Hello and good day to you from episode 46 of our podcast series Project Breakaway. A metaphorical and a literal time in the day when we here at Predator cycling take some time away from working in the back shop to come and share with our listeners what we're doing, how we're doing it, what it takes to do it, our ideas, our innovative success stories and even our missteps and failures. If you find yourself with an interest in bicycles, composite manufacturing, out of the box design or even curiosities beyond, I encourage you to stick with us, settle in and learn a little. I'm Courtney B, co-owner and project manager of Predator cycling. And I'm here with my partner, Arm Goan, the other co-owner, CEO, lead designer and engineer and daycare daddy. Uh, yeah, so we, uh, if you hear a child, that's because there's a child here with us today. There is. You have a special guest. I'm sure he'll make an appearance at some point in the podcast. He is silently eating pizza and macaroni and cheese. Yes. But I don't know how long that'll last. Yeah, we'll see. So we'll try and uh get through this quickly. Um, first of all, I want to wish happy birthday to our number one employee. Well, yeah. Yeah. Happy birthday. Sir Charles Henry Widmore Bressler Goan, 13 years young. That's the dog. That is a mouthful. Uh, yeah, that is our uh faithful Charlie. Yeah, so if you hear a little tippy toppies, the dog's here too. Dog's always here. Dog's always here. He loves her basically. Yeah. Okay, so cool. So let's move on. This past Wednesday. You partook. Sure. Partook is still the past tense of partook. You partook. And an Nvidia sponsored live stream about their Omniverse platform. Yep. You can go to twitch.tv/nvidiaomniverse or youtube.com/nvidiaomniverse and they should have those recordings readily readily available. For those who did not catch it live. Yep. So. Um now we've talked about this this product Omniverse. Um a lot, how we use it, what we want to do with it. And this topic seems to get us a lot of traction here and more and more inquiries come in. And more interest comes in, the more we promote it or discuss it, I guess. To me, I feel like we talk about it non-stop. But I guess the more we talk about it, the more people are like, I guess catch on. Yeah. It's also it's an interesting topic because it's um. It it it's, you know, Omniverse is like this thing. It's like everyone's like, oh, it's like a program. It's like, yeah, it's a. It's a platform with a bunch of tool kits. It's an ecosystem. Um and it's got a lot of tools that come into it. And there's a lot of interest in it because I think a lot of times people have a hard time kind of grasping what it is. Um. And it it doesn't have a lot of traction yet in manufacturing and product development. Um, which ironically, I think is probably where it's most powerful. Um, or I'm just biased because that's what that's what we do. Um. But yeah, so I think we always get quite a bit of interest on it. Um. Yeah. So you wanted to do more of a deep dive. into the specific applications that you discussed on the live stream. Yeah, a little bit. Just kind of go back into it and just kind of like just kind of discuss what Omniverse is, how we use it. Um, because it's something that we get, I mean, especially when we go to trade shows and stuff. Um, I mean, obviously, we're usually going with Lenovo or Nvidia. So obviously that's the interest. But, um, um, it's surprising how many people that like you think should kind of know what it is. Don't know what it is. Well, no. Okay, so back up. Yeah. So the word on the street and it's maybe overused, underused, hyped up, misunderstood is metaverse. Yeah. So Omniverse is Nvidia's metaverse essentially. Yeah. Um, now there's meta, which is formerly Facebook, which I think people are more when they hear the word in tune with. Oh yeah. And what direction they were going with it with like gaming and avatars. And that type of alternative reality. Yeah. And then there's what we're doing with it. Yeah. With Omniverse that is more business and designcentric. Sure. Well, okay, so we're not doing gaming. Although gaming, movies and entertainment is a huge part of the Omniverse. It can be. Yes. That's not how we're using it. No. So explain more about that. Distinguish the differences that, you know, us normies who see metaverse. Yeah, absolutely. So like I think the big thing here is like what is the metaverse? Um, yeah, see, even Sammy doesn't even quite understand what the metaverse is. Um, but the metaverse is this idea where um, it's a, it's a twin of of reality. It's a place where, um, you have, um, models, um, you know, objects, meshes, um, that also have real physics. So like, you know, if you stick a ball in the air, it falls. Um, I don't believe in physics, so I think the metaverse is perfect for me. Well, kind of sort of. So like, I mean, we have this idea where, um, we have physics applied and we have, uh, um, real time, you know, Nvidia calls it ray