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How Did This Ugly Prototype Become a $1B Business? | Standard Bots

America installs a fraction of the robots China does, and Evan Beard thinks that's a problem for everything we build. He's the co-founder and CEO of Standard Bots, a New York company making AI native industrial robot arms, designed and built in the US. In this episode of ODDS, we go inside the Standard Bots factory, from the room where they make their own circuit boards to the floor where robots learn new tasks in minutes. Evan tells us why it took seven years to sell the first 100 robots, how his friends staged an intervention to get him to quit, why he testified to Congress about American manufacturing, and why he thinks robots are the next great computing platform. If you're into robotics, AI, manufacturing, or how hardware founders keep going against the odds, this one is for you. ▀▀▀ 00:00 America Is Falling Behind on Robots 00:52 Ten Years to Build a Robot Company 01:38 7 Years to Sell the First 100 Robots 02:54 Why New York, Not Silicon Valley 03:18 From Web Design to Y Combinator to Robots 04:15 Talking to 100 Customers 05:29 A Robot Anyone Can Use With an iPad 06:09 We Won't Profit Off Our Customers' Pain 06:40 Why Build Robots in America, Not China 07:43 Inside the In-House Electronics Room 09:46 Robots Are the Next Platform 10:35 The American Dream and Manufacturing Jobs 11:59 The Friends' Intervention 13:08 Prototyping at Home, All Night 13:53 The Naked Artist in the Garage 14:27 Outgrowing the Factory 15:20 "We Need It Done in a Week" 16:58 If a Demo Works, Is It a Good Product? 17:34 Why Arms, Not Humanoids 18:17 Why 70% Reliability Is a Terrible Teammate 19:00 Training Robots With Field Data 20:32 The Labor Shortage 21:12 Designing Robots for Ordinary People 22:02 Will Robots Replace Humans? 22:52 The Odds of Building the Next Apple or Nvidia ▀▀▀ ODDS is a startup documentary series for founders who defy the odds. We go inside a startup to see how a crazy idea becomes a real company. Visit ODDS website : https://odds.eo.team Follow EO: https://www.youtube.com/@eoglobal?sub_confirmation=1 Magazine: https://www.eomag.io Instagram: https://www.instagram.com/eo.build/ X: https://x.com/eo_build Business inquiries: partner@eoeoeo.net #Robotics #Startup #ODDS

Evan Beardguest
Oct 29, 202623mWatch on YouTube ↗

EVERY SPOKEN WORD

  1. 0:00 – 0:52

    America Is Falling Behind on Robots

    1. EB

      In the last year, China has installed nine times more robots than the United States. They install more robots than the rest of the world combined, and that we need to catch up because robots are not a category of hardware. Robots are the category that makes everything else. Semiconductors, medicines, defense systems, energy infrastructure, and so much more. And I've testified to Congress twice now, the Joint Economic Committee and the House Science Committee. The United States is no longer competitive in manufacturing, and we're falling further behind every day.

    2. SP

      And we are a robotics company based here in the United States that's making the hardware, the software, and the AI stack.

    3. EB

      Our robotic arms operate in factories from small businesses to Fortune 500s, like Lockheed Martin, Verizon, and even NASA. When our customers succeed, America succeeds.

    4. SP

      Robots that do back flips, but nobody needs a robot that does back flips. It's cool to build a robot that can run race. Nobody needs a robot that can run race. We are focused on solving real problems for real

  2. 0:52 – 1:38

    Ten Years to Build a Robot Company

    1. SP

      people, and we're solving them fast.

    2. SP

      We are growing so fast that about every six months we're adding additional space to the factory.

    3. EB

      We officially started 10 years ago, but the first couple years were really experimenting with how are we going to build? There was a time where my friends had a little intervention for me, and they're like, "You said you wanted to build robots, and you've been doing it for years, and you don't seem to have any products that you're shipping," and like, "Are you sure that this... You can do this? Like it's think it's time to go do something else." When you're trying to do something hard, it takes time, and it took a really long time because we, we weren't just writing software for other robots. We're trying to build the thing from scratch and design our own motors and our own motor controllers.

