Catalyst with Shayle Kann - Cracking the code on autonomous trucking

Episode Date: May 7, 2026

Even though autonomous passenger vehicles have entered the mainstream in cities across the country, autonomous trucks still lag behind. But Humble Robotics thinks it has cracked the code with a new design that completely does away with the tractor-trailer model we see on the highway every day. In this episode, Shayle speaks to Eyal Cohen, founder and CEO of Humble. The company built its electric trucks from the ground up. Fully cabless, they combine the tractor and trailer into a single platform designed to optimize energy efficiency, unit economics, and roadway safety. Shayle and Eyal explore topics including: The differences between autonomous passenger and freight vehicles The challenge of transporting heavy payloads at high speeds Why Humble has shifted away from LiDar in favor of a camera-centric approach offered by visual language models (VLMs) The unit economics of electric and autonomous freight Why Humble is embracing a "hub-to-hub" model for its trucks The evolving regulatory landscape for autonomous trucking Resources Catalyst: Volts crossover: Six big energy questions Latitude Media: Can the Tesla Semi finalize decarbonize trucking? Latitude Media: Rivian and EnergyHub are teaming up on managed charging The Green Blueprint: A billion-dollar play on electrified transport Credits: Hosted by Shayle Kann. Produced and edited by Max Savage Levenson. Original music and engineering by Sean Marquand. Stephen Lacey is our executive editor. Catalyst is brought to you by FischTank PR, an award-winning climate and energy tech, renewables, and sustainability-focused PR firm dedicated to elevating the work of both early-stage and established companies. Learn more about their PR approach and how they can support your company’s messaging by visiting fischtankpr.com. Catalyst is brought to you by EnergyHub. EnergyHub helps utilities build next-generation virtual power plants that unlock reliable flexibility at every level of the grid. See how EnergyHub helps unlock the power of flexibility at scale, and deliver more value through cross-DER dispatch with their leading Edge DERMS platform, by visiting energyhub.com. Tune into Critical Capital, a brand new podcast from Crux and Latitude Studios. Hosted by Crux CEO Alfred Johnson, Critical Capital explores the interlocking forces powering clean and critical infrastructure. Join us every other Tuesday for in-depth conversations at the intersection of energy, government, finance, and global markets. Listen here, or wherever you get podcasts.

Latitude Media, covering the new frontiers of the energy transition. I'm Shayal Khan. I lead the early stage venture strategy and energy impact partners. Welcome to Catalyst. So Waymo's first public ride service was in December 2018, years before the meteoric rides of LLMs that we've seen since then. And it's interesting to think about what's happened with autonomous vehicles, which were capable of driving on public roads, at least in some limited capacity, even back then. Not all that limited, I should say,

but limited, nonetheless, before the current wave of AI. Anyway, I was listening to an interview recently with the co-CEO of Waymo, who described how they've been able to integrate the newer AI capabilities into their system and how that's allowed them to basically supercharge their growth and to deal with a wider variety of edge conditions than they would have otherwise.

Obviously, Waymo now is ubiquitous, where I live, in the Bay Area, and increasingly is becoming so in many other cities. the path to autonomy for light duty vehicles seems very clear. Less so at this point for trucking, though the market is huge. Trucks hauled over 11.2 billion tons in the last year in the U.S. alone. There have been a bunch of attempts at autonomy for trucking, and in some ways, it intuitively seems like it should be an easier challenge, but in reality, turns out maybe to be a harder challenge. We'll get back to that. Anyway, we just don't have this equivalent of Waymo in terms of, trucking yet. So what would it look like for someone to start fresh now, fully immersed from day one

in the new wave of AI, particularly in this context, having benefited from the advent of things like vision-language action models, which is sort of an offshoot of LLMs aimed more at the physical world. By the way, I find autonomy interesting in its own regard, given that autonomy really goes hand-in-hand with electrification. We've seen that already in the light-duty vehicle world. I think we're starting to see it now in heavy-duty. In any event, A. Al-Cohen is the founder and CEO of Humble Robotics, a company that we at EIP just announced we invested in a couple weeks ago. Ayal is a veteran of the autonomous trucking world. He worked at Apple, Uber, Spark AI, and Wabi before starting Humble. And his view is that starting with a clean sheet, both from a

