Noosheen Hashemi - January AI & Scalable Metabolic Health

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[00:03:25] All right, we are live. Nishine Hoshemi, welcome to the Future of Fitness. How are you today? I'm doing great. Thanks for having me. Yeah. This is super interesting. You know, as I was telling you, I've been a connoisseur of wearables since they really kind of got going. And I've worked with a couple different startups that feed data through various sources. And what you're doing at January AI is revolutionary for a lot of different reasons.

[00:03:53] Number one, the lack of needing CGMs. So continuous glucose monitors. But also the path you're paving with AI and improved health outcomes and metabolic disease. It's super exciting. And this is the kind of thing I think when people dream about what AI can be in a positive note, this is the type of thing that they hope for. So very exciting. Let's start with this, if you don't mind. Nishine, just give us a little of your background on how you got to be at the helm at January AI. Sure. Yeah.

[00:04:23] I started my career in technology back in a long time ago, 1985. Actually, 1984 is when I graduated from college and briefly worked at a semiconductor company before landing at Oracle for the following 10 years. So my life has been about software. And then after Oracle, I had a very brief time off.

[00:04:48] I had worked famously impossible hours, 18-hour days, seven years straight, and then 14-hour days, three years straight. And so, yeah, I had a little brief moment when I went around the world. And then I landed at what at the time we called the dot-com in the mid-90s and was there for a year.

[00:05:18] The company got sold, and I went on and had a couple of kids and started a couple of foundations. And then in 2013, decided to go back to the dark side and ended up starting my own company in 2017. Awesome. And is that January? That's January. Yeah, that's January. Yeah, in 2013, I went into my family.

[00:05:45] My family office has invested in a lot of small companies. And I started sort of going around and helping entrepreneurs that we had invested in. And two, three years later, I decided, you know, I want to do this myself. I'm going to roll up my sleeves and start something from scratch, from a clean sheet of paper. And so, at the time, I was dealing with a chronic condition myself. And then both of my parents were having medical problems.

[00:06:15] My father was diagnosed late. He passed away. And my mother, he had already passed away. I was, like, looking for answers because he was such a health nut. But I've spoken extensively about the unfairness and the, you know, the crazy thing where you can live your life so well,

[00:06:43] but then, you know, not be told about something that happens until it's too late. And then my mom was misdiagnosed. She was diagnosed as having asthma. She had heart disease. And she almost died. And then she, we basically, the kids figured it out. And we kept her alive. Usually life expectancy after diagnosis for heart disease about five years for heart failure. And for her, we kept her alive another 10 years.

[00:07:09] So about 15 years by managing her diet 100%. Just having, you know, no more than two grams of salt a day, which is really impossible, especially my mom was a foodie. And that was really, really hard. Yeah, so I ended up on this health search and came across Mike Snyder, my co-founder, who is well known for a field called multiomics, which is the idea of looking at your health from various angles,

[00:07:38] like your microbiome, like your genome, looking at it from your blood tests, your wearable data, and a number of other data, like what's your behavior online. You know, you can actually figure out. So multiomics can very accurately and very early detect what might happen to you later in the future.

[00:08:03] And where, you know, traditional medicine can only really tell you after you've been showing symptoms already. And with multiomics, no symptoms shown, you know, by looking at these various pieces of the puzzle, you can put together what is likely going to happen to this person. So I became very interested in this, found Mike Snyder, we decided to start a company together. He has type 2 diabetes, and he's obsessed with wearables. And that's kind of how we ended up in this direction.

[00:08:33] Yeah, multiomics. Okay. Multiomics. Yeah, it's a new term for me. I'm already learning. We're only five minutes in, I'm already learning, and I love this. So, okay, you started in 2017. Is that what you said? Mm-hmm. Mm-hmm. That's early, right? That's when you started, yeah. Yeah, that's when I started my podcast. Yeah, good memory. That's early. I mean, when you talk about, like, the discussion around metabolic disease, artificial intelligence, most of this really wasn't in nomenclature, right? It wasn't around.

