Catalyst with Shayle Kann - The coming robotics wave

Episode Date: March 20, 2025

Robots are becoming cheaper to make and more powerful because of AI. In the climate tech space, they’re already laying transmission lines, inspecting wind turbines, and installing solar panels.. And with labor productivity stagnating, immigration restrictions tightening, and the cost of labor rising, they’re looking even more appealing.  So where might robotics have the biggest impact on climate tech? In this episode, Shayle talks to Andy Lubershane, a partner and head of research at Energy Impact Partners (where he’s a colleague of Shayle). Andy also recently wrote a blog post on the effects of autonomy across climate tech. They cover topics like:    How more affordable parts and better foundation models are making robotics cheaper The high CapEx and low OpEx that make automation expensive to start, but valuable with high utilization Robotics-as-a-service companies that help to overcome these initial CapEx challenges The most promising applications, like manufacturing, construction, and maintenance The hopes for more humanoid general-purpose robots — and the challenges in making them Recommended resources Steel for Fuel: Autonomy is real now SemiAnalysis: America Is Missing The New Labor Economy – Robotics Part 1 Steel for Fuel: From SaaS to Robots F-Prime Capital: State of Robotics Credits: Hosted by Shayle Kann. Produced and edited by Daniel Woldorff. Original music and engineering by Sean Marquand. Stephen Lacey is executive editor. 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. Catalyst is brought to you by Antenna Group, the public relations and strategic marketing agency of choice for climate and energy leaders. If you're a startup, investor, or global corporation that's looking to tell your climate story, demonstrate your impact, or accelerate your growth, Antenna Group's team of industry insiders is ready to help. Learn more at antennagroup.com.

Hey, it's executive editor Stephen Lacey. Many of you were loyal listeners to a show I created and co-hosted for eight years called The Energy Gang. Well, we're back. Jigger Shaw, Catherine Hamilton, and I are excited to announce our latest project, a weekly news roundtable called Open Circuit. Every week we'll break down how major projects come together, how deals and policies get structured, and what it takes to build critical infrastructure at scale,

all through the lens of current events. You can subscribe to Open Circuit wherever you listen to podcast, or follow it at Latitude Media.com. Latitude Media, podcast at the Frontier of Climate Technology. I'm Shail Khan, and this is Catalyst. Everything it takes to build a robot is much cheaper now, and you can build them much better with AI. Coming up, the robots are coming.

When utilities need flexible capacity they can count on, they turn to Energy Hub. Energy Hub works with more than 170 utilities, coordinating over 2.5 million devices to manage 3.4 gigawatts of flexibility built for the moments when utilities can't afford uncertainty. Energy Hub builds and operates virtual power plants that utilities actually stake their grid planning on, coordinating EVs, batteries, thermostats, and more through a single platform built for utility scale. Predictive, verifiable, and designed to perform when it counts. Learn more at energyhub.com.

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 tankpr.com. That's F-I-S-C-H-Fish-Tankpr.com. I'm Shail Khan. I lead the Frontier Fund at Energy Impact Partners. Welcome. So lately, I've been spending a lot of time learning about a broad set of technologies that I've been grouping under the term physical AI. This is applications of AI to the physical world.

So AI for atoms, not for bits. To the extent that there's going to be a big impact of AI on the energy sector, on climate tech, apart from its obvious impact on energy consumption, which we've already talked, talked about ad nauseum here. This area, physical AI, is where I think the impact is going to come from. So we're going to start talking about it more here. We've already covered it a bit. For example, when we talked to Doge from Google DeepMind a while back about AI for Materials Discovery, which is a category I think is interesting in the physical AI world. But one other obvious manifestation of physical AI where we've been exploring and investing at EIP for a while now is

in robotics, which I find. to be fascinating and incredibly interesting. As does my partner, Andy Lubershane, Catalyst Regular, NDAP's head of research. Andy's been on a bit of a robotics tear lately, so I figured I would bring him on to talk about robotics in general, but also its applications to the sectors where we focus. So here's Andy. Andy, welcome back. Thanks. I think this is my first catalyst pod of the Brave New World of 2025. What a world that is. What a world that It is. All right, we're going to talk about your favorite topic of the past few months, anyway, which is robotics.

