Revolutionizing Electronics Design with AI | Utilizing AI Ep. 12

AI isn't just for software. As companies like Flux AI are leveraging generative AI to act as a designer to bring your ideas into the real world, they enable a user to design electronics, creating the schematics needed for a contract manufacturer to produce it Flux. AI is also a community of users for support and ideas.

Will AI enable on demand manufacturing of just about anything we can dream up? That's the question on this episode of utilizing AI with Olivier Bran and Mattias Wagner. Welcome to utilizing ai, the podcast focused on practical applications of artificial intelligence from the Futurum Group.

Every Wednesday, we explore news and use cases of the way in which AI is transforming enterprise IT and the industries it serves. I'm your host Stephen Foskett, president of the Tech Field Day Business Unit here at the Futurum Group, and today we're talking about bringing AI into the real world. But before we dive into this discussion, let's meet who's on the panel today.

Hi, I'm Olivier Blanchard. I'm a research director at the Futurum Group, and my primary focus is intelligent devices. So anything that has AI embedded in it, from rings and other wearables to PCs, to the IO ot, to robotics, to cars, uh, is, uh, is the the stuff that I focus on.

Hi, I'm Matthias Wagner. I'm the founder, CEO at Flux. At Flux, we aim to take the heart out of hardware, and we're building the first AI hardware engineer to help go from a, from a prompt to any physical product you can imagine.

Excellent. And, uh, again, I'm Steven Foskett, the organizer of Tech Field a and the host of, uh, utilizing ai. So I am an IO OT enthusiast and all around nerd, as you can see from the background if you're watching the video.

Um, and of course it's pretty exciting to think that somebody like me without a hardware design experience could develop a specialized iot device just by talking and yelling at my computer. Uh, but I think, uh, Mathias, that's pretty much what Flux is doing, right? You wanna tell me a little bit more about what it is?

Yeah, totally. Um, yeah, I mean, I think you're spot on, right? Uh, you can come to Flux and, you know, just like if Cha pt, you can enter a prompt, you get a poem or some marketing copy outta that with Flux, right?

You can enter a description of a device you want design and manufacture, and then Flux will go and design that for, you'll source all the components, figure out the architecture, you know, ask follow up questions to nail down the details you haven't thought of, uh, and then go ahead and design it for you, you know, and get that manufacturing ready. And that can be really like, I mean, um, pretty much anything, uh, uh, I'd say like, you know, there's like simple devices like, you know, think controller for farming irrigation systems or so to like the kind of controller boards that's in vending machines, all, all the way to like, you know, uh, uh, the kind of electronics that go into a satellite and go to space, right? So that's kinda like the range of applications we've seen so far.

Yeah. So one of the questions I have for you actually, Mt. Is, is what, what level of proficiency in, uh, PCB design, uh, is, is this really for, can, can someone say a, a, a tech savvy, remotely tech savvy farmer, for instance, uh, who wants to build, uh, their own drones or their own equipment or their own like sort of sensor technology to do very specific things on their farm or in, in their ag agricultural, uh, uh, facility?

Could they just come to this and, and use flux to go from zero to complete design? Um, or do they need to have some semblance of, of training already or experience in that field? Yeah, great question.

No, I think you spot on there, uh, with the user segments, right? So that's exactly the kind that come to us today. We do have indeed Farmers who are building their own farm automation equipment.

And so I'd say like anyone with like a somewhat technical background can gr this today. Of course, what we're working towards too, right? It's like these, you know, if you think about how easy it's become for like 12-year-old kids to build iPhone apps, we wanna enable them to build their own iPhone road or an iPhone equivalent device, right?

And that's what aiming for. But today, yeah, it's mostly technical crowd. These are not, uh, uh, uh, uh, users who have necessarily designed A PCB before, but they have like maybe like a mechanical engineering background, uh, or industrial design background, right?

Or, or software engineering background, right? Um, and then, you know, we, we make this as easy as we can here for them to design a board and look, in some simple cases, you can really go from a single prompt to the fully finished thing. And in other cases, you know, take a little bit back and forth, you know, on being more specific about what you want.

Um, it it in that direction. So I think it's not unlike your typical like, you know, chat typical session, but like sometimes on the first prompt you put in, you get exactly what you wanted, and other times you have to nudge it a little bit into the right direction. Okay.

