Evidence receipt / belief
Published · transcript-backedMark Bissell: belief
6 Feb 2026 Latent Space The First Mechanistic Interpretability Frontier Lab — Myra Deng & Mark Bissell of Goodfire AI
“I think the reason why post-training is a place where this makes a lot of sense is a lot of what we’re talking about is surgical edits.”
Source trail
Everything needed to verify it.
- Speaker
- Mark Bissell
- Attribution
- Verified speaker
- Claim type
- belief
- Recorded
- 6 Feb 2026
- Publisher
- Latent Space
Transcript context
…I think so. Yeah. Yeah. I think that’s certainly one of the use cases. I think. Yeah. Yeah. I think the reason why post-training is a place where this makes a lot of sense is a lot of what we’re talking about is surgical edits. You know, you want to be able to have expert feedback, very surgically change how your model is doing, whether that is, you know, removing a certain behavior that it has. So, you know, one of the things that we’ve been looking at or is, is another like common area where you would want to make a somewhat surgical edit is some of the models that have say political bias. Like you look at Quen or, um, R1 and they have sort of like this CCP bias. Is there a CCP vector?…
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