[00:09:02] So how did you start to identify that this may be a future path? Part of it is that, part of it, it's multiple things. One is that I'm an obsessive researcher. So, well before I fell into metabolic and AI, I fell into just healthcare as a sector that was going to explode. And I got that, I mean, I started researching in 2015, between 2015 and 2017. I looked at every series BDO that had been done, and I read everything you can imagine.

[00:09:32] I mean, I'm a very, very, very thorough researcher. And so I was already landing on health. But health and healthcare was really a sad story. Nobody wanted to invest in, you know, sick care, basically, right? And our thinking was that nobody wants to change their behavior. Nobody wants to, you know, behavior change is difficult. Touching healthcare was like touching the plague, you know. It's just nobody wanted to do it. But, so part of it, I'm a big researcher.

[00:10:01] Part of it is because of essentially the people that I happened to find. I happened to find Mike Snyder, who was a multi-opics person, had type 2, sort of led me in that direction. And the technical co-founder that I found was an AI-obsessed physicist, theoretical physicist. Just so it just happened. Like the sun and the moon all got actually aligned that way.

[00:10:30] And then I got lucky. That's the third factor, which is luck. Which I shouldn't say we got lucky that we got the pandemic. But I think for the planet, I think this idea of a moment's pause, of just saying, what's happening here right now? Why are 40% of the people who died from the pandemic had some kind of underlying condition? This idea that having an underlying condition is not okay. It's not something we should just live with.

[00:11:01] And, you know, 60% of Americans have at least one chronic condition. And a smaller 10% of the population has five chronic conditions at the same time or more. So, you know, what kind of odds are we giving ourselves? So, but I was, I am a futurist. So, I could see very, very well.

[00:11:26] I could see AI and health coming together long before venture capitalists had practices in healthcare, long before all of this. So, we started essentially working on AI and healthcare when OpenAI started its work. And it was sounded very, it sounded very esoteric and impractical and undoable. And people were like, what are you doing? Well, I'm turning food into an asset.

[00:11:53] I'm turning food into a measured variable into, in someone's health. They're like, how are you going to do that? People, people famously eat, you know, whatever the hell they want. They have, you know, food is something you didn't touch in 2017. People are supposed to eat whatever they want, anytime they want, however much they want, anything else.

[00:12:13] So, this idea that I could sort of show you a mirror, if you will, in terms of what's happening to you metabolically, cardio metabolically, based on what you're eating, was just inconceivable at the time. But we absolutely had that vision. And we were obsessed with continuous glucose monitors in 2017. And we thought, well, there's got to be things we can learn at the intersection of CGMs.

[00:12:42] And CGMs themselves, revolutionary, really interesting, close the loop. But CGMs and smartwatches together, now that's really interesting. And then we quickly learned that one of the most important factors, well, the most important factor in your metabolic health is the food you eat. And 100%, we proved it, we published it, it is a fact that over and above anything else, you know, people think, I'll just eat two pizzas and then I'll just work out for two hours. No, it doesn't work that way, actually.

[00:13:11] So, not to confuse weight also with metabolic health and having that sort of massive jolt of, you know, massive kind of assault on your metabolic system if you actually ate two pizzas. So, yeah, so that's kind of how we ended up here. It's really interesting. And spending, you know, I think eight or nine years that I did in kind of in the trenches, as I would say, of working with clients.

[00:13:41] Nutrition is such a emotionally charged topic for many people, right? It's, you know, like you could get, you know, there's a million jokes, but like a, you know, a carnivore guy and a vegan in a bar and some joke comes out of that, right? Like it's very emotionally charged. But what I've loved about wearables is not just the data that you get. It's become an objective starting point for conversations.

[00:14:08] So, if you are a practitioner or someone who's trying to guide people to a healthier lifestyle, you know, have something that it's not emotionally charged. It's just data. It's just information. Now you can have a real conversation about that. I feel like that's something that you guys are making more accessible to people. So, you know, as you started this journey in 2017, how has the product and the experience evolved into what it is now? Yeah. Yeah, I'd love to talk about this. So, in the beginning, of course, we were in research. So, for three years, we sat in research. We were in stealth.

