@levie: We’re going to see an increasing divergence between what AI does in our personal lives and in daily productivity vs. wh…

We’re going to see an increasing divergence between what AI does in our personal lives and in daily productivity vs. what it can do in very deep domains like math, science, legal, coding and more.

Up to some threshold, capability was evenly felt across all domains because the models were just becoming mildly useful in general. Now, the deep domain work is about to go vertical.

Most people won’t actually notice these benefits in their day to day life directly (indirectly they certainly will over time), but the experts in these fields will. And there’s no inherent ceiling to what capabilities are needed, unlike in the consumer space where needs can get met relatively straightforwardly.

This will often lead to a capability overhang, though, as many of these performance gains need to be applied to data sets and workflows in an applied way for that area of work. But this is ultimately how you get breakthroughs in life sciences, real world automation, new cyber capabilities, and more.

Noam Brown (@polynoamial): An internal version of Astra, @OpenAI’s next major model family, solved 10 major open problems in mathematics, quantum complexity, and theoretical computer science.

We believe it will be a major step for scientific reasoning.