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83: AIoT and the Future of Business with Justin Grammens of Lab651

Published June 22, 2021
Run time: 00:52:56
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Businesses who aren’t exploring smart technologies will eventually go the way of the dinosaurs. Justin Grammens is an expert on IoT, AI, and where the two meet. He joins the show to chat about how and why businesses should start exploring these emerging technologies and where they’re making the most impact.

In this episode, you will learn:

  • How Conversations on Applied AI was born and how it’s evolving
  • Why fear exists around artificial intelligence and how there’s always something for humans to do next
  • What AIoT is and where it’s making an impact for businesses
  • How businesses can bring more value to the market and get ahead of the curve with AIoT
  • Why companies should start small with applying smart technologies
  • How to determine if product ideas are “good or bad”

This episode is brought to you by The Jed Mahonis Group, where we make sense of mobile app development with our non-technical approach to building custom mobile software solutions. Learn more at https://jmg.mn.

Recorded June 15, 2021 | Edited by Jordan Daoust | Produced by Jenny Karkowski

Show Links

JustinGrammens.com | http://justingrammens.com/

Justin Grammens on LinkedIn | https://www.linkedin.com/in/justingrammens/

Lab651 | https://lab651.com/

Emerging Technologies North | https://www.emtechnorth.org/

Conversations on Applied AI Podcast | https://podcast.appliedai.mn/

The War on Normal People by Andrew Yang | https://www.amazon.com/War-Normal-People-Disappearing-Universal/dp/0316414247

21 Lessons for the 21st Century by Yuval Noah Harari | https://www.amazon.com/Lessons-21st-Century-Yuval-Harari/dp/0525512179

ThingCloudApp | https://lab651.com/thingcloudapp/

The Innovator’s Dilemma by Clayton Christensen | https://www.amazon.com/Innovators-Dilemma-Revolutionary-Change-Business/dp/0062060244

TimBornholdt.com | https://timbornholdt.com/

JMG Careers Page | https://jmg.mn/careers

Email careers@jmg.mn

Connect with Tim Bornholdt on LinkedIn | https://www.linkedin.com/in/timbornholdt/

Chat with The Jed Mahonis Group about your app dev questions | https://jmg.mn

Episode Transcript:

Tim Bornholdt 0:00
Welcome to Constant Variables, a podcast where we take a non technical look at building and growing digital products. I'm Tim Bornholdt. Let's get nerdy.

A quick note before jumping into this week's episode. We at The Jed Mahonis Group have a lot of fun projects coming in the door. And as a result, we're looking to expand our team by bringing on some iOS and Android developers. We place an emphasis on hiring for fit as opposed to skills. Skills are something that can be taught and fostered through mentorship and experience where fit on the other hand, it's harder to define, but we've outlined some of the traits we're looking for on our careers page at JMG.mn/careers. So whether you have one year of experience, or 20 years of experience, if it sounds interesting to you, you would be interesting to us. So please reach out at careers@jmg.mn. We'll put that email address and a link to our careers page in the show notes as well.

Today, we are chatting with Justin Grammens, co founder of several innovative technology companies, including Lab651, Emerging Technologies North, Recursive Awesome, which is one of my favorite company names ever, and Captivation. Justin is also an adjunct professor at the University of St. Thomas and host of the Conversations on Applied AI podcast. Without further ado, here is my interview with Justin Grammens.

Justin, welcome to the show.

Justin Grammens 1:41
Thanks for having me on, Tim.

Tim Bornholdt 1:42
I'm really excited to have you. We were kind of talking before the show, it's nice to have a fellow podcaster on. Do you find yourself enjoying this side of the mic better? Or the the host side of the mic better?

Justin Grammens 1:55
Well, you know, it's tough. I think with regards to better, that can be a little bit of a relative term, but I think it's more or less like, you know, what do you find interesting, and I think sitting on the other side, the side that you're on, you know, you get a chance to ingest. You get a chance to sort of take in a lot of what people are saying in the people that you're interviewing. So I like that component. I really love just learning. You know, I tell people, I'm kind of a lifelong learner, I believe. And so the whole reason I really was interested in podcasting was sort of born out of that idea. Hey, how could I find people that are a lot smarter than me that have been doing a lot of really cool stuff in technology? And how could I listen and learn from them? So I really enjoy that aspect. I obviously, you know, sitting on the side that I'm on right now being interviewed, I love to share, right? So I'm sort of also a teacher at heart. And I think throughout my career, I've always tried to mentor people, you know. I teach classes at the University of St. Thomas. And I've always enjoyed sort of sharing what I know. So again, like I say, it's probably just a different perspective, just two sides of the same coin. But yeah, looking forward to sort of being on this side and sharing whatever we're going to talk about today, whatever we want to discuss.

Tim Bornholdt 3:04
Yeah, definitely, I find it exactly the same way where it's really nice to be able to have a conversation with somebody that is an expert in an area that you're not as versed in, but you can kind of pull out those questions and kind of play the straight man, so to speak, if we're talking comedy terms, where you can kind of just pull out those nuggets of information that you know you're interested in. And usually, if you're interested in something, then you find that there's a lot of people also that are kind of interested in how that stuff works.

Justin Grammens 3:33
Yeah, absolutely. I mean, some of the things that I've done in my career that I've started a number of different user groups around town, and I tell people that you know, if you're in your basement hacking away on something, some piece of code or some piece of new technology, likely there's somebody else down the street that's wanting to do the same thing. And so you know, if you can raise up the flag, you know, raise the flag up the flagpole and say, Hey, let's get a community together around this. I've found it to be very successful and very rewarding. And I've done that multiple times. And it's been a lot of fun.

