theCUBE + NYSE Wired: Physical AI & Robotics Leaders | Jeff Cardenas, Apptronik

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Jeff Cardenas

CEO

Apptronik

play_circle_outline Apptronik's journey from lab to Series A funding round

play_circle_outline Versatility and adaptability of humanoid robots in various applications

play_circle_outline Expanding Robotics Capabilities with Advanced Hardware and Sensor Technology

play_circle_outline Focus on building platform for ecosystem of developers

play_circle_outline Funding Validation Sparks New Start Line: Building Robots for Societal Benefit and Commercial Viability

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Jeff Cardenas, Apptronik

Jeff Cardenas

CEO Apptronik

Join us as we engage in a discussion with Jeff Cardenas, co-founder and CEO of Apptronik, during the NYSE Wired Robotics and AI Media Week, hosted by theCUBE at the New York Stock Exchange. This conversation explores the transformative landscape of humanoid robots and the collaboration between technology and Wall Street.

Jeff Cardenas, a distinguished voice in robotics, leads Apptronik, a company emerging from the Human-Centered Robotics Lab at the University of Texas at Austin. In dialogue with John Furrier of theCUBE, Cardenas unfolds the journey f... Read more

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What challenges did the company Apptronik face in getting humanoid robots into the real world and raising funds for their project? add

What are the stages of integrating robots into society and what potential applications are being considered? add

What are some of the advancements in robots for the age of AI in terms of hardware components and sensors? add

What are the plans for Apptronik in terms of building platforms and enabling developers to create applications in the field of robotics? add

What are the company's current goals and focus for expansion following their recent funding and profit gains? add

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Jeff Cardenas, Apptronik

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>> Welcome back, everyone. I'm John Furrier, host of theCube. We are here live at our New York Stock Exchange Studio theCube and with the NYSC Wired community an open community of experts weighing. This of course, we've got our Palo Alto Studio and New York Stock Exchange connecting tech and Wall Street. This week we're focusing on a series of robotics and AI leaders. Our next guest Jeff Cardenas, co-founder and CEO of Apptronik, who's got some incredible momentum, real market validation, humanoid robots, relationship with Nvidia, really pioneering this next-generation wave of digital twins and a variety of other great things around robotics and AI. Jeff, thank you for spending the time in joining us today.

Jeff Cardenas

>> Thanks for having me.

>> So first, you guys just raised an oversubscribed Series A funding round $403. A million monster round on a Series A. Congratulations. Usually see that kind of numbers with success and momentum, usually Series As we see around 50 to maybe a hundred million, 400 big number. So one congratulations and talk about the round, why the momentum, share why the big number, and what you guys went through to get that.

Jeff Cardenas

>> Yeah, well, it only took about a decade to get to the starting line for us. So the company Apptronik started in 2016. We came out of a lab called the Human-Centered Robotics Lab at the University of Texas at Austin. So we've been at this for almost a decade. The work from the lab actually started working at NASA Johnson Space Center for something called the DARPA Robotics Challenge. So two of my co-founders were on what's called the Valkyrie team from 2013 to 2015, and that was very early days of humanoids. So from the beginning of the company, we've been focused on how do we get humanoid robots out of the lab and out into the real world. How do we realize this future of robots becoming an everyday part of our lives? And this has been quite the journey for us to be on. So for the first five years of the company, we raised no money at all. We bootstrapped the company. Prior to this round we actually had more revenue than money raised. And so it's a bit of an atypical Series A, but it's been quite the journey for us to get here.

