Embedded - 403: Engineers Are a Difficult People

Episode Date: February 25, 2022

Shawn Hymel spoke to us about creating education videos and written tutorials; marketing by and for engineers; and bowties. You can find Shawn teaching FPGAs, RTOSs and other interesting topics on Digikey’s YouTube channel. Shawn also has two embedded Machine Learning courses on Coursera (free!).  Or start at his personal site: shawnhymel.com where you can find written tutorials like How to Set Up Raspberry Pi Pico C/C++ Toolchain on Windows with VS Code. Shawn talked about Discovery-Driven Growth: A Breakthrough Process to Reduce Risk and Seize Opportunity by Rita Gunther McGrath and Ian C. Macmillan. He referenced  Blue Ocean Strategy: How to Create Uncontested Market Space and Make the Competition Irrelevant by W. Chan Kim and Renée A. Mauborgne Elecia enjoyed The Visual Mba: Two Years of Business School Packed into One Priceless Book of Pure Awesomeness by Jason Barron Embedded has: A Patreon page where you can support us and get into the Slack community A newsletter that sends you a weekly email about the show and little notes Transcripts that you can use to look things up or follow along if the speakers are unclear If you’d like to help the show grow, please write a review. Or share it with a friend. Or send it to your school’s Dean of Computer Science and/or Engineering and tell them it should be part of the curriculum to see what engineering lives and careers are like. Or send it to your company’s Director of New Hires and say it is important for techy folks to stay current and engaged in embedded systems. Transcript

Welcome to Embedded. I'm Alicia White, alongside Christopher White. Our guest this week is Sean Hemel, and we're going to talk about teaching, learning, and maybe some marketing. Marketing? Hi, Sean. Welcome to the show. Hey, thanks for having me. Yeah, I'm excited to talk about all those things. Could you tell us about yourself as if we met at, I don't know, Hackaday Supercon? Yeah, absolutely. And you picked my favorite conference because that always feels like a gathering of family to me. You probably recognize me wearing a bow tie. That's kind of my signature move. So if you've seen any Google videos or YouTube videos with me, I'm generally in that bow tie. Right now I'm not wearing it because

I don't need to be seen on a podcast. So I will make that admission. Part of who I am is creating technical content for people to teach them. I want to make electronics accessible to ideally everyone. And I recognize that a lot of the topics are fairly complicated. So I do my best to break those down and teach them in whatever manner I can. And that includes video, maybe it's written, maybe it's demonstration, whether it's a project or demo code that can be shared via GitHub. I just want to teach people and get them excited about electronics, about machine learning, about embedded systems, and so on. I did some work at Sparkfun Electronics as an engineer. I moved over to marketing to do more

of that teaching and marketing side. Part of that included learning more about marketing. And then I worked for myself as a freelancer for a little while, generating content, a lot of blog writing, a lot of videos, and much of that appears on DigiKey's YouTube channel, where I did a number of series around KiCad, FPGAs, real-time operating systems. And I recently took a full-time position at Edge Impulse to do more or less the same. I'm a DevRel or developer relations engineer where I'm making content, giving webinars, going to events, and generally teaching people about embedded machine learning. All right. We want to do lightning round where we ask you short

questions and we want short answers. And if we are behaving ourselves, we won't say, are you sure or why or any of those things. Are you ready? Yes, let's do it. Polka or swing? Oh my goodness, swing all the way. Favorite dev board? Ooh, man, you know what? I continually go back to the, I'm drawing a blank, the Arduino Pro Mini, the one that Sparkfun put out years ago. I use that in almost everything. And that 328P is just a, you know, tried and true. It works almost every time. Introvert or extrovert? Definitely introvert, despite what a lot of people may think upon first meeting me.

Engineer or educator? Ooh, can I pick yes? Sure. If you could teach a college course, what would you want to teach? So I actually have a couple of courses that I think are in line with kind of college, but they're pretty compressed around embedded machine learning. They're up on Coursera for introduction to embedded machine learning and computer vision with embedded machine learning. I would say they're kind of at a college level, but I compress and abstract away a lot of things. That being said, if I could actually choose what I wanted to teach, it would

be something called life skills with a Z, obviously, or just how to be a good person. Kind of like home ec where you learn basic how to stay alive and manage a budget, cook yourself food, but also how to socialize, deal with rejection, you know, not be a jerk in the world. I'd love to teach a class like that. Where do you source your bow ties? Anywhere I can get them. As, you know, old white guy as this sounds, but Brooks Brothers make some of my favorites. There's a local place out of Boulder that I am forgetting the name of right now. Uh, Carrot and Gibbs is the name. And, uh, there were a couple of others that I like, but it's usually like Brooks Brothers

or any type of local shop that I can find when I'm wandering around cities. I will try to pick some up. Do you have a tip everyone should know? Uh, let's see a tip that everyone should know. Let me think about this one. So a general tip I like to think about is, I'm going to go to that life lesson here as far as when it comes to engineering and you want to sell your thing or you want people to use it, the idea of if you build it, they will come 99% of the time doesn't work, which is where it helps to know a little bit of biz dev, a little bit of sales and a little bit of marketing if you care to have other people use the thing that you're making. Well, that's actually

going to make a good transition. So let's just go right there. So we hired a social media person a little while ago, and we haven't really gotten a lot of new listeners, although I think we've strengthened the channels and our newsletter looks nice now and all that. But the podcast market as a whole, since the pandemic started, has kind of been going down. And we'd like to reach more listeners because I really think we do a good job. Chris does a fantastic job on making us have good sound. And I think we help people stay in engineering or get into engineering and enjoy technology in a way that many other people don't. How do we, but I've always had, I mean, Sheila's Joe Jackson, that was the guy. I've always had a if you build it, they will come mentality.

And my first job was at HP where it was said that the marketing would advertise sushi as cold dead fish because they were very, here's what it is. And yet we've stagnated and I want to do better. How do I do better? Uh, that is a super broad question, but it is definitely, it is definitely the questions. That's definitely the type of question that I think most marketers ask themselves about them, about them, their company, the product, what they're trying to market. And there's a saying in the marketing world that something like 50% of all marketing doesn't work and 50% works. And the trick is figuring out which 50% works. And it's a constant game of figuring out what works in your particular market, what resonates with your audience.

And there are scientific approaches to doing that. And there's a good book around it. And the name of the book is escaping me right now. So if it's something I can throw into the show notes later, I'll get back to you on that. Yes, please. And the author is a legitimate researcher, a PhD in marketing, and she breaks down how to approach marketing like a scientist. It's a pretty technical book. It's super dry. They talk about areas where you can expand in the sense of how do we create product? How do we create social capital? All of these things, and you can map them out. You can find ways to measure and you iterate on that. And it's not as simple as just, oh, I think that the color red is going to appeal to this audience. Let's put it on our site. You measure it, you do red

versus blue and you learn and it takes time. And I think that's the big thing a lot of people don't understand about good marketing is it takes time. We always hear these great stories of, oh, I imagine that the sound of the toothbrush is what draws people in and they do it. They make the toothbrush sound a certain way and it generates a hundred times revenue. There are a few stories that do that from a couple of marketing geniuses throughout the years. But reality is that marketing takes time, effort, and a lot of science, a lot of hypotheses that you have to test and come back and iterate on and build. And that's really hard, especially when people just want to say, oh, I'll pay you for one video and that's going to generate a million views. You're like, not really.

