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Biohub's strategy is to couple a frontier AI lab with a frontier biology lab because the biological data needed for these models doesn't yet exist — it must be invented through new scientific approaches.

Mark Zuckerberg explains that unlike language models which can draw on abundant internet data, biology lacks sufficient existing data — so Biohub must invent new imaging, cellular engineering, and measurement techniques to generate the novel datasets needed for modeling proteins, cells, and whole biological systems. ✦ AI generated

Mark Zuckerberg · No Priors · 2026-06-10 · original ↗

plays this moment only · 4:10 — 5:45

The real focus and the unifying theme at this point is the virtual biology initiative around taking the unique data sets that are able to be generated in order to model, effectively starting with the smallest pieces of proteins, but then eventually cells and whole biological systems. ... You want to build a frontier AI lab, but you need to couple that with a frontier biology effort that can do the work of basically being able to understand and get the data that you need to actually be able to build these models. Because unlike language models, there's just like a lot of data out there on the internet. That's not really the case with biology. I mean, there are obviously a bunch of different data sets that exist that academia and scientists have generated over the decades. But a lot of the stuff that I think we want to put into this, it doesn't exist, right? It's like you want to be able to visualize things that people haven't been able to see before, which is why we're doing the imaging work. You want to be able to record things that are going on inside the body, which is why we're doing the kind of cellular engineering work. You want to be able to measure things like inflammation in ways that haven't been possible, which is why the Chicago Biohub is focused on building those kind of devices and being able to do that.

verbatim transcript · starts at 4:10

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