Artificial Intelligence Podcast: ChatGPT, Claude, Midjourney and all other AI Tools

 Are We Ready For AI To Start Welding With Mark Barglof

• Jonathan Green : Artificial Intelligence Expert and Author of ChatGPT Profits • Episode 364

Share episode

Welcome to the Artificial Intelligence Podcast with Jonathan Green! In this riveting episode, we delve into the transformative role of AI in manufacturing with our special guest, Mark Barglof, a leading figure in kinetic technologies and a pioneer in welding solutions through robotics.

Mark shares his insights on how AI and robotics are reshaping the manufacturing landscape, making processes more efficient and less reliant on manual labor. He discusses the remarkable advancements in AI-driven machine learning models and computer vision systems that enable robots to program tasks on the fly, creating new opportunities for automation in the manufacturing sector.

Notable Quotes:

  • "It's shocking, honestly, how far the advancement is with AI capabilities in manufacturing." - [Mark Barglof]
  • "What we're doing with AI is it's really got the metrology or the measurement systems built in as it's doing it." - [Mark Barglof]
  • "A huge red flag for me is if a company wants to automate just to cut workforce—it's not about reducing people, it's about filling gaps and increasing productivity." - [Mark Barglof]
  • Mark also shares his vision for the future of automation, emphasizing a balanced integration of AI and human expertise to foster innovation and efficiency.

Connect with Mark Barglof:

If you're fascinated by how AI is revolutionizing the manufacturing industry or want to gain insights from a thought leader in robotics and welding solutions, this episode is a must-listen! Stay tuned for more eye-opening discussions on AI's impact across various sectors.

Connect with Jonathan Green

Are we ready for AI to start welding? Let's find out with today's amazing guest. Mark Barglof. Welcome to the Artificial Intelligence Podcast, where we make AI simple, practical, and accessible for small business owners and leaders. Forget the complicated T talk or expensive consultants. This is where you'll learn how to implement AI strategies that are easy to understand and can make a big impact for your business. The Artificial Intelligence Podcast is brought to you by fraction, a IO, the trusted partner for AI Digital transformation. At fraction a IO, we help small and medium sized businesses boost revenue by eliminating time wasting non-revenue generating tasks that frustrate your team. With our custom AI bots, tools and automations, we make it easy to shift your team's focus to the task. That matter most. Driving growth and results, we guide you through a smooth, seamless transition to ai, ensuring you avoid policy mistakes and invest in the tools that truly deliver value. Don't get left behind. Let fraction aio help you. Stay ahead in today's AI driven world. Learn more. Get started. Fraction aio.com. Mark, I'm excited to have you here because we often think of AI as just inside the computer, but it can be really helpful in the physical world as well. And I'm really interested 'cause we just had an incident recently where a robot in China attacked someone and that got a lot of attention, but it's that company has had multiple robot attacks. It's maybe it's the company. It's if it happens a bunch of times and it's the same place, maybe it's them, but just loving your perspective on kind of. The manufacturing world, what is starting to happen and what's like the overview just to get started. Yeah. Yeah. So kinetic technologies, like you said, Jonathan, we're a welding solutions provider. We do it through robotics. Have been using some really cool technology, throwing some things together in the manufacturing space. To your question, what are we seeing, particularly when it talk about ai. Robotics up until I would say with the last five or 10 years when AI really has gotten to be accessible has been a fairly manual process to, to program a robot. I gotta do, gotta move it from here to here and do this and that. Last 15, 20 years we've been looking at different vision systems, but there's been inherent problems with that. So like the manufacturing light, differing light conditions, those types of things make it pretty hard. To do these operations. And, really when you're doing manufacturing stuff, it's built around human beings that are seeing things. They're thinking about stuff. They're manipulating parts, these types of things. And so robotics has been good, but it's been fairly simplistic. I, it's, I'm not saying it's simple, but as far as its ability to do things it, we've been looking at ways to, traditionally, how do you make it so that a robot, you move from here to here? There's very repeatable process. There's few, there's things that we're looking at that are specifically more simple tasks. The redundant things now is what we're, what's really coming online is the computer vision. Machine learning models that are able to identify parts systems that are able to take CAD drawings, interpolate those CAD drawings, and then actually send