vehicle perspective and from a tech stack perspective, will allow Humble to dramatically accelerate adoption of trucking autonomy. So I talked to him about the broader world of autonomous trucking, where we are today and where we're headed, and what he's building at Humble. That's coming up after the break. Trillions of dollars are flowing into clean and critical infrastructure, but those investments aren't driven by technology alone. They're shaped by markets, by policy, by capital, and by the institutions that connect them. I'm Alfred Johnson, CEO of Crux, and host of a brand new podcast, Critical Capital. Each episode, I talk with people

deploying capital, shaping policy and building the clean economy. Tune in as we unpack how progress is actually made. Listen to critical capital on Spotify, Apple, or wherever you get your podcasts. Catalyst is supported by Fish Tank PR, an award-winning PR firm focused on climate and energy tech, renewables, and sustainability. Fish Tank is known for generating prominent and effective media coverage for the brands they work with. If you want a PR partner that's thoughtful, shoots straight, and gets results, you'll like Fish Tank PR. To learn more about Fish Tank's approach, visit Fish Tank, P.R. That's f-I-S-C-H-F-Tankpr.com.

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Hey, Al, welcome. Thanks for having me. I have a bunch of questions for you. Let me start with this one. You know, Waymo has done 200 million miles now on public roads and is driving me all over the complicated and messy streets of San Francisco. So, you know, passenger vehicle autonomy is clearly here. across a bunch of cities.

And yet, we're not there on trucking autonomy. Why is that? Well, that's a great first question. You know, so I think we need to go back a little bit to kind of when autonomous trucking started and the history there, and it'll help explain a little bit of that. So, you know, there's been like unmaned military defense experiments

for a long time, but from an industry that's not defense. And Thomas Trucking really started in 2016. There was two companies, StarScale Robotics and auto. And I was part of Auto. I joined pretty early. And I joined Auto at the time. I think there's some fallacies. I think maybe that we had at the time or misunderstandings about the space at the time. They'll help explain to answer your question. But when I joined, I had been working on passenger car autonomy with other efforts. I was an apple for a bit. And the, the, the, the challenge that I saw was cities felt very hard. Like at the time, given where the tech was, we were just like, how are we going to solve San Francisco and everything that happens in San

Francisco? And, you know, the way the tech worked at the time, still for a lot of companies works this way, is we were doing this very complicated HD mapping procedure where like basically vehicles would drive and try to capture the world in 3D and, you know, try to maintain this sort of updated high-definition map in 3D to locate the vehicle across. to. It all felt very hard at the time. And when I learned about auto doing trucking, I was like, hey, this feels like a more straightforward problem, has great commercial application. Why don't we go tackle that? I didn't know too much about trucking. I mean, I like trucks. Most people are like in awe of like big vehicles, right? But the highways felt easier. And they felt

easier because, you know, when you drive on a highway, mostly what you do is go straight. And what it turns out is that actually the passenger cars have a lot of structural advantages in in developing an autonomous system that were very difficult for trucks on highway. And so even in 2016, when we were doing, at auto, we did this, we did this beer run 100 miles long with nobody in the front seat. And everybody felt like, okay, autonomous trucking is right around the corner. You know, what we're, what we found over time is the highways were way more difficult than we expected. They're challenging. I mean, by the way, my premise here is that everything will get automated. And passenger cars just happen to be first.

But everything will get automated. It's just sort of the march of the technology of progress. But the highways we thought would be easy, they turned out to be hard because of edge cases. You know, you're driving at a higher speed. You're talking about a vehicle that could weigh 80,000 pounds in some cases if it's at full gross weight. And your stopping distance is long. trucks just had challenges on highway that make them more difficult. Would it be accurate to put it as like on a highway,

you probably have fewer edge cases than you have on like a San Francisco street, but it's harder to manage. It's harder to deal with those edge cases because you're going at high speed and an 80,000 pound truck, et cetera. Yeah, I think probably like different kinds of edge cases, the way I would put it. You see them rare, you see them less often, which is one key issue. Like a lot of the times you're driving on the highways, nothing happens.

And I used to actually joke that, like, you could just take a truck with no perception system and put it on the highway. And as long as it stayed in the lane line and stayed at 55 miles an hour could probably complete 200 miles with no issue. It's just that occasionally things happen on the highway that are very difficult to manage. And you don't see those events very often to be able to handle them and learn for them. So that's one challenge. Another challenge is that, you know, the truck, the passenger cars, like a Waymo, you know, when they're are confused about what to do when the robot doesn't know what to do next, it can stop, it can stop and assess. And it's annoying and I'm sure you've seen videos of Waymo stuck, right?