That's not quite how that works if you're trying to generate a market for your product. In this case, I guess it's a podcast. You know, just the one video on YouTube doesn't generate an audience. It might get some views. If we're lucky, it goes viral. There's no viral button. It's just you hit on something that the audience resonates with and it causes them to share it. And there are some ways you can tailor that, but there's no guaranteed this video will be viral. So all of those things in mind, marketing is a tough thing to do. And you talk about the podcast. I find it interesting that podcast listenership has gone down. Since we ended the Hello Blink show, I haven't paid attention

because I thought there was an uptick initially during the pandemic as people were stuck inside, hopefully listening to more podcasts. So that's interesting for me to hear that in general, it's gone down. And it's a question of who is your audience? That's always where I start with. Who do you want to attract? And I know that for Embedded FM, it's a lot of very technical people. And you've got great guests. You do a great job on the show. You have a good product. There's nothing wrong. I looked at the iTunes stats and you are blowing Hello Blink show out of the water. You've got five-star reviews and lots of listenership. So I think you have a very good base and it's how do you reach beyond that? And there are a number of ways to do that. You can grow a community,

like say host a Discord channel, host a forum that draw people in, but that's not your top level funnel, right? That just keeps people engaged. When you start talking top level, you start thinking SEO, organic. How do people search when they search for something on Google, right? What are they looking for? And so you need to tailor your content around that. I don't know how good, this is a blind spot of mine, I don't know how good Google is at saying, let's find what's being said in a podcast and make it searchable on the internet.

So really that comes down to having great show notes and making sure you hit all of your good SEO things. It needs to be more than 500, 800 words, whatever it is at the given time. Maybe slap in some pictures, link to things so that people can, you know, click through them and make it a good page. And the big thing is to make sure your title, when you're picking a title that people can find. I'm sure you all know all these things. I want to do that. Never. I'm sure you all know all these things. This is like marketing 101 type of thing. How do you draw people in? You can also run targeted ads. This is where people think, oh, I just spend a hundred bucks and I get a thousand dollars in

revenue. And targeted ads have gone way down in usefulness in the last decade. And so really, what targeted ads can do is help you learn about your audience. And I would look at things like Facebook, where you can do things like, oh, I want, you know, middle-aged women who have a degree in whatever, and we can run ads against them versus another segment of the population. And you start to learn like, oh, this segment engages with these ads more than this. And you start to narrow down and figure out, you know, you might have an idea of who's listening to your podcast, but when you run some of these targeted ads, you start figuring out, oh, these people actually care more than I thought. And you can

start generating content more for them. And then that's when you start ramping up like, oh, let's send them more things that they're engaged in. So there's that side of it. There's also, um, you could do an email newsletter. I'm actually pretty bad about doing those. We have one. You do? Okay. I'm personally bad. I should sign up for that.

You're pointing out my ignorance here. Well, we don't talk about it on the show. We really haven't talked about it on the show much. And we only recently got it to be more than basically an RSS feed. So now it tells you the show notes. It gives you the transcript, it pulls out a quote, we hint what the next show will be, and if there are anything else, bonus content, like if my class is open or whatever, or we have a giveaway going on,

that's all in the newsletter now. Oh, perfect. So now that we've talked about it on the show, I would say it's a great time to connect those things, right? Use the newsletter to drive people to the show. Use the show to drive people to the newsletter. The more you can connect those things, the more people see how well your product is, I would say, supported. Or at least it gives the illusion of your product being supported, right? I know that anytime you're working on something, it always feels like you're scrambling to throw it together. At least that's how I feel as an engineer. But having content around it really helps if you want to engage with the newsletter rather than the podcast. You don't want to duplicate those efforts exactly or make the newsletter just a transcript, but you can link to the transcript, pull up quotes like you're saying, offer a picture, keep people engaged in that readable format. That's a great way to keep people coming back and engaging with your work. So I hope like it's, I know I throw out a ton of ideas here and it's really trying to figure out what works for you, what feels natural.

And the other thing is maintaining brand authenticity. As soon as people think that you're trying to push something on them, like a used car salesperson, it's they're turned off immediately, especially engineers is what I have found. As soon as they feel like that pushiness, they're gone, right? They're out. I was going to ask, that was my next question, is I have this notion that engineers consider themselves at least resistant to all marketing. They'll put up ad blockers, they will pretend that none of this has any effect on them. Is that actually true, or is it just that it requires a different approach? I think it requires a different

approach. A lot of engineers I know subscribe to newsletters, right? And if you ask them if that's marketing, what are they going to say? No, it's a newsletter. Right, right. But it's absolutely marketing. It's a form of engaging with an audience to, you know, and ideally it, the newsletter provides something, right? Good marketing should give something, right? It's, it's what's relevant in the industry or, or here's some good resources. A good newsletter knows how to write things for the audience that they engage in. And if you're using HubSpot or, or what or MailChimp or one of those, you'll see click through rates, how long people read it. You'll get those stats back to see how long people are staying on that newsletter. And that really helps. That helps you craft it to maintain better

readership. And so if I feel like the newsletter is doing something for me and I read it, yeah, I stay subscribed. Absolutely. But I am resistant to ads as well. So I think we consider marketing to be that general, oh, big billboards, the fluffy thing, the woman throwing the hammer at the TV and the Apple commercial. And those all express great things. And if you're talking about a why for a brand, they help convey that. But I'm with you. A lot of engineers are like, yeah, that's just fluff. I don't care about that. But if you know how your audience thinks, like say it's mostly engineers, offering technical things or technical advice in their field,

they're going to be super engaged with that. How do you target that individually? I don't know. I can't tell you that one. But news or relevant things or a cool interview, they're probably going to engage with that. So knowing your audience is the most important thing. Knowing your audience and offering something. Do that 51% of I give you something and then later on you can be like, well, hey, if you haven't heard our show, come listen, assuming your primary goal is to get listeners. Yes, our primary goal is to get listeners. And that's kind of odd because what you're saying, give them information. Well, that's what we want to do. We just want them to listen. And so that's a little odd. I know that a lot of people are using podcasts as a way to nurture a community, to create a community for later conversion to sales or partial. It's part of the funnel.

But for us, the bottom of the funnel is listen to the podcast, stay an engineer, be enlightened about diversity, and think about tools and enjoy technology and engineering and science and learning. And that's all we want. I don't even enjoy technology. I know. If you can't be a good example, you can at least be a horrible warning. And there's your quote for the show. So yeah, what you're saying makes sense, except we're not selling what we're selling. It sounds like a lot of work, Sean. It really does.

That's the other problem with being an engineer is, you know, I don't really want to do anything. I mean, we already do a lot of work for the show. Transcripts and tweets. So is this the sort of thing I could just buy? Yes, actually. There are marketing services out there. How good they are is going to be up to what you're trying to sell,

how well they know the audience. Because sometimes they're just going to be like, well, what you need is a logo and all these things. You're like, but I really don't think my audience cares about those things. We have a Pitchin logo. Oh, your logo is awesome. I love your logo. What year is it?

