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…e you, like all my customers are saying. I want this, there’s all these problems with the model. Yeah, yeah. But my customers don’t care, right? So like, how do you, how do you think about that? Yeah. So I would say a couple of things. One is, you know, part of our goal with Bolts and, you know, this is also kind of established as kind of the mission of the public benefit company that we started is to democratize the access to these tools. But one of the reasons why we realized that Bolts needed to be a company, it couldn’t just be an academic project is that putting a model on GitHub is definitely not enough to get, you know, chemists and biologists, you know, across, you know, both academia, biotech and pharma to use your model to, in their therapeutic programs. And so a lot of what we think about, you know, at Bolts beyond kind of the, just the models is thinking about all the layers. The layers that come on top of the models to get, you know, from, you know, those models to something that can really enable scientists in the industry. And so that goes, you know, into building kind of the right kind of workflows that take in kind of, for example, the data and try to answer kind of directly that those problems that, you know, the chemists and the biologists are asking, and then also kind of building the infrastructure. And so this to say that, you know, even with models fully open. You know, we see a ton of potential for, you know, products in the space and the critical part about a product is that even, you know, for example, with an open source model, you know, running the model is not free, you know, as we were saying, these are pretty expensive model and especially, and maybe we’ll get into this, you know, these days we’re seeing kind of pretty dramatic inference time scaling of these models where, you know, the more you run them, the better the results are. But there, you know, you see. You start getting into a point that compute and compute costs becomes a critical factor. And so putting a lot of work into building the right kind of infrastructure, building the optimizations and so on really allows us to provide, you know, a much better service potentially to the open source models. That to say, you know, even though, you know, with a product, we can provide a much better service. I do still think, and we will continue to put a lot of our models open source because the critical kind of role. I think of open source. Models is, you know, helping kind of the community progress on the research and, you know, from which we, we all benefit. And so, you know, we’ll continue to on the one hand, you know, put some of our kind of base models open source so that the field can, can be on top of it. And, you know, as we discussed earlier, we learn a ton from, you know, the way that the field uses and builds on top of our models, but then, you know, try to build a product that gives the best experience possible to scientists. d earlier, we learn a ton from, you know, the way that the field uses and builds on top of our models, but then, you know, try to build a product that gives the best experience possible to scientists. So that, you know, like a chemist or a biologist doesn’t need to, you know, spin off a GPU and, you know, set up, you know, our open source model in a particular way, but can just, you know, a bit like, you know, I, even though I am a computer scientist, machine learning scientist, I don’t necessarily, you know, take a open source LLM and try to kind of spin it off. But, you know, I just maybe open a GPT app or a cloud code and just use it as an amazing product. We kind of want to give the same experience. So this front world. I heard a good analogy yesterday that a surgeon doesn’t want the hospital to design a scalpel, right? So just buy the scalpel. You wouldn’t believe like the number of people, even like in my short time, you know, between AlphaFold3 coming out and the end of the PhD, like the number of people that would like reach out just for like us to like run AlphaFold3 for them, you know, or things like that. Just because like, you know, bolts in our case, you know, just because it’s like. It’s like not that easy, you know, to do that, you know, if you’re not a computational person. And I think like part of the goal here is also that, you know, we continue to obviously build the interface with computational folks, but that, you know, the models are also accessible to like a larger, broader audience. And then that comes from like, you know, good interfaces and stuff like that. I think one like really interesting thing about bolts is that with the release of it, you didn’t just release a model, but you created a community. Yeah. Did that community, it grew very quickly. Did that surprise you? And like, what is the evolution of that community and how is that fed into bolts? If you look at its growth, it’s like very much like when we release a new model, it’s like, there’s a big, big jump, but yeah, it’s, I mean, it’s been great. You know, we have a Slack community that has like thousands of people on it. And it’s actually like self-sustaining now, which is like the really nice part because, you know, it’s, it’s almost overwhelming, I think, you know, to be able to like answer everyone’s questions and help. It’s really difficult, you know. The, the few people that we were, but it ended up that like, you know, people would answer each other’s questions and like, sort of like, you know, help one another. And so the Slack, you know, has been like kind of, yeah, self, self-sustaining and that’s been, it’s been really cool to see. each other’s questions and like, sort of like, you know, help one another. And so the Slack, you know, has been like kind of, yeah, self, self-sustaining and that’s been, it’s been really cool to see. And, you know, that’s, that’s for like the Slack part, but then also obviously on GitHub as well. We’ve had like a nice, nice community. You know, I think we also aspire to be even more active on it, you know, than we’ve been in the past six months, which has been like a bit challenging, you know, for us. But. Yeah, the community has been, has been really great and, you know, there’s a lot of papers also that have come out with like new evolutions on top of bolts and it’s surprised us to some degree because like there’s a lot of models out there. And I think like, you know, sort of people converging on that was, was really cool. And, you know, I think it speaks also, I think, to the importance of like, you know, when, when you put code out, like to try to put a lot of emphasis and like making it like as easy to use as possible and something we thought a lot about when we released the code base. You know, it’s far from perfect, but, you know. Do you think that that was one of the factors that caused your community to grow is just the focus on easy to use, make it accessible? I think so. Yeah. And we’ve, we’ve heard it from a few people over the, over the, over the years now. And, you know, and some people still think it should be a lot nicer and they’re, and they’re right. And they’re right. But yeah, I think it was, you know, at the time, maybe a little bit easier than, than other things.…

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