Daniel Ek: la vida después de Spotify, incentivos sanitarios fallidos, detección temprana de enfermedades y el potencial de la IA

[0:00] All right, everybody, welcome back to the All-In interview show, where we, the All-In podcast, dedicate an hour to just some of the great thinkers, creators of our time, and today will be no different. Daniel Ek is with us. You know him, the co-founder of Spotify, which he started 20 years ago, and he ran it for those two decades to an extraordinary state of affairs today. Well over 700 million active users, over
[0:31] 300 million premium subscribers, but on January 1st this year, he shifted and became the executive chairman with me and David Friedberg today. Daniel Ek, how are you, sir? Welcome to the program. >> Well, thank you so much for having me. It's good to be on. >> Yeah, it's good to see you. We've known each other for 20 years. I remember the first Shac, your partner, leaned into me at a internet summit or something and said,
[1:02] "Hey, check this out." And he showed me Spotify. But this was at a time when nobody had a subscription service. So we're going to talk today about your new startup, which is incredible in in the healthcare space. But take us back to the launch of Spotify and how that crazy idea got started. And then how hard it was to break through with the music industry, which are also known as the hardest partners in the world. >> I'm going all in.
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[2:03] sort of saying whatever anyone asks me about the story is like, well, I had hair when I began this and by the end of this I obviously uh ended up being bald. So, uh you you can see that it wasn't an easy journey. All jokes aside, I mean, just to kind of set the scene, I mean, I started Spotify in 2006. I was 23 at the time um and the world looked a little bit different. So, this is pre uh iPhone, pre uh I mean, Facebook existed, but it was college-only. YouTube uh didn't
[2:33] exist. Uh so, just like that kind of dates me, but this is before all the things we now take for granted. And um and and the world at that time uh and the music industry at that time was in freefall because uh music piracy was kind of rampant. So, we had uh Napster, we had Kazaa, we had all these things and there was an organization called the RIAA that went around and actually sued individual consumers in the US for illegally downloading music. And so, I was sitting in Sweden and I was thinking
[3:03] to myself, you know, this is this is wild and this is crazy. There's no way to put the genie back in the bottle. And me and my co-founder Martin, um we were kind of sitting and spitballing startup ideas at the time and and you know, Martin asked me like, well, you know, if you could do anything you'd like to do, what would you do? And I said, well, you know, my real passion is music, but that that seems like a really stupid idea. And he's like, well, why is that a stupid idea? And I kind of told him about, you know, it's really hard because uh you have to do all these
[3:34] deals with the record companies, you have to then figure out how to do licensing and copyright and you have to do all of these different things. And he said, well, what if you did this? And then he kept asking these what if questions and eventually I ran out of reasons to say it. So, I said, well, I guess you could do something, and if you did something, it would feel like you had all the world's music at your fingertips. And he's like, well, that sounds pretty good. And I said, well, okay, well, let's give it a a try. Um we started trying to license
[4:05] music. Um The originally the idea was to try to go global from day one, and everyone was just laughing at at us when we were originally saying that. Um but I I sort of lucked out because it turned out that one of the worst music markets in the world was my home country, Sweden. And part of the reason why it was one of the world's music markets was because we had super fast broadband already from the early 2000s. So, we were kind of living in the future where people had such
[4:35] quick bandwidth connections that they could download pretty much whatever they wanted. So, they were were doing it, and iTunes actually wasn't even available in the marketplace. So, there was literally no legal options. So, I think the music industry had lost like 80% or something of its revenues. And so, it was like a it it was kind of this crazy uh you know, coincidence and kind of all of these things the complex of events where we figured out, you know, that me and my partner, we we basically took all of our
[5:06] own money that we had made from prior startups, and we said to the record labels, what if we would guarantee you that basically you'd keep your bonus for the next year, and you make your budget for the next year, you know, if if this really is as bad as you think it is, then you just shut it down after a year, but you still made the bonus. Um and if this actually works, you win as well. So, you win no matter no matter what. And they're like, okay, well, this seems kind of like an interesting idea. Um and they eventually after a few years
[5:36] of negotiation agreed to it. So, we launched in late 2008. Um and it instantly became a huge hit. We then took it to the UK um and made it huge hit there. And then in 2011, 15 years ago now, uh, we launched in the US. Um, and, uh, yeah, I'm in. And the rest is sort of a history. >> I mean, isn't it amazing, five years in the laboratory just to get to the to the to the US market is a quite a, uh,
[6:07] quite a journey. That's a lot of pain and suffering. >> Yeah, but but you know, you know the crazy thing is, uh, I'm on the same journey now again. >> Yeah. Here we are. >> Neko, actually, uh, as crazy as it is, uh, we started the company, um, eight years ago in 2018. Um, and we started it in Sweden, um, in 2023. So it took us five years to develop the product, um, try it out in Sweden. And then once we proven it in Sweden, we took it to the UK and did it
[6:38] there. Um, and then from there on, now we're launching in the US. So it's the exact Spotify playbook again, but this time in healthcare. >> One of the afflictions of great entrepreneurs is your entrepreneurial. All right, I mean, you just can't stop. >> Or maybe I just have a high, uh, pain tolerance. I'm not sure which one it is. >> Yeah, once things got smooth, you had to get back into it. But at what point did you start thinking about doing other things, Daniel? Were you like actively angel investing at Spotify over the years as CEO? The
[7:09] business is building hundreds of millions of users, it's public, successful. Things are growing nicely. You've got a great leadership team. We've obviously met a lot of your team over the years. How did you start to do these other projects? I know you've got a few others and and focus on Neko. >> Yeah, it's kind of crazy. I I'd forgotten about it, but but, uh, my team now showed me very recently, like I I apparently did this lunch with the FT interview in, I think, 2012 or 2013 or something. Just after the US, uh, launch of
[7:40] Spotify, uh, where I was talking about healthcare uh, already back then. So I've been thinking about healthcare specifically for a very very long time. Um and it's just been you know, I I I think a lot of people just talk about sort of all the stuff that's going bad in the world, but my view is that actually most things are going pretty well and it's kind of up into the right on the technology curve and all the things that we're getting, but I try to focus on the problems that aren't going that well.
