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In the City of Neon & Code, Your New AI Stylist Is an Algorithm
In the City of Neon & Code, Your New AI Stylist Is an Algorithm
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- [00:00]
Dr. Tamara Nall
Imagine an AI that can dress men better than they can dress themselves. One that understands their schedule, the weather and personality. Today on Lead with AI, I'm joined by Zohair Karut, the head of AI of Tailor, the AI powered men's clothing subscription service, redefining personal style from data to design. Taylor doesn't just recommend clothes, it curates confidence. Let's get into it.
- [00:34]
Dr. Tamara Nall (Intro/Outro Host)
Welcome to lead with AI. I'm Dr. Tamara Nall. In each episode, we will take you behind the scenes with visionary leaders shaping the future of AI across public and private sectors. Join us as we explore groundbreaking projects and innovations that are transforming industries and making a real impact on people's lives. Let's dive in.
- [01:04]
Dr. Tamara Nall
Hi, everybody. How are you? I am Dr. T, your host with lead with AI and we are always proud to start by saying we were number one in tech this year on Apple Podcast, and we also won the W3 award for interviews with podcasts as a gold winner. So we're excited and I'm really excited about having Zohar Karu with us, who is the head of tech AI at Taylor and my husband, as well as a lot of people in my network who are men are very fashion forward. And when I learned about Taylor, I was so excited. So welcome, welcome, welcome. Zohar, glad to have you here with us on Lead with AI.
- [01:47]
Zohair Karut
Happy to be here. Thanks for having me.
- [01:50]
Dr. Tamara Nall
Absolutely. So I'm going to always start like I do, and that is tell us about you, Tell us about you, your passion at your core. And I know the founders started Taylor with specific goals in mind and it is led by AI. So talk to us about you, the founders, and how y' all even knew there was a need for Taylor.
- [02:16]
Zohair Karut
You know, I've always been doing data and analytics for a long time in different industries and always looking for ways to make things simple. Data can help make complicated things simple. And so, you know, AI has many applications, of course, as we're all discovering these days. And. But at the core, I think there are two main ingredients that help make AI applications successful. One, there is a lot of different data to process. I mean, for example, think about when you're driving down the street in the car, your brain is looking at lots of different things, right? The traffic lights, the pedestrians, the speed of the cars. And you're processing all of that data. And so it requires a lot of data inputs to be successful. And then number two is you need to be able to scale it. Some people are better drivers than others. If we could just take the knowledge of the best drivers, and somehow that. Right. And use it. That's important. So when you think about clothing, there's so many data inputs to think about. Like, it's like, what's the weather? Do I have a party coming up? Is this going to fit me? Does this shirt go with this pant? And there's so much to consider that. And some people are good at it, but if we can somehow capture that knack that you know and get that style and scale it to the masses, that's what we're trying to solve for.
- [03:32]
Dr. Tamara Nall
That's amazing. And tell us a little bit about Taylor. Tell us what it is.
- [03:37]
Zohair Karut
Tail Taylor is designed to help give men everywhere the confidence they need to succeed by helping them look good through styling. It tries to learn your preferences, you know, your color preferences, your size preferences, the way you like your clothes to look. But also, we'll try to sort of expand your boundaries a little bit. Like, you don't want to keep, you know, buying the same stuff over and over again and just wear a jeans and a T shirt all the time. So how can we think about what might look good on you? And so it's like having a personal stylist in some ways that tries to understand you and tries to. Tries to, you know, get you to. To look better so that you can achieve what you want to achieve. So.
- [04:17]
Dr. Tamara Nall
Got it. And I'm gonna go to a question that I normally ask later, which is, you know, if we were to open up the hood, what is the brain of Taylor and how does it work? So let's go ahead with that, you know, because I want to continue with that. That line of thinking. So it. Are you taking pictures from the clothes you have in your closet? Is it giving recommendations of things you need to buy and where to buy them? Like, how does it actually work?
