Apptronik has a totally different approach to building humanoid robots

humanoid robots apptronik

Who will win the race to have the world’s first usable general purpose humanoid robot? I thought I knew all the companies making general purpose robots:

  • Tesla
  • Sanctuary AI
  • Figure AI
  • Fourier Intelligence
  • Agility Robotics
  • Boston Dynamics

I was wrong … there’s probably a bunch I don’t know. But one that popped up as interesting is Apptronik. They’re based in Austin TX, they’re partnering with NASA, and they’re building Apollo, a 5’8” 160-pound robot.

In this TechFirst podcast, we chat with CEO Jeff Cardenas. And we learn that he has a completely different approach to building a humanoid robot than probably every other robotic company out there. Keep scrolling for more, or hit the Forbes post for my take on one part of what Cardenas said regarding robotics and international competitiveness.

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TechFirst audio podcast: Apptronik’s ‘Apollo’ humanoid robot

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Transcript: humanoid robots, work, and the future with Apptronik CEO Jeff Cardenas

John Koetsier:  Who will win the race to have the world’s first usable general purpose humanoid robot? Hello and welcome to tech first. My name is Jonkitz here. I thought I knew all the companies that are making general purpose robots, right? There’s Tesla, there’s Sanctuary AI, there’s Figure AI, Fourier Intelligence, Agility Robotics, Boston Dynamics.

I’m sure there’s a bunch more that I don’t know, but I know that I was wrong because one that just popped up that launched this week is. Apptronic, they’re based in Austin, Texas. They’re partnering with NASA. I want to hear more about that. And they’re building Apollo, a five foot eight, 160 pound robot.

Here to chat is CEO, Jeff Cardenas. Welcome, Jeff. 

Jeff Cardenas: Thanks for having me here. 

John Koetsier: There’s so much competition right now. What is going on? 

Jeff Cardenas: It’s an exciting moment. I think for robotics and the world as a whole, we finally reached an inflection point. And it’s funny because when we first got started, everyone told us not to do humanoids.

And now everyone’s getting into the race. But it’s been exciting and interesting to see it all play out. 

John Koetsier: Everyone is doing humanoids, and that’s a real challenge, right? There’s pieces that are known and capable. Shoulders, necks, maybe, right? Walking with a bipedal robot is not necessarily the easiest thing in the world, but it’s been done, and it can be done.

Really challenging parts, obviously in the brain and the hands and fingers, we’ll get into all that. Tell us about Apollo, which you’ve called the world’s most capable humanoid robot. 

Jeff Cardenas: Yeah, so Apollo is the result of many years of hard work and research and development. At Abtronic, we’ve built 13 different robots overall in eight iterations on humanoids.

So we started in humanoids when we were still working in the lab at the University of Texas at Austin. Started working with NASA back then for the DARPA Robotics Challenge. Two of my co-founders, Dr. Nick Payne and Dr. Luis Cintas, were on the Valkyrie team. And basically, Aptronik was created in 2016 to commercialize the work out of NASA.

So back then, Valkyrie was… Millions of dollars. It was 300 pounds, but it was one of the very first electric humanoid robots. So we felt like, Hey, general purpose robots, more versatile robots are going to be the future. Electric is going to be the way to go. And we want to build a commercial version of this.

And so. Got it out into the world now, finally, seven years later, in many years of work to get here. It’s really, 

John Koetsier: It’s great to hear that because you launched with Apollo yesterday, right? And so the world wakes up and says, Oh. What’s this new company? What are they doing? Right? And it’s like that old phrase, like an instant success.

You just weren’t around to see all the work that went into it, right? So you built a bunch of robots already. You built a number of iterations on the humanoid robot. Talk about that journey a little bit. 

Jeff Cardenas: Yeah, for us, we always saw that this was really a technology problem more than was a market problem.

I think a lot of entrepreneurs and other folks are looking to get into this space because they see the market opportunity. But for many years, the technology problems had to be solved to make it viable. So it’s interesting to hear you say, walking, we can do that. That was not the case even.

