Everything Jeremy Wohlwend said on any show that made the record, most notable first. Each card names its show and opens the statement there.
AI Excels at Structure Prediction but Fails to Model Physical Folding
“Folding is the more complex process of actually understanding, like, how it goes from, like, this disordered state into, like, a structured, like, state, and that I don't think we've made that much progress on, but the idea of, like, yeah, going straight to th…”
Structure Prediction Models Degrade Without Co-Evolutionary Sequence Data
“What it implies also is that, you know, in absence of that co-evolutionary landscape, the models don't quite perform as well.”
ML Folding Models Only Possess Localized Understanding of Physics
“I think one of the thing, at least I believe is that once you're in that sort of approximate, you know, area of the solution space, then the models have like some understanding, you know, of how to get you to like, you know, the low energy low energy state. An…”
Compute Constraints Forced Boltz-1 to Train Once With In-Flight Bug Fixes
“And actually we only trained the big model once. That's how much compute we had. We could only train it once. And so like, while the model was training, we were like finding bugs left and right. A lot of them that I wrote. Yeah. And like, I would, I remember l…”
Models Excel at Monomeric Proteins but Struggle on Other Biomolecular Modalities
“And, you know, we've seen in some of the latest GASP competitions, like, while we're becoming really, really good at proteins, especially monomeric proteins you know, other modalities still remain pretty difficult.”
Current Models Fail to Predict Protein Conformational Dynamics and States
“Proteins are not static. They move, they take different shapes based on their energy states. And I think we are also not that good at understanding the different states that the protein can be in and at what frequency, what probability.”
Pairwise Representation Mechanisms Have Survived Since AlphaFold 2
“And yeah, I think too, it's really survived the test of time. I mean, you know, this thing came out in 20, 21 and it's largely the same. I mean, there's been this change to the structure module that's been like largely simplified, but where a lot of the magic …”
LLMs Need Massive Parameters for Memorization, Unlike Biology Models
“Part of the reason the LLMs are so large isn't just because of their reasoning capability, but it's also because of, like, the sheer quantity of information that they store. And I think here there's a little bit less of that, you know, and I think it's more ab…”
Structure Generation Reduces to a Ranking Problem When Sampling Is Scaled
“If you can sample a ton and you assume that, like, you know, if you sample enough, you're likely to have, like, you know, the good structure, then it really just becomes a ranking problem.”
Demand for Smaller Protein Modalities Is Driven by Manufacturing Ease
“There's a general pattern. I think in a, 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 yo…”
Boltz Will Cede Discovered Molecules Rather Than Develop Therapeutic Drugs
“When we say we have no interest in making Dress, we're serious. Like, you know I mean, when it was with the academic labs, basically the, you know, it was, they keep it, they do whatever they want with it. And with the CRO so far, yeah, we've been very, yeah, …”
Alternating Atomic and Token-Level Modeling Enabled AlphaFold 3 Small Molecules
“The other part, I think that's enough for three is sort of this moving away from modeling just at the amino acid level to actually sort of having the model sort of alternate between you know, sort of atomic resolution modeling and then more like it's got token…”