I had a question. Well, about podcasts specifically, and maybe you haven't thought about this having had your own podcast. The way I relate to podcasts after I've been listening to one-to-one for a while is less about, I don't really care what they're saying a lot of the

time. I'm just enjoying the conversation and the people I've had in my ears for a couple of months or whatever. And if that's the way most people relate to podcasts, that seems like a very difficult thing to market, to say, hey, join us and you'll become our, you know, you can pretend we're your friends. That's because I wanted to target ads to podcast listeners first and engineers second. Yeah. And it sounded like that wasn't, those weren't categories people had. Well, maybe you could run two different ads, you know, buy out smaller slices, spend half on each and see what performs better.

Half of marketing is science. And the other half is what? Making stuff up and seeing what sticks. For podcast listenership going down, people aren't commuting anymore. That seemed to be when they listened to podcasts. Yeah, we had a real cliff March 2020 that was immediate and obvious.

It crawled back, but it's definitely less than it was. And maybe we're annoying of it crawled back but it's it's definitely less than it was and maybe we're annoying yeah i mean it's very possible we've just become very annoying i highly doubt it i i also think that when when you consider other podcasts you know your your your big name podcasters engineering is is somewhat of a small slice. What? What? So it's kind of one of those like setting the expectations of like, okay, who do we want to join this? And if it's really for engineers, like understand, you know, it's not going to be Joe Rogan, right? It's not going to be, he's a terrible example, but you know what I'm saying? Thankfully not going to be, yes. Oh yeah, goodness. I really don't. Yeah.

But as far as popularity goes, he's a household name that everyone knows. So set your expectations. I always say go after the niche market because it makes a lot of sense where you can foster that community. And also the idea of creating a community Because right now it's only us talking. But I know that like Chris Gamble invites people to join his forum that he runs contextual electronics. And I, which is, which is a great way to foster kind of that. It's a lot of like freelancers and hardcore engineers asking each other's questions. And it's a good community. So maybe a discord channel or something where it's not just, oh, hey, listen to the podcast, but hey, listen to the podcast and hang out with us on Discord or whatever it might be

so people can feel more engaged. Once again, this is one idea about creating community engagement. I make no promises as to how well that will work. It works pretty well because we do have one. Sorry. No, you're good. Pitch it. Let's go.

It's for Patreon supporters. So, you know, you give us a buck once and you get the Slack link. And it's not like I ever check to see if you ever give us money in the future. And the Patreon group is pretty fantastic. People bring in technical problems and we discuss them. Jobs and stuff. And last week we had the podcast about scheduling. And that all came out of a discussion from the Patreon Slack group.

It's a really interesting group. I mean, I bring my problems there too. I bring my complaints there. Well, yes, we have a channel called Complainatorium, and it's just a list of what people don't like today. Yeah, so if you don't want to join Twitter and you just want to complain about stuff, you can join our Slack for a dollar and then complain all you want to some other people. We also have a Good Stuff channel. That one's good, too.

So that's a more traditional marketing funnel where you're talking about you have a sales, you have a conversion. It could be a dollar. Yeah. But your community is actually locked behind that. And you'll have to forgive my ignorance about not knowing about that one. But your community is locked behind whatever paywall, right? It could be a very simple paywall.

So it's more of a traditional funnel rather than having both side by side. And it's mostly just, I mean, we're not trying to make a lot of money off of that. It's mostly, here is a small hurdle that you must go over to join this community. To be serious about it. Yeah. And because monitoring it takes time and making sure everybody stays nice, which they do. But it isn't free and open because we do want people who are at least a little serious about wanting to be in the community instead of just signing up 10,000 people and having them never show up. So it sounds like we're doing mostly the right things.

Yeah. Just to do a little bit more. And it could be, you could open it up for free if you wanted to. But I, you know, in my experience, if you want to kind of keep, you know, the trolls and whatever out only, you know, have people who are serious, absolutely charge, charge a buck. I mean, that that barrier is not a lot to people who want to contribute and be serious about being part of the community. And I find that it adds value to it, right? It pays a little bit for your time, but for the consumer, it feels like, oh, I'm now committed to being a part of this because I put in something that means something to me. You know, it's a dollar, whatever. And it pays for transcripts and it pays for the social media help we get. And then that leads to the newsletter looking nice. And so we don't make any money off of it. No, because we've got to pay for hosting out of that too. Yeah.

And mics, which we didn't have to give Sean. To shift away from the podcast, if that's okay. Oh, yeah. So it still makes sense when you've got like some recognition out there. How do you build from zero? Like if I've got a little product I want to make or some content that's brand new and I'm an unknown person, what is the path there? You go on a podcast. Absolutely. Putting yourself out there is the first way to do it. And that is,

Harris and I would tell people on the show, we've had a few people on who had the exact same problem, right? I'm building this thing. I don't know the first thing about trying to sell it. And the first thing we tell them is start telling people what you're building. As much as you're comfortable sharing, because we get it, sometimes you don't want to give the big reveal, you don't want to give away too much. But if you can have parts of it be open source, start posting on a project site like Hackster or Hack If yours is a, you know, photography or an art thing, maybe Instagram or TikTok, you know, know your audience first, find a social media and try to like snap a picture of what you're working on once a day. You know, the parts of it that you can share, make a tweet. Does it suck? Yes, absolutely. I hate it. I hate doing it, but it's, you know, kind of part of the job. And I have some fun, great conversations with people, but social media to me is a job, right? It's just one more thing I have to do to build an audience. a business, it's going to take time to grow it. You can do some tricks. You can buy followers. You can buy

email lists. But to me, buying follower stuff actually work. It feels kind of scammy. Yeah. It's very scammy. It's very scammy. It's it will erode trust, right? It's a quick fix for a bandaid. If you want to look important, very very very for a very short amount of time once people find out about it especially engineers it comes across as that scamminess so personally i would avoid it i prefer to like grow stuff naturally um in the sense of people people should choose to follow me right i shouldn't have to buy that opt-in and really when you're buying that when you're buying followers you're buying the little number so that other people see that and go oh this a person is because the followers you're

buying are probably not doing anything for you right exactly yeah they're not they're just so you have that number so you look legitimate or important um and and any little tweaks you can do to look legitimate or important right have a you know a fun logo with an old-timey radio. That helps a ton. And look kind of like a business. If you want to be a business, get that LLC rolling. Those kinds of things can help make you look legitimate and start talking about what you're doing. Start engaging with people, other followers. You can find the hashtags you want to go after and just start commenting on conversations that you see. And that will help grow your audience over time, at least on social media.

And make sure you have some type of call to action on whatever page. Say you have your social media profile. Say like, oh, I'm building this thing at blah, blah, blah, blah.com. Or check out my LinkedIn thing. Or drive them somewhere. Or like, hey, you want to keep up with check out my LinkedIn thing or, you know, drive them somewhere or like, Hey, you want to keep up with what's going on, sign up for my newsletter. And it starts to, whether people click on it or not, it starts to show that, Hey, you're serious about building this thing. And over time, and I mean like years, people start to like pay attention.

