (!) of content.

• http://www.machinedlearnings.com
  Paul Mineiro has had to do with Vowpal Wabbit.

• http://www.johndcook.com/blog
  John D. Cook writes about scientific computing, math, stats, and what not. He offered some worthwhile thougts, for example on the most important skill in software development.

• http://blog.echen.me
  Edwin Chen has some interesting posts, like the one about clustering McDonald’s menu. It answers an interesting question: how many clusters are there in the menu?

• http://lemire.me/blog
  Daniel Lemire’s writes about hardware, science (including women’s ovaries) and other interesting stuff.

Inactive

• https://medium.com/halting-problem
  Halting Problem was like The Onion, but focused on tech, smaller scale and more… smooth? Stopped posting in 2020.

• http://zinkov.com
  Not that much content, last post from 2019, but some nice entries, for example on how to read scientific papers.

• https://jakevdp.github.io
  Jake Vanderplas’ had written mostly on machine learning, Python and visualization. Stopped in 2018.

• http://yerevann.github.io
  An Armenian blog on neural networks, no updates after 2017.

• https://jmetzen.github.io
  Jan Hendrik Metzen has written a couple of posts on machine learning and Python back in 2015.

• http://researchinprogress.tumblr.com
  Life of an aspiring scientist in animated pictures (last post in 2014). Here’s one, entitled “How I sell my method”:

  

And finally, a one-time, easy read: You and your research - a transcript of a 1986 talk by Richard Hamming, a great scientist. He talked about how to be a great scientist.