[8:10] You know, one of those happens to be healthcare. So I've been kind of interested about this as like, you know, how is it that we're spending more and more money on healthcare, but getting worse and worse outcomes. Um and what can we do about it? And so that really kind of got me into the space. I think healthcare is kind of unique and kind of special. I honestly didn't have any money until Spotify went public, so I wasn't a prolific angel investor. >> What year was that? >> That was 2018 we went public. >> 18, right. Yeah. >> Yeah. So
[8:41] I probably started doing a little bit of investing in 2018, but I had no money before then, so you know, it was literally just kind of all in focus on Spotify for I guess you know, the better part of 12 13 years before I made any investing in in anything else. And then you know, you and I we were talking about it at this dinner like a week ago or something, but you know, I then tried to do a little bit of investing. I had actually already started
[9:12] uh Neko at that time and I kind of just realized that I loved building way more than I loved investing and and so right now >> Chamath came to the same conclusion. It's so painful to watch companies you invest in. This was our whole dinner conversation the other night. >> and you can't do anything. >> Well, you you spend time on boards. That's why I don't join boards anymore. You're sitting on a board you advise the CEO and they don't listen to you and you pull your hair out like I would have done something different. Why didn't you do this? And you know, and if they are listening to
[9:42] you and you're effectively instructing them on what to do, it also doesn't work because they're not leading. And so I I became pretty committed to this idea like you find amazing entrepreneurial founder CEOs, give them money and never look at it again and you'll be fine. Generally better than not. And then, you know, the flip side is if that's really what you're passionate about and you're you have the activity or the agency, it's to step in and do it yourself. >> more instruction they need, probably the less chance they're going to succeed.
[10:12] >> Yeah. >> So Daniel, maybe you could just give us the overview on Neko, kind of what the >> Yeah, and how you came to and how you came to that idea, right? How did you come to the this specific idea? >> I started researching the space uh a very, very long time ago. And maybe just as a quick primer for the audience, the US uh is spending 18% of its GDP on health care. It's the single largest line item uh in the budget uh right now. And if you take heart disease alone, um it's in the hundreds of billions of
[10:43] dollars that are being spent on that disease group alone in the US alone. I mean, it's just insane. It's larger than Fortune 10 companies revenues, uh just one disease group. So it's it's a gigantic uh problem um as I mentioned. And so I started looking into everything from like, you know, drugs to um you know, can you make more efficient drugs? Is it about cancers and and basically started like targeting like what are the the real reasons why it looks that way. And I
[11:13] think the the the real conclusion I ended up being there's lots of reasons, not one. Um you know, we see um but we see a few really big ones. Um um cardiology or cardi heart health is a major one. Uh we see um skin cancer melanomas being another big one. So there a few sort of major uh groups of illnesses that is over representative. Uh but, the major one is really chronic disease um overall. And
[11:44] the crazy thing about chronic disease when you read about it is that if you discover these things early, they're totally preventable and uh the cost of dealing with them is very small and the suffering for the person um you know, uh uh that are having it and their family and community is very small, too. So, the key thing is if you discover things early, um you're actually good. And so, then the question is, well, why don't we discover things early? And it it happens to be that we don't have
[12:14] enough data. So, everyone in the entire health care industry is in agreement that we have to take health care from reactive to preventative health. And uh but, then, you know, there uh now all the disagreements starts, which is how do you do that? And and uh our view, uh my co-founder Yael Mar and I, um our view is is really that it all starts with having better data. If you have better data, you're going to uh be able to discover things much more easily, and that in it in itself then
[12:45] leads you to uh have a chance of discovering those things much earlier, which then creates this virtual flywheel of then changing health care. >> So, predictive data that allows you to be predictive about future adverse health outcomes and course correct ahead of time. >> Yeah, that's that's the holy grail uh is to get to that point. And and and essentially, our view is that the way you get there is that you need a lot more data than you have today both uh for from each modality that you gather
[13:17] data, but also across multiple modalities, and you need it longitudinally. So, you need it over time. So, if you if you had a lot more data and you had it uh over time, uh you'd be able to have a lot higher likelihood of doing those kind of predictive analysis. And then what we then said is well, well, okay, how do we do that? And it so happened to be that if you think about really what's happened in the last 20 years, one of the biggest innovations, of course, is the smartphones. And we've
