Fabian Theis
Guest on Latent Space: The AI Engineer Podcast. 216 claims across 1 episode, Nov 2026.
Positions over time
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Predictions, in their words
As stated, each with its moment. A date appears only where the speaker gave one.
“Suddenly here you can maybe ask some evolutionary questions that you couldn't before. Not that we can do this so well, it's not our core expertise, but you know, sort of you can start doing these fancy, um, sort of cross-species, cross-tissue type of latent spaces.”
Expects: Cross-species, cross-tissue latent spaces may enable researchers to ask new evolutionary questions. · no date given · not yet resolved
“A lot of people then start throwing around robotics and so on as well, but I, I think that's a tad too early 'cause the, the cycle times in terms of our assays are still a bit on the long side. But I do think this will come.”
Expects: Robotics will become relevant for laboratory experimentation in the future. · no date given · not yet resolved
“Because I, I'm quite convinced that we need to go to multicellular systems to have actually really interesting readouts. But I think everyone is scaling this, these, these levels up, and at some point, you know, we're gonna go maybe even to human genetics as a perturbation.”
Expects: Human genetics may eventually be used as a perturbation. · no date given · not yet resolved
“So I think in the future, the bigger part, at least of the sort of more used models, will be those more flexible, very much data-based ones where you then a posteriori put the interpretation on top.”
Expects: Most more widely used models will be flexible and data-driven, with interpretation applied after training. · no date given · not yet resolved
“So I think in the future, the bigger part, at least of the sort of more used models, will be those more flexible, very much data-based ones where you then a posteriori put the interpretation on top.”
Expects: The speaker expects that, in the future, most widely used models will be flexible and data-driven, with interpretation applied after training. · no date given · not yet resolved
“And for these of course there's not so much at least inductive biases and issues. So I, I do think we're gonna, gonna hit this regime actually quite soon and we do see this also in a few papers.”
Expects: The relevant scaling regime will probably be reached quite soon; the speaker says a few papers already show it. · no date given · not yet resolved
“Or choice of the metric. Yeah, and I, I think that they could-- you can discuss it. At some point, we're gonna have agents sort of trying out all kind of combinations of whatever algorithmic thing you can come up with.”
Expects: The speaker expects agents eventually to test many combinations of possible algorithms. · no date given · not yet resolved
“And of course, then there's also this angst that at some point, like Astra 2.0 might be doing parts of this already anyway, yeah.”
Expects: Astra 2.0 might already perform some of this work. · no date given · not yet resolved
“And, you know, obviously the, the ultimate vision being that we want to RL everything. We want to do RL also in, in, in, in this loop. It's a bit out there, but you know, I think we're, we're slowly getting there.”
Expects: Fabian Theis's long-term vision is to apply reinforcement learning throughout the laboratory experimentation loop, though he says this remains a distant goal and progress is gradual. · no date given · not yet resolved
“I do think that there's a whole bunch of reasons why we're gonna see that sort of scale up from all these models working well in terms of being generative, but also sort of lab in the loop on the molecule level now being exported and sort of really working one level up on, on, on the cell level.”
Expects: Fabian Theis expects generative models and molecule-level lab-in-the-loop approaches to scale up to work at the cell level. · no date given · not yet resolved
All 14 predictions
“There's a whole bunch of cancer systems, but you know, also for, let's say, if you wanna study diseases with hard to acquire material, let's say you wanna look into the genetics of some type of, of neurodegenerative diseases or so. Like typically it's very hard to get access to tissue, right? So you take stem cells from the sk-- you take cells from the skin, differentiate them, make-- turn them into these mid little brains, and then you can potentially study some, some things there.”
Expects: Organoids may enable research on diseases, including neurodegenerative diseases, when the relevant tissue is difficult to obtain. · no date given · not yet resolved
“There's people sort of doing interesting things on protein design. There's people doing, like, you know, patient cohort type of representation, genetics and so on. And now you sort of can start putting them together, and one of our big visions is sort of to, to intersect and to go virtual human and so on.”
Expects: The center will integrate its research areas toward creating a virtual human. · no date given · not yet resolved
“Like when patients, you know, sort of go to, to different states in US is similar as in Germany, when they go to different places, it's like very hard to build patient trajectories, right? But there are some places that know how to do this, and there's a thing like the European Union tells you, it's called the European Health Data Space, where in like maybe next two years, these things need to be sort of going across boundaries.”
Expects: The European Health Data Space is intended to enable health data to be shared across borders, perhaps within the next two years. · 6 Nov 2026 – 6 Nov 2028 · not yet resolved
“We haven't really spoken so much about it, right? But once you have these perturbation world models, you can actually go back and drive the experiments, right? So I do think computational startups can be very good also data generation, and I think this is what will be also turned not just into nice papers, which is sort of mostly our business, but also I think in this next generation of startups.”
Expects: Computational and data-generation work will be commercialized by a next generation of startups, rather than being limited to publication as research papers. · no date given · not yet resolved
Appearances
Claims per episode
- 6 Nov 2026Controlling Biology - Fabian Theis, Helmholtz MunichLatent Space: The AI Engineer Podcast · guest