Join 📚 Josh Beckman's Highlights
A batch of the best highlights from what Josh's read, .
It was like a fantastical version of their old jobs, a new financial system with all the bits of the old system that they liked, none of the bits they disliked, and some new bits that they dreamed up because they thought they might be cool.
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Bloomberg
The other thing about chat was when we had these instruct models. The task of “complete this text, but in a nice or helpful way” is a pretty poorly defined task. That task is both confusing for the model and for the human who's supposed to do the data labeling.
Whereas for chat, people had an intuitive sense of what a helpful robot should be like. So it was just much easier for people to get an idea of what the model was supposed to do. As a result, the model had a much more coherent personality and it was much easier to get pretty sensible behavior robustly.
John Schulman (OpenAI Cofounder) - Reasoning, RLHF, & Plan for 2027 AGI
Dwarkesh Patel
Imagine we want to compute the square root of a number n. The basic idea of [*Heron’s method*](https://en.wikipedia.org/wiki/Methods_of_computing_square_roots#Heron's_method), named after the mathematician and engineer, Heron of Alexandria, is to find a number g that is close to n and to then average that with the number n/g, which corrects for the fact that g either over- or underestimates n.
Estimating Square Roots in Your Head
Gregory Gundersen
...catch up on these, and many more highlights
Readwise