[00:00:00] Speaker A: There is a big dichotomy in the world of AI between digital world artificial intelligence and physical world or real world artificial intelligence.
[00:00:15] Speaker B: Hello everyone, and welcome to the Robot Industry podcast. Thank you for subscribing. And my guest today is Ben Wolf, and He is Paladine AI's president and CEO. Ben, welcome to the podcast.
[00:00:27] Speaker A: Hey, Jim, thanks for having me.
[00:00:28] Speaker B: You're a lawyer by trade and you've worked in different roles, some at the former Sarcos Technology and Robotics Corporation was now rebranded as Paladine AI. And in fact, you recently came back from retirement to lead the company. Can you tell us a little bit about yourself and why you decided to come back?
[00:00:44] Speaker A: Sure. First off, you know, I've been in business of one type or another for more than 40 years, and only 25% of that time did I spend as an M and a lawyer. You know, transactional lawyer, deal lawyer. I had started my first company when I was 17 years old, actually started working when I was 13 years old. So, you know, I have a. I have a long history of working in business before I became a lawyer. And after I was a lawyer, I left the practice of law back in 2004 to run a large investment fund, multibillion dollar investment fund. At the same time, my partners and I started a telecommunications company called Clearwire, which became the first 4G wireless carrier across the United States and several other countries in Europe, ultimately sold that to sprint for $14 billion and just have had lucky enough to be in a number of different CEO roles and board roles for both public and private companies. I first got involved with the robotics industry and Sarcos Specifically in 2015 when I partnered with the management team of the business when it was owned by Raytheon. And we did a management buyout of the business and spun it out of Raytheon. And at that time, we were focused on trying to take the technologies and robotic systems that the US Pentagon had spent a lot of money investing in with us to commercialize those products and bring them to market both for defense applications and for commercial applications. Fast forward to 2021, when we became a public company by merging with another public company in what was called a de SPAC transaction. At that time, I retired, as you pointed out, because I had already been the CEO of several public companies and had decided that life was too short to be a public company CEO again. And so we recruited a new management team right after the merger, after going public, and I retired. Then a couple years later, the board contacted me and said, you know, we'd like you to consider coming back. And so I spent some time kind of getting back up to speed on the company and where it was and thought that we had an incredible opportunity in front of us on a different path than what we had originally set out to pursue. So originally we were focused on robotic hardware systems and bringing them to market. But what evolved over the time period, over let's say the last five years, was that we had also been developing a proprietary artificial intelligence platform designed to make robots smarter. And as I got re engaged with the company, I discovered that that was an absolute crown jewel in the company's technology portfolio and became convinced that that was the right future for the company to pursue. So when I came back as CEO early this year, we put all of the hardware development efforts on the shelf and focused all of our resources on commercializing our artificial intelligence platform, which we have now done. And we have two products that we are bringing to market and we can talk more about those when you're ready.
[00:03:22] Speaker B: So Ben Paladyne has traded on NASDAQ as pdyn. And by the way, I was with a public company and I know how hard it is as we went from $18 a share to $3 a share. Do you have any regrets about going public via that special purpose acquisition back in 2021?
[00:03:38] Speaker A: You know, as you point out, our stock has dropped precipitously. Our valuation from that time has dropped. And that's always painful. It's painful for investors first and foremost. It's painful for our employees and our team. But having said that, the merger transaction allowed us to raise a lot of capital at a good valuation for our prior.
It's hard to say I regret doing that. There's no question though that today being a public company has a lot of challenges associated with it, particularly when you're at the stage that we are at. Back when we went public in 2021, a lot of companies that were essentially pre product launch were getting funded and going public. And what happened in the year or so after that is that virtually every company that was a pre revenue or pre product commercialization stage public company had investor enthusiasm, kind of turn around on it and disappear. What we've learned through that is that long term shareholders, public shareholders, are not ready to be investors in pre revenue or pre product stage companies. And so that's just a fact of life, but we make the best out of it in terms of where we are today.