This is not a, like, you know, if somebody came to me and they're like, you know, we need 10,000 followers in a month. And I'm like, you can buy them. That's about your only option. Or, or you throw a lot of money at some famous person to do influencer marketing, you know, to talk about you on whatever podcast or whatever it might be. That's about it. Otherwise you're going to events to show it off. You're coming, you know, you're trying to get on podcasts. You're asking people you're trading content. You're on social media. You're trying to build a site. You're asking people. You're trading content. You're on social media. You're trying to build a site that looks good with a newsletter. You're trying to do all of these things.

And yeah, if you're alone, you're trying to do this while building a product, which is rough. I get it. We have no call to action, like anywhere. What do you want to do? I mean, we're engineers. We're like, okay. Don't email me for sure. We have a show.

Don't email me. We have a show. We think it's really cool. And that's pretty much what everything says. We don't say, and you should listen. We just, it's like, that's implied. Our listeners are smart. I don't want people to listen. I want them to subscribe, but I don't want people to listen to me.

That would be awful. Why would I want that for anyone? You just want the number. But no, it's because the people are smart. Of course, they should know that they should listen. I also have a notion that video is like the thing now. That's the hardest thing. That's the thing that people engage with most.

It's the true of Instagram and YouTube and all these things. They're all shifting to video and people don't respond to text. They respond a little better to images, but really they respond to video. And I was kind of learning about this when I was doing my band's record. And it's hard to do video. It's like 10 to 20 times more difficult than building anything else. So I'm resistant to that. I'm also resistant to people seeing me. So is that true? Do people seem to engage with video more? And is that something people should consider more? And can we use puppets? You can, yeah, you can make video however you want. I love puppets. I don't know, because I don't have a good apples to apples

comparison between the two. I think it's different media for different audiences. You can't do video in a commute, right? Like, unless you want to, you know, risk a crash. But, you can't do video in a commute, right? Like unless you want to risk a crash, but you know, once commuting comes back, I'm sure there will be an uptick in podcasts just because you can't do video. Um, tick tock is going outrageous right now because yeah, video is hotness and it's, and it's appealing to a certain crowd. It's appealing to that younger crowd who want to make videos, share, do the music thing. Um've not really found what works for me in TikTok. I've seen some people, engineers who have done educational things, but they're very brief,. And I'm like, I know that took them a lot of time to produce this one minute video for TikTok. And that's it, right? It's social media. It's ephemeral, right? It's gone. It might exist on your profile, but that's why I don't like social media. It's not evergreen. I want people to search for my content, right? If you type FPGA into Google, right? I want people

to land on my video every time, not it's gone in social media. So that's why I don't want to spend a ton of time to make a video that hopefully goes viral and 100,000 people see it, and then tomorrow they're on to the next viral video. And you've got to keep feeding that, right? It's not – Constantly. You've got to keep feeding that. You do. But it works for some people. It absolutely works.

I'm not saying it doesn't work. I just hate it. Good. Yes. I mean, I didn't understand how much work social media was if you weren't just using it as a way to... Complain. Deal with excess thoughts. Sorry, that's what I used it for. Well, yes, but I usually just, you know, the things that I didn't know who to say them to, I would just spew them to Twitter and get randomness out there.

And hope they didn't know they were directed at them. It's all subtweets. This is hard. I mean, the whole, you have to spend a lot of work on it. It's hard to hear as an engineer because I want to spend all my work building things. The cool stuff. Yeah. Yeah.

So are there people who like marketing? Yes, they're called marketers. Oh, I'm dying. Oh, my God. Yes. Yeah, you can get a marketing degree. You can get a, you can get a marketing degree. You can, you can do marketing. My, my experience is, is marketers will sometimes struggle with understanding the engineering audience. It's, it's, it is a very different audience than what a lot of marketers may have

experience with, if that makes sense. Like we talked about earlier, a lot of engineers I know are the first to run ad blockers because they don't want marketing. But you can absolutely market to engineers if you know what kind of content they consume, right? They want to listen to Embedded FM. They want to watch the how-to tutorials or things like Hacksmith or probably like Physics Girl or some others who are fantastic YouTubers. And they're educational too. They teach you these technical things about the world. Engineers engage with that kind of content.

So knowing that, you can craft content targeted at engineers. And that's what I've been doing for a while. Mine's more educational than it is entertaining, but entertaining still works. You just have to speak the language. And finding somebody who knows both the marketing side, how to do all of the things in marketing, and how to talk to engineers, that's not usual. Do you like to learn things? Do you like puzzles? Do you really enjoy blowing crap up? Please come listen to Embedded FM. I watched that in a heartbeat.

Blow stuff up, Dad. Listen. What you said about them not knowing, not them, about what some marketers not knowing about how to market engineers, it kind of got a real good view of that when I was at Fitbit

because sometimes marketing would turn their view inward and at all hands meetings they'd produce these nice videos for and there would be directed ad engineering okay here's the product you just worked on here's how we're selling it and here's this this sizzle reel of all this stuff and we'd all just be sitting there going whoa no no that's awful this is this is please please make this stop um but it probably worked outside the company um yeah so yeah it's it's it's it's a it's a difficult engineers are difficult people yours are a difficult people oh that's nice sounds like we're all speaking from experience here you mentioned content creation which i mean i remember telling something somebody that i was

an engineer and then i mentioned something about the blog and then i mentioned something about the podcast and they were like wow you're just a great content creator and i'm like no i'm an engineer i'm not a content creator. And I'm like, no, I'm an engineer. I'm not a content creator. Don't say those words. But you embrace them. And so they must mean something different to you. What do they mean?

What is it that non-me people think content creator means? I'd love to know what they mean to you, but I will answer the question first. To me, content creation is any sort of media generally put out on the internet. Blog posts, social media posts, YouTube videos. You know, like if I create a cat meme, that's content. If I write a 4,000-word essay about how this particular microcontroller is terrible, that's content. It's just the all-encompassing word for creating material to be on the internet and ideally viewed by others. I think the difference is

whether or not there's a secondary purpose to it. What do you mean secondary? Marketing. Oh, got it. So you're saying content creation as far as I'm creating ads that mimic something helpful. That mimic something helpful. That's it. Not the ones, I mean,

you have ones that are actually useful and then they're sponsored by various people. But there's so many times where it looks like it's going to be useful, but it's just an ad in the end. And I hate that. And that was what I always thought content creators did, is they basically got paid to promote something in a sneaky way. Got it. Okay, thank you for helping me understand that connotation because I think there's terrible content and that's what you're describing is terrible content.

I think especially engineers will pick up on that BS very fast, right? As soon as it's like, oh, do you have this problem? You know, 25% of people have these problems and there are ways to get over this. And you're like, and you read this like long article and it ends with, if you want to learn how to get over this problem, then pay us $25 for this ebook. And you're just like, I'm out. Oh God, why did I waste five minutes of my life? Is that a form of, you know, this is a squares and rectangles kind of thing. Is that a form of content? Sure. It's written material that exists on the internet meant to be viewed by others. It fits the strict definition of content. Is it awful and subversive? Absolutely. It's the used car salesman. It's kind of like saying the used car salesman coming out to you and talking to you. Are they using language?