[13:47] had more and more sensors packed into those smartphones, so there's more and more cheap sensors and cheap electronics that's available to us. So our view was like, okay, well, we should be able to utilize this to build a lot more sensors than what's been able to be built before. And then the other thing, you know, we started pre-the LLMs and everything like that, but it was then called machine learning, but today we talk about it as AI. We should have a lot better intelligence. So if we have all these massive data sets, we should be able to
[14:17] make really good predictions about it. And obviously again, similar to that, this is exactly what we learned with Spotify, too. The more data we're able to gather, the better predictions we're able to give you about what song to play next. And so this is exactly the the same thing that you now need to do in health care, but obviously it's across multiple modalities and now across longitudinal data sets, as well. >> Is there evidence today that some of this early observational data can affect
[14:47] ultimate health outcomes? I mean, I can see this working for metabolic conditions, things related like exercise depletion rates and blood sugar and sleep, but ultimately the correction there is typically diet, exercise. What are some other examples of major diseases that we can kind of identify ahead of the curve, course correct, >> And maybe just explaining what Nico is for people who don't know. >> Yeah, yeah. Maybe I'll start there, and then we can get into it. So
[15:17] in a very simple way, the experience of Nico today and in Gen 2 is it's $499. It is a reinvented healthcare experience from the ground up. Vertically integrated, we do everything from building our own facilities to having our own nurses and doctors on staff to building our own diagnostic equipment and doing everything on our own on the software side. So it's it's it's really kind of an end-to-end solution that we've designed from the ground up. And we designed it
[15:48] with the goal of creating the most valuable hour you can invest in your health. That's the mission that we have and that's what we're coming to work to do you know every day of the the the every every day really at work. The experience is really you come in. The first thing you typically tend to do is that you draw blood from us. So we then measure 53 blood markers. You then go through our skin rig where we have a camera system takes
[16:20] over 6,000 super high-res images across your body where we index every mole and lesion and all of the possible rashes and rednesses you may have as well. That gets indexed. We then look at it into your heart and blood circulation. We look at grip strength, all the sort of traditional markers that we have very good scientific evidence are valuable indicator as you think about sort of health. Then at the end of this visit that lasts
[16:52] for about an hour, you get uninterrupted time with a clinician and you go through all of the results including the blood works during that hour. So you have a complete set where you can go through your values within that hour with your doctor and the doctor will answer any questions you may have, but you will also with that clinician sit down and go through results, um, know, about things you may even want to improve as well when it comes to your health. So, that's the that's the
[17:22] experience that we're launching with today, in New York, in the US, and obviously we'll we'll launch in many more places across the United States over the next coming months. >> And just the identification of things ahead of the curve. Cuz I I've heard of other There was a one medical, there was Forward. I mean, there were a few other kind of attempts at making these integrated centers where you go in and get preventative checkups with their own instrumentation and and I think I've heard the thesis a little bit before. What have you identified that maybe is
[17:52] novel, Daniel, that we that we haven't seen in the past? >> I think first and foremost, the important thing it to mention is as I mentioned, we started this in 2018. So, this company's been around for 8 years. We've done more than 100,000 scans already. So, we actually publish data every year. So, we've just published our third year data survey, where we go through the health outcomes that we have across our members. And around 1% of our members have a serious underlying medical situation
[18:23] that is undiagnosed that we discover. Um, so, you know, again, the the good news is many of our members are healthy and we're just talking about improving their current health status and as you correctly pointed out, a lot of that ends up coming around stress, around diet, around sleep, and those things. Um, but, um, the most encouraging thing we're finding out is we've done these studies for 3 years in a row is that the people with the worst health status are the ones that are improving the most.
[18:54] So, it turns out that this ability of of having a clear visual understanding of where you are in your health journey currently today and having a clinician that sits down with you explaining the the the situation and possible remedies to that is a huge um benefactor for getting people to start improving things around lifestyle. So, we've seen members that have gone from year where they've been smoking to not smoking as part of then having to do this NEKO and
[19:24] prioritizing their health. Um we've obviously seen people with severe medical uh underlying illnesses that have gone from discovering those and then treating them and having much better overall health um as a result. So, it's really kind of all across uh the basic. But I'll I'll give you a very concrete example. So, um take dermatology as a great example. The average person um at NEKO today has 950 moles.