that to the robot. To do programming on the fly which are exciting. All of that stuff is extremely exciting because it opens up new doors for higher levels of automation. And, eventually what's happening, with robots I haven't seen a robot attack yet I'm not sure how they did that, but but no, what we see a lot with the robots is we're looking at these tasks that frankly nobody wants to do anyway. So we're making a better quality of life, we're increasing productivity. And, the robots are really a big part of that. When I look at a lot of these like 3D printers and manufacturers, the big problem with 3D printer is that it can't tell when it's made a mistake. So it will do it. You go to bed, it's doing an eight or 12 hour print. If it made a mistake an hour in, it doesn't have that detection ability, and that's really for scale, right? When you're doing a thousand units a day. If it doesn't notice, it's like that. I love Lucy conveyor belt where she's eating the chocolate race. It's getting off track and you can't self-correct the self-correcting iss really important.'cause what if it picks up? A metal, that's the wrong metal. Human's gonna go, wait a minute, that's copper on iron. But the ai, if it doesn't have ability to detect that, now you've got this huge problem. And I think the computer vision makes a lot of sense to me as that critical component. It has to have the error check element. Is this the right thing? Because I watch a lot of welding videos on TikTok and YouTube. It's very fascinating to me.'cause like they'll have a welder do something. They're like, oh, that's a $12 weld and that's an $18 weld. There's. There's an element of consistency. There's also an element of knowing, this one's a little, this one is gonna take 12 seconds, not 10.'cause there's something slightly off. And how close is AI now to being able to tell and to adjust on the fly without needing someone right there watching it? Using that human time component as the human, as the error check. Oh, it's shocking, honestly. I mean it how far the advancement is and what we've got with the capabilities. There's a couple things. Some of the stuff that we're using here at Kinetic, we use a just signed on as a reselling partner for a technology called aji. And to your point, and what that does is it takes a CAD drawing. So you put the part in the cad drawing, the system takes and analyzes the part what it should be. You can even put in things like, to your point, Jonathan, on, on error checking. You can put tolerances in. But if there's part deviation within tolerance, the system is able to accommodate for that and make changes. So we just, I just had a conversation with a potential customer yesterday about what you were just talking about. It's Hey, this system is so flexible. What happens if it allows me to do, allows me to make mistakes, which, if it's starting to, and heat that welding has heat inputs change the material properties, they change, they make it bend, those types of things. So we want systems that are flexible and adaptable to be able to handle that. But to your point, the layer of intelligence that we're seeing is not only can I accommodate for that, but at some point I can say, stop, something's wrong here. I'm outside of tolerance. And what's neat is too, is you know, traditionally what we've done is we will do a part, and when you do it manually, oh, you go do it. And welding especially is one of those things that there's a, there, there are some individuals that are really good at it. They produce really good quality welds. The same time you brought in the new guy, he comes in. It's terrible. It looks horrible, but then that stuff get, has to get checked at the end of the line. What we're doing with AI is it's really got the metrology or the measurement systems built in as it's doing it. So not only can you do a better job, but you can also come out and make sure that it's within tolerance. It's within spec. It's pretty cool stuff. Do you think we're getting to the point now where we could have more, like smaller businesses can have a fully automated processes, like CNC machines are super cool, but you put the metal in, it does one thing you take, like you have a human that's watching it taken to the next step and take it to the welding machine. Do you think we're getting close to the point where there can be an overarching processor, AI that's watching it go through the entire fact, like a fully robotic factory almost, where it goes through multiple machines? I do, I really do see that. And I see that move towards the smaller manufacturing starting to see the capabilities. And there's a couple things that lead to that. One of 'em is ai, of course. But there's also the rise of more collaborative robotics operations. Programming in general has become much simpler. As manufacturers start, smaller, manufacturers start to see that. I don't need to have a staff of robotics engineers. Maybe you partner with somebody like Kinetic to get the initial system. But then we give the tools to the manufacturer so they're able to keep up with it. So that's where I see, the AI portion of it is not