Inspired with Alexa von Tobel
00:30:22 · Alexa von Tobel, Boris Sofman
[00:30:22] S1: Boris, that's actually a theme that we've heard on many past episodes where this isn't getting rid of that job. What it's simply doing is actually taking somebody from being a line worker and actually making them the factory manager [00:30:36] S0: That's right. [00:30:37] S1: To your point of many machines. So in fact, we're up leveling, upskilling these jobs, and you just said it's incredible expansionary, which means now rather than huge projects that we want done for society sitting, you know, unresourced, they actually now... We we can go do more with the supplies and infrastructure that we have. That's wonderful. What are the other advantages? You had said that there's a ton of other advantages of this. And and by the way, I've obviously spent a lot of time on the Bedrock Robotics site where you can actually see the machines moving around and picking up the dirt, but talk through those other more subtle advantages.
00:31:15 · Boris Sofman
[00:31:15] S0: Yeah. And this is where like, as we started to spend more and more time with our partners who eventually are our customers, it's amazing to hear the sort of ways that they can like start to leverage this and rethink their business. So I'll go through a few. So labor, very obvious. Everybody's struggling with this and every one of our partners, like not a single person gets laid off. They take on more work, they meet the demand. Like they start allowing people not to get stressed until like over time where you start to have fatigue and safety risks. So that's a given, what else can you do? Now all of a sudden you're able to compress schedules. A job that because you can barely staff one shift, nobody's even thinking about nighttime in most cases. Now, of eight, ten hour shifts, can do fifteen hours, twenty hours, twenty four hours, and now you can take a project to compress it. The utilization of your machines increases, you can take on more work, the profit margins of the entire kind of business end up increasing. That's critical for, so imagine like you're a developer that's doing a commercial facility or investing in a factory, you're taking a loan at 9% interest. If you compress that by a month, it completely changes your IRR, everything transforms. A data centers gets millions of dollars revenue every day, it's up and running. So that's massive. The predictability and the accuracy of these systems is gonna be exceptional. And most importantly, it's very predictable. So what happens now is because of both the variance of the work and the attrition risk on jobs and all the uncertainties that happen, GCs will put a 5% contingency on their bids oftentimes because of they're on the hook for liabilities if they're over. If that 5% becomes 2% because now you have complete control over surging labor the predictability of your work, You tighten up your entire operations. A GC will win every single bid because a lot of these are won by like half a percent. So that becomes a superpower. We see unprecedented levels of detail on the site. Now they can see the productivity mismatches and trucks to excavators. They see the progress. You can see real time estimates. And so that insights and analytics can fully improve.
00:33:25 · Boris Sofman, Alexa von Tobel
And safety is a huge one where not just the people safety, which is again, the most dangerous profession in the entire country, but the amount of secondary damage around hitting fire hydrants, damaging a truck, damaging the machine itself, preventable kind of wear on the machine, all of this improves. And now this, the every machine that has a spotter behind it, all this kind of disappears. So you start to have all of these like layers of benefit where, and then when you now put all these together as an operator, it sounds a lot like trucking where you can now move these machines anywhere you want, start a project 200 miles away the the next day. It rethink... You rethink the entire physics of the whole business. [00:34:07] S1: Okay. So Boris, now I wanna get your head up and think about the entire category, which is really the intersection of AI and robotics over the next decade. You have spent... And by the way, you have such dad points. I'm like, I just like sitting here reflecting your kids, then you're so cool. If we look out the next decade, what are some of the big predictions you have? Give us Give us just some of your very clear predictions that you have for the whole category.
00:34:35 · Boris Sofman
[00:34:35] S0: Yeah. So I think physical AI is going to be, in my opinion, the biggest theme of the next ten, fifteen years. We've seen the transformation on the digital side, astronomical, everything that Anthropic, OpenAI, everybody's doing. At the end of the day, 80% of the world's economy is still physical industries. It's industrial, it's construction, agriculture, mining, manufacturing, logistics. So I think we're just scratching the surface in this. We've seen the beginnings of it in transportation with Waymo, and it's literally just the beginnings. It's trivial percentage of the... There's 3,000,000,000,000 miles of driving per year in The US. Waymo has done cumulatively 200,000,000 in the entire history of the company. So it's clearly in the beginning of this astronomical ramp. We're pushing in as significant of an industry in these kind of the heavy machinery and construction and related industries. I think manufacturing is another astronomical one where like these are like 10% plus of GDP industries that all have like such a transformative ability to kind of reshape the way they work. And so I generally do think that the theme of the next ten years will be bringing AI into physical form. The way that happens though is not gonna look like OpenAI and Claude. You're not gonna have this like single model that solves everything because that was able to bootstrap off of this infinite amount of data that was publicly available on the internet. Here you have way more differentiation in the platforms and the sensors, and you have very complicated safety risks. And so you're gonna see more vertical integration like what we're doing in construction, what Waymo is doing in transportation, but the businesses can be trillion dollar businesses because of how big these sectors are.
00:36:18 · Alexa von Tobel
[00:36:18] S1: Not only do I agree with you, be back to companies, one called Bright AI, which is physical sensors for very specific categories, and Treeswift, which is physical robotics for trees and for overseeing forests. And so I I deeply agree with you, which is it's not a one size cuts all LLM that can solve, you know, millions of use cases. You actually need the datasets and to to go... And and and you're really building a very, very unique dataset that will be powerful here. Talk a little bit about, like, a contrarian view that you have. Like, what's an opinion that you have that maybe others don't have given your perch?
00:36:59 · Boris Sofman, Alexa von Tobel
[00:36:59] S0: Yeah. I'm pessimistic about this wave of humanoids. I think that this is technology that could be much further away than people think because there's still pretty massive advances that need to happen in tactile sensing and simulation. And particularly when you look at sectors like the consumer market where you have very high quality bars that people expect, price point pressures that are like extreme, you have so much combinations of technology risk and then product and market risk that I'm personally... I can understand the excitement about it, but the idea that there'll be this like universal kind of platform that kind of solves everything. In my mind, I think this could be almost like a .com style situation where it's not wrong, it's just off by a big period of time and there's like big advances that need to happen and it comes back and these things start to happen much later than people think. But the solutions that are actually much more practical are more surgically focused solutions that can provide really deep value focused on a particular application in industry. And so I am much less optimistic about that as a category of robotics immediately today as a practical kind of like, you know, near term business case. [00:38:18] S1: Do you mean humanoids in warehouses or humanoids in homes or all humanoids?