The Bitter Lesson: The history of reinforcement learning
I've been trying to understand how machine learning actually works. Not use it, understand it, down to the ifs and loops. How does a program built out of plain conditionals get better on its own? So l...
13 Kesä 1h
The Pre-Training Wall and the Treadmill After It
I've been confusing Don with frontier-lab links late at night for a bit. Ilya Sutskever told a NeurIPS audience that pre-training as we know it would unquestionably end. There's only one internet, and...
9 Touko 56min
Story: The Aging Programmer
Kate Gregory has been writing C++ for over forty years. Books, keynotes, a consulting firm she built from the ground up. At sixty-three, she's one of the most experienced programmers alive. She survey...
2 Huhti 41min
From Hacker News to TikTok - How Algorithms Learned to Hook Us
Corey told me about his AI cat reel problem. He found these AI-genearted cat videos hilarious. Who makes these? He kept sending them to his wife. Then he tried to stop watching and he couldn't. So I w...
2 Maalis 41min
Notes: The Universal Paperclip Clicker
Multiple VS Code windows. "Agent stopping" in a robot voice. A laptop stand on the treadmill so Claude can keep working while I run. The Big Rich sitting unread by the fireplace while I check if the m...
4 Helmi 11min
Story: Inside Early Google - Race Conditions, Java Pain, and the Birth of AdWords
Ron Garret left JPL for a 100-person startup he'd just discovered on Usenet. Four a.m. alarms. Burbank to San Jose on Southwest. A rented room in Susan Wojcicki's house. He expected the search engine ...
2 Tammi 37min
Story: Godbolt's Rule - When Abstractions Fail
What do you do when your code breaks and the only fix is to dig into the runtime below? Matt Godbolt lives for that. Tile-based renderers, color-coded scanlines, zero-copy NICs—each story is a clue th...
4 Marras 202544min