only to the tools as far as the end process, but also. Some pretty powerful tools that are starting to come in for programming. If we've, even if we get away from something like a pre-packaged system, like a bji that does the does the scan into the CAD and the auto doing the programming, some of the other robotics operations. This couple weekends ago we were stuck on a robot. Couldn't figure out how we were just trying to approach, how do we approach this robot programming? Put it in chat, GPT we taught chat, GPT how to do some robot programming. And pretty soon we came out some pretty, pretty interesting solutions when it comes to programming. So I see that, as you start to get, workforce that gets much more comfortable with the AI tools that are available, they're gonna start to see that robotics becomes very accessible. The tools themselves, you, you're usually looking at it going, oh man, that's a, that's gotta be a, it's got a robot, it's gotta be millions of dollars. Not necessarily, we're looking at pricing for cells with some of the flexibility. It's about a high-end CNC machine. Yeah, I think that. A lot of smaller companies think, oh, only a huge company can afford this. But the advantage of smaller companies is agility. That you don't have to, like, whenever I work with a really large company, it's like you have to do the same proposal to seven layers. Oh, I like it. I'll tell my boss, I like it. I'll tell my boss, I like it. I'll tell my boss. And there's this really long buying cycle. Sometimes I know companies, it's three or four years to make a decision, whereas when you have a small company, one owner. They have that agility, which is a really major advantage. And I'm wondering if it's starting to enter into the manufacturing space where'cause I'm seeing in a lot of other sectors we're seeing fragmentation, which is I was just talking to some earlier today about how information or trainings actually people would rather buy from a smaller company. Where they can talk to the main person. Instead of talking to a certified coach who's just an employee, it's like I'd rather talk to a smaller shop, or the person who's running is the person I get to ask the questions to. That's how I like to do business as well, so I can see there's this chance, especially now where we're trying to shift a lot of manufacturing back to America. It's a big push right now, and there's this big opportunity. It's like, how can we do that? It's like usually foreign manufacturing. It's cheaper because they have lower safety levels. Have something that costs the same amount but is also safe is are the numbers starting to get to the point where someone can actually manufacture in America and compete without having to sacrifice safety? I. Particularly with automation. Yes. I believe that's true. When we did an install of a welding system in a company and they were really good at data collection. So they knew what it took before, what it took afterwards. I. And they saw a greater than a 500% increase in productivity in so much solder that they had to, the welding process used to be the bottleneck. They had to, they went down the line, powder coat became the problem, had to build a new powder coating facility. So with things like if you can create 500% higher productivity with the same workforce. You can amortize the higher wages and the safety requirements and those types of things across more parts. Now we become very competitive. Particularly what we're seeing too is that the quality, our quality standards are higher in the United States manufacturing. Some of that stuff comes in, from other countries and it's, it may not have the same quality as you would through the uni US manufacturers, there's, there, the pricing thing is there's multiple layers to that nut that has to be pulled apart. One of 'em is, if they're dumping raw material, say you're in another countries, China, India, whatever and they, their raw material costs are significantly lower than ours. That's gonna be that's one of those factors that, that is, that's tough to overcome. The other thing, and this is I don't think people understand this in the United States and I wish I had the graphic, but the most, the highest buyer and imp implementer of robotics is actually China. And some of these countries that we're looking at to say, oh, we're gotta attack this from a labor issue, our labor costs are higher. They're already automating at a very high level. So US manufacturers, I'm really, I would like to really push 'em to say it's not just about you, if we're, if we've got a discrepancy currently in price. As they start to bring robots online and they can increase productivity, we need to be even that much more efficient. So we need to have more automation. We need to have a higher level of productivity to, to cross that chasm, bridge the gap. And to, to the point of safety, robotics actually, and before this I worked I had a, I was a co-founder of a company where we built driverless agricultural equipment. And you know what I, what shocks me, and we saw this too, like with Waymo and those types of things, as the, as things are