Yes. Right? Like, okay. It fits into that technical definition, but oh, it feels gross, right? You want to take a shower when you're done. So I try to create content that is ultimately helpful. And what I call top of funnel marketing is I want to create content that's educational. It helps people. And is there a secondary motivation for selling something? Yeah, but it's so far down the line. My goal first and foremost is to help you. I really want to teach you embedded machine learning, right? Am I going to happen to use this tool called edge impulse? Well, yeah,

it makes the job easier. Am I going to use Arduino? Yeah. It helps teach me. It helps, you know, me teach this, this concept. Um, I have had people, you know, once I started doing freelance stuff, I have people, you know, hey, we'll pay you, you know, what's your rate to make a video for this product? And I turned down a lot of work because I don't want to just make a video selling their product, right? I want to teach with the best tools that I think are the good teaching tools, which is one of the reasons I really like working with DigiKey is because they have a vast array of tools. So when I went to teach FPGAs, I got to look through their catalog and say, you know what, I think this is the best tool, right? They're not trying to push a particular

product. But it happens to be sponsored by DigiKey and they own the content and it lives on their channel and they can, you know, gain followers that way. So is there a motivation to gain followers so that people can eventually stumble upon DigiKey ads for stuff? Yes, of course. But the stuff I create is first and foremost trying to teach and help. It just happens to be done through a company rather than through a university. Can you put the Edge Impulse TinyML on an AppMega 328? So what I like to tell people is you can run machine learning on anything that, you know,

any processor will run machine learning. It's just a question of do you have enough space? Do you have enough RAM, flash, and can the processor speed meet your timing requirements? A lot of what we consider machine learning now is really neural networks and deep learning. And so will

a 328 run a neural network? Probably. I mean, if you're talking like two nodes, yeah. Oh yeah. Is it useful? That's called linear regression at that point. Yeah, exactly. Can you run linear regression, you know, with a, oh my goodness, what is it called? A non-continuous activation function, right? That's kind of all it is. Can you do that on a 328? Oh yeah, easy. Is it going to train it? Probably not. You can run inference. Is it useful a Cortex M0, so it's possible. You're just missing a lot of those really nice optimizations, like your DSP optimizations, that allow you to speed up inference. So how did you learn about machine learning? So this is an interesting one because I actually have my master's in it,

just I didn't call it machine learning. Your background is computer engineering with a master's in EE, and that's machine learning? Correct. No. So what my master's thesis was on was using something called hidden Markov models to classify RF signals. And so, yeah, it was actually pretty slick. And this was in 2010, 2011, prior to our current, you know, blossoming of deep neural networks. It was around the same time that I think Google Brain was doing their stuff with collecting all the images to classify cats. And I didn't, we didn't even call it machine learning. It was my advisor at the time just said, hey, we're trying to do this thing where we're classifying RF signals, and we think hidden

Markov models will do it. You know, they were like, oh, don't worry about neural networks, right? We were at the end of that winter, that machine learning winter. We just didn't know it at the time. So I learned how to train a hidden Markov model using either Viterbi or the BOM Welsh, and I can't remember which one was trained. I think Viterbi is their forward propagation. This was like 10 years ago, so help me forgive my ignorance. I'm sure somebody will be like, well, actually, and tell us what the terms are. But we trained it to recognize different RF signals based on, I think, encodings. And it could look at like your frequency spectrum and say, oh, you know, we think that's QAM, however you pronounce that, like quadrature, whatever.

We think this is, you know, single sideband, blah, blah, blah, different types of modulation and encoding. And it was like four or five we could do. And while that was proven at the time, I was actually writing CUDA code for NVIDIA cards that would parallelize all this and running tests to see how fast we could speed this up and taking the algorithms and parallelizing the algorithms and figuring out, okay, can we take, you know, big O of N squared to like big O of N or big O of log N and making the algorithms faster that way.

And it turns out like just doing one or two, not so great. But when you start talking like, oh, let's run multiple models against this, like a forest or a tree, much better. I'm sure there's plenty of libraries and other frameworks that allow you to speed them up even better now. CUDA has blossomed. You can run TensorFlow on top of CUDA, and it's fantastic. So that's what I was playing with at the time. And the funny thing is, throughout my entire thesis, throughout my entire master's,

not a single mention of machine learning was used. The term was just not used because I was in the electrical and computer engineering department. That's not machine learning. We're just matching these patterns. It was pattern recognition. It just also happened to be machine learning because we were training an automated algorithm that would update its properties to solve some problem. It met the definition. It just wasn't a neural network. Even when I was reading about neural networks in college, I don't think the term machine learning existed for that. And I mean, I took an AI class in college, but it was AI winter, and it was not really...

I mean, we talked about it, but we talked about it like history and like maybe someday but not in college the apple 2 had just gone off for sale by about three or four years so there wasn't much going on i think i liked you for your 386 it was a 486 dx 250 i'll have you know. Did it have a turbo button? Of course it did. They all had the turbo button.

Yeah. Okay, okay. Gotta have the turbo button. How did you learn about FPGAs? I knew them since school. I learned about them when we were doing computer architecture. It was like sophomore year. And we needed to do,

we designed a 4-bit processor as a group project. It was, I think, based on MIPS, if I remember what we had to do. And this was like 2003 or something at the time. And we started learning about FPGAs, like, oh, we could write it up in Verilog, and that was how we turned it in, and we could run it on a simulator.

But our group actually was like, oh, can we borrow an FPGA board? Because we wanted the extra credit because that's the kind of students we were. And we got it to work. We got our processor to work on an FPGA. But honestly, after that, we never really touched them in school. And I know that there are a lot of great engineers who specialize in them. They create hardware language for them. That's what they do. And FPGAs have a certain niche and they're very, very popular.

And it wasn't until many, many, many years later that I'm sitting at SparkFun and I've had this question a few times. People come up and they're like, oh, I've heard about these things called FPGAs. What can you do with them? And my super snarky answer that I never tell people, but for some reason I'm going to say on this podcast, is what would go through my head is

if you have to ask, you probably don't need an FPGA. Yes, that's what I say to neural networks most of the time. Well, maybe I can change your mind about neural networks, but I still stand by that for FPGAs. Yeah. So what I, what I realized is that people really want to know what they are. They want to tinker with them. And there's, there's some good content out there, videos by people who know FPJs a lot better than I do. But I found that there were, they were generally fairly disjointed and taking you from like, I don't know anything. And they would like cover the super basics of like what a cell is and what a lookup table is. And they'd show you like, okay, let's like, not even really blinking a light, but like, let's do like a simple adder or a simple state machine. And then they would jump to just something like massively advanced. And I'm like,