Five years ago, we had no idea how to do dynamic walking. Boston Dynamics was really 10 years ahead of academia in terms of the type of walking that they were doing. And everybody was trying to figure out how to catch up and do what they were doing for many years. And so, piece by piece, we had to solve these problems.

And, the way that we viewed it was, this is a technical challenge, and we need to solve the key pieces that are needed to make this real. How do we go towards viable, commercial, general purpose robots? And we basically just broke the problem down into, and from, and solved it from first principles.

So started with electric actuation for humanoid robots, we’ve done over 35 iterations on electric actuators. Some of those are small, medium, large of the same family of actuators, but a tremendous amount of R&D there. Elon’s talked about the need for actuators for these robots. And that’s been our body of work.

That was my co-founder, Dr. Nick Payne. That was his thesis in grad school was next generation actuation for legged robots. And, the electronics didn’t exist. We needed more real time communication because you have a lot more sensing in these robots. And then certainly the software, which I’m sure we’ll get into, but we started basically at the foundation and we bootstrapped the company.

So I mentioned, it’s funny that everyone’s into humanoids now, because when we got started, everyone told us, do not build hardware, focus on the software, focus on the AI. And the problem was the robots didn’t exist. And we’re like, well, what are we going to put this AI on eventually as it matures and develops, we don’t have the robots yet.

So we have to build these systems. And so we bootstrapped ourselves and what we would do is we would work for other companies. We’ve worked with several big automotive companies looking at things like humanoid robots and we’ve helped them. Build their systems. We’ve built and delivered a variety of systems, including some of the robots for sanctuary.

We’ve partnered with sanctuary in the early days and they’ve been a great partner along and we built their first prototype for them. And each time that we would. We would build these robots. We would iterate, we would learn something new, all getting towards the point of building the robot. We always ultimately wanted to build, which is Apollo.

And so, the thing that I love about robotics is, you got, at the end of the day, you can talk about what a robot’s going to do, but you have to show it in the real world. So our philosophy has always been show versus tell. So we didn’t have a need to really get out there and say, Hey, we’re going to do this.

Our view was like, well, let’s do it. And then we’ll show off what we do. And we’ll let our work speak for itself. And so we really had our heads down over these years, just. Trying to get this stuff working, solving the technology problems iterating pretty quickly as well. And, we’ve had robots walking for 7 years.

We’ve iterated on, we’ve built full systems in 3 months. So it’s not that we’ve been taking our time doing this. We’ve actually been cracking these problems and we’re at this point where. We’ve met the threshold where everything is good enough, which I think of this like the personal computer in 1982, right?

It’s like, it’s the beginning of, a lot of things had to build on each other and converge for this breakout moment to happen, but we’ve got that work behind us. And I think the robot we’ve put out there we’re really proud of and excited to see where it goes. 

John Koetsier: I love that approach. I really love that approach because you didn’t put a guy in a suit and walk up on a stage and say, here’s our robot.

Right? That has a couple hundred year history. I’m glad you didn’t do that. Super. Interesting in terms of the approach talk about before we get into the details of the robot, give us the high level specs. I mentioned five foot eight, 160 pounds. I think it’s five hour battery life. Is it a swappable battery?

Is it a hook it up and charge? How fast can it go? What can it do? 

Jeff Cardenas: Yeah, so 5 ft 8 weighs 160 lbs, it can lift 55 lbs, and it has a 4 hour battery initially, and it’s swappable. So we’re targeting 22 hours a day, 7 days a week, uptime. It can also be tethered as well, and opportunity charged, like what in autonomous mobile robots.

It is fully electrically actuated. We, as I mentioned, we’ve had a tremendous amount of iteration in that space over the years. So, we think that we’ve got a really unique solution for performance and cost, right? Performance at cost. So there’s a trade off where you’re, you can purely focus on performance, which to me, Atlas is an amazing machine.