[00:14:39] So, what we were looking at for three years were things like, first of all, we used to eat. We used to actually experiment on ourselves. So, eat the same breakfast nine days in a row, same amount of workout, same amount of everything. Or eat and walk across just the office just to see what happens. We call the prancercizing. Any kind of movement lowers your blood sugar. It's incredible how sensitive this is and how important it is to do it right after you eat it.

[00:15:06] Not 20 minutes later because by then your blood sugar is already spiked. So, we were excited. We ate guar gum. You know, we would, you know, the stuff. We did so many things for three years. But on a machine learning level, we first, we essentially started working with JIGL, glycemic index and glycemic loaded foods, and trying to understand if you could produce this for any food. That was one area of search. Another area of research for us was nutritional inference.

[00:15:36] If I look at any food, can I tell what macros does it have? And how can I do that? That was another machine learning project that we did. And then we ran a clinical trial from 2018 to 2020 where we, for over 1,000 people, we put CGMs on them, we put smart watches, and we looked at their behavior, and we looked at essentially the glycemic response of their body to the foods they were eating.

[00:16:05] And we came up with our first paper in 2020 that we put out at the American Diabetes Association convenings. And that paper predicted someone's glucose 33 hours into the future, which is incredible. You could only predict people's glucose about half an hour at that time. And it was also trained on food. So it wasn't just like, I can tell you if this person's glucose is going to go up or down in the next 30 minutes.

[00:16:31] It was like, I'm going to tell you what will happen to this person's glucose if they eat pizza versus apple versus any food. And that's just crazy because none of the prediction models were or are trained on food. Only January is trained on food. So basically, most of the prediction models are trained on carbs, carbs and insulin. Sort of, they just tell you, you could say, I'm going to have 40 grams of carbs. They say, take this much insulin.

[00:17:00] That's kind of what was available. So we changed the state of the art dramatically in 2020. And then other people started putting out, like, basically put a very thin app on top of a CGM and took it out as their own CGM, which is crazy because none of these companies make CGMs. They're all marketing firms. But they all kind of, you know, and the public doesn't know that. So the consumers think that, you know, they're all making hardware, which they don't. But they are basically app companies.

[00:17:30] They're marketing companies that did a really good job taking basically what already existed and made it accessible to people via telemedicine and all of that. So we said, OK, fine, we'll jump in and do that. But now, so in 2020, we put out our first version, our V1 of our product, which was really the app we had built to run the clinical trial. So we took the app we had run to run the clinical trial and we put it out in the app store and said, OK, great.

[00:17:58] We put some lipstick on it and said, let's use this. And we started getting, you know, hundreds of orders, especially because because the sector was very hot. Other other players were like, oh, we have two hundred and fifty thousand people waiting. And so people would just come and get it from January, that kind of stuff. And it was it was very cool. And we had incredible clinical outcomes. We had, you know, anecdotally, people were losing, you know, 10, 20 pounds.

[00:18:29] But also we ended up eventually publishing on that first version of the product we published in NPJ Digital Medicine, which is an imprint of nature that came out last November. So we published what we were doing in 2020, 2021. We published it in 2023. And people had, you know, dramatically changed the way they were eating. They were eating fewer carbs and fewer calories.

[00:18:54] They were eating more protein, more fiber, both of which help your blood sugar. And they were living more in better, healthy timing range. And they had lost weight. So that was really exciting. But the product was clunky. And we decided it was it was also a very rigid product.

[00:19:13] It was a 90 day product because it was the mindset was still based on diabetes prevention program, which is like, oh, you know, you have all this content, you know, tell people you have, you know, kind of like new, which is very old world. It's super old world to tell people you have three tasks today. You know, that's not how that's not how it works. So that was our vernacular. We're like, what are the best products out there? You know, Amada, Noom, all these people. Great.

