SDS 654: Mike Wimmer: The 14-Year-Old A.I. Entrepreneur

This is episode number 654 with Mike Wimmer. 

00:19

Today I’m joined by Mike Wimmer, the 14-year-old sensation, who has already completed a computer science degree, and he did it with a perfect 4.0 grade point average. So, yeah, he’s 14. You heard that right. Now that he’s done with his formal education, the young teenager is focusing his attention on his tech companies and his socially impactful AI projects. Let’s jump right into my conversation with Mike so you can hear all about it from him.

00:47

Mike Wimmer, welcome to the SuperDataScience podcast. It’s awesome to have you here. I’ve heard so much about you. I can’t believe I get to meet you in person. How you doing today, man? 

Mike Wimmer: 00:56

I’m doing good. Thank you so much for having me on the podcast. It’s great to be here. 

Jon Krohn: 01:00

Yeah. Where are you calling in from today, Mike? 

Mike Wimmer: 01:02

Salisbury, North Carolina. So about an hour north of Charlotte. 

Jon Krohn: 01:05

Nice. Pretty pleasant winters down there. 

Mike Wimmer: 01:09

Yeah, we get, I mean, sometimes we get pretty low. It gets cold, but… 

Jon Krohn: 01:14

It gets chillier. Yeah. 

Mike Wimmer: 01:15

Yeah. It gets chilly. Very, maybe one or two days of snow, but that’s about the extent of it. 

Jon Krohn: 01:22

Sounds great. So I know you through Kate Strachnyi, who’s been on the SuperDataScience podcast three times. Most recently in episode number 651. That was just a couple of weeks ago. And then we alsothrough Christina Stathopoulos. Sowe had a great episode with her number 603. I got to meet her in person here in New York for filming that episode. And yeah, then actually, you know, had a great rest of the day with her in New York. Went out for lunch and then got to meet her husband for dinner on another day. It was really fun to get to know her. So you’ve also met with both of them, Kate and Christina in real life, right? 

Mike Wimmer: 02:02

Yes, I have. I actually met with both of them on the same trip to New York City as well. That was great. I mean, of course we can meet virtually, but meeting in person is not, it’s just a totally different experience. 

Jon Krohn: 02:14

Yeah. It was much more of a connection for sure. 

Mike Wimmer: 02:17

I [inaudible 00:02:19] with Christina, cuz we went to Jacob’s Pickles. 

Jon Krohn: 02:21

That’s where she took me too. Oh man, yeah, that’s exactly, that’s where I went for dinner. Yeah.

Mike Wimmer: 02:28

Awesome. Best place in New York.

Jon Krohn: 02:31

Yeah, it was great. Nice. So Mikein December you completed your undergraduate degree in computer science at Carolina University, which you know, in and of itself to our listeners who aren’t already familiar with you, that might not sound like the most incredible feat, although, you know, finishing a degree in computer science is great at any age. But Mike, how old are you? 

Mike Wimmer: 02:55

14. 

Jon Krohn: 02:57 

So obviously, that’s incredible. And so to have attained something like a degree at 14 years old, you obviously put a lot of focused work in and no doubt you have a rare intellectual capacity. But is there anything that you can share with our listenersthat they can actually implement themselves as to how they could be learning more efficiently? 

Mike Wimmer: 03:22

Sure. That, that’s a good question. To be honest, one of the biggest things that I always did in school was making sure I stayed organized, making sure I had everything together cuz I was sticking, at many times, 10 classes at one semester. So being able to do that, 

Jon Krohn: 03:40

Wow. 

Mike Wimmer: 03:41

I had to stay organized as to where exactly and what I was doing in every class. And to be honest, I didn’t study a whole lot. I just realized that at an early age, I was a type of learner where it was more of hands-on. And for example, trying to learn a subject it’s less about learning the theory of it instead of how I can relate to it, is where am I gonna use this in life? Where can I, what can I do with this? And if I get that example, I instantly understand it and have it and can relate it to what I’m doing. 

Jon Krohn: 04:16

That makes a lot of sense to me. And I think I learn the same way and I like to teach in the same way as well. I like to get people hands-on as soon as possible.

Mike Wimmer: 04:24

Right, right. 

Jon Krohn: 04:26

For sure. Cool. Well, so then I know that you have a big interest in AI and we’re gonna get into that later on in the show, but was it because of your interest in AI that you studied computer science? 

Mike Wimmer: 04:39

Yeah, well it was interest in technology and AI as a whole, I would say in general. And when I was, began teaching myself, cuz I taught myself everything I know as far as technology. I love being able to delve into many different aspects of technology. For one day I could build an AI system the next day I can build a mobile app or integrate with IOT devices, build a robot, all of these different things that I can learn. And it’s endless. 