The Boston Dynamics robot … It’s like a formula one car. It’s really performance optimized but is very difficult to mass manufacture Atlas, it’s got custom hydraulics and other things in it. And so what we’ve really focused on is how do we get performance at cost? How do we find the right trade off and ultimately build a commercial product that we can build for less than $50,000 as our target.

And it can still have the performance that’s needed to do the work that we needed to do. And then through COVID, we learned a lot about the supply chain. And so a lot of the ideas that are now in Apollo are getting around. Supply chain constraints so that we can really scale this thing up into big volumes and we don’t have any single source vendors in terms of what it does.

Initially, we’re focused on what we call gross manipulation, and that’s compared to dexterous manipulation, and we’ve learned that because we’ve built a lot of robots over the years, and dexterous manipulation is very difficult. We have a ton of respect for folks that are going after that in this space.

But it’s a really difficult problem. And the exciting thing for us at this juncture is we don’t have to solve that problem to get these things out into the world. Turns out there’s a huge shortage in logistics. And a lot of those tasks are just moving boxes or totes from point A to point B. And that’s something that we know how to do now.

And so that’s where we’re going to start, but then the beauty of a general purpose robot. It’s a software update away from doing something new. And so we’ll continue to get more advanced as we move into this and get them out into the world. 

John Koetsier: Super interesting to talk about hands and gross manipulation versus dexterous.

One robot CEO that I chatted with before said, the robot’s basically a hand delivery mechanism because the hands do all the work. Right. And he said, actually, creating a hand, a robotic hand, like the human hand and capability is beyond our capability right now. It’s not just beyond any one company, it’s beyond human capability right now.

There might be some different opinions on that we’ll see, but that’s where, of course, maybe half of the degrees of freedom that a robot might have exists. So, it’s a really challenging thing. And then, of course, wear and tear. All those little motors in the hands, skin, whatever you use for skin, super, super hard.

So I see that challenge. You talked about a software update, which is amazing. That’s incredible. Is there a possibility of a hardware update? So let’s say three years from now you crack human hands, maybe not quite as good as this cause you want to hit your 50, 000 target level, 90%, 70%, whatever enough for many manufacturing type jobs.

Can you like, take a hand off and plug a new hand in. 

Jeff Cardenas: Yeah. Yeah. So Apollo is modular. There’s this big debate of wheels versus legs too from the traditional folks in automation. Like what do you need legs for? We can use wheels in all these applications and what we’ve done with Apollo is just taking everything we’ve learned because we’ve been building these robots with customers over many years.

And so, We’re able to take all of that learning and inject it into Apollo. And some people are going to want these things on wheels. There’s a big, huge number of advantages to legs. We think legs will win the day. Overall, there’s this problem with legs that the robots can fall over. And so in some cases you can have wheels.

The beauty of robots is you can have your cake and you can eat it too, and that you could build them to be modular. So Apollo is modular at the torso. So if you want to put it on wheels, you can throw it on wheels. We think that will demonstrate that legs will be the most versatile platform longterm and.

The reason we know about the challenges of wheel bases is because we’ve designed them. And so we’ve deployed versions of humanoids on wheels and we’ve learned from that. And so the same thing is true with the end effectors. I agree that I’m sure that’s Jordy that’s saying hands and, I agree that long term the humanoid needs hands, but in the near term.

There’s many applications where you don’t require a full five fingered hand and you can do things with a one degree of freedom hand. There’s a whole range of things you can do. There’s a whole range of things that robots do today with pincher grippers or, and so you can expand and you can, you don’t have to solve all the problems at once.

I have a ton of respect for Geordie. I’ve worked with Geordie over many years. He’s a visionary. But we’ve just taken a different approach in terms of how we’ve thought about that. And we want to partner with folks like Sanctuary. They’ve been a big partner on it with us. They can put their hands on a robot like Apollo, and we can work together there as they start to crack the dexterous manipulation problem.

So yeah, it’s modular at the chest. It’s modular at the end effectors, it’s also modular at the head as well in terms of putting different sensor payloads on it. So we have a standard sort of camera based vision system, but there’s also debates about LIDAR. Do you need lighter or not?

