Applied AI on the Edge Proves There’s More to AI Than ChatGPT - Brian Cavanaugh, CEO of VigilanteX

With artificial intelligence stepping off the laptop and out onto job sites, factory floors, and flight decks, are we preparing students for the AI that sees, senses, and acts in the real world, not just the kind that chats back?

Matt Kirchner sits down with Lieutenant General Brian Cavanaugh, USMC (Ret.), CEO of VigilanteX. After decades commanding Marines and integrating emerging tech into national defense, Cavanaugh now leads a company building applied AI platforms at the edge: solar- and Starlink-powered trailers with cameras and compute that monitor sites 24/7 and turn video into real-time safety, security and efficiency intelligence.

Together, Matt and Brian unpack what “applied AI” really means across the edge-to-cloud continuum. They discuss AI agents running on the edge, natural language search over video, and systems that close the loop from sensor to decision in seconds. They also explore why simply teaching students to prompt chatbots isn’t enough, and how K-12, CTE, and higher education can catch up to a world where AI is baked into every system, every site, and every mission.

Listen to learn:

• How VigilanteX combines solar power, Starlink, cameras, and edge compute into their tech.
• The difference between AI at the edge and AI in the cloud, and why latency, bandwidth, and resilience matter for safety-critical environments.
• How AI agents work at the edge, and why they can work faster and more efficiently than humans (freeing up humans to do more interesting work).
• Why Cavanaugh believes every student should understand how data moves from sensors to the edge, to the cloud, and back into real-time control.
• What China’s national push for AI education signals about global competition and how U.S. educators should respond with applied AI in the classroom.

➡️ Watch the Full Episode on YouTube

3 Big Takeaways from this Episode:

1. AI at the edge is becoming a digital teammate. VigilanteX’s platforms use cameras, connectivity, and on-site compute to watch for fall risks, PPE issues, intrusions, and abnormal conditions across construction, manufacturing, logistics, and energy sites. The system flags events in real time, routes the right video to supervisors, and builds a data trail leaders can use to change procedures before accidents happen.

2. Edge-to-cloud literacy is a new baseline skill for technical careers. Cavanaugh and Kirchner break down how raw sensor and video data is processed locally, filtered, and then pushed to the cloud for storage, analytics, and dashboards. Understanding where computation lives, what data moves, and how AI agents plug into that pipeline prepares students for roles in automation, OT/IT, robotics, and cyber-physical systems in any industry.

3. We need to teach applied AI, not just chatbots. While large language models are powerful, the episode shows how AI is part of the edge-to-cloud continuum. Giving students hands-on experience with autonomous systems, computer vision, and industrial data flows helps them see AI as something they can design, deploy, and govern rather than a black box that only lives in a browser.

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Transcript

TechEd Podcast Introduction: 0:09

This is the TechEd podcast, where we feature leaders who are shaping, innovating and disrupting technical education and the workforce. These are the stories of organizations leading the charge to change education, to rethink the workforce and to embrace emerging technology. You'll find us here every Tuesday on our mission to secure the American Dream for the next generation of STEM and workforce talent. And now here's your host, Matt Kirchner

Matt Kirchner: 0:38

it's Matt Kirkner, your host for the TechEd podcast, where our audience knows just about every week we have one conversation or another around artificial intelligence, it's something that absolutely fascinates me. Is absolutely transforming about every aspect of our world, every sector of our economy. Today, we're going to do an episode that is largely comprised of applied AI and some really, really amazing technology that we see being deployed by today's guest and his company. His company is called vigilantic. So the guest is Lieutenant General Brian Cavanaugh, and I'm really, really excited for this episode. We are going to see some really awesome examples of applied artificial intelligence. But Brian, as you've given me permission to call you. Welcome to the TechEd podcast,

Brian Cavanaugh: 1:24

Matt, thank you for inviting me and thank you for what you do with TechEd. My view is just, you know, this area for our nation and our future is extremely important, the education aspects, you know, since our foundation, the technology aspects, you know, I think about Benjamin Franklin. Now there's Andrew Graham Bell, and this is just another transition period in in our history that's most

Matt Kirchner: 1:46

important. Where would we not be with folks like like Benjamin Franklin, absolutely, and the attachments to to electricity, the technology that began with the with the telephone, and is now the basis of the technology we're using to record this podcast. The compliments of Alexander Graham Bell, great inventors like Thomas Edison. I mean, this really is a country full of a history of inventors, a history of innovation. I know your company isn't any different, Brian. We're going to learn about that today, but I want to start out with as I introduced you at the outset here, Lieutenant General Brian Cavanaugh, I know you were educated at the US Naval Academy, worked your way up to Lieutenant General of the Marine Corps. And for clarification and starters, and I actually learned this on an episode with Todd, young senator from the great state of Indiana, who I think had a similar path. He went to the to the Naval Academy and the Marine Corps. And I was like, how does that fit together? He said something along the lines of, No, there isn't a Marine Corps Academy. If you go to a military academy on a path toward the Marine Corps, you're going to the Naval Academy. Did I get that right?