Tim Bornholdt 4:01
I love it. Just a quick recap to for my audience too. Talk a little bit about your show and the kinds of topics that you do engage about on that show.

Justin Grammens 4:10
Sure. Yeah. It's called Conversations on Applied AI. And so the focus really is around number one artificial intelligence, of course. And that is such a broad term, it can be everything from machine learning, deep learning. We have a person that I've been speaking with really about cognitive computing, voice activation, you know, things like that, digital assistants, smart speakers, all that type of stuff. So really sort of broad topic around artificial intelligence. I really like the applied aspect of it. So not so much theoretical and like that aspect. I'm really trying to bring together a community of people that talk about applications, how we can apply this technology in all sorts of wide areas in everything from farming to smart cars to, you know, home to industrial applications. There's just such a broad area in which we can apply artificial intelligence.

And then the last piece was the conversational aspect of it, right. So I really like to have conversations and sort of get a chance to sort of know the person you're talking to. So oftentimes we talk about, you know, this technology, but, you know, vast majority of the conversation can veer off into other things that they enjoy doing that's completely outside of the tech round.

So yeah, it's called Conversations on Applied AI. It really came out of the applied artificial intelligence group that myself and a couple other people started here in the Twin Cities, right before the pandemic started. And so we've been having these monthly meetings, and after we've been doing these monthly meetings, I'm always like, Well, geez, you know, how can we do something a little more regular. So this podcast was a way for me to sort of keep the momentum going. And, you know, it still has yet to be announced. But we are planning on having a conference this fall, too. So, really excited to announce that, you know, once we can sort of get our ducks in a row, but yeah, that's sort of a little bit of background of the show. And it all sort of falls under this nonprofit that I'm a part of called Emerging Technologies North. So you can go to EMTechNorth.org. And you can find out about, you know, what we're doing around all areas of emerging technologies. And I'm just focused specifically on artificial intelligence. But the whole idea of this nonprofit is to really sort of further all sorts of emerging technologies here up in the upper Midwest, up in the north.

Tim Bornholdt 6:30
That's so cool. The applied part of your podcast and what you do is the part that really speaks to me, because I know probably not a lot of people listening to this show have computer science degrees, maybe they do, I honestly, you can't tell what podcast but that's part of the fun. But me personally, when I was going through my computer science classes, the whole time they teach you theory and the algorithms and it's high level stuff of just how all of the things work, and how they can kind of be put together. But as somebody that likes to actually tinker and get down to brass tacks and use these technologies to actually, you know, improve people's lives and give value to businesses and whatever, just actually doing things with it, I find is so much more fun than talking. It's not to dog on people that like, you know, there's people that really love talking about, like designing programming languages, and all the nuance that goes into that kind of a thing. And it's all just purely theoretical, and some people get a kick out of that. But that's why I've really enjoyed following your group, and I've attended some of your events and seeing how the different people that you bring in bring so much interesting, they bring such an interesting perspective to how you can apply some of these things like artificial intelligence, for example, just to the real world. Because it's something that it's cool in theory, but like, how do you actually go out and then you know, do something with it, and, again, bring value to people's lives?

Justin Grammens 7:54
Right, right. Yeah, I mean, the use of technology, is I mean, the technology itself is not really what's fascinating and cool. It's the application of it. And, you know, you can sort of like look back over history over the past 100 years of all new inventions and new things that have been created. But you know, if you read a patent, for example, I'm just kind of going off the cuff here. But if you like, read a patent and say, Oh, wow, okay, this is kind of an interesting piece of things. It's not the patent itself that is really unique, I believe, or that is a game changer. It's the application of it, right? It's actually putting it into practice, and putting it into the marketplace and seeing if it has value. And some things have value. Some things don't honestly, that's just the way that things work. But I think when it comes to technology, and especially I believe artificial intelligence, machine learning, deep learning, this whole sort of realm, it really is now starting to have a huge significant impact, you know. The whole term came out really in the 60s. And it was this idea of sort of having computers think and behave like humans. And while that's cool and interesting, there's been a number of false starts. There's been a number of things a number different ways that the technology has sort of evolved. And then it's sort of said, Well, geez, it's not as easy as we thought. And I think now we'll release over the past, you know, 8 to 10 years, we're having this convergence of everything from hardware, to new algorithms, to honestly enough data, to be able to now really have huge impact in our life. And of course, the internet played a huge part in that aspect. But it's an exciting time to be in this space.

Tim Bornholdt 9:27
It's hard for me to, we've got like a script of bullet points and stuff like that. And sometimes Jenny gets upset when I go off the rails, but I'm doing it anyway. With artificial intelligence, I since I have an expert on, you know, we might as well broach the subject, you know. So many people are afraid of AI and afraid of, you know, potential applications of it. And I mean, you could argue that all technologies that we have made available to us can be used, you know, for quote unquote, good and quote unquote, evil. But I think there's so many people that have this fear that we're going to have Skynet and you know, someone's going to come back in time to save Sarah Connor or whatever, you know. There's so much fear around AI. How do you approach that subject of like, people being afraid of AI and people being afraid of how you can, you know, have computers uprise and do all that kind of crazy stuff. Do you see that as like a realistic possibility? Or is that still something that's like way, way down the road that we would even need to consider?