Our vision approach doesn’t need LIDAR, but in some cases, when you start to put these robots outdoors, if you want to add LIDAR, you can. This is something I think Boston Dynamics has done a really good job of with SPOT, is they created the ability to put different mission payloads on the back of SPOT, and something that we learned from along the way and part of what’s designed into Apollo.

John Koetsier: Love it. And as you hinted, Geordie is Geordie Rose. He’s the CEO of Sanctuary AI and the former CEO of a quantum computing company that sold a 15 million quantum computer to Google, but it’s still around. I want to, there’s so many places to go here. I do want to talk about the brain. That’s really challenging, right?

You’ve got to, How are you building intelligence into your robots? Is it pre programmed maneuvers? Is it versatility with a certain level of intelligence? Talk about how you’re doing that. 

Jeff Cardenas: Yeah. So I think the long term goal is to start to get towards more and more intelligence overall.

But I think in terms of AI and intelligence as a whole. For humanoids, you can really break it down into two buckets. So the first bucket is physical intelligence. So that’s like coordination, hand eye coordination, the ability to balance walking as part of that’s physical intelligence. 

The other side is cognitive intelligence.

So how do you make decisions? How do you reason about the world? How do you abstract ideas, things like that. What I’d say is that we’ve really focused on building from the bottom up and there’s different approaches. You can go from the top down, as in, start with the intelligence and think about how to build a machine around that we’ve gone from the bottom up, which is start with the actuators, the motor controllers, the electronics, really the basic building blocks and then build up into intelligence.

My view was that you want to build. The most capable platform you can possibly build and then you can think of these intelligences as software that you can put on top of the robot. There’s people that disagree with that and say, well, in order to get to full intelligence, you need deeper integration. And I think we’ll see, but we’ve really focused on this physical intelligence and.

The exciting thing for me, and you had a question that maybe we’ll get too deep, but it’s like, where are we at? I think of this as really an evolution of what’s already being done out in the world, and we don’t have to solve new problems to get humanoids out into initial applications to show utility for humanoids to be fully realized.

Yes. You need much higher levels of intelligence than we have today to be fully realized. Humanoid, I think, but we have a lot of the building blocks already today. So for example we in, if you think of the evolution of robotics, 2004 collaborative robots came out. Those are human safe robots.

By 2010, compute got good enough. Batteries got good enough. We could have mobile robots. And we started to do things like SLAM and navigation. By 2016, machine learning came to the scene, and we could do intelligent grasping. So what we’ve done is build on all these things that we’ve seen work in production, and really build from the bottom up, and integrate those things together, and taken maybe more a conservative approach than some people are taking, to basically, use what we know works, and use what we’ve known, we can deploy into the world today.

And then. We can always add these other sort of more difficult sort of R and D problems later on down the road. And so, we can dive in deeper where we want to go. 

John Koetsier: It’s fascinating to see the different approaches and that’s the beauty of the sort of free market innovation system that we operate in the Western world, at least where you do have those people who are coming top down and want to build intelligence and the intelligence will do everything.

That’s a risky bet. It’s an amazing bet if you make it and you win, because if you win, you’ve solved everything, quote unquote, everything, right? But if you don’t win, you end up with an expensive boondoggle that doesn’t accomplish anything. It doesn’t, it’s either. Really good, because you can’t have a robot out in the wild, maybe making a sandwich or slicing something up or using a tool that could be dangerous that is potentially dangerous.

Your approach in software mirrors your approach in hardware, which is starting from the ground up. What can I do? What do I know I can do? What do I know I can do today? And that seems to be a very Pragmatic and practical way of doing it. I think that’s super interesting. I do want to go deeper into what this means and what it looks like, but maybe before we do that you’re doing this in Austin, Texas.

And you feel that is significant. Why? 

Jeff Cardenas: I think if you look, there’s people out there that are saying there’s going to be more humanoid robots than people one day. Like I said, it’s funny to me to have that out there when everyone thought these things weren’t viable even.