- [04:43]
Zohair Karut
So it's basically a matching problem, if you think about it in the sense that, like, I don't know, if you're on a dating app, you're trying to match person one with person two, right? And so here in the world of Taylor, you're trying to match the person with some clothes, right? And so you have to learn about the person, what they like, what they don't like, the kinds of things going on in their life. Then you have to learn about the clothes. Hey, this one's, you know, trendy, or it's more conservative. It stretches. It doesn't stretch this. And you have to try to match all of that together to make it happen. And you don't have to do it just for one piece of clothing. You got to think about multiple pieces of clothing because sometimes you're trying to do an outfit, not just a shirt, for example. Right. And so that, that is essentially what is happening. And you know, thing. And people change, right? They're, you know, sometimes their body shape is changing over time, sometimes they're going on vacation and they're like, need something or like, I've got, you know, this office party I'm going to, so I need something. So how does it continually try to learn that information to make the best recommendations possible?
- [05:47]
Dr. Tamara Nall
Got it. So when a man signs in, does it have say, like, is your body type straight or is it like this? Do you select that and then it actually colors.
- [05:57]
Zohair Karut
No, absolutely. When there's a first, when you first sign up, there is a styling quiz that you take that helps sort of jump start us understanding you. Like, what do you typically wear? Are there some favorite brands you like? You know, what sizes do you wear? What colors do you like or don't like? And so this is some basic information to get started. You can also go through some of the inventory and sort of favorite a few items like, oh, I really like the look of that shirt or this pant or whatever that can, you know, jump start the starting point of like where you are in terms of what.
- [06:29]
Dr. Tamara Nall
Okay, got it. Now does it keep you honest? So for instance, if is there. What if somebody says, I would like to eventually wear that but can't wear it now, does it segregate that or it really depends on. Yeah.
- [06:42]
Zohair Karut
Well, you're not, you're not going to be happy if you get things that don't fit you, for example. Right. So you just, you're paying for the service as a subscription to get you things that you're going to use and enjoy. So it doesn't serve you any benefit to quote, live. Right. And so, but you, but that said, you have to be willing to kind of try new things because if you were just going to go buy your own clothes at XYZ store yourself, why do you need Taylor? Right. Like you got to be to, to, to think about and, and accept that maybe I would benefit from some advice and guidance, basically. Right, so.
- [07:20]
Dr. Tamara Nall
Right, right. Got it. And does it do it for my entire like wardrobe and it also does it for an event because we talked about the weather and it could, you could be going to a baby shower or to a bachelor's party. So I can use it for an event or one specific purpose or, or for my entire wardrobe is that what we're saying.
- [07:40]
Zohair Karut
So depending on the type of subscription you sign up for, there's a different number of items that you get per week or month, you know, month or depending on the frequency that you sign up for. And we'll ship the clothes out to you keep them, you ship them back. Right. And if you, even if you love something, you can even buy it honestly. Right. And keep it forever. And so it is. And so if there, if you, you have to provide some input into, hey, I got XYZ coming up. Right. It's, you know, but over time you could fully integrate with your calendar or it could do other things. Right. But like you provide some input into it. There are some, there are humans involved as well. It's not entirely machine oriented. Right. There are humans kind of checking and balancing and making sure that it is doing what expected, but it is definitely trying to use intelligence wherever possible.
- [08:30]
Dr. Tamara Nall
Okay, got it. No, I'm glad you added that because I was, I wasn't. I didn't know for sure whether or not the actual articles of clothing were included. But you actually send them. And then I can select whether or not I want them or send them back. Okay. Yeah.
- [08:43]
Zohair Karut
Like you sign up for whatever X items a month, you get them, you keep them, you send them back. Right. And in that way. And so the art of it and the science of it is sending you things that you will enjoy. Right. And fit you, of course. Right. And so, you know, it's not, it's not a catalog where like, okay, send me this one, this one, this one, this one and this one. And like shopping on an online website, it is a little bit of the, you know, surprise effect or joy effect when you open up the box, you're like, oh, okay, that's, that's, that's interesting. Right.