    4. SP

      And that is something that most companies can't say because they know there's over 2,000 components. There's probably over 200 subassemblies inside of each

  3. 1:38 – 2:54

    7 Years to Sell the First 100 Robots

    1. SP

      robot.

    2. EB

      It took us seven years to sell our first 100 robots, but we've been growing five to 10 times every year, and by the end of next year, we're on track to be 10% of new deployments installed in the United States. And I think when the platform shifts, you have a chance to create a generation defining company. It's a company that could be the size of an Apple or an Nvidia, and just as important as one of those.

    3. SP

      This room is so badass.

    4. SP

      Yeah. Should we go inside it?

    5. SP

      The... May we?

    6. SP

      Yeah. Of course.

    7. SP

      Oh my God.

    8. SP

      More than a million dollar order that's due in reasonable part to the AI work that everybody's been working on there. So this is huge. It's a product that's actually working and doing real work. So, uh, thank you to everybody involved across that whole account and across that whole product stack.

    9. SP

      Literally every single person in the manufacturing world did some form of weekends, stayed really late.

    10. EB

      I'm Evan Beard, CEO of Standard Bots. We are America's largest maker of AI native industrial robots. We're deployed today across Fortune 500s, automotive, aerospace, oil and gas, and defense. So many different use cases. We also have small, medium sized businesses across almost every state in the country.

  4. 2:54 – 3:18

    Why New York, Not Silicon Valley

    1. SP

      Why did you start a robotics company in New York instead of Silicon Valley?

    2. EB

      When you look at the culture of this area, in Silicon Valley, the average retention, it's like something like a year, where people are jumping company to company, and when you're trying to do something really hard, you want people to stick around. I was working in this entirely different business, and I discovered web design at some point in sixth grade, and then I started to make money building websites.

  5. 3:18 – 4:15

    From Web Design to Y Combinator to Robots

    1. EB

      Back then, not everyone had a website, and you could go and say, "Hey, build you a website." After college, and I did computer science at Duke, and after college I did Y Combinator. I was building a CRM. We were trying to make a personal CRM to track your relationships, and at Y Combinator there was a partner who was building these humanoid robots that were, like, eight feet tall. They actually had a whole machine shop in the Y Combinator office, and they were building all kinds of stuff and having so much fun every day. After Y Combinator, this robotics guy gave me a bunch of books. He's like, "I self-taught. I studied software in college and I self-taught electrical and mechanical." Read those books and I started tinkering kind of at nights and weekends and then... and that's where I realized that really the robotics was on the menu of something I could spend my life on, and that's how, what I wanted to do. So the early years were a little bit of a self-taught PhD trying to figure out how to make these products, you know, from scratch. If you have a lot of passion for anything, then it becomes simple that you can learn. It's just you log the hours. When you like what you're doing, you can log the hours

  6. 4:15 – 5:29

    Talking to 100 Customers

    1. EB

      to learn.

    2. SP

      Do you remember who's the first customers you did?

    3. EB

      So really the, the first customers came from the discovery. Y Combinator really drilled into your head was to make something people want, and that's all about talking to customers, really understanding the problem that you're trying to solve. We spoke to 100 customers. We asked, "What do you like about your robots? What do you not like?" And a lot of the robots today are just too hard to use. They have these interfaces where you have to memorize what's in there. They'll have menus and it's like single letter in the menu, so you have to s- study the manual to know what to do, and it's so far from the software we're used to today. And so realize that, and the customers would say they can't set it up themselves. Their team can only hit start, stop, and reset. And so they paid $50,000 for a robot to be installed, and they can't do anything but start and stop it.