But it's mostly annoying, not a hazard. So when in San Francisco, when a passenger car stops, you know, people go around and they honk, they call, they call annoyed their local politicians, whatever. But mostly it's a safe situation. You don't have that advantage on a highway. So stopping a truck on the highway is actually extremely dangerous and could easily cause an accident, especially if there's like a band or a hill where you don't see. You know, it's trucking, the margin for errors less. So all these things just sort of started to pile up in trucking. And I think it just took longer to solve. It will get solved. But I think we in 2016, when I started with the auto, Auto and Starstee, we thought they were easier. It was going to be an easier road. It just turned out that we had some

misconceptions about the space. So where are we today in terms of autonomous trucking? I mean, you said Otto and Starsky were the first two. There have been a bunch of other, I guess, what I would call, serious attempts since then. Like, how far have we gotten? Yeah, many serious attempts, I would say, and by serious, I mean real technology development, real capital, real, real efforts. They've all kind of followed a similar blueprint, I would say. They take existing tractors that have been manufactured by OEM, sometimes in partnership,

with an OEM like Volvo, sometimes just sort of buying from a lot and doing a quick retrofit. And, you know, the attempts so far, you know, there have been a few driverless runs. And by driverless, I mean nobody in the front seat. There's a lot of like sort of debate about what driverless even is. Right. For example, I think Aurora, which is one of the largest players in this space, you know, they do what they call driverless runs, but they sometimes have a safety observer. This is from their public writings. somebody sort of watching the system, but they call it driverless as in maybe they don't touch the wheel or engage in any way.

So there have been driverless runs, even going back to that 2016 auto. There was a company, there's a company in Bot Auto that just, I think yesterday, did a commercial, what they call the first commercial driverless run. I saw that on LinkedIn. But I would say there's not a regular driverless service for trucking on highway that exists today. And that's 10 years after we've really put serious effort into the space. And five years plus after passenger vehicles really hit the like inflection point where those rides are getting taken, you know, all over the place in multiple cities now. And even on highways now, as of more recently, of course.

So, yeah, so it's interesting. And I think like when you take a step back, surprising because intuitively I would have thought the same thing, I guess that you intuitively thought, which is that like all things, equally you would think trucking is easier. It's just like less fewer things going on on a highway than there are certainly in the streets of a dense city like San Francisco. But yeah, it turns out that those things are harder to handle. One thing I'm curious about, though, is that this first wave of autonomous vehicles, both trucking and passenger vehicles, I would say, was built pre-LLMs, pre-current wave of AI.

And, you know, Waymo essentially made it to market before, certainly started offering commercial passenger rides before, like, GBT3, for example. And so they probably weren't leveraging, like, the latest and greatest from Transformer world at that time, but obviously have been incorporating it since. And I'm curious what, like, so if you're, the difference is between evolving a tech stack for autonomy that was built in 2016 or 2018 or 2020 and then layering on whatever you can do today versus starting fresh today. What is the difference between those two? Yeah, great question. So the landscape obviously has changed a lot. And again, if I go back to that

2016 era, you know, this was even before ML had really taken off en masse in a lease autonomous vehicle. So, you know, to stay between the lane lines, we might just actually be hand coding. Look at these two different pixels. Is one yellow and is one knot? That's where the lane line is. Very, very, like, simple, you know, handcrafted kind of algorithms. So the whole space has evolved tremendously. And I think a lot of the companies have had to break down their stacks and re-engineer them multiple times. And I'm sure Waymo, I'm sure Waymo has had to do the same. But today, I'll give you one example for Humble, my company. You know, we, we, we, we, we, Most of my time in this technology space, we've been pretty LiDAR heavy, like,

LiDAR first, I would say. And even for trucking on highway, and there's been attempts to develop these very long-range LIDARs. I could see, you know, 300, 400 meters so you can handle the stopping distance of a truck. The LiDAR technology for a long time was really good. And it was a little challenging to make it, like, robust and reliable and at scale, but the technology itself was very good. And cameras kind of lagged behind.

Like, we weren't doing so much with the VATTS. vision side of it. Today, for me, at Humble, we flip that, and we do a lot more on vision algorithms. We're camera first. And that's because of just the evolution of this technology has just changed so much, where now you get to all this intelligence kind of, I want to say for free, but there's, you know, when I take an open source, you know, the corollary to an LOM is a VLM, like a vision, a visual language model. And if I take an off-the-shelf VLM, something that understands an image and tells me what's in it, it's very, very good. Like, there's a lot of intelligence to make them there.