Brian Cavanaugh: 2:52

Absolutely right. Yeah. And actually, one of my closest friends, she's in the Marine Corps, and she came out of Marquette, which I know

Matt Kirchner: 2:59

really, okay, my alma mater, Marquette, university. That's That's amazing. Do you do you know about what time she was there? Graduated in 91 huh? Okay, so that, that that in E, do you have any idea what the major was? I do not know. Okay, so we'll do some homework on that. My wife and I both graduated from Marquette in 1991 and chances are that, yeah, one of the other of us probably, probably cross paths with, with your friends. So we'd love to, love to go deeper on that when the when the time is right, yeah, for sure. So I will tell you, I'm proud of my my education at Marquette University. It doesn't quite hold the sway that an education at the Naval Academy does. So we'll get into that. But, but let's talk about your career a little bit, and some of the highlights of that career, before you retired from military service. And before you answer that question, I cannot be in the same room, either virtually or in person, with a military veteran without saying thank you for my freedom, and I mean that as sincerely as I can possibly say it so. Thank you for that incredible service and the freedom that we enjoy here in the United States of America. Thanks to incredible servants like you. And with that, tell us a little bit about that experience in the Marine

Brian Cavanaugh: 4:05

Corps. Thank you, Matt, and thank you for the acknowledgement. And you know, I won't speak forever. I feel blessed to have been able to have that opportunity. If you'd have met me in high school and asked me if I was going to go in the military, I would have said absolutely not. I wanted to go to Duke University I went to, I grew up in Baltimore, actually, with one of your previous guests, Dr Charles Johnson Bay, and I went to high school together and Baltimore Polytechnic Institute. And so it's a very engineering and science based school, and that really fed well into Annapolis. And like you mentioned earlier, the Naval Academy produces naval officers, and naval is Navy and Marine Corps. So soldiers of the are the Marines, right? So technical background, mechanical engineer there. So just you know, right in my wheelhouse after graduating, went into the Marine Corps. I was inspired by a gun re sergeant that was in part of the training curriculum while I was at the proportion. Up school and I became a helicopter pilot. So I've been able to serve basically 34 years. I graduated 1990 served for 34 years, four Pentagon tours, which total about 10 years. Heavy focus in the western Pacific, so a lot of time in Japan, Korea, Thailand, everywhere else out there, with the focus area out there, I've flown basically all over the world, six or seven continents I've served on. So just a true blessing. Nothing I ever dreamed of in high school, by any means. But you know, just you know, very fortunate to be able to have had this type of career

Matt Kirchner: 5:40

and not just served, which obviously would be impressive enough, but at the level of Lieutenant General, which is, which is incredibly impressive. Talk Talk about that, that career pathway in the military, and what was it about you that led you to such an incredibly high rank? And then also talk about, you know, how many, how many folks were under your purview? How many individuals did you did you lead? Help us understand that a little

Brian Cavanaugh: 6:04

bit. I'll start with kind of why you serve. One of my passions is to be able to help people. And as you go up in rank, you obviously have more purview over the people you help. So as a young guy, you know, I thought, Okay, I'll do about 20 years, and that'll get you to the rank, about Lieutenant Colonel, Colonel, and your commanding units, about 2000 ish, marines and sailors. Well, once you make general, you have a major impact at strategic and operational level in your institution. You're able to influence the decision making at the highest levels, provide different perspectives on things and really to impact and help a lot of people on the western Pacific side. I was the deputy at Marine Forces Pacific, which is about two thirds of the Marine Corps operating force, so roughly 7080, 90,000 folks. Amazing. And then my last assignment as a Lieutenant General was out of Norfolk, Virginia. I was a fleet Marine Forces Atlantic commander, and that's the other 1/3 of the entire operating force. Amazing.

Matt Kirchner: 7:08

Yeah, and I wanted to give you the opportunity to share that so that our audience get it gets a sense for how special this individual is. So we're talking with somebody that, as our audience now knows, is someone who's pretty special, someone who has exactly the right view of leadership. But it's all about service, and it's all about understanding that that leading is about being a servant to the individuals for whom you're responsible. And when you do that, it is amazing, when you when you take that approach, the amazing things that people will do for you and for in your case, for their country, for any organization. So servant leadership is at the heart of how I think about leading certainly appears, Brian is at the heart of how you think about leading as well. I should also just mention, as you began the answer a little while ago, that you were a helicopter pilot. I was at the Reagan Library earlier this week and actually boarded a much older version of Marine One. So the that, that part of the conversation is timely for me, because I was just standing board a helicopter, not in the air, but but in them, in a library just a few years ago, h3 it was, yep, that's exactly right. Was that the same kind of helicopter that you, that you flew?

Brian Cavanaugh: 8:15

Yes, I flew H threes and 860s while I was at hmx one in support of President Bush, the main platform, age 53 excellent.

Matt Kirchner: 8:25

Which President Bush was that W or HW the younger? Okay, yeah, George Bush the younger. I met the older one at one point, I never, I met Laura Bush. I never met, I never met W, but I did, did spend some time with HW years ago. That was a pretty special night as well probably do a whole podcast about that, but we'll Excellent. We'll plan on it. We'll keep it rolling here. I want to, I want to give a little bit of an example. I was just sitting at a table in California over the weekend talking with some folks about coaching our kids into whatever that came after high school for them, and I made it really, really clear to our two children that, look, there's all kinds of great options for you as you're leaving high school. You can and none of these are mutual exclusive, and they can stack on each other. You can go to workforce, directly to workforce. You can go to a university. You can go to a technical or community college. You can serve in the military. I mean, we would support any of those choices that are that our young people, that our kids, in our case, made. And as it turns out, a lot of a lot of young people are, or should be, considering careers in the US military. So I would love for you to share before we get into the great things you're doing at vigilantics. Brian, you know, why is a military career such a great option, and what are some of maybe those personality traits that might be inherent in a young person that would lead them to a career of service like the one that you had,