I feel like I still don't understand Verilog or VHDL from watching your video series. I'm like, okay, I'll start kind of with what they had and I'm going to build the building block so that you can go watch or engage or read books with the more advanced stuff. And that's where I decided to put together this FPGA series for DigiKey. And yes, I had to reteach myself Verilog because we probably touched VHDL or Verilog. I don't even remember what we did in school. I mean, I'm talking 20 years ago at this point. So I had to reteach myself that, and that was the goal. It's like, okay, I want to make a series that actually helps people or people who haven't seen them in a while, you know, learn them. Because at least for me, schools didn't do a good

job of teaching FPGA. They taught computer architecture and the theories around that, but not how do you implement this well in hardware. Did you start making the series, start thinking about the series, and then have DigiKey sponsor you? Or did DigiKey say, we want some videos and we'll give you a pretty broad range of topics to choose? It was a collaboration effort. My time spending working with DigiKey was we would maintain this brainstorming list and we'd meet every other week. And we'd kind of go through and be like, okay, what's on the horizon? We try to figure out what's coming up the next couple of months. And something that was on there for a long time, for more than a year, was like, we should tackle FPGAs. And they're like, yes, yes, yes. And it was finally like, okay, guys, I'm going to do this. I'm going to learn, you know, reteach myself, Verilog, grab an FPGA kit. And I think that the

tooling, the other big thing is the tooling was finally there to make it accessible in an open source, easy format. So you don't have to download this massive eight gigabyte IDE with like buttons everywhere. And you're like, oh, this is proprietary proprietary and it's, I don't know where to start with this. And like, could I teach that? Yeah, absolutely. But it's like, then I'm teaching Xilinx, not really general FPGAs. So I found an open source tooling set that allowed me to teach, you know, let's focus on just the Verilog so you can get your hands around that. And once you kind of understand that, yeah, jump to the more advanced tools if you want, but it was really also the tooling that was finally there. And it's still kind of beta-ish, but it worked. This might be too delicate of a question, but did they pay you

as an engineer or as a content creator, which isn't usually as much? Oh, you're asking about levels. I won't talk about specific numbers because I'm not, I was not, first of all, I was not an employee of DigiKey. I was a contractor. And so part of my negotiated contract rates with them included things like I'm going to pay an editor to help me with this. Right. So I had some built-in costs. So it doesn't, how do I translate that to saying, um, what's my salary. Right. And I could talk about my salary, but then it's like, well, my taxes look different and an LLC looks different than this. And I've got pre-tax purchases based on my deductible. It's really hard to do an apples to apples comparison.

The numbers that I would try to break it down to is I generally tried to maintain something of an engineering salary because I considered myself an engineer first in some respects. Even though I like to say I'm both an educator and engineer, I try not to lose that technical side because I feel like a lot of people, once you learn a technical side and you just create content around there, you stay within that realm rather than going, okay, I need to learn how to do an RTOS because I haven't touched an RTOS since grad school, and that was 10 years ago. But the technical knowledge is still there. I reteach myself this, and then it's like, okay, I'm going to teach others about this.

Could you have just an educator do that who is a great teacher but doesn't know the technical side? That's going to be tough. And vice versa, right? Somebody who just knows the technical side but can't teach very well, also difficult. So I, you know, because of that specialty, I will usually try to negotiate something closer to engineering pay ranges. How did you learn to teach? Let me see. This was probably, this probably started back when I don't know, second or third grade,

when my, my teachers approached my parents and said, you know, Sean is, you know, he's a good student, but he struggles with, um, public speaking. And sure enough, like I, like, you know, anxiety, sweats, like, like blanks. Like I remember one, one talk that I had to give in like fourth grade or third grade or fourth grade. And they brought out the camera, which was or third grade or fourth grade. And they brought out the camera, which was the worst thing in the world. And I just couldn't remember what I was supposed to say. And I just kind of like mumbled blankly into the camera and like, they like played it in front of the, in the library at my elementary school. It was like, this is the

most embarrassing thing I have ever seen in my life. Um, and so since then my parents worked with me and I'm, I'm super privileged and super lucky to have such great parents. They worked with me to to to help me. Right. They, you know, like, oh, I have to give a speech tomorrow for school. And this was like a book report. Right. Like really basic stuff in like fifth grade. So they would help me like, oh, let's do slides, because in 1995, slides weren't a thing. So my dad rented like a slide projector. He had one for his work and we like made slides, which was wild at the time. Um, so he taught me like the tech behind it. He also like made me practice in the mirror and then practice in front of them. And like, I would

spend three nights doing this until I could recite it. Um, and that helps build a confidence of it at an early age. And, you know, giving a talk in front of an audience, I still get nervous. I, you know, I still get the butterflies in the stomach stomach. And once I kind of find a groove, I'm good. But the anxiety is still there around public speaking. And since then, since early elementary school, I've always enjoyed doing the speaking. I've enjoyed practicing it. I would always be the first in class to get it out of the way so I don't have to worry about it. But I'm like, yeah, I'm energized. Let's do this. Let's just nail it, get it done. So I don't have, I'm not the one waiting until the end because then the anxiety is worse when you have to wait to give a talk. So it was really like started really, really early because I was first terrible

at public speaking and then got better, got better. I did Toastmasters when I was in Boulder. That just helped nail a few speaking things. I still stumble with resets is the thing that I still have trouble with. So I usually edit those out of my own videos. And I'm guessing Christopher will probably edit those out of some of these too, but no big deal. Sometimes ums like I just did there when I'm trying to think, but I work on not doing as many of those. In addition to public speaking, I also started teaching swing dancing when I got involved in it. So 2010, I started swing dancing. I want to say it was probably when I moved to Boulder. So 2013, I started teaching it, even beginners. And I fell in

love with the routine of it. Every Friday, I'd show up and I'd teach with somebody basics of swing dancing. I loved teaching beginners. It would take them from nothing. A lot of these people did not have any dance experience. And my goal was within an hour, make them feel sort of comfortable doing something on the dance floor. And the key there was teaching the same lesson over and over again. And we had some plants in the audience, people who didn't

want to take the advanced lesson or wanted to learn how to teach. We put them in the audience and after the lesson, we would take them aside and go, what did we do? Well, what can we improve? And we would take that. And after doing this like a dozen times, we had our beginner lesson down and we had, we had got to the point where we had a hundred people in these beginner lessons and it would take up like half of a basketball court because we were doing it in the CU Boulder gym. And we would just nail these lessons over and over again. And I got, um, it was a lot of fun teaching and I got involved in doing videos at the same time with spark fun, doing my first video and working on getting more comfortable with, uh, camera work. Because if

you watch those early videos, I am so nervous. You can probably see me sweating and I am talking a lot faster than I am now. And it was awful. I still go back and watch them and just, oof, you know, nine years ago, I've improved on camera work. And it's just, yeah, cameras were frightening to me. I like how you had a problem and it became a career. I mean, it's kind of amazing. Yeah, what I find is a lot of people, that's a story I hear over and over again, right? I have a speech impediment or I have a learning disability or something like that. And they work so hard on it that they become really good at whatever it is or teaching it or something that it somehow becomes part of their career. It's an identity for them.

And the same for me. So back to machine learning, what is the best intro or hello world or blinking LED projects to introduce someone to machine learning on devices so when you say on devices like like microcontrollers embedded systems i'm assuming it applies yeah embedded fm it's got to be right um so the the basic one um especially for edge impulse is gesture recognition and it's it's a good one. It's something physical you get to do, right? The idea of like the magic wand. I wave a board and make a gesture and it goes, oh, you made this gesture. You waved or you did back and forth or it was just sitting there, right?

A little bit trivial in the sense of what am I going to use this for other than, you know, making a Harry Potter style magic wand, which is fun. I've seen some fun projects with that. But, you know, what problems does it solve outside of, you know, cosplay or art? I'm not super sure, but it does demonstrate kind of your blankie. The one that I personally like to use is keyword spotting. How do you get your ALEXA device to recognize you when you say something? And I won't say it because I have one sitting right here. But that's a really fun demo. I think that brings together a lot of embedded concepts that keyword spotting kind of seems simple on the surface, right?