Justin Grammens 10:28
Yeah, my personal opinion is I think it's way, way down the road. And I don't think it's anything that we need to be too worried about. These are some of the things that I talked about with some of the listeners, you know, when I'm interviewing people, and I would say, by far, you know, and again, this is just my opinion, but I would say, by far, the consensus that I'm getting from people that are deep into this space, is the same thing, that what's going on right now with artificial intelligence is it's really automating away a lot of the mundane tasks that, quite frankly, people don't want to do. And there is, you know, a fear that now all of a sudden, what are these people going to do? Right, and there's an interesting book by Andrew Yang called The war on Normal People. And I'm not sure if you've read that, but it's pretty interesting. He paints kind of a grim future with regards to what could possibly happen. And, you know, part of the book is about actually having this universal basic income concept. But if you take that aside, it's like, you know, there is this fear that all of a sudden, with self driving cars, we're not going to need truckers anymore. With, you know, ai now actually doing stuff that surgeons can do, actually performing surgery, for example, or actually looking at, you know, CAT scans, and all this type of stuff, now we don't need doctors. And people can view this as a slippery slope, right? And that all of a sudden, now, what are humans going to do. They're going to basically become irrelevant. And I think while AI is a different, unique beast in a couple different ways, and this is where artificial intelligence and sort of the Internet of Things change is, it's not only the smarts that are there, but now with sensors and robotics, and like I said, self driving cars, now they can reach out and touch the world, right? They can actually physically change and alter the world. And when people start seeing that, then they start thinking, Well, geez, if this thing is smarter than me, faster than me, can work longer than me, you know, then I'm going to become completely irrelevant. And I believe that while that is an initial knee jerk reaction, I still believe that there's going to be things that humans will be able to do better than any machine could possibly do. And some of it is in the creative side, right? We don't have machines that can actually be, you know, like this podcast here. What you're doing Tim, everything that you've been doing, while there are bits and pieces of it that we could automate, I think the overall concept. You thought this idea up of his podcast, right? You birthed this idea. And I birthed a number of different businesses, and people have done that. And that's where I think humans are going to continue to excel in that space.

And then I also believe that, you know, while the physical manual labor work that machines have always done and have always done better, there still is an ecosystem around that, right. And it's not going to be completely automated away. So to answer your question, to come all the way back, I believe that, yeah, while there's a little bit of a fear that it's going to take away people's jobs, or that there's not going to be anything left for humans to do or it's going to turn evil on us. You know, I think it's so far away, that I'm not really super concerned with it. And I also think that if people hear the term artificial intelligence, they sometimes think that we have general artificial intelligence, which is this idea that you could actually, essentially plop a robot out there, and it can figure out the world and it can learn. And kids, babies, you know, we were talking about our kids, you know, growing up, they learn way faster than any robot could ever possibly learn. What robots are really good at learning is very narrow things, right? You teach a robot how to pick up a spoon. Okay, it can do that. But actually, once you tell it to pick up a ball, it can't do that. And so you have to teach a robot how to pick up a ball. And so why I think where humans are going to continue to sort of excel is in this general artificial intelligence space. And robots are by nowhere near having that type of cognitive ability that even kids that are six months old are able to look at patterns and discern things and do things on their own that, you know, robots are still a long, long, long, long away from doing.

Tim Bornholdt 14:42
I really like that you brought up that Andrew Yang book. I haven't read it, but I've followed Andrew Yang's, you know, career especially as he was getting into the limelight during the last election, but just the whole thought of a universal basic income and like just all the talk around that of with AI and with robotics and with us, you know, creating these machines to do our work more efficiently, faster. And if you look back over the last few 100 years of civilization, I mean, it's been this, like progress that we've made of creating something to make our lives easier, like attaching a plow to a horse, like that saved us so much time, you know, and creating an automobile and flying and doing all these things. Tere's been these monumental shifts in how we work and the definition of work has evolved. But I'm in the same camp as you as you know, we create these devices and these robots, and we create this artificial intelligence in order to make our lives easier. And there isn't going to be, I don't think, a point where most humans are going to say, Well, you know, I'm done with working. I'm done with being creative. I'm done with, you know, finding purpose in my life, all of that stuff. Like that's things that humans are always constantly striving for, and trying to achieve. And just because we create, you know, it's easy for me to say, in a privileged position where I'm not a trucker, but that trucking example is one that's a great one of, there's going to be jobs like that are routine and mundane. And it's like there is like a badge of honor to be a trucker, and to drive long hauls, and I get the the community and the vibe and the appeal of that. But it's also like a really hard job and a thankless job. And something that, like, if you were able to take those humans that have that drive and that passion and retrain them to have a similar passion and drive to, you know, create, to do, to be rewarded for putting in a hard day's work, you can find ways to marry the technology with that human element of wanting to strive to be, you know, better in one way or the other to achieve. I don't think like just having robots and computers taking away more mundane, automated, what's the word, automatable tasks, that's not going to necessarily mean the end of civilization, or that Skynet is going to take over, that all humans are going to become lazy, just like in, Wally. You know, I don't think it's going to be quite like that, personally.

Justin Grammens 17:16
Agreed. Agreed. Yep, yep. Yeah. And, I think, you know, what, like I say, with any new technology, it can be used for good, or it can be used for bad. And I think, you know, it's always fun to sort of play the devil's advocate, you know, and say, Well, what if. And I think it's healthy for us to have these conversations and talk about what could possibly happen. I just think if you look more on a historical nature, that I think there is good reason to say that, you know, I think we will all be better as a civilization because of this new technology. And you know, just to kind of drop another book. I'm not sure if you've ever read the book Sapiens by Yuval Noah Harare, but it's actually a really, really good book. And he's got three of them, but his most recent one. And that one's really about homosapiens. And why did homosapiens end up essentially being, you know, the master race over the Neanderthals that were going on at the same time. But he has another book out called 21 Lessons for the 21st Century. And it's a really, really good book. And he's a historian by nature, actually. And he is just a great writer, and he dives deep into the stuff.

