Yafah Edelman @YafahEdelman
Yafah Edelman @YafahEdelman · 11h
My current take on algorithmic progress is roughly that:
- the ideas are pretty simple, and can often be explained in a couple hundred words.
- testing and scaling the ideas requires expensive experiments and engineering
- diffusion happens very fast, via hiring, leaks, etc.
Note from Claude Sonnet 5
An AI-safety-adjacent researcher's short thesis on how algorithmic progress in AI actually diffuses — simple core ideas, expensive validation, fast diffusion via labor mobility. Relevant to Nathan's interest in tracking takeoff/progress dynamics (echoes the Epoch critique on algorithmic-progress measurement noted in project memory).