A World Model of Life: Biohub's Alex Rives on Virtual Cells, Measurement, & the $1.8B Data Push

Nathan Labenz (0:00)

Hello, and welcome back to The Cognitive Revolution. Today, my guest is Alex Rives, formerly co-founder and chief scientist at Evolutionary Scale, makers of the ESM series of models, and currently head of science at Biohub. The Chan Zuckerberg Initiative backed Moonshot with the inspiring mission to cure or prevent all disease, which just announced a $1.8 billion expansion of the Virtual Biology Initiative. A day to generation effort that brings together the Department of Energy, the NIH, Google DeepMind, Isomorphic and Meta. I opened by asking Alex what curing all disease means to him, and if I should expect to live much longer than the standard human lifespan. Calling himself a practical person in response, Alex described not immortality, but a world without cancer, without infectious disease, and without chronic or degenerative conditions.

From there, we get Alex's perspective on why today's virtual cell models have not revolutionized medicine. The heart of the issue, Alex says, is that our ability to observe what matters in biology is still very limited by the measurement technology we have available. As a result, we simply don't have the quality of data needed to represent the fine-grained causal structure that models presumably would be very happy to learn. Better architecture is built on clever inductive biases can help make the most of scarce data, such as in the extremely thoughtful use of physics in alpha-fold style models. And we do see real progress in next-token modeling of the biological code. But the available data is still failing to capture critical information about how cells and tissues work. It's on this basis that Biohub is investing so heavily in data. By opening new modalities, as they did with the laser phase plate, and advance in microscopy that's allowing scientists to begin to see directly how individual proteins and other macromolecules interact inside the cell. And also by systematically building cell atlases that link molecular and imaging datasets across hundreds of billions of cells, representing both healthy and diseased states.

The goal over the next few years is to build an information theoretic model of the cell, which effectively encodes the physical programs that run life. Starting with a transition function that takes a cell or tissue state and a set of inputs and predicts a distribution of cell states at the next time stamp. Ultimately building toward what Alex calls a world model of life.

This of course would support the use case that I always dream of, which is answering the question, how do I push a pathological state back to a healthy one? Or in other words, how do I effectively treat this disease?

Along the way, Alex describes how the LLM training paradigm applies to biology. His vision for RLVR for biology with lab verification. He reacts to my proposal for a million Brian Johnson's, and he ponders whether biological and language-latent spaces will ever become deeply fused or will remain separated by tool calls. Noting that things we most want to know about biology today are novel concepts for which we don't yet have words and names.

Finally, I asked Alex how he tracks his own health. He answered that he's so focused on Biohub research that he barely thinks about it. Which surprised me until I considered that if he and the Biohub team are successful in creating the data layer needed to train the highly generalizable BioFoundation models, a little bit of timely, relevant personal health context might indeed be all you need. With that, I hope you enjoy this look ahead toward a world model of life. With Alex Rives, Head of Science at Biohub. Alex Rives, Head of Science at Biohub. Welcome to The Cognitive Revolution.

Alex Rives (4:03)

Thank you. Great to be here, Nathan.

Nathan Labenz (4:05)

Yeah, I'm excited for this conversation.

Let's start with the big picture. Biohub has this grandiose mission, which I'm excited about, of curing all diseases. What does it mean to you? Should I think of that as synonymous with another phrase people sometimes use as solving biology? Should I think of it as applying to aging? Are we living forever in your vision of the future? How grand is this vision ultimately get?

Alex Rives (4:30)

Yeah, that's a great question. How do we define this? Well, I think I'm a practical person. So I think about what is going to be possible in a realistic time frame. I think a good place to set our sights is to say that what we want to do is really live in a world without disease. What would that mean? That would mean a world where there's not cancer, a world where there's not infectious disease, a world where there is not chronic disease or degenerative disease or all the kinds of afflictions that have been really fundamental to the human condition for a very long time.