And one of the things that I, well a piece that I remember from the book was, you talked about creating the plow, right. And so when the plow was created, people were actually able, you know, the plow wouldn't run on its own right. You still need the person behind the plow to actually run the plow. But then when the automobile was created, then people were like, Well, geez, why do we need horses anymore? You know, and why do I need to walk anywhere? And so there was a way for things to move forward, where it's like, well, I'll work in the automobile plant, right, for example. So this concept was that you could always find something for humans to do next. Right? They were always sort of part of the equation. And the fear is that now when we get to this point of artificial intelligence, there is no next, you know, springboard. There is no place for humans to basically go. But it was interesting that they were saying that, in this book he was talking about, they were talking about drones, and basically saying, Well, geez, now they're flying all these drones all over the world. And so now we don't need pilots anymore. Instead of having to launch a fleet of 30 pilots, we can have like one person sitting, you know, in their office controlling all these drones flying around. And it's like, geez, we just lost 30 pilot jobs. Right. So that was the negative side of that. But what he said was after all this data was collected from these machines, then they actually needed you know, I think 50 people to actually do the analysis on all the data that was collected by this one pilot, for example. Right? And so it's not just the actual, again, I think the mundane aspect of it is the flying, you know. Who actually wants to go on missions and fly stuff when you could actually have drones do the mundane stuff. But at the end of the day, what we're getting out of it is value, which is data. And then people still need to have humans and stuff work on that piece of it. So I think you kind of got to look in between the cracks and see, yes, okay, there's going to be less physical things that we're going to be doing, less people going out, quite frankly, less people are going to be going out and actually being in risky situations. But there's still going to be a ton of work that's going to need to be done on the backside of all of these technologies. And so the humans are still going to be very important in the loop.

Tim Bornholdt 20:37
Well, not to belabor the point too, but I was reading yesterday about bridge inspections, and how so many bridge inspections these days are done by drones. And the person that was talking about this said, you know, they were asking, Are you worried about drones taking over your job? And he was like, Hell no. Because there's so many bridges that need to be inspected. There's so much work that needs to be done. And even once you've done that inspection with a drone, you know, even if you put a 4k camera on a drone, that still doesn't give you the same tactile feel, and the same type of experience that you would get inspecting a bridge up close and personal with being able to touch it and smell it and feel it you know, whatever, you would need to do to be able to do that. And, you know, technology will continue to move forward and help us innovate in many ways. But like you said, I think it's more of jobs just evolving. And as a species, I mean, just the time it took for the Wright brothers to fly a plane to the time that we landed on the moon was only 66 years, right? Like that's not even blinking an eye in the context of like life on Earth. That's like nothing. And in our entire evolution as a species, technology has progressed slowly and moved very methodically. But now that we're all talking together with the internet, now that we can have communications with people all around the world and collaborate and share information, this pace of evolution is coming so fast, and I think, maybe that's something you could speak to as well as like, how can we as humans, you know, adapt quicker and become more comfortable with this rapid pace of change that we've seem to be going through here in the last 100, maybe, you know, call it 150 years?

Justin Grammens 22:17
Yeah, I think burying your head and not using some of this technology is probably the worst thing you can possibly do. Right? So if you don't get exposed to it, then things always seem a little more scary. And so I was talking with somebody recently, actually, I think it was when I presented at this Minnesota High Tech Association conference or whatever, they kind of asked about, well, how do you deal with people that are sort of old, older age groups? And how do they start working with us? And I said, you know, get them an Alexa, you know, get them a Google Voice. You know, a lot of people need to start just using it, and it's most especially I think if they're in the sort of the older age category, and it's not familiar to them. So I guess that's what I would say is at least start there with some sort of virtual assistant, and just start playing around with it. Right? I view it as more of a fun thing.

And yes, you know, Amazon, Google, Apple, they're all getting our data. And I think the more that we can, I guess, make sure that we're getting value out of that, right. So I'm not a huge, like, worrisome about data privacy. I am though, trying to educate people on just make sure you know, just make sure you're getting something in return for it, right. So if you're using your phone, and you want to get to certain locations, your data is being used to help the entire system work better and become more efficient, right. I mean, I took my kids to the Science Museum today. And I followed a special route that Google told me, because obviously, it knew where my car was, and knew where everybody else's car was. And I avoided, actually, quite frankly, probably avoided more accidents and traffic delays. And I used less energy by following the most optimal route. So all that being said is I would say, Yes, I think people need to, obviously, you know, use it if you can, read up on it. And, you know, listen to podcasts, you know, take in as much data and as much as much information as you possibly can with it.

And then, you know, I guess to kind of talk the other side of it is maybe be a little bit skeptical, you know. Ask some questions about, you know, if I'm using this, what value am I getting out of it as a general Joe or Jane consumer? And if there's value in there, then great, you know, I would say continue to use it. If not, then some of these features, which is what I would say going back to Internet of Things and AI, some of these features should be able to be turned off. Right? You should be able to turn off certain features and say, You know what, I don't want my data to leave this device. I actually don't want these additional things just because I choose to have it that way. So from that standpoint, some companies need to get better on actually allowing people to opt out of things. But as a general consensus, I guess I would say, you know, educate yourself and try some of these new things that are coming out and see what you like, what you dislike and just have a conversation about it.