I capture some audio, maybe do a little bit of DSP to pre-process that to get some kind of features. I send that off to a trained neural network, and it tells me if it heard the word that I trained it to listen for. And it's a cool project because it does have applications beyond just waking up a smart speaker. I could yell at a machine to stop doing whatever it's doing as an extra safety mechanism. I can tell my phone to do things. I can, let's see, give directions to a robot. There are lots of things. I think keyword spotting has a little more use beyond it,

but it is more complicated, right? You start having to talk about, I need to meet timing requirements. And that becomes a fairly intermediate or advanced microcontroller or embedded system concept. Because now you're saying, okay, I need to fill a buffer. I'm sampling a microphone at 16 kilohertz or eight kilohertz. That's probably as low as you want to go for voice. And I need to fill a buffer. And when you think about it, that's a lot of data to fill a buffer with. And I have to be able to fill that buffer at the same time I'm performing DSP and inference. So now you're talking, okay, now I need to run a real-time operating system, or I need to bring in things like hardware interrupts with direct memory access so that I can fill a buffer while inference is being performed on the main process.

Or maybe it's a dual core like your ESP32. I have one core worrying about filling the buffer and it sends stuff off to another core that does the processing for you. That's why I really enjoy keyword spotting. But I wouldn't say it's blinky. I would say it's non-trivial. And doing keyword spotting really helps me grasp the embedded implications and how difficult it is to do on something like a microcontroller. That's interesting. I mean, the throughput problem is always one that kind of gets people a little mixed up on because the idea of continuous input and output and yet windowing and overlapping windows, it just, it is not as easy a problem as it looks. Absolutely. Yeah, and in this case, you generally have to use a sliding window to capture that data.

I have some listener questions for you. All right. Well, actually, the first one is not a question, but a comment that your Hello Blink show, which was your podcast, was fantastic. Why did you stop doing it? I really appreciate it. I love to hear that people liked the show and that they found it useful and or interesting. It was kind of a career decision for both myself as well as Harris. We did it for about a year and we had a lot of fun. We met some really cool people doing it and we're really happy that people are still enjoying it to this day, right? We've got some downloads that are still happening on the site. We have it up. So feel free to check it out. And it really was a focus on trying to help engineers or people wanting to make a product or software

people understand a little bit about the marketing and sales side, especially people who want to branch out on their own, quit their jobs, and create a product or a service or whatever it is, and market themselves or market their product, just to give them an idea of what that looks like. And we chatted with a lot of cool people who had done it or were struggling with it, and they could share their stories. And it was even more niche. We talked about how niche engineering is. That was even more niche in the engineering world. We didn't see a lot of growth. We have a few loyal fans and people who really liked it, which we were so happy to have. And we met great people on the show, but really it came down to me wanting to move away from just being kind of this marketing

strategy advisor. That's kind of where I thought my career was going. What is that a year and a half ago, two years ago to be, Oh, let's, you know, I want it to be kept on as a retainer to do kind of marketing training for how companies can create content and market to engineers.

It, it would probably pay very well. And I'm sure there's a need for it. I just really didn't want to get away from the technical side of things as, as every, you know, every, anytime it comes up in my own career, it's like, Hey, do you want to go into management? I usually turn that down because it removes me from the technical side. So I just figure out how to navigate my career to like grow in my career and avoid being

in management. That's been my like MO for, you know, since I started working in like 2006 or something, but you know, it was kind of a pivot for me. And it was also a pivot for Harris when we chatted and we decided to end the show. He wanted to move away from trying to just gather these one-off, um, clients and work more closely in a capacity that was helping people with the sales cycle for like CRM. And the idea of having a podcast and, you know, did the podcast have a dual purpose? Did it help both of our careers? Absolutely. Like, right. We get back to that conversation of like creating content to help us. And for both of it was, it was kind of a funnel to meet people, to have content out there that would introduce

us as like the subject matter experts in sales and marketing. And, you know, they would hire us to do these things and what we saw them hiring us for kind of pivoted. And we didn't see the show fitting into that picture anymore. Um, and it allowed us to pull back to focus on more of the things we wanted from that pivot in our careers, if that makes sense. Okay, a question from John Shook. The breadth of your tutorials is kind of amazing. How do you develop that scope of expertise? Oh, I really appreciate it. I have to say that I don't have a lot of in-depth expertise. I'm pretty wide in what I know as far as embedded systems go, except for maybe that DSP machine learning stuff. I've

been diving more into that recently. I'm just about done with that hands-on machine learning book, which has been really fascinating, but it is drinking from a fire hose. It's doing a lot of stuff in Python. But other than that, when it comes to FPGAs, other than what you saw in the YouTube, I haven't tinkered with FPGAs since college. It was really just learn enough to get to a few basic demos. And then I have kind of that knowledge now. I've created content.

I can always go back and reference that content. But that's it, right? If somebody were to ask me questions about FPGAs outside of what I showed in those videos, I would be very ignorant of it. It's really, I kind of have a beginner maybe touching into intermediate levels of knowledge around embedded concepts across a variety of things. I have a friend who's a FPGA developer, and I asked him about, you know, how do I approach, um, doing the double buffering to avoid meta stability? And like, he helped me understand that. Um,

so I lean on some, some people to help me understand the more advanced stuff that's out there and kind of same for our toss. Um, except I did tinker with our tosses outside of that, that class. Um, because like you kind of need to now with Arduino, if you're using some of the advanced boards and they, they abstract it a little away, but I'm like, oh, I can run multiple threads. Let's figure out how to do that. But some of the advanced stuff in our tosses, I don't know anything beyond what's taught in the course,

if that makes sense. So it's kind of broad for the sake of teaching it and creating content, but not super deep. I have not a lot of knowledge around things like software engineering practices. So, you know, I kind of stumble my way through continuous integration if I have to do a pull request for something on GitHub. I'm like, you know, how does Travis CI work? I don't know. I need those little checkboxes to show up. You know, hopefully my code's good enough. And that's kind

of all I know. How to set it up? No clue. And a question from Twitter from A-Ray. Do you have any predictions for the next eight years for TinyML or embedded machine learning? I wish I could say I had, you know, these amazing predictions about what the world's going to look like. Where the trends I see going, voice is huge. And that goes a little bit beyond TinyML, right? Right now we're relying on keyword spotting to do some of that for us. But the ability to talk to our computer, I think is really, really undertapped at the moment.

And I know that people are working on it. We have the smart speakers, we have Siri, we know what those things look like. But I think having more natural conversations with computing devices is going to be massive in the future. And a lot of that will require larger machine learning beyond just your embedded side. So on the embedded side, there are some areas of growth that I see. Vision is a big one, not just doing self-driving cars, whether you consider that embedded or not, but things like being able to detect if somebody's in frame.

So we have a camera, you know, your doorbell cameras, a lot of them can do person detection now. That's a lot of that's probably being done on the device itself. I don't think mine connects to the internet and can it see a person? Yeah. It knows when there's a person at my door. Um, and a lot of that's tiny ML. You can also do things like smart buildings where you can identify people. I'm sure y'all have experience with those really awful PIR sensors that they try to replace all the light switches with. Yeah. You're laughing. You know what, exactly what I'm talking about. And you're sitting, you're trying to work late at night in the office at like 6 PM and the lights keep going, turning out. You have have to like get out of your chair and wave and jump around because those PIR sensors are so bad.