Five years ago there were novelties. And I think that’s exciting. I’m not sure that they’ll all be humanoids, but I think there will be a lot of humanoids. And I think it’s the most versatile platform you can build. But the reason I think Texas is important is, where are we going to get all the robots we need?

So if you look at the world today. There’s hundreds of humanoids, maybe right? There’s not very many of these systems. So how are we going to go from hundreds to thousands to millions to maybe billions? And I believe that Mexico is going to play a big role in that for North America. I think if you look at Mexico relative to other cCountries where we’re doing manufacturing today.

It’s got a lot of advantages. It’s about a third cost of labor, depending on how you measure it. It’s geographically located, really close to the U. S. market. So we can get from Monterey to Texas in 2. 5 hours anywhere in the U. S. in 24 hours. And they have the skill sets to be able to pull this off.

And so I’ve always felt like the Texas Mexico corridor was going to be one of the most important manufacturing corridors in the world over the coming decades. And this is something that I was saying, coming out of grad school we were, we had two key ideas when we started Abtronic.

One was that robots had to become more versatile. And two was that somebody had to be building. Robots domestically here to serve the U. S. Market. We didn’t have any major domestic O. E. M. S. And we got started. And so if you agree with the premise that, hey, we’re gonna need domestic manufacturers long term, the question is, where is that going to happen?

And Typically, it’s been on the east or the west coast. The big hubs for robotics have been California or Boston, but I think Texas actually has a number of unique advantages over those hubs where I really believe that Texas has actually much better adjacencies than those other places and so I always felt like Texas was the place to do it.

We’re already producing gearboxes and a lot of the heavy machinery. We’re doing a lot of that for the energy industry before. But as you look towards what’s coming next, is there’s a lot of people in Texas that are looking for. Okay, as the oil and gas boom ends, which it will at some point, where do we apply all of this industrial base that we already have built?

And for a number of reasons, I think robotics actually makes a ton of sense for that. And that’s why I think Texas is going to be important. 

John Koetsier: Well, it is interesting. Cost of living is certainly less, proximity to Mexico. I was going to make a joke, what is this access to labor that you’re talking about?

Aren’t the robots going to build the robots? But I’m sure there’s going to be some tricky jobs for humans in all that stuff. Let’s look forward a little and let’s say we’re in a future where we have tens of millions, and we’re progressing. How does this change our world?

How’s it changing our economy? 

Jeff Cardenas: I think that it fundamentally changes the way that we live and work. And the reason I think that is because as humans, our most valuable resource is time and our time here is limited. And, you had great thinkers in the last century, John Maynard Keynes famously predicted that we would have a 15 hour work week.

And so what I think changes is that instead of doing things that we have to do, that somebody’s just got to do, we can now have machines that do that for us. And what that does is free us up to spend time on things that we really value. Why do we spend more time at work than we do with our families?

And the answer to that today is, well, someone’s got to do that. We’ve got to keep the economy running and going. We have to provide goods and services to our fellow man in order to keep all this moving. But I think what robotics has the potential to change is to change that equation. What if the cost of goods and services dramatically falls because They basically will, slope towards the cost of the raw materials as the cost of labor continues to go down.

So goods and services could become much cheaper and much more abundant than they are today. And that frees us up to do, spend time in a way that we want. And there’s this interesting quote that I heard, what did Darwin, Galileo Newton, what do they all have in common? They were all very wealthy, and so they had time to think and contemplate their existence and think about these higher level ideas.

And today you have people that are stuck in a cycle of working all the time to make ends meet. And I think, an optimistic version of the future is you start to free people up. They’re able to think about things like their own health, about taking care of each other. We start to fix the health care, the education system.

And ultimately we evolved as humans. And I think that, applied in the right way. It could be a really positive thing. 

John Koetsier: Super interesting. Okay. So, you’ve launched the robot, you’ve launched Apollo. What can somebody buy or rent today? 

Jeff Cardenas: So today we’re working on pilots and, my whole philosophy, a core sort of value for us at Aptronic is show versus tell.