Tim Bornholdt 25:05
We've kind of danced around both AI and IoT, and especially in this podcast, we've talked in several episodes in the past about those topics separately, but we've never really talked about the two combined. And it'd be hard pressed for me to have you on the show specifically, because I did check out your talk at the Minnesota Tech conference last week. And I think talking a little bit about AIoT, and some of the untapped potential of the partnership of those two. And, you know, maybe you can talk to us about maybe where that's kind of heading going forward in the future here.

Justin Grammens 25:39
Yeah, yeah. So, you know, I've been involved deeply with internet of things here for more than 10 years. And what I think the industry started to realize was, you know, IoT really is about connectivity. And it's really about getting data from the physical world and connecting these things together. And while that's great, it's missing sort of the intelligence and the intelligence demonstrated by machines, which is sort of like I was talking about sort of the classical definition of artificial intelligence is, you know, some very human level of intelligence demonstrated by machines. And so what we're starting to see is sort of this overlap of what we're calling the artificial intelligence of things, where you have Internet of Things, devices, actually, in some ways I like to call it the central nervous system, right. So you have these devices that are actually out in the field or at home, whatever they are, but they're actually getting data from the physical world. And then you sort of have an option. You can send it to the cloud, or you can do some onboard processing. But at some point, there needs to be some sort of intelligence baked into these things. And I think I read the quote, IoT is reactive. AIoT is proactive. And that's where you start getting these digital assistants that can actually tell you things ahead of time. You start getting, like, specifically in manufacturing, sort of predictive analytics, you know, fault tolerances are starting to go out of band, so maybe you might want to replace certain things. You start getting self driving cars, right, that can now start avoiding accidents before they happen. And that's kind of what I like to view the artificial intelligence of things is, is that whole entire system of not only IoT, but also artificial intelligence coming together to make these devices not only connected around us, right, and we talk a lot about connected products, but really make them smart, right? And anytime you see things around a smart speaker, a smart thermostat, and smart car, smart watch, smart is basically telling you, it's codeword for intelligent. And that's the course, in artificial intelligence, that's powered by a computer.

So these things are all around us today. I think what's happening now is we're starting to more or less put a term, the industry is starting to put a term around it, to really sort of highlight the fact that we need all of these aspects in order for us to really build products that make sense in the world, you know. Connecting things for the sake of connecting things is not really worthwhile. Artificial, I guess, you know, intelligence or building smart things is not useful, unless it can actually, obviously touch the physical world. And oftentimes, you actually need data from the physical world. You know, and that's where IoT comes in. Right? We're not talking about doing financial analysis, or some sort of, you know, other thing that doesn't involve sensors or sensory. That's really where AIot, I think, plays is, is there is a sensor involved. There's some data from the physical world. And, you know, we're being proactive and reacting to that really much, I guess, better than we ever could, and doing it ahead of time and providing value to customers that are using it.

Tim Bornholdt 28:53
A lot of the AIoT space reminds me of the 90s when the internet first came out, and all these businesses were kind of trying to figure out how to get started with being on the internet. And you saw a lot of experimentation and a lot of weird things and stuff that obviously didn't go anywhere. But then we kind of as time went on, you kind of figured out why you needed to be on the internet and how you would use that to further your business. Now that we're in, with IoT and with AI and AIoT, I think a lot of businesses are the same place, like how do you get started in this space? And how can you start exploring there? So maybe you could share some examples of, you know, maybe where AIoT has made an impact on some of the businesses, you've worked with at Lab651.

Justin Grammens 29:38
Yeah, yeah, I think some of the places that you should start is, first of all, is a business use case, right? So I tell people, let's talk about technology second. Let's figure out what you're trying to do within your business and how you want to essentially, like, let's paint the picture forward. So regardless of how you're going to do it, I always sort of start with that value in mind, and I think more often times than not, if I can get also a business to think about what are the costs associated with it? What's the cost associated with sending a service tech out to the field? What are the costs associated with the machine being down for, you know, a day or two, for example? What are the costs of we will talk about, you know, Tesla, right, like, what are the costs of cars getting in accidents, you know, human lives and stuff like that? So, if you can put $1 value on it, you know, great, but if not, if you sense that there's something there that the industry is looking at, especially if you're sort of, you know, looking to sort of maybe get ahead of the competition, then great. Let's put together a plan and figure out how we can kind of start with a minimum viable product.

And I'm sort of a big, big fan of the Lean Startup methodology, right, sort of the build, measure, learn. And we usually sit down with companies and figure out okay, from a technology standpoint, what sensors do we need to add? You know, what apps do we need to build? What kind activity do we need to figure out and do on this physical thing that's in the field, or, like we do at Lab651, we can actually build you the physical thing, you know, as well and put all the conductivity inside of it. But some companies already have things that are out in the field, a piece of machinery, for example, or, you know, we're working with a company now that basically has like a fluid valve, and they want to be able to measure all sorts of things around these valves. And so you know, how do we make that valve smarter? And so let's start small,, as I tell, sort of, like, let's build just one or two. And we have a product out there that's called ThingCloudApp. And we really work with companies to create a thing. And that thing can, you know, this is where we actually sort of figure out the actual sensing that we're going to be doing, and what data, what sort of microcontroller we might need to put on the device, what sort of smarts we need at the edge. And then the second piece of that ThingCloudApp is the cloud, right? So we're sending data to the cloud, and we are able to easily ingest it. And then the application part is whether it be a mobile app or a dashboard, something like that, be able to visualize and see your data. And I would say, Don't jump into the whole artificial intelligence stuff to begin with, likely you won't have enough data to do a lot of that stuff. And let's keep it pretty tightly contained, and sort of like a closed loop. Like, let's just evaluate the data that we're starting to get.

