At the heart of an industrial revolution is an innovation that changes everything. Building AI Boston sees artificial intelligence as a renaissance. From the heart of innovation and the mecca of tech learning, we bring you AI for real people. A conversation for everyone. Owner UJ Guen is the director of computational design at New Balance, where he leads a team of creative and technical professionals who develop end-to-end computational design workflows and futuristic concepts. Owner has a PhD in computation with a minor in media arts and sciences from MIT and a bachelor of architecture from Middle East Technical University. He is passionate about rethinking part-whole relationships to advanced computational design innovation, and while his work has been featured in popular science and earned him awards and opportunities to speak around the globe, owner's goal is to empower his team and his company with value-driven, innovation thinking while attending to the broad history of computational thinking and making from touring to AI diffusion models. Owner, welcome to the show. Thank you for having me, Anna. Thank you. Oh, my gosh, friend. You're one of those unexpected finds, and I will say everyone knows I'm not a technical person, but you had me at quoting the humanities, and I can't wait to dive into this conversation with you. That's great. I think there's a lot of discovery between the technical and non-technical, I would say, which I'll gather in my mind, sure. They definitely go together. And what's fascinating about you is you have sort of decades of experience in kind of examining that human AI question, or human, I will say, machine learning question. But I want to go back. Since you love history and I love history, take me back to your own history. Were you technical? As a kid, were you interested in technology? Yeah, it's a long discussion. I think I always have this kind of like, the light line between what I really like doing because my mom was a painter, painting teacher. I always had that artistic, let's say, filter throughout the world, to the world, I would say. And then I was really technically inclined starting in early ages. I had this experiment set in primary school. So this all kind of started together. And then I think it just pretty much kept going in high school, college years, and so on. So I can't go into detail, but yeah, it started early. I'm curious about this kind of experimental set. Was that chemistry? Was it science? What were you studying? Yeah, it's a lot of like simple physics, I would say. I mean, chemistry was allowed, but to a certain extent, right, just to make sure that I don't like burn and blow up things. But actually, chemistry came back to my life in high school. At the time, you know, I was looking into organic chemistry, which is a college level learning. But yeah, all this was kind of like being combined through some chemistry Olympics and also looking into math and also trying to paint at the same time. Yeah, a lot of confusion, but a lot of discovery as well. No, I really relate to that. It wasn't until I studied Einstein that I understood I was doing that as a kid. I think what I love about your journey and we'll get more into exactly what that is. But I think one of the things that I've heard you talk about is that you probably from your mom were allowed to play. Oh, yeah, absolutely. Yeah, and that play is really kind of a key to your ability to be an innovative thinker. Absolutely. But play is amazing, right? So I think there are two things and history has been evolving on this like these two different things. People usually again, like categorize one is maybe play. So hands off like experience building the experience and learning from what you touch with what you break and so on. And the second one is also recording, right, which is in ways of like writing and reading, right? So that's kind of like the so it's like learn from the experience, but at the same time record for the next generations and the next generations can learn by reading. So that I'm just bringing that in also because I started like I just learned reading and my parents bought me a kind of like bag of books pretty much like 29 books, I remember. Wow. But I was also into that at the time, which also influenced, you know, I still keep reading I cannot get away from it. So I think it's fascinating. And you know, okay, so I get naturally curious. I guess that's probably where we really intersect is our natural curiosity. So books are great. But I think the intersection between the humanities and then you said that's let's talk about your degree because you came to MIT right more than two decades ago and you got this fancy degree. And you're an expert in computational design. I think just for our listeners sake, can you break that down in the simplest way. Sure computational design is so designing involves intentions, thoughts, and a goal that you're trying to go towards right. And the design object or the design discovery is where you're trying to go but it never ends. So there are multiple tools or ways of thinking as you do that. And if you are doing that through algorithmic thinking, and if you are writing software to get there and if you are using digital manufacturing tools and you know the emergent materials to make those discoveries. So I think pretty much where design thinking and computational thought and computational making meets is what computational design is. I'm an architect by training. So my bachelor's in architecture. So again, just thinking about human scale and making and building architectures on its own is a very sophisticated, I would say field because you have to learn too many things in a very short amount of time. So computational design it's on top of that right so you have to also learn