[00:19:39] We'll come up with something that is task oriented, where you give people, you know, three to seven things to do in a day. One of them is read an article. One of them is like, you know, avoid spiking foods today or eat these many calories or whatever. So very successful, but not as cool as we thought our version two was, which was what we call an always experience. You basically came in. It was very much self-managing. You weren't told to do anything. You were just given some targets. And that's it left on your own.

[00:20:08] And that actually was incredibly successful, more successful clinically. And we have a paper that we've submitted right now on that experience that we hope gets accepted. And we showed even more weight loss. So when people actually had tools and they were self-managing, weren't being told what to do. Like in the old program, we had today, you know, eat your breakfast for two or three days, then eat a keto breakfast, then eat. Then you had a sugar shot.

[00:20:38] And we compared these three. We said, here's your breakfast, how much it looks, you know, and this is how close it is, let's say, to the keto versus the all sugar. And we gave these people these experiential things. Here, we weren't doing any of that. Nothing. We were just saying, here, just throw on the CGM, wear your spot watch, walk around, and we can tell you how much you're fasting. How close to bedtime you're still eating. We were giving them these counterfactuals. Like yesterday, you ate this, but you could have eaten this.

[00:21:08] Or yesterday, you ate this. But if you had walked 20 minutes after, this is what would have happened to your blood sugar. Just by just very, very hands-off, frictionless. And we had great clinical outcomes. But this technology still was out of reach for most people. Still too expensive. It was $288. And it was a tremendous amount of burden that we were carrying on behalf of the CGM maker.

[00:21:32] Because anybody who's built a business around CGM will tell you that there are a lot of problems with it. They fall off. They can be wrong. Sometimes you just get a bad one. And so there are a lot of issues, a lot of service issues, customer service issues that really look bad on you. And also, they're just inaccessible. They're just too expensive. So our obsession was with...

[00:21:56] So we wanted to come up with a version that could be broadly used for educational purposes. So the first time that we put out our paper, we could predict glucose while the person was wearing a CGM. But without having to eat something. So it was wild they were wearing a CGM, but they haven't eaten... You know, we trained their AI on A, B, and C.

[00:22:26] Now they're eating, you know, G, H, I. And we could predict their glucose to that. Revolutionary, incredible. But the next stage, we were able in B2 to remove the CGM. And still be able to predict for the person. And then after that, we were able to actually draw CGM curves for people. As long as they kept logging their food and wearing their smartwatch, we could still do that with fairly high accuracy.

[00:22:56] And the next thing that happened, which is our version 3 of our product, which is what's in the app store today, that product doesn't use a CGM at all. So we've taken elements of the models, demographic elements of the models, like how old you are, your height, your weight, your gender, whether you have prediabetes, diabetes, you're unhealthy, et cetera, your ethnicity.

[00:23:20] And we are now extrapolating directionally correct information for you, which we think is wonderful for educational purposes. It's fantastic. And if you really, really want to know if you're a rice spiker versus a potato spiker, throw on a CGM. But if you don't, for most people, we feel like education is what's lacking. And awareness and just having that on your radar, what could be happening to your blood sugar.

[00:23:49] I continue to be surprised how little people know about nutrition and how little people know about volumes. Like I was speaking at the Fortune Global Forum a couple weeks ago in New York City, and we were sitting at this table and there were these mini desserts, like mini brownies and mini donuts. Six of them were almost 1,000 calories. They were only very, very small.

[00:24:14] And 1,000 calories, like, you know, all I can eat in a day is 1,300 calories because I happen to have high body fat, unfortunately. That's all I can manage. So if I just blew 1,000 of those calories by just eating those little things, just not thinking that, you know, they don't look low volume. So I think all of us miscalculate just what we're doing to ourselves every day from volume perspective and from blood sugar perspective.

[00:24:43] Certainly from macros perspective, we are not really that focused on protein and fiber as much as we should be. Awesome. So in the current edition, what's in the App Store? And I believe from the information I have, you guys have over 100,000 users now. And it hasn't been in the App Store super long, right? I mean, it seems to be accumulating users pretty quickly. Like, walk me through, like, what is the consumer experience? What's the user experience from start to finish? Once they find the app in the App Store and they download it, what happens?