- [09:17]
Dr. Tamara Nall
So I like that based on my preferences. And that can go all the way from casual up to formal.
- [09:22]
Zohair Karut
You can choose what you want. Right. But you know, and so it's not going to send you your entire closet every month. Right. But it's going to send you a few items for sure.
- [09:33]
Dr. Tamara Nall
And try different types of clothing.
- [09:36]
Zohair Karut
Yeah.
- [09:36]
Dr. Tamara Nall
It might be casual or might be formal.
- [09:38]
Zohair Karut
Yeah, that's right. You can select the style that you prefer. You can also set, look, I don't need any shorts. I only want tops. I want, or I only want. You know, right now it's getting cooler. So sometimes we'll throw in a jacket or a blazer or things like that as well. Right. And so it's trying to understand what Again, who you are and what you need now. Right.
- [10:01]
Dr. Tamara Nall
Okay. I love that. I love that. Now, let's talk about the holy smokes moment. So tell us a scenario. Take us there. Where a customer or a user used Taylor and. And it changed everything for them, where it was like, wow, I really needed this and didn't know I need it.
- [10:18]
Zohair Karut
Well, there's two parts to the kind of the holy smokes one. Holy smoke fact you should probably keep in mind is about 30% of all clothes go straight from the factory to the landfill. And, you know, people are like, wow, that's a lot of quote, wastage. Right. So from a. From a sustainability standpoint, Taylor's also trying to play a role in that. Hey, we can get signals about what customers really want. And then, number one, you're renting clothing. Sometimes you only wear things once, and then you toss it. Right. And so here you're getting more sustainability. Also, you're collecting a lot of data about what types of things men seem to want. Okay. People in the Northeast in this age range who work in these industries are typically buying or renting, in this case, these types of clothes. And then signals can go back to the manufacturer, like, oh, we should. We need to make more tighter fit, or we need to make more whatever. Right. And so that's. That's an important aspect to Taylor as well as. And that angle of not just making people look confident. Good. But also time to think about how to make this whole process more sustainable. Right. And that's. That's one. In terms of kind of magic moments. I mean, look, there's been many. Well, first of all, let me say that I find this whole AI thing and large language models magic and some way itself. Right. Like back when I was an undergraduate, I programmed a neural network to play tic tac toe. All right? And that was. That was kind of hard at a time. And I'm. Now I watch these large language models in action, and I know what it's doing behind the scenes. It's just predicting the next word. Right. If you ever watch chat respond to you, it goes kind of one word at a time. And it's basically trying to predict the next word. And it's fascinating that it's able to put together a coherent sentence, frankly. Right. And so. But then, you know, in terms of our customers, where there's lots of magical moments about, hey, I this their clothes, help me land that job, get that date, win that case in court, like, whatever it is. We've heard multiple stories from all kinds of people Right. And so it's really satisfying to know that we're helping others.
- [12:27]
Dr. Tamara Nall
No, that's amazing. That's amazing. And just for one more example, and I call this the real world example, tell us a time, obviously, you're head of AI there at Taylor. Tell us a time where you were wowed by what it did. I don't know if you have a victory dance or a victory shout or chant. If you want to do that, you can too. But, like, tell us a moment. Take us there where you were wowed by what it could do.
- [12:51]
Zohair Karut
Well, you know, it's. Some of these algorithms are so powerful, like, you can't fully understand exactly what it's doing. Right. And the minute it spits out an outfit, you know, and it's not just one particular moment, like, I like. Even when it's fitting, outfit like that does look good, right? You can look at something and say, okay, that looks bad. Right. But it's. It's sometimes hard to say, okay, what really looks good. Right. And the fact that it's able to actually understand all of these different nuances and put together something that, you know, you might see on the page of a magazine that somebody who's, you know, very experienced was able to do. You're like, wow, okay, a algorithm did that, right? And so that's a pretty magical moment, or a wow moment. I mean, the first time you see that happen, you're like, okay, that's pretty good. Because otherwise you need an army of humans to help style all these customers, right? And you need. And the fact that you're able to scale that. Back to my point I've made earlier about AI can help scale things, right? Scale expertise, I think is really powerful.