automated, they become repeatable. I know what a robot's gonna do. It's gonna do the same thing that it did before, which is an interesting comfort when, we start to do more complicated parts. Oh man, we're doing this. We just finally made it work. The robot's doing it and at some level you go, oh geez, that was a hard road to get to that. I hope something doesn't happen. But when, but with automation, what's, what occurs is that the robot's gonna do the same exact thing over and over again until it wears itself out. So that, that helps with the safety aspects.'cause, like the rogue robot going crazy, it's just not gonna do that. Not unless somebody programs it to do that. It's gonna be moving from point A to point B and gonna do that for rest its life. Big concern, certainly from ai, stuff that I hear all the time and this idea that everyone's gonna lose their jobs. And I always say we still have farmers. There's still, like we have, it's massively mechanized, but there's still, farmers live on farms, there's still people who have chicken farms, there's still people driving the tractors or even when they have automation funds, they're still getting up at crack of dawn and being part of it. Do you think that it requires someone who has a welding expertise to. Watch robotic welder to check its work to be able I wouldn't be able to tell a good weld from a bad weld. So you could put me in charge of a robotic welder and I won't know. So does it. Yeah, that, and that's a good point. I like how you brought up the agriculture thing. I'm also a farmer. I worked in ag for a lot of years before I did this. The robotics portion of it, same type of thing. The conversation about a hundred years ago was, if we go to tractors, what are we gonna do? You know what I look my horse, the infrastructure around keeping a horse, feeding it the oats, the, there was entire industry around that. We went to tractors and people found places to go. Same thing with industrial manufacturing is the, we're in manufacturing 4.0, which is now what, that means there's four industrial revolutions. We're in that fourth industrial revolution. The three before, it didn't mean that, our population continues to grow. People are gainfully employed. We're not booting people out on the street as this mechanization occurs, it's just that we start to become more productive. People start to look more towards, like you said, more towards thought leadership. So making humans do what humans do the best, which is, creative thinking and free, throw free thoughts and those types of things. And that's to the point of with welding, we say this all the time. I can't be your welder. We can take a good welding process and institutionalize that and continue to do it, but if I have to teach you to weld, I. And then put a robot in there. We got problems. So you still need to have the art and science of the welding, you can be really good at the science, the material science portion of welding, but maybe not have the best trade skills, the art of making sure that the torch is doing the right thing or whatever. Yeah it's you absolutely. In fact, I think that there's gonna be a fairly significant increase in, in demand for people that are more, deeply rooted in the weld process engineering portion, the process portion of it. It's productive, the robot's just gonna sit there and pile parts behind it. You gotta figure out what are you gonna do next? Where's that stuff gonna go? Where does that bottleneck start to move? Yeah, I think we've got to the crux of what I'm really interested in.'cause it's the same thing that I deal with, which is, first of all, people will say, I do digital automation. So same concept. If they don't have a process, they'll say, we don't have a process yet. And I said, then how do you know? Like I, if you don't have a process, I can make it faster, but it will just break faster, right? If you have a road that just goes off a cliff and I make the road faster, great. It's still going off a cliff. And that's really important. I always say. Master the process before you automate it.'cause you have to know what you want. If you can't tell good output or bad output, then automating doesn't make a difference.'cause you don't know what you want and that's important. The second part is there's this constant fear I get, especially when I work with a staff. They go, oh, don't automate it so much that I get replaced. I'm like, no, that's not what I really do is push everyone one level up in management. So the person who's doing all of the manual entry, now they're managing the AI doing manual entry. You still need that person. Because you've seen where the AI goes rogue or makes one bad comment or makes an AI in Canada made like a refund guarantee. And they go the AI said it works for you, so you have to honor it. And that's it. So it's like a really big deal. So I don't really see exactly like you're saying that. Humans disappearing. It's okay, we still have this amazing workforce. How could we redeploy them? That's the mindset I mostly encounter. I very rarely encountered someone who goes, you automated everything. We fired 20% of