Robotics is not a new thing. It's not a new thing in the sectors we're going to be talking about. So I want to start with a why now. I think there's kind of an obvious trite answer of like, oh, AI showed up until you could do more with robotics and capabilities for getting unlocked. I do think we should talk about that too. But beyond just like AI arrived, why do you suddenly find robotics so interesting? AI is definitely one of the reasons that I'm interested in it, but that's partially just because I'm a little bit of a contrarian. And so when people started getting excited about large language models

and other generative AI stuff a couple years ago, I sort of started thinking, first of all, I'm a little bit, I'm not as excited. I'm personally only very recently have started to see applications where I think there's some real, I won't go ahead and say transformational value, but next level value in LLMs. So I sort of started casting about looking for

where in the wide world of AI do I think there actually are transformational opportunities for energy and climate technology specifically. And robotics increasingly started to stand out to me. I think that's both because empirically we're seeing interesting companies and opportunities that are related to robotics in energy and climate tech, but also because of some big,

I think big secular macro tailwinds that are really blowing in the favor of robotics. And that's both on the demand side and the supply side. So on the demand side, I think it's largely related to how difficult it is to get people, to get labor, to do the kind of really hard physical work in manufacturing and construction to build all of the stuff we're going to need to build

and install in the energy transition. And that's kind of related to, you know, three big macro factors that aren't really going anywhere fast. One is the big global demographic transition. So, you know, especially in advanced economies, there's just fewer young people who are being born today and were born 20, 25, 30 years ago to do all that hard physical work. The second in some advanced economies and now in the United States is just the likelihood of a more restrictive immigration environment, which has been one of the primary ways that the U.S. has escaped from this global demographic challenge that some other advanced economies haven't in the past decade or two is importing young people via immigration. And then the third is this long-term trend that's really concerning for economic growth overall,

which is just labor productivity kind of stagnating in advanced economies. Not across the board. Obviously, we've seen big improvements in labor productivity in certain sectors and basically in tech and anything connected to the Internet and computers. People have gotten a lot more productive in the last 10, 20, 30 years. But again, in the sectors that we care about the most when it comes to decarbonization and really anything having to do with energy, which are basically manufacturing and construction, labor productivity has been flat really for the past 10 to 15 years.

And in construction, it's actually worryingly declining, really, for the past decade. And so we need more, we need people to be more productive in the future. the physical world, and robots are one way to make them more productive. So that's the demand side. What do you think? Yeah, I mean, one thing that I find interesting, clearly, we've heard, you and I have heard over and over again that labor is becoming or has become or has been a constraint in a bunch of these sectors, construction in particular, but manufacturing and stuff as well. You hear it a lot, anecdotally. One thing I haven't heard, though, I don't know if I would realistically expect this. But one thing I haven't heard is somebody saying, I can't build X because I was not

able to find enough people to do it. Or like, I couldn't cite this manufacturing facility. I failed. The binary question of was able to build it or not was no. So I hear a lot of the labor as a constraint, it's getting harder and harder. I don't know about you, but I haven't yet heard the labor was the cause of a failed attempt to build something. No, that would be, that would be really scary. I haven't heard that either. I think the way we see it play out is rising wages, which is good for people who are doing the physical work, but more expensive for any kind of project that takes a lot of labor. And then again, like you said, just sort of generalized complaints that it's hard to find people or that people don't stick around for very long. They go and find work elsewhere. And so

you have to train up new people. And so, yeah, I don't think we ever see it in terms of like project canceled because workers all quit or there aren't any workers to do the project. But it's sort of just a general, a drag on everything, probably. That is harder to pin to any kind of specific instance. Okay, so that's the demand side. And I think that's like, I don't know, it doesn't feel like maybe with the exception of restrictive immigration, which could actually provide like a significant shock to the system on the labor force side.

