Thomas von Tschammer: evaluation

Transcript context

…How far does this go? Is there any limit to it? You know, I kind of imagine a, everything is an RL loop as kind of the end state. You know, you can imagine putting agents into every seat in the company. And again, we've, you know, keep in mind we're going to need some oversight for this, but in terms of, thinking kind of a first principles limit paradigm first, you could have product strategies, virtual market testing. There's increasingly models that in the same, general spirit as you have models that will validate the aerodynamics of your design, you can have models or scaffolds around foundation models that can sort of act as like virtual customer panels. So you could imagine, really from even the highest level, getting into a fast loop that's fed by RL, where you have at least a sufficiently good reward model to steer it in the right direction. And then that can kind of cascade all the way back, perhaps, right, to to the designs itself where you can imagine a not too distant future where I can sort of speak a perhaps rather complicated mechanical, electromechanical product into existence in a way that I can now like speak a video into existence. Do you see like any fundamental gaps in that vision? Like what, if anything, would prevent that from happening in five years' time? No, we didn't. I think the capabilities are there. The main question for big companies to implement that is infrastructure, governance, mostly, right, and data, obviously, making the data flows and it's at the right locations. In terms of capabilities today, we have the right piece of the post. I strongly believe so, and it's going to go even faster. the latest frontier models that are being developed, right? I don't see any reasons for it not to happen. Again, we won't break the physics. The physics will be there. That's why we need to have those two combination of tools that are grounded in physics. We talked about primical simulation solvers, right? They will be there and they will remain there. They will be the fuel essentially for these models in engineering, right? But I don't see any fundamental reasons for it, but they're happening quickly and actually quickly. Do you think humanoid robotics or robotics more generally is critical to this, especially on the unlocking the speed on the manufacturing side? I mean, I think there's a lot of different ways you could imagine unlocking more agility on the manufacturing side. How much do you think things like humanoids matter versus just kind of general intelligence that will also design the machine tools and, kind of bring all the same. You can kind of imagine the version that is like built on this. If humanoid robots are sort of the analogs of LLMs, you can imagine that's one kind of way that we get like crazy responsiveness from manufacturing. But maybe another is just that, again, the reasoning models bring all these same engineering paradigms to the machine tools themselves. And that, you know, is enough to kind of speed things up.…

Stored transcript either side of the excerpt. The highlighted words are the published quote; the surrounding text is unedited source, never generated.