Alex Rives (Head of Science at Chan Zuckerberg Biohub) discusses the technical shortcomings of existing cellular foundation models.
Assertion Supported
ESMC model search generates novel antibodies achieving therapeutic-grade binding affinity levels
“What we're able to see is that, you know, you can search ESMC and you can actually find antibodies that are reaching the level of affinity that are, I should say, are really at the level of affinity that is needed for therapeutic function and activity.”
Assertion Supported
Rives: ESMC is state of the art among open models for multimer prediction
“Yeah, I mean, I think we're state of the art for open models.”
Prediction Not checkable as stated
AI cell simulations will enable parallel reasoning across millions of biological hypotheses
“We're gonna have increasingly capable and accurate digital representations of molecules, genomes, cells, ultimately physiology. That's where you want to get. We're gonna have to go up that, that complexity scale, the levels of biological complexity that requir…”
Insight
Rives: Curing disease requires personalized computational models, not conventional pills
“What is, you know, what is the cure to disease look like, right? It's not a pill, right? It's not a medicine in the conventional sense. You know, it's going to have to be a system that is capable of modeling and understanding, you know, the underlying physiolo…”
Assertion Not checkable as stated
Scaling protein models by orders of magnitude unlocks emergent biological capabilities
“So our team has really explored that idea over a number of different years, and we've really kind of, I think, seen the scaling curve and really seen as we have increased models by an order of magnitude kind of in each generation that, you know, there's this e…”
Assertion Supported
Sparse autoencoders found a single learned feature for nucleophilic elbows in ESMC
“You know, what we found basically is that the model has a kind of a single feature for this nucleophilic elbow and is activating across these like very evolutionarily diverse families, you know, really completely different structural topologies, proteins that …”