Brian Cavanaugh: 9:46

absolutely Matt. So I'll start with myself again. Coming out of high school, I had no aspirations to join the military, but I would say, from start to finish, I finished high school at 16. I had to wait till I turned 17. I. And then came on board from start to finish, 39 years, three months. It's just a treatable thing, purpose driven. It wasn't anything I ever even considered, and it's just special. Every field you can think of is in the military. So we may associate military with just what we see in the movies, but we have doctors, we have lawyers, we have dentists. I mean, we have, obviously, aviators, submariners. There's just so many aspects of all industry representative in the military to do that mission. So it's purpose driven. It's great opportunity. When I was in uniform and I go talk to high schools, I would tell them, you know, obviously I'd start with the Marine Corps. Hey, you know, love for you to try to be a Marine, right? And right, the rest of the services, right? Army, Navy, Air Force, Space Force. And then I would transition, if none of that interests you, the government, civilian side is critical to our national defense and our national security. And I talk about all the opportunities on the government side of service, and then the defense industrial base. So welders, electricians, all those kind of vocational aspects. How long does it take to build a ship or a submarine? And we need artisans to do that. So it's a expansive there's nothing that's off the table of opportunity in quote, unquote, that military construct.

Matt Kirchner: 11:22

I think it's important for us to note that Brian just the wide range of careers, and you know, kind of going back to to my own two kids, neither of whom decided to pursue the military out of high school, but one of whom is now living in Washington, DC, and working pretty closely with the Department of Defense. So to your point, you know, in that case, the civilian role, and not employed by the DOD, but, but in a advisory role to the DOD. All kinds of incredible opportunities for careers in service to the United States. And when we think about a student who's considering a military career, are there certain experiences, types of students, interests that would be appropriate for, you know, for a student who's in one of those to maybe be even more considering of a military career than

Brian Cavanaugh: 12:05

others, I think when you look at the I'll say the characteristics or traits, I think Naval Academy kind of gets it right, because they focus on moral, mental and physical, right? So that moral foundation is, you know, it's mom and dad or grandma or however that that home construct is, yeah, and your belief system, the mental is the educational aspect. In my opinion, you always want to learn. You're never going to get there. You want to keep being a voracious learner. And then the physical aspect is a key piece, obviously, especially as a young person, you have to have certain level of physicality to go and do the mission sets that we do in the military.

Matt Kirchner: 12:42

Yeah, those are great, great examples. I was just, by coincidence, we're recording this episode about four or five days after we recorded one with former Wisconsin Governor Scott Walker. And by coincidence, we're both Eagle Scouts, and I was just reflecting on the scout oath and the Scout Law and and just, it occurs to me how well that applies to the three examples that you just offered in terms of moral, fundamental and physical and all three of them being incredibly important, you know, also important, by the way, and is a way of segueing into the next conversation is the incredible work you're doing at vigilantic. So you're the CEO of a high tech company, which has to be a really, really cool transition. Transition. Let's start out with just the overview of the technology. What are the applications? What industries are leveraging? The visual analytics technology?

Brian Cavanaugh: 13:27

It's a really interesting industry. What I'll say is it's really about integration. So we all know AI has been around for a while, but we associate it with chat, GPT and text and something you do at your desk. Our company, with our partnership with spot AI, we're taking that kind of same construct, you know, into the physical world. So on edge compute with, you know, their software, and, you know, with our cameras and our solar panels, batteries just fully remote, having that kind of at your desk feel out in the real world, we were able to go across many industries. So we focused initially on home builders and the security aspect, because that's kind of what everybody looks at in this form factor, is they'll look and see a trailer, and you've seen these in major retailer parking lots, the trailer with some cameras on it, everybody goes right to security. But with what we have security is probably less than 10% of the capabilities of the vessel. It's about safety. So if you think we've transitioned into large GC so folks that build stadiums, folks that build the freeways across our nation, we're working with a lot of organizations that are very concerned about their people. The AI agents can tell when someone does or doesn't have a hard hat on and notifications, if someone's up on a rooftop not strapped in, they can send a notification. And then the project management aspects, supers have to go out, or PMS have to go out, site to site to site. You can just kind of sit at your desk and see all your sites very rapidly. So that time saving aspect is. Of another feature that we kind of offer, bringing the AI into the real world. That's where I think there's a lot of opportunity for young people to think about as they think about, what will I do when I graduate high school, or what do I want to study in college?

