Latent Space: The AI Engineer Podcast
00:31:15 · Fabian Theis
[00:31:15] S0: I I very much agree that these funding models very much matter for the flexibility, but also the set of teams that you can set up and like the long term vision that you can have. So Helmholtz, this is not just Germany, but I would say maybe Europe's largest, what's called research organization in terms of funding. It has a different set of areas that it focuses on, health being one of the big ones, but then it has sort of material information sciences, physics, and so on. And essentially getting fed federal money to put into a deep research question. I've been building up what's called the computational health center at Helmholtz Munich, which I think has now something like maybe 45 group leaders and professors, and maybe 500 to 600 people now. So we are, I think, the largest academic place for health AI type of research in Europe, where we have people really working on all scales. Like, you know, I'm sort of focusing on the cellular scale, but, you know, there's people doing DNA foundation models. 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 to to intersect and to go virtual human and so on. But having said that, the key thing is in contrast to universities, that even though we all have affiliation to universities, mostly to the Technic University or the University of Munich, the two top ranked universities interestingly in the European Union. So we have this sort of place where we have these affiliations at universities. Right? But we don't have undergraduate teaching. We essentially just have PhD students and postdocs, but we interact very much with the universities and in particular also the clinics because you wanna have sort of this translational thing in there. And increasing... That's maybe an interesting link. So this is maybe a bit similar to NIH type of models like in US, but sort of distributed all over the country, not just sort of in one place.
00:33:00 · Fabian Theis
And maybe the one interesting link is that increasingly the government and this sort of realization also in in Germany is is sort of dawning that there needs to be much stronger transfer component, not just by going into translation to universities, but also in into sort of value creation outside of the academic realm, which is obviously going so more more into startups and so on, which I think the Boston environment has always been one of the key examples, but now, of course, more so now also the the the Bay Area when, you know, recently I was visiting, I believe maybe Genentech or colleagues, and we went to a restaurant, and then one of the waiters was asking us, hey, are you guys talking about AI and bio, you know, I have been also interested, so like everyone's sort of thinking about this startup ideas and so on, and I I kind of felt that's a it's a good environment, and this is something I think our PhDs are now more and more doing, and and we were sort of learning there, and I think also in terms of sort of value creation, Munich in particular is actually at least in Continental Europe, maybe the prime place now for VC capital, but also sort of deep tech, particularly the bio and and defense area sort of pretty exploding. So this stuff starts to work.
00:34:04 · Brandon Anderson
[00:34:04] S2: One thing... One... The thing you were talking about startup, I think, really fascinating. I've heard that Germany has had some issues with their startup ecosystem. It's it's had... It's difficult to create a startup there compared to even other places in Europe. How... Like, what is the competitive landscape for startups right now in Germany and specific... And how does Germany become more competitive broadly? I I have a vested interest in this because I'm I'm probably gonna get my German citizenship soon.
00:34:31 · Fabian Theis
[00:34:31] S0: Welcome. Let me know if you come come by Munich. So I think traditionally, Europe... But I would say definitely Germany is is quite bureaucratic, and processes are far from as digital as you would expect in different places. Not that I'm saying that US is maybe the best example for fully digitized processes, but stuff is definitely faster. The thing is people have realized that now, and I think the the particular startup creation and implementation is, I think, more than competitive in Germany versus Europe. It's actually sort of the the the prime number, and in particular, like some hotspots, Berlin, but in particular, Munich sort of the... I I think is is the capital for for an... Highest number of startups. And I think even nowadays, if you look into European Union, there's equally as many startups being created as in US. The thing is where Europe and particularly also Germany drops off is at the scaling part. So, you know, early VC and also sort of non dilutive type of money, this is there. But then when you go into scaling, these big VCs that sort of take these bigger risks are, I I think, not not closely as present. So I've I've I've saw this again and again that, you know, if you wanna sort of really go into the the sort of bigger tickets sort of series A and so on. The series B, you... People start going more into US also for that. But maybe I'm sort of simplifying here, but this is at least my current learning, Brenner.
00:35:44 · Brandon Anderson
[00:35:44] S2: Okay. You are on the board or I guess part of several local startups. Right? What what does it take to go from, you know, idea to creating a, you know, to creating a new startup in Germany?
00:35:56 · Fabian Theis
[00:35:56] S0: I I don't if if if you heard that the European Union tries to regulate a whole bunch of stuff, and that can be sometimes an advantage. You know, it's kind of cool, like, you know, all across Europe we can now go with a mobile phone. You might have heard that everyone needs to have USB C, things now for their mobile phones. This kind of kind of cool stuff. So there's some some good stuff coming. But then of course there's something like things like the AI act and so on that make things a tad more complicated. Luckily, not yet for research, but you know, for data access across hospitals and so on, there's some, you know, and we were talking about about health deep tech type of stuff, right. So there's some, systems that I think fantastic in Europe, and I'm thinking about Finland, you know, Finjan, Denmark, and so on with this sort of very detailed description of the population in terms of sampling, getting medical records connected far better than... I mean, of... US is also similar to MS, like like in terms of sort of getting all the systems sort of to talk to each other. Like, when patients, you know, sort of go to to different states in US, it's 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 Dataspace, where in... Back maybe next two years, these things need to be sort of going across boundaries. You need to sort of start building these these health record type of combinations. So I do think divisions are starting to happen, but the scale is is not as fast. So I think what you need for a tech startup, what I noticed is is always the biggest thing is you need to have the best team for that. And you know, we have professors and and PIs that really think about this. So for example, for for the department that I called it at, I said, guys, every every PI of a group we don't expect you to at least have one one one spin off in in in the next three years. Let's see how that works. Right? But you sort of you sort of get people a bit a bit on that track. I But think this is happening very much from a bottom up nowadays anyway, where the students are actually pushing for that.