[19:54] >> That's pretty crazy. The average person has 950 moles. >> Yes. >> That's insane. Some percentage you can't tell I guess is the punchline here. They're like not detectable by the human >> Uh well, if you really went through your skin, you'd you'd be surprised how many you'd find. I mean it's a big dispersion. Some have, you know, many, many thousands and some of them have >> Seems like a perfect AI application for AI, obviously. Yeah. >> Exactly. So, if you think about it across a normal uh doctor's visit, how likely is it that uh that doctor will
[20:25] check out all the 950 uh moles that you may have? It's not going to happen. So, normally what happens in a normal doctor visit would be you may say, "Look, uh I have a mole." Or the doctor sees, "Hey, let's take a look at that mole. It looks a little bit funky." And then they bring out their their tool where they inspect it. Um they usually these days have a software that checks against whether uh this mole take a camera across many different um frequencies to then discover both the
[20:56] the size of this mole, but also the texture of the mole and so on and so forth. We literally do that. Um and we first have an AI system that flag uh possible risk factors, and then we have a human clinician that then goes through and reviews those as well. And should we even at that point find something, we then have expert dermatologists on staff, multiple of them that then also reviews that results. So that's just one indicator of like what happens in one visit. But
[21:26] let's now presume the scenario that we'd have multiple visits. And maybe one year it's actually we don't discover anything. But because we've cataloged and indexed every single one, we can actually now in a longitudinal base look at them from one year to the next year. So it may be growing abnormally. These are things that if you think about it, even the best doctors in the world can't possibly remember how your mole may have looked like from one year to another. So again, back to your point, this is a
[21:56] perfect application of AI, right? But we look at this as like this is a perfect application of how health care should look like. It should seamlessly be both AI and amazing clinicians. Uh, in a great package experience. So that's essentially what we're trying to do with with Neouka. >> That's great. And are you actively running it as CEO, Daniel, or are you operating part-time? Yeah. >> No. So similar to Spotify these days where I have two great CEOs. I have an
[22:26] amazing co-founder and partner Yael Mar, who's really the brainchild of Neouka. And he's the one who's doing most of the work even though I'm sitting here and taking most of the credits at this point. But yeah, he is the real brain. >> Great. You know what I'm struck by? The cost of this is so cheap, $499. You also have Function Health and Superpower, two other great services, about 350, 400. They just do blood work. But if we look at the spending, right? Right now, it's health care number two. Social Security number one. And and
[22:57] fast, your favorite coming up is the interest payments, which I believe will overtake our health care spending. You could actually have folks come to this every year or every other year for four or oh every American four or eight percent of the cost of the total we spend on health care and I'm I'm curious is this something you expect people to do yearly or something every other year and what impact do you think an investment of every American getting this done every year or every other year or maybe every three years even which would be
[23:28] down to two percent of our budget what impact would that have on the forward looking budget and then the forward looking spend if you had and have you done those kind of calculations? >> Yeah I mean look uh we we obviously have a view uh but I think it's too early to say so I don't I don't want to sit here and say that we know conclusively what will happen but I think the the the what we do recommend our members is to try to do this on an annual basis and the way I kind of make this analogy is uh most of us today uh are trying to go to a dentist on a yearly basis.
[23:59] For some reason we don't do an annual health checkup most of us on an annual basis. So for me this this should be as as regular as going to the dentist or doing anything else like and it should be a an amazing experience. This should be uh you know again as I said what we're really doing as a mission here is is trying to create the most valuable hour you can invest in your health and and you know we know a lot of people are busy so we want to be brutally efficient with people's times. You can actually if
[24:31] you don't have any questions and you're just interested in really doing the test results you could probably get by in 30 40 minutes uh and and do it so we're not talking about a lot of time uh to do that and obviously uh $500 is still a lot of money for people but I do think it's a great investment if you can afford it um to do. >> I'm going all in. >> Starting business usually means a bunch of different services just to look legit. Not anymore. With Northwest
[25:03] Registered Agent, you get a complete business identity all in one place. A business address, domain, website, phone number, and more. With privacy protection built in from day one. Don't spend hundreds [music] or thousands on services you can get from Northwest for free. Visit northwestregisteredagent.com/allinfree and start using free resources to build your business today. >> [music] >> That $500, you lose money on every visit or break even and then like there's some