from computer science and how computers work and what computers can and cannot do. So I had like multiple rounds of, let's say architecture jobs but also teaching at architecture schools. And then I was you know I got my masters as you mentioned it MIT and then I had the six years of break of teaching and you know making an architecture. And I was back to PhD for another five years. So those five years, much later in, you know, in life compared to let's say my peers. Let me again like read more, you know, simmer the thoughts and so on and so forth but towards the end I was a little nervous, you know about the next step so kind of like becoming a middle aged young man I would say maybe and also like feeling a little behind compared to other people in life with a PhD right so it's interesting. So new balance approached me and it was a big question because I hit next to nothing about, you know, footwear design knowledge, but we're interesting thing is that you can transfer all this learning and understanding about humans about making complex shapes about forms about design thinking from skyscrapers to shoes. Yeah, I wanted to take on that adventure. Without knowing how long this would go and actually it's getting close to one decade now so this is my ninth year at New Balance. And the biggest impact there was I think I always had this tendency to become an influencer like really drive a group of people instead of me contributing on my own you know making these magic tricks. I wanted to invest into the growth of others and have a huge impact across the company. So, luckily New Balance also wanted me to do that. So I think that created this crazy synergy for me to start as a sole contributor. I'm about to hire the sixth, you know, member for the team as of now. If you think about it in the industry is that it's a huge kind of like acceleration that you know it doesn't happen that often. So, yeah, yeah. I think it's fascinating. I think one of the things that I like so as a completely person, I think one of the most interesting things about watching your TED Talks or your, you know, your, your speeches and your. So interesting is just that there's this very human driven element of using AI as a tool. And, you know, I feel for you because I have advanced degrees in my family and, you know, I really related to that dilemma you had when you said you made this this leap into your career job or your career path when you were talking about I just like studying clouds I just like studying open ended questions not okay let's take it to something practical. But I think the thing that I get overall from you and distill down is the sense of positivity do you feel like AI is presenting more positivity in the world and challenge or fear and and how and and how is that relate to your day to day thinking. Yeah, this is a good one and I think it's presenting both right that there's a lot of anxiety about it. And also there's a lot of like positive things that may happen with it over time. So, which, you know, the short answer there is I think whatever we want to do collectively is going to happen. Right so that that's the like cold arms or like the press warning. I really believe in like our projection about life and things we do has a great impact on what happens next. So, from that perspective I think being positive thinking positively is is a crucial, you know, let's say activity, both mental and, you know, is an actionable as well. So one thing I just want to touch upon because you talked about like being human, right. When we face technology there's this always this uneasy feeling of thinking it as the other. Kind of true right so we interact with screens and keyboards and so on so these appear to be as natural as as they could be but they're not fully because we really you know have the creatures we move with thought but it's not only thought it's like the census right. One big challenge about machine is is is the is the sensing part of things right so I can talk to you easier than I talked to a camera right because you're responding to me even in the same place. You can kind of like use our kind of let's say the sensation. And yeah I think the step step one. Let's not get too anxious. Remember we are human right so I think it's kind of uneasy feelings also very existing in Renaissance. I give that example all the time because there are new ways of making the perspective emerges and there's this suddenly this frame that you have to put your picture through a you were you know like maybe painting more freely so you know it was a great opportunity but also a crazy limitation you know in what you're trying to do. I just remember that we remain as humans as of now. So how can we really be you know stick with that stick with the fundamentals and the value and bring the technology by acknowledging that I think that it's simple thought even makes a huge difference. No I think you're right and I think it's in having conversations like this I mean the goal of the show is to make other people feel like they're not left out of the conversation. But I think that a person like you that really studies it from a historical perspective can lend a lot to that conversation. I mean I think since we met I'm noticing all of the kind of the fun things about history that you know I gravitate towards and we talk about you know are we ushering in a Renaissance now to the people that know what's going on. Absolutely this is part of the dynamic that you live in every day and that I hope to open up to the rest of the world is like the people that are actually at the core thinking about you know not just designing a better shoe which full disclosure. I have a background in holistic health and this idea of 10s integrity where the whole body system is is key to performance and