And so I think that every company kind of has to kind of rethink their stacks as the technology evolves. What really hasn't changed that much, though, is some of the validation that you do, some of the safety engineering that you do, the evolution of the hardware technology, because that's gotten a lot more robust. So when you start a new effort now, you're kind of using a pretty different technical. approach for the brain, the AI, but you're using a lot of very well-understood techniques for the rest of it, for how you develop a safe system. That's evolved tremendously in 10 years, big saturday. For those who aren't already familiar, what are these vision language models,

these VLMs that you referred to? Like, what is it and what does it actually enable? Yeah, so a VLM is like an LOM corollary is the way I think about it. And it's taking an image as an input, providing some interpretation of what that image is happening in that image. And it's not something that really I had to use in my past. Like this is very new to me also when we started Humble. And our head of autonomy, Drew Gray, has been really, really in-depth in it, in the VLM space. But what I've seen coming out of it is like what I think a lot of people experience now.

Like if you go to chat, GPT and you upload an image, right? and you say, hey, what's going on in this image? It has a pretty good understanding of what's going on in that image. And sometimes you will find intelligence baked in there or some, you know, I guess intelligence is like a hotly debated concept here right now, but bear with me. Like it's some understanding of the image that goes beyond. There's just a dog in here. It's like there's a dog that may have come from that door on the left or, you know,

this construction cone is sitting on a pickup truck, not on the highway, and therefore is probably not an important construction element because it's just being carried by a truck, just to give an example of an edge case. And so the VLM brings some of that understanding right from the jump. And that's really cool. I'm like pretty novel. Like I mean, when I started 10 years ago, like nothing like this existed. And so you had no, like you had to sort of like code in all the intelligence, like really trying to understand what the features were. You know, we would take imagery or later data. We would send it to get labeled. People would put box. I'm sure you've images of boxes around it that say like dog or human or whatever right and we would say if you see a

human you probably want to do this kind of thing i mean it's more complicated than that but but we didn't get this this intelligence layer for free um and uh you know there's open source technology out there that is very very good uh you'll find uh you'll find free vlms or open source vlms um that have a lot of intelligence just available which is like kind of a also kind of a wild place to be uh so Yeah, quite an evolution. My understanding of this sort of like censored debate in autonomy world, at least for passenger vehicles, right, there's the like LiDAR, radar fusion side, which seems to be Waymo does a little bit of everything. Then there's like Tesla, which is camera first and camera only basically, maybe potentially a little bit of radar. But as I think about it, so I can see how these VLMs as an extension or corollary to LLMs allow you to do a lot more.

with video and, you know, just like get further faster on camera data. But my understanding was always that the limitations on camera for autonomy are more around like it can get obscured in certain conditions and things like that. And that's where you want your LIDAR or whatever, which doesn't have the same set of issues. Is your view like you can go camera only as a result of the VLMs or is it you can lean more heavily on camera, but you still want this sensor fusion approach. I think especially for trucks, and given what I was talking about earlier with this 80,000 pound vehicle that you might be moving on the road, you want it to be as safe as it can possibly be. And so, you know, in my mind,

it's not a dogmatic debate about camera or a LIDAR. It's what's the best technology for the moment that makes it the safest. And for my perspective, for a vehicle, a truck, for example, you put on the road, you would want it to have camera, LIDAR and radar. to do a level four, level four being driverless, to do a level four truck today. And the reason, and the reason I say that is because you want to be able to see the world in multiple ways. But there's always a sensor doing the most heavy lifting. This is not sort of this like co-equal, like democracy between the three sensors.

It's usually like some sort of priority is put on some algorithms depending on what you're doing. LIDAR doesn't see traffic lights, right, very well, or it doesn't see the red green. So you would use camera primarily for that. But radar can see better at night. Radar can see through weather in some cases. And so if you want to make a safe product and trucking in particular, you want to really take advantage of all those today. A human, and when you think about the end state, you know, a human is effectively two cameras, right?

Two eyes, two cameras. And they're able to navigate the world fairly well. And so you could make the argument that over time, trucks would go to a vision-only system. But I think the debate, you know, sometimes you see around like Tesla and Waymo and others, it feels a little dogmatic. I think most of us on the trucking side have taken just the approach that, hey, that our margin for error is very low here. It's a very heavy vehicle. We have to be extremely safe. So we just put as much equipment as we can to sort of try to guarantee that safety and get very creative on the algorithm side and how to take all that data from the three different modalities.