So what we’ve done is we’ve built a demo center here on site at Aptronic. We’re mocking up the use cases that we’re looking to deploy Apollo into. So for the remainder of this year, we’re basically signing up pilot customers and we have some of the the marquee customers in the world that have already signed up, and we’re doing these on site proof of concepts through the rest of this year, where we’re demonstrating it might what I tell the partners we work with.

If I can’t do it here at my facility, I can’t do it at your facility. So make sure that you’re comfortable with the performance of the robots here, and then we’ll get it on site early next year. So next year we start with The initial sort of fielded pilots and we feel that a lot of systems up into this point.

So we’ve already put one of the things I tell people when they come to Apptronic, they’re looking for all the robots and we have a lot now. But for many years, every robot we ever made, we sold because that’s how we stayed alive. That was our, that was our business model. We were entirely funded on revenue for the first five years.

We only just raised money in the last couple of years. And so, but next year, we’ll get them out into the world. We’re not putting out pricing just yet. But a big part of what we’ve cracked is the ability to make these things affordable. And so that’s going to be a big part of our value proposition as we move ahead.

John Koetsier: You appear to have been remarkably capital efficient. I know many of the other entities, companies, departments that are building or trying to build general purpose robots. They’ve raised 100 million dollars. They’ve, they’re part of a Trillion dollar company or a multi-billion dollar company.

You’ve been scrappy, you’ve been bootstrapping, you recently raised what, 14, $15 million which is interesting. But that all seems to accord with Connie, your philosophy of start small, build what we know and even to the, to your go to market strategy of bringing people in, seeing what can do super, super interesting.

And I really liked that actually at 50, 000, assuming you can get there. Cause that’s your goal. It’s not there yet. And you’re not in mass manufacturing yet. I’m assuming it’s 50, 000, that’s a very interesting price point, because if you look at the kinds of jobs that you’re going to place us in and logistics and stuff like that, you’re spending probably a bit more than that.

If you look at entire costs for having an employee and benefits and other things like that. And. That sounds interesting. Do you know how you’re going to bring them to market? Are you going to sell them outright or are you going to have a SaaS solution? What’s your thinking there? 

Jeff Cardenas: Yeah. So, once again, the way that I asked, right.

John Koetsier: Robots as a service, not software as a 

Jeff Cardenas: service, robots as a service. And the, one of the exciting things about why this is feasible now is we already have business models that exist for selling mobile robots. It didn’t exist before the AMR market took off, but now there’s lots of companies that are selling mobile robots to these exact same markets in logistics.

And so customers now know how to buy them. The two ways they’re buying AMRs today are either robots as a service or CapEx. Typically with a SAS component to that. So some, the larger companies want to own their own fleets, they want volume discounts and other things. And so they’ll buy them outright. But I think largely what you’ll see in the early stages of the humanoid market is robots as a service model where they want to try them out.

They want to see how this works. There’s people that are worried about technical obsolescence, right? Like how quickly is this going to mature and develop? Am I ready to buy a fleet yet? Or do I want to wait some time? And so for a number of reasons, I think robots as a service is going to be important for this.

And now as an industry, we know how to do that. There’s third party financing groups that have already set up around this. It’s now something that the market understands, which wasn’t the case, five years ago. 

John Koetsier: I keep thinking about additional questions. We’re having a great conversation.

I want to ask this one. Where do you situate the United States and maybe North America a little more broadly in terms of global innovation of humanoid robots? Because you’re obviously U. S. based. There’s a bunch of others .. Figure. 

We’ve talked about the one in Vancouver, right? Geordie Rose’s company. 

We’ve talked about Boston Dynamics, right? So yeah, Sanctuary is the one in Vancouver. I visited Robot Island. It was sort of the name for it in Denmark. It’s gotta be about three years now, just pre COVID where there’s been, there has been for about a couple of decades, a global concentration of companies in automation and robotics is Odense Denmark.