Jon Krohn: 05:10

Right. 

Mike Wimmer: 05:10

So with that in mind, that’s why I chose a CS degree because I really wanted to ensure that I could, you know, instead of having to make the hard decision of focusing on one specific area, I could still remain where I can go delve back into each of those areas. 

Jon Krohn: 05:27

Nice. So that makes a lot of sense to me. You don’t, with that kind of approach, so say if you’ve done a data science degree instead it’s like a counterpoint, then you’re really focusing in on AI models, data cleaning, that kind of thing. But you’re not developing the kind of broader skillset that a computer science degree gives you, where you can actually be bringing your applications to life, 

Mike Wimmer: 05:48

Right. 

Jon Krohn: 05:48

Like you said, IOT applications or mobile applications or browser-based applications or whatever. 

Mike Wimmer: 05:53

Right. 

Jon Krohn: 05:53

That kind of thing you do learn to do in a computer science degree. So in a way, it allows you to dip your toe into the water of AI a bit during the degree, but simultaneously have a way of realizing those AI applications in real life. 

Mike Wimmer: 06:07

Exactly. And kind of adding to that, I think many people have really called me a great integrator is what they’ve called me, where I can take skills and knowledge I’ve gained from different experiences and projects I’ve done in my lifetime, you know, from what I’m just playing around for fun, for example. And just be able to integrate them together in a way that’s never been thought of before. And one way that I always illustrate that to other people is there was actually a surprise article written about me and from a special forces media outlet that called me the real Tony Stark. And of course, I was honored to have this, this name that moniker has stuck with me because when people ask me like, how does your mind work? I say, well, when you watch Tony Stark and you see him with all his screens and dragging different things together to build Iron Man suits and such, that’s how my mind works. I can drag different things from here and here, data science and software engineering and UI UX and graphic design and bring them together into one unified thing. So that was always an example that I always used to show other people, this is how my mind works. 

Jon Krohn: 07:17

Cool. Yeah, and you’ve got, actually, if people are watching the YouTube version, so most of our listeners are listening in an audio-only format and they’re missing out on all of the displays that you’ve got in behind you. So yeah. So are any of those touch screens? 

Mike Wimmer: 07:32

These are, these are not touchscreens. Mainly mechanical keyboard and mouse. Buttouch screen in the future maybe, that’s the next step. 

Jon Krohn: 07:41

Yeah, no doubt it’s coming. You’ll just be like grabbing different software libraries, different functions and just dragging them by hand and slamming them together. That sounds like fun. 

Mike Wimmer: 07:51

Maybe AR, maybe we can do that AR. 

Jon Krohn: 07:53

Yeah, that sounds great. So yeah, so what initially sparked your interest in AI in the first place? Is that kind of something that kind of, as long as you can remember, you’ve been fascinated by it? Or were there particular events that inspired your interest in it? 

Mike Wimmer: 08:10

You know, I think there was one particular event that I can think of that really sparked my interest in AI. And we were, I was with my parents going down the road in the backseat and we’re driving down the interstate and we pull up beside this Tesla on the interstate and the Tesla was on autopilot and I was just completely mesmerized by the fact that it didn’t hit the car in front of it and the car behind. It didn’t just stop in the middle of the road, it was driving perfectly in the middle of the two lines. Even the coolest part was the guy that was driving was completely out cold sleep. So that was like 

Jon Krohn: 08:45

Oh my goodness. 

Mike Wimmer: 08:45

That was one of the coolest things I saw. How does it, how does it do that? Well, how does it not hit that car in front of it? And that, that’s something that sparked my interest in AI as to see how did that thing work. And immediately when I got home, I began trying to research, well, trying to answer those questions, how does this thing work? And in doing so, I said like, Jack going back to being hands-on, I said, the best way to learn how this thing works is to build one yourself. So I took an RC Corvette and I had gutted it out, put computer chips in it, ultrasonic sensors on the front and the sides and the back. And I had basically made it work where it would avoid obstacles, it would drive between two walls, like Lane Keep I had just seen with the Tesla, and it would drive right smack dab in the middle just like the Tesla did. 

Jon Krohn: 09:38

Wow. 

Mike Wimmer: 09:38

And that was something, I was like, “Hey, I built something just like that Tesla”

Jon Krohn: 09:43

So you’re not old enough to drive. And so you were like, well, “I’m just gonna make a car that can drive me around anyway”. 