>> Yeah, it's nice to have that validation and extra cash. It's not going to hurt. You don't run out of business when you have cash. So great mission, we love what you're doing. Talk about the momentum specifically as the world certainly last year we saw that at NVIDIA GTC. Jensen in the one-on-one I had with him talked about robotics aggressively, even though it was a year ago. This year on stage you saw a lot of robotics conversation, but also conversation around computer science. I mean Jensen is the only CEO that I've seen on these keynotes that actually he says computer science multiple times in keynotes. Usually, it's for the mass market. He also showed road maps, price performance, first token out, a lot of nerd talk, a lot of technology explaining the new realities of AI infrastructure. And we were saying on theCUBE even then like, "Hey, robotics is a North Star because it all has to work." So you are in the toughest area of robotics right now, which is humanoids. You need precision, everything's got to work, the safety's got to be there. Talk about that momentum and why that's important and how hard it is. Can you scope and share the degree of difficulty it is to achieve the level of success you guys are seeing?

Jeff Cardenas

>> Yeah, well it's an interesting story for robotics. Humans have been thinking about robots and particularly humanoid robots for longer than we've been thinking about computers. The first attempts at making something like a humanoid robot, a mechanical human were in third-century BC China. There's documented evidence of Leonardo da Vinci trying this in the 1400s and even in 1500s in Japan. So this is something that humans have been thinking about for a long time and we're right now at this moment in human history where it's suddenly all possible. So it's been quite the challenge for us to build into. The simple way of thinking about this is really the evolution of computing. So computers have finally gotten good enough that they can go from the digital to the physical world. And as you start to think about the power of AI and it coming into the physical world where I think it can really improve the way we live and work, the question is what is the form factor? And for us from the very beginning and I think for Jensen and other folks that are talking a lot about humanoid robots, the entire world is built and designed around the human form. So this idea that you can have a versatile robot that can do a whole range of things, that can work with humans and around us both at home and in our work environments is really the North Star and the Holy Grail. And all of these pieces, as you mentioned, are really just now coming together. If you take this analogy you can think of what we're in is we're basically in the personal computer era of robotics. So this is the inflection point where we go from these big industrial machines to versatile machines that can do a much wider range of things, but it's early days. You can think of it like the early '80s for personal computers.

>> Yeah, and I love that analogy. If you see some of the examples of successes, I'd love to get your reaction and thoughts on this. This hardware-software integration is super valuable because we now have the ability to have a matrix-like experience, plug in, and learn how to fly a helicopter. But applying that to versatility of the physical machine, in this case humanoid robot is a key design. We're starting to see that it's not just build the bespoke siloed products. They're not monoliths, they're connected. Can you share how you see that and how people who are coming into the market, seeing what you're doing, is there a pattern to that kind of architecture? I mean it is a system. I mean, supercomputing's been democratized, so great. We not supercomputing, you pointed that out. Hey, we got more compute. But it's not just compute, it's a system.

Jeff Cardenas

>> Yeah, that's right. So traditionally, we had the first robot went into a General Motors factory in 1961. So from a robotics standpoint, we've had robots in production in working environments for over 50 years. The challenge we've had in robotics is these have traditionally been designed to do one thing. So we have thousands of different types of robots out in the world, but each of these robots largely does one thing. What the future looks like is one robot, one platform that can do thousands of different things and so this is a shift towards versatility. So even though it looks complex when you see it, the idea is very simple is we want versatile robots that can do many different things. Very tightly coupled with versatility is how the robot will operate in these environments that are already designed for humans. So traditionally, one of the big impediments to wide-scale adoption for robotics has been systems integration. The fact that we have to modify the environment for what the robot can do. What has a lot of people excited about humanoids and what had me as a naive grad student excited about humanoids is this idea that you don't have to modify anything. So you can drop them into our environment. So they're versatile, but they also retrofit into a world designed for humans. They can use the same infrastructure and the same tools. And what this really represents is a paradigm shift. And as I mentioned previously, we've had to have all of these pieces come together to make this possible but we're at the very beginning of this and it's going to be a big trend in the future.

>> Yeah. And I love that whole analogy, that PC revolution because we saw that Moore's Law at that time kick in, maybe we call it Jensen's Law or Jeff's Law. I mean we're starting to see more innovation. So talk about the design roll-outs now from a practical use, what is the utility you're seeing? You mentioned you got some deployments. The first wave of the PC was simple. I can use spreadsheets. Right? And with this, it's-

Jeff Cardenas

>> That's right....

