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Reflections on 1,000 Days of Math
I finally hit 1,000 days of doing math daily! Early on in my journey I was a lot more aggressive with my XP targets, but settled into a low-volume rhythm as my goals evolved. I worked from MF1 (Math Foundations 1, lowest level) into MF3, then about halfway through MF3 I started M4ML (Mathematics for Machine Learning). ### Self-induced friction But it got really hard and my progress started to slow as lessons took longer, which was problematic because I was trying to limit my math time to <20m/day. That may have worked fine, but I really screwed myself by relying on…
5 min · 1,105 words
A Necessary History of the Oddest Letter: W
Linguist Danny Bate traces how W emerged after Rome's fall—from foederati names and medieval spelling experiments to the oddest letter in the modern alphabet and what its history reveals about language change.
11 min · 2,473 words
Four CHI '26 papers I wish I wrote
Janet Davis highlights four CHI 2026 papers she wishes she had written, reflecting on research themes and why each piece of HCI scholarship stood out.
13 min · 3,021 words
A careful comparison of typeclasses and ML-style modules: what each abstraction is for, where the persistent confusion comes from, and how to choose between them when designing APIs and language features.
10 min · 2,361 words
Jens Egholm Pedersen argues modern science is synonymous with open-source software: why reproducible code matters as much as papers, and what researchers should do next.
7 min · 1,517 words
How Your Code Runs: The Journey of a Program Through the CPU
A clear walkthrough of CPU architecture—control unit, ALU, registers, and memory—and how a simple program is compiled, loaded, and executed instruction by instruction.
3 min · 730 words
lcamtuf argues that electronically controlled working memory—not Babbage—was the real bottleneck unlocked on the path to modern computers, tracing early registers, delay lines, and RAM.
8 min · 1,775 words
Bartosz Ciechanowski’s interactive explainer of what sound is, how it is created and propagated, with playable demos of waveforms, frequency, and hearing.
34 min · 7,924 words
Gregory Gundersen reconstructs backpropagation from first principles, explaining why the algorithm needs a backward pass to compute neural network gradients efficiently.
6 min · 1,490 words