tracing, um, visualization. So we can apply what your eye sees and yet how physics is applied to it. So we can take things like, um, digital tools like bicycles and parts and components and actually make this really cool, um, ecosystem where, um, you have the parts themselves and and you have physics and and and visualizations being applied to it. So, um, you know, that's what the metaverse is. Um, what's interesting with Nvidia is they've allowed us all these different ways to interact with it. So like they have all these different kind of apps that they've built and they've also built this kind of framework where we can build our own apps and our own integrations. Um, so like the same metaverse that, you know, Nvidia has built here in Omniverse, um, that we're accessing for manufacturing needs and like photo realistic renders of our bicycles is the same ones that you use as a game for building games because it's truly a a real metaverse. It's not You know, it's not a hype, it's not it's it's the real thing. You want to eventually cuz like a big I think a big thing of the metaverse is people think, oh, it's AI, it's like you need like goggles or something to put on your head to like Right. Which is game. I was kind of asking you. I'm like, I don't understand this. New like VR gaming. Do you just buy a headset? And how do you get the games? Do you download them? Literally somebody just asked me this the other day. I don't know how it works cuz I'm old and I need like a Sega Genesis to understand how things work. But Yeah, so like you can PlayStation just released theirs where they you can actually play games in VR. It's available soon. For us, like VR goggles and stuff would be like, you put it on. You're in a shop. Which I think people have seen like the factories and stuff. Factory work. Oh, I put a goggles on and now I can see a package move throughout the building. Like see through the walls and I see a conveyor belt. Or like Yeah. I know people they do like training now at like big box stores and stuff. Where you wear goggles. Like this is how you, you know. Yeah. Which doesn't make any sense anymore. Like this is how you become a cashier and you don't need a cashier anymore cuz there's a robot. There's anyway. Yeah, soft checkouts and stuff. But yeah, so like there's a lot of ARVR. Um, um, Yes. That's that's that's totally valid. And that's what a lot of people think of the metaverse. Is like, oh yeah, like, you know. I think like Facebook does that um or meta does that um uh surgery. Like surgery replica. Um, I had a game like that for the Wii. Commercial all the time that you see. Like practicing surgery. Working in the metaverse. I was going to say, are you talking about doctor? Wasn't it doctor? I don't remember what I remember. Because you used like the the Wii remote. And it was horrible. It didn't work very well at all. Well, it's first gen. But um, My point being that is that yes, that's one representation. But the other representation is is that um you can actually it's probably going to rabbit hole here. But like in the metaverse, you could actually run like synthetic data. Which is where things get really interesting. Like, you know. Nvidia's interest is because they run like the chips. And software behind like the Yeah. So it's it's They're not like coming out with games and stuff. They're coming out with the engines that run the games. Yes, they're coming out with an engine to build the omniverse. And the omniverse They're building the ecosystem. runs on um their GPUs. Yeah. Um, and in our case, we're running um all their GPUs inside of, you know, massive Lenovo hardware is how it works. So the slogan, we were talking about slogans earlier. I was talking about Duncan Donuts. I was like, the world runs on Duncan. So like the metaverse runs on Nvidia. Yeah. Yeah, it does. That's literally well, yeah. And hopefully it tastes better. Um, yeah. Um, yeah. Yes. Um, from our coffee conversation earlier. Yeah, so it's a revert back. But yeah, so I mean the idea here is like is is the metaverse itself is a very interesting thing. And and the applications for it are super interesting. And so like for us here, you know, we're taking products that we design um and prototype. And and make digital prototypes. We're able to take multiple different types of software um and connect that into the omniverse really efficiently. Uh, well, sometimes not that efficiently, right, Sammy? Um, but, uh, yeah, so like we can actually take data sets, drop them into Omniverse. Um, and we can basically see how they connect, build them out together and start applying, um, simulation and start applying synthetic data. So like I say synthetic data. Um, I think the perfect example of this is where we're trying to take this is when you look at our, um, arrow bars. Um, the the custom arrow bars. that we build and where we take, um, the the in Corey's position, we take multiple positions of Corey on the bars in different hand