I used AI to fix transcription errors, rerrarange the ideas, and suggest tweaks to the title and some sentences.
Three of the most exciting projects to come out of EA in recent years are, in a vague sense, CEA spinouts:
* Kairos is directly a spinout of CEA and now handles most support for university AI safety groups. Basically everyone I've found who knows them is really excited about what they do
* NEST is an opinionated ideas-fi...
This post presents the executive summary from Giving What We Can’s impact evaluation for 2025. At the end of this post we share links to more information, including the full report and...
I was debugging something last week and had this weird moment where I could tell immediately that the output was wrong but had no idea how to fix it. Sat there for like twenty minutes just staring at the error, knowing exactly what wasn't working and zero clue what would.
And I realized — this isn't just a programming thing.
It shows up everywhere once you look. In science: disproving a hypothesis takes one counterexample, proving it takes forever. Learning a language: you can hear bad grammar way before you can produce good grammar. I spent a year in France and by month three I could tell when someone sounded off. By month twelve I still couldn't order food without getting laughed at.
The gap is checking versus building. Verifying is cheap. Constructing is expensive. And yet somehow we cross this gap all the time — we use wrongness as a compass, slowly walking from "that's not it" toward "this might be it."
I've been trying to find what people call this. Optimization? Solomonoff induction? Generators vs discriminators? None of them quite fit what I'm pointing at. Feels like there should be a name for the specific thing where verification is the cheap half of learning and construction is the expensive one.
Or maybe I'm just describing something obvious and don't know the word for it. That happens a lot.