The coming robotics wave

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.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  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. Jigar Shah, 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 podcasts or follow it at latitudemedia.com.

• 0:35Speaker 01

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• 0:40Shayle Kann?

  I'm Shil Khan, and this is Catalyst.

• 0:44Speaker 03

  Everything it takes to build a robot is much cheaper now, and you can build them much better with AI.

• 0:50Shayle Kann?

  Coming up, the robots are coming.

• 1:04Speaker 04

  Catalyst is brought to you by Antenna Group, the communications and marketing partner behind the most influential companies in energy, climate, and infrastructure. For three decades, Antenna has helped ambitious companies stand out, build market leadership, and become category-defining brands. From breakthrough startups to global industry leaders, their team brings the expertise, relationships, and track record to accelerate your momentum. Learn more at antenna group dot com.

• 1:31Speaker 00

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• 2:03Speaker 04

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• 2:37Shayle Kann?

  I'm Shayle 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 about ad nauseam 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,

• 3:22Shayle Kann?

  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 Lubrashain, Catalyst regular and EIP'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.

• 3:57Shayle Kann?

  Andy, welcome back.

• 3:58Speaker 03

  Thanks. I think this is my first catalyst pod of the brave new world of 2025.

• 4:04Shayle Kann?

  What a world 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 and so you could do more with robotics and capabilities are 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?

• 4:35Speaker 03

  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 of 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 but next level value in LLMs. So I, you know, 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?

• 5:18Speaker 03

  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, you know, some big, I think, big secular macro tailwinds that are really blowing in the favor of robotics. And that's both on the 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 to build all of the stuff we're going to

• 6:00Speaker 03

  need to 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 US has escaped from this global demographic challenge

• 6:45Speaker 03

  that some other advanced economies haven't in the past decade or two is, you know, 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 in the sectors that we care about the most when it comes to decarbonization and really anything having to do with energy,

• 7:29Speaker 03

  which are, you know, basically manufacturing and construction, labor productivity has been flat really for the past 10 to 15 years. And in 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 physical world. And robots are one way to make them more productive. So that's the demand side. What do you think?

• 7:56Shayle Kann?

  Yeah, I mean, one thing that I found 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 I able to build it or not was no. So I hear a lot of the labor is a constraint. It's getting harder and harder.

• 8:39Shayle Kann?

  I don't know about you, but I haven't yet heard the labor was the cause of a failed attempt to build something.

• 8:47Speaker 03

  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, 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, but it's sort of just a general, a drag on, on everything probably that, that is

• 9:31Speaker 03

  harder to, to pin to any kind of specific instance.

• 9:34Shayle Kann?

  Okay. So that's the demand side. And I think that's like a, I don't know, it doesn't feel like, maybe with the exception of restrictive immigration, which could actually provide like a, a significant shock to the system on the labor force side. The rest of it is sort of a 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,

• 10:16Shayle Kann?

  meaning what we can produce for robotics and the cost of it.

• 10:22Speaker 03

  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, I think, a year and a half or so ago. There's this research group at Stanford that built a robot they call Mobile Aloha

• 11:07Speaker 03

  using new methods of, you know, training this very simple, relatively low cost, you know, basically system of a couple of robotics 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 is the has been the challenge in the past for anything in robots. I mean, there are, you know, hundreds of thousands, millions now of industrial robots installed worldwide, which are largely just these robotic arm systems that are doing largely deterministic tasks in factories.

• 11:50Speaker 03

  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 of decades now. But what AI makes possible is to much more quickly train robots to navigate in more complex, chaotic environments where

• 12:21Speaker 03

  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, like AI is making real progress and that I do think unlocks robotic opportunities that were not available even five to seven years ago.

• 13:02Speaker 03

  And then in addition to that, you know, 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, you know, 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.

• 13:42Speaker 03

  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, they had to invest a lot in making sensor technology much cheaper. Other boring things like actuators, you know, just electric actuators for, you know, 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.

