Inspired with Alexa von Tobel
00:28:20 · Alexa von Tobel
[00:28:20] S1: I'm gonna get to what the technology is in one second, but I wanna cover two topics. One is what is the role of the human in these more autonomous excavators?
00:28:30 · Boris Sofman
[00:28:30] S0: So when you look at the operations of a construction site, you have huge amounts, like diversity of machines. You have lots of operators. You have supervisors. You have you even have like spotters for safety of all these things happening. And so we're starting with an excavator doing mass earthwork. And then the way these systems are designed, the technology very quickly snowballs the way we saw Waymo now stamping out lots of cities. We start with earthwork for next grader and then start adding new capabilities like demolition, material handling, trenching, fine grading, new machines like wheel loaders, bulldozers, motor graders. And then eventually you start being able to go up level and be an orchestration layer where you're able to kind of coordinate a team of machines doing work. And as a GC, you can set a goal and it's a digitized manufacturing process and all sorts of things start to be appear when that's possible. Now, what's interesting is that on the construction side, there's such a gigantic span of expertise and these machines have huge diversity of use cases of what they're used for, particularly an excavator, which is the most complicated of these machines, where it's a minimum six degree of freedom machine and sometimes as much as nine. And so it's effectively like an arm and that's why it's so versatile. And so what we'll end up doing is starting to focus on these large scale use cases. But what that enables is in an industry that is so severely labor constrained, the workflow can actually move around and just being able to meet the demands of some of this work, they can make a project pencil out means that they can take on so many of the projects that currently are just being completely unfunded, like heavy civil work, schools, data centers, housing, and all of these places where we're feeling the pain. And it's actually quite expansionary where the jobs will shift around and you might have a person supervising 10 machines and doing the work on a side that like is not autonomous and is actually much more complex.
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.