    4. SP

      In most of the robot industry, the user interfaces are designed to be very, very rigorous, very, very step by step, but they're super hard to use. And so once some integrator learns how to program a Fanuc robot, it's really painful to try and go and program another robot. You actually have to spend a full day workshop... It's a three-day workshop, uh, trying to learn how to program. Three people from the company have to be there, and one of those people has to score over 90% on their exam.

    5. SP

      So with that in mind, one of the skills that we've created, and what we were talking about before, is a, an

  7. 5:29 – 6:09

    A Robot Anyone Can Use With an iPad

    1. SP

      idea of a locate skill, for example. Make it really easy for your robot to find a part and go get it. Historically, if I wanted to move 60 pieces one at a time to some place, I would have to program all 60 of those points individually, and then it would... they'd go there one at a time, and if anything moved, it would break, because it... robots are historically pretty dumb. They could only do one simple thing, and they go to that spot, and if it's not in that spot, everything's ruined. We wanted to make it really easy that anybody can use an iPad can now use a robot. I can speak from my own experience. When I first started here, I'd never used a robot before, never operated one, never worked at a robotics company, and I grabbed an iPad and just started messing around with it, and I was playing, and I made my first routine in about 15 minutes.

    2. SP

      I ask myself this question probably every day:

  8. 6:09 – 6:40

    We Won't Profit Off Our Customers' Pain

    1. SP

      Why do customers want to work with Standard Bots? I think it's we've changed the way in which robotics is done in America. They are very inflexible for their customers, and, you know, their service programs they really tout are a for-profit off of your customer's pain. So I always tell our team, "We will not profit off of our customer's pain." When customers are happy, you know, they want to buy more, but if you're profiting off of their pain, they don't want to work with you anymore. So our goal is to make sure that we profit off their production.

  9. 6:40 – 7:43

    Why Build Robots in America, Not China

    1. EB

      But we find ourselves in a dire position today. The United States is no longer competitive in manufacturing. Any company that builds hardware here can tell you that if you source from China instead of making things here, it can be five to 10 times cheaper.

    2. SP

      But wouldn't it be cheaper to make them in China? Why are you building them here?

    3. SP

      Throughout my career, I've worked in, um, high-volume manufacturing and in factories. The trade-off earlier in my career, uh, when I was working at Google with a lot of contract manufacturers, especially in China, was that, uh, people were cheaper than automation in most cases in those, in those factories. I think it's one of the most important things about our company is that we're building the robots in America to use in America. And if we were building the robots somewhere else outside of the country and we didn't own that production, there's a whole host of problems that come with designing something and then having someone else build it for you, and especially if it's overseas where there's language barriers and, and culture barriers in the way that make it difficult to, um, communicate about projects. Since our company runs our own factory, we remove all of that.

    4. SP

      So welcome. This is our factory floor. We

  10. 7:43 – 9:46

    Inside the In-House Electronics Room

    1. SP

      are in currently in about a 30,000 square foot space that we are expanding into 70,000 square foot. Everything is designed by Standard Bots.

    2. SP

      This room is so badass.

    3. SP

      Yeah. Should we go inside it?

    4. SP

      Uh, may we?

    5. SP

      Yeah, of course.

    6. SP

      Oh, my God.

    7. SP

      So this is our SMT room. This is the first modality that, uh, Standard Bots has brought in-house. So basically what happens is we purchase these bare boards, uh, which is a, a green circuit board that doesn't have any components placed in it. We purchase these components and reels to the left. All of these boards are designed in-house, and we manufacture them all here. So every single electronic board that's gone into a Standard product was made in this room. These boards are brought in through a conveyor belt, and as you come in, you can see the pick-and-place machine. All of these individual rolls are different electronic components, and then you can see the machine picking them up and placing them onto the board. These are hundreds and thousands of components that's getting placed every minute, so only automation would let it happen. After that's done, you can see our operator doing a manual inspection to make sure all the components are in place correctly, as well as putting some of the larger components that is not handled by this robot. So once that is done, you can see the components rolling off the, the conveyor belts here, and then it goes through our aerial optical inspector, or AOI, uh, where camera goes over each of the components onto the board to make sure that it is placed correctly and bonded properly. And then after that, out comes completed boards, and these are ready to be used for our manufacturing. The full stack vertical integration of our design for our robots and products is definitely a huge benefit for us. Because AI is so fast developing, the requirements of what our robot should have or shouldn't have is constantly changing. So then to have this capability in-house means we are able to pop out a board in a day or two as soon as we have a design change or new, new concept in mind, instead of waiting six, seven, eight weeks to bring in a board and then test it. There's also a lot of restrictions going around, around the world also, so the fact that we have full control over manufacturing and design of our boards and electronics in-house let us be completely free of any restrictions that happen in the future as- also.