[25:34] profit that comes from maybe the upsells. Take us through the economic model here and then how that will work with the insurance industrial complex as uh dysfunctional as it is here in America. >> Yeah. Well, uh so the benefit of of being vertically integrated is that we've been able to build um you know, everything ourselves, which means we can also cut costs uh in a pretty dramatic way. So, within that uh $500 a year, um we are um
[26:05] the unit economics are positive. And uh we have clinics today that are profitable that we're operating uh already today. So, so we think this is a good price point uh to enter in because it's a great value uh for people. Uh but because we do all the things ourselves, we're able to still make this um you know, economically viable for us to to create a great business and to be able to grow and invest in that business so that we can spread it to more places as well. >> So, Daniel, are you focused exclusively
[26:35] on this project? You have other stuff you're working on? >> I'm not exclusively focused on it, but it's obviously one of the things that are taking a lot of my time and rightfully so. It's one of the biggest problems in the world. Um but uh I'm still spending time with Spotify. I'm exec chair um there. Uh so, that's uh still you know, uh my baby. even though I'm not involved in it on everyday basis. And we have a few other companies with Prima Materia, which is company I I created
[27:05] together with Shaq that you just mentioned earlier. Where we're trying to really do you know, what I mentioned before, which is like how do we how do we pay it forward and >> [clears throat] >> kind of almost be like the greatest co-founder you could possibly find. That's that's what the ambition of Prima Materia. >> The healthcare thing really perplexes me. I kind of look at the the biggest issues for affordability for people in the US right now. It's, you know, buying a home, dealing with your educational
[27:35] costs, and then healthcare costs is one of the top three. I feel like we can solve education costs and we can solve home costs with certain market incentives that have been distorted. But healthcare is much more complex. As you look at the US system, beyond just kind of preventative care, the cost for servicing patients in a hospital, like why is it $15,000 to get stitches at an ER? You know, why is it $20,000 to get a
[28:06] drug that costs 30 bucks to make? You know, why when the doctor's making 200 grand a year does the doctor seeing me for 8 minutes cost my insurance company $6,000? I mean, what is going on from your view that extends beyond like getting in front of all of the catch-up problems and so on. But what's structurally going on with the healthcare system in the US? And if you were emperor of the US for a day, and you got to say you could do anything you wanted, what are the top kind of three things that we're missing
[28:36] that maybe Neko doesn't necessarily address today, but are kind of things that you would recommend we fix? >> Well, I mean, again, I'm I'm definitely not an expert on the US health care system. But for me it is like the show me the outcome, I'll show you the incentive. Um it's it's one of those classical problems, and if you really really think about it at the moment, the entire system uh is predicated on and and the healthcare system was built around a time when we were dealing with the um infectious disease. That was how the
[29:07] healthcare system was built uh and and dealt with. So, all the incentives are really around that, which means we're fixing you acutely when there's mass of amounts of symptoms. So, uh where we have to go is we have to go to the healthcare system being preventative. That means it has to be way more long-term today. So, I'll I'll just mention one of the problems that exist is uh because normally your healthcare is tied to your employment in in one shape or form, and because the average uh tenure of your employment is not that very long, it means that you may have
[29:38] only 2 3 years uh at one employer, um and then you switch. And when you switch, you switch insurers, too. So, one of the questions then, if you're that insurer, should you invest in something where the payback time may be 10 or 15 or 20 years um to do that? Uh those are just some of those sort of incentive things like how do we how do we look at the ROI of some investments that may be 10, 15, 20 years into the future, and who takes those investments? These are not easy um
[30:09] things to answer, and I don't claim to have all the answers to them, but one of the things we're trying to do with that is we're just trying to bring the cost down so that the ROI doesn't have to be that we we have to invest or the insurance industry have to invest or employers have to invest millions of dollars speculatively hoping to get it back in 20 years' time with very little data. So, our view is like if if we lower it so it may may not be a million dollars, it may be you know, I make it up, tens of thousands of dollars,
[30:41] um even if that payback time was 10 or 20 years, I I I think that there would be a higher propensity and likelihood for a pickup on that. And then the second thing we're trying to do, obviously, is we're trying to add more data uh to the system. And if we had more data, then uh it's much more likely with these multimodal longitudinal data sets to be able to kind of actually see, well, what's the efficacy of the these things over time. This is also part of the reason, by the way, why we are investing in uh in in releasing our data
[31:12] every year of what we're finding um so that people can see, okay, well, what happens um both on an aggregate NEKO population, which is also super cool because normally in healthcare systems, you they're very country-specific. Right? Like and and so this is one of the few healthcare companies that are are it's not global, but at least multi-country systems straight away. Um, so that's also super interesting. Like, what are we finding in the UK that may or may may be similar or dissimilar