[00:04:37] Speaker B: Tell us a little bit about your team. Like how many people do you have currently working at Pelodyne AI.
[00:04:42] Speaker A: We are about 70 employees, which is down from its peak of about 350 employees. We did a significant layoff over the last year where most of our hardware team that had been developing all of the hardware systems wound up leaving us. But we retained virtually everybody that was on our software team. We've grown it a little bit since I returned. We have a handful of job openings open right now. Most everybody is based in our Salt Lake City facility, which is where headquarters is located. But we have a few people in different parts of the country that work remotely.
[00:05:14] Speaker B: And so no more robots.
It's all off the books now. It's all AI.
[00:05:18] Speaker A: Yeah. The hardware systems are. You can still see them as you walk through our facility, various stages of development. But today our focus is not on trying to continue to commercialize those hardware platforms. I believe there's still significant value to what we developed over the years, and maybe someday they'll come back, but. But right now we're focused exclusively on AI.
[00:05:36] Speaker B: So there are certainly assets of the corporation. Like you say. Can you talk about Paladine AI's technology and how it's differentiated from other AI solutions for robotic automation?
[00:05:47] Speaker A: Sure. First of all, I like to talk about the fact that there is a big dichotomy in the world of AI between digital world, artificial intelligence, and physical world or real world artificial intelligence. And the distinction that I draw there is if the AI platform and algorithms is primarily designed to take a lot of data and process it to come up with some kind of an answer that better informs humans about the state of the world or the environment or an activity that's digital world. It's kind of like just. Just dealing with the stuff that's in the cloud, the Internet, and not trying to physically manipulate objects in the real world, which is what we do. So Paladine AI and other companies like us are focused on using algorithms to make machines smarter so that they can be able to do tasks that historically have been too complicated or challenging for machines to be able to do. So that's the world that we live in, the physical world, AI. And what makes us different than most of the other companies that I've seen that are trying to pursue that capability is we do not rely on foundation models, complex foundation models. We don't have to rely on large data sets with potentially billions and billions of data points that have been trained or learned over years of time. And we don't rely on computing in the cloud. We do everything on the edge, right where the robot is. What that does for us. Is it gives us the ability to teach robots how to perform new complex tasks in a small fraction of the time that it takes our peers to be able to do the same thing. And it's not just about a savings of time. It's also about expanding capabilities by making robots more agile and able to perform a variety of tasks. Most robots or automation machines today are programmed to be able to perform a single task or a very narrowly constrained specific set of tasks. Our objective is to be able to teach a robot how to perform a wide variety of tasks, to be able to reason almost the way humans reason. We actually try and emulate the way humans reason with what we do with robots.
[00:07:47] Speaker B: So the value proposition of Paladine AI is really about kind of time to market. It's about reducing costs for the robot owners.
It's about speed, really.
[00:07:58] Speaker A: It's both about speed, but also about agility. I mean, if you think about having a robot that can only perform a single task and being able to expand that now to be able to do a dozen different tasks, now, all of a sudden the ROI for that robot owner changes dramatically. And so it's not just about speed, although that's a big part of it. It's perhaps even more important to think about robots being more the way we humans are agile and able to do a lot of different tasks.
[00:08:22] Speaker B: Ben, thank you for that. How much of Paladyne's current AI solution is based on the robotics development and work from Sarcos?
[00:08:30] Speaker A: Great question, and the answer is virtually all of it. We conceived originally of this approach to AI through our process of developing human form factor robots like our exoskeleton. And the original intent was to be able to have a human operator wear the exoskeleton robot and teach it how to perform tasks perfectly the first time, just as we humans do. You know, there's not a lot of trial and error when we're trying to perform a basic task, like moving a box from one location to another, we don't have to put a lot of thought into it. A robot, on the other hand, would have to be highly programmed to be able to do that task, especially in an environment that is variable in nature, where there's changes in the environment. So to be able to wear a robot, teach it how to perform that task, step outside of the robot, and now have it perform it autonomously was our original focus. I can tell you, if it had not been for our 30 plus years of hardware system development, we would not have come across this approach to AI. And I And it's certainly something. If we were just a handful of PhDs coming out of grad school, working in a garage somewhere, we would never have stumbled on this approach. So I can thank the years and years of investor support that we've had on the hardware side of getting us to where we are now on the software side.