- [13:56]
Dr. Tamara Nall
So, yeah, I mean, so basically what you're saying is it took you, Zohair, as the head of I of AI now, to like, a Runway model based on how it tailored your outfit?
- [14:07]
Zohair Karut
Okay, yes, we're still improving the model. I'm not. I'm not going to, you know, leave for Milan tomorrow. I'm okay right now. But. But yes, that's right.
- [14:17]
Dr. Tamara Nall
For the power of it. That's good. Now talk to us about how you think. Think about ethics at Taylor. How does the company think about ethics and the guardrails and all the things that are really important?
- [14:30]
Zohair Karut
Yeah, well, you know, in. In the world of fashion, I mean, you can. You can have a fashion disaster. I'm not sure how to call it an ethical mistake. Right. Like, but. But regardless, we. We do have, you know, guardrails in terms of actually putting humans in the loop and they're looking at them and go, wait a minute, wait a minute. That Hawaiian shirt doesn't go with that jacket. Like, what's happening here? Right. And so, yeah, you know, maybe for some customers it could, who knows. Right. And but it is those, those are some of the guardrails we're using. We're, and we're constantly evaluating the data behind the clothes. And like, we, we try to get data from manufacturers or otherwise. I mean, obviously anybody's selling their clothes on any website like Nordstrom or whatever has a description of their clothing. Right. And so we try to get that description, we make sure it's right, and then use that information to, to size things. And for people. Now, what's challenging about the fashion industry is every, and you know, anybody who's shop for clothes, especially for women, not maybe as much for men, like a size 6 doesn't mean a size 6 and you know, in different brands. Right. Or whatever. And so that's what makes it even trickier. So you got to take into account all these different nuances. So from an ethical standpoint, we certainly want to, you know, use your data according to privacy rules and things like that. We don't want to share, you know, publicly things about you personally, but we want to use your personal information to make you as happy as possible. Right.
- [16:05]
Dr. Tamara Nall
And so, yeah, no, no, it's really interesting when you say, you know, a size 6 might not be a size 6. I find that often I order my size both in clothing and in shoes, and I'm like, okay, the model they used had a small foot or the model they use had a smaller frame than, you know, my frame.
- [16:24]
Zohair Karut
So I mean, it doesn't, it's really honestly frustrating because I'm sure to the consumer as well, because why don't they just standardize it? Like, why do they have to like play with the sizes and then you have to guess. Well, I wear this size in this brand, but in this brand I wear this size, but in this brand I would like. It's, it's. The industry has made it complicated for no reason, in my opinion. Right. So.
- [16:47]
Dr. Tamara Nall
Huh. Now do you think that it will get to a point within the fashion industry where you won't start with like a size 6 foot model or a size 6 model and AI will predict it kind of what you're doing and you will take the human out of.
- [17:01]
Zohair Karut
That part in terms of having the models themselves. Right. Is that what you're saying?
- [17:06]
Dr. Tamara Nall
Yeah, like you, at some point, you Won't need a human model.
- [17:09]
Zohair Karut
No, what you really need to know, you know, is how big is the shirt? Right? How wide is it, does it stretch? How long is it? Like, if you have all of that information, I don't, you don't need to see the picture on the model. Right? Because even if they put it on a six foot model, like, well, I'm not six foot, so I'm not even sure what to do with that information. Right. So it's a, again, it comes down to that matching problem. What can I learn about the clothing? What can I learn about you? How do I marry those things together?
- [17:40]
Dr. Tamara Nall
Yeah, I really like that because it is very disappointing. When I order something, I come and I'm like, okay, like this started with somebody that, that is like the standard, but not really the standard.
- [17:50]
Zohair Karut
That's right. So that's, that's right.