[31:43] to the US. That's going to be super fascinating. >> find between Stockholm and the UK? I mean, I can take some guesses, but I'm guessing people in Sweden were much more fit and in the UK, you probably had more cardiovascular disease and diabetes. Yeah, and those are the two, I believe, you tell me if I'm right, Frieburg, aren't those like the two biggest uh spends in terms of healthcare spending? Is I think diabetes is number one. I could be wrong, but cardiovascular diabetes seems to be the big two. So, what did you learn between the two populations? >> Well, I I I mean, it's really early and
[32:14] it's still on relatively small base. It's 100,000 scans, as I mentioned before. Um, but I I so I I don't know that I think we're ready to speak about sort of population-level um health outcomes. But as we grow in NEKO, I I think we will. And and that's going to be super cool. And then, you know, we're we're already today doing um lots of clinical trials. We've done four already. We have two underway. We have another four we're going. So, we're partnering with the research community as well deeply around
[32:46] these data sets that we already have today and that we will gather more on to tomorrow, too. And I think my my point with all of this is really just to say, "Look, we actually it's for for for people in tech, the amount of data that exists in the healthcare system is actually not as the data sets are not that large. That's the crazy part." Um, and so, you know, I I think it's a pretty safe set that if we can 10x or 100x the amount of data that comes available, we're going to be able to draw super interesting
[33:18] conclusions about that. Not just Neko, but the whole healthcare system. Yeah. That's really the bet we're making. >> Put it Put in the wearables in there. It's going to be really interesting with the Oura's, the Whoop's, the Fitbits. You start Apple Watches. You start correlating that data with the blood work. I noticed Whoop offering labs now through Quest. And I I don't think maybe you can sync, you know, your Oura Whoop with some of those. But we don't I've never seen any data. You know, we have sleep, we have recovery, we have heart rate, we
[33:49] you know, but I don't think anybody's put the blood work together with that. And then your system I mean, this could really change everything in terms of healthcare if we can correlate that. Maybe you could speak to the impact you think wearables are going to have. And do you think you partner with them or you just have a a Neko wearable you eventually just make part of this subscription at $9.95 because it does seem like there's These are commodified for the basic 80% of it, I'm sure. >> Yeah. >> So, what are your thoughts there? >> Well, already today we we do allow you
[34:21] to import your Apple Health data. So, if you do have a wearable data, we will take that. So, anyone who and a lot of the big Oura, uh, etc. do um, allow you to write a lot of that to Apple Health as well. That's just one one sort of example of that. So, yeah, we would we would love to have of course more data um, um, because that enables us to again, when the clinician sits down with you, to be able to give you a much more 360
[34:52] perspective about your current health status. So, that's one of the things that we encourage, but I do want to say also that I think that this is just like the the the service that we're launching today, it is very rare in itself that um, you know, when you create a diagnostic product, normal the normal way of doing that in this space is you create a spend X amount of years doing R&D uh, for that thing, then you literally spend the next 10 years selling exactly that thing. And with Neko, within this 3-year
[35:23] when we launched and now launching in the US, we're on gen two. So, we've already upgraded our uh, diagnostic infrastructure. And so, I think what you should expect with Neko is that we're launching with one thing today, but we're going to keep adding more and more and more value. We're going to keep adding more and more um, you know, a valuable um, diagnostics that we can find and we can put in at uh, the price point um, you know, so so that's kind of the goal.
[35:54] So, this is just the beginning and and the goal is obviously to make this even more valuable so that we can deliver against our mission of having the most valuable hour you can spend on your health. >> Daniel, do you want to take a step back and talk about what's going on broadly in the tech industry right now and AI? You know, what's your view on pacing the frontier? >> these questions. Yes. >> Do we Do we need to pace the frontier? >> I'm struck by the fact that if if we kind of look at the the the world um, and and certainly over the last few years, I I kind of alw- al- always say,
[36:26] you know, uh, we're walking into uh, COVID and every one of us became a virologist. We were all of a sudden supply chain experts after the first, you know, oil tanker in the Hormuz Strait got stuck somewhere. You know, and then with Ukraine war broken out, we were all military experts and military strategists. >> podcast right now? >> I know, I'm just talking in in >> It's actually the we renamed it the All-In Laboratory Pod. It's the All-In
[36:58] Lab because we are just we're we're just a lab. We need to be regulated because our opinions are so dangerous, you know, that maybe Spotify's podcasting could regulate us. Because our opinions are so crazy. [laughter] >> Yeah, my my point is just like everyone expresses these things with such extreme confidence and it turns out most of the time we ended up being completely wrong, even the biggest experts. So, I'm not sure I have much value to add except to say that I believe that we're still in the innings where we can alter the