And I haven’t seen anything come out of there. And they’ve been instrumental with some of the big manufacturing companies globally with large scale robots and automation stuff. But I haven’t seen a humanoid robot come out of there. Why am I seeing so many in the States and where do you situate the U. S. in terms of global innovation for humanoid general purpose robots? 

Jeff Cardenas: Yeah, so this is a topic that is important to me because I think the race is on. There’s a lot of interesting stuff that’s coming out, all over the world. I think one of the reasons that you see the U. S. leading right now is because the U. S. Government has invested so much money and the R&D that was required to make this happen. So whether it’s Figure, Boston Dynamics, or us … any folks have teams that have their roots in something called the DARPA Robotics Challenge. The DRC, they injected tens of millions, I think it was over 100 million total DARPA did to really advance state of the art for general purpose robots.

And that was 2013 to 2015. 

And the seeds were planted back then. And we’re just now seeing the fruit that’s being beared off of that investment. But that’s really what made Boston Dynamics big, was DARPA funding in the early years. Atlas came about for the DRC. So the very first Atlases were designed for the DARPA robotics challenge.

And that’s really what spurred a lot of the innovation. There has not been as much government funding in this space since the DARPA Robotics Challenge. And I think that if the U. S. wants to continue to lead, the government’s going to need to step in a big way and really inject more money into it.

But, this is the same thing that happened with autonomous driving. There was something called the DARPA Urban Challenge, and there was a couple DARPA challenges that… That really seeded the technology that moved it from the lab and may give it the 1st nudge out into the commercial space. And then companies were built out of that.

And so, Jerry Pratt, that’s over at Figure … he had a big role in the DARPA robotics challenge and did great work there. And then Boston Dynamics certainly came out of that in terms of who’s leading in the world and where do we go from here, I think China is making a big push in humanoids in particular.

And the government there is really stepping up to make it happen. And so I really want to see the US government respond. This is a race that I think is important long term, how should these be deployed? And I think it’s an area that we can lead, there’s other great countries doing amazing things as well.

There’s great work happening in Korea, certainly in Japan as well. And then all across Europe the stuff coming out of ETH Zurich and groups like antibiotics, they’re doing really great things though, not in humanoids and more versatile, cutting edge next generation robots. 

John Koetsier: It’s important.

It is really important. Hey, because if you win here, you win. We talked about the cost of information approaching zero. We’ve talked about the cost of software approaching zero because replication is essentially free, right? If you achieve a working and capable general purpose humanoid robot, the cost of labor, as we’ve already talked about, starts to approach zero as well.

And all of a sudden, that opens up a ton of capability for manufacturing cheaply. Onshore manufacturing, other things you want to do, jobs that were not, you couldn’t pay for them before, maybe environmental reclamation, maybe public works projects, you couldn’t pay for them before, you couldn’t afford them before, all of a sudden they become affordable and desirable, and everything that a society wants to, as well if you.

You are concerned about the declining population in some of the older nations of the world, Europe, Japan, those sorts of places. China as well. Those that’s all critically important. 

Jeff Cardenas: Yeah. And I have an interesting story about that because the U.S. actually invented the very first industrial robot. So it was invented in the late 50s, went into a General Motors factory in the early sixties, it was called the Unimate arm and the company that built it, Unimation actually ended up folding in the eighties.

I’ve heard a variety of different stories on what happened, but long story short, they didn’t. They didn’t keep getting funded. They didn’t keep getting backed in a critical time. General Motors, I think, was involved somehow and pulled out well. So the U.S. invented the very first industrial robot and effectively lost the first wave of industrial automation.

The big four that were producing all the industrial arms, two were Japanese Fanuc and Yaskawa. One was Swiss ABB and the other one was German KUKA. And so, I think this is important for policy makers and others because this next wave dwarfs the first wave in impact and size. And so I think it’s important to get it right.

But it’s an interesting story and something that I try to tell everyone that will listen when, whenever I get a chance. 

John Koetsier: Jeff, this has been a wonderful conversation. Thank you for taking the time. Yeah. 

Jeff Cardenas: Thank you very much.

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