positions, gestures, um, angles. and then run CFD analysis on it. This is something that we can start. Um, we currently automate out in the in the in the program side for like fusion. Um, and we create the data sets and then run that in, um, CFD solvers. But we can also run that in a position where we're, um, dropping those model sets and some basic CFD data into Omniverse and then they have a couple engines like modulus where we can actually run, um, and create simulations. and and make variations of that and based on those simulations get new results. So you're really talking about this like generative style, um, development process that can actually happen inside of Omniverse. I mean, you know, we're not quite there yet, but we're definitely moving there pretty quickly. Um, so I mean that's it's definitely. I don't know, it's cool. And that's what's, I don't know, for me that's what gets me excited about. Um, Omniverse. Because, um, because it's this really cool platform, like we can kind of really build whatever we want on it. We don't have to just rely on, um, you know, the packages that are built by vendors. Like we can actually build. But there's a huge learning curve. That's kind of why they took an interest in us is because you're kind of like. using it as a, I mean not beta, I mean it's out, but like. Yeah, for application that other people are using it. For sure. So. We are and I think, you know, we're definitely on the on the forward edge of stuff like this because, you know, we work a lot with software companies and hardware companies to design and develop workflows. And I think our workflow is. I don't know, I think we got a pretty cool workflow. It's pretty unique. It's it's very digital. Um, so it makes, um, integration for things like this into Omniverse very, um, fluid. It's a very, um, fluid transition into into it. So. So what was the live stream? Like what were questions that were asked? Live stream is was a lot about workflows. So basically kind of the concept of like showing some of how we take data sets from fusion, um, from Rhino and we basically dump that into, um, into Omniverse create. Um, and we can visualize it and build it and build our assets. Um, it's also super helpful. because sometimes we get models or meshes coming in from, um, vendors and we're able to drop all that into Omniverse. convert everything to USDs and and kind of build a a. assembly. Also, I mean, the RF 20, when you think of it, it's not that big of a product. She's like, oh, you know. It's a bike. It's not that big. Um, but it's it's it's it's about 7,100 components that build that bike. I think you were talking about how like there's so many components, like each chain link and whatever you've designed and whatever. But like I think the topic was like getting each of those parts in the on the verse. Charlie, I know it's your birthday, but calm down. Um, Okay, anyway. But. But because I guess. Right. You don't you don't think about it. Right. Like, oh, I see a digital image, oh, that's cool, there's a bike and it's in a park and you're riding it and it's going forward. But you don't realize that you have to actually like code and digitize every single piece of that bike to replicate the movement. You know? Yeah. It's it's definitely. Oh, the little one's coming to you now. Uh, it's definitely a challenge. Um, but when you're. It's definitely a challenge. Um, but it's. You know, the part that's cool about it in Omniverse is that it doesn't see the chain as, you know, a thousand parts. It sees it actually as like three parts that are just closed. Oh, so that's literally the opposite of what I was just thinking. I thought it was literally reading like all those hundreds of thousands of parts. And somehow making it work. It is. It is. But you're saying it's grouping it. It does, but like. So for instance, a chain is I I believe it the chain for us is is like 1300 components. Um, but it's really just. Is it using like AI to like determine like where we like say you see a bike. A digital bike like riding through a park and now there's a curve. Does it has to like the engine has to like compute that curve. Or is AI computing the parts moving? So, well. Now you're saying it's about okay, so this is what's so interesting about Omniverse. Is that you actually have physics. I mean, I know you don't. I don't believe in it. But it has it. Um, so the idea being that when you have um a turn or a like. For instance, a wall. And the if you've animated the bicycle to go down, roll down a hill and there's a wall at the end of it. Um, when it hits the wall, I mean, it will collide. Okay, now let me reiterate my theory. I'm sure physics exists digitally in the perfect scenario. I'm saying physics doesn't doesn't happen in the real world because there's so many other things that happen. To ruin what your outcome. This is what you always say, hey, you drop something. The ball should do this. And I say, no, it never happens. It never does that. Something