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in this space. One is just, to some extent, it's like timing. You're starting fresh now, and so you get to like, build from the ground up using VLMs and these things that didn't exist before and benefiting from all the learnings that we've seen on passenger autonomy and so on. The other is the form factor of the vehicle. So you mentioned that most of the attempts in autonomous trucking have been, you know, attaching a bunch of sensors to an existing truck, which is also, by the way, how it's been in mostly historically in passenger autonomy, right? Like, that's what Waymo's doing on these

jaguar vehicles and these other ones. Tesla maybe is a little different with the Robotel but those aren't really out in the market yet. So that is similar. You are taking a clean sheet approach and building a vehicle that doesn't even have a cab. I guess in the long arc of history, of course that's how it's going to end up, right? When we don't need a driver, we shouldn't have

a space in a driver for a vehicle. But apart from that, give me the thinking that led you to building a new vehicle. Yeah. So, right, at Humble, we have this cabless, autonomous way. electric class eight truck, right? And, you know, the thinking that got me here was, it's a couple

of things. It's kind of interesting. First, I was like, okay, if you were to imagine that long arc of future, like you're saying, what does that vehicle look like? What is the simplest possible vehicle to move freight? And it's like a box with wheels, right? Basically, it's a, it's a platform concept where either a container is being loaded onto that platform or maybe there's a, or maybe it's just a box of the box truck moving. And that would be, that would be, theory the lowest possible cost of moving freight, right? It can't possibly get lower than that, I don't think. Maybe there's some new, new mechanism to do it, at least for on-road trucking. So that's the first, that was the first thought that got us here. And the second was like, okay, is this possible

today? Can we do this with the technology and where it is today? And, you know, that's where we started exploring it with Humble. And the, no, the answer, the answer became like, yeah, this, the technology is there. Like, basically, there's enough, there's enough here where we can take that long arc of history and move it in a little bit, move it forward. And then along the way, because you're doing a clean sheet design, you could think about all these problems that you run into into the space. So I'll give a couple examples of what you can just rethink with this kind of vehicle. So one way to think about our vehicle is that it combines a tractor and a trailer together

into a single platform, right? And a lot of challenges with doing this, by the way. Right, because part of the market is like the tractor and the trailer are owned by different entities as it stands today, right? It's not the entire market. Sometimes it's the same player, but, you know, they get separated sometimes and sent off in different directions. They get separated and sometimes for very good reasons.

Like, you know, trailers are relatively inexpensive, you know, tractors are relatively expensive. So there's a lot of like, there's a lot of kind of interesting thinking around like trying to combine this concept. But just from the technology side, for example, if you've made the tractor smart, like like the other autonomous truck players, and you've left the trailer. conventional or like a dumb trailer, quote-unquote, right? You can't, for example, put sensors on the back of the trailer. Like, you have a smart tractor, but you're just taking trailers from everywhere.

So you can't see behind you. You can't see directly behind you. If you can't see directly behind you, you cannot handle, for example, an accident where somebody just drives right into you. And I think that's, there's maybe some clever ways to do that, but that's tricky. You cannot back into a dock, right? Because that requires some amount of understanding of what's going on behind you. behind you. One interesting, this is just like a kind of like an inside baseball thing, but one

interesting challenge we've had in the industry is that trucks today, if they're pulled over, they're required by law to deploy warning triangles. And those warning triangles go behind the vehicle. If you only have made the tractor smart and the trailer has not been touched and you don't have a driver there, how do you deploy those warning triangles? And so, you know, companies like Aurora and I think Waymo when they were working on trucking, they they proposed using lights that are high up on the vehicle to indicate that the vehicle stalled as a replacement for the triangles. But there's advantages and disadvantages to that, right?

And so just being able to access the rear of the vehicle and have this full vision from a technology perspective just allows us to kind of to do more. And when I was thinking about, what is the real future here for freight? Again, sort of now long arc, but what you would want is all freight to be fully automated. completely hands off, nobody touching it. It goes to a warehouse.

It loads up. It loads goods from a warehouse into that vehicle and drives his destination and unloads, right? And completely hands off, no human. I think that's where we want to get to. But to do that, you have to kind of treat the whole vehicle as smart, not just the tractor. And so that's how we got.

So it's kind of this interesting combination for us of the technology is ready. The simplest concept that we can come up with for moving freight is the capitalist vehicle. And there's actually a real structural technology advantages to doing it in the long term. And so that's where Hubble is today. You mentioned your vehicle is electric autonomous.