how we think about health. So I think a better shoe is always an interesting you know problem but in the grander scheme you know just this culture that you've been immersed in for over a decade. I hope that it spawns better better conversations throughout the world that this is not separate from you know we're all part of this mix and yeah I think you know where you are you're very lucky so what are you looking forward to in the future what gives you hope and what do you think the AI is going to be used for in terms of different solutions in the future. Yeah. I think again, just trying to approach it from a, you know, positive perspective is that there is a lot that we can solve and automate and help with almost everything by using these sort of technologies right. So touch upon Renaissance which is like 150 years is a run number. And then if you look at today what happened with AI is like actually the how the awareness of people right so people just got aware because AI got scaled or AI became available in a different fashion and flavor starting in 2022 which is Gen AI right, language models and diffusion models became accessible. But if you pause and look into this AI research started around like 1940s right. And then we were receiving digital electronic computing and interestingly AI is a part of AI is why computers exist. So researchers didn't think hey let's create something that automates stuff and then we can think about intelligence. So we're trying to model the human intelligence, hence computers came to be right so there's an interesting fact yeah and when we think AI we think oh they first found the computers and then you know, think about intelligence now it was a model of the mind computer as model of the mind which already has some sort of intelligence to that. And again like looking into the future, you can use any tool for making good things for humanity and not so good things for humanity right so a hammer can become a tool to build things, but also it's a heavy object right so it can end up some like harm like we can even harm ourselves if you're not using the tool in the right way right so this is an interesting concept. And I think same applies to AI. What we can look into is again look at collectively this technology if it is enabling us to collect data or use the data that we already have. We have already collected for a couple of decades now to build insights we were never able to before right. Yeah, so that's a crucial moment there we can kind of like localize these kind of like data and try to think hey, can we do anything in manufacturing can we do anything in, you know growing let's say better produce in a healthier way can we help people learn faster. Can you automate this and that and even have people have more longer holidays so they can just go for a cloud gazing and rest and be healthy. Yeah, I think those are all what potentials we can look into beyond all the, all the benefits of you know making everything like optimizing everything and you know being more creative, which which are obvious right so I'm not talking about them. No, I look I appreciate I know I gave you a big wide topic let's go a little smaller because I wanted that one of the articles I love that you wrote for the age of awareness was called using generative AI to gain knowledge insight and wisdom and design a better version of your life. Now you've got my full attention, you know and then you quoted Herman Hess who's one of my favorite authors so let's break this down a little bit. Is there something that you could bring down to the to the micro that you believe that generative AI can actually do for designing life. We can all understand. Sure. I think I think one thing that we can look into is what is being written what is being said about the tools right so, and that's usually and whatever becomes the hype or the main use of a tool. We can think from the angle of the you know the main distribution the bell curve right in the middle of that bell curve is what we usually do but it's not the most creative it's not the most valuable, you know area or it's not the most efficient so my question is always okay, how can we go towards this kind of like crazy valuable end of the bell curve or pull whatever we are doing there like in terms of efficiency creativity having a better life and just kind of like expand that right. That's an important point and one way to do that is again I will go back to your example about experimentation like play playing right. And one important I think example I can give there is, you know when diffusion models about image making became widely accessible people started making a lot of images, and also they started confusing what they do with the diffusion models, let's say making the image of issue or image of a building. I think they were designing right. Yeah, the moment there is okay you're not designing it you're making a representation of something that looks like issue or that looks like a building. And even if you're you may be using maybe prompting in a amazing way but we have to stop and think okay how much I'm learning from this process. And the easiest way to see that is give anybody these tools they will spend let's say 200 hours and they will wear out because there's more end to this stimulation is kind of like, you know that's throwing this throwing the scrolling the phone, and you're not really creating anything. Let's like take it to where our users can really relate let's go back to the shoe model if you will and then what's what's interesting to me is that we never seem to cease being fascinated by new shoe design and I think that's because. I mean I know the difference in my personal life between shoes that actually work for me functionally and feel different. And that's where my mind is