What I'm Reading This Month
I don't have a "microblog" or "federated social media" account because I find the ease of posting distracting. I could spend all my free time whittled away in trivial conversations. I was thinking about this when the three millionth person suggested I join Instagram. I don't understand the IG. If you do, and find it useful, great. I refuse to join anything related to Meta/Facebook/Whatever-they're-called-this-year. It's all a big data vacuum. I can burn time on xmpp, irc, matrix, or delta chat just fine; no need for big tech companies to mediate the experience.
Instead, I read longer form articles on purpose. All that is a preface to a few links:
-
How We Lost Communication to Entertainment, https://ploum.net/2025-12-15-communication-entertainment.html
- This is not the future, https://blog.mathieui.net/this-is-not-the-future.html
- You're overspending because you lack values, https://www.sherryning.com/p/youre-overspending-because-you-lack-values
- Cultivating Innovation in a Research Lab, https://cacm.acm.org/opinion/cultivating-innovation-in-a-research-lab/
- Reinventing AI: Is it Time for a New Paradigm? https://cacm.acm.org/opinion/reinventing-ai-is-it-the-time-for-a-new-paradigm/
- Tech Workers vs Enshittification, https://cacm.acm.org/opinion/tech-workers-versus-enshittification/
- Quantum Computing, https://nostarch.com/quantum-computing. Every book on quantum computing spends the first twenty-five percent of the book speed-running undergraduate and graduate math classes; calculus, linear equations, etc. This book is no different. Maybe after reading a few of these books, I'm finally remembering the math lessons.
- Learn Physics with Functional Programming, https://nostarch.com/learn-physics-functional-programming. Literally reading this for fun. I'm re-learning Haskell as a side benefit.
- Goliath's Curse, https://en.wikipedia.org/wiki/Goliath%27s_Curse.
- Making It So, https://patrickstewartbook.com/. This is a cheat as I started reading it over the summer, but then come back to it every so often.
- Make Your Own Neural Network, https://bookshop.org/p/books/make-your-own-neural-network-tariq-rashid/36f95415033beace. We have no end of power in our existing devices, especially if yours includes an NPU. This is focused on python, but the principles work with any programming language. I use julialang. I may start using Haskell as I relearn it.