Mike Wimmer: 09:52

Exactly. So after that I said, well then if it drives in, this is an interstate, what if it drives down street roads? How does it know a stop sign? How does it know a traffic light? How does it understand those things? So that’s where I went into the object detection and neural network stage of AI. And that’s where I developed, continuing with my car guy theme, I developed an object detection system for my Hot Wheels cars, just for fun. And that was where every car was red, I was wearing a red shirt all just to try to basically confuse the model as much as I could. And after posting that video on LinkedIn, it went viral and there were thousands of people commenting about how well it worked and they got the complexities of things. And from then on, I really knew I wanted to delve deeper into AI and keep being on the cutting edge of it. And to be honest, you know, I posted this stuff on LinkedIn as far as that goes. I wasn’t expecting it to go viral. I was just nine years old having something fun to do on Saturday and said, “Hey, this is cool. Why don’t I post it?” And that was just all it was. But it was a fun experience to do for younger me, but since then it sparked my interest in AI and want to keep moving forward and seeing what the next generation of it is. 

Jon Krohn: 11:13

Super cool. So you obviously have that early interest about five years ago and things like, I guess convolutional neural networks at the time were probably what you’re using for that object recognition. Are there any particular AI applications that captivate you today?

Mike Wimmer: 11:27

In particular, I still think AI applications, I think one of the biggest right now is still that I keep going back to that autonomous car Tesla thing, if you will ask. That’s one of my biggest, every sci-fi movie, every sci-fi book, everything that you see, it’s all about, “oh well the car drives itself”, the car does this or that. I want to get to that. Sure the Tesla is extremely close to that, but I want to get to where even as far as the law making side of it, where… 

Jon Krohn: 11:56

Right. 

Mike Wimmer: 11:56

We have the car not having, you don’t have to even be attentive. We wanna make sure we can get to that point and everyone’s safe and hopefully just make the world safer. And it’s things like that, that impact people and help people, that’s the examples that I like to go back to.

Jon Krohn: 12:11

Nice. And so I learned just before we started recording that you actually have a really exciting project, 

Mike Wimmer: 12:18

I do. 

Jon Krohn: 12:18

That you might wanna tell us about on air, reveal it for the first time here on the SuperDataScience Podcast. 

Mike Wimmer: 12:24

Absolutely. So I am excited of course, to be working on a environmental reef conservation project that’s focused all around the invasive lionfish. So lionfish were native originally in the Pacific Ocean and they were brought into the Atlantic Ocean in the 1980s, like exotic pets in aquariums and such. And like some other species lionfish have gotten into the local waters and they’re spread anywhere from Brazil down up to Canada and even over into the Mediterranean. So this is becoming a huge issue because these lionfish have no natural predators over here, unlike in the Pacific. And they’re eating the small reef fish at super-fast rate before they even reach maturity. And they’re be eating, my lionfish, the reefs are dying and they’re moving elsewhere. The other issue with this is they don’t bite the line and they very, very seldom go into a fishing pot. So the only main way to capture them is to spear them and divers go down, you know, of course only 130 feet to be able to spear them. The issue is lionfish haven’t been seen anywhere from 130 feet to thousand of feet down. 

Jon Krohn: 13:38

Wow. 

Mike Wimmer: 13:38

One of the very few fish that can do that. So most of their environment is, we can’t dive that far. So teaming up with a team in Bermuda, who has a ROV or remotely operated vehicle, has began to spear the lionfish using the vehicle and capture them. And a pilot drives the ROV from a boat and being able to go much farther than divers can go. The issue with this is that the ROV can spear and hold lots of lionfish and it’s great to use, but it’s extremely difficult to drive cuz you have currents, you have different, the ocean is very, very big challenge as far as driving something. It’s not like,

Jon Krohn: 14:21

Right. You can’t just grab something and pull or, there’s no friction on the ground. Yeah. Floating around. 

Mike Wimmer: 14:28

Exactly. So in order to be able to scale this, where that pilot they’re using has had hundreds and hundreds of hours driving this thing. And so if we’re gonna be able to have multiple pilots and fisheries being able to buy this and use it, they’re not gonna have that training. So to scale this, I’m currently working on to bring AI and data into it to improve these challenges. And in the middle of developing a bespoke system for detecting and targeting lionfish, which I named Alfred, which is autonomous lionfish, real-time edge detection, depopulation. 

Jon Krohn: 15:07

10 out of 10 for that name. Great work. 

Mike Wimmer: 15:10

And using the high res images from the camera, I can scan the ocean floor and identify a lionfish with over 99% accuracy with a neural network that I had built and trained. And it’s gonna greatly reduce the chances of even missing a lionfish because they have this way of just hiding in plain sight where they would just sit there at the bottom and inside of reef and you can’t even see them if you can just pass right over them. So being able to have the AI scan them like that is gonna be super easy to, a lot easier for the pilot. And the next thing is of course to make the ROV easier to drive. So using those same camera feeds and the data sensors aboard the system, Alfred will also actually lock on and drive the ROV within the actual ballistic zone of the spear. Exactly like a fighter jet where when you see a fighter jet lock on it, it’ll drive, that’s exactly the way that’s exact, it’s the same thing. It’s exactly way it works, except got a spear instead of a missile.