our workforce. That wouldn't make me feel good. That would make me feel terrible. Yeah. So yeah. Are you seeing that same mindset when it comes to manufacturing automation where they're like, we already have these great employees. Now we can deploy them and make'em 10 times more effective. Absolutely. Jonathan, I, one of the things that I so a huge red flag for me. First of all, I love everything that you said. I'd like to get a lot deeper into that, particularly because, I really appreciate the leadership aspects of all the things that we do. So ai, I like to talk about that later, but but. A huge red flag for me when I first start the initial discovery phase with a company that's talking about automation. If they're like, okay, here's the people we need to get rid of, we need to get rid of Bob, Sally, Joe. It's okay, we got a problem here. You, you can't do. If I'm gonna, if I'm gonna five x your productivity, you're gonna need Bob, Sally, Joe. This is not, you do not see the value in automation, if that's what you're trying to do, is eliminate positions.'cause at the end of the day, if you want to get rid of those five people, so first of all, in the United States automation, if we can get five X productivity, all we're gonna do is reduce our dependence on export, or on import. But we can do it. We can consume all of it. We're a net importing country. That means that we are, we're, we have a deficit when it comes to our productivity. So you need everybody that's in the workforce. But when I talk from company to company, everyone I talk to, they said, Hey. It. I have a list of 10 welders, 20 welders, 25 welders, and this list is not going away. I just can't fill these positions. We want to increase productivity. We wanna increase profitability. We want to create a good place to be. So those are the actually the green flags that I see when we start with that consultation. When somebody goes, Hey, I just had a company that came in. They said, we, I've had two companies in the last three, two or three weeks. We were doing the initial consultation talking through welding automation. A company comes in, one company came in, they said, we have a, we are very proud of our diverse workforce. We would like to know how can we do this to back this up to to make it so that this diverse work workforce works better together, becomes more productive, remove jobs, create environments where we're gonna, we're gonna have people that are able to upskill. So we have really smart people. They just need a little bit of help when it comes to maybe some of the stuff that's harder to teach. But then from there they've got minds that are beyond sitting in a welding hood and doing the same thing in a monotonous job. And I love that. I love those stories. You know what, the other company that we talked about where they increased productivity of five x, they good data people. They actually increased their staffing and their weld department and increased the salaries by 35, 40% I think. So the people that were doing the job before and doing a good job at it, they just were, had a pile of parts sitting on top of 'em all the time. Once they got tools in place that were able to increase pro productivity, they upskilled. They got, they started to learn how to do robots. They did welding better. And it made a lot of sense to increase their salaries because now they've taken on new responsibilities. Yeah, huge red flag. If you're saying, Hey, I, in any way, shape or form, I'm gonna start getting rid of people, it's nah, you're, what we're doing is we're filling holes in the workforce that just don't exist today. And we're just filling it with robots and automation. Yeah. One of the things I always say is that everyone wants to work remotely. Now, if you have people coming into the office and you get rid of 'em all with an automation, you're gonna really struggle to replace them. Because I see people protesting outside like an Amazon office and they have like massages and sadness rooms, and they have a five star chef. I've never had a job like that where they were like, would you like a massage at work? I'm like, what? And if they don't wanna work there. They don't wanna work anywhere. And manufacturing obviously you have to be there in person. Even more and I love you brought up the repetitive task 'cause that's really challenging. I used to have a friend who put the back seats into Saturns and he loved it. He did the exact same four bolts a hundred times a day, 200 times a day. And I was like, I couldn't, that's a specific skill to be able to do a repetitive thing. I'll get distracted. And then something bad will happen. That's my big problem. And it was really amazing to me. I was like, you have the skill, which is rare, the ability to focus. I. To do the same thing over and over again and not get distracted. And to be consistent is really hard. And he was like, but he loved it. He did it for years. He was like, it's his dream job. And I was like, that's amazing that you found the thing you're at. But that's not very common. It's less and less common now.'cause now we see it. Everyone's watching TikTok. I have