There's this very interesting and very appealing direct correlation between autonomy and electrification that you see broadly. I presume you sort of knew from day one this was going to be an electric truck. But electric truck, I mean, setting aside autonomy even, And it's got its own set of open questions on, of course, things like range and weight of the battery and charging infrastructure and charge time and so on.

So how do you think about the electric component of your vehicle? Yeah. And I think it starts with that vision that I talked about of having fully hands-off rate. If you were going to have fully hands-off rate, you would want it to be electric to charge, to handle the charging in an automated way. It's really hard to do that with diesel. Like, how are you going to get a diesel pump, you know, like into a – I mean, you could maybe do it with robots. They could be challenging. So part of the electric story for me is just like, how do you get to this fully automated freight vision?

So electric is good from that perspective. There are challenges charging – forget the autonomy side, right? Electric trucks in the U.S. have had a challenging rollout. They've been – the electric trucks themselves have been fairly expensive, in some cases, $400,000. A truck today – a tractor today is – somewhere between 150 and 250 depending on what you're buying. So tractors are a very expensive electric truck. There's charging infrastructure that needs to exist.

Electric trucks are kind of having a moment again now because of the volatility in the world and some of the challenges that are going on. But in general, it's been a tough rollout. But what we have seen in countries like China is that electric trucks are really taking off because the infrastructure developed. And once it's there and the costs are where they need to be, It makes a lot of sense. It's harder on the long haul.

I think that's something that as an industry we have to reckon with a bit. You have to put a very large battery to do long haul. It is very heavy. You need a lot of power to charge. You need a lot of charging infrastructure. But for use cases that are more local, short-haul, drainage, drages moving freight out of ports. Electric makes a lot of sense.

And so my career started in electrification. I worked, Bay Area was very big for electrification for a long time. That kind of moved out a little bit. But I loved working on motors and batteries and the technology there. So I always, you know, in the back of my mind, wanted to get back to it. And this was an opportunity for me because of that vision, that long-term vision, because it makes a lot of sense for kind of the short-haul moves that we're aiming to do with Humble. And, you know, like I said, like electric trucks are adding a moment.

It is the technology that some countries have adopted en masse. It just needs to be applied in the right way. And there's always going to be challenges in tech rollout. Charging is certainly one of them. But they're solvable. They're all solvable. Do you think you need to solve them? There's like a chicken or egg challenge often in things like this,

where it's like you need that charging infrastructure to be there in order for your customers to buy and utilize your truck. You don't necessarily want to be an EV charging company, I suspect, but somebody's got to do it. And there has to be enough of a demand signal from your customers such that somebody will build the charging infrastructure. And if it's third-party-owned charging infrastructure, make money on it, right?

It's kind of a high enough utilization and so on. I think we're starting to see this happen at ports and things like that to some extent where you've seen a little bit more electrification already. But is your view kind of like a build-it and they will come sort of a thing? If we build the vehicle, our customers will want the vehicle, charging will show up, or do you need to be more proactive? Yeah, I think it's a little bit of both.

So there has been quietly an industry built up on electric trucking. There are a few startups and companies out there that have been working on depots and solving electric trucking. And I think there's been some shift to more short haul. Tesla semi, obviously, I think just rolled out of production, which is really great for the industry. And that'll induce some charging efforts. So it has been happening. It just been happening relatively slowly, I would say, compared to what the industry expects. But I feel like it's inevitable.

And by, you know, as humble grows, you know, my, my, my, my conversations with customers around this is we will help you solve it. It might not be that humble itself is developing technology around charging. We have, we have our hands full with autonomy and, and a clean sheet design. There's a lot there, right? But, but we will help the customers solve it because we, we know everybody in the industry. We've been working with them for a long time. And, and there's, there's a myriad of solutions, right?

You could do charging at the ports and the warehouses themselves. You can have depots. There's public infrastructure, private infrastructure. But I think what we'll see is, again, especially with what's going on in the world right now, I think we'll see a steady improvement in that. And eventually you'll have real uptake on electric trucking because from a cost structure perspective, once the charging is in place and you've sort of changed your operations and navigated that a little bit, there's a lot of advantage to it.

What do you think the rollout of autonomous, back to autonomous, sorry, not just electric, but what's the rollout of autonomous trucking going to look like? I think people now have an intuition for what it looks like on the passenger side. It's sort of like, okay, company X, usually Waymo, maybe it's going to be Tesla soon, maybe it's going to be Uber at some point, you know, says, okay, we're now offering publicly available rides in City X, and it's ring fenced. You can only go, you know, within these boundaries. and they do that for a while,

and then they expand the boundaries, and then they go to a new city and so on. So now we have a sense of like, here's what's coming in terms of passenger autonomy. I imagine I can't quite work the same in trucking. So what's that going to look like?