always happens. Yeah, so like. So, yes. You're 100% correct. So basically, I mean, I another way of saying what you're saying is basically, um, physics is is correct. It's just we don't always account for all the variables that are out there. In real world to to equate. But in Omniverse, there's a perfect world. It is a perfect world. But also it's interesting because you can connect Omniverse to the real world. And start trying to capture that data and understand what's happening. So like for us, like when we do test. bench testing on our product. Our simulation is done on the actual machine that we fabricated ourselves here. So we have a very close representation of what the testing machine should do and the results that should come from it. So we have a relatively closed loop system. And I mean if you look at the simulations that we ran on like on Corey for aero bar extensions, I mean, we were very close. We were plus or minus just a couple percent on on um on what his wind tunnel data and real life data did to to our simulated data. But we're Did you see his wind tunnel data? Did you see his wind tunnel data? I didn't see the actual data, but we got some benchmark concepts of where the the data sets are. Um, so um, you know, we we knew that we're on the right trend. And more importantly, we we knew we're on the trend because um, we um um, we we knew we're on the right trend because of the hard data we had from race results and the the the result data. Um. But the the um, my point is is that you can connect so many different things. So we can bring all that kind of data sets into Omniverse and lay that in. And because we have real-time physics, um, we can actually solve problems. Or you know, for instance, like think about something that's relatively complicated and hard to do in animation. It's like a drivetrain system. So like a bicycle chain. And the way the chain interferes with the pins and the outer links and inner links and a cassette and a derailer. Um, in Omniverse, you could you can use physics to drive one another. So there's collisions, right? That chain is colliding with the cassette and there's a there's an interference there. And it's turning the cassette. Um, those are things that Omniverse can do. Um. And that's a big ask. I mean, there's not very many softwares that can actually do that. Um, and because it is a real world, I mean, it's a metaverse. Um, you know, that's a power because we can take that kind of information. Um, and then basically build upon it. So now that bike is going down the hill. And now it's um, we're looking at how that chain is responding. And, you know, we can start analyzing more data sets. Um, if we're taking in real world data, we can actually try maybe an overlay the data on top of itself. Anyways, my point is is that it kind of becomes limitless and what we can do. Um. We can take so much information and and put it together. Um. And that's what's kind of cool about it. And, you know, I mean, we're fortunate where we can actually run all that locally. So, um, it makes it even cooler because it's stuff off. Oh, it's not just you. You know how to run it. I guess. I guess. It's not just like I could just log on and. Hey, look at me. No, it is. It is a little cumbersome to do and there's lots of data sets and connectors and things. But, um, I mean, even me that's like I'm not a developer. I'm I'm just a a software guy that designs and models. Just some guy with a computer. That makes things. Who likes to Google. I do. These are all truths. These are all true statements. Okay. Now there are a few more things on the horizon with Nvidia. Yeah. And just uh they just released a workflow video of their processes on their YouTube page and within their tutorial documentation. Yeah. Yeah. Mhm. So basically we gave them some digital models that they can utilize to showcase their software capabilities. And that's cool that they get to help us on projects and then, you know, in return we give them some stuff so they can. Yeah. Showcase their stuff for other people. Yeah. So we worked with um um the team over at Nvidia quite a bit. Um Craig and uh TJ and Mike have have have been huge players in helping us. And uh we worked with them to basically come up with an asset set that you can um use in Omniverse. Um and they're able to basically showcase on how we use like fusion um and Rhino and Omniverse together and bring in different assets from different places. And and kind of merge that together inside of um inside of Omniverse. Um. So it's pretty cool. It's pretty exciting. Um. Uh Craig kind of walks you through the whole thing. And he's. Um very talented modeler designer. So um it's cool to see his his uh take on all of it. Um. And yeah, it's it's a good little um series. And it really I think it it's a good case because it's actually like a real workflow. You know. It's not like. This hypothetical. Mhm. You know. Perfect storm. It's like a tangible object. That's like. Yeah. And it's