Vision Podcast #16 – Building a Career in Machine Vision w/ David Dechow

MVPro Media – The Vision Podcast #16

Guest – David Dechow, Motion AI

Josh kicks off the year with an interview featuring David Dechow, a renowned expert in machine vision and industrial automation. David shares insights on his decades-long career, the importance of fundamentals in machine vision, and the value of mentorship and continuous learning. His thoughts on emerging trends in 3D imaging and the proper application of AI provide a compelling start to 2026 for both new and seasoned professionals.

“Find something you truly enjoy doing, dive deep into it, and you’ll never really work another day in your life” — David Dechow

On this page:

• Podcast player
• Guest information
• Useful links
• Episode chapters
• Episode transcript

Listen to the Episode

About our Guest

Useful Links

• David Dechow on LinkedIn
• Motion AI | ai.motion.com/
• “Keys to Deploying Machine Vision in Precision In-Line Measurement Applications in Manufacturing”
• “Software basics in 3D imaging components and applications”
• “Best Practices for Implementing Vision Guided Robotics”
• A3 Certified Vision Professional Program

Episode Chapters

Click onto the chapters to access the relevant section of the transcript below.

1. . What Makes a Vision Application Valuable– David answers the favorite application question and explains what he values most in machine vision projects.

2. Early 3D Vision and How the Technology Evolved – A look back at early 3D robotic guidance, custom-built systems, and the evolution of vision tools and algorithms.

3. Building a Career Around Machine Vision – How David shaped a long career across integration, education, and industry leadership.

4. Teaching, Certification, and Growing the Vision Community– David discusses education, the A3 Certified Vision Professional program, and why sharing knowledge matters.

7. Vision Fundamentals in the Age of AI – Why imaging, specification, and correct tool selection still matter alongside AI.

8. Mentorship, Motion AI, and What’s Next – Advice for engineers entering the field, mentorship, David’s role at Motion AI, and what’s ahead.

Episode Transcript

[00:00:00.160] – David L. Dechow

When I started, that was the only way I learned. I literally drove around east of the Mississippi and visited all of the people who were doing machine vision.

[00:00:09.200] – Josh Eastburn (host)

Welcome back to the MVPro podcast. We hope you enjoyed the holidays and are feeling ready to dive back into machine vision. Because today I have an interview that I’ve been looking forward to for a very long time. David L. Dechow is an engineer, programmer, and technologist widely recognized as an expert and thought leader in the integration of machine vision and related automation technologies. Today, Mr. Dechow is Machine Vision and Industrial Automation Solutions Architect for System Integrator Motion Automation Intelligence, but he has had a decades long career serving the automated imaging industry, founding two integration companies and working for others like FANUC America and Landing AI. Mr. Dechow is a recipient of the AIA Automated Imaging Achievement Award, recognizing career contributions to the vision industry. He is a member of the A3 Imaging Technology Strategy Board. As a key educator in the field of machine vision, Mr. Dechow has participated in the training of hundreds of engineers as an instructor with the A3 Certified Vision Professional program since its origin. He’s also known for his frequent informative technical articles, papers, webinars, conference sessions, and classes covering a wide range of topics involving machine vision and associated enabling technologies within industrial automation.

[00:01:24.700] – Josh Eastburn (host)

The reason I was so excited to have David on the show today is because typically we’re talking about the cutting edge stuff, right? latest developments, new products coming out. To start 2026 off, I really wanted to take it back to fundamentals, which is really where I think David’s work shines. We also talk a fair bit about career development. So whether you’re just coming into the field trying to learn the technology, or whether you’re kind of considering what the next step for your career might be in 2026, I promise there will be something worth listening to for you today. Ready? Let’s get back to basics.

[00:01:59.370] – Josh Eastburn (host)

I think I have more questions here than we can hope to get through, but we’re going to try.

[00:02:06.530] – David L. Dechow

Yeah, that’s fine.