The rest of it is sort of an ongoing, somewhat long-term trend. And so you could imagine there being more and more interest in automation across a variety of sectors, but nothing that would trigger like a wave of deployments absent something changing on the supply side, the actual capabilities and costs of the automated systems in the first place. So let's switch from the demand side to the supply side. What gives you a fair amount of optimism on the supply side, meaning what we can produce for robotics and the cost of it. The supply side is definitely where the more interesting

why now elements come into the picture. So we can start with AI. AI is getting better. It's getting better a lot faster, and that's not just related to generative AI, building large language models and large multimodal models and doing digital stuff. Emerging from that ecosystem,

we're also starting to see some real seminal research on the application of generative AI to robotics. People should go and check out things like Google's Palm E model that was published a year and a half or so ago. There's this research group at Stanford that built a robot they call Mobile Aloha using new methods of training this very simple, relatively low cost, basically a system of a couple of robotic arms on a little push cart. They've made really remarkable progress

at the ability to train robots to engage in less structured environments and perform really highly unstructured tasks, which has been the challenge in the past for anything in robots. I mean, there are hundreds of thousands, millions now, of industrial robots installed worldwide, which are largely just these robotic arms, systems that are doing largely deterministic tasks in factories. So, you know, passing one part from one side of an assembly line to another and doing a very

deterministic, you know, weld, for example, between two sheets of metal. That's been going on and actually gradually growing amidst these macro-demand-side tailwinds, really, for a couple decades now. But what AI makes possible is to much more quickly train robot. to navigate in more complex chaotic environments where you can't train them to do the same thing over and over and over. And that's where a lot more of the most exciting opportunities

in energy and climate tech come in, both in manufacturing, but I think more in the deployment side where you're actually having to build stuff out in the real world, which is inherently chaotic and unstructured and impossible to program deterministically. And so that's one thing. AI is making real progress, and that I do think unlocks robotic opportunities

that were not available even five to seven years ago. And then in addition to that, one of the things that I think has excited me is just it's getting a lot cheaper to build robotic systems of basically all kinds, because all of the components, of building a robot, all the inputs into just about any kind of robot are getting cheaper. So again, starting with AI, the computing hardware to run AI is getting cheaper.

All the computer chips, GPUs have gotten much more highly performant in just every dimension very rapidly and continue to. But also the more mundane or relatively mundane aspects of a robot. So all of the kind of sensors you need to navigate in a less structured environment. So LIDAR, for example, the cost of LIDAR systems has come way down, I think, 90% in the past 15 years. And that's largely been driven by investments in autonomous vehicles, right? Which are now finally coming to fruition and becoming a real commercial enterprise. But along the way, they had to invest a lot in making sensor technology much cheaper.

other boring things like actuators, just electric actuators for the joints that make robots move. I'm sure no one listening to Catalyst needs to be told how much battery costs have come down in the past 15 years. So basically everything it takes to build a robot is much cheaper now, and you can build them much better

with AI. Well, that's the thing about robotics in general. When you start looking at these companies who are doing various things in robotics, but this is like almost universally true, if you're able to price the service at roughly the equivalent cost that the human labor alternative would have cost,

because the cost of the robots is so low now, the payback periods on these things are like remarkably fast, assuming you get high enough utilization, right? So like the big questions are, can you price at the equivalent or close to the equivalent, how much is the thing being used? But with such low capex, you get these extraordinarily fast payback periods.

And so the unit economics for this stuff just looks remarkably good. And so the question is like, will that pricing power hold, one, and two, will they work? Like, will they be reliable, at least as reliable as humans, if not more reliable? Like, can you trust them? Will your customers be happy with you? but because that bomb cost, the cost of the equipment, the materials that goes into it is so low, you don't need crazy high pricing. There's no premium on a robotic-based system to replace a human labor-based system, generally speaking.