Jon Krohn: 16:14

Cool. So, so the spear like flies outta the vehicle and it’s got like a string on it so you can like retract it or something. 

Mike Wimmer: 16:21

It’s actually, it’s not on track system. So it’s almost like a catapult-type system is how it works. So it doesn’t exact fly completely out of the vehicle. It’s still remains in there. It can be refired every 10 seconds is how that works. 

Jon Krohn: 16:37

Cool. 

Mike Wimmer: 16:38

So you can fire it, bring it back in because not only are these fish harmful to the ocean, but they’re also a great food source. So being able to harvest them because, you know, normal restaurants and such can’t keep getting them, it’s a more of a special type deal. So being able to keep it as a, you know, continuous food source as well. So there’s, it’s performed great in all testing to date so far. And I’m looking forward to the actual deep water testing coming in the next few months. 

Jon Krohn: 17:07

That’s really exciting, Mike. 

Mike Wimmer: 17:09

I’m looking forward to actually using data on the robot to be able to understand like the habits and the behaviors of lionfish and where do we see more lionfish at during these particular times and such. And also maybe even start mapping the ocean floor using SLAM and gathering data as far as that goes to see stuff like that. So it’s, there’s a lot coming down the road with it. I’m super excited about it.

Jon Krohn: 17:34

So how does an opportunity like this come up? You know, if you were at a university or something, you know, I could see like somebody reaching out to you or like, how does that, so people just kind of know who you are and they say, “Hey, I’ve got this big lionfish problem real Tony Stark, we need your help on this problem. The world is in danger.” Or was this like an idea that came out of your own, you were like, you read about an invasive line fish species and you were like, there’s gotta be a solution. We can use AI here. 

Mike Wimmer: 18:03

Actually it’s really from podcast listeners really. That’s where I get a lot of my, a lot of my contacts is through that. There was the company in Bermuda, they were listening to podcasts and I was on there and they said, well maybe he can help us with the lionfish problem. And they contacted me and it’s, you know, they were like, well it’s, it’s gonna be a long shot, but he might respond. And it was I, and then when I responded, they were like, “Whoa, you actually responded to me. Wow.” It was one of the, you know, for me being able to, I’ve getting, you know, requests from many people daily about, “Hey, can you work on this or can you work on this?” And I really picked the ones that I think is gonna be most impactful to the world because I don’t have unlimited time, nobody does. So being able to have something that can impact the world in the biggest way is what I want to work on and this is what I feel can be one of those projects. 

Jon Krohn: 19:04

It sounds great. I’m so glad that you’re not like working on financial market engineering or getting people to like click on ads more. This is, yeah, this is a really great use, 

Mike Wimmer: 19:15

Awesome. 

Jon Krohn: 19:15

Of your yeah, your tremendous capacity, your ability to integratelike no other. Awesome Mike, so in addition to that really exciting project with the lionfish, you also have two companies that you founded. So there’s Next Era Innovations and Reflect Social. So what are these two companies and how are data or AI involved in them, if at all? 

Mike Wimmer: 19:41

Absolutely. So Next Era Innovations is my first company that I actually founded at age seven. And I originally began with Next Era Innovations doing robotic applications for the Nao robot. And Next Era also acts as my, I call it my parent company for everything that I do. All of my private and military work all go through Next Era Innovations and every idea that I have spins off from Next Era. So if I come with a new idea, it’ll originally remain in Next Era and spin-off if it actually goes somewhere. So I think the first one of those spinoffs is Reflect Social and Reflect Social is a software as a service that’s focused on integrating consumer IOT devices together into one easy to use app. And this way users don’t have to have those 15 different apps or 15 different devices and they could just use one app that does everything.

20:41

And Reflect, also integrates those devices together in order to build things that within different constraints of the device ecosystem. For example, we have Apple and Google and Samsung and they don’t talk to each other. Well, I’m the translator. I speak all the different languages. I talk to them all. And one example of this, of Reflect that I talk about a lot is the, in our household we took our video doorbell and I built an AI facial recognition system to detect our family members that would come in and it automatically scans their face and then unlocks the door with a smart door lock. It’s a, many people, it’s just two devices and an AI system, but no one’s ever really done it before. And it’s so simple things that you can connect together is that makes this life easier. And as far as data goes with Reflect, there is a ton of data that Reflect uses and utilizes every day from, there’s a thousand different devices and they all have different data streams and how they talk differently. 