  11. 9:46 – 10:35

    Robots Are the Next Platform

    1. SP

      Then when did you start your mission to bring robots back to America?

    2. EB

      We really thought about what's gonna be the defining platform of our generation.

    3. SP

      What is a great platform actually do? It makes building really easy, and right now programming a robot is painful. It's slow, it's expensive, and everyone is solving the same problems again and again. Every once in a while, the platform changes. Mainframe computers give way to the personal computer. The PC gives way to the internet. The internet gives way to mobile. And every time, a few companies come along and define the next generation, and it's happening right now. Software's leaving the screen. It's moving into the physical world, and it needs a k- new kind of machine to run on. That machine is the robot.

    4. EB

      And when you're gonna have something of that importance, the next major platform, it becomes clear it's a foundational technology.

  12. 10:35 – 11:59

    The American Dream and Manufacturing Jobs

    1. EB

      We have to build it here in the United States.

    2. SP

      My parents came here from Cuba early 1960s, and my dad was driving a cab. My mom was a secretary. Worked so hard and get enough jobs that they saved money, bought their first house, and kinda like, you know, made their way up that way, the American dream, right? There was that sort of mobility, like economic mobility in the country because there were a lot of jobs out there to be had that you could work to try to earn that, uh, capital, to try to move up the social ladder or whatever, or, like, the economic ladder, whatever you're trying to do. And slowly but surely, as we've moved from, like, more of a software world in- instead of a hardware world, we've offloaded a lot of those jobs to, like, other countries.

    3. EB

      We see jobs go every year to other countries in manufacturing, and manufacturing is really the heart of our middle class here in the United States. In the face of this, the only thing that can turn the numbers around are making our workers more productive, and robots are the tool to do that, and the robots are the way that we earn the right to create high-paying jobs and to do it, to build things here in the United States.

    4. SP

      But at the same time, the US manufacturing base, especially for something like robotics, is very much lacking. It's very hard to source high-quality parts at low price, at high volume with a short lead time. So inevitably, we do have, find ourselves going to, uh, offshore sites for our certain needs. One of the ways we want to fix this is, is vertical integration, meaning almost every single modality of manufacturing that is involved with our robot making, we want to be able to do it in-house.

    5. SP

      But it is true,

  13. 11:59 – 13:08

    The Friends' Intervention

    1. SP

      hardware is hard. If you've never designed something for mass manufacturing before, then you'll start, get too deep into your project before you realize all the mistakes you made.

    2. SP

      What was the most difficult moment for you?

    3. EB

      First prototype was a couple weeks, but 100 customers took six or seven years, I think. There was a time where my friends had a little intervention for me and they're like, "You said you wanted to build robots, and you've been doing it for years, and you don't seem to have any products that you're shipping," and like, "Are you sure that this, you can do this? Like, it's, think we think it's time to go do something else." It took a really long time 'cause we, we weren't just writing software for other, it was trying to build the thing from scratch and design our own motors and our own motor controllers, and we were writing the firmware to commutate the motor to switch it, you know, so the magnet, the electromagnet had the right interaction to spin at very high efficiency. And we have a very small team at first, because we really bootstrapped the company. So the first robot, I was doing the software and the electrical design, and co-founder was doing the mechanical design. It was, uh, originally a home robot entirely made out of plastic, and we learned that, uh, plastic is not the best for, you know, it was kind of before we'd run FEAs and, and really knew how to, to

  14. 13:08 – 13:53

    Prototyping at Home, All Night

    1. EB

      run FEAs. We didn't yet have a lot of mechanical people on the team, so gears stripped and that was the start of the learning process. I think you just gotta get on that loop where you're learning.