[00:02:07.650] – Josh Eastburn (host)

Okay, great. So it’s become tradition in the inaugural year of the podcast for me to ask about favorite vision applications. And honestly, that’s kind of my favorite part. And yeah, like I feel like I need to give a warning to future guests. Have a good answer ready, because like we are judging you on your answer to this question. But I’m really excited to ask you about it because I know you have seen some stuff. You’ve owned and operated two integration companies and somehow you’ve kept one foot in the trenches even while becoming this prolific trainer and media voice, which I will also want to talk about. But just to kick things off, I would love to hear about a favorite project of yours. What comes to mind?

[00:02:49.460] – David L. Dechow

Well, I think that’s a great question. And I’m not going to avoid it. I will say one thing to start out. I often say in my webcasts and in my classes that I give, I’ve never met a vision system I don’t like.

[00:03:07.780] – Josh Eastburn (host)

Yeah.

[00:03:08.260] – David L. Dechow

And I’ve used, and over my career about 40 plus years, I’ve used just about every vision system that has commercial vision systems ever come out. And you can do so many things with vision. And I would say that my answer to that question has evolved over time and probably will continue to evolve. The way I think things are now, the things that interest me the most, and I think are not only interesting just to me, but also, let’s say, emerging, not brand new, but emerging applications in machine vision that we can do more and more with over time. First of all, 3D imaging. I have done 3D imaging again since the start of my career, and I just love 3D imaging. I think it has a lot of value in a wide variety of applications. Another thing I’ve often said, if people have heard me say talk like this before, is that if I had the opportunity, I would have an imaging system that would gather 3D, 2D, color, even non-visible if possible. Yeah. Because when you’re doing a vision application, all of that stuff can only enhance the success of how you’re analyzing the image.

[00:04:19.530] – David L. Dechow

So here along comes 3D, and really the trend right now is 3D systems, 3D imaging systems, not counting the software, but 3D imaging systems themselves, give us a nice point cloud, really high res point cloud, or a high count point cloud, along with that color image. It’s become kind of the thing for the 3D system to offer. And so I’m pretty excited about the possibility of 3D systems. I’ve been doing a lot of vision guidance recently in 3D and bin picking, for example, in 3D. That’s become one of my favorites. Another one I like a lot because of its value to the end user, but one that is also, I would rank in the higher echelon of being a difficult application, and that is precision online metrology. Using either 3D or 2D, in many cases 2D. And so as an application, I find that to be, again, not only of interest, I really doing it and it requires some skill to make it work really well and really repeatably. I’d say that would be the other one that’s really on the top of my head. But don’t get me wrong, I think every machine vision system, every machine vision application is valuable to the end user process. So I like those, but I’ve never met one I don’t like.

[00:05:38.200] – Josh Eastburn (host)

I read that you started your first integration company in maybe it was 1990?

[00:05:44.040] – David L. Dechow

Yes, that’s correct. And I had already been doing machine vision integration for about eight years before that.

[00:05:52.040] – Josh Eastburn (host)

Yeah. And when were you first introduced to 3D imaging?

[00:05:57.400] – David L. Dechow

That’s interesting. Prior to when I started my company, I did a a 3D imaging application for robotic guidance, believe it or not, as early as 1985. It was really fascinating project. I don’t know all of the competitive environment, but I sensed that I was one of the early adopters. I had to, of course, at that point, you had to create the 3D image on your own. You didn’t buy a 3D imaging system, but it was for a robotic this will tell you how old it is. It was for robotic riveting of truck frames. Of course, there’s no such thing as riveting anymore. It’s all weldment. But guiding a robot to do in 3D to do robotic riveting. I didn’t do a lot after that and in that particular context. But then as I got, as you say, I guess I got into more and more working with my own companies. I did saw a lot more 3D opportunities.

[00:06:50.460] – Josh Eastburn (host)

Interesting. And what company was that with? Do you remember?

