Evidence receipt / recommendation
Published · transcript-backedMentions personal use of Opus. Mentions personal use of Fable. Mentions personal use of Soul. Mentions personal use of Kimi k three.
8 Aug 2026 The Cognitive Revolution Thinking in Silico: Goodfire CTO Dan Balsam on Concept Manifolds & a $1000/Month ML Research Agent
“Like, I use Opus and Fable and Soul and Kimi k three for different things. And we've done we like, we've built the interpretability infrastructure and the training infrastructure, which is now all in our product,”
Source trail
Everything needed to verify it.
- Speaker
- Dan Balsam
- Attribution
- Verified speaker
- Claim type
- recommendation
- Recorded
- 8 Aug 2026
- Publisher
- The Cognitive Revolution
Transcript context
…We'll come back to this probably toward the end. I have some kind of zoomed out big picture questions for you. One of the challenges obviously with, like, trying to develop techniques that you wanna hopefully will be relevant at the frontier is there's not too many open weights models that you can hack on that have the intensity of RL that is going on at the Frontier Labs, which is leading to these colorful problematic behaviors that we're seeing. But at the same time, it also, like, really amazes me over and over again that astounding work, including the the Cameron Berg paper that I think about all the time about the anti correlation between deception and role playing features and claims of subjective experience. Lawn Llama three three seventy b, and that's, like, two years old. So are you guys able to see features that you think are kind of the relevant features that are leading to these, like, relentless hacking behaviors? Well, I think that's that's an active area of of study for us. Yeah. And something that we hope to publish more on in the future. For what yeah. For what it's worth, like, I actually think the gap between open and closed models has shrunk, like, quite considerably. I use Kimi k three. Like, I use Opus and Fable and Soul and Kimi k three for different things. And we've done we like, we've built the interpretability infrastructure and the training infrastructure, which is now all in our product, which lets us…
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