    2. SP

      I was doing all the prototyping at home in my office in, in Westchester, New York. I had a 3D printer that would run all night. I would work all day on the design, get prints onto the printer at night. The printer was super loud, and my wife would complain that, you know, it was waking her up 'cause it was the room next to my bedroom. And, uh, every day was a new challenge. We didn't know what was gonna go wrong, what was gonna break, or what we needed to fix, and there were a lot of moments like that where it was kind of like, well, is this gonna sink the project or not?

    3. EB

      Hard at times to think like, "Okay, let, let's review. Like, why do we think this is a good idea? And like, am I wrong? We're going like, have lots touched with reality in some way [laughs] here, and should we just call it quits?"

  15. 13:53 – 14:27

    The Naked Artist in the Garage

    1. EB

      At one point my wife said she thought of me as a, as a naked artist, just sort of painting in the garage. When the world looks at you that way, as a naked artist painting the garage, you can't really care what it thinks too much, or you don't wanna be doing that very much longer. So I think that's the hard part, is you really have to look at yourself in the mirror at some point and just decide, "Okay, doesn't matter what they think. I think this is the right move. We're gonna stay on, on this."

    2. SP

      We made it through all of them, and now we have hundreds of those robots in the field that are working beautifully, and it's incredible to see how that's gone from there to, uh, grow the company to where it is now.

  16. 14:27 – 15:20

    Outgrowing the Factory

    1. EB

      And because we listened to them and we knew what we were gonna build, we've always had customers lined up, and we still do. We've always shipped every robot we made immediately.

    2. SP

      This is where the start of what the new front space, uh, is going to be. Because we're growing so rapidly, we are outpacing the ability of construction team to fix up the spaces, so we had to move our hardware engineering test cages into here before we even finish out the space right now. And this is the rest of the area. It's currently under construction. Uh, it's a much bigger space at the front that will become our customer facing area, our AI testing area, as well as applications team.

    3. SP

      And then you see how we've got this guy who's gonna lay flat.

    4. EB

      Does RealSense have a POE version?

    5. SP

      Uh, there's a-

    6. EB

      Oh, so this will lay flat.

    7. SP

      Yeah, that'll lay flat.

    8. EB

      Okay. Shorter.

    9. SP

      Yeah.

    10. EB

      Like a shorter one. Okay.

    11. SP

      Exactly.

    12. SP

      How did you guys scale up an American robot company that fast?

    13. SP

      Evan has a unique

  17. 15:20 – 16:58

    "We Need It Done in a Week"

    1. SP

      ability. One thing I like to say about Evan is that, uh, he often will say, "Oh, we need to get this done in a week," and the whole team will say it's impossible. And he'll come through and say, "No, no, we need to get it done in a week. We need to get it done in a week." And we'll say, "Nope, we can't do it, can't do it," and then a week later we'll get it done. He's right about 80% of the time, and so, uh, 20% of the time he's wrong and it takes us a year, but 80% of the time he's right, and so he's right often enough that we can't say no because he'll say, "Yeah, you can do it. I, I know how to do it," and he'll, he'll give us the direction to get that done in a way that I've never seen a leader do before.

    2. SP

      We had a big trade show earlier this year, Automate, that was, uh, nine weeks after I joined the company, and, uh, he wanted to do a live demo on stage. The whole team, including myself, told him that this was a terrible idea, and, uh, he was right. We stayed up late. We worked our heads off trying to get everything ready, but it landed.