That's pretty good. So what type of, um, what type of equipment do you need for this? Is this just like, just any laptop?

Do you have to have minimum specs to run this? Uh, and, and I also assume that, um, just from looking at the website, right there is, there's certain types of files. So you have to be able to run some kind of design software on this, uh, like CAD or something like that, or is it all, uh, cloud-based and, and included in, uh, in flux, it's Batteries included, right?

So included it, it, uh, flux runs in the browser. You need nothing else as I can, you know, I always say you can go here from like the idea to the fully finished product, uh, uh, all within flux, right? So no, you don't need anything else.

Uh, in terms of specs. I mean, look, I think like any kind of machine made in the last five years or so, will, will do fine older one probably too. I think it depends a little bit on the size of project you have, like a larger, more complex projects gonna take more memory, and then sure, maybe you high end machine, but I think, you know, any average machine made in last five to six years will do fine.

Cool. Okay. So, um, following on this, this line, we'll, we'll switch in a little bit, but I'm just, I'm interested because I might actually be interested in using this.

Uh, and I don't have necessarily the practical skills required to do this, um, even though I have the theoretical skills as as an analyst. Um, but I, I saw on your website that, um, there's a, there's a human support element to this where, uh, users of flux can call on, uh, an active builder community, I think is how you phrased it, and also also engineers who might be on call. How does that work?

Is that sort of like a, a, a free floating community that can just use Flux as as sort of a, a meeting point? Or do you have staff that helps customers? What's, what's the model there?

Yeah, great question. I mean, to start with, right? Flux is a platform that's much designed like in GitHub, right?

GitHub is this like pillar in software engineering, right? For engineers to work together to collaborate together, to learn from each other and to use each other's stuff, right? All these like breads and butter kind of things, we need to make software, whether it's like an encryption library, uh, uh, server, uh, library, whatever.

You can find those in GitHub and use those and remix them and all that kind of stuff. And so we've built the equivalent of that for electronics, right? If you think about electronics, you need the, the, the, the digital representation of a semiconductor or so, right?

And somebody needs to put that in there. And so that's either comes from the semiconductor companies themselves that are represented on flux, right? Or that comes from users who do that, or, or semiconductor distributors, right?

So there's a big community aspect to that to create this, these like nuts and bolts that you need to build your stuff there. Um, so that's on like the first layer. And then of course, yeah, we have like a big Slack community, uh, where people post jobs, you know, the people look for jobs if they have questions or they brainstorm ideas.

And you know, I think this idea that everything is better if you do it with others. Um, and that's a providing there. And so there's other users there, there's power users there, and there's of course also like, uh, our team members are there.

I'm, I'm out there, you know? Um, and it goes all the way from like, you know, reporting a buck and getting that fixed to explaining to how something works to like learning what to build next for us, right? What's missing here?

Where are the gaps where people get stuck? Um, and so, yeah, I think, you know, we zoom out here, when we started a company, it was clear about what we were doing was really big and ambitious, and it was gonna take a long time and it wasn't gonna work if we wouldn't like work directly with the users from the, from day one, right? And so I remember, like, we started a company six years ago and we shipped the first, I don't even wanna call it a beta, the first thing we shipped three months in.

And it was embarrassing to demo that to users, but, you know, but we learned from that, right? And so that's like that spirit lives on, right? To be close to users and get feedback and, and, and do better.

So once you've made the design in flux ai, um, AI can't manufacture things. So I assume that you, uh, produce a, uh, production ready, uh, schematic that can be then sent on to a contract manufacturer, of which there are many now who would be happy to manufacture, um, you know, small or even large volumes of these things. Um, can you talk a little bit about how, uh, it goes from ideas to designs to actual physical product?

I mean, you held something up in your hand just a minute ago, I'm assuming you didn't solder that together. Uh, who did I try to avoid soldering these things these days? 'cause it's, it's tedious, um, because it's so tiny, you can't even see that here.

But, you know, it's like tiny, tiny components here. Um, so no, what's the process look like? Yeah.

So today how this works is like, yeah, we, when we, when you're done in flux, we give you the manufacturing files. These are ber files, some other format, and then any manufacturer in the world of which is 10,000 right? Can take these files and make this for you.

What's interesting in, in PCB boards is like that making PCB boards has been automated for a very long time, right? The whole form factor here exists because it's automateable. That's the whole innovation here, right?