Matt Kirchner: 15:14

You and I are so aligned everybody, when they think of AI, they think about chatgpt, perplexity, Claude. I mean, it's generative AI. And obviously that's important. We like to say that, you know, all of those are AI, but AI is so much more than generative artificial intelligence. And to your point, you know, the whole applied AI side of things, how are we deploying, you know, edge devices, Edge sensors that are intelligent. We'll get into, you know, what we mean by that in a moment, to add the edge and then deploy artificial intelligence, and utilize artificial intelligence in every level, control systems, networking in the fog, in cloud, in the cloud, what we call the edge to cloud continuum. And that is really where the action is, I think. And there's a certain group of students that are going to really, really get fired up about writing the next best AI algorithm, or understanding how to create 50,000 lines of code using AI. That's awesome for them, but for the other 95% of students and young people and all of us, it's really in the applied artificial intelligence. So just so I understand Brian exactly the technology we're talking about here, or at least close enough. So we're deploying cameras on the edge. So I look at a large general contractor who's working on a huge project, be it to your point, a stadium, a new freeway system, large commercial building, what have you. And you think about the pressure on a general contractor to make sure that their employees are working safely. And there's really two parts to that. The first big part of it, and I think the biggest part is obviously, as someone who spent my whole career in manufacturing, the rule number one is, send your people home safely. You know, it doesn't nothing that we are doing is so important that we wouldn't want somebody to go home to their family at the end of the day the way that they came in the morning. And so that's the really, really big part of it. And then the added aspect of this is the responsibility on the regulatory side. So we've got all kinds of, you know, OSHA regulations and other regulations that we need to comply with. And as somebody that's worked not necessarily in the construction space, although I did a little bit of that more so on manufacturing, the implications for not playing by the rules in that regard can be really, really hefty. And so making sure we're complying with both of those. So now I've got technology that can kind of monitor using edge security devices in the cloud. To your point, are people using their PPE safely if I'm doing confined space entry, or if I'm, you know, if I'm up in the air working on something, am I properly deploying fall protection? All obviously, for the safety of the of the employee. And so we're able to utilize AI to identify, among other things, when somebody might not be following exactly the policy or the procedure they need to follow in order to work safely. And then we can correct that on the fly Wait, rather than waiting until, you know, a tragedy happens to to correct for that. Am I getting that somewhat right? You're

Brian Cavanaugh: 17:55

getting it absolutely right. I mean, awesome. There's so many aspects of kind of what you just laid out that are important to address. And bottom line is we want everybody to go home safely every day, and it's across industries, and it's inside and outside, right? So with our workout system, we have our trailers outside, but with our partnership, we cover inside and outside, so on the manufacturing floor all the way out to a job site, and it goes across different verticals. So I use construction. I used freeway oil and gas, you know, different cameras. You can get thermal cameras. You can get all these different other technologies. And the AI agents that are built, essentially, if you were standing there and you saw it, you could see, what would you want to do about it, right? And that's what an agent can do. As a military person, from a security aspect, we would have military guys kind of roam around and look and do these things, but you know, 24/7 doesn't blink is the preferred method. From a security aspect, you talk about safety with the OSHA. You know, you can program what those OSHA violations could be and detect those when they occur. You can be passive and capture data like I had 17 folks without a hard hat today. You don't have to always take action immediately, and then now you have all this data, and you can make informed decisions at a higher level, at a strategic level, about, you know, procedurals, things that you need to change, or this super is doing better than this super. I say, used AI as a tool to help you, one, bring it right home every day. And then secondly, you know, become more efficient and effective in the jobs that you're doing, absolutely and

Matt Kirchner: 19:31

who wouldn't want to be more efficient and effective in their in their work. Talk about the trailer part. You mentioned the trailer a couple times. I want to make sure that that's clear from for our audience what you're referencing there

Brian Cavanaugh: 19:41

sure our specialty trailer. We call it Argos. It's solar panels, bifacial solar panels with battery backup. So it's a NDA compliant. It's ruggedized, do t certifications, nhtsp, it's tollable. You can move it, put it anywhere as long as you have sun. And we use. Starlink. A lot of folks use cellular, but when you have that high definition video, you want to be able to transmit it without bandwidth restrictions and those types of things. So So Starlink solar panels or software anywhere that you can use Starlink in the world. And as long as the sun comes up, which it does every day, as far, so far, yeah, you have this, this ruggedized, really military grade trailer that you can put somewhere in again. What is it you want to see? And then what do you want to do about it once it's seen? Yeah, I can do all that awesome.

Matt Kirchner: 20:32

So there's no people in the trailer. It's all electronics and technology. Got it super, super cool. All right, so now that's now that's launching a whole bunch of questions in my head that are going to be fun to explore. We'll start out with in our audience, individuals that listen regularly know that we use this, this term, the edge to cloud continuum, all the time. I'm a huge believer that we teach artificial intelligence by teaching the edge to cloud continuum. You know, the example that we'll use a lot of times is Spotify, and your phone, it can perfectly predict the next song that you want to hear all the time. How does it do that? Well, number one, your phone has 23 smart sensors and smart devices on them. By smart we mean two things. They have embedded intelligence and they have the ability to communicate with each other. Once we do that, all the concerns about latency and bandwidth that we used to have in terms of sending data back and forth to a computer network, a control system, a cloud, those start to go away. So we can deploy way, way more of them. And that's what's happening in the, you know, in the world, not just of technology, but every sector within our within our economy. But my phone has these 23 smart sensors and smart devices. Those are communicating with my phone, which, by the way, Spotify, knows everything about me. It knows what I listen to, it knows what I skip. It knows what I swipe. It knows what I play over and over and over again. It knows who I follow. It knows who follows me. It knows when I was born. It knows where I live. It takes all this information and it says, All right, this is exactly the next song that Matt Kirkner wants to hear next. It's doing that, not just at the phone level, but it's communicating with the fog, which in that case is a regional data center, and also with the cloud, which is an external data center where all these algorithms are running to do all that prediction. And so if we teach students that edge to cloud continuum, and really anybody, not just a student, if we teach them the edge to cloud continuum in any sector, now you can start seeing how that applies to other sectors. We talk about it in manufacturing with smart sensors, devices, programmable logic controllers, data collectors and computer networks and then cloud computing. Same thing happens in healthcare, same thing happens in energy, same thing happens in retail, hospitality, in defense, in construction, across every one of those segments. And so that's when we talk about the edge to cloud continuum. That is my belief of how we teach AI is we teach how that data is moving back and forth. So in that context, let's talk about what's happening with your technology. So on the edge, you've got cameras and sensors both. Is that, right? What kind of things are on that trailer that are monitoring a job site, for example?