    3. SP

      Evan, he got into the factory every single day until we fixed those challenges. He was there for months on end. He put his full focus into that and showed that if you put full energy into something and, you know, you have a belief that you can do it mentality, that you can truly do anything.

    4. SP

      So I wonder, why do you think they can finish the task in such a short time?

    5. EB

      That's nice of them to say. I think that you set out whatever you think you can achieve in life, you do. And if you think that something's gonna take some period of time, it will take at least that amount of time, no matter how long. So we do try to set tight timelines and really think through whatever we're trying to do, what's the fastest way to accomplish that thing? I mean, it's key to really doing anything ambitious is you believe you can do it and you believe you can do it in a reasonable timeline, and if not, you've kind of broken down the problem and, or simplified the problem so that you, you can do it in a reasonable amount of time.

  18. 16:58 – 17:34

    If a Demo Works, Is It a Good Product?

    1. SP

      Then what's the real technical challenge right now? If a demo works, does that mean it's a good product?

    2. SP

      I've been working in the r- robot industry for over 15 years now. You see customers that fall into two camps. There's the people that believe that robots can do everything, and there's the people that believe that robots are totally under, overrated. And reality is somewhere in between. The capability is advancing extremely quickly now. We got stuff that was totally impossible just a couple years ago. At the same time, there's a lot of stuff robots can't yet do reliably and can't yet do quickly enough. And so you see YouTube videos and you see that they're sped up. You look for the, how quickly a robot drops an item. If the item follows this super gravitational acceleration, you know the people making the video

  19. 17:34 – 18:17

    Why Arms, Not Humanoids

    1. SP

      are cheating.

    2. SP

      So how do you think about the humanoid robot right now? Why do you want to focus more on the robot arm?

    3. SP

      When people see a robot that looks like a person, their imagination is that it does what a person does, and there's still some problems that haven't been widely solved in the industry.

    4. EB

      We have a theory here which is, uh, this is our home alone eval, which is that if you're gonna have a humanoid, it needs to survive the home alone test, which is couple five or eight-year-olds trying to trip it and flip it as it goes up and down the stairs. And if it can't survive that, then it can't go in the home. 'Cause if you have a couple hundred pounds of metal falling on you, um, obviously it could break a leg or worse. And so, so we don't think legged humanoids are the answer. That's why we're, uh, you know, we focus on arms and wheel bases.

  20. 18:17 – 19:00

    Why 70% Reliability Is a Terrible Teammate

    1. SP

      Reliability is one of the critical things for our industry. I think it's one of the biggest gaps between the foundation model companies at the current s- frontier of where robot capabilities live, and the real industrial users that are trying to count on the robots as a teammate. Researchers like to focus on the progress you can make from 30% to 80% success rate, because it's easy to get enough trials to be statistically significant. For industrial use, though, if I have something that only works 70% of the time, that's a terrible teammate. Industrial applications are typically targeting 99, 99.9% success rates, and I think this is an active area where the research field is behind where the, uh, current, uh, real needs are. We've done a bunch of amazing work to generalize, but we need to increase the reliability of systems. The best data comes from the field right now, and I think everybody agrees

  21. 19:00 – 20:32

    Training Robots With Field Data

    1. SP

      on that. If you want to have good field data, you need to have distribution to be in the field. Our robots are in the field. That gives us unique edge on the right data to train robots to full reliability.

    2. SP

      So this is the, uh, the Echo device, um, which is the data collection device that I worked on. We've iterated on this for months at this point with our, with our data collectors. It's, you know, just a little handheld gripper. It'll have a camera mounted so that you can collect data with it. You can go, you know, grab things, move them around, and it looks exactly like a robotic gripper from the perspective of the camera. So when you go to put the camera on the robot, um, there is no domain gap between what the camera on the data collection device sees and what the camera on the robot sees. So you can use the videos to, to train.

    3. SP

      As humans, we kind of naturally know, like, to pick from here, but of course, our AI models don't have that kind of knowledge, so we have to teach it with our training data, and that's what she's doing right now, picking it from different orientation.