[00:09:40] Speaker B: Paladine AI is hardware agnostic. And what do you mean by that, and how do you accomplish it?
[00:09:45] Speaker A: What we mean by that is being able to have our system operate on a wide variety of different robots made by different companies and OEMs. So, for example, our Paladyne IQ industrial robot software platform today is operating on robots from Fanuc and ABB and Universal Robot Cobots and Kuka. And it is a whole approach that we had which was very different than the way most robotic software has been developed over the years, which is platform specific. Our approach was we wanted to be agnostic so that it could operate on a wide variety of platforms. And in fact, in addition to those ones that we just mentioned, our drone software is now operating on a wide variety of different types of drones. So it's all designed to be almost the way you think about Microsoft products on a PC. You know, they are intended to work on a lot of different computers. Our software is intended to work on a lot of different robots.
[00:10:37] Speaker B: So, Paladin, obviously you've mentioned a couple of your clients already who are the robot OEMs. So who are Paladyne's AI customers and the industries that you're primarily focused on?
[00:10:47] Speaker A: So we have just launched the IQ product on October 1st for commercial deployment. And so we are starting to trial it with some commercial customers. Most of them are in some form of manufacturing. So think about whether it's automobile manufacturing, whether it is aviation or aircraft manufacturing, whether it is electronics manufacturing. And our specific sweet spot, Jim, is those areas where humans are still doing a job because it is variable or complex in nature. And we now can step in with a robot partner and automate that task.
[00:11:21] Speaker B: Can you give us some examples of maybe some projects that you're either working on, you're announcing? I know it's kind of difficult because a lot of this stuff is a little tiny bit secret, but it can't be secret very long. It's a small industry.
[00:11:32] Speaker A: So one project that we've actually publicly talked about is what we're doing with the U.S. air Force. The U.S. air Force has wanted to automate the process of refurbishing or remanufacturing aviation components. So think about things like Props on a prop plane or brake drums, a variety of components that wind up getting corrosion over time need to be refurbished. And today, the way that job is done is a human gets into a paint booth with a hazmat suit on and has a media blasting tool or a sandblaster and spends time bent over this item and blasting it and trying to use a lot of precision in terms of how much pressure is applied, what the angle of application is, what the distance from the object is. All things that we humans are pretty good at kind of assessing in real time on the fly. And the task was to figure out whether we could use an industrial robot to do that job with our software. And we announced, I think it was a handful of weeks ago, that we had successfully passed the first phase of the criteria for that contract, moving into the second phase of the contract, which will involve actual deployment of the commercial systems to do the work. But that's a great example of a job that humans are currently doing. It's a dirty, dull, boring, sometimes dangerous job, which is perfect for automation, except it's just been too complex to automate historically.
[00:12:54] Speaker B: So where do you plan to find new customers?
[00:12:56] Speaker A: So we're talking to customers across a wide range of manufacturing industries. We're also talking to them in the logistics and warehousing space, a variety of services spaces like manufacturing, I'm sorry, repair and maintenance operations in the aviation industry. And so we have a small sales and marketing team today. They're going out to what we think we would refer to as Lighthouse customers, thought leaders in the industry, folks that have experienced or expressed a willingness and a desire to adopt new technologies. And our whole focus is to try and create some track record of success with a handful of Lighthouse customers and then get the word out. And once the word is out, we think there will be some other followers that come along in those respective industries, because at the end of the day, everybody is focused on trying to address the labor shortage, particularly in the blue collar space, trying to address the increasing costs of labor and trying to improve output and efficiency and quality. And those are all things that we can help those companies achieve with our software platform.
[00:13:55] Speaker B: So your perfect bullseye customer is these people with these complex problems. The shift number two is not coming into work, or shift number three is not coming into work. And so you want to take these complex problems, is that. That's correct.