Um, and so in that sense, can AI make this, I mean, it kind of does, right? A robot will actually assemble this, right? Um, and what we're essentially providing you is the, the files to program these robots on the assembly line to do this for you.

It's funny, um, I actually, to that point, I actually have, uh, the name tag in the front of my office at, uh, I'm, I'm at home, but at, at the office here, um, is a PCB that was, uh, created as a one-off, and it, and, and it just spells out my name in the traces. And, um, so you're, you're absolutely right. I've definitely seen this in action.

And of course I've got friends as well who have, uh, had, uh, contract manufacturers. But of course, um, what I hear from folks who've been involved in this is that there's often a, a bit of back and forth and fine tuning, you know, all that. Um, is, is flux helping with that whole process as well?

Yeah, it's a great question. Um, so yeah, look, ideally there isn't back and forth. You design a straightforward, they just make it, they say that you have it on your doorstep, right?

Ready to go. Um, but you're right. In some cases, uh, the manufacturer has some questions or feedback.

Um, today what you can just do, you can just copy. When they email you, you just copy paste that into flux and flux will fix that for you, right? Um, and, uh, you know, but, but of course what we're working towards tools like to integrating that too, right?

Because that feedback is of course, an important step of learning these, right? Learn what mistakes they made or what cost fiction and manufacturing and to not do that again in the future, right? And I think that's one of these big, uh, compounding effect things here, network effects you have in ai, right?

The humans of course, learn too, what's much more lossy process, right? Whereas like these CI models, when they learn, they tend to not forget that. Um, and so it's very effective.

And so you, you reach quickly here, like a, a high situation of like knowledge that prevents them from making mistakes in the future, at least for like that category of problems you work on, Right? So my, my next question, if I can, if I can get in there real quick, is, uh, I just got back from CES, uh, in January, and, um, surprisingly enough, the, the, the big theme at CES wasn't necessarily AI or A IPC or AI devices, it was robotics. Uh, even though I think we're still very, very early, early in the game, every single vendor that I talked to, even the keynotes from, uh, the big semiconductor companies from Qualcomm, intel, amd, Nvidia, uh, arm nxp, Texas Instruments, everybody was about robotics.

Whether it's robotic arms or delivery robots. Obviously humanoid robots are always the flashy thing that's shown on stage. Um, but it feels like there's, we're an inflection point with robotics in general, all form factors.

And I, I I, I look at your company, I look at what you're, the service that you're providing, uh, for, for designers and for, you know, small businesses, large businesses, and, and the, the power that you're sort of democratizing in terms of designing, uh, uh, even FPGAs. And I, I was wondering if you could talk a little bit about where you think you fits into, um, I think this, this transition into sort of mainstream robotics and how your company, how flux specifically with this, uh, this prompt based model can help accelerate that scale that, and make it more available for, for a lot more companies, whether they're startups or established companies that just wanna build their own robotics, uh, departments. Yeah, good question.

Where to start? Um, I mean, I think with robotics, but yeah, you're totally right. It's an exciting time because, you know, we have, like, for the first time now, these like reasoning engines, right?

Uh, uh, and, you know, for robotics, like the hardware we've had for a while, if you look at robust dynamics been putting out for the last decade, right? It's incredible stuff. But we haven't had, we didn't have these reasoning engines, right?

And so now we have those, and so it's like a new wave of innovation down robotics. And at the same time, by, you've seen it, but all the demos you see, yes, these robots can reason now, but they reason very slowly, right? It's like a watching, like a tour, you know, either a leave of, of, of, of salad or so, um, and I think that will get figured out, right?

I think you were very early and we're probably still a couple of years out from seeing like, like a truly humanoid, you know, latency kind of capability, uh, uh, robot. But I think it's gonna happen. Um, I think in the meantime, there's of course a huge opportunity for these like domain specific robots, like think about, trying to think of the company's name, but there's like a company that make like robot vacuums, but with the AI now, right?

And that's a huge leap forward towards what we happen is like Roomba generation of vacuum stuff, they're kind of like, it worked, but they're kind of dumb, right? They'll eat a UB cable, you know, every time. Um, and so I think data, like you're gonna see a lot here now, starting already now.

And I think flux is kind of like in the same category, right? We're like very domain specific. It's an AI model, an AI agent or robot, if you wanna call it that, to make PCB boards, right?