>> okay. So there was some basic utility that replaced others, obviously manufacturing and other systems, obvious human replacement. But what else do you see as the utility application? As you look at what you're doing now, early days with some of your customers, what are some of the key low-hanging fruit? Then what's the dots that connect? What's that bridge to the future as you guys are building it out?

Jeff Cardenas

>> If you take the computer analogy, what's a computer for? It could be used for so many different things. This is what we want robotics to do in the future. But just as you mentioned with the computer analogy, we had to have initial applications that really proved value. Things like spreadsheets or Word processing, that's the stage we're in for things like humanoid robots. My view is the market's going to play out in three phases. So we're going to start in the industrial base, that's what we're doing today. We have great partners, Mercedes-Benz while we're working in automotive manufacturing. We're also working in logistics with groups like GXO. And so we're going to start manufacturing logistics. That's important because we don't have to... We can work around experts so we're not working around the untrained public while we solve things like safety. So we can also get the robots in very high density. So doing relatively simple repeatable tasks around experts is stage one of the game. Stage two is starting to mix these robots around the general public, so still doing commercial applications in my opinion. Things like hospitality, retail and healthcare, which I'm very interested in. And then stage three is the thing that I've been dreaming of since I was a kid, and I think a lot of people watching this might be looking for, which is robots in the home. Everyone always asks when are these robots going to fold their laundry. And we're working on that. And I think long-term where this goes is things like elder care and assistive care. Robots that help with us as we age, but also if you take a very long-term view and you think about the moon and Mars and other places beyond the sky is not the limit in terms of where these robots go. I think these will help us explore the cosmos in the long term. So we're in early days and you can think of it as happening in these phases and we're building up towards that.

>> Not to take it a little tangent here, but I've been getting a lot of commentary on space tech over the past couple years. And you go back a couple years ago, everything was software-defined. You send up CubeSats for like 100K. so you got a lot of congestion and contention in space. That conversation goes along like that. But we should have a joke that said you can't do break-fix in space, but now you can. I mean, think about things like environments that are hostile in this case space. There's a use case where you could have a robot doing break fix, swapping out from motherboards, or doing things like really building out stuff. I mean that's an extreme example, but other extreme conditions could be factory floor, it could be geography. You're starting to see now reality kick in that there are plain lines of sight, clear lines of sight on real value use cases where there's clear economic model. I mean digging a trench in a certain elevation, for instance, or doing tasks. I mean obviously different robotics there, but humanoids have a unique footprint construction. Where do the humanoids fit? I mean obviously, cranes are turning into robots, arms are robots, but now you get the humanoid, there's a social good meets capitalism angle here, because you're starting to see things get done that are betterment type things, use cases. You mentioned hospitality that translates into healthcare. So a lot of convergence between culture and tech and money happening. What's your vision around those three areas coming together in one?

Jeff Cardenas

>> Yeah. Well, humans are tool makers and we shape the tools and the tools shape us. And so we want to build things that improve the human condition, that improve the way that we live and work. And I think potentially a robot has the opportunity to be one of the most powerful tools we've ever created. As humans our most valuable resource is time. And some of the ways that I explain what a robot is you can think of it like a time machine. What if you didn't have to do these things? What would that free you up to do? There's these famous stories about the washing machine entering the home. The washing machine enters the home, what comes out of that? What comes out of that is books, knowledge, opportunity, the chance to earn living wages and get out of the house. People used to spend hours a day washing their laundry over a bucket and now they have this machine that can help them. The idea for these robots is basically that can allow us to do this at scale. This can unleash human potential. One of the areas that I think it's really interesting to think about this is in things like elder care, the way we age. You can think of one of the things that's driving this is a compound effect of changing demographics. So on the front end, we have a shrinking labor force. We have young people that don't want to go into the same jobs as their parents did. We have an aging and shrinking workforce and so step one for the robots is to step in and help out there. But on the back end of this, we have an aging population that doesn't have young people to care for it in the same way they did in the past. And so robots can help out there as well. So the core idea for us as roboticists and as a company is how can we use these robots? How can we use our tool-making as humans to improve the human condition and improve the way we live and work? And I think that's a really exciting area to dream about and to really put into practice as we move ahead.