[00:25:13] Well, the first thing they do, they have to go through this onboarding process where they tell us about themselves. So, for example, what food sensitivities they have or food allergies they have. Because our recommendations are all highly, highly personalized. So if you just never want to eat abalone, we will give you an abalone recommendation. So a lot of it is about understanding your preferences, your dietary preferences, and understanding what you want to and not want to eat.

[00:25:39] Also understanding your physiology, demographics like we talked about. This episode is brought to you by our good friends in Matabolic. Matabolic is a boutique franchise system built for entrepreneurs and backed by experience. Founded by former professional athletes Brandon Cullen and Kirk DeWall, Matabolic blends elite training principles with a proven business model. With 36 open locations, 8 new markets launching soon, and another 50 plus in development,

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[00:26:37] And then you're ready to go. Once you're in the app, you can start taking pictures of anything. And I really challenge anyone here to show me a better food scan experience than what's in January. I would love to see where it is because we benchmark everyone. We benchmark anyone. You mentioned a couple of names before we started. We benchmark everybody that you can think of.

[00:27:03] From the kings, you know, of food tracking, like MyFitnessPal, to, you know, metabolic players, like Levels. We are absolutely the best. There's nothing better than we are. So take a picture of anything in front of you and get its macros right away. Get its macros, like, basically, its macro and micronutrients, you know, carbs, all that. And then see the impact. See the blood glucose impact. And what comes next is counterfactuals.

[00:27:33] This is what only AI can do for you, which is if I ate, you know, this is basically, this is your curve. But if you cut out half of the rice, this would be your curve. You cut out half of the wheat or, you know, bread, this would be your response. So you don't, so you could play with it. I think, you know, when I first started way back in 2017, Chris Gardner from Stanford University worked with us very closely. He always said, he's sort of the god of nutrition there.

[00:28:02] He said, you can't get people not to eat something. You just tell them, don't eat sugar. Don't eat flour. Don't, you know, eat broccoli, you know, all day long. And like to walk 10,000 steps, they're just not going to. And they haven't. And this sort of one size fits all doesn't work. What you can do is to try to get people to eat a little bit more of what's good for them and a little bit less of what's not good for them. And to get them to understand that just over time. And if you can do that, you're very successful.

[00:28:32] And we do exactly that. So if you can experiment a little bit, like you have to give up French fries completely. No, but, you know, you can see the impact, you know, visually. And the beauty of AI is you don't have to eat it to see the impact. And that's really the genius of AI.

[00:28:54] And that's not only we've been able to make that available to people who wear CGMs, but now available to people who can't afford or don't want to wear a CGM because it's invasive. Yeah. And what's, uh, it's awesome. And, you know, it's, I think you'll start to see the thing about human behavior change from my experience is that you, number one, you got to meet people where they are. Right. It's sometimes it's just a bridge too far.

[00:29:20] And that's why, you know, a lot of times it's very hard for people to get into the gym if they're coming off the couch, like to come in and start doing three classes a week or CrossFit or something like that. It's too far. It's too much. Right. But everybody has a phone, right? Everybody knows how to use apps. So kind of meeting them in that space and educating them. And I think that's like, you're starting to see this, this huge decline in alcohol intake. And I have to believe that has to be due to wearables and what people are starting to see in their sleep in their HRV.

[00:29:48] So they're starting to get educated themselves through the data. Right. So it's really, it's a really cool time. Nushin, what is, what is the business model for you guys? Like, how are, how are you, how are you looking to scale this? So we are, so we have generally been direct to consumer. We have had a few deals with drug, with pharma and food companies, very, very large companies. But right now we're looking at API deals. We're trying to go B2B.

[00:30:17] We're trying to provide our experience inside other people's experiences. So we are talking to a number of very, very prominent apps that you use every day, literally every day, about how we can embed our technology into their user experience. And these are people that are, you know, delivering food from, you know, restaurants or grocery stores. These are people who are delivering, you know, diabetes prevention.