I think that's right. And actually, there's a subtle connection here to batteries and battery costs and battery performance and electrification in general. And you mentioned utilization, right? So if you are building a robot, it is still substituting CAPX for OPEX effectively, right? You're taking OPEX, which is human labor cost, out of the equation for some number of years,

and you're investing a big chunk of CAPEX up front in order to do so in terms of building the robot. And so because of that, in general, utilization is really important for the techno-economics of any robotic system. high utilization to get that rapid payback period or IRA. And battery technology coming down has a couple of impacts on that economic equation. One is that, yes, the CAPEX in general just becomes cheaper because the power system for the robot has become much cheaper, battery and a

motor. And secondarily, all of the other operational costs generally tend to fall. You know, the cost of energy, right? If you're running a robot off of an onboard engine, it's going to be a lot cheaper if you're running it with a battery, and that favors higher utilization. Generally speaking, electronic components, motors, for example, relative to an engine, electric actuators relative to hydraulic actuators. They're also more, they also have lower operations and maintenance costs. they're more durable. And so running these systems electrically tends to be able to get you

the kind of high utilization and low maintenance costs and low operational costs that you need in order to make that equation pencil. So in a way, actually, electrification, which I know is a theme that you guys talk about a lot on catalyst, but electrification is really good for robots as well. They sort of go arm and arm.

Yes, although I would say the two things that sort of, these are not enough to stop the tide, stem the tide of the robotic revolution. The two things that sort of point in the opposite direction to me that are related to what you just described are, one, electrification is great, and robotics is a form of electrification, but when electricity prices are rising, it's harder, and electricity prices are definitely rising, so that's one. And two is this cap-ex-op-x thing, right? Which I hadn't really thought about, but it is a good point.

It is similar to not just batteries, like renewables, right? Renewables are relative to fossil generators are all CAPEX and very little OPEX as compared to fossil generators, which are some CAPEX and some OPEX. But the challenge of the high-C-CAP-X-low-OPEX switch in today's environment is that interest rates are high. And when interest rates are high, the cost of financing stuff is higher, and you have to finance more if you're trying to get a payback on your CAP-X. So both of those things are probably marginal headwinds, I guess, against the robotic revolution. Like, I haven't heard anybody saying, well, I would automate this system, but the cost of electricity is too high.

Just again, because the unit economics otherwise are so good. But you could imagine that being a factor. And similarly, we have seen folks who are having to finance deployments of a fleet of robots of one kind or another, and the cost of capital does matter to them. So, either of those could be transient, and you could see even more tailwinds in the future if they go away. But those are the two things that I think from a macro level make it, I don't know, marginally more challenging, I think. I agree, especially on cost of capital. I think that's the bigger constraint, right?

And that is why we see there's this idea of like a RAS model, a robotics as a service business model, which, you know, shifts the cost of capital from the customer to the robotic producer. And actually, I think that's generally the way we're seeing some of these systems get rolled out. It also helps because sometimes a robotics company can make sure that their product is utilized more if they're able to deploy it amongst a bunch of customers rather than just sell it to one customer. So that takes the edge off, but I agree, cost of capital is a concern. One of the reasons that it's so important that the capex, just the cost, has come down so far. power plants are becoming a reliable way for utilities to manage capacity. But enrolling devices

is just the start. What really matters is confidence, knowing those resources will perform when dispatched and being able to prove it from the control room to the living room. Energy Hub's platform handles the full picture, from near-realtime forecasting, locational dispatch, and the kind of rigorous verification that holds up when regulators, grid operators, or leadership, ask, did it deliver? easy enrollment creates momentum, proven performance builds trust. That's why more than 170 utilities rely on Energy Hub to manage over 2.5 million devices delivering 3.4 gigawatts of flexible capacity. See what that looks like at energyhub.com. We're living through a profound economic shift, and energy sits at the center of all of it.

