I’m so incredibly proud of what we are building at @arcee_ai . It’s a truly special place. We are only getting started though.
We’ve been quiet for a while, but we haven’t been idle. I can’t wait to share more about what we have been grinding on for the past ~6 months.
I won’t spoil anything, but you can get some idea from this announcement.
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.
Unfortunately, with access to an abliterated DeepSeek V4.1 model, there is little value to KYC holding back the frontier models now for cyber.
In fact, making it hard to secure systems w extra friction in American Enterprise is hurtful to national security.
So at this point I just have to assume all software has basically been a wet paper bag of security for years.
government agencies must be so pissed at all their exploits getting exposed.
I bet new grads I'll be interviewing before long won't even know what Tensorflow is. I had to explain to one of the younger people on my team yesterday what Caffe2 was 🙃
beggin @arcee_ai to drop a nemotron-3.5-super-shaped coding agent RL-ed to death inside prime-agent. just a little something for the gpu poor out there.
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