[00:06:54.730] – David L. Dechow

That I was working for? Yeah, no longer there. A company called Martin Systems out of Lansing, Michigan. That was one of the early companies that did offer machine vision systems integration. And that’s originally why they brought me online was they said, We’ve got this vision system. We can’t figure out how to program it. You want to try? I tried and I loved it. And again, I always tell my students, find a career, find a thing to do that you love doing and you really will never work another day in your life. You’ll just enjoy, you know, enjoy what you’re doing for work and it’ll be a pleasure.

[00:07:27.320] – Josh Eastburn (host)

Were you committed to vision at that point in your career, either through your education or early work experience? Did you know that’s what you were gonna do?

[00:07:35.000] – David L. Dechow

No, you know, back then there were no vision, there was no such thing really as vision. It did exist, but it wasn’t a technology in the forefront of automation. And there were no classes, no training other than what you could get from the vendors. I came out of a computer science environment.

[00:07:52.220] – Josh Eastburn (host)

Oh, okay.

[00:07:52.820] – David L. Dechow

Which helped me work with the machine vision stuff. But most of it in that context was, I think people got it great. Now you can learn machine vision from things like CVP classes, things like MVPro magazine and so on. But I had to dig and scratch to get mentors and look up information to learn what machine vision did and how to do it.

[00:08:12.140] – Josh Eastburn (host)

That’s fascinating. Do you remember then what some of the tools were that you were using back then to build that yourself?

[00:08:22.050] – David L. Dechow

Yeah, I think people would be shocked. Early vision systems had some very cursory tools. One of the earliest ones I worked on, all you could do was access pixels. And if you wanted to, for example, extract an edge, you had to write your own edge extraction algorithms or turn that into a line or turn that into a circle. A lot of it was very low level, very low level algorithms, even as late as the 1980s. But people were using a broad range of vision systems and the tools got better very quickly. Of course, some of the favorite tools nowadays, geometric searching and even normalized correlation, those kind of didn’t come into play until late eighties and early nineties, but it was a pretty it was pretty much the Wild West in terms of vision algorithms. Yeah.

[00:09:06.900] – Josh Eastburn (host)

So you identified this early on. Fell in love with it and have made such a rich career from what I can tell. From your enthusiasm, that certainly comes through. And so I’m curious, and I think other people would be also, of how you have made a career of kind of doing everything there is to do in the industry outside of maybe R&D within one of the sort of vision vendor outfits, right? Yeah, tell me how you have managed to do it all. What does that take?

[00:09:35.640] – David L. Dechow

It certainly does take really enjoying what you’re doing, of course, as a first step. I found that I wasn’t doing enough machine vision. And that’s actually when I did start, I did start my first company for the sake of concentrating exclusively on vision. And when you do focus on a, well, a technology or a discipline, let’s call it, if it’s not a technology, a discipline, When you do focus on a discipline, and again, and enjoy it, but when you do focus on it, you really have the opportunity to dive deeply into that. And that’s been my commitment to myself is to always get as deep into the technology as I can and understand everything that’s going on. I liked your comment about the R&D though too, because I have not done R&D. Interestingly enough, and highly respect the people who do research and development of the raw algorithms. I would call myself more of a practitioner. I use algorithms, I use the technologies, but it still requires that you know how to use them. I can teach in the in classwork or in courses, I can teach all of the algorithms, but learning how to use them is really an ongoing thing and learning where to use them correctly is an ongoing thing.

[00:10:48.950] – Josh Eastburn (host)

You received an AIA award for your contributions to the industry and, forgive me if I’m beating on this too much, but I just think this is, I’m just really interested to, to talk about that and what that meant for you personally and professionally. Were you surprised? Were you, we, did you know you were in the running? How did that come together?

[00:11:08.590] – David L. Dechow

I was surprised. I didn’t know in advance. I think I, I was surprised, but extremely honored. They don’t give that award away anymore after AI merged with A3, but some of the people that are recipients of that award, I’m just plain honored to be a part of it. There are many people that really deserved it. I hope that I deserved it as well. But all of the work I had done in the industry, even up to that point, particularly in working on educational opportunities for people through the trade shows, through conference sessions, through webinars, I think that was a part of the impetus behind me receiving that. And I really, I’ve continued that into today.