Brian Cavanaugh: 22:51

Yeah. So cameras and sensors we use our standards is like a 30x PTC, so pan, tilt, zoom, camera, 60 degree view, and again, individual customers will determine what it is they want to see. The agent is developed for that particular thing, and when it's detected, the beauty is that will create an incident. That incident is then stored, so we have two terabytes on prem on the machine, but the incidents are stored and then sent to the cloud. So we're not processing on the cloud, processing at the unit level, for speed, the security, all those things are are enhanced when you can do

Matt Kirchner: 23:30

that for absolutely and so, you know, you start thinking again about the edge the cloud continuum, rather than to having to send all of that data that you're collecting up to Starlink, and then via Starlink, it would go to and it is the selective data that you're using is going then to to a data center of some sort. You've got a lot of that data being stored on prem and now, and you've mentioned agents a couple times, let's go into agent tech AI, and in how we're deploying AI agents, which to me, my best analogy there is, it's like a digital employee, right? We can create an agent to do anything that a person would do, but it'll do it digitally. It'll do it much more accurately, and it'll do it faster. So talk about the whole agentic AI side of your technology.

Brian Cavanaugh: 24:10

Brian, I think that's the I'll say the secret sauce is just Sure. Again, that's why you can go across all the different verticals, once you understand, okay, if I were standing there, and I'll use a safety officer, for example. Again, this form factor, everybody looks at the machine and think, okay, security, and that's less than 10% I believe what the capability is. So let's take a safety officer, and a safety officer can't stand on a site where there's a oil and gas platform or field or construction site college campus. I mean, just think about all the different use cases. You can't stand there, 24/7, right? You can. So you develop the agents. What is it you want to see? I want to see no hard hats or safety vests or crowding, you know, because you know things, something's about to happen, anything that you can your mind, can think of if you were standing there and want. To say you can train an agent to detect that on your behalf. Once it's trained, you upload kind of positive images of that negative image that then you validate. Once it's trained, it'll continue to that learning process, and you continue to validate that. It just gets smarter and smarter.

Matt Kirchner: 25:15

Yeah, that's so cool. And I know you can't give up the you know, the underlying technology wouldn't expect you to, but I want to make sure that that point is in law. That that point isn't lost on our audience, is that a lot of times people working in the AI field use big words like agent tech AI. And, you know, sometimes they use them because that's the parlance they use to communicate with each other. Sometimes they use it to impress you or confuse you, or, you know, make you feel like they're smarter than you are. The truth of the matter is, it's really simple, and I love that example, because you're like, we because you're like, we could have a security agent on a job site that's a human being that's doing something. You know, that job probably isn't the most fascinating job, just sitting there and watching to make sure that people are complying with whatever regulation. You know, maybe it pays okay, maybe, you know, maybe not. But now we're taking that technology and deploying it to and then we can take that individual and put them in a role that might be even, you know, even more interesting to them, better paying for them. You know, what have you. The other thing that you already mentioned, and I saw it in manufacturing, right? We used to do all of our visual inspection using people, and so if you're, you know, you're inspecting for compliance with the with a some type of a specification provided to you by whoever is expecting that part next that you're manufacturing. The truth of the matter is, the visual inspection by a human being, it's about 95% accurate, maybe 99 or 97% accurate, I should say, which seems pretty good, other than you realize then that 3% of what you're doing is going out the door and it isn't, it isn't right, right? So that that can be a real problem. So, so the other thing is just the the accuracy side of this that you're able to do with agentic AI. And as young people are thinking about careers around artificial intelligence, how you create an AI agent for a specific task, for a specific application, is really where the future a lot of a lot of this, a lot of this technology is so really, really fascinating. You know, how you're utilizing it. What any examples on the sensors? I mean, are we talking about temperature sensors, moisture, humidity, proximity, light. I mean, what kind of sensors are you using?

Brian Cavanaugh: 27:17

So I think if you use, like the thermal cameras, the thermal cleansing is an example. We have a site where we're just really looking at batteries and make sure that they don't heat up to a certain level, yeah, cause all that runoff. That's an example of, you know, one of our use cases,

Matt Kirchner: 27:33

perfect. Yeah, really, really fascinating. I could sit here and just talk about the technology and the applications for the next two hours. I'm not sure the audience would be as fascinated by that as I am. Somebody will take that offline, along with some of the other discussions about former presidents and what you know, whatever else we've already teed up here for future episodes, but I want to stay on the topic. And let's you mentioned spot AI a number of moments ago, as you were introducing the company and the technology, talk about that relationship and that platform, and you had said at some previous point that it does for video, what chat GPT has done for TechEd. So tell us what spot a spot AI is.