And you mentioned the early days of the internet. You know, just think about just early modems, right? And the disconnection factor and people being very, very slow. We're still in those early days of Internet of Things. I mean, I've been doing this for 10 years, and it's still very early. And the problem too is there's just 1000 different technologies you can use, you know, it's like, oh, should we use this? Or you know, 5G's coming? Should we wait for that? Should we use 2G? Should we use Laura? Should we use BLE? I mean, there's just all these different sort of technologies out there, and I'm kind of a proponent of, A, just get started, and then, B, just start small and start to understand and get the system working sort of end to end. And then, you know, as we work through customers over, you know, sort of a two to three month period, we can start looking at the data and start saying, does this make sense? Should we, where are the gaps, because inevitably, there are gaps. You never build, you know Tim for building software for a long time, you never hit it right the first time. There's always you need to go 10 degrees to the left, and then 10 degrees to the right. And over time, you eventually hone in on exactly what you really want to bring to market.

But use this early time here to again, experiment and explore and be open to sort of the shifting landscape. But I would say, yeah, start off with a business use case. We work through people through our ThingCloudApp sort of experience. Since we have a lot of ready made technology, ready made solutions, we can easily get data to the cloud. We easily have apps and dashboards we've already built for many customers, you know. Leverage open source software, whether you bring in an outside consultancy like us, or you just use an internal team. You know, keep it small, keep it tight, you know, self contained. You really do not want to have, you know, scope creep inside of this, and then just review often and say, does this make sense? Should we continue? Should we continue our path forward?

And so we've done this with, you know, a dozen different companies at various stages. Sometimes they start internal and then they bring us in on the outside. Sometimes they start with us on the outside and then they internalize it. But yeah, I mean, I've got a whole host of companies and at least I talked about some of them at the Minnesota Tech Conference, but everything from consumer appliances. We do a lot of work with Kenmore. We've done a lot of work with Craftsmen and their smart lawn equipment, to you know, industrial companies that are doing industrial grade paint mixers, to companies that are doing dash cams. Companies like Eaton that have done hydraulic hoses. Yeah, all sorts of stuff.

But these are companies that in a lot of ways are seeing that, and this is where the whole business angle comes in, I'm kind of going off a little bit of a rant here, but the business angle come comes in, because a lot of these companies are selling a physical product. And they realize that physical products are commoditized. Right? So over the course of a year or two, every appliance looks like every other appliance, right? Every other lawnmower looks like every other lawnmower. And so companies are starting to realize, well, how can we bring more value to the market. And this goes for not only consumer equipment, but industrial equipment as well. And so companies need to start thinking about more of a service based model, more of a data play, more of an interactivity. And I would dare say more of a smart play, right? Everyone's expecting these things to be smart around them. And whether it's something sitting in your home or something sitting on the factory floor, everyone's expecting things to be smart. And so how you've run your business in, you know, the 20th century is not going to work in the 21st century. And that's really what I think I'm really talking to people about is AIoT brings in this thing where it's like, it's just going to be expected that I'm going to have voice activation with, you know, everything around me. It's going to be expected that there's going to be an app that's going to be monitoring, you know, the flow controls within my system. It's going to be expected that my appliances know when I'm home, and when I'm not, so they can dial down, you know. I go on vacation for two weeks, well, you know, the appliances should just figure that out, right. And so these manufacturers that have just been manufacturing stuff, you know, for the past 100 years, are going to be in for a world of change. And you talked earlier about, you know, it being 60 years before we started to fly on the moon. I think it's going to be, you know, six years, before, all of a sudden, these things are gonna be all around us. And things are gonna be going very, very fast with regards to technology advancement, and companies need to get ahead of the curve to do this. So that's really what I try and do is try and educate companies on doing this, and then sort of help them get jump started.

Tim Bornholdt 37:05
Man, there's so much to unpack in that, but I loved it. Because one thing that I found interesting when you were talking was most companies come and want to bite off a lot and you kind of help coach them into starting small and being lean and doing something tiny, find the adjustments, go from there. And I think it's really funny to me that the longer that I do this, it's the same way with apps, it's the same way with, you know, like any project you ever take on. I think sometimes people, they put the cart before the horse, whatever analogy you want to throw out there, their eyes are bigger than the plate, whatever. They get so excited to want to build, you know, be 10 steps ahead of where they are, where it's like, you just need to take a half a step first and make sure that the ground in front of you is steady, before you take even a full step and then take another step after you go there. And it's interesting to me to hear that that's the same principles that you apply to even, you know, large corporations that have been doing this for a long time. You don't build out institutional knowledge by taking massive risks and huge steps, you know, you really make a lot of progress by starting small and taking little steps, incremental steps to get to that final destination. I think it's really cool that that's kind of the approach that you take when you're trying to get started in a space that's as complex as IoT and AI and everything like that.

Justin Grammens 38:37
Yeah, I think like you said, I think that the more complex it is, the more that the ground is shifting, and you know, to use your words, you know, you want to take small steps. So when you have all these different technologies coming to bear on one solution, you really need to make sure that you have your ducks in a row. And you can even break it down to even just small, small pieces, like you know, let's not even get the data to the cloud today, right? Let's just set up a environment where we can actually just capture it and make sure that it's actually staying on board on the device, for example, and could even just use Bluetooth Low Energy and send it to your phone, for example. Right? So start super, super small. So yeah, I am a huge proponent of that.