[00:11:49.610] – Josh Eastburn (host)

Yeah, and that’s really why I’m bringing up all of this sort of foundational career stuff, because I think one of the things you are best known for is your long time contribution to the A3 Certified Vision Program. I think, I don’t know if I read this in your bio maybe, but I think you have taught at this point hundreds of classes on Machine Vision Fundamentals, is that right?

[00:12:09.390] – David L. Dechow

I would, I don’t know if the classes are in hundreds, but certainly the students are in hundreds, if not thousands at this point. And I’ve always felt that, that if people who are in, let’s say in the know insiders in the technology and really know the technologye, we, and I’ll say this even selfishly, we want the technology to succeed. That’s something I’ve always, I’ve always felt is that I want this technology to succeed, become accepted. And I believe that the more people know how to use it when you share your knowledge, the more accepted it’ll become and then we’ll all prosper. I think some people have a feeling, I don’t want to teach anybody that they, then they’ll take my job or, yeah, no, I like to share. I share whatever I can about machine vision with the hopes that one or two of those people in that audience will say, boy, that sounds exciting. I want to do it. And then I’m going to convince my, I’m going to convince my manager to buy more machine vision. That’s the selfish, that’s the selfish side of it. Yeah.

[00:13:08.340] – Josh Eastburn (host)

No, it’s smart. And I think that is what makes tech communities great, right? Yeah. Whether you’re talking about the open source world, where there’s very leans into that idea, right? But just that idea of sharing knowledge and then that knowledge should be available, right? And that how that rising tide lifts all boats. Yeah, I love that. So I wouldn’t even begin to try and recap everything that you cover in your courses, but maybe put on your, the mindset of an engineer who is entering the profession now in an age where deep learning powered algorithms are becoming part of every product. What aspects of vision fundamentals do you think are most important? Today to invest in understanding.

[00:13:54.470] – David L. Dechow

The part of machine vision and even computer vision, I differentiate those terms as being traditional versus AI algorithms, but the one coherent, important thing about any vision application in industrial automation remains correct specification of the project and correct specification of the imaging. I know we’ve had, in the advent of deep learning, as a tool, I call it a tool, it’s not a solution, it’s a tool in machine vision. With the advent of deep learning, we saw a lot of discussion about how we don’t even care what your image is, just take it with a cell phone and we’ll do industrial automation. And we knew that was wrong at the time. Everybody knew that was wrong at the time, but it’s proven out to be wrong. AI can do, or deep learning can do a lot of things, but it needs to be part of the tool, the kit. And in all cases, the imaging has to be, has to work correctly. And how do you get the imaging to work correctly? You dive deep into understanding the application, analyzing the application, even prototyping, doing proofs of concept, doing feasibility studies. And know exactly what all the, let’s say, gotchas are going to be when that camera gets online, that’s the first step and then correctly specify the remainder of the project.

[00:15:20.780] – David L. Dechow

There’s a lot more to it, of course, but I think if I were to pick anything, I’d call that it.

[00:15:25.820] – Josh Eastburn (host)

I’d like to pick at that a little bit. Yeah. So maybe another way to think about this too is you’ve mentioned one area where you’ve seen people going wrong, right? With the new fangled technology. And I, yeah, I think you’re totally right. Everybody, especially as technologists, right? We intuitively know it can’t be that good. Especially for an early generation product. What are some other maybe common pitfalls and where people are overlooking some of those fundamentals?