Paint me that picture. Yeah. So I'll put Humble aside for a second and just look at the industry as a whole. And, you know, you have a number of very large players, very well capitalized, some public companies, all kind of going after. the on-road long-haul autonomous trucking, and they will continue to work on that, and you will see

autonomous trucks on the highway. And I think you'll see them very soon, and they will be driverless. All the sort of pieces have sort of do come into place, like hardware and supply chain and regulatory efforts. You know, that took a while to sort of make sure state and federal regulators understood kind of the technology and how to deploy it. So those large players, I think they will start deploying. I mean, traditionally, they've been calling it a hub-to-hub model, right, where it's like you can imagine at either end of a highway segment, you know, a destination for autonomous truck to go and drop off rates. Sometimes you'll see it go right to customers. I don't think you'll see generalized solutions where there's just like autonomous trucks zigzagging like everywhere

for a while. But I think what you'll see is some specific segments, mostly in Texas, where you'll see occasional autonomous trucks and some scale. applied there. That's for the long haul side, at least in the space that Humble plays in, for Class A trucking heavy hall and the short haul, there really hasn't been a whole lot of effort in that space yet. So we're one of the first companies to tackle that. So we'll see what our rollout looks like over time and how that goes. We're fairly young. We're less than the year, but we're moving very fast on that front. But I think you'll see long haul Thomas trucks moving. I think the question will shift to can we get a truck safely?

across the road in most cases to can we handle the operational concerns? Can we handle the unit economics? Like that's a challenge. You know, if you take a very expensive truck and then you make it significantly more expensive and, you know, then you're saying we've saved on some labor costs, you have to make that argument work really well. I was going to ask you that question on unit economics. I mean, I guess one way to get at it is like in a normal truck movement, this is going to vary substantially, I'm sure in terms of long haul versus short haul and other things. But like what portion of the fully loaded cost of delivery is the driver? You know, how much savings do you get economically removing the driver?

Yeah, so don't quote me, but about we use Atchery. It's an industry guide for trucking costs. And trucking costs in 26 or 25 will have to be about $2.30, 40 cents a mile, at least for the long haul side. And I think the driver wages are about $1,000. or a dollar ton of that per mile. So fairly significant. 30, 40%, something like that, is the driver.

So that's maybe, if you're trying to save money and go autonomous, that's like the headroom you have to play with to make the vehicle more expensive. If you have to make the vehicle more expensive because you're adding sensors and things like that. Correct. Yes, exactly. So it's like, you know, you have to offset that labor reduction. Or you have some room to play with there, but you'll have some remote assistance. the vehicle will be a lot more expensive because of the sensors. There's no getting around that.

A lot of the current OEM efforts to, basically the way it works a lot in industry now is that an OEM will make a tractor and will partner with an autonomous provider to put the sensors on it and they try to do this at the factory. That's the goal. But often they're using a fairly expensive tractors like the higher end models because they have more room in the tractor for equipment. They call those sleepers where, like, a driver might sleep. And they replace some of the, like, the bed with a, with computer, for example.

So those vehicles are expensive. They become very expensive until they're at scale. So there's a challenge for sure in the unit economics. I think, like, you even see that with Waymo's today, right? Like, they have to get the unit economics down low enough to make the waiver argument worth it. So I think that'll take time. That'll take time. And part of the story for Humble and the reason that I started thinking about the lowest possible

cost moving freight was the unit economics. It was like, well, if you remove a cab, you've taken out some significant cost from the vehicle. You've also taken out significant weight from the vehicle, and that allows us to kind of rethink the unit economics a little bit. Yeah, it strikes me that, at least for a period of time, Waymo is getting away with inferior unit economics. Like, they definitely have inferior unit economics, and I can tell you from personal experience, I'm sure you have, too. I ride Waymo's around, even though they're more expensive than Uber's right now, because it's cool and it's novel. I doubt that same dynamic exists to the same extent in trucking. It's like a classic thing of a B2C versus a B2B market. A hundred percent. You have to save money, I assume,

in trucking, in order for it to be adopted at any meaningful scale, maybe people will pilot something, but I don't know why else they would do anything at scale unless they can save money. Yeah, I think that's a real challenge. There's a real challenge of what you're saying, and it's very true. It's like, In this B-to-B market, when you're dealing with freight, you know, there's a safety component, there's a reliability component. Like, is my freight coming on time? There is a, but ultimately, you know, it's the cost of moving freight, and it has to be, it has to be advantage to a shipper that's moving freight to want to use an autonomous service

in some way. I'll give you, I'll give an example of a challenge that the industry faces on the long-haul side. You know, originally, a lot of the ideas were build, you know, basically make a rail, like I said. So you can imagine at the highway there's like a depot right at the highway. And you would aggregate freight at this depot. And then a Thomas truck would take it, you know, hundreds of miles, maybe a thousand miles, like a long distance and drop off the freight at the other end of that segment at another depot.

