The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
00:39:21 · Harry Stebbings, Jason Lemkin, Rory O'Driscoll
[00:39:21] S2: What caused you to change your mindset? [00:39:22] S0: Because the the medical evidence for GLP ones is so... It's so profound. It's so for heart disease, for so many other things. And I think our ability to tailor drugs to extend longevity is the massive market. It's better than inference. You know, and if you talk to any just physicians at the cutting edge now, they're all saying to anybody like your hip or whatever, just don't hurt the other one. Like, just get there. Like in another couple of years, the amount of longevity we're gonna able to achieve is so much higher that I just think the wackos of the microdosers of SF and Brian Johnson made me skeptical, but just the overwhelming evidence of the benefits that almost everyone should be on the GLP-one, right? And the fact that we're going to get better and better at figuring all this stuff out. I mean, we're just walking sets of cancer and heart disease and other things that having material impacts will radically extend longevity, radically extend longevity. [00:40:14] S1: There's a whole sequence of steps before you even have adequately good molecule identification with some understanding of how it works, and then you still have all the different biophases. So as I say, I do believe it'll be harder to capture value than you think, but I'm really glad they're trying. Guys, I wanna talk
00:40:14 · Rory O'Driscoll, Harry Stebbings
[00:40:14] S1: There's a whole sequence of steps before you even have adequately good molecule identification with some understanding of how it works, and then you still have all the different biophases. So as I say, I do believe it'll be harder to capture value than you think, but I'm really glad they're trying. Guys, I wanna talk [00:40:29] S2: about one which may be a little bit earlier than usual, but we have Mecca, which is the MACRA or the surge for robotics data, physical world data that can be implemented in most often robotics. Raises 60,000,000 series b from Sequoia. The reason I wanted to bring it up is that, you know, we have micro AGI in Europe, which has posted race to a 100,000,000 very quickly. There's Macca, which is well over 100,000,000 in ARR. There's another provider that I'm forgetting the name of, XOFT or XO Soft or whatever it is, that's again over 100. And we just see the sheer volume of data providers over 100,000,000. What should we read, infer, analyze from this?
00:41:10 · Rory O'Driscoll
[00:41:10] S1: You can infer from data in general that Intropic and OpenAI spend a large amount of money on training data, as do the other three wannabe foundation models, And there's an entire industry that suffers to take care of that. It's an interesting business because you only have five or six large competitors, and they all obviously want to go on and sell to enterprises. But the vast, vast bulk of the dollars come from a relatively small number of enterprises. Yeah, those companies are going very quickly because, you know, the financial model companies want want data. They want it now, and they're willing to spend big to get it. So they've been able to go from zero to hundreds, and in the case of some billions very quickly. And the interesting thing in the foundation model cases, there's clearly an end revenue source that's paying for that. In the case of robotics data, it all makes sense. It's the same analogy. There's a bunch of companies really interesting doing various forms of models for robotics. It's obviously early in this deployment life cycle. So you know, you've got the early burgeoning spend, you've got the 10,000,000 and the $100,000,000 deals, and you can get that on venture dollars from the robotics companies and fund... Yeah, and financial model companies too, because they want be in robotics. I think what's going to scale that to a billion or 2,000,000,000 is when the deployments happen, and that's still unproven in terms of timing. Because I mean, the humanoids, I saw a GXO, which is a logistics company that one of my companies deal with, they sent me a post, one of the guys there did it. It was the summary of the post was 42 POCs of humanoids, zero deployed. And then there was some thread about the BMW relationship with Figr, where, again, we talked a big game, but the humanoids aren't out there. So I do think there was a deployment issue in robotics, which will filter back upstream to a ultimately spend on data business until such time as the unlock happens at the deployment level. But for now, you know, definitely making hay while the sun is definitely shining.
00:42:58 · Harry Stebbings, Rory O'Driscoll
[00:42:58] S2: Are we doing Mecca from our [00:42:59] S1: investment committee? You you have to do the second half of the Sequoia round that the regulatory 20 x step up or whatever it is they deem to be appropriate. So... No.
00:42:59 · Rory O'Driscoll, Jason Lemkin
[00:42:59] S1: investment committee? You you have to do the second half of the Sequoia round that the regulatory 20 x step up or whatever it is they deem to be appropriate. So... No. [00:43:09] S0: Well, it's just... Listen. I'm not smart enough to really know. I do think it's it's an interesting play in the sense that, obviously, the current level of interest in robotics is beyond an all time high. Right? It's it's... And and they all need training data. Right? And you can be skeptical of some of these folks, but the demand for high quality training data, even if it's just paying people to wear sensors and do work, it's just off the charts. I met a founder at YC Demo Day. He wasn't in this class of YC. He was just there that I knew from saster stuff. And he tilted his company into doing just a very niche version of training data. And he did 30,000,000 in sixty days. And he said, the problem is they just don't want to do all the stuff that he's asked to do. He's like, we have 300,000,000 of demand. It just takes so many specialized humans in so many countries to do this niche product. We're turning away two seventy out of 30 because we don't want to do it, right? So if you could nail that two by two of being able to provide the data labeling, the humans and the everything, you have the right one. Maybe I'd rather do this than invest in a bunch of robots that are gonna throw Aunt Bessie out the door or smash their fist through my kitchen when they're trying to grab the pots. I'm certainly skeptical of the residential ones. Maybe this is the safest place to put our money.
00:43:09 · Jason Lemkin, Harry Stebbings
[00:43:09] S0: Well, it's just... Listen. I'm not smart enough to really know. I do think it's it's an interesting play in the sense that, obviously, the current level of interest in robotics is beyond an all time high. Right? It's it's... And and they all need training data. Right? And you can be skeptical of some of these folks, but the demand for high quality training data, even if it's just paying people to wear sensors and do work, it's just off the charts. I met a founder at YC Demo Day. He wasn't in this class of YC. He was just there that I knew from saster stuff. And he tilted his company into doing just a very niche version of training data. And he did 30,000,000 in sixty days. And he said, the problem is they just don't want to do all the stuff that he's asked to do. He's like, we have 300,000,000 of demand. It just takes so many specialized humans in so many countries to do this niche product. We're turning away two seventy out of 30 because we don't want to do it, right? So if you could nail that two by two of being able to provide the data labeling, the humans and the everything, you have the right one. Maybe I'd rather do this than invest in a bunch of robots that are gonna throw Aunt Bessie out the door or smash their fist through my kitchen when they're trying to grab the pots. I'm certainly skeptical of the residential ones. Maybe this is the safest place to put our money. [00:44:17] S2: Oh my god. I would way rather do this than any robotics company.