Brian Cavanaugh: 28:09

Well, Spot AI is led by two phenomenal gentlemen that we're obviously partnered with and very close with. They went to Stanford, and I'll say loosely, when everybody went to the cloud years ago, they went to the edge, and they were kind of first and into this area, and very, very experienced, I'd say, probably one of the global leaders in I'll call on the edge technology, and the partnership with us helps them grow to the physical world on the outside of the buildings, kind of like you described. So again, AI has been around for a while, you know, chat, GPT and techs, but to be able to search video, you know? So think of the same type of application chappy GPD does for the text, right? Our partnership with them, we can do that in video. So you can go into our system. It's all web based, a single user interface for entire ecosystem. So if it's inside or outside and everything in between. You can go in and you can type in text and search the video, much like you would do outside of the physical world you're

Matt Kirchner: 29:08

creating. You're engineering a prompt, I should say. But instead of doing that in text, you're doing it using video. And then is the model kind of the same where a generative, pre trained transformer will kind of predict the next word, and that's the kind of predictive side of generative artificial intelligence. Is it doing the same thing? It doing the same thing with video? Or go a little

Brian Cavanaugh: 29:25

deeper, there it does. So you would type in text like, show me all yellow forklifts in the past 30 days. You put the what, you know, you type that in, and you can put the window that you want to look and it'll go through, you know, months worth of video in seconds, yeah, and pop up all those video clips of the thing that you're looking for, cool before you take a human days, yeah, absolutely look in and just try to find what you're looking for. And it does it instantaneously.

Matt Kirchner: 29:54

It's amazing. So it almost feels like, you know, if I go into my, you know, my photo app. On my on my smartphone, and I say, you know, find all the pictures with dogs, and it'll go and find, find the dog pictures. It's doing the same thing, but it's doing it with whatever you're trying to monitor outside, as it relates to security, yeah. So think about that as far as whether it's, you know, whether it's compliance, whether it's going back and even, like, accident investigation or near misses or those kind of things. It feels like there's all kinds of applications there. That's that's really, really cool,

Brian Cavanaugh: 30:24

and you can set it up to create the cases, right? So, like, if you know that, you know these types of things are something that you want to keep, the agents will automatically create a case for it and store it for you, so that when you go back, it's already there.

Matt Kirchner: 30:38

That's cool. Who creates the agents are those all custom, are those turnkey, kind of existing on the platform. Or how does that

Brian Cavanaugh: 30:45

work? We have some preset so, like common so like in construction, like on indoors, like your experience with manufacturing, you know, forklift incidents or the crowding or hard hat detection, those are kind of standard. But any custom one can be built. The custom ones can be built in a matter of seconds and minutes. I mean, it's not

Matt Kirchner: 31:01

that hard, okay, so, so, so an individual utilizing the platform can create their own agent. Yeah, awesome, yeah. This is really, really cool. So tell me a little bit about who creates all this and what is their background. Are these data scientists? Are these computer programmers? Are they AI agent or AI experts, I should say, or, you know, who developed all this stuff again?

Brian Cavanaugh: 31:24

So the spot AI, the founders and their team came up with kind of all this, and they, they developed the software, and it's so user friendly. So at the customer side, sure, even a simple helicopter pilot can go build this agent, yeah,

Matt Kirchner: 31:37

simple helicopter pilot, right? As if that's Yeah, but believe me, I was, I was in the cockpit of that, that helicopter over the weekend. There's, there's nothing simple about what's going on in there, but, but, but, but your point is well taken. You don't need

Brian Cavanaugh: 31:49

to be a data scientist. I'd say that's pretty simple stuff.

Matt Kirchner: 31:53

So let's talk then, about, you know, whether it's a software developer or somebody who's an expert in AI, somebody who's an expert in camera technology, I mean, all these different applications on the on the edge as it relates to artificial intelligence, and talk about, you know, students and some of the careers. So, you know, we're big believers that we teach all of this stuff using applied artificial intelligence. And when I say applied, you know, in a school, I'm thinking like, all right, I can, I can have a scaled down autonomous vehicle platform or drones that are using edge to cloud technology. I can have a advanced manufacturing or industry 4.0 application that's using smart sensors at the edge and communicating with, you know, with cloud software that's finding patterns in what I'm seeing in advanced manufacturing. I can have students who are, you know, coding. They could be programming. I mean, the precision agriculture, you think about the applications there, they could be learning on like a small tractor that's full of sensors and communicating with the cloud using GPS technology and software and so on. That, to me, is how we teach this, right? We teach it in a hands on way we teach it on the applied side. It's not all theory, it's not all coding and programming, not that that isn't important. But there's way more to it than that. Are we like minded? And I mean, I kind of feel like we already are from that previous part of the conversation. And then talk a little bit about how your technology serves as examples of why we should be teaching it that way,

Brian Cavanaugh: 33:13

we are absolutely like minded in this and I'll start my comments with and I'm sure you're familiar and your listeners are familiar with the mandate out of China that all the children learn, starting in primary and secondary education, it's a requirement.

Matt Kirchner: 33:27

So, yeah, let me just tell you I was, and maybe, maybe, if you're a regular listener, you already know this, but I spent, I spent a week in China in August, visited 26 tech, tech companies in six days. And that shocked me. And so keep going on that it's mandatory K 12 education mandates AI education in China. So keep going right?

