Today, we are announcing our Series B funding round, valuing the company at more than $1B. This round accelerates our next-gen Trinity models across diverse infrastructure, expands our work with the DOE and national labs on Genesis-Science-1, and enables us to build the platform teams need to build, evaluate, deploy, and operate open models in production. We are grateful to our team, partners, open-source community, and investors. Led by @Vista_Equity, Cambium Capital, and @emergencecap, with participation from AI10 Ventures, @Hitachi, IAG, @M12vc, @p7ventures, and @Wipro.

Our hypothesis: LLMs have a pressure for information density, leading to compressed language, novel ngrams, and a preference for short alternatives in linguistic alternations, even when this is not humanlike - humans have a pressure for successful communication with other humans

lmao john schulman just basically blurts out that thinking machines is working on a continual learning model

High alpha in looking at the data

So in like 5 ish years ... what is going to happen to all the H100s ... landfill?

If gradstudents knew what actually worked in training SOTA LLMs they would be so mad

People I work with have called me a “boomer” because I used tensorflow at the beginning of my PhD