real. And and it's not a small data set. I mean. That like I said, you're I think there's it's got to be at least 2,000 parts in that assembly. There's got to be at least 2,000 parts in there. Mhm. Um. So that's not a joke. To be able to to computate, you know. Um a lot of software would struggle with that. Mhm. Okay, anything else to discuss about that? I know we're going to keep this one a little bit short. Yeah. So no. That's. Because of all the people here today. Looking at you, Lil Ann. Um. So um. Anything about that before I move on? Yeah. No, that's it. It's there, it's online. Check it out on YouTube. Yeah. On. Twitch. Twitch. I don't think it's. For the young kids. You don't think they're recording us on Twitch? The the the. No, that recording is not on Twitch. The the one that Craig did the the two-part series workflow. Yeah, that's on there. And it's also on the I saw it. Oh no, is it? Is it on he's the youngster here. Uh is it on Twitch? Is it on Disney Junior? Um no. So it's on YouTube and it's also on the documentation on Nvidia's website. Um so some of the tutorial documentations. It's also on there. Um. And yeah. So I think that should uh should be helpful. Anyone that's looking at Omniverse. Look at that. It's a good data set. Especially if you're doing like actual products um and you're doing like Omni. You know, you're working in fusion. You're working in Rhino. I think it'll help you kind of at least understand the workflows that we're using. Um that can that could be um helpful. So. And our friends at Lenovo also hooked us up with tickets to the 3D experience world. Yeah. Here in Nashville. So. not to travel. Yeah. Uh to the Music City Center here in two weeks, Valentine's Day. It's going to be a great date. Oh yeah, date night. Um, so you love a good convention. You always say that. You do, you do. Your eyes light up. If it's interesting. If it's an interesting convention. Yeah. Like if we were going to Bravo Con, I don't think I'd be that interested. You may be. I think you would. I think you'd be interested in Beverly Hills. I think you'd be interested in New York. And definitely Southern charm. Anyway. That's just that's my area of expertise. But your area of expertise is 3D experience world. Which I assume means 3D software and other things. Yeah, so I think it used to be called SolidWorks world or something. Um, because it's I mean it's it's uh. It's like a design and computer guy conference. Yeah. Or girl. Yes. So they are uh the makers of SolidWorks, Katia, um, and what is it? Simulate, simulate, I think, is their simulation system. Um, that software that I don't use. Um, so I'm actually interested to see. I'm kind of. Yeah, I'm like. Totally anticipating. So it's like super cool and you're going to geek out. And you're going to be like. Oh, this, this, this, this. I'm going to be like. Yo, bro. Bro. Real it in. This is Michelin Star restaurant and we have a Taco Bell budget. Probably. Uh, I I've always wanted to use uh I've I've played around with Katia before. I've always it's always been an interest. Well, you know what, you can play around with it because I'm probably have the booth set up so you can play with it. Hopefully. I'll take a video so you can, you know, hold on to those memories. Uh, yeah, no. It'll be fun. I'm excited. I'm excited to see. Like I it's stuff that I never worked on, I've never I've played with it very little bit here and there. So. Uh, I'm interested. Uh, just to see what it is. Like I don't know. Check it out. And it's downtown Nashville, so maybe it'll be like a whiskey tasting too. Everyone loves design and whiskey, right? Yeah. I'm sure there's got to be some sort of catch down there. Hopefully. Anyway. Um, that's it. That's all I got. Anything else to add? No. No. Just working on the normal stuff here. So. I'm just going to chug along and hopefully next week there are no children here at the shop. No. No children. Okay, so we thank you for choosing to take some time with us. And we look forward to future breakaways. Look for us on Instagram and LinkedIn, Facebook, Twitter and in person here in Tennessee. We ask our listeners to please share, like and subscribe. We're available on all major streaming platforms. Thanks for listening, have a good one and find some time to break away.
EpisodeJan 20, 2023 · 23:28
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Project Breakaway with Predator Cycling
46: NVIDIA Omniverse Livestream Overview & The Existence of Physics, EP, 046
Join Courtney B and Arm Goan as they recap Arm's recent NVIDIA Omniverse livestream, offering a deep dive into this powerful platform. They clarify Omniverse's role as a digital twin of reality with real physics for manufacturing and product development, distinguishing it from popular metaverse misconceptions. This episode explores its applications in design, engineering, and creating photorealistic renders for their cycling products.
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