Brian Cavanaugh: 33:48

So the point I was going to make is that I think we're behind in that thought process. I think our children need to know it's not it's not okay. I don't want to go in and be a programmer or, you know, it's across all and I gave an example of a couple of industries, right? And that's just a couple, but your mind can think of myriad industries that there's application. So if you want to go and if children students, want to go down a different route, you can't ignore it, right? Your point is spot on about just the versatility in not only our education system of implementing some type of learning, I think, I think we kind of limited to, you know, AI's writing papers, and that's the extent of the conversation. That's just so I'll say insufficient for what we need for our future, our national defense or national security, and all those aspects

Matt Kirchner: 34:39

they hear again, this could be a whole episode. I think we have a huge opportunity. There's the education model in China. There's also the US is attitude, for lack of a better term, toward the intellectual property as it relates to coding and programming and how China looks at that. In China, it's all open source, right? There's no IP really, not to say nothing, because I'm sure they protect some of it. It's. Some level. But generally, somebody who's innovating in China, all that, all that code is open source. I mean, so you, you know, you create a new AI algorithm, you put it in a humanoid robot, you know, it's on GitHub two months later, and the whole world has the ability to look in the, you know, look under the hood and see how you're doing that in the US. It's exactly the opposite, in the sense that we are closed source companies like meta AI, companies like anthropic, they're not out there sharing all their code with everybody else. It's like, That's your secret sauce. You used that term a little while ago. That's how we do this, and we're not sharing that with anybody. That creates a competitive advantage, and in a capitalistic economy, creates an opportunity for us to generate revenue and ultimately net worth and wealth. So two really, really different ways of looking at the same, same issue. So your comments on education, on applied artificial intelligence, on the sense of urgency. This isn't a five year problem. This is a five month problem we have here in the United States of making sure that every every school across the country is teaching applied AI, super, super important.

Brian Cavanaugh: 36:03

What I thought about this in February to today is there's so much change is happening so rapidly. And that's to your point about, like, you know, five months, right? And then the others are, the historical approach, as you're talking. It just made me think, you know, like the World Wide Web, you know, microwave, all the things that we kind of gave the world, yes, historically, this is a little

Matt Kirchner: 36:24

different, right, right? Yeah, exactly. Yeah. Everybody's innovating and things to learn from both sides, but I think the stakes are higher, too. To your point, I mean, it's, you know, it's, it's one thing to say, well, we could microwave an egg faster than you could. It's another thing to say that we, you know, we can. We can build an AI platform that has the ability to transform the entire world economy, you know, the country that does that, the company that does that, the individuals that do that, obviously, the impact is way, way bigger than, you know, than the proliferation of the microwave oven. So the stakes are super, super high. I think you make a really, really good point, actually. And also looking forward to hearing a little bit more about vigilantics and in the applications for your technology. So far, we've talked about construction. We've talked about building freeways and infrastructure. What about applications in the military? Is that a future opportunity,

Brian Cavanaugh: 37:14

absolutely when I just retired last year? So when I joined this effort, I thought about these applications, and you get that epiphany, man, I wish couple of my responsibilities was the Marine Corps security aspects of garden embassies and garden nuclear weapons and those types of things. And, you know, just augmenting, I tell folks, because some people get concerned about AI's taking human jobs. I'm like every command I've ever had, every effort I've ever led. I never had enough people to do the task that I had to do. Right? I could take, like, one of our machines and put it there and free that individual up to go do something that deem a lot more important than kind of standing there with that capability. 24/7, right? And then, you know, the recycle and of you know, every post three to three to five people and all those types of things, I could just eliminate that and move those folks to go and do other things. There's so many use cases from a military construct that this would benefit.

Matt Kirchner: 38:18

So I think about the same thing from my days in manufacturing, where everybody was like, aren't robots going to take all the jobs? And I've been, you know, as long as I was in manufacturing, I never had enough people to get the work done. And there's more jobs in manufacturing than there are people to fill them, you know, we'll worry about that when the time comes. But for right now, let's just find a way to get the work done. And good chance there's going to be that much more work waiting for us once we once we solve for this problem. So that's never been an issue, at least in my career. Think about for a moment, Brian, you know, what does the future look like of AI in military operations? I'm sure there's a ton of stuff that you could never share, but but in terms of what you could How is AI gonna gonna affect and impact the military operations over the course of the next, say, three to five years?

Brian Cavanaugh: 39:00

I think that the simplest form is just like in industry, looking for those efficiencies, whether it's in human capital, where we can, you know, start having like, you know, the paralegal type of work done, or administrative type of work, or logistics, those types of things. I think you're going to see a transition there, and then as you go to the higher end where it's going to help in planning and help in strategy and help in execution, right? So again, our machine can tell you when something's happening based off of, you know, what it sees. If you expand that out, if you have, you know, let's say better cameras or satellites and things that can extend out and use an AI to help you speed up that decision

Matt Kirchner: 39:43

cycle. So if I'm a student that's hearing that and I'm saying AI is going to have huge applications in the US military, and thinking about the military as a potential career choice, how should I be preparing myself for that career pathway? What are the things. A student could do in middle school, in high school, what are those things they should be preparing themselves