Trillions of dollars are flowing into power plants, transmission lines, battery factories, data centers, but the future of energy isn't shaped by technology alone. It's shaped by markets, by policy, by capital, and by the institutions that connect them. I'm Alfred Johnson, CEO of Crux, the capital platform for the clean economy. Join me for my brand new show, Critical Capital, as I talk with people deploying capital, shaping policy and building projects. Together, we unpack how risk is priced, how incentives are structured, and how progress is actually made. Listen to Critical Capital Capital on Spotify, Apple, or wherever you get your podcasts. Are you tired of overpaying for big-name PR firms, but not really knowing what they're delivering?

Is your comms team wasting time reviewing lengthy messaging briefs and decks, instead of engaging journalists or producing content? Are you wondering why your competitors are getting press and you aren't? Fish Tank PR is 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. Whether you need to position yourself as a thought leader in between project announcements or translate complex ideas and technologies into tangible, compelling stories that resonate with the media, Fish Tank can help. Check out fish tankpr.com. That's F-I-S-C-H-Fish-Tankpr.com. Okay, so we're talking about robotics in a very generalized sense, and you've mentioned, you know, building stuff. But I do want to talk about it specifically in the context of energy and climate, what we spend our date.

on. So talk about where you think there is the greatest applicability, the most promise for this new wave of robotics in, let's say energy in particular. Yeah. So, as I said at the beginning, I'm increasingly cautiously optimistic about generative AI in the digital world. Large language models, I think, are starting to show some real promise, you know, making gains across lots of areas of knowledge work, which does apply. in just about any enterprise in the energy sector, for example. But it is super hard to get excited for the implications for energy and climate tech in terms of the big picture. And so generally speaking, I think where robotics come into play and where they can make a real difference is in manufacturing and construction. And getting down to brass tax, like what we're starting to see, I know a bunch of us at EIP are starting to see in the market, are these very use-case-specific,

I think the investment firm F-Prime, which puts out an annual robotics report, which is really good, calls them vertical robots, right? The robots that are built for a very specific vertical sector, really in kind of an increasing array of applications that are relevant for climate tech. So, you know, there's, there's a number in our portfolio at EIP that we can point to.

It's a company called Infravision, for example, that has a robotic system, which consists of a quadcopter drone, kind of like you see all over the place these days, but it's a somewhat specialized version of that. But even more importantly, connected to this ground-based system, which enables the drone to string a transmission conductor and be a tool to help facilitate, make much safer and faster the process of stringing transmission lines, which, as we know, is one of the bottlenecks in terms of cost and speed in the energy system today.

We think that they can make a real difference there. So that's one example. And really, these robotics companies range far and wide because, increasingly, again, they're able to operate in much less structured environments than, you know, the industrial robots we've seen in the past. One thing I want to point out this interesting about Infrovision is people think of robotics as being one-for-one replacement for, like, a human doing a task. And Infravision is a replacement for humans, sure, but humans in helicopters, basically helicopters

doing tasks, right? And so one of the things that I think is interesting there is, you know, if you're looking for applicable use cases. It's like where, yes, there's like a bunch of expensive manual labor, but human labor. But it's also where we've just like dramatically over-engineered because that's been the only way to build something in the past. And that's where you can get these much more modular, bespoke, much more intelligent, faster solutions to produce the same outcome. It's simultaneously over-engineered, right, like a super expensive person in a helicopter. and under-engineered in the sense that you really don't want to have a helicopter flying anywhere near a transmission tower.

I mean, there are real safety implications there. And I think, you know, there have been people that have been killed over the years, installing transmission conductor in those settings. And actually, I believe that's part of the reason that Infravision was founded, actually in Australia, is to avoid those kind of safety incidents in the future. So, yeah, that is another potential benefit of something. some robotic systems, right, is you can take a human out of a dangerous situation. All right, so Infrovision is a good example.