21:45

And one example of a data thing that I use in our home is we have a fountain and when the wind blows at a certain speed, the water blows out of the fountain and the pump burns up and then that’s like a 500 dollar pump. So in order to solve this, I says we can use the wind data and being able to keep continually gather the wind data, it’s above a certain speed that a user can set. It cuts off the pump and keeps checking. Or if it starts raining, it cuts off the pump. Just general simple things that simplify the lives of everybody or even like our outdoor lighting system, we have a timer every time the power goes off, the timer goes off, it’s completely, the timing is way off. Or say over time sunrise and sunset changes and it comes on at the completely wrong times. So in order to fix that, I also use another just simple smart plug and use a sunrise and sunset data to say, for example, 15 minutes before sunset, have the lights come on and then come back off. Just simple things that make life easier. 

Jon Krohn: 22:54

Makes a lot of sense. So Reflect Social. A lot of the projects that roll up into Reflect Social, involve passing data through different systems. They might even be differentcompletely different operating systems like the Apple iOS and the Google Android system. And so you figure out ways of integrating different components together to solve new problems that haven’t been solved before. 

Mike Wimmer: 23:16

Exactly. And to be honest, I will say the launch of Reflex Social has been delayed a few times. One of which, or many of which was for the high interest in acquisition. Although the buyer’s intent was to shelve it and that didn’t really coincide with my desire to help people. I of course since rejected that offer because if I wanna build things we put on the shelf, I might as well go build a Lego. So instead of doing that, I will just continue doing Reflect Social. And since it’s beta test, I’m now actually currently working on to revamp the interface and make it codeless and easier to use. Cuz I want to make sure I impact most people possible. And as far as easy to use, I always say if my grandmother can use it, everybody can use it. That’s my metric I always use. Right. Make sure that everybody can use it. 

Jon Krohn: 24:08

Nice. You’re really good at spinning out the analogies and you’ve got really humorous ways of making points. I love it, Mike. Nice. So what are some kinds of software tools? So you just talked about all of these Reflect Social projects. We have a great sense of the kind of work that you do. What kinds of software tools do you use regularly? Like, you know, what are your favorite programming languages or you know, these kinds of questions? Yeah. 

Mike Wimmer: 24:39

And currently, I use Linux as my main development operating system. That’s kind of what’s what I’ve been using mainly. And then Python is my main programming language right now. I know many other languages, C++, C, Java, JavaScript, Swift, html, css, r and many others. But I always really come back to Python because of that versatility and that ability to do anything. You can build a game one day, the next day you can build AI system all in the same language. You don’t have to learn something different. Not that I’m not learning different, I just like, you know, same, same system. Right.

Jon Krohn: 25:17

Yeah, it’s interesting. Python is often described as like a glue programming language. 

Mike Wimmer: 25:21

Yes. 

Jon Krohn: 25:22

And so that kind of in an intuitive way, it makes a lot of sense to me that with all of the kinds of gluing that you’re doing with Reflect Social, that yeah, Python seems to be a perfect fit.

Mike Wimmer: 25:33

Of course. Of course, I use for the actual mainstream app stacks and things like that for app development as well. And as far as actual like hardware, I actually just got a big workstation from Lambda with the three dual-boot TPUs in it. 

Jon Krohn: 25:52

I saw you post that on LinkedIn. Yeah. That’s pretty cool. 

Mike Wimmer: 25:55

Yeah. That’s cool. 3 3090s I believe 500 gigabytes of RAM. 

Jon Krohn: 26:02

Wow. 

Mike Wimmer: 26:02

So that’s, any AI model I need is gonna be trained on that from now on. I’ll say that. 

Jon Krohn: 26:09

Nice. And then you you mentioned a stack there, you used an acronym there that maybe some of our listeners don’t know. So you said the MERN Stack. Do you wanna tell us about that production stack that you use? 

Mike Wimmer: 26:21

Yeah, so it’s a MERN stack. It’s MongoDB, Node.js, Express and React or React and Express, the other way, whatever. 

26:30

 Basically it’s a way of developing responsive web applications to be able to use on any platform and be able to just, you know, work with or other, no matter what browser, what platform it just works and what Windows sizes, all that good, happy, fun stuff. Have native databases and back ends and front ends and be able to talk to each other. 

Jon Krohn: 26:52

Yeah. So MongoDB is the database, Node is the back end, React is the flexible front end that works really nicely across all kinds of different situations. And then the only one there is Express, I don’t really know, Express very well. What does that do? 

