Jeremy Wohlwend, co-founder of Boltz, discusses whether AI structure prediction models genuinely learn physics principles or rely on evolutionary hints to narrow the energy landscape search space.
Insight
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…”
Insight
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.”
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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…”
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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.”
Insight
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.”
Insight
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 …”