There's a couple of others that we've invested in but haven't announced yet, so we can't talk about in great detail, but maybe paint a broad brush as to additional categories, whether we've invested or not, that you think there's sufficient opportunity in climate energy. Yeah. So in the past 10 years, right, there's been a lot of experimentation using drones. Again, the sort of standard quadcopter form factor to do all kinds of inspection work across lots of different types of big and tall assets. And that includes, again, lots of stuff in the energy sector, wind turbines, for example.

Inspecting a wind turbine with a drone is a fantastic use case because yet again, as in the case of information, the alternative is sending a person to client. a hundred meter tower or higher and attach themselves to a giant wind turbine nacelle and climb out on the blades connected by ropes. Like this is dangerous, difficult work. It's hard to find people who have the stomach for. Sending a little drone up to collect imagery of that turbine is a fantastic alternative and that application has gotten a lot of traction. But, you know, again, as robotics technology improves, especially the AI side, which makes these systems capable of interacting with their environment in more complicated ways, we're seeing a transition just from doing inspection work to doing actual maintenance work. So now there are a handful of robotics

companies that are doing maintenance on wind turbine blades, for example. Another area that we're seeing robotics come into play is in the construction of renewable assets. So there's also a handful of companies out there that are showing a lot of promise in large-scale solar project installation. That's another area where you have to find people, lots of people who want to go out into, in some cases, the middle of nowhere in a typically hot, sunny place, and do extremely repetitive work, lifting heavy objects. I think average kind of solar panel now weighs something like 80 to 100 pounds. Yeah, I think it's the new ones, because they're getting bigger and bigger, because you're making bigger and bigger modules. So like your 700 watt module now is 80 plus pounds,

which like, as you can imagine, it now takes two, often three people to lift it. And you're taking it like a long ways actually out in the field. You have to kind of see it to really understand it. But like there's just a lot. And that's just the, that's just the, that's just the, the, the, pick in place of the module, right? But like all these systems also have tracker systems, and there's actually a lot of work to be done to install the tracker, install the panels on the tracker, fix them, all that kind of stuff. So it is, it's a remarkable feat of engineering and construction that we build these multi-hundred megawatt solar projects, but it's, it is an incredible amount of labor. It really makes my shoulder hurt just thinking about it.

And as solar project, you know, you can kind of envision as like the perfect frontier, I think, for robotics today because the work is very repetitive, right? I mean, you're doing largely the same thing over and over, in some cases over thousands or tens of thousands of acres with thousands of these solar panels, the exact same systems. But the terrain is complex enough. There's enough differences in how you have to approach, you know, installing the racking system in slightly hilly terrain or, you know, depending on the, you know, the moisture content of the ground, right? And installing the panels on a tracking system themselves, right? Like, you can't completely automate that in the same way you do so in a factory.

There's enough. enough chaotic elements that means you really do need the next level of AI and robotics in order to automate things effectively. But it's not so challenging. It's not so chaotic that you need robots that are capable of responding to anything that comes at them. Right. We know one of these companies did like a pilot out in the field in somewhere in the southwest of the United States. And it was like a one-month pilot. And over the course of that month, they experienced like every type of ambient condition. Like there was everything from like a 110 degree day to high winds to sleet to ice, to, you know, like the, just the moving out of

the factory and into the world, if you're trying to operate as close to 24-7 or at least every day as you possibly can, they're just ambient conditions you have to deal with in addition to undulating terrain and whatever else it might be. So yeah, I do think of there being a spectrum here of like on one hand you have a robot sitting sedentary in a factory, you know, doing the same thing over and over and over again with very few things that can screw it up. That's by the easiest application of a robot. On the other end of the spectrum, I don't know, is maybe like a fully autonomous vehicle that has to plan for every possible edge case in the real world and has like enormous safety implications every time it tries to do anything. And that's like a really,

really hard problem, which obviously we're making a lot of progress on thanks to Waymo and folks. But this kind of like field construction type of thing is somewhere in the middle of that spectrum, I think. Totally. Yeah. I think the question you have to ask if you're considering a robotic solution is just like, how long is the tail of weird stuff that might come up that it might have to deal with? And in the autonomous vehicle case, that tail is extremely long, right?