Brian Cavanaugh: 40:05

for? I think the main baseline thing is to be a voracious learner, right? And if you're not interested in coding and those type of things, which like, Well, I remember carrying four train cards back, right? Exactly. It's a little different now, but just, you know, everything's evolving change. So you want to be very adaptive to change. And, you know, find what it is you like and that you're interested in, and then understand how AI can be used as a tool to support the things that you want to do. And then, again, I tell you, there's, there's not a job that I can think of that's not in the military, whether it's in the Navy with our corpsman or our doctors or aviators, there's, there's infantry. I mean, there's so many aspects, you know, munitions, TechEd, there's everything that you can think of. Those opportunities. Are there one? It's a way to serve your country, do something that you're passionate about, meet wonderful people from all across the globe,

Matt Kirchner: 41:02

yep, and launch, launch an amazing career, whether it's 39 and a half years in the military, and then being the CEO of a tech company or, you know, taking an on ramp or an off ramp anywhere along the way, is just an incredible way to launch your career, build discipline and learn incredible technology and also get some help with whatever comes after you know your military service as well. So super, super career choice and wouldn't, wouldn't hesitate to encourage as many of our young people as possible to to consider that as one as they move through their their education pathway, which is kind of where I want to leave us here. Brian, couple more questions for you. One on education. We've talked a lot about applied education, applied artificial intelligence, education, graduating from high school when you're 16 years old, what students can be doing in high school to prepare themselves for military careers? Is there something about education from your particular pathway, which was unique in many respects, that you would say, I have this view of education that's a little bit different, or might surprise some

Brian Cavanaugh: 41:59

folks, here's a good one. So growing up, I'll say our mother, my sisters and I, we had no idea that college was even an option. So for us, it was ninth grade, 10th grade, 11th grade, 12th grade, 13th grade, 14 I didn't know choice. So just that fundamental, I'll say discipline and thought process really was a benefit to us. And, you know, I don't know that people think about that, right again, I had no concept of, I thought you everyone had to go to college, Huh? Interesting. Not the case, sure. So it was never, it was never option in our household.

Matt Kirchner: 42:40

Got it? Yeah. So there's Yeah. So everybody has to, has to go to college. That was just the expectation that you had growing up from, you know, the environment in which you grew up, and especially during that era, right? I mean, that was to, you know, that was the ticket, and in a lot of ways, to the college education. And so kudos to your family for encouraging you in that regard. And now we think about this stage of the world, which is now, you know, a few several decades later, all these options and all these on ramps and off ramps that didn't necessarily exist. So so consider your options. Certainly, a four year university can be a great one, but, but not the only one. And make sure you keep your your options open. I

Brian Cavanaugh: 43:17

want to make sure I do say that for your listeners that that's not an option or not a consideration. Yep, I would even reinforce that the military or government service options or the vocational options are absolutely a way to get a good start, learn a trade, learn all these things that we've discussed, and then go on and have a phenomenal career.

Matt Kirchner: 43:40

Exactly right? And that's the beauty of the world we're living in today is, is that, you know, we've got work to do and making sure students understand all those options, but they certainly have them. And whether it's, you know, government service, whether it's the military, would love to see that at the top of the list of as many students as possible. And glad you mentioned that we're going to take you Brian for the last question. Back to we usually say to your sophomore year in high school, it's a question we ask a lot of our guests on the TechEd podcast. In your case, sophomore year of high school, you were almost graduated, so let's, let's say, let's say we're going to take you back to your 15 year old self. And if you could give yourself Brian one piece of advice to that 15 year old young man, what would that be? I would

Brian Cavanaugh: 44:18

focus on enjoying today and not worrying so much about tomorrow. I think we all get in the habit of, you know what I gotta do, what I gotta do. And I'll go back to my time when I was hmx. When you leave the squadron, you generally have an opportunity to go up to the Oval Office and get a chance to meet the president, take a photo. So my wife and I went up, and somebody told me, he said, make sure you look around. You're you're in the line, you're kind of moving up, you're moving up, and then you get to the crest of the opening, and you see the president, and then you kind of go in, take the picture, chit chat, and then you're Yeah, and it's like, did I get a chance to look around right absolutely? And I would, I would advise myself to enjoy the moment, enjoy the day as as much as you can. And tomorrow come, don't.

Matt Kirchner: 45:00

Rushing whether you're standing in the Oval Office, which, by the way, is a bucket list item for me, I haven't had that opportunity. I pray that I will at some point in my life, but standing in the Oval Office, what an incredible opportunity that must have been. Take it all in. Slow down. Enjoy today. Tomorrow is another day, and we'll take care of itself one way or the other. But enjoy every single day. I've certainly enjoyed this day spending time with Lieutenant General Brian Cavanaugh, Chief Executive Officer of vigilantics. We've learned so much about his incredible work, about edge to cloud technology, the edge to cloud continuum. I'm so glad we had you on as a guest, Brian. And thanks for being with us. Thank you, and we will link up the show notes at TechEd podcast.com/cavanaugh that's TechEd podcast.com/c. A, V, A, N, A, U, G, H, so any of those references we made today that we want to go a little bit deeper on, we'll be sure and place those in the show notes when you're done there, check us out on social media. TechEd podcast is on LinkedIn. We are on tick tock. We are all over Facebook, you'll find us wherever you consume your social media, including Instagram, by the way. So wherever it is you go for social track us down. Say hello. We would love to hear from you. Love having Brian Cavanaugh on the podcast this week, a great conversation, and look forward to seeing everybody next week. My name is Matt Kirkner, host of the TechEd podcast, thanks for being with us. You.