And it doesn't make that by being a human, human humanized robot that you tell to, and it sits there and sold this for you all day, right? It does that by being very special on the design and then being able to utilize the existing manufacturing capacity of the world, of the world economy, right? To then turn these designs into, into real products, right?

Um, and I think that in this domain, yeah, I mean, the thing is probably, probably couple more decades until you have human robots who could replace that capability. Human robots who could replace that capability. Um, but yeah, but, but it's in the end, it's, you know, flex is also just a giant robot.

Yeah, yeah, yeah. No, it's, it's, it's cool. Like I, I, I feel like you're, you're the right company at the right time, especially with, uh, you know, how much easier you, you make it.

Uh, just before Steven asks you, uh, his next question, next, I'm wondering if, uh, how well you scale, let's say that everybody discovers flux, right? Worst problems to have, uh, and everybody wants to start using it and building their own boards and developing their own robots and their own systems, uh, or improving on existing ones. Um, can you scale well, uh, well enough to, to meet that kind of demand?

Or, um, are you currently structured where it might be, it might turn into a first come, first served, uh, kind of service? Yeah, great question. Um, no, I think the way we see this is this, right?

This, today there's a, a market of tens of millions of users in the world ready to adopt flux. And that's like mostly people who've like worked in technical fields before where that, again, they've before just used mechanical cat tools, right? And then just bought the electronic someone om or contacted out.

I think those is, that market's up for grab here now for a company like ours, right? Um, and then, but if you go all the way here, right? Then, look, if I can type in a prompt and I can get any product manufacturer, I can type in any idea, and I, and that's, and get this back within like 10 days manufactured ready to go.

Um, and we do this for electronics today, but, you know, why will we not also deliver the enclosure for this, right? The enclosure for this is pretty simple. We know where the plug, you know, where the heat sink has to go, we can make the enclosure for you.

And most enclosures aren't like, you know, a piece of jewelry like your iPhone is. Most enclosures are gray PVC boxes, right? Especially in industrial applications.

So that's, you know, that's not so difficult to do, but if you can do that right, then why would you still go spend two hours on Amazon looking for the product you were looking for, if you could just describe it and it got made for you. Yeah. Right.

Yeah. And so I think on that level, right? Yeah.

Then there's a market of billions of users, right? Uh, and let's look, that's a long road. Uh, but that's the, we're on.

Yeah. What, yeah, no, that makes a lot of sense. What About that?

So let's take that to the next, uh, the next level. So you're talking about designing PCBs here, but, um, what about everything else? I mean, it's gotta have an enclosure.

Um, you know, what about batteries? What about, uh, you're building your giant robot, uh, you've got, uh, motors and wiring and you know, joints and, and whatever else. You know, what about screens?

What about, um, everything else? I, is that all part of the flux world as well? Or is that something that's handled differently?

Yeah, that's a great question. So, yeah, no, today the hyper focus just on everything that goes to make the sport, right? And look, and, and if display is mounted on the sport, that'll work, right?

Um, and, and we do this simply because, like I said earlier, right? This is, this is a form factor that was designed to be automated. It's meant to be fully automated for a hundred years, and then we're finally here.

Now, we can actually fully automate this, right? And so that's kinda like the beach at here, you know, that we've built out for ourselves now, uh, and we're doubling down on that, uh, for the, for the, for the coming months. But then, yeah, right?

I think from here we go to enclosures from, from there. We're gonna go to like, you know, something that has a put an enclosure and maybe motors or display or the batteries or a bunch of sensors that are not on the board themselves, right? Um, and yeah, from there, we're gonna go to full robots or smart toasters or, you know, you name your category, right?

Um, because there is like a huge, there's huge infrastructure in the world to build these things if you can deliver them the design files, right? Like the bottleneck isn't in the manufacturing capability. There's thousands of, of, of, of manufacturers just in China, right?

Who would love more business and who don't care whether they make five units for you one unit or 5 million units, right? They're just looking for more business. Um, and so, and so that's kind of like you, the, the, the, the need, you know, we're serving, right?

In the, in the short term. Yeah. I have a question about software real quick.

Um, so, and, and the answer might be very, very short. Um, but essentially, right now, obviously this is really good, but this is also fairly new. I'm wondering if you like, where the limitations of, of your software, uh, and especially the, the sort of like prompt based, um, you know, design generation, um, that, that you have the AI working in the background, what are some of the limitations that you're working on improving mm-hmm.