Mike Wimmer: 27:06

Express is just like how they talk to each other more or less. It’s more of just how they communicate. That’s, that’s basically it. I guess it’s just another acronym they put in there to make it four letters. I mean… 

Jon Krohn: 27:18

Yeah, they didn’t want MERN without the E. Nice. All right. That’s super cool Mike, thanks for telling us about the MERN stack and about the tools that you regularly use. I’m sure our data science listeners will be happy to hear that you’re using Python. Cause if that’s your choice, then it seems like we’re going to have lots of young people continuing to be using Python and all the Python skills we’ve been developing over the years will still be…

Mike Wimmer: 27:45

There is one other tool that I use. I think it’s kind of a different tool that many people would think about, but like I said previously about school, organization is super key. And when I’m working on, you know, two different companies, I’m working on military projects, working on this lionfish project, and many other of my pet projects all at the same time, I gotta keep my tasks together. So in order to do that, I actually keep a Trello board of every single project that I work on to keep track of everything that’s been completed. What do I gotta do next? What do I gotta do here or there to make sure I always just stay on track? 

Jon Krohn: 28:24

Nice. That’s a great tip, Mike. Thank you. And yeah, something that I certainly support. I use Trello for managing the projects of my machine learning company as well as in my personal life. It definitely helps me keep everything on the ball. Awesome. So got a kind of a big open-ended question for you here that I’ve been excited to ask you. Sothere are a lot of exciting technological changes that are happening individually at an exponential pace. So data storage is always getting cheaper and cheaper. Compute is getting cheaper and cheaper. The amount of sensors that we have collecting data are becoming rapidly more abundant all over the world. We have more people and devices interconnected than ever before. So people can share ideas in real time through archive papers and GitHub commits, and then machines can also be sharing information over the internet. 

29:24

So technology is advancing at a faster pace all of the time. Every year that passes. We’ve got, I mean like ChatGPT comes out and then all of a sudden everyone’s like, “Oh my goodness, how can we be integrating functionality like this into our platform?” Or “What does this mean for other kinds of models that we could be developing, now that we’ve seen that ChatGPT is possible?”. So with these tailwinds of remarkable technological change happening, what excites you about the future or how technology could evolve over the course of your lifetime? 

Mike Wimmer: 30:02

Well, that’s an awesome question by the way. One thing that I, when I think about the future, one thing I always think about is that I was born in 2008 and the iPhone was released in 2007. So with that in mind, I’ve never lived a day without an iPhone or WiFi. Those were things that I’ve always remembered because there’s never been a day without it that I’ve always, I’ve had. So when we look back 20 years, I think that was one of the most landmark moments of technology was that introduction of the iPhone. It was one of the biggest deals of the time. So to be honest, I don’t think it’s a specific technology that I’m looking forward to, more in general, what is gonna be that next landmark advancement? What’s gonna be the next thing, the next big thing like the iPhone where we got it in everybody’s hand now what’s that next thing? And I’m almost excited that I don’t know what it is, but also I’m excited to see, to be able to work towards that and figure out what that is and what everybody’s gonna want in the future. So nothing specific exactly. Just excited to see what it is and if I can work on it.

Jon Krohn: 31:18

Cool. Well then let me twist the question a little bit. So maybe instead of like a specific technological advance, what about maybe how you could envision life changing? Like, so maybe like the aggregation of like socially impactful technologies. Like what would, you know, there’sas you’ve noticed from all of your specific projects, you’re constantly noticing things that could be improved, things that could be automated even when it’s big-scale projects like the lionfish infestation. So yeah. Is there some kind of, yeah, maybe not like any one particular technology that you’re looking forward to, but just like a way that life could be better for all of us on the planet? Do you, like, I assume you’re, you probably have quite an optimistic, a techno-optimistic perspective. 

Mike Wimmer: 32:18

I think there’s, there’s two main things that I would think about is that robots will in the future, make jobs easier. And that’s something that many people are afraid of, where even like we’ve seen with ChatGPT it’s, “Oh, it’s gonna take my job”. No, it’s not, it’s gonna make it easier because does ChatGPT make mistakes? Yes. Or robots gonna make mistakes in the future? Yes. So there always has to be someone, I don’t wanna say a babysitter, but someone watching over it, if you will. That is a tool, it is not an employee. That’s something that I’ve always thought about is, it’s a tool that you can use, not an employee that you hire. And another thing is like cognitive robots help the aging populations and of course like those repetitive tasks and that we’ve already seen being automated in factories with robots and things like that. 

