The Information's TITV
00:53:07 · Stephanie Palazzolo, Nicole Su, Brittany Greenfield, Jessica Lessin
[00:53:07] S0: it comes to diligence process for investors. And you mentioned two things. You mentioned these kind of like multiple tranche rounds that we've written about where, you know, maybe the headline number is 3,000,000,000, but actually investors got in at 1,000,000,000 and 2,000,000,000 and 3,000,000,000. And you also mentioned maybe there are some other terms that are more investor friendly. What are some examples of these like other terms that are, you know, maybe more friendly to investor that you're seeing? [00:53:29] S3: Maybe the the most common example will be warrants. I think a lot of them will come with pending warrants. I think that would be a good concrete example to give. I think others is too bespoke to really talk about. [00:53:41] S4: Mhmm. Mhmm. [00:53:41] S0: And are are these signs that power is shifting over at all to investors? Or do you think the power still lies in the hands of the founders for these hot rounds? [00:53:50] S3: It still totally depends. I think quality of the investors, quality of a team, right, the scarcity of the assets, it all depends. [00:53:59] S0: And you mentioned that there's both FOMO, but also investors are trying to be more disciplined. Does it feel like any part of the market right now is especially overvalued or certain parts of the industry? Like, what do you think is the most overvalued these days? Tough question. [00:54:16] S1: You can't say everybody is.
00:54:16 · Jessica Lessin, Nicole Su
[00:54:16] S1: You can't say everybody is. [00:54:18] S3: But but at the same time, I do think from my seat, right, I'm seeing up and down the AI stack, but also vertical apps as well. I think what I'm seeing is I'm seeing a lot of companies, particularly in the application layer, they have tremendous growth. But if you look under the hood, right, how much they own when it comes to intelligence and how do actually have a flywheel of intelligence as they accumulate more customer data. And then what's really the sustainable business model and a sustainable moat that can defend, right, as frontier models also getting more specialized? I think that's a big question mark. So I think I'm excited to see, like, how these vertical apps companies that would, you know, really come up on the curve and come to getting a sustainable business model can drive profitability alongside of growth. Mhmm. And that's one. And then the other one is everybody's favorite topic these days is physical AI. I think it's really because the promise that, you know, bringing generalized AI into the physical world is huge. The TAM is much bigger than what we're doing in this digital AI world. But I think it's also, again, it's the difference between the expectation of how big the TAM is and the pace it's going to take to actually unlock that TAM. I think we're still in very early days when it comes to building general purpose robotics models. A lot of promising progress, but I think we haven't reached the tragedy moment anytime soon.
00:55:44 · Stephanie Palazzolo, Nicole Su
[00:55:44] S0: And I feel like, you know, speaking of physical AI and the world of, you know, robotics and all that craziness, I feel like there is a bigger debate now between, you know, like there have been some studies that have shown that actually the general language models are actually pretty good at maybe directing robots better than people expected. I guess I'm curious, do you feel like there's still a strong argument for, you know, robotic specific models versus everything just being controlled by, you know, general language models? [00:56:16] S3: I think the reasoning part, I think, is totally transferable. I think it's more about interaction with the physical world and especially when it comes to specific form factors, because I'm seeing really good progress when it comes to robotics model architecture evolution, right? We started with the BLM and VLA and our world models allow people to predict the future, but at the same time, like we are missing previously, like inputs like tactile data, but I've seen some of these leading research teams have started publishing paper about how they actually were able to integrate all this tactile data into their foundational model that has all the elements of LLM for reasoning, L VLA for, like, interaction between vision and action, but also word model for prediction. So I'm seeing... I think it's gonna be a combination of all these model architecture to work together to unlock the physical AI world. Yeah. So kind of like
00:57:07 · Stephanie Palazzolo, Nicole Su
[00:57:07] S0: what you're saying, maybe today's reasoning models would be good at deciding what next step to take. But when it comes to, you know, how hard should I grip something or like what does it mean for a robot to pick up a glass of water off the table? That is something that's so niche that it's not really captured yet in language models, it seems. I see. You know, switching gears a little bit, we talked a bit about apps and physical AI. You know, one area that's gotten a lot of investment is infrastructure, data centers, chips, that whole area, right? So it feels like up until maybe the last couple of months, that was a very obvious area of investment. But I think maybe more recently, there's been questions about, you know, how much debt can these companies take on? There's been IPOs getting delayed. [00:57:48] S3: Do you [00:57:49] S0: feel like there's a turning point coming for these startups when it comes to how enthusiastic investors are about them?
00:57:49 · Stephanie Palazzolo, Nicole Su, Jessica Lessin
[00:57:49] S0: feel like there's a turning point coming for these startups when it comes to how enthusiastic investors are about them? [00:57:57] S3: I'm definitely seeing a change in terms of valuation levels for these type of companies. Obviously, early days when there is definitely secrecy in terms of the investable opportunities in the public market, some of these companies, you know, definitely rode the boom of AI infra build out. I think now it's really more about the heightened or increased investor awareness when it comes to the risks associated with cost of capital as well as the ability to execute. So I think many of these businesses, the fundamentals didn't change, right? But it only changes how investors started changing their way to value these companies. [00:58:31] S1: And [00:58:31] S0: I guess what are investors so worried about now when it comes to these, you know, I mean, there's a whole bunch of them. There's obviously the Neo Clouds. There's the companies that are building the data centers. Like, is there something specific that they're worried about now versus maybe a couple months ago?
00:58:45 · Nicole Su
[00:58:45] S3: I think it's what's really interesting, like from my seat, I'm definitely seeing I think we all see there is a huge demand for compute. Like, we don't need to debate that. And then there is also a huge wave of new companies being formed and trying to become neo cloud and who all need a capital injection. So you can see there's a big gap of, yes, there's a huge need to compute, in shortage for sure. And yes, there's a bunch of people who really want to start building out this compute. They have access to a specific piece of powered land or they have something they have unique access. But the really missing link is that we don't really have the capital today to breach this. I think investors historically has become very used to financing customer offtake contracts. The reason why they are willing to lend is because of the quality of their customers, right? Most of the time, these are hyperscalers. However, we're in this next wave of, hey, a lot of AI compute demand is coming from AI native companies or new labs where like there is no really truly rated credit for any of these companies. So I think lenders are definitely become more and more cautious when it comes to companies who are actually serving that bunch of companies. So I'm seeing that, I guess, the missing link is very much like the investors' willingness to back these type of companies and the level of risks they are willing to take, and then the costs come come with that.