I will also say that, you know, when you have all these different technologies going on at the same time, it's hard for one person to be a really, you know, competent expert in all of them. I would say it's nearly impossible. Right? And so that's where I think, you know, either our team at Lab651, we have a number of different disciplines that we can bring to bear. But also if you're doing it internally, you need to realize that there is not only the technology side, but I touched on it a little bit, there's the finance side of it, right. There's actually I would say a huge component of it is your customer. So getting something into their hands when you get an install going and you have a couple of these things in the field, you've got to listen to your customers, you know. You probably know this better than anybody as you guys are building out your apps. But you need to understand you need to service them. And then you know, you have the CEO of the company, you have the people, the IT support, the people that need to maintain this, whether if you're putting something on site, like how does this thing work in their IT infrastructure.

So I've seen so many projects where somebody has had an idea, and they've started. And it's just an engineering group. That's all it is. And they're building technology, and they build stuff, and you know, these projects go 3, 6, 9, 12 months, then all of a sudden, tada! You know, we're gonna bring this to market, and literally, the rest of the company is like, what the hell just happened here, like this doesn't solve the market problem. Have you guys thought of X, Y, and Z? Like, how are we gonna sell this, who's our sales, you know, all this type of stuff around it. So like I say, these solutions that we're building aren't just like, well, let's crank out an app in a weekend type things. These are things that actually fundamentally change the way the business is run. And you need to involve the entire business. And that's where I think, that's where I've seen, that's where I believe we've seen a lot of fits and starts and like, slowdowns. So while Internet of Things is sort of still this big, you know, term projects, I've just seen so many projects over the past 10 years start and stop, start and stop. Because of this, you know, because there are a lot of companies that are either, A, stubbing their toes, and sort of not actually building the market what their customers are asking for. But also it is a complex thing and you need involve a lot of people and that can, especially in large organizations, man, that can take a long time to get some consensus moving. So where I'm sitting on the outside sort of waiting and helping companies sort of move things forward. But some projects will take a year before they finally actually sort of get the general consensus and approval from everybody to get going. And you know what? To be fair, that's probably right. You know, you don't want to start early. So I applaud these companies that make sure they get everything in a row. And we are able to be much more successful. The end of the day, I love working on successful projects, rather than ones that just are sort of quick hits fast things, and you know that they go down in flames, because that's not good for anybody.

Tim Bornholdt 42:06
I couldn't agree more. One thing that made me think about, and I'm really curious to hear your opinion on this, so a lot of times people come to us for building mobile apps, and they tell us their idea. And then they right away ask, Is this a good idea? Or is this a bad idea? And I hate that question more than anything in the world. Because it's like, I don't know, you know, like, that's your job, right? But like, how do you help people determine, especially, you know, mobile apps and IoT have kind of been around for a similar amount of time. But to my mind, and maybe that's because I'm in the mobile app space, I think it's a lot easier for me to figure out that, you know, what is a good mobile app idea versus what could be served with a different type of technology? Or a different type of solution? Do you have advice for people when they say, you know, It'd be really cool if my company added this type of AIoT to our services? How do you help people really vet through that process of determining whether that's a good idea or a bad idea?

Justin Grammens 43:10
Yeah, it's sort of a constant poll on both sides. I mean, I think my initial reaction is, Have you asked your customers? Right? I think the first thing that I say is, you know, whoever is selling your product, feet on the street, start having those conversations, because you guys have a whole pool of people you can ask, you know. I'm one little data point here. And yes, while I understand the technology, and I can give you a lot of examples of other companies that have done it, only you know your business and only you know your customers the best.

So, I start there with, you know, Hey, have you asked them? But also, you're not going to build a, you know, monumental, you know, like a game changing product by asking your customers. Your customers aren't going to give you that. And that's where I think, you know, that's where I think Steve Jobs was just so great, right? He was just always pushing it, while he was asking customers, and they were finding what they were doing, he actually was a genius behind a lot of these new products. So you have to sort of take both sides, you know. You got to understand what's in the market, what people are willing to pay for. But then you also need to start thinking about further ahead. And, you know, while people maybe don't see it, they're not gonna come out and tell you, I will buy this. You need to be thinking ahead. And that's where these experiments happen, quite frankly. That's where I'm talking about, you know, don't invest the farm on this new product idea. Let's start out and build a couple small ones. And maybe we could probably do five or six different concepts, you know, that you're coming up with, on sort of a quick budget, and then you can bring it to the customer and say, I know you didn't ask for this really, you know, or a component of this you were asking for but here's what we're looking to do. And can we install it at your site? Can we, you know, can we plug it into your system? Can we do whatever to it? And, you know, the good customers are going to be the ones that are going to say, you know, Yes, this sounds interesting. I mean, you'll be surprised too, a lot of your customers actually want you to succeed, you know. They actually want to be a part of some of these. They want you to be a part of some of these, or they want to be a part of some of this new technology and say, Hey, I'm beta testing some of this new stuff with you guys.