>> It's a great mission. And again, not to go on a tangent, I was talking with an impact investor and they got an impact fund around loneliness. Huge issue for robotics. We're seeing AI in emotional support. So the human interaction not only does it free up time to get a job, but also interact with other humans. I mean, if I can get tasks done, I can free up my human intelligence. So you have a confluence of these trends. It scares most people because they don't know what they don't know. So I'd love to get your perspective on the good side of it and what people who might not know what it yet means. What does this humanoid robotics wave mean for them?

Jeff Cardenas

>> Yeah. Well, I think humans are generally afraid of every new technology that gets introduced into society. So it's interesting if you look back on history, people were afraid of trains. There was these myths that if you move too fast in a train, it could scramble your brain. People were afraid of electricity and people were certainly afraid of computers. And this whole idea of jobs and computers was at the forefront of the computer revolution. There was competing ideas. One idea was that you would have a supercomputer that sat at the center of a company and then you could have a four-person company that did everything. A competing idea was this idea that computers would augment human potential, the personal computer. And we see how computing panned out. If you look at the way... Our view of robotics is you can take nursing for example. In nursing, we have a major nursing shortage so some estimates will be short 10 million nurses by 2030. So maybe an older way of thinking about it would be this idea that you would have robot nurses, but do we want robot nurses? We want humans taking care of humans. When you sort of dig into this and you ask, "Well, why do we have a nursing shortage?" The answer is very interesting because 40 to 60% of the work that a nurse does has nothing to do with their clinical training. They're basically fetching supplies, changing soiled bed linens, doing charting, doing all sorts of things that have nothing to do with their clinical training. The way to think about robotics is what if you pair a nurse with this robot such that the nurse could offload all of the worst parts of their job to a robot that would enable them to do much better patient care. And so this is the frame to think about. And I think if you start to go through that frame as an average person, think about all the things that you could offload, whether you're at home or at your job to a robot, how that might improve the way that you both live and work. And I think that's the optimistic future that we're fighting for.

>> Yeah. And I think that's right on. It's the creativity that unleashes there. They can apply what they want to do. Let's get into some of the tech, because again, like I said at the top, you have partnerships with NVIDIA, Google, all the top companies. You're at the confluence of industrial technology, design, hardware, software. Can you talk about some of the technology you have? Obviously, computer vision is a big part of robotics. We're seeing that in a lot of the conversations we're having here on theCUBE. There's a real tech opportunity. I'm sure you're attracting a lot of talent. I mean, who wouldn't want to work for you guys? I mean, humanoid robots are the coolest thing. There's big problems to solve. We've all dreamed about robots. I mean, people who are in tech who know are usually sci-fi fans at some level, at least I am, but most are that I know. But robotics is a community as well. So you have a community of experts, you have a lot of open source mindset system thinkers, but now you've got this industrial piece design to it. I mean, it's all the pieces. What are some of the tech that you guys do? What are you most excited about? Can you just share what's going on under the hood or under the humanoid?