able to compute the feeling of it what my body can tell with the senses. How does that figure into what you what you do at New Balance. That's perfect actually bringing the discussion like full circle right because at the very beginning we said sensations of human beings right so how can we discuss AI from that perspective. Same goals for shoes and computational design so there are so many data points that we can think about. And the domain I want the domain and context changes let's say that what is the purpose of the shoe is it trying to make you more comfortable is it trying to actually expand the let's say the life time of the shoe itself. That you're trying to make it more durable or is it really for an athlete like an elite athlete who already broke her record three times already and she wants to break it for the fifth time or the. None of the none of the previous matters is just kind of like augmenting her performance so she just kind of calls for that 0.5% better timing which is exactly how you win you know gold medals in the Olympics. Right. And I think at that point yeah so that we can work with data we can model for you know what we know in data trying to let's say find a solution whichever it is from what I explained. But also you cannot just virtually or like physically make the product and expect it to 100% you know perform in the way you anticipate. Because again it goes back like somebody needs to put it on somebody needs to feel it and somebody needs to perform in that so what the process in the process what happened is we took that person. We looked into all the sports sports data like right around her look into biomechanics in this scenario and then we took the existing let's say footwear and we tried to kind of augment it and make it better. But again there has been already in this process there has been computational filters of understanding someone coming up with data and numerical terms which is already not the reality so we kind of reduce the reality into numbers and systems. And we designed with that so then come the end of the you know process the shoe has to be worn and ran in so the solution for that is really working like one to one producing options giving us the you know benefit benefit of thought and say hey instead of one shoe let's make three different versions or four different versions. And see what the outcome is from those tests. So again in the test you can still use data right so we can kind of like measure the performance with this let's say these like four options. But there's one dominant factor that you cannot make measure which is what comes out of the mouth of the performance right right so the athlete comes back and says hey in number two I feel this way but the fourth is giving me this confidence. I don't know why so let's say she doesn't know why and our numbers are not necessarily telling that. So which is to bring again this is exactly the framework for one action numbers. And blocked you know on the wall which is what you throw on the wall. So you learn how to work with both and you have to experience actually that you gain through trying to merge these two two differences streams they appear to be two different things but actually they're all like combined in essence. So if you work this way. I think you can really make a difference. Wow. Do you foresee in the future a time when people can have shoes that are completely customized to their body. You can technically do actually you could have done that already. Right so the technology. Yeah the technology exists for a long time. The only problem is scaling right so it's not only customization let's say on the digital world which is you know involved sensors and scanners and generative engines like for creating models. That's all possible when you go to manufacturing side. It's the how you distribute the manufacturing with existing technologies. If you replace the existing technologies it becomes a huge operation. Yeah yeah. And also that you know where this happens is another problem right. So all this scaling and cost is totally changing. Let's say the plans or the idea of mass customization. I'm not saying it's not possible it's possible but again you have to invest in what you think is the most valuable. Well I think the most valuable part of this conversation friend is that I have gained new insight into how minds like yours work and then I find it relatable and also enjoyable you've really broken down a I am probably one of the more interesting ways and I just I'm glad and I give new balance a lot of credit for putting a genius mind like yours in the at the helm. I'm humbled I'm trying and I think try trying without stopping is one of my strongest you know let's say skills. Yeah not everything is perfect but I'm really I'm really happy and honored that the company but a new balance scale supports this kind of let's say you call the genius I'm going to say I'm a little lost but you know I can create value so I'll keep trying. I'm really thankful. Brilliant and great for the up and coming you know where where you didn't see the end of this road here we are and I think it goes towards that positive end of the scale so thank you for bringing all of this delight. It's a pleasure to talk to you owner. Likewise and I appreciate the opportunity to just share my thoughts with you Anna. Much much appreciated thanks. So any of you out there if you'd like to look in the links for the show notes we're going to include some of the highlight reels that I find fascinating from our friend owner and please come back and chat some more I think there's a second part to this conversation. Thank you for joining us on building a Boston stay tuned for more enlightening episodes that put you at the forefront of the conversations shaping our future.