So, yeah, I would say that's sort of like, I guess the steps that I would go through with them. And again, I love just conversations, just like, you know, open ended stuff. Well, what if, because sometimes, the customers don't understand, you know, the customers that come to us that are, you know, building the things, don't understand really like what's possible, right? And so, you know, they might be way off on Mars thinking, Well, yeah, we'll have a battery that will run for 10 years, and it will do this, that and the other stuff. And I need to kind of rein them in and say, We're not quite there yet. You know, but have you thought about this? And they're like, Oh, I didn't even know we had a sensor that could do that. Or, Oh, wow, you know, you mean, we could actually, you know, put in an Alexa skill, you know, in a couple weeks? Yeah, absolutely. You know, that's not that hard. So a lot of it is just education for them on understanding really what's costly and hard to do, quotes from an engineering standpoint, and what are some easy things, and then you know, have some good conversations between them and their customers, and then start getting stuff out in the market, and just going through an MVP process.

Tim Bornholdt 46:17
I think that the partnership between the tech provider vendor whoever, and the company is really the crux of determining whether you've got a good idea or a bad idea. I mean, I think you hit it right on the head, where really talking to the customer should be number one, just with a bullet of making sure that your customer actually would want something like that. But I think doing a lot of that ideation, and talking through with people, and a key part of it, too, is not making them feel dumb. I mean, in this space, I know so many engineers that are brilliant, brilliant people, but they just don't have those soft skills to be able to actually talk to somebody and help them with a problem without making them feel dumb. I know a lot of times even in class going through college, you know, people would be arguing over stuff and making you feel like, What you don't know that? What are you an idiot? And that just doesn't help. What helps is when you can bring your expertise in whatever industry you're in, manufacturing, healthcare, whatever, you have that certain skill set of knowing your customers, hopefully relatively intimately, right? And then so you have that voice that you can bring, and then you can bring us ideas and problems, and we work together to tell you well, you know, here's what we've done in the past for other people. Here's the state of technology. And yeah, maybe this idea that you have will be great in 30 years, when the technology catches up. Here's what we can do in the meantime, to help push you to in that general direction. And again, it's just baby steps moving forward together and trying to get that trust where, you know, we're trusting that you understand the industry and the customer and knowing what problems need to be solved. And at the same time you trust us in saying, you know, we know what technology is out there, and how we can actually apply that to this specific problem to give value to your customers.

Yep, yep, totally, totally. Yeah, I would say just to drop another book, if you've ever read The Innovator's Dilemma. It talks a lot about companies losing their market leadership, really, because they listen to their customers too much, you know, as well. So, you know, it's this idea that, you know, you got to sort of play this Yin and Yang, and when you're an innovator, and you're an innovative company, and oftentimes, that's who your customers are, at least that's the customers that I love working with, right? Customers that are thinking about innovation and thinking about using this in a new way. They need to listen their customers, obviously, but they also need to know when they sort of have to go off the beaten path. And oftentimes, it can actually be, what's kind of cool in the book, it really talks about large companies, like large customers, are actually the ones that are hardest to change, right. So if you're selling into a large enterprise organization, likely they're not going to be the ones that are going to give you the ideas for your next generation of product, right. So it's actually talking to your more small customers that are actually willing to take a risk with you, like I was talking about earlier. And then also is they're oftentimes just a little bit more susceptive to these disruptive technologies that you're really trying to bring to market. And again, from a business standpoint, I talked a little bit about it like, these businesses are going to become dinosaurs if they don't create smarter and smarter things around. And so you know, servicing your customer is really good. But I would say just the caveat with that is is you know, service the ones that want to be disruptive and innovative with you a little bit more. That's what this book kind of talks about.

I love it. Justin, this was an awesome conversation. How can people find you and learn more? I mean, you've got so much going on right now. Where do we people even get started in entering the world of Justin?

Justin Grammens 50:11
Well, you can go to JustinGammens.com, actually. That's a fine place to start. It's got a picture of me, and me and my family, my kids and then there's links off to all sorts of things that I'm working on. Obviously, I'm on LinkedIn. So just search for me on LinkedIn. And you know, everything I've been talking about here is our services that we provide at Lab651. So go to Lab651.com.

Tim Bornholdt 50:37
I really miss the days of everyone having their own website with just a picture of themselves and their family and a short bio. I mean, I have the same thing too at Timbornholdt.com. And I'm just glad that there's somebody else out there that's still holding strong with having their own personal domain and keeping their own little chunk of the internet to themselves.

Justin Grammens 50:56
Yeah, and I can't even remember when I registered that, but I registered it. And I'm glad that I did. And, you know, it's, yeah, if you want to know all about me, and what's so fun is obviously things will change over time. Right. So once I get involved in other technologies, I will sort of use it as this sort of memorialization place, right, where I can just kind of go back sometime when I'm 85 years old and look over and see some of the things that I've accomplished.

Tim Bornholdt 51:20
And now also to just check out archive.org on that and see the history of evolution of design. It's cool when you've had a site up for several years, and you can just see how often it gets redesigned and styles and trends and stuff. I mean, I don't update mine really ever. But if I still had all my sites from way back in the day, it's definitely fun to see how the internet has changed in such a short time.

Justin Grammens 51:46
Oh, gosh, yeah. Yeah, for sure. For sure.

Tim Bornholdt 51:49
Justin, thank you so much for joining me.

Justin Grammens 51:51
Yeah, Tim. I appreciate it. Thank you so much.

Tim Bornholdt 51:54
Thanks to Justin Grammens for joining me on the podcast today. You can learn more about his work at Lab651.com or JustinGrammens.com.

Show notes for this episode can be found at constantvariables.co. You can get in touch with us by emailing Hello@constant variables.co. I'm @TimBornholdt on Twitter and the show is @CV_podcast. Today's episode was produced by Jenny Karkowski and edited by the dazzling Jordan Daoust.

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