[00:30:46] They're people who are basically providing either chronic condition care or lifestyle or wellness kind of things. So we are, our goal is to be a B2B company and provide services inside these other experiences that people already love and already are, you know, are successful. So we are world-class, best-in-class technology. We're trying to connect to best-in-class distribution channels where people have customers, people that are showing up for some value.

[00:31:16] And we're trying to add to that value. Yeah. Yeah, I love it. You know, give me a picture of where you think this is going in like five years, right? So this is Q4 2024, let's just say by 2030. This AI, you know, starts to make things more accessible, more, and that's the, to me, that's the promise of artificial intelligence. It takes, you know, things that would cost a lot of money, makes them very accessible for many people.

[00:31:41] And then, you know, I think we're starting to look at this year, you know, between what happened in the pandemic and then no need to talk politics here. But, you know, with RFK Jr. now in the conversation, at least bringing a conversation about health and metabolic health more to the table across, you know, more of the country, it's just more in the forefront. So people are ready, right? People are starting to see that they want change and we need change. Otherwise, this country is going to be bankrupt.

[00:32:08] So where do you think you, what kind of impact do you think you can make by 2030? So, yeah, so I would love to see RFK Jr. succeed in fighting big food, sort of. It is, everyone has tried before, no one has succeeded.

[00:32:27] I don't think that anything short of what happened before with tobacco is going to make a difference, which was really a combination of legal action, government regulation. There was, you know, about transparency, about labeling, you know. There was so many things happen. If you go in and just abstract UPT, explain to me what happened in the sort of anti-smoking movement.

[00:32:57] It was a combination of government, nonprofits, and people, and like advocacy groups that sort of sued. It was a combination of a lot of people. It wasn't like one or two people. There was a combination of a lot of people and it was sustained and it was very specific and it was able to do. Unfortunately, some of those, unfortunately, no company can on their own start restricting themselves.

[00:33:27] You know, if companies wanted to start cutting sugar in foods or changing the type of sugar they use in food, you know, in terms of corn syrup, which is one of the worst things that you could do. I mean, I could even talk about the impact this has on farms and U.S. farming and it's just bad. It's bad for everybody. It's really bad. And, you know, one out of three people has pre-diabetes.

[00:33:50] I mean, you know all this because if you've been listening to things, you know that we can't even, we don't even have national readiness because not enough people can actually qualify for armed services, you know, because they are too obese. We have our level of obesity is too high. I mean, it hits us in every, it hits us in our $4 trillion healthcare industry, which is more than 80% of it is chronic conditions, most of which is lifestyle and preventable.

[00:34:21] So, I mean, it's kind of insanity what we do to ourselves. So, I wonder, I mean, if there was going to ever be a moment where we had enough chutzpah to do it, it would be now because, you know, Donald Trump has won the popular vote, you know, the Electoral College, the Senate, the House, the Supreme Court. And, like, we have all of it.

[00:34:48] So, this is as close to top down as it gets, as close to China as it gets for us, right? And so, we have the moment if we wanted to, we could start asking, for example, all chain restaurants to label their foods. It's not very hard to do that. But you can have one milkshake that's 1,200 calories just like that. You know, and people just don't know they're throwing in 5,000 calories, you know, 4,000 calories a day.

[00:35:16] And a lot of nutritionists will tell you it's not about calories. That's true. It's not fully about calories. Yes, sugar is your biggest culprit. But calories do matter. You put any kind of 5,000 calories of non-sugar in your body, it's still not going to be good. I learned this in early days of CGM. I used to be like, oh, I don't eat sugar. And I was eating avocado and coconut. I was getting fat like crazy because, you know, fat is fat is fat.

[00:35:44] And so, if I were to have hope, I mean, this would be the most hopeful moment that I would ever have for actually doing something about the U.S. healthcare system, about the food system, which is really, really bad. But we've done in the pilots that we've done with big food companies, we have shown them what their foods are doing to people because we can feed it to our digital twins. And they have seen it.