Jeff Cardenas

>> Yeah, yeah. Well, I'm excited about all of it, but you can put it in two buckets. You could say the hardware and the software. So I'll talk about both maybe briefly. So on the hardware side, you could think of a robot as a network of motors and sensors. So what's changing in robots for the age of AI is instead of pre-programming a robot step by step, we are using sensors in the feedback loop. So now they have vision, so they have cameras, they have a sense of touch for sensing, they have a variety of other sensors, temperature sensors, accelerometers to see where they're oriented. And you're using the input from those sensors then to tell the robot what to do dynamically. So now it can actually respond to the world. The base layer of the hardware is the motors itself, the muscles of the robot. These are called electric actuators. So we've done over 60 iterations of electric actuators, really trying to find the trade-off between safety, performance and cost, scalability. You also have the cameras, you have the batteries, and the robotics industry is benefiting from a lot of the previous industries that have been built up. So we got cheaper motors with the consumer drone industry. We got better batteries and better sensors with electric vehicles and autonomous driving. We're building on top of this over many years. On the other side, you have the software and you have the AI. And there's really been a breakthrough on the AI side in just the last few years with generative AI. This idea that today the way you learn to... The way that you program a robot is you get a master's or a PhD or some technical training. What generative AI enables you to do is basically program a robot just by showing it what to do. And this will have big implications in the future where you'll need no technical training to interface with these robots and they'll be able to do anything you basically show them in the future.

>> And when you get the generative AI bump here, which is a great enabler for you, how do you guys view that? Because again, I look at what's happening in some of the advancements with the chips and the systems. I mean, you basically have an AI factory in a robot. It has the vision, it's learning from vision, it's probably processing a lot of interactions with software. What runs it? I mean, what's the OS? Is it proprietary? Did you guys build your own OS? Is it Linux? I mean, people want to run these AI factories in whatever microcosm of their outcome is... I mean beauty's in the eye, the beholder. It could be enterprise in a data center, running an AI factory, could be a robot on board system, say in your case humanoid. There's a lot of people working hard to figure out how to make this work. Again, you're doing it at the highest end. What's running everything?

Jeff Cardenas

>> Well, there's many different layers to the stack. So yes, there's a version of Linux or Ubuntu at the base layer of the system. We've built our own operating system, if you will, that we're building everything on top of. And then there's the high-level AI. It's sort of the cognitive intelligence that you might think of. And we have a deep partnership with Google DeepMind and really pushing the frontiers of what's possible on these robots altogether. A lot of people might think that the models run in the brain of the robot. The interesting thing about Apollo is the compute's actually in the chest of Apollo, but it's a hybrid approach. So some things are happening in the cloud and then the real-time actions of the robot are actually happening directly on board on the robot. But it's a hybrid approach. And there's the operating system and then the AI that sits on top of that.

>> And in terms of any kind of innovation coming that you see it coming from the marketplace, is there an ecosystem building around you guys? Is there, say I build a model, how do I integrate it in? Let's just say I have a breakthrough and I figure out how to do some precision task and I built software for it. Can I upload that into the system? I mean, how do you view the expansionary, either inference or additional training? I mean, that's one side, and then you got also the input coming in that's new data. So again, the data challenges are probably multi-fold, but those are two specifics. I could see some innovation happening. We're seeing other companies where this plug-in model, for lack of a better word or model being prompted or integrated. You mentioned integration. This is a key layer, right? So you mentioned that. So I like to understand how that works from your standpoint because if you've got the humanoid structure, the innovation could scale in on the software side.

Jeff Cardenas

>> Yeah, I think there'll be tremendous opportunity for software in a whole ecosystem. I mean, think of this just like computers or smartphones. So what we want to do at Apptronik is build the best possible platforms, the iPhone of robots, if you will, or the Pixel of robots depending on which camp you sit in here, but the platform. And then we want to enable an ecosystem of developers to build on top of this platform that is robust and safe to deploy different applications. So this will be really important for the next generation of engineers. We want to get them access to really solid hardware. And then I think over time this will really grow and expand. Today in robotics, you're seeing most of these robot companies like ourselves really go vertical and go all the way to the end customer to prove out commercial viability. This is similar to the way the early days of the PC worked as well. And then as the industry matures over time, I think you'll start to see whole ecosystems of developers that are enabled as the industry grows and matures.