[00:15:55.420] – David L. Dechow

Yeah, I think it goes back to like a little, little comment about it, things being tools in the machine vision toolset. People want things to be so easy and point and click and just pick one, I’ve picked one tool and I’m going to use this is going to work for everything I do. And that I think is the other biggest pitfall that people have in doing machine vision. Let’s say we get the imaging right, we analyze the application and then one might mistakenly just say, oh, all I need to do this application is this. Tool. There was a time when that was search algorithms. There were, there, it’s more and more, all I need is deep learning. And the fact of the matter is getting to a reliable and robust, a repeatable machine vision solution requires that you use all the tools or you’re able to use all the tools and then apply the right tool for the exact project. And I see this all the time as I look at applications and as I get contacted by people. We tried this and we threw a bunch of blob analysis at it and it didn’t work.

[00:17:05.090] – David L. Dechow

Okay, sure. That’s not, you did a great job, but let’s try to do it using a few other, your image looks good. Let’s try using a few other algorithms that make that more robust and more precise. So using the whole toolbox, if there was a one hint, that last, that one other thing that would be the big gotcha that I see is use the whole toolbox, make sure that you have the whole thing, the whole thing. Working reliably.

[00:17:30.030] – Josh Eastburn (host)

That’s interesting because I guess any tool can become a crutch, right?

[00:17:33.870] – David L. Dechow

If it’s- Absolutely.

[00:17:35.230] – Josh Eastburn (host)

If you don’t have enough of them in your toolbox, the old hammer and nail. Hammer and nail analogy. Yeah. And so, you know, to, to go back to your earlier point, deep learning could be your current crutch. Or maybe it is going to be for a generation of engineers that are coming in until they kind of broaden their palette. Yeah.

[00:17:53.070] – David L. Dechow

I think that, again, I’m not against deep learning. I’ve even worked in, worked in with a company that did deep learning exclusively. I’m not against it, but when we, I think as technologists, as we’ve said, or as engineers, when we rely exclusively on one thing and hope it will solve every particular problem, we’re not doing ourselves a favor. We’re not doing the application of favor. So I, there are, and we, we could go on and on about what are the specific times when you use deep learning, and there are some, but again, Just, it will be the, it will be the golden child of machine vision for a while, yes. But people are already saying, yes, this is a tool. This is something we can use, but maybe not for everything. Yeah. A lot of the things, I was going to say a lot of the things that are, it’s interesting though, too, if you go under the hood, a lot of things that are touted nowadays is AI. Have very little of what the common user would call AI in it. I’ve made the argument many times, you could say, and probably very quite correctly, that machine vision in and of itself is AI.

[00:19:06.780] – David L. Dechow

And a lot of the tools that we use in machine vision derived from the early, early AI, quote unquote AI work in the late 50s and early 60s. We’re still using those tools and they’re under the hood, even if we don’t use deep learning.

[00:19:21.490] – Josh Eastburn (host)

Yeah, 100%. It’s certainly a marketing shorthand for the latest generation of computer technology that you don’t understand yet. But you will, we will all come to discover that these are precisely named and researched algorithms, and that will become the new trade name for what we’re looking for to incorporate the next, the name of the next tool. Yeah, we’ll learn, we’ll catch up. But to kind of put a bow on this conversation about vision fundamentals, If I have never heard of this program before and I’m going, okay, I’m listening to you talk about this dilemma, right? Of having tools but not enough tools, right? And getting that breadth and getting that depth. How do I make that happen for myself? How do I become a certified vision professional?

[00:20:03.440] – David L. Dechow

That’s a great question. And I do get students even in the CVP classes saying, how do I turn this into my career? What am I going to do? The CVP class is a great foundational class. I give the fundamentals, but the whole coursework is several classes and it’s a great foundational set of classes for understanding machine vision. But I do think you have to go beyond that. I have two, if I, right off the top of my head, I have two things that immediately pop to mind. We have, I think the current trend is to not want to learn as much, but want to have something shown by example in a webcast or something, and we want that to work right out of the box. We just want that to work. And the fact of the matter is, of course, it doesn’t usually. So we start with understanding the fundamentals and understanding the coursework of something like a CDP, and then move on to actually working with the product hands-on. Are products, hands on, working with the technology hands on, and literally going through how those particular products define themselves, what their user manuals are, what their technology are, read the technology that is under the hood in the product you’re using, and try to understand that.