And thinking is like, yeah, we will do like these sort of short moves to the depots. And then the Thomas truck with its cost advantage structure would move the freight the long haul. And then you do these short moves again. Well, the challenge in that is today. you don't have those depots, and somebody has to build those depots, and those depots are friction. Like, who is moving the freight to that depot? And why do they want to move into that depot, as opposed to just what they do today, which is just take it from their warehouse to the other end? And so you can see that, like, some of the, I think the economics here are tough. And in this industry,

in particular, the economics matter a lot. So I think Waymo has managed the cool factor and, you know, people are willing to pay more. And I think there is an experience component to it. it, right? I think people sometimes say they prefer Waymo's for the experience. I think Waymos did an excellent job with the interior and the experience, right? But so I think they, they have a little bit of an advantage there. I don't see that as much in freight. Like, it's hard to, like, what's a premium service in freight? I mean, one example, I mean, to give the counter argument, you know, you could say, okay, this truck could go day and night, right? There's no restriction on, like, how often that vehicle can. Maybe there's, like, some argument there. But in general,

in general, like, yeah, you have to get the cost structure down. Part of the reason I started humble in a way is, like, I was just really thinking about the customers, what they need, like, what their challenges are, and how to just get the cost of freight to be as well and meaningful as possible. I guess final question for you, what's the regulatory landscape like? Like, what do you, you know, are we allowed to run driverless vehicles on, and I guess is it tied to are you on a city street or in a, a drainage situation versus a highway, and are those regulated differently, or is trucking regulated

as one category? Yeah, that's a great question. So the regulatory landscape is interesting and fun. I actually kind of like really enjoy this part of the industry, and I love talking to the regulators about it, because I kind of feel like we're all breaking new ground, the regulators and the industry, and it's good to do that hand-in-hand and have good dialogue on it. You know, the situation today is there's, you know, we work with NHTSA. That's a major regulator for the trucking industry.

We work with the FMCSA. It's another regulator for the trucking industry on the federal level. There's state laws that are state by state. You know, a lot of the testing for autonomous trucks has happened in Texas because the regulatory landscape there has been favorable to Thomas trucks. In California, a week ago, you were, you would not have. have been legally permitted to do a driverless truck. And today you are, so there was some legislation,

or some new rulemaking there that allows for it with certain conditions. So it's an evolving landscape. The, you know, for us developing this cabless vehicle, you know, it's got a sort of additional remitory challenge that you're changing what the truck looks like, right? There's no steering wheel, there's no windshield, right?

Windshield is required by law. So how do you have a, that. So the way that works is that we talk to the regulators about what we're trying to do. And we come up with a good plan for how do we do this, how do we test it to be safe. Our vehicle, our vehicle looks both like a tractor and a trailer. Like it has, it has in some ways, like you could think of it as like a smart trailer that just drives around by itself, right? So if it's a smart trailer, how do you regulate a smart trailer versus a smart truck, right? There's a lot of questions like that that we just work with the regulators on.

But, you know, I would say that the regulators in general in the space have been very, very good to work with. And, you know, everybody kind of sees where the technology is going. And they just want to make sure that it's done in the safest way possible and, you know, thoughtfully, safely. And there's also, you know, this other component the regulators are thinking about, which is what's happening around the world. We see actually a lot of driverless efforts deploying in places like China, right? So are we being competitive in that regard while also being safe? But yeah, it's an interesting question about the regulatory side. Actually, really fun one to kind of figure out hand in hand with them.

All right, Ayal, thank you so much for doing this. That's super interesting. Thanks for having me. Ayal Cohen is the founder and CEO of Humble Robotics. This show is a production of Latitude Media. You can head over to Latitudemedia.com for links to today's topics. This episode is produced by Max Savage Levinson, mixing and theme song by Sean Marquand. Anne Bailey edits the video version of the show.

Stephen Lacey is our executive editor. I'm Shail Khan, and this is Catalyst.