For 2026? Where yeah. Where you're not as good as you'd like to be yet in, in some way.

And if the answer is no, we're great, we can, you know, everything is perfect. That's, that's a fine answer too. Um, but I expect that you probably have some things that you wanna improve on.

I'm just wondering what those are. Yeah, great question. Uh, no, everything's perfect.

I sleep wonderfully at night every night, you know? Um, no, no, it's a, it's a bucket with a lot of holes. Uh, that's the valid of it, right?

Uh, that's, that's the fun part. Um, yeah, where's falling short? I think, you know, the big issues here, uh, that we're working on is just recall, right?

So, look, it's not good enough if the model gets it right, eight out 10 times, right? Especially along of a chain of like thousands of, of decisions that need to be made, right? If you, along every step only get it eight out 10 times, right?

And at the end, you got it all wrong, right? And so that's something we're working on. Uh, um, and then the other thing is like speed, like doing that faster, right?

I mean, yes, you could argue, look, it's, it's a miracle that the, the model can do something in an hour that would've taken an expert weeks, right? Um, but if you really wanna wield this like a guitar, which is like, think about a guitar, right? It's an incredible tool.

It's like so intuitive and responsive, right? And playful, and you can discover, right? And think that the feedback loop is really fast.

Um, we think that that's kind of like what really amplifies, you know, human innovation and creativity, like fast feedback loops, right? Try something, get a response, try something new. And I think that's what we're trying to get to here, but flux too, right?

To be really like a, a aspiring partner and where you can really go quick and forth and play with idea and iterate, right? Because, you know, we've all like made things, whatever, we've written something or built something, it's all about getting into like an, an, an effective loop here, you know, of like making something, getting feedback, whether that's good or not, changing a little bit, trying it again, right? And that's what we're trying to get to.

Um, and then, you know, I mean, with the third site would be much more boring, is to just support much more manufacturing processes, right? If you think about PCP boards, like if you wanna make, even if you wanna make an actual iPhone, right? An actual iPhone is like a thousand phone components, 12 layers.

It's like a very high density design, and you need to support like a bunch of manufacturing processes to make a board like that. And we don't have them fully covered yet. Or like at the level where you could actually effortlessly make something like an iPhone, right?

Um, and so that's what we're working on, Right? No, those are good answers. Answers.

That's What keeps me up at night. Yeah. Yeah.

Thanks for being candid about that. 'cause he could have just basically said, no, everything's good. Um, a a question about that.

So in, in a past life, I was a, a product manager. And, and so I, we, I helped develop, uh, new products and, and upgrade old ones. And, and I remember, I think it was an ideo, uh, tenets, uh, ideo, the design firm, right?

From, from, uh, the, the nineties, um, that was, uh, fail as fast as you can or something like fail fast, you know, uh, succeed faster. And this seems to me you talked about something that would've taken a designer weeks, just a mere hours with this, and that's how you're, you're shrinking that, that time envelope. Um, I wasn't thinking necessarily, when I'm listening to you talk about this, about the finished product, I'm thinking about as, as this former product manager, the prototyping process of all these different iterations.

Like, I have an idea, I wanna build this, um, I wanna create a working prototype as quickly as I can so I can test it and then see if that's really what I need, or if I wanna add some features, make some changes, and then take what I learned, what works, what doesn't iterate, iterate, iterate, iterate until after two or three, uh, different iterations or maybe 15, I finally arrive at a manufacturer, uh, tested prototype that works and, and that I can fairly quickly turn into a production, uh, a production ready product. So to me, in, in, in all of this, one thing that we haven't talked about really is, is this process of either failing quickly or learning quickly, uh, and getting there faster through these prototype iterations. Do you think, um, that is still an old school way of doing this?

Do you think that your tool helps get to that finished product with fewer iterations? Or is it just, you know, faster iterations, uh, to get there? Not less necessarily, but just getting there faster?

It's a great question. I think if you look at like AI coding tools, which I would say is probably like the bleeding edge of AI right now, the process has to make, software has drastically changed in the last 12 months, right? It has changed more than a change in the last 40 years, over the last 12 months.

12 months ago, if you wanted to build a feature in like, some piece of software, it would probably start with like a conversation, a whiteboard exercise. Your designer would throw some mockups together, and then you maybe do some user testing with that. Eventually you would get somebody to implement that test that, right?