[00:21:26.890] – David L. Dechow

That’s a step I don’t think you can skip and become truly proficient at what you’re doing. The other thing is an art that I think we’ve lost in the last 20 years is the art of seeking out mentorship. There are people in your company that probably know in your company or maybe in your sphere of influence that probably know this technology really, really well. Seek them out and talk to them and ask them about your applications. Don’t just, don’t just email technical support. This isn’t working the way I want it to. Seek out mentors in the industry who can help, who can help or give you little bits of information as you go through. Like I said, when I started, that was the only way I learned. I literally drove around the east, east of the Mississippi and visited all of the people who were literally doing machine vision, folks like Perry West and Nello Zuech at the time. And others. I’d say that’s it. Learn, learn the technology by actually diving in and not expecting just one, one thing to work when you click on it. And then also seek out mentorship. This is, this technology is still one of those where we, when we interact with other people who have done this before, we learn more. We learn a lot more.

[00:22:45.150] – David L. Dechow

 i have people in right here in the company in Motion AI where I work, people will work with me in the lab. Learning how to do machine vision applications. New engineers come in and they work with me in the lab and learn how to do the applications. See if you can work, if you’re in that same boat, see if you can work out something like that. And I think I can guarantee it will help you if you’re listening and you’re the person who wants to do machine vision. I really think it can guarantee that you move forward in that field.

[00:23:15.530] – Josh Eastburn (host)

So if you want a shortcut, listener, Motion AI is hiring. I happen to notice.

[00:23:21.770] – David L. Dechow

I think they are. I don’t watch that. I don’t follow that, but yeah, I think they are.

[00:23:25.450] – Josh Eastburn (host)

Yeah. I happen to see that. So you can, you’ll work shoulder to shoulder with David.

[00:23:30.010] – David L. Dechow

Yeah. Yeah. I’ll go out, even go out on a limb. And I’m comfortable doing this because I do it in every webcast and every class that I give. Drop me an email. I, I haven’t been inundated by emails even after saying that, but I’m always happy to talk to somebody or look me up on LinkedIn. I’m always happy to talk to somebody who wants to know something about machine vision. And if anything, I probably talk too much, but I do enjoy having people who sincerely want to know more about machine vision and I’ll make myself available, maybe not on a hourly, every hour of every day, but if you want to drop me a line, do so. I’d love to hear what you’re doing and help if you have a question, help you in any way.

[00:24:13.270] – Josh Eastburn (host)

That’s fantastic. I will be sure to link that in the show notes, at least to your LinkedIn profile.

[00:24:19.090] – David L. Dechow

Sure.

[00:24:19.210] – Josh Eastburn (host)

Um, we’re coming up on time already. And so, my goodness. Yeah, I know. This has gone fast. Um, so actually one thing I wanted to touch on before we wrap up, because you have been prolific in trade media and different industry journals. Are there any sort of your many articles that come to mind, let’s say, that you would recommend as a read to somebody who is trying to get some of the fundamentals?

[00:24:43.730] – David L. Dechow

Yeah, yeah. I have, I do a lot of them. I do a lot of webinars. If I were to pick a couple going back to my earlier, our first discussion about what’s the favorite apps, right? I have a couple I think stand out recently. They’re, I’ve got just tons of older articles and webinars, but some that I’ve done recently, I think that really stand out that you can find online are one about, I’ve got actually a couple out there about 3D imaging and bin picking. And I think that you could look those up.

[00:25:15.610] – David L. Dechow

Yeah, we can- Another is, yeah, I’ve got a couple on precision metrology in inline measurement. I really think that those were valuable articles. And then I’ve done this topic before, but coming out in the beginning of the year there’ll be an article on designing and deploying machine vision systems. That very first step that I mentioned right off the bat here, that very first step of making sure that you analyze the application and what questions to ask and then how to translate that into a successful machine vision system. And that’s another one we’ll see shortly. And it has been, I have a couple out there from prior years. And I think I mentioned it. If you want to see what’s available online, just Google me. Just type David Dechow in the Google bar and it pops up. Page after page of art, current and old art, if you want to go back that far.

