Speakers in the public record
Claim mix
belief 8evaluation 1prediction 1commitment 1
Evidence policy
Every row below preserves an exact excerpt. Identified speakers are linked; unresolved voices are labeled and excluded from people counts.
Claim ledger
The useful parts, with receipts.
11 published records
“I think at the end of the day, like, you know, for people to be convinced, you have to show them something that they didn’t think was possible.”
- Speaker
- Not verified from transcript
- Publisher
- Latent Space
“You know, as we mentioned, like I think at the very beginning is the goal with the product has been to, you know, address what the models don’t on their own.”
- Speaker
- Not verified from transcript
- Publisher
- Latent Space
“General pattern, I think, in like in trying to design things that are smaller, you know, like it’s easier to manufacture at the same time, like that comes with like potentially other challenges, like maybe a little bit less selectivity than like if you have something that has like more hands, you know, but the yeah, there’s this big desire to, you know, try to design many proteins, nanobodies, small peptides, you know, that just are just great drug modalities.”
- Speaker
- Not verified from transcript
- Publisher
- Latent Space
“In my opinion, all the people we basically talk about feel that this sort of like in the wet lab or whatever the appropriate, you know, sort of like in real world validation is the whole problem or not the whole problem, but a big giant part of the problem.”
- Speaker
- Not verified from transcript
- Publisher
- Latent Space
“The ranking model ends up finding something it really likes. And so I think our ability to get better at ranking, I think, is also what’s going to enable sort of the next, you know, next big, big breakthroughs.”
- Speaker
- Not verified from transcript
- Publisher
- Latent Space
“You know, we have a Slack community that has like thousands of people on it. And it’s actually like self-sustaining now, which is like the really nice part because, you know, it’s, it’s almost overwhelming, I think, you know, to be able to like answer everyone’s questions and help.”
- Speaker
- Not verified from transcript
- Publisher
- Latent Space
“On the other hand, kind of going to your question of, you know, why do we care about, you know, how the protein falls or, you know, how the car is made to some extent is that, you know, sometimes when something goes wrong, you know, there are, you know, cases of, you know, proteins misfolding.”
- Speaker
- Not verified from transcript
- Publisher
- Latent Space
“And there’s a lot of like healthy skepticism in the field, which I think, you know, is, is, is great. And I think, you know, it’s very clear that there’s a ton of things, the models don’t really work well on, but I think one thing that’s probably, you know, undeniable is just like the pace of, pace of progress, you know, and how, how much better we’re getting, you know, every year.”
- Speaker
- Not verified from transcript
- Publisher
- Latent Space
“One thing I was thinking about with regards to infrastructure, like in the LLM space, you know, the cost of a token has gone down by I think a factor of a thousand or so over the last three years, right?”
- Speaker
- Not verified from transcript
- Publisher
- Latent Space
“One of the critical kind of, you know, beliefs that we had, you know, also when we started working on Boltz 1 was sort of like the structure prediction models are somewhat, you know, our field version of some foundation models, you know, learning about kind of how proteins and other molecules interact.”
- Speaker
- Not verified from transcript
- Publisher
- Latent Space
“I do still think, and we will continue to put a lot of our models open source because the critical kind of role.”
- Speaker
- Not verified from transcript
- Publisher
- Latent Space