kids too. It's like they can't keep, if they can't watch a seven second video, how are they gonna do the same thing 150 times a day? So I think that's very interesting. And I think this is the. Critical part is to see that tools and automation don't replace jobs. As we brought in automation, we switched to automobiles. We didn't fire everyone. Like we didn't suddenly have, everyone have not a job anymore. Jobs just changed. So when they talk, this is one thing that I get frustrated. I say, oh, jobs are gonna disappear. It's no, they're just gonna be new ones. Right? There was no job robot repairman 20 years ago. Right now, that's a job. Then there's gonna be a job like machine learning and AI training. There's so many new different names for jobs and so many different opportunities, and I think it's also really interesting to see that it doesn't require a massive college degree and a doctorate to work in a live technological, because that's the whole point, is that it's making it more accessible rather than less accessible. Like I rarely hire my staff. I rarely hire people that have been to college. I'd rather have someone that knows how to work. All my friends went straight into working at high school. They became adults a lot faster than I did. They had to start having a responsibility. There's really a different mindset, and that's what I find really fascinating. I think that we're gonna see more and more as we start to realize as we switch away from this mindset of replace your workforce with robots and ai. There's no way, like when you have a humanoid robot, when you think about how expensive those are and the components inside and they break easy, right? You have a thou, the more complex a machine is and you have something walk around like a person, those are like $6 million. What employee would you replace with a $6 million fragile robot? That's the thing. It's like that would never happen. We don't have enough rare earths and batteries to put inside like that will never happen. That's definitely science fiction. And once people let go of that and think you can't replace your workers, what you can do is upskill them, make them 10 times more valuable, be more agile. And that's when smaller companies, smaller manufacturers, smaller businesses can really be agile because these large companies are really making slow decisions and that's why they're getting behind the AI curve. Just to like in your seeing in your industry. When you look towards the future, what do you think is gonna happen over the next like three to five years when it comes to AI and manufacturing and in welding and other types of machining? Yeah, it's, it I'm almost hesitant to answer because it's unbelievable what I see in advancements almost every day. Each time chat, GPT drops a new model. It's oh my goodness, I can't believe I'm living in this environment where you can have this type of a technology. But, we're, I would say AI is still, it's like you said, there's some scariness to it. People still look at it, oh, it's robots given, it's Terminator, judgment day type of things. I think as people as AI starts to get more integrated into people's lives, just like the internet, as, I was a kid, we'd go to the library and they had one dedicated computer that you could look at, what do I do with this thing? And now it's just. Ubiquitous. That's what you do. It's kinda like an extension of your brain, and I see that, when manufacturing, there's several things that as we start to evolve, not just in the process, but you go beyond that and you start looking at what if? What if I could. Take, and this is not a what if it's possible, it is happening. You know what, if we could take and look at productivity or we look at the parts that come through and we can scan that stuff, start to create heuristics, start to understand when a machine starts to go down. So we have prognostic type of applications the increases quality catches, things faster, reduces recalls those types of things start to get better as we go through the AI stuff. The things that were complicated before that you had very few people doing, those things are gonna start to be easier and more accessible. Like with the robotics space, as the, as AI starts to come online, that's where we're really gonna see that robotics becomes much easier to implement. And when I first got into the robots, I, I, we started Kinetic. We were an engineering prototyping house. I did work in ai worked in machine learning, computer vision applications in the Ag tech world. But when I saw the first robot, the collaborative robot, I thought, wow. I do think in some point down the road we're gonna be going and getting our cobots, our collaborative robots to do things like dishwashers and doing your dishes. That if you know you've got something that can interpret where stuff is at, it, programs on the fly, it picks it up, puts it down, that makes it so the life's a little bit better if I didn't have to deal with doing dishes every night, which is always a problem. But you start to see that, I think just across the board now. It does bring up a good point, Jonathan. When you talk