[00:36:11] They have seen, in fact, food that was created for people with diabetes, you know, was spiking a diabetic person's blood sugar 70 points. If you're already at 180 because that's your baseline is 180, another 70 points. I mean, what kind of food is that? Like, why are you doing that? So, yes, I'm very hopeful. But I don't – people have tried before and they were told to go sit in the corner.

[00:36:37] You know, I think Michelle Obama tried it once and it was like – it was like didn't go anywhere. She was told, exercise, you know, get out and do some workout. But so, I think I'm not 100 – I'm very optimistic. I'm super optimistic. I'm super happy about this moment because I feel like we have a shot. We have a shot. But I think we have to execute well and we should execute with clinical evidence.

[00:37:04] We should execute with, you know, having all the voices, including from the industry, at the table. And I think we should do this constructively, but we should do it fast because we're killing ourselves. In terms of what AI will do for people, I think that the more wearables people wear, the more prevalent wearables become. You know, I mean, Apple Watch is still being sold at an unbelievable rate. People are adopting Apple Watch even to this day.

[00:37:33] Like, Whoop is doing a good job. Aura is thriving and is doing very, very well. You know, congrats to my friends at Aura. They're doing a really, really good job. I mean, you can buy Aura at Target at CVS. It's becoming very accessible to people. People love the form factor, right? I'm wearing both of these. People love the form factor. It's four grams. It's super easy. You can sleep with it and it's really easy. So I think the more people wear these things, the more CGMs.

[00:38:01] Dexcom and Avid, Lingo and Stellar, both are coming in over-the-counter CGMs, right? The more people wear wearables, the more AI can help you because we can machine learn off of this 24-7 data to see what is normal for you. What is baseline for you? What is a thing that's bringing your pattern? We can use that data to predict. Absolutely.

[00:38:25] Now, I do think that, you know, the people who make devices are not necessarily going to be excited about using AI to replace themselves. So I don't think they're going to be at the forefront of AI, frankly. I think they're going to be disruptors like January who are going to say, wait, we don't need to do this and this. We can already do. The question is how fast can we adopt these technologies in the U.S. healthcare system?

[00:38:51] So really the message I want to really share with you is that we have the technology today. Like this is not about the future. AI is here right now. And we have AI for metabolic health. Right now we can make all Americans healthy. We can. And we have the tech. Do we have the political will? And do we really have the political will to do it? Because we can do it. We have the tech. It's not a matter of technology.

[00:39:17] And like you and I both said, if you give people these frictionless tech, they will figure it out over time. They'll figure out, you know, I can't drink too much. I can't drink more than one. Or I shouldn't drink after two o'clock. Or they will figure this out. And so for all those people who have no hope around behavior change, I have all the hope in the world around behavior change. Awesome. Awesome. That is one hell of a call to arms. I appreciate it.

[00:39:46] Machine, this has been really interesting and really positive. You know, I think it's very optimistic. So really appreciate you coming on. Love to get you back in about a year, maybe get an update on what's going on. Maybe we have some great news about, you know, the political will of the country. And yeah, we'll see what happens. That'd be amazing. I'm here to help. I'm here to help. I definitely want to jump in and do whatever I can because this is the moment. Awesome. Ladies and gentlemen. Great to meet you.

[00:40:15] Nushin Hashemi. Thank you. Great to see you. Bye. Hey, wait, don't leave yet. This is your host, Eric Malzone. And I hope you enjoyed this episode of Future of Fitness. If you did, I'm going to ask you to do three simple things. It takes under five minutes and it goes such a long way. We really appreciate it. Number one, please subscribe to our show wherever you listen to it. iTunes, Spotify, CastBox, whatever it may be. Number two, please leave us a favorable review.

[00:40:45] Number three, share. Put it on social media. Talk about it to your friends. Send it in a text message, whatever it may be. Please share this episode because we put a lot of work into it and we want to make sure that as many people are getting value out of it as possible. Lastly, if you'd like to learn more or get in touch with me, simply go to thefutureoffitness.co. You can subscribe to our newsletter there, or you can simply get in touch with me as I love to hear from our listeners. So thank you so much. This is Eric Malzone and this is the Future of Fitness. Have a great day.