- [17:52]
Dr. Tamara Nall
Okay, well, we're kind of talking about the future, so why don't we continue along those lines of tell us, what does the future look like? This prediction, be it five years, shucks, it could be an hour from now with AI. Right? The future could be an hour from now. But what does the future look like with Powered by Taylor?
- [18:10]
Zohair Karut
Well, look, I think it's making confidence and style easy for everyone. And so you can, you can of course, take the men's clothing line area that we're in now, you can expand in different ways. You could start going into other, you could do shoes, you could do watches, you know, some other thing. Right. You can expand the kinds of things. But I think this concept of making it simple for people and still look good and be confident is important. I mean, look at, I don't know, let's say Steve Jobs or even Mark Zuckerberg. Right? Steve Jobs, like black turtleneck, that's all he wore. Why? Well, didn't have to think about it. That was easy for him. Right. And so hoodie, you know, Mark Zuckerberg, where's the hoodie? Why easy right? Now, if style could be made easy, would he have worn something besides a gray hoodie? Okay, maybe, Right. But he just didn't want to spend his brain power thinking about it. Right? And so that's, you know, I think, you know, and learning more and more about you, maybe learning your calendar, learning, you know, about who you spend your time with or like you can think about all the different types of data you could start to gather together to help, you know, shape you. And if you take this burden off your mind, like AI can remove burden from you. Right? Like I don't need to drive anymore. This thing is driving itself, right? Like, I don't need to think about what to wear today because it's helping me think about what to wear today. Right? And so you can imagine not just sending you items, but like, telling you every day in the morning. Like, you know, you, you, you. You've seen, I mean, science fiction time movies, almost like, okay, it's Tuesday morning. Here's. Here's your outfit kind of thing, right? Like, you got a meeting at 10:30. You gotta, you gotta, you gotta this, this, and you got an evening whatever. Here's what you recommend, you know, for today. Okay, great. Like, I, you know, if, if you can take. Machines can help take mental workload off of humans so that humans can, uh.
- [20:08]
Dr. Tamara Nall
So how value things. You're right. If I could get something where I don't have to think about what I wear in the morning or every day, that is amazing. So that, that is a really bright future. That is a really bright future. So I appreciate that. Now, our listeners love to try out things. So for all of our male listeners that want to try out Taylor, what's the best way to. To do that today?
- [20:30]
Zohair Karut
Well, the easy answer is go to Taylor. AI either one, it's tae ta E L O R and sign up. Right. And give it a try. Right. And you'll experience it for yourself. Awesome.
- [20:42]
Dr. Tamara Nall
Y' all heard it there. T A E L O R A.
- [20:46]
Zohair Karut
I. Yeah, that's right.
- [20:47]
Dr. Tamara Nall
All right, awesome. So my last guest, whom I call a genius, has a question for you, Zohair, who is another AI genius. And that question is, if machines could flip feel, what emotion do you think they experience first?
- [21:08]
Zohair Karut
That's an interesting question. I would say if they could feel an emotion, I think the first emotion they would probably feel is guilt. And I would say that.
- [21:16]
Dr. Tamara Nall
Oh, wow.
- [21:18]
Zohair Karut
And I would say that because sometimes the machine is wrong, right? And it sometimes doesn't like to admit it's wrong, but sometimes it'll. You can. You can get ChatGPT, for example, to admit it was wrong, but then if it felt guilt, it's like, okay, next time I'll be more careful. Next time I'll be more there. Like, you know, so that's. That's my answer. So.
- [21:39]
Dr. Tamara Nall
Oh, my goodness. I love that. Unexpected. I did not think that would be the answer. But yeah, guilt. I love it.
- [21:47]
Zohair Karut
Good.
- [21:47]
Dr. Tamara Nall
Okay, so let's move to bonus rapid fire. I'm going to ask you a question, and you'll give me the first thought that comes to your Head. So the most overrated tech trend.
- [21:57]
Zohair Karut
Oh, well, right now everybody's calling everything an agent, which I find interesting. Right? Like agent this, multi agent that. I mean, some of it's legitimate, some of it is a stretch. And just because the computer does something for you doesn't mean you'd have to call it an agent.
