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TBPN · 4 min · Jan 27, 2026

Open-model labs compete on research talent, not nationality

LALucas Atkins · CTO, Arcee AI

Lucas Atkins says the competition is against skilled researchers and labs, not China as a country.

In this episode

Full analysis
  1. 3:05:17A personal assistant emerged from a simple messaging hack6 min
  2. 1:37:41Media companies lose their way when they chase scalePro pick 7 min
  3. 3:38:31Agent payments need better economics and a clear use casePro pick 8 min
  4. 1:20:20Insurers spend $70 billion a year on back-office BPO3 min
  5. 2:18:39Northwood built eight satellite ground units in four weeks4 min
  6. 2:08:26Open-model labs compete on research talent, not nationality4 min
  7. 3:20:56Personal agents could reduce apps to APIs4 min
  8. 1:28:45Insurance agents can learn repetitive tasks in legacy systems4 min
“I'm not competing against, you know, China or or other countries for, like, open weight, you know, sovereign language models that that people can own and deploy themselves.”
LALucas Atkinsat 2:09:45 · TBPN
2:09:45

Takeaways

  1. Atkins frames the competition as a contest between research labs.
  2. Open weights can build community and customer adoption.
  3. Larger models can support products that are harder to host independently.

About this segment

Lucas Atkins says the competition is against skilled researchers and labs, not China as a country. He explains how larger open-weight models can support product ecosystems and revenue.

LA

Lucas Atkins

CTO, Arcee AI

  • John Coogan, Host · Co-host, TBPN

    Co-founded Soylent and Lucy; OpenAI bought his show TBPN in April 2026.

  • Jordi Hays, Host · Co-host, TBPN

    Founded Branded Native; co-founded fintech Capital, which Rho bought.

From “🦞 Moltbot / Clawdbot Creator Peter Steinberger, Palmer Luckey, and more”, Jan 27, 2026. Watch the full episode

Transcript

From the transcript TBPN publishes with the episode.

  1. 2:08:32

    So Yeah. Yeah. Take us through the landscape of who you're competing with. Set the table for us so most people will be familiar with Deepsea, Quen. Like, how are these companies resourced? Is this just China's national interest that they're funding these? Do they have good business flywheels at this point? Because I imagine you have a plan to sort of unseat them Mhmm. In in the open source race.

  2. 2:09:00

    There you know, there's a lot of rumors about how all of you know, how all of this capital gets allocated into, you know, these different companies. Rumors. Hedge files. Well, there's rumors that the government's giving it to them, they have favorites, you know, there's shady deals going on, but the reality of Wait, it

  3. 2:09:19

    you're saying they didn't train the models with scraps in a cave? In a cave? No. No. Well, actually, frankly, if you look at kind of the horsepower that we're dealing with, a lot of them, you know, seemingly did. It's very impressive. That's that's that's kind of the you know, you want there to be this kind of battle of, you know, The US versus China in this race. That obviously plays into our incentives. Yeah. However, they these are extremely talented labs. And so when it's I'm not competing against, you know, China or or other countries for, like, open weight, you know, sovereign language models that that people can own and deploy themselves.

  4. 2:10:02

    I'm competing against, like, the other researchers there, like, the Sure. You know, that human being, and and you have some extreme talent. So, yes, it used to be really hard to make money making open source models. As they got bigger and as they got harder for other people to host themselves, it you know, the the the the systems and the economics started to work out because they get the, you know, the community buy in and excitement of something being open source. But if it's a trillion parameters, you know, your average consumer is not gonna be able to run that on their toaster. Right?

  5. 2:10:37

    So it it ends up you kind of get this win win situation. And now that that has kind of started to flywheel, they've started to, you know, do the OpenAI and the Anthropic and the Google Play where they're building products around it. And and it's really becoming a very lucrative ecosystem.

  6. 2:10:56

    Yeah. How are you scaling the business? What have you chosen in sort of the business model world? There's there's so many ways that you can build around open source technologies. What's working and what are you thinking about the road map long term?

  7. 2:11:14

    There's we we were in kind of a uniquely a unique a very fortunate position when it came to this. We had always been customizing models for people. We had always been working for, you know, enterprises, developers, businesses. How can we, you know, make sure that they're getting the best out of their own hardware? The only thing that really changed was that when customers wanted something to be based in The United States or from The United States, there stopped being competitive options.

  8. 2:11:42

    Sure. And we never really liked the idea that, like, the foundation of our business relied on other people releasing models. Yeah. So it was, like, six months ago that we we kind of fully decided, hey, you know what? Let's try it. Yeah. And and we had success with our first model and then our second, our third, and it it kind of, you know, brought us to this. So the economics of our business doesn't change so much. You know, we're still working with customers. We're still delivering, you know, models and and and powerful tools, though we have a much more robust control of the stack, which means that the degree to which we can customize and and and the kind of period in training that we can go back to for those customers just kind of Yeah.

  9. 2:12:25

    Increases drastically. So