You're going to encounter some weird shit in a city in San Francisco driving along the streets. Everything is sort of an exception, whereas in a solar field, there's a lot of exceptions to the norm you're going to encounter. But it's manageable to be able to build a robotic system relatively quickly that can take a lot of significant human labor out of the equation. And, you know, I think the more, I think the more, that roboticists are looking for these applications across the energy world, the more they're finding them and developing robotic solutions. So we see them in vegetation management, for example. We have in our portfolio company at EIP, a company called Sive Motors, which makes an electric autonomous commercial lawnmower for mowing big commercial lawns. We're also seeing some

specialized versions of that that are that are being developed specifically for large solar projects where they have to sort of sneak under the panels right and and do vegetation management which actually is a significant expense one of the larger operations operations and maintenance expenses on large solar projects we're now seeing robots applied to an unfortunate area of of climate tech which is wildfire mitigation, everything from robotic systems that are clear-cutting and burning areas of, you know, overgrowth near, for example, electric power assets to prevent ignition to companies. I saw recently a company that's using a drone to go in and doing thinning in forests,

both for kind of forest management and collection of, you know, woody biomass for various purposes. So, you know, it's kind of hard to say anything. It's hard to make blanket statements about where the opportunities are because I think we're just going to see them popping up more and more in these vertical robotics applications.

What we've been talking about so far mostly are this host of companies, there are tons of them now, that are like applying robotics to a specific vertical and doing generally some version of that robots as a service type model. There are various versions of it, but generally that is what they're doing. They're not selling systems usually. They're operating those systems and selling a service.

But that's not really the only category of like novel robotics companies. And so I'm interested in how you've been thinking about where the opportunity lie in the application of robotics into energy and climate. Is it in these like find use case, build, robotic system, deploy system for that use case types of businesses, or are there others that you think are interesting as well? I do really like the vertical robots, the find use case, build a robot to solve that use case, or a collection of related use cases world. And, you know, I think what we need to see from companies in that, you know, that, that taking that strategy that they can get off, I think for companies that are adopting that

strategy, they need to be betting on a significant first to market or one of the first to market advantage. And what I mean by that is they need to be able to get their units, their robots, out in the field early and start to learn about those kind of strange exceptions that they're going to be encountering in the field, start to collect more and more data. so that they can train their robotics model to do things more and more efficiently. So that two to three years in, when another company comes along and thinks to themselves,

hey, robotic components have gotten a lot cheaper, and I think I could build some sort of robotic system to solve the same problem or a similar set of problems. That company A, who entered first, will have enough of an advantage and come down the performance and cost curve fast enough that they'll be able to maintain that lead and that they'll be sort of the obvious choice for potential customers. And I think we are at this kind of inflection point in the

robotics market where it is now possible to build a solution fast enough to get it into the market fast enough and actually get it into the field fast enough to generate that kind of a data moat and a training moat. And just sort of a standard sort of learning curve. So that's why I think that that space, you know, is pretty rich and, you know, really like seeing companies developed there for new use cases in particular. The other places you could make a bet, I think at the other end of the spectrum, and there are plenty of, there's a lot of bets or a lot of capital being made, a lot of capital being put into bets in this side of the spectrum is the general purpose robot and the most, the marquee version of that is the humanoid robot,

right? And the theory of the case there is that the world that we live in is the world that humans built, and therefore lots of tasks are well suited for a humanoid form factor. And that goes for both in controlled settings like factories as well as in the field. And, you know, there have been at least in the hundreds of millions of dollars invested. Now, I think in some cases in the billions of dollars invested in individual companies that are developing humanoid robots with that theory of the case, that they will be more general purpose and can apply to a way. wider range of tasks. There's a bunch of reasons why that is a, I think, at least one order of magnitude, maybe a couple orders of magnitude, harder problem than building these kind of specialized robotics as a service. Obviously, it's a problem that some companies think that