- [22:14]
Dr. Tamara Nall
Okay, got it. Underrated tech trend.
- [22:20]
Zohair Karut
There's some very interesting things happening right now. I mean, it's really sort of below the radar for many folks, but in the world of science research and peer review. Right. There's a lot of research that happens in the world, and I did a PhD for example, and obviously a lot of professors doing research and things, but there's this concept of peer review where you do something and your peers out in the world have to review it to see if it's legit and they agree with the findings, et cetera, which takes time and just takes a long cycle time to get that through. If you could get machines doing peer review, you could really accelerate innovation, in my opinion. Right, that's. That's one interest. That's. I think it's, like I said, a little below the radar, but the speed of change is not slowing down, the speed of change is increasing.
- [23:10]
Dr. Tamara Nall
Right, right, right. Have not heard that one. That's a great one. Okay, what's the book we should all read about? AI or the future?
- [23:20]
Zohair Karut
This is not a book. Okay. But I recently, and it just came out very recently, watched that. I think it's called the House of Dynamite on Netflix. It is about a. It's fictional, of course, but a nuclear missile being launched towards the United States. And everybody is trying to decide what to do. Right. And you know, do we counterattack? Do we do this, do we that? Like, I won't say too much more for those who want to watch it, but the fact that, you know, you think to yourself, would you let a machine make this decision? Would you let a human make the decision? How is the human supposed to make this decision? Like, it's very complicated. Like, I mean, people think the machines could do everything. I'm not so sure. Right. You should watch this and decide for yourself.
- [24:05]
Dr. Tamara Nall
It's on Netflix top 10. So I definitely saw it the other day when I was going through. So, okay, now I'm going to definitely watch it. It's not sci fi, is it?
- [24:14]
Zohair Karut
No, no, no. It's all realistic. Everything is. Is realistic in the movie. It's. That's not like, you know, something made up. It's all. It all really could happen just like.
- [24:26]
Dr. Tamara Nall
The show, it really happened. Okay, well, I'm gonna watch it. And everybody who's listening, you should watch it.
- [24:32]
Zohair Karut
Yeah.
- [24:32]
Dr. Tamara Nall
Okay, now scare us. Wow us. What is your biggest, boldest AI prediction?
- [24:43]
Zohair Karut
Well, I think it's going to be in the world of health care and along the lines of personalized medicine and getting to, you know, one concrete example would be there'll be at least one form of cancer that's curable or cured or treatable, you know, reversed or whatever. I don't know how long I'll call it, you know, five, six years from now. So.
- [25:11]
Dr. Tamara Nall
Awesome. Well, can't wait for that.
- [25:12]
Zohair Karut
We.
- [25:13]
Dr. Tamara Nall
That is much, much needed.
- [25:14]
Zohair Karut
Yeah.
- [25:14]
Dr. Tamara Nall
Well, so here. I have so enjoyed this conversation, talking about Taylor and how y' all are changing the world for men in fashion. How can people get in contact with you? How can people learn more about Taylor? What are all the social media handles?
- [25:28]
Zohair Karut
That's right.
- [25:29]
Dr. Tamara Nall
Let us know so we can stay in touch.
- [25:30]
Zohair Karut
No, absolutely. So, you know, again, get on Taylor. AI T A E L O R A I sign up for yourself. You can reach me@ZohaIRaylor AI Z O H e r and happy to answer any questions that people have.
- [25:46]
Dr. Tamara Nall
Amazing. Well, thank you so much and can't wait for everyone to sign up. We do have a lot of people who sign up based on this podcast, which I really, really love. And I get all these private messages about, oh my God, that was a great guest. And so you will get the same, I am sure. So everyone, guess what? Until next time, lead with AI.
- [26:12]
Dr. Tamara Nall (Intro/Outro Host)
Thanks for tuning in to lead with AI. I'll see you next time as we continue exploring the cutting edge innovations shaping AI across the public and private sectors. Until then, keep leading with AI.