>> Jeff, I really appreciate you taking the time. I'd love to do a quick follow-up on your journey. You mentioned the years you've been working on this. How are you feeling? Because I mean, I can only imagine the sigh of not relief, but finally, it was here. They get it, the world gets it. I've interviewed Andy Jassy many times at AWS now he's in charge of Amazon, and he always says, "If you have a vision, you have to be willing to be misunderstood for a long time." So one, how are you feeling right now? And two, what is the biggest thing people misunderstand about what was going on leading up to this moment? We're at the, again, another start line as you say. I mean it's like the world spun into the direction you're there, right? So how do you feel, and what was the biggest, if any, misunderstanding the market might've had or people might've had?

Jeff Cardenas

>> I think generally the timeline is probably the biggest misunderstanding. People would generally tell us early on, yeah, those will be viable one day, but in 50 years and we just saw all the building blocks. I think it's been interesting for me to see the evolution of this because I believed in this so strongly over a decade ago, and it's been interesting to see the market play out. I had a mentor that told me, he said, "You got to pick something that'll be everywhere in 10 years that's nowhere today." And I was really enamored with the personal computer revolution and with what Apple did. And so I went into school with that frame, which is what is the next big platform shift that's coming? And I thought it would be robotics. I thought humanoids made sense and the way that myself and my co-founder viewed it was regardless of how long it took, we were willing to spend our life working on this. And so that's what we did. I've made the joke that everyone gives you a lot of different advice when you get started, but maybe the only consistent advice people told us was, "Don't do humanoids. Get a real job." And so it's been interesting to see it flip and I think it's exciting. For me, it was always obvious. I think what we have to be mindful of now as an industry is now that the general public is getting very excited about these robots, it's still very early days and there's still a lot to prove out in these systems. So I want a robot in my home as much as anybody else does, but we're at the very beginning of this, and so it's going to take time. And so I think that's the next lesson of the game is now that everyone's waking up to it, just being patient to let us do this in the right way.

>> Well, I'm so glad you guys stayed on the mission. It's a great mission. We're super excited for you. We love it for the industry. We know it's a safety-first paradigm as well. And you got now 400 million plus in funding, plus you got working capital from profit. What are you optimizing for? What's your focus now with the expansion?

Jeff Cardenas

>> We want to build the best robots in the world. We want to capture people's imagination about what the future can look like and the role that technology can play in it. In some ways, I feel like we've lost a sense of wonder that we had back in the 1950s, this idea that we would have flying cars and rocket packs and Smell-O-Vision and robots in the home. And so we want to hopefully restore that sense of wonder. And we want to do that by building amazing products that are designed to benefit humanity as a whole. And we want to do this in a safe and responsible way so that it's good for all of us. So I think that's our goal. Our goal is to show versus tell. I call this the commercial viability stage of the humanoid space. So we have to really prove that these robots are useful with unit economics that make sense. And then in the backside of commercial viability will be the commercial scale stage. But as I mentioned, it's still the very beginning. So we got a lot to prove in the years ahead.

>> It really is unique and I love that whole double bottom line philosophy. You're not a nonprofit, but you can have that kind of vibe. It is a societal benefit. And of course, I'm old enough to date myself to say I love The Jetsons and Star Trek original. So everything that's there, it's going to be invented. So thank you so much for sharing. Love the commentary and appreciate it. And congratulations on the funding. It's validation. Again, it's just the beginning of another start line, so appreciate you.

Jeff Cardenas

>> Thanks for having me. It was a pleasure.

>> Okay, I'm John Furrier, your host of theCube here at our East Coast access point. We have a network building with the NYSC Wired and theCube and Silicon Valley connecting tech and money and Wall Street together. Plow in the fields for the future. The trailblazers, whether it's crypto, robotics, AI, they're making a difference these experts. These mixture of experts are putting it together. Of course, we're bringing them on theCube. Thanks for watching.