It's like a lot of steps in the process. And if you look at like software teams like us, like work now is, we skip all that, right? Somebody has an idea at 2:00 AM in the morning, right?

They typed the idea into one of these coding agents, and the coding agent would just build the thing into our actual product, right? And on Monday morning, they just show off that working thing in the product that's like ready to be shipped and Yeah. Right?

Yeah. And make it much more responsive and intuitive, right? Again, like going back to this guitar example, right?

Just like a guitar, if I like pulled a string and then had to wait five days to get like the sound back, you know, that would suck. You know, like a guitar would not be as popular as it's today if that was the case, right? It's so popular and, you know, adopt and, and fun because it's so immediate, right?

And it's immediacy, you know, I think we, we've seen software happening now, right? And we're gonna see that in half two now over the next 12 months. Yeah, no, this could, this could become addictive, um, for Yeah.

For tankers, right? Yeah. It's fun, right?

It's, look, it's fun because you can try so many things right before, right? In this like linear sequential world we were in, I had to have an idea. I had to like, kind of spec it out, try it out.

I could only do one thing at a time. But that's another thing with agents, I can now try 20 ideas at the same time as these ideas come, I just drop the prompt and then an hour later I check back in where, where it ended, and then look, maybe it went nowhere. That's fine.

No, I don't care. It's just a random idea. Maybe it's actually amazing, but then double down on that, right?

And that's like the power you get here now. And I think in Harvard it's gonna be amazing because you know how expensive it's to run one process. Like you can't try 20 different things, right?

Because there isn't enough time and money in the world, right? To do that. Even like on at large companies with lots of resources, like you think of Apple here or meta making hardware, sure.

They maybe have like four, five different teams working on different versions of the same product or idea, right? Uh, with ai, they could be working on like hundreds, so thousands of different approaches to the same idea, and then pick the winners or mix and merge the winners, right? Um, and that, and that mind boggling speed too.

And so that's kind of like the elasticity and, you know, immediacy we're working on, On. Yeah. No, this is, this is very Tony Stark in a little bit, right?

And just kind of Oh, For sure. You know? Yeah.

No, no, this is exactly, I have a screenshot of that in our pitch deck for investors, right? No, no, you're spot on, right? Yeah.

Really, I think this is exactly like the kind of future that's gonna be real within a year. Yeah, no, it's great. And it's gonna be available to everybody, right?

That's thing this gonna be like, like Tony, like in the, in the Marvel universe, only Tony Stark has this, and that's why he's the Ironman and has all these things. But like in the, in the, the, the future of a building, everybody's gonna have access to this, Right? Which means also that you're, you're sort of flattening a lot of the moats that keep some companies with all this expertise and all this investment, uh, sort of in the lead, you're, you're making it much more accessible to startups or individuals or, or even universities, uh, who want to really innovate, uh, yeah.

In, in That space. You know, people always ask me who we're competing with, and, and they think of the legacy tools here, and I tell like, no legacy tools, software, right? I have like, my, my favorite example here is like, we have a customer, they make vending machines, like for snacks and beverages, and they used to, before they started using Flux for a single vending machine, it took like four or five individual PCP boards that they had to like, buy from a distributor who bought it from a distributor, who bought it from a distributor, who bought it from an OM somewhere, right?

Had to integrate those under into a single machine on the assembly line, configured this wired up, right? Then in the field, one of these machines breaks down. You've gotta bring replacements for every single board, figure out which one's broken, replace that, right?

Um, it's workable, it's cumbersome. Now, fast forward that to them using Flux now, right? They have a single custom board met with Flux that does exactly what they want, no more, no less, right?

Um, the board custom pennies on the dollar because they're just paying materials now. There's no distributors on middleman that get a cut on the assembly line. You put one board into the machine, cable in, it's working, the machine stops working in the field, there's one board to replace, right?

So the total cost of ownership suddenly is like 100 of what it was before, right? Plus, you can make it exactly what you want. You're not dependent on somebody else to build the thing you want.

You can make it that, right? And that's the power, that's the opportunity. Yeah.

No, it's, I, I, I couldn't have said it better myself. So I think this is all the time that we have, so I really appreciate it, Mathias. Um, this has been really interesting.

