Inspired with Alexa von Tobel
00:24:46 · Boris Sofman, Alexa von Tobel
[00:24:46] S0: got so many many cool dad points. My five year old knows how to draw... Operate an excavator. It's amazing. [00:24:51] S1: I'm like, of course, your dad points are legit on fire. Can we quickly rewind? Tell us in plain English. What is Bedrock Robotics doing with excavators? [00:25:03] S0: Exactly. So we are retrofitting existing heavy machinery like... Starting with excavators and then turning them into a into driverless machines. And so we have a retrofit that turns existing Caterpillar machines, for example, into ones that are capable of being fully operatorless for the scope that's cleared for. And that increases with software updates. Our customers end up being the general contractors that own and operate these machines and Bedrock becomes the digital operator of those machines. And so we enable these excavators to be completely operatorless and be able to do their work without any constraints and at a superhuman level of safety and precision, and enable these contractors to then leverage that to really rethink the way they operate their businesses. [00:25:58] S1: Okay. So I have so many questions, Boris. You went from obviously, and that's why I wanted to touch on the trucking, really thinking about fully building autonomous trucks. And then you shifted into another heavy machinery industry, so not that dissimilar to trucks, and made the decision to retrofit. Let's double click on the decision not to go build autonomous excavators, but instead to retrofit. Why?
00:26:24 · Boris Sofman
[00:26:24] S0: So if we could do that at Waymo, we would have done that as well. The thing is in cars and trucks, can't, you physically have to redesign these platforms to be drive by wire so you can control it digitally. And then have the redundancy we talked about in brake steering actuation because of safety reasons. And so these programs are really complicated. They took oftentimes kind of jointly with the partnerships like hundreds of millions of dollars, four to five years. And every single time we made a vehicle program like this, the Chrysler Jaguars, Daimler Freightliners, Zoox, Hyundai, it would take this sort of an effort. And so that's actually a huge barrier to get to market. Here, because of the way these machines are designed, we're able to retrofit them with a sensor and compute suite that turns them into autonomously capable, but we're able to ensure that they can still fail safely to a stop. And so we can safely deploy them fully driverlessly without having to fully reinvent an excavator or wheel loader or bulldozer. And that's actually incredibly enabling because we can get to market a lot faster. And then long term we would partner with the OEMs to go and do this at manufacturing time because there's huge advantages there as well. But this is one of the reasons that we're able to get like later this year, we're gonna release our first driverless systems, excavators doing mass earthwork as the first entry point. And we can do this a little bit over two years since the start of the company where AV companies would take many, many more years and far more expense in order to do this. And so for us, this was an advantage. And as a customer, you now do not need to buy another, like these machines cost $600,000 And so instead of having to buy a brand new machine that is custom and much more expensive and complex, you get to use your existing systems with a very inexpensive upfit and immediately start leveraging these capabilities with much less investment.
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.