• 14:27Speaker 03

  So basically, everything it takes to build a robot is much cheaper now, and you can build them much better with AI.

• 14:34Shayle Kann?

  Well, that's the thing about robotics in general, you know, 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 remarkably fast. Assuming you get high enough utilization, right? So 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.

• 15:18Shayle Kann?

  And so the question is, 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.

• 15:50Speaker 03

  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 CapEx 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 upfront 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. You want to get high utilization to get that rapid payback period or IRR.

• 16:37Speaker 03

  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, you know, 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,

• 17:20Speaker 03

  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 like electrification's really good for robots as well. They sort of go arm in arm.

• 17:58Shayle Kann?

  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 CapEx OpEx 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

• 18:41Shayle Kann?

  to fossil generators, which are some CapEx and some OpEx. But the challenge of the high CapEx, 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 CapEx. 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 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

• 19:23Shayle Kann?

  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 marginally more challenging, I think.

• 19:41Speaker 03

  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 a RAS model, a robotics-as-a-service business model, which 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 agreed, 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.

• 20:28Speaker 04

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• 22:38Shayle Kann?

  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 days 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.

• 23:00Speaker 03

  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 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

• 23:41Speaker 03

  tacks, like what we're starting to see, and I know, you know, a bunch of us at EIP are starting to see in the market are these these very use case specific, I think the the investment firm F Prime, which puts out an annual robotics report, which is really good, calls them vertical robots, right, they're 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.

• 24:22Speaker 03

  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 and be a tool to help to help facilitate, make much safer and faster the process of of stringing transmission lines, which, as we know, is one of the bottlenecks in terms of cost and and speed in the energy system today. We think that they can make a real difference there. So, you know, that's one example.

• 25:07Speaker 03

  And, you know, really, the these, these robotics companies, you know, 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.

• 25:22Shayle Kann?

  One thing I want to point out that's interesting about Infravision is people think of robotics as being a 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're, 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 like much more modular, bespoke, much more intelligent,

• 26:05Shayle Kann?

  faster solutions to produce the same outcome.

• 26:08Speaker 03

  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, 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 that Infravision was founded, actually in Australia, is to avoid those kind of safety incidents in the future. So, yeah, that, that is another potential benefit of some robotic systems, right? Is you can take a human out of a, out of a dangerous situation.

• 26:50Shayle Kann?

  All right. So Infravision's 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, in climate energy?

• 27:11Speaker 03

  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 Infravision, the alternative is sending a person to climb a 100-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

• 27:52Speaker 03

  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

• 28:30Speaker 03

  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 know, 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, is that right?

• 29:12Shayle Kann?

  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 pick and 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's a remarkable feat of engineering and construction that we build these multi-hundred-megawatt solar projects, but it is an incredible amount of labor.

• 29:58Speaker 03

  It really makes my shoulder hurt just thinking about it. And a 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

• 30:40Speaker 03

  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 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 like robots that are capable of responding to anything that comes at them.

• 31:16Shayle Kann?

  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 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, there are 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

• 31:59Shayle Kann?

  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 probably the easiest application of a robot. On the other end of the spectrum, I don't know, it's 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

• 32:30Shayle Kann?

  Type of thing is somewhere in the middle of that spectrum, I think.

• 32:33Speaker 03

  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? Like, you're gonna encounter some weird shit in a city, in San Francisco, driving along the streets. Everything is sort of an exception, whereas, you know, in a solar field, there's a lot of exceptions to the norm you're gonna encounter, but, you know, it's manageable to be able to build a robotic system, you know, relatively quickly that

• 33:11Speaker 03

  can do, take a lot of significant human labor out of the equation. And, you know, 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. You know, we have in our portfolio company at EIP, a company called Scive Motors, which makes an electric autonomous commercial lawn mower for mowing big commercial lawns. We're also seeing some specialized versions of that that are being developed specifically for large solar projects, where they have

• 33:55Speaker 03

  to sort of sneak under the panels, right, and do vegetation management, which actually is a significant expense, one of the larger operations and maintenance expenses on large solar projects. We're now seeing robots applied to an unfortunate area of climate tech, which is wildfire mitigation. Everything from robotic systems that are, you know, 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

• 34:38Speaker 03

  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...