Uh, and now I'm not just interested in Flux as a, as an analyst. I'm actually interested in Flux as a, as a potential practitioner. Like, I feel like I might actually be able to, uh, uh, to start dipping my, my toe in, uh, in this PCB design, uh, space, um, which I think is the point of this.

Like everything that we just talked about, I mean, throughout this episode, obviously this podcast, but also really in the last five minutes has been, uh, sort of encapsulated this opportunity of this intersection between, um, ai, browser-based AI that can, can basically allow you to describe what you wanna build, and as a companion, as an expert, it helps you build it and get from basically idea to manufacturing. Um, and, and I really wanna thank you for your time today in explaining this and also, uh, for your vision in building this, because this is the kind of application of AI in the real world, um, that it, that's, that's a lot more real than a lot of the other, uh, AI applications that, that we've heard about. Uh, and also it's ready now.

It's not something that we have to wait for six months, or two years, or three years. Um, it's available now, uh, right now. So I'll, uh, thank you again.

I'm gonna turn it to Steven. Um, thanks. Uh, and I, I hope that we can continue this conversation soon.

Yeah. Um, on that note, um, before we go, um, uh, Mattias, um, where can people continue the conversation with you? Where can they learn more about Flux AI and, um, will we be seeing you in the physical world anytime in the, in the coming months.

Months? Yeah, great question. So, look, you can find us at Flex ai.

That's a good starting point. If you wanna start building and start, you know, exploring what this, what this, what this new world looks like. Yeah.

Come there. Sign up. Um, where you can find me.

Look, you can find me on Twitter or LinkedIn, you know, just the me if you wanna get in contact with me. Uh, I'm out there. Uh, in terms of physical world, great timing.

You know, we've been remote for the last six years. We're moving into an office, right? So we have an office in San Francisco and downtown on Second Street.

Um, so, you know, we'll, we're aiming here, like as we're moving into also host a bunch of events here, you know, uh, and turned us into like, kind like a maker space if you'll of the new age, right? Uh, where we together here figure out how to, how to build this. And, and I think that's a big thing.

You look, we're extremely early in August. This is day one, right? And if you're excited here about exploring this, definitely come and try our product.

But also, like, if you wanna get involved here, get involved with the community. Look, we're hiring any role you can imagine. We're hiring for it, right?

You also wanna be party and help us build this. There's a lot of stuff to be figured out. Um, we're really excited about it and we think now's the time, so let's do it.

Excellent. Yeah. Well, hopefully we can see you.

Uh, we are out in, uh, we California for Tech Field Day, fairly often in the Bay Area. So maybe we'll see you at one of our future, uh, tech Field Day events. Um, That'll be awesome.

Olivier, uh, what are you working on these days? Uh, what can we look forward to hearing from you? What am I not working on?

Uh, robots apparently, uh, but any kind of physical ai. So we have reports coming out fairly, uh, uh, fairly regularly. Um, whether it's, uh, a market forecast for devices, PCs, et cetera, or, um, uh, semi-annual IT decision maker surveys that, that look at how the enterprise is looking at, at investing in, uh, in AI and AI devices.

Uh, I attend pretty much all the conferences, or at least all the major ones. So you're bound to see me at anything that has AI and, and devices sort of like converging. Obviously, we just did cs.

I'll probably be at Mobile World Congress in Barcelona. Uh, and then, uh, many more beyond that. Where you can find me is on x, uh, formerly Twitter.

Uh, just look for Olivia Blanchard. You'll find me fairly easily. I'm on LinkedIn, and obviously if, uh, all else fails, you can Google me or look for me at, uh, the futurum group com website, uh, where I publish semi daily articles and commentary on tech.

Excellent. Thanks a lot. And, uh, as for me, you'll find me as, as FoST on most social media.

Uh, and of course, uh, as I mentioned, I am, uh, uh, a nerd. And so you'll find me, uh, dabbling with, uh, projects like Home Assistant and ESP Home, which I'm sure, uh, Mattias is familiar with as well. Um, and thank you everyone for listening to the Utilizing AI podcast.

Uh, if you enjoyed this discussion, please do subscribe on YouTube or your favorite podcast application, and consider giving us a rating and a review. This podcast is brought to you by the analysts and experts at the Futurum Group, where insights meet ai. For show notes and more episodes, head over to Text Strong ai, the utilizing AI YouTube channel, or the Text Strong TV app.

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