[37:28] impact for how to use these technologies. Um, and you know, my view is that every great technology has extreme positives and extreme negatives and it's really up to us now to steer this towards the outcome that we want. Um, I think it's great that the debates are being had, but honestly I have no sort of strong opinion one way or the other if we should pace it or if we
[37:58] should not. I I just know that if I look at healthcare and I look at what we're doing at Spotify, like it is truly amazing. I mean, the perfect music product is one that um, you know, I've described this many times and I think we're getting closer to it now, which is which is awesome is right now, you know, you can put together a better playlist yourself than what the system could do. Um but I think in the future uh
[38:28] downrightly, we can soundtrack every moment of your life in an amazing way uh where you just feel more. Like the the power of great music is that you will feel more. If you're happy, you'll feel happier. If you're, you know, uh uh wallowing and and feeling sad, you know, you'll feel feel feel even more uh wallowing and sad in that moment. And you know, that that's thanks to AI. And then uh if I look at, you know, the example we talked about with dermatology, like you know, 950 moles
[38:58] being able to track them over time, keeping you safe, like these are positive amazing examples with AI. And yet we talk about this thing as as we we we we tend to amplify that, but I want to see more positive examples of AI. Uh I I think we as an industry have done a terrible disservice of not talking about all the really really um crazy positive stuff that we can use AI for that actually greatly benefits everyone. >> And in that sense, do you also think
[39:29] about the benefit and the value of open-source AI, open-weight models? >> Absolutely. >> I think you can now look at like a 13 cent per million token output cost versus $30. >> Mhm. >> That's an incredible difference that unleashes this technology across a broad spectrum of businesses and individuals, that there is no, you know, concentration of value or wealth amongst a handful of businesses or individuals. That if we can really make these open
[40:00] weights and open-source models proliferate, but obviously this regulatory conversation may restrict the expansion of open-source and open-weight models. And if you have a view on kind of the importance there. >> I think technology has always gone between open and closed, right? Like, we had a Windows versus Linux in the first iteration, you know, um iOS versus Android. Like, we we've seen this play out so many times, and where we tend to net out is that we tend to have both. Um
[40:31] and, you know, to the extent that I have a view about it, I've very positively advocated for open-source models uh before, and I will keep on doing that because I think that that brings a lot of innovation that will be uh really helpful for the ecosystem, um as well. So, I completely agree with you, Dave, with that. Um I think that, you know, if you if you look at these now, and certainly what we're seeing um you know, at Let's take Spotify as an example, where where obviously using a lot of the
[41:01] frontier models, but we we have a bunch of fine-tuned um models ourselves, too. Um and we tend to do both, and that is actually making us more innovative, and that's actually allowing us to do certain things that we couldn't do uh with the frontier models, uh either because of cost or inefficiency reasons, or sometimes because we just couldn't tune them uh the way we would want it. And so, uh I I I personally think it's like uh it's going to be both, um but one of the things I heard
[41:31] uh that that is a perspective I haven't heard before that maybe I would encourage people not that I am sort of an expert on all of these things, but I I'm I'm surprised that people haven't talked about sort of the amount of compute. So, if you think about it, it's for me, this isn't about just the intelligence itself of a single model, but it's still, you know, of the basis of, you know, the amount of compute you're doing can indicate something, right? Like, so, if if I'm using 100,000 GPUs for something,
[42:03] uh that's probably going to have be uh a lot more powerful than if I'm running an open-source model on my home PC. It it it's probably very unlikely that I'm going to be able to do an enormous cyber thing, certainly if if if the companies have mythos class models to try to you know, protect themselves that I should be able to with an open source model on my home PC do a lot of damage. So, you know, I I I just find it to be a fascinating thing to just think about if there's a
[42:34] way of um of of looking at the amount of compute as well and and um as one sort of factor in that. >> Right. Assuming assuming model equivalency compute as a key metric of defensibility and that's really where we can start to build guardrails around who can have access to the most compute and how do you get certified for compute as opposed to certified for software? >> Wasn't that the original like 2 years ago that one of the original concepts of limiting this was how many teraflops or
[43:07] how many GPUs you had? >> What they did that that was how they wrote the regulatory laws around regulating models. >> Right. >> So, they basically said a model that was trained on X number of teraflops. And it was like this was like a California genius >> static >> California genius genius assembly got together and said, "We figured it out. We know how to classify, you know, scary models and bad models and good models." >> ethernet cables are in your data center as a proxy for how powerful this is?