33:10

But one other major thing that I see in the future is where we have IOT devices now, where we have, you know, simple lighting, we have door locks, we have ring cameras, simple things like that. Those will also become robots. So you will have, and we’ve already seen a little bit of that with the iRobot Roomba situation, but even more so in a larger scale, you’re gonna have a robot that does your dishes. You’re gonna have a robot that cooks your dinner, you’re gonna have a robot that folds your clothes. These different things, like we have an IOT ecosystem now, will be that mixed in with robots is what I think. As well as an actual like an avatar, that talks to your life. Where we have some of that now with like your Alexas and Googles. But to any, like I said, to an even more crazier cooler extent I guess you can say, where you can have like a Jarvis from Iron Man, going back to that example, it’s your personal assistant. 

34:10

It knows who you are, it knows exactly what you want and need, all of those things that’s not, it’s more personable if you will. 

Jon Krohn: 34:19

Right. 

34:19

Instead of you talking to, like we do now, we go on our light for, you know, let’s just say for example Phillips U Light and you go to the app and you turn it on. Well, instead of doing that, or you can use Reflect Social. But anyway, instead of doing that, you’ll have this personal assistant that just controls your entire life and you’ll just say, “Hey, I need my, I want, you know, x, y, z to eat today.” And it will automatically talk to the food robot and do that. Or it can even monitor based on smart watches and things, your mood and knows that if you come home from work that day and your’re frustrated that you wanna listen to this music and this lighting and this whatnot, just to, just making life easier and simpler and automating things that wouldn’t always be that.

35:15

Nice. That’s a beautiful vision. And so in that future where we have machines taking on more and more of the labor that we need to be doingand even more and more of the cognitive labor. So you know, we’ve automated quite a few kinds of repetitive mechanical tasks and in the future, more and more cognitive tasks will be automated. So I imagine that people will have more time than ever to be kind of doing whatever they want. So they could be, you know, engaging in leisure time, playing cards with their loved ones, playing sports. That all sounds really nice. But I also like this idea of there being more people like you out there, that are thinking of other challenges that could be solved. And so do you have any ideas as to how we might be able to encourage people to be more inventive with, you know, today people have anybody could learn, you know, like the tools that we talked about today, Linux, Python, the MERN stack, Trello. These are free tools that anybody could be learning how to use and making real-world applications that make life easier for everyone around them. 

Mike Wimmer: 36:32

Right. 

Jon Krohn: 36:35

But so few people do it. So, you know, is there anything we could be doing? How could we be encouraging people to be taking advantage of all of these free educational opportunities and open source tools to also be making a big positive social impact like you? 

Mike Wimmer: 36:53

Sure. I think there’s one big thing that I always come to mind when I think about getting other people interested in it. When I look at myself and that is staying out of the box and thinking, thinking differently. Like for example, you know, it’s not like this is the only way you can use Python. This is the only way you can use MERN. This is the only way you can use Linux. There’s thousands of different ways to do it. It’s more about, you might have a different way that’s not the textbook way like I do. Cause I’ve been self-taught, don’t get funnel into this is the exact way you do it. Cuz if everybody does it the same way, nothing’s gonna come out of it. So with that in mind, I always make sure I keep myself out of the box. That’s why I was self-taught.

37:38

I do things completely differently than some people do, you know, that have been taught some other ways and self-discoveries and things that I’ve done. And you know, I even walked into a, I was doing a presentation at a classroom one time that was for computer science students. I said, I showed some code, I said, now teachers don’t fret when you see this code cuz I was self-taught. I might do it differently than everyone else does. And it’s doing things like that that I think is something to teach to other people. But another thing is do not be afraid of failure because coding and technology is very, how do I wanna put this? It’s gonna tell you when you’re wrong. I mean it, there’s errors, there’s bugs constantly. And I think it’s, don’t be afraid to try and fail.

38:27

Cuz failing is where you learn, failing is where you, failing is where I come up with all of my greatest ideas is when I fail and come up with something new, come up with that different way to do things. That’s something that I think needs to be, when people start getting into technology, they’re gonna get discouraged. Oh, my code doesn’t run right, I can’t do it correctly. No, it’s more, you haven’t learned it yet. It’s what I say. It’s not that you can’t do it, you haven’t learned it. So that’s, that’s some key things that I think is key as far as that is and getting people interested in technology. But it’s also as far as that goes, you know, people also, you shouldn’t be shoved into technology. If you have a desire to go in the technology, do it. But you shouldn’t be. 

39:19

Cuz if you shove them to doing it, then you’re gonna be, you’re not gonna do it well. That’s just like if people say you’re gonna be a doctor, you’re gonna be a lawyer, they’re not gonna be happy with their job. So that’s something that I always keep as far as especially, you know, referring to parents and things like my parents did. They didn’t push me to say, know you’re gonna be this tech CEO or whatever, they said it was more of whatever you wanna be. And they gave me the resource to be able to do that. And that’s something that I think is important. You know, let the child or even adult in that sense be able to do what they want to do. I mean, I would, that’s just what I wanna do. I would come home from school and use, took over my dad’s desk and put my computer beside of his and be able to sit there and stream videos on his computer and try to do the same thing on mine. And that’s what I wanted to do. But some, it’s just not for everyone sometimes. So that’s one other key thing I would say. 