• 34:51Speaker 03

  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 these vertical robotics applications.

• 35:05Shayle Kann?

  What we've been talking about so far mostly are this like 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 but generally that is what they're doing. They're not selling systems. Usually they are 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 how you've been thinking about where the opportunities lie in in the application of robotics into into energy and climate.

• 35:46Shayle Kann?

  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?

• 35:56Speaker 03

  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 are taking that strategy that they can get off. I think 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

• 36:38Speaker 03

  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 themselves, hey, you know, robotic components are have gotten a lot cheaper and I think I could build some sort of robotic system to solve solve the same problem or similar set of problems. You know, that company A who entered first will have enough of an advantage and come down the 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. For potential customers.

• 37:21Speaker 03

  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 mote and a training mote and just sort of a standard sort of learning curve. So that's why I think that that space is pretty rich and 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

• 38:05Speaker 03

  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 there have been at least in the hundreds of millions of dollars invested now, I think

• 38:48Speaker 03

  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 wider, a wider range of tasks. There's a bunch of reasons why that is a I think in 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 that some companies think that they have a they have a good chance at solving, you know, Tesla being sort of the the most preeminent example.

• 39:32Shayle Kann?

  Right, okay, so those are good categories. I think there's there's maybe a couple more worth highlighting for a moment that are not specific to to energy or climate or anything, but just like in out there in robotics world, one is the kind of generalized models, the equivalent of the L L M's but for robotics. Some of those are are popping up right now and 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 for robotic systems, you know, selling bits and pieces and bobs that are going to go into robotic systems under the under the assumption that we have a big growth market. And so if you're 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?

• 40:17Speaker 03

  Right, these are the the picks and shovels for for robotics, the inputs to robotics. Yeah, on the on the robotic on the AI front, there is this category of robotic so-called robotic foundation models, which, yeah, are kind of trying to be like like an L L M for an L L M for movement, a large movement model. You know, there's a variety of ways to try to describe it. And then there's 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

• 40:58Speaker 03

  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 the entire Corpus of the internet to work with, just this mind-boggling amount of data out there. If you're 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.

• 41:39Speaker 03

  And that just takes, that takes real clock time and clock money that, 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, I don't know about the, the robotic foundation model world as much. I have my skepticism about that, about that approach, kind of in a similar way as I have some skepticism about LLMs themselves, which is that I'm not sure, I'm not sure about the long-term moat. And I'm also, you know, not convinced that the companies who are building robots, especially really, really highly sophisticated robots, are willing to cede that part of the, of

• 42:22Speaker 03

  the value chain to a, 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, 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, there's actuators and motors. You know, robots are, are in many ways sort of like more complicated autonomous vehicles. Like they have to have a lot of the same sensing systems embedded within them.

• 43:03Speaker 03

  They have to have actually probably more of the, of the actuation systems because you, you know, if you're building a humanoid, it has a lot more joints than a, you know, than a, than a standard car, right? And, and so, yeah, you're gonna, you're gonna, 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, a boring but not so boring picks and shovels bet on the robotic revolution.

• 43:34Shayle Kann?

  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.

• 43:49Speaker 03

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

• 44:09Shayle Kann?

  I'm picturing like middle, what I imagine middle school Andy to be like, and I imagine he was probably into robots.

• 44:16Speaker 03

  Yeah, he's not so far away.

• 44:20Shayle Kann?

  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 to latitudemedia.com for links to today's topics. Latitude is supported by Prelude Ventures. Prelude 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 was produced by Daniel Waldorf. Mixing and theme song by Sean Marquand. Stephen Lacey is our executive editor. I'm Shayle Khan, and this is Catalyst.