[00:14:07] Speaker A: That's correct. I mean, tasks where there is variation in either the tasks being performed or in the environment. So humans are doing the job today, but humans don't really want to be doing that job. They'd rather be doing something more productive and more challenging from a mental perspective. And that's where our software can come in.
[00:14:24] Speaker B: I'm going to throw a question in for you about automation integrators. Is that one of the paths that you might go down for your software is working with the integration community?
[00:14:33] Speaker A: Yes, that's something we'd very much like to do. Working with software, with systems integrators. The SI community makes a lot of sense for us. They're already working with many of the companies that we'd like to ultimately work with. And I think we can be beneficial to the SIS because we can help them accomplish their customers goals faster and at less cost.
[00:14:51] Speaker B: And there's millions of robots out there now. Right? Like that's the other part.
[00:14:54] Speaker A: That's right, that's right. And we have the potential to improve the capability of the millions of robots that are currently embedded in the workforce. But more importantly, I think we're going to see many millions more over the next five years get deployed. And we think we can be a catalyst for helping that. Because if we can make robots more capable, there should be more demand for the robots themselves.
[00:15:11] Speaker B: Absolutely. You're almost this like extra ROI kick in the pants for robots. It's like, okay, and by the way, we're going to put Paladine AI on your, on your robot and make you more productive for Gen 2 and Gen 3 of whatever system is going to be used for. Sure.
[00:15:24] Speaker A: That's right.
[00:15:25] Speaker B: So what's your vision for the future of Paladine AI and maybe the product roadmap a bit.
[00:15:31] Speaker A: So as I mentioned, we've got these two different core products. One focused on industrial robots and cobots and the other focused on mobile machines. We start with drones, but ultimately that platform that's intended for the mobile robotic area could work on humanoids, could work on things that float, fly, drive, whatever it might be, particularly when there is a particular kind of task involved that is complex. So I see the continued evolution of these two products enhanced capabilities, probably not diversifying into other products. We want to remain focused on these two products and our goal is to ultimately have thousands of machines around the world using Paladyne AI software to do these complex and challenging tasks.
[00:16:13] Speaker B: Well, that's exciting and I'm interested to follow you guys and talk more about where you're at outside of leading a public AI company. What do you like to do in your spare time?
[00:16:26] Speaker A: We own a horse ranch here in Texas. That keeps us busy. We have a large quarter horse breeding program, so we do a lot within the equestrian community. Our daughter competes nationally in equestrian activities, so we travel around the country with her pursuing that. And then my wife and I enjoy different types of hunting and so we, we spend a lot of time in the outdoors hunting game.
[00:16:46] Speaker B: That's, that's so interesting. My daughter, as a matter of fact, was a polo player when she was younger, so I totally understand where you're at. That's interesting. Is, is there anything today that we've forgotten to talk about?
[00:16:58] Speaker A: Ben, I think you've covered all the good stuff.
[00:17:00] Speaker B: Thank you so much for coming on and we I hope to talk with you soon.
[00:17:03] Speaker A: Thank you very much.
[00:17:04] Speaker B: Our sponsor for this episode is Earhart Automation Systems. Earhart builds and commissions turnkey solutions for their worldwide clients. With over 80 years of precision manufacturing, they understand the complex world of robotics, automated manufacturing, comp and project management, delivering world class custom automation on time and on budget. Contact one of their sales engineers to see what Earhart can build for you and their
[email protected] and Earhart's hard to spell. It's Ehrhardt. And I'd like to acknowledge a 3 the association for Advancing Automation. They're the leading automation trade association for robotics, vision and imaging, motion control and motors, and the industrial artificial intelligence technologies. Visit automate.org to learn more. And if you'd like to get in touch with us at the Robot Industry podcast, you can find me Jim Beretta on LinkedIn. Today's podcast was produced by Customer Attraction Industrial Marketing and I'd like to thank my team, Chris Gray for the music, Jeffrey Bremner for audio production, my business partner Janet, and our sponsor, Earhart Automation Systems.