[00:26:11.800] – Josh Eastburn (host)

Excellent. I’d like to end with a plug for Motion AI. What took you to Motion AI? This is not your company, correct? Yeah. Unlike a lot of your career has been your own integration companies. Yeah. What brought you together and yeah, what are you excited about? What’s going on there?

[00:26:25.560] – David L. Dechow

The main thing was that it was a company that did and focused on machine vision integration. After my, after I sold my first company and the second company, I retired, I went and worked for just a wonderful employer, and that was Fanuc America as a subject matter expert for machine vision and vision guidance in that team. And I loved that company, loved the work that I did there, but longed to do something that was more focused on machine vision and the integration of the components without starting another company. That’s a whole another story. You can spend a whole episode on why or why not to start a machine vision company. But anyway, that’s the reason I went into that came to motion, which is at that time, Integro Technologies, but I came here just exclusively because I wanted to be in an environment where I did more and more machine vision integration. So I’ve been very happy with that.

[00:27:23.400] – Josh Eastburn (host)

Excellent. That makes a big difference to keep one hand on the technology at all times. So let’s talk maybe about anything that’s coming in the year for you. You mentioned a few articles coming out, presentations, conference appearances that we should look forward to in Q1.

[00:27:40.210] – David L. Dechow

Yeah, yeah. I’ll, while in Q1, I have, again, I mentioned the article, and I have two webinars, and I always say this about my webinars and my classes, I always say, I’m not promoting anything commercially. I just want to share what we can do to learn more about machine vision. So yeah, I do have a couple of interesting webinars coming out in February. One on, if I say it, if I got this correct, I believe one is on hyperspectral multispectral imaging and another one on non-visible imaging. Forgive me if those aren’t the two, because I do something like 24 webinars every year, so there’s sometimes lose track, but, yeah, that’s coming up in the first quarter. Second quarter, of course, I’ll be at, I would, I will give a kind of a plug for this second quarter, I’ll be at Automate, the Automate show this year. I really think that’s a valuable show if you’re into machine vision, robotics, motion control. Great show to go to. And of course I’ll be speaking there in the CVP classes and other presentations. I will get, put a little plug in for that show.

[00:28:51.030] – Josh Eastburn (host)

That’s for you, show. And if I want to, yeah, yes there are. We’re hoping to get onto some of those too. If I’m hoping to sign up for one of your certified vision professional classes, I would do that through automate.org, correct?

[00:29:04.290] – David L. Dechow

Correct. Yes, a3@automate.org and they have a lot of options for you to take the classes. And I encourage you though to come and see it live. Cause I think, I think we, I personally get so much more out of it when I have a live instructor, but the online classes have worked very well and certainly can get to any of that through A3.

[00:29:24.910] – Josh Eastburn (host)

That’s a fantastic bit of advice. And referring back to what you were saying really about mentorship, I think as technology people, one of our, let’s call it points of pride, is collecting war wounds, right? The long tech support call, the late night, the weekends, right? Where we brutally earned this knowledge, right? And we hold that pretty precious. But seeking out that knowledge through one-on-one mentorship, through education, is also a valid path, right? And complementary in a lot of ways. Yeah, I think that’s a great note to end on. I hope our listeners will take advantage of that and look forward to seeing you this year.

[00:30:01.650] – David L. Dechow

Absolutely. Same here, Josh, and I really appreciate you having me on and thoroughly enjoyed it. Great to be with you.

[00:30:07.810] – Josh Eastburn (host)

Same here. Thank you to David and to Motion AI for kicking off the year for us. Check the show notes for information on how to sign up for his live training at this year’s Automate Show in Chicago. For MVPro Media, I’m Josh Eastburn, wishing you a blessed 2026. Be well.