they have a good chance at solving, you know, Tesla being sort of the most preeminent example. Right. Okay. So those are good categories. I think there's maybe a couple more worth highlighting for a moment that are not specific to energy or climate or anything, but just like out there in robotics world. One is the kind of generalized models, the equivalent of the LLMs, but for robotics. Some of those are popping up right now and also raising a lot of capital. And then the other category, maybe on the other end of the spectrum, is just like components for robotic systems, you know, selling bits and pieces. and bobs that are going to go into robotic systems under the assumption that we have a big growth market. And so if you're the best at selling whatever widget that needs to go into every

robotic arm or something like that, then you've got a big business. How do you think about those two categories? Right. These are the picks and shovels for robotics, the inputs to robotics. Yeah, on the AI front, there is this category of robotic, so-called robotic foundation models, which, yeah, are kind of trying to be like an LLM for movement, a large movement model. There's a variety of ways to try to describe it. And then there's also a category that's related, which is sort of other software tools for accelerating the development of robots. For example, simulation software, which tries to build in realistic physics engines so that you don't have to collect data from a robotic. system moving around out there and interacting with things in the real world that you can actually

do lots of collect lots of that data virtually in a simulation before you actually deploy things physically which could make a real big difference because otherwise you know you unlike in the case of training large language models where you have the entire corpus of the internet to work with just this mind-boggling amount of data out there if you're just a trying to collect data to train a robot, kind of the only way to do it is to go out and have the robot go and do stuff. And that just takes real clock time and clock money that the LLMs have not had to deal with. And so I think, you know, the next generation of simulation software could be really valuable in this case. I don't know about the robotic foundation model world as much. I have

my skepticism about that approach, kind of in a similar way as I have some skepticism about LLMs themselves, which is that I'm not sure about the long-term moat. And I'm also not convinced that the companies who are building robots, especially really, really highly sophisticated robots, are willing to cede that part of the value chain to a third party. So, you know, curious about it, but come to it with a bit of an eye of skepticism. And then, like you said, there's all the non-software components, too. There's sensors. It's perhaps, you know, maybe we'll get to that next generation of LIDAR,

cheaper and better LIDAR sensing solutions. Maybe it's some other sensing modality. There's actuators and motors. You know, robots are in many ways sort of like more complicated, autonomous vehicles. They have to have a lot of the same sensing systems embedded within them.

They have to have actually probably more of the actuation systems because if you're building a humanoid it has a lot more joints than a than a standard car, right? And so yeah, you're going to, I mean, that may be an area where

the best bet is to make on the existing suppliers, and it very much is sort of a boring but not so boring picks and shovels bet on the robotic revolution. All right. Well, I think we've covered the first level of robotic obsession. There are many levels beneath that, into which we're both diving at the moment, but can cover another time. So, Andy, thanks again for your time, as always.

Always happy to be here and always happy to talk about robots. It's one of the things that's most... It's most palpably exciting, right? Like, you can just, everyone can think about a robot and see how it might solve some real problems and do things that you just don't want to do. I'm picturing, like, middle, what I imagine middle school, Andy, to be like,

and I imagine he was probably into robots. Yeah, he's not so far away. Andy Lubershane is my partner and our head of research at Energy Impact Partners. This show is a production of Latitude Media. You can head over Latitude Media.com for links to today's topics. Latitude is supported by Prelude Ventures. Pralood Backs Visionaries, Accelerating Climate Innovation

that will reshape the global economy for the betterment of people and planet. Learn more at PreludeVentures.com. This episode is produced by Daniel Waldorf. Mixing and theme song by Sean Marquan. Stephen Lacey is our executive editor. I'm Shale Khan, and this is Catalyst.