about, the smaller companies and the agility, that is the most important thing. There's gonna be companies and I can see 'em, these larger companies that just aren't, they've got this. I was just received a, from a client, I've seen this a lot where I get like 47 pages of requirements for, Hey, before we put a piece of machinery in, we gotta do this. The cost and the implementation cost doing that and the leadership capital that needs to be burned to get some of this means that they gotta do, it's gotta be right, right off the bat. Whereas a smaller company's taking the iterate to put something in, take a look at it. How does it work? Make a change? We're working with a company currently we're putting in a cell in New York and they. They they're automating a welding process that they've been told they can't do it. AI isn't there, but interestingly, to the job point, what they're doing is they're putting in, they're, they've, that entire industry has been created around cooling and data centers. So to your point of, I think that American manufacturing, just in general, we're gonna see more. It's gonna be more productive. Working in a factory in the next five years, I think is gonna be a lot more advantageous. People are gonna go, it really does feel more like a comfortable environment, the environment's clean. The robots are doing the stuff that we don't want to do. Humans are most empowered to do the things that we do best, think, communicate, rationalize create, be more creative, be more have more of a focus on leadership. So the workplace is gonna start to evolve. And then the things that we're doing, when we talked about before, all the people that were taking care of, shooing, horses, the blacksmiths, now the tractor comes in. They start doing different things but, and then the industry start to crop up. Like this company that's all of a sudden, there's this huge explosion in requirements for, we've worked with companies that, for radiator or for generators. The gener, the backup generators for the AI data centers, huge demand for that didn't exist before. Same thing with tubing or coolant pipes or those types of things that help to cool these data centers. And you'd also talked about, the jobs that are being created, for example, in the, machine learning environment where we need to classify photos. In my last company we used a company that would outsource these jobs to, image classifications. So we'd send tons of raw data out to areas that were socially disadvantaged. Some places in rural India, we had them classifying images, image imagery which creates a whole new set of revenue possibilities that weren't there before. We also, if we needed it to be based in the United States, we could have it done in, some rural places that are really socially disadvantaged where it's hard to get a job. Now, all of a sudden we have this job of going in and doing image classification so that we can run it through our models. Yeah, I think that's really amazing. I think that's the kind of mindset I have about AI and automation is that it's moving us forward, not moving us backward. And I think that's what gets me excited and hopeful. And I think a lot of people are gonna find this really interesting for people who are interested in what you do and wanna know more about kinetic kind of thinking, oh, maybe AI welding or these types of technologies really help our manufacturing.'cause we do have. A lot of manufacturers, a lot of people manufacturing space to listen to the show. Where's the best place to find out what you're doing and check out the amazing stuff you're doing now? Yeah, always could go onto our website. It's www dot K-I-N-E-T-I-C-T-E-C-H-L-L c.com, which. When you start a business you don't think you're gonna have, you're like, oh yeah, that sounds good. Kinetic tech llc.com. It becomes, yeah, it's on our email and everything else, but yeah, check us out there. We do, I spend a lot of time we, we focus on the aspects of leadership. What does it mean in a management organization and manufacturing to implement automation? Ai, we I spent some time communicating that on LinkedIn, so check us out on LinkedIn. We do have a little bit of Facebook presence, but most of what we do, most of our communication goes through LinkedIn or over our website. Amazing. I'll put the links in the show notes and below the video. Thank you so much for being here again for another amazing episode of the Artificial Intelligence Podcast. Thank you for listening to this week's episode of the Artificial Intelligence Podcast. Make sure to subscribe so you never miss another episode. We'll be back next Monday with more tips and strategies on how to leverage AI to grow your business and achieve better results. In the meantime, if you're curious about how AI can boost your business' revenue, head over to artificial intelligence pod.com/calculator. Use our AI revenue calculator to discover the potential impact AI can have on your bottom line. It's quick, easy, and might just change the way. Think about your bid. Business while you're there, catch up on past episodes. Leave a review and check out our socials.