So, you know, something like a camera, while it might require more power, perhaps there's ways, you know, just take a picture a second or a picture every minute and say, hey, is there a person in this frame? And it's been trained and does some tiny ML to identify people. And it says, oh yeah, leave the lights on or make sure the building or this room is at a particular temperature. So smart buildings is a big one. The other big thing is predictive maintenance. That's big in industry.

That's kind of getting into your IOT, your industrial IOT applications, where it's pretty hidden from us as consumers. We always think about IoT, the smart home, and we really haven't seen much of that outside of the smart speaker, right? That was like the BS promise to us like eight years ago, right? It's really in the industry that's seeing a benefit from these sensors being on devices or these machinery or robots. And we want to know if something's going wrong so that we don't have to have somebody there watching the machine the whole time. A few sensors, like a vibration sensor, can tell us if a bearing is going out. And yeah, you have to spend a few dollars more to put a sensor on it,

and maybe you have to train it. But the idea of saying, oh, this robot arm is about to break, you should probably go maintain that and replace this bearing is about to go or whatever it might be can save you thousands or millions of dollars and prevent, you know, big accidents because a bearing broke or a motor gave out. And you can know before it actually happens. And that's a big area of study right now to figure that out. And that's been going on, like NASA has put out data sets to try to do this because satellites, right? You put something up in space and you're like, is it going to go, is it going to fail on us? We don't know, right? Do we need to go repair it? How much life do we have left on this, this, you know, giant camera or, or research station? And it's being researched.

And that's a perfect application for embedded machine learning, um, for identifying when things are going to break, um, whether that's sound, whether that's motion, cameras, whatever it is, that's another big one. And that's a ways away. And five years, I suspect we will see, you know, hopefully in two or three, we'll see more applications of that. But I like to think about, you know, what's going to happen in eight years, you know, that five to 10 range, better interactions with humans and computers, that's going to get a lot slicker. And things are going to start telling us when they're going to break before they actually do. Maybe not your blender, but like your car. Yeah. I mean, that makes a lot of sense. The car has many of those sensors. It's time for

those sensors to go into something smart instead of waiting to talk to the mechanic after it's broken. Yeah, and I would like, rather than just one light and like an error code, it would be great to be like, oh, hey, there's like a weird vibration on this thing, or like there's a knocking and it can tell you more about it

rather than just go to your mechanic. And I can see the computer interface because I have been thinking what I want is to be able to change to a different program with voice command, you know, Word, Google Doc, something that I don't have to move my mouse for that I could talk to. I'm sure you can make that happen. I probably could, although I don't know how to go to the app. Yeah. But yeah, I can see how computer interfaces are going to change, even in small ways like I want, but there'll be bigger ways too.

Yeah, in ways we can't imagine. That's the thing that I can't impress enough. If I could predict what it looks like in eight years, man, I'd be a lot wealthier than I am now. But I'm not really. I'm making engineering money. That's about it. But yeah, it's going to be ways we can't fathom. And that's where I think machine learning is so cool. It feels, to me, it feels like those early days of like, you read about early days of computing and people hacking on these big mainframes to invent things that, you know, they weren't intended for. And that's so cool with machine learning right now is people using them. The idea of like GANs generating content or generating deep fakes. Dangerous, but really slick. That's a cool application. And if people are interested in learning more about machine learning, you have some courses. You mentioned them earlier. Yeah. So I've got two on Coursera. One is Introduction to Embedded Machine Learning,

and the other is Computer Vision with Embedded Machine Learning, where we build on that first course, and we use the OpenMVCAM or the Raspberry Pi to train things like image classifiers or object detection systems. Are they expensive? Which things? The boards or the courses? The courses. No, they're actually free.

You can optionally pay to have a certificate if you want to show it off on LinkedIn, Which things? The boards or the courses? The courses. No, they're actually free. You can optionally pay to have a certificate if you want to show it off on LinkedIn, but they are absolutely free for anyone to take. There was a button here that said financial aid available, and I was wondering. Yeah, that's Coursera's thing. They put that out there. That's what they do. If there's any money involved in whether it's a certificate or you have to pay for the course, they slap that on. I don't have much control of that. And Sean, it's been really great to talk to you. Do you have any thoughts you'd like to leave us with? So the one career advice I can possibly give to people if they're thinking about things

is the idea of finding Blue Ocean. It's a good book, but you could probably get the idea of it. It's a book written by W. Chan Kim and Renee Mauborgne. It talks about the idea of, it's really a business book. It's a business and marketing book. And it's finding areas where there aren't a lot of people, there isn't a lot of activity. If somebody opens a McDonald's on your street, is your first thought like, oh, I should open a Burger King because McDonald's is doing so well. And it's like, well, you know, there's already a fast food restaurant there. That's now red ocean. Um, in the sense that like there's sharks in there, they're already getting at whatever's to be fed on. It's a terrible analogy, but yay marketers. Um, but try to, you know,

as long as you're still interested in, it's motivating to you, try to find areas where there's not a lot of movement right now. Um, you know, what long as you're still interested and it's motivating to you, try to find areas where there's not a lot of movement right now. You know, what has, they call it blue ocean, right? You're sailing, there's no sharks in the water, and, you know, go out and find areas that are potential growth that don't have a lot of activity. You know, don't open the gas station next to a gas station and expect to do as well as that first gas station, right? Because now there's two. It's a little bit of scarcity mentality, but the idea is finding areas that aren't. So I hope that helps thinking about career advice.

That's how I try to approach some things. I happen to be a decent fit for machine learning stuff because I studied it and I had a decent grasp of it. And I took Andrew Ng's course on Coursera, which was amazing. It is amazing. Oh, you took it. Oh, it's so good. I tell people to take that all the time as like a first step into ML. And I fell in love with it. I really enjoy it. And doing it on embedded systems, at least at the time and a little bit right now, it's still fairly blue ocean, right? There's not a lot of companies tackling this concept of throwing deep learning algorithms on microcontrollers. And it's weird and bizarre. But, you know,

there's market for it. There's potential things to come from this. You have to be careful. Well, no, I didn't. It's all about the features. But that is an entirely different show. And we should not keep you any longer. Thank you so much. Our guest has been Sean Hemel, Senior Developer Relations Engineer at Edge Impulse and Technology Marketing Strategist, Advisor, and Content Creator. Links will be in the show notes, or you can find Sean on YouTube, Twitter, and Instagram, as well as his website, seanhemel.com. Thanks, Sean. I really appreciate and I'm honored you all invited me to be on the show.

Thank you so much. Thank you to Christopher for producing and co-hosting. Thank you to John Shook for suggesting Sean should be on the show and to our Patreon listener Slack group for questions. And of course, thank you for listening. You can always contact us at show at embedded.fm or hit the contact link on embedded.fm, where you can also sign up for newsletters. And now a quote to leave you with from Bill Nye. There's nothing I believe in more strongly than getting young people interested in science and engineering for a better tomorrow for all humankind.