    4. SP

      We've iterated on this device, like I said, for months to make it functional and more ergonomic. Um, originally when we first gave a prototype to the data collectors, they could only use it for 20 minutes before their hands started to hurt. Now we're up to a few hours. So, you know, you can use it for basically a full day with some breaks built in without stopping to collect data, which will help us, uh, ramp up that data collection flywheel.

    5. EB

      We have a bunch of different ways to demonstrate a task. This is one of them. This is called Show Path. You can demonstrate a task to the robot, and it learns how to do it. The whole idea is that you can move it, and it'll be able to translate what it's doing and grab. So it's that quick to train something like this. To train a vision

  22. 20:32 – 21:12

    The Labor Shortage

    1. EB

      routine, we showed you how to train, you know, vision, but to train an end-to-end AI routine that can grab hooks that are moving around. In the United States right now, they struggle with labor. It's hard to find good people. There's a, there's shortage of millions of workers over the coming years. It's very difficult to find the manufacturing talent you need to, to scale with you.

    2. SP

      I came from a background of machine shops, and what we have is we have a lot of skilled tradesmen that are aging out and retiring. So one of the things that we're trying to do is utilize the less resources of skilled labor and push them to more skill intensive tasks.

    3. EB

      I think it's really important to design for ordinary

  23. 21:12 – 22:02

    Designing Robots for Ordinary People

    1. EB

      people, and if we look at the Industrial Revolution, of course, that was all about automated textile making equipment, and Great Britain, or England, kind of dominated the whole world because they could make textiles for so much, for much less and more efficiently than everyone else. And but what we saw at that time was there were a lot of people, the people that were making the textiles by hand could not operate the automated textile making equipment, and there was a whole group of folks that were left behind. And so we view it as not only is it what customers want, because it is what they want, they want their team to be able to unbox a robot, and not only is it investors want, because it is what they want, it has to be scalable, but it's also the right thing to do if we look through the lens of history, because we don't want to leave anyone behind. We want the existing workers to be able to shift into these higher paying, safer jobs, manage these robots. They're the power tools of the 21st century designed to, to help them do their job.

    2. SP

      If your products

  24. 22:02 – 22:52

    Will Robots Replace Humans?

    1. SP

      take off, there will be no human at all as a factory. Do you think it's as a good thing?

    2. EB

      At Standard Bots, our mission is to expand human capacity with the world's most accessible robots, and that means making robots that anyone can buy and deploy and making them more capable with AI, so you can automate tasks you just couldn't automate before. We hear from customers that it's very hard to hire, and that's where the robot comes in. Instead of welding yourself, you can manage six welding robots. That is actually a better job. It can be a higher paying job. It can be one where you're not in the weld smoke, a safer job. The robots are in the weld smoke. It's like the R2-D2. They are not replacing the humans. They're making the humans more productive. Our platform on the hardware side works the same way on the software side. It's like industrial Legos. You can have the ideal form factor for your application. It might be six arms on a mobile base, and that's going to give you, as a customer, the best ROI.

  25. 22:52 – 23:53

    The Odds of Building the Next Apple or Nvidia

    1. SP

      10 years in, what are the odds of success in here?

    2. EB

      I think the odds that we're successful, they've, it's always been long. It's, it's like becoming an NBA player or something like that to try to start the biggest robotics company in the world, and it's really hard, but we're so proud of where we've come. I think where we are today, we've de-risked many things, deployed in Fortune 500s in all these different areas. We're deployed in almost every state. We've got hundreds of use cases deployed. So I think the odds are looking better every day, but I think the size of our ambition to build an Nvidia or Apple sized company, to fulfill that, it's always long odds. And the best we can do is our best. You know, I mean, at the end of the day, we're here on Earth for a really short time, and if we can give back in some way, then I think that's the, the highest and best use. It's like you're giving some kind of gift to the world, and my unique talent is making robots. [upbeat music]

Episode duration: 23:53

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