[43:37] >> How many watts of power went into making this model? But, I do think your point of compute as a roadblock is probably a good one. This is what it used to be You You remember when Cray supercomputers came out? And there was a limited access and they were considered like a security risk and you had to get approved in order to get access to a Cray supercomputer because you could use them to design nuclear weapons and you could use them to crack codes and do all the things that people worried about. Yeah, today a Cray supercomputer I think is less power than a washing machine or something some some product we probably
[44:07] have in our kitchen. >> Yep. >> It is a really great point actually, Daniel, because if you've got strong compute installed as a defense capability, assuming model equivalency, you're going to be hugely advantaged. >> I haven't seen it in the debates at least, and and I'm surprised, but maybe it's something I'm missing. So, hey, before we let you go, I guess two questions for you. Take them whichever order you want. What's the strategy strategy and how does Spotify look at something we care about deeply, podcasting, which is, you know, built on
[44:37] open standards, and you guys have become a major player in it. Open standards are kind of moving one direction, and Spotify's got a lot of proprietary stuff. I've talked to you about this and some of your team members, like, "Hey, can we keep supporting the open source part?" And then the second piece, people don't know this, but there was this incredible company, Stardoll. It was one of the first companies in Stockholm, Sweden, to ever get funding from American VCs. You were the CTO, if I remember, or the intern for a couple years? >> Uh well, I was the intern, CTO, whatever. >> But this People don't know this. This
[45:09] was an incredibly innovative company in terms of, you know, many variables, like digital goods and subscriptions and all that stuff. So, maybe take us through either both of those questions, cuz that's just, you know, two personal things that I would love to hear about if we were at dinner. >> Yeah, I mean look, again, as I said, I think the open and closed are going to be two things that are going to exist um side by side. So, the interesting thing about today is like on the one hand, of course, we're
[45:39] huge platform in podcasting, and we have a destination. There are certain things that we're doing that general podcast may or may not be doing. You know, one of those will be how we're handling comments and so on that are specific to the platform. But we actually do have tools. So, what a lot of people don't know is that we also through our platform aggregate and distribute podcasts onto a lot of the other podcasting platforms. So, there's a bunch of podcasters that are using our
[46:09] tools to then distribute to some of the other platforms, too. And we're obviously doing that through open standards. So, I don't think the answer for us is like um one way or the other. We think both can coexist. But obviously, if you're if you want to innovate within a standard, then the key is to uh have other people agree to that standard, and that can sometimes take you longer, so it might be harder to innovate innovate. Um so, Spotify's approach has been let's support both um in tandem. Um >> Yeah.
[46:39] >> So, that's that. And then then >> Well, then there's two features I'm just wanted to make sure I ask you about. There's one for going live, so this is part of the new standard. So, having that on our page, uh so when we go live, it actually respects the RSS feed and sends that note out. And then there's another one called value and donations where the person who has like, you know, if they happen to be doing donations on whatever platform or they do them through PayPal, those two the like podcast OGs in the underground really want Spotify to support. So, I'm
[47:09] just doing my job in representing as a 17-year podcaster. Please add those two or support those two if you think it's worthy of doing. >> All right. Well, it it's no longer my decision alone, I should say, but I will certainly bring >> right to the chairman while I got him on the line. >> Yeah, of course. [laughter] Of course. But >> And yeah, tell us about Stardoll, yeah. >> I I'll definitely bring the feature request to the team. >> Tell us about Stardoll. While you while you wrap up here, what did you learn there when you were 20 years old, 21, 22, whatever it was at Stardoll? Yeah. >> Yeah, you know, it was a great
[47:39] experience. It was it it's kind of a, you know, uh it brings me back memory lane, you know, I um I did Stardoll just before I started Spotify. Um so, there was a entrepreneur called Mattias who uh was kind of one of the OG entrepreneurs um in the Swedish ecosystem. He had been around since the dot-com bubble, and he had It was originally the site called Paper Doll Heaven in Turku, Finland, out of all places, by this old lady and her
[48:10] son. And um Index Ventures had invested in in it and taking kind of a majority stake to help doing this because they had no idea of scaling this site. And actually um you know And and and Index and Matthias kind of came in and with with the idea of rebranding it and building it into Stardoll. And so they came to me one day and they they sort of asked around for people who knew tech and could be technical enough to help build it. And I had already decided I wanted to go build Spotify, but
[48:42] Daniel Ek is very good at convincing people to do things. And so as a favor to him and sort of me hoping that he would come and fund Spotify, which by the way didn't end up happening, but um you know, I I kind of said, "Okay, fine. I'll help you for I think it was 6 to 12 months, something like that." But so I went over to Finland and I checked it out and it was kind of wild and crazy because I think the average page load
[49:14] time at that time was like 4 minutes. So it took 4 minutes to render a simple page. So it was basically the server was completely breaking down by it seems. I was like, "Holy this is crazy. I wonder how much more traffic you could do if you actually made this work like in a snappy way." And so we basically re-architected the website. I hired an entirely new technical team and brought it down to under a second of load time and obviously the traffic exploded. Sequoia invested.
[49:45] >> Yeah. >> You know, and I said, "Okay, well, I've done my part. Thank you." And then I went off and built Spotify. >> It's amazing these origin stories like what happened right before the thing is always interesting to me. Listen Daniel, continued success. If people want to try Neko n e k o >> Yes. >> where can they go? >> So we all launched the first one at 300 Lafayette. So go sign up on Nekohealth.com
[50:15] wait list and we'll try to get to you as soon as possible. >> And this is in New York 300 Lafayette Street. >> So only New York so far but we're expanding quickly both the number of venues we have in in New York. We're launching in Florida as well in Miami and we're launching in DC and we're going to try to launch all over the US in the coming 12 to 24 months. >> Yeah, it's great right on Houston Street. That's a back in the day when pseudo had their big studios they were right around the corner from you. Talk
[50:46] about memory lane. All right, continued success. Everybody go to Nekohealth.com and sign up for the wait list. We'll see you next time. Bye-bye. >> I'm going all in. >> [music] [music] [music] >> I'm going all in.