Jon Krohn: 40:21

Nice. That was a really wise perspective, Mike. And I wholeheartedly agree with you. You know, I kind of came from this idea of how can we push people into tech? And your, yeah, I hear your point about, you know, it’s not for everyonebut people who do find it interesting, encourage them, give them the resources and that includes, you know, the resource of time. 

Mike Wimmer: 40:41

Exactly. 

Jon Krohn: 40:41

To be pursuing their interests. That’s a really wise answer. Thanks Mike. Alright, and then, so this isn’t a question I ask guests very often and I don’t know why I thought it would be a particularly interesting one to ask you, given that you’re only 14 years old, butwhen you retire Mike, what are you hoping to be able to look back on? 

Mike Wimmer: 41:05

Well, I will say one thing. I probably never retire because this is my passion because I’ve never worked. So I never really started working cuz I don’t feel like, well I’ll say this, I don’t feel like I’ve worked a day in my life with what I’ve done. I love what I’m doing. So yeah, retiring, I may never, I’ll always have that next idea, next thing. But when I legally retire, I guess you can say I’ll put it that way, my entrepreneurial goal is to build technology that enables people to live better lives. And I hope that in my entrepreneurial endeavors, whether it be what I have going on now or the 50 ideas later, that I’m able to help to better of the lives of others and the environment through all these different advances in technology and in general just hopefully make a difference in the world. And another key thing I think of is that it will take a diverse team to be able to make this noticeable difference in the world. And I welcome anyone with this same mindset to reach out to me and I will make my contacts available and cuz I want to impact the world as much as possible and see if anybody else would like to as well. 

Jon Krohn: 42:19

Nice. Yeah, that is very generous of you, Mike. So yeah, how should people follow you or reach out to you after the show?

Mike Wimmer: 42:27

So you can contact me on my LinkedIn as well as my website nexterainnovations.com. 

Jon Krohn: 42:34

Nice. All right. And then I just kind of had the right flow there, usually my pen ultimate question is, do you have a book recommendation? But you kind of, you just said, oh yeah, you know, [inaudible 00:42:44] people to get in touch. So I gave you my ultimate question pen ultimately. Sothen my very final one here is Mike, do you have a book recommendation for us? 

Mike Wimmer: 42:52

I do here, I have actually here, I have it for you. Probably is just the Elon Musk book. I’ve always taken it out for inspiration and things just because to be honest, he’s a big out-of-the-box thinker and that’s one of the reasons that I admire him more than anything. It’s not the money, it’s not the fame, it’s the out-of-the-box thinking. And these other two here were actually AI books recommended by both of our friends, Christina. So we got AI 2041 and AI Superpowers and love just getting these, getting these different perspectives on what other people think the future of AI is and what we can do to see if we can get to there. 

Jon Krohn: 43:40

Super cool. Yeah, those AI books will be easy to find. That Elon Musk biography there, who’s the author of that? 

Mike Wimmer: 43:47

Ashlee Vance. That’s who the author is. 

Jon Krohn: 43:48

Ashlee Vance. Yeah, I think that’s the most famous one. Cool. Alright Mike, well thank you so much for taking the time out of your busy well organized daywith all of your great socially impactful projects. It’s been such an honor to meet you, Mike, and it’s been such a great episode. Thank you for coming on and maybe we can have you on again sometime in the future to let us so we can check in and hear about all the amazing innovations that you’ve been working on since.

Mike Wimmer: 44:14

Absolutely. Thank you so much for having me on and all the listeners there, you can follow me wherever you like. 

Jon Krohn: 44:20

Sounds great, Mike. Catch you again soon. Bye. What an inspiring young gentleman Mike is and his ability to communicate confidently and effectively. Remarkable, I mean, at any age, I had a barrel of laughs filming with him and yeah, I really can’t wait to have him on again in the future and hear about all that he’s been up to. 

44:40

In this episode, the 14-year old phenom filled us in on how he got started with AI by using convolutional neural networks for object recognition, how he’s now using AI to detect and spear invasive lionfish with remote-operated vehicles that the MERN software stack for building applications consists of MongoDB, Express, React and Node. And he shared his vision for an automated future with tons of people inspired to create socially impactful solutions with tech if they are innately interested in doing so, just like Mike himself. All right, that’s it for this inspiring episode with Mike Wimmer. Until next time, keep on rocking it out there folks. And I’m looking forward to enjoying another round of the SuperDataScience Podcast with you very soon.