I want to start with like, you know, when you're thinking about like tracking and construction, what's the similarity versus like differences?

Yeah, so the similarity is very natural where you are coming into an existing gigantic industry.

So, you know, trucking is like a trillion dollar industry.

Construction is a two trillion dollar industry, right? And you have this ecosystem that has its own way of working, physics, complexities and constraints.

And at the end of the day, the companies that you are partnering with or selling to, you have to genuinely provide a value.

They don't care as much about why you're technically cool.

A consumer might actually care a little bit more about that, ironically.

And number two is like from the fundraising perspective, like what do you think is like the core benchmark that VCs actually want to see to, you know, to back something like this?

Why is there a need for autonomous construction equipment?

Yeah.

It's a great question.

Uh, there is an unprecedented need to build, so we're onshoring manufacturing.

There's housing shortages, road shortages, the data center boom that we've all seen, uh, water treatment facilities.

All of these are pushing on an already incredibly strained industry, and the labor supply is actually continuing to fall, where some of, uh, the contractors we partner with are seeing huge retirement rates.

And so there's an absolute bottleneck that effectively becomes a radiation on the whole economy when you can't build the things that the country needs.

So, so what is the constraint on your ability to build the fleet that you can then deploy? Because the number of projects you take on will be dictated by how many of these autonomous machines can be deployed.

Is that a one to one to world models? Or is there a variation in what Bedrock uses to power its machines?

No, world models will be used for simulation and training purposes.

The actual ML model is effectively a large transformer-based end-to-end architecture.

It's taking as an input sensor data, machine signals, goal of what you're trying to achieve, you know, a variety of other factors that kind of give you the pose.

And then it's, um, processing all of this with a particular structure and outputting a behavior for the machine.

Um, uh, as well as, you know, potentially other behaviors like honking the signal that you're ready.

Uh, and so that behavior, uh, can actually govern a complicated machine, like an excavator that has six to nine degrees of freedom.

So are you now just like in data abundance as a company? Because I feel like if you've done that much actual earth moving after all the training, you've talked about all the data, all the sampling, all the modeling, you must just have a ton of fresh and useful data.

What's your expectation for the next five to 10 years? Kind of what's your mental model of what's probable?

Trucking is an incredible space.

It was such a deep passion of not just mine, but actually a lot of the team at Bedrock is from the trucking program.

We just kind of really loved working together on this.

As an industry, it's astronomically large.

So the entire ride hailing industry in the US, I believe is something like 50 billion in revenue.

Trucking is a trillion.

First of all, what made you make this leap? What was the problem you saw? What was the aha moment that made you want to start this?

So the- I, I imagine, like, the economic trade is pretty good?

Uh, econo- economic trade is fantastic 'cause the cost of hardware is also, uh, a lot lower because now there's an ecosystem of components being driven by automotive space and others, and so we can, uh, enable these machines to be autonomous, you know, f- for a lot less cost.

But then you're able to operate, uh, eight hours a day, fifteen hours a day, twenty-four hours a day.

You can compress schedules.

You improve safety.

You get visibility of your work, higher predictability, and so when you change the physics of how you actually manage the operations of a construction project like this, uh, suddenly you can get a lot more productive and fundamentally expand the sector, and you can utilize your machinery a lot more with a lot less constraints, which immediately helps general contractors and subcontractors, who are our customers in the end, uh, do work.

Mm-hmm.

Um, and so that adds an incredibly high bar to releasing a car and, you know, to go driverless in San Francisco, or a a hundred and ten thousand pound machine to go and do a excavation project in a, you know, for a factory.