Google I/O 2026, Birth Rate Debates, SpaceX IPO, Karpathy Joins Anthropic

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We are live from the team panel trail the temple of technology the fortress of finance the capital of capital Google IO starts today uh and the stock is ripping I think uh people might have missed this if you haven't been uh watching closely but Google is up 140% in the last year absolute ripper it's almost a$5 trillion company now 46 >> I was really confused what chart you're reading because it's down 1.3% today >> today okay no it is up it is up massive think in years, sometimes decades. >> Yes. Yes. Uh and and uh yeah, they pulled in just shy of $110 billion revenue last quarter. Uh and they're in a great position for the next era of the AI story. So, uh GCP is growing faster than AWS and Azure. Um Wall Street has basically fully repriced the company um uh as a like a full stack AI winner. That's the new narrative across uh Google Cloud, Google search, Gemini, the models, DeepMind, everything that they're doing. Uh so long gone are the concerns about Google's search weakness. Uh because even core Google search is so is showing resiliency. Uh Google search the business continues to grow. Queries are at an all-time high. They're not reporting exact numbers of queries, but Sundar said that on the last call that it's at an all-time high. Certainly not going down. and uh search and other revenue which is their bucket there is uh is up 19% year-over-year so holding up well uh and Google IO generally offers consumers uh launches or previews of tons of new products I'm getting called um uh previews of tons of new products and features um and uh the Verge was saying that there might be some like AI fatigue which is maybe an overstatement given that, you know, people are getting booed. Actually, the former CEO of Google uh yeah, understatement given that uh the the former CEO of Google, Eric Schmidt, was booed off stage at a commencement speech. Uh and so, uh that is a good point. But, you know, the people that watch Google IO, the Google core consumers, uh they are fans of this stuff. I think they're generally pro AI, excited about new features. Some of the new features that we'll show are very, very cool. Um but uh there is this like goal of being ambient and useful instead of pushy and desperate. Uh many Google experiences now have duplicative Gemini panels. And I was writing this uh update in a Google doc and I noticed that I had two Gemini stars basically uh one Gemini star in my Google doc and then another in the Chrome browser that I'm using to load Google Docs. And uh and it's a really hilarious outcome because I was writing this in sort of like h a half window to the side of the screen and if I open both Gemini panels, the Google doc disappears entirely and I'm just left with two chat boxes to interface with a Google doc which I don't really use AI in the actual Google doc. I just kind of write it. Um but uh there's you know there's stuff it everywhere and then actually make it useful, make it ambient, make it uh delightful. And so, uh, that is, I think, what consumers are looking for, more than just an AI button in a new place. Uh, but they're certainly showing that already. Um, and so, uh, uh, the new Gemini video model looks incredible. We'll play some videos of that. Uh, and there will be tons of delightful experiments that may turn out to be blockbuster products or they may get sheld by year end. That's kind kind of the beauty of Google's culture is that they have plenty of opportunity for experimentation. Uh we sort of uh some people remember all the all the things that are in the Google graveyard. Uh but uh most people just remember Gemini and whatnot. So yeah, we can play this video uh with sound because the sound >> V8 engine features eight cylinders arranged in a Vshape driving a single crankshaft. They take turns firing to deliver smooth massive. That's pure mechanical genius at work. A V8 engine features eight cylinders. So, I feel like this got rid I mean the the video fidelity is incredibly high quality. There's no six fingers. It it looks HD. The motion looks good. The lips are synced. And I feel like they got rid of that like hollow sound that you used to hear in AI video that where the audio was generated, but it's a lot more subtle. >> It's really subtle. Um there is one weird thing in this where uh it says pure. He says deliver pure massive and then it just cuts to the next scene. If you That's pure mechanical genius at work. A V8 engine features eight cylinders arranged in a Vshape driving a single crankshaft. They take turns firing to deliver smooth massive that's pure mechanical genius at work energy or smooth massive propulsion something like that. So like it's crazy because you see these and you're like ah like this is it like it's done. Like this is fully fully done and then there's just like ah we're at 99.9% now and I want to be at 99.999%. Also, like this is kind of a nitpick, but isn't that a V6? Right. There's >> Wait, play the video again. Let's see. I want to see if it's a V6 or V8. Uh because when I look at those graphics, I think uh Okay, let's count the cylinders. Oh, yeah. No, no, it looks like an eight. It looks It looks like eight cylinders in the back. Now, count them up. >> I can't really tell, but yeah, it it it's odd. It's It's uh It's so passive, but uh I don't know. Is it good for video explainer channels on YouTube? Bad for video explainer channels on YouTube? Certainly commoditizing the production of video explainers. I've seen a lot of these video explainers that will show you like inside of a rocket or inside of a an RPG or or an AK-47 or Glock. And those get like tens of millions of views. They can be viewed in any language. Uh but they're very intense from a uh from a CGI perspective. Maybe you have to go and model every little detail, every pin in the in the weapon or whatever the object is that's being visualized in this particular video explainer uh close to being on command. And then the question is where does the value sit? Does uh if you prompt YouTube and you ask for a video explainer of uh you know a chair break it down, explode it, show me the inards, will it just do it on demand for you? Will it just generate that or will this still sit below the creators? Uh >> yeah, I've always had the question at what point do you go to YouTube and there's just a series of videos waiting for you that were generated based on your interests. Right. Sometimes sometimes, you know, you might be going to YouTube because your favorite uh sports team just played and you want some analysis on the game or, you know, your favorite fighter or something like that or some news is happening. And it doesn't seem like we're that far from a future where you land on on YouTube and YouTube is just again fully generated a video based on what it knows about uh your interests. Uh that said, that would cause potentially creator strike. >> Yeah. >> Because it's YouTube starting to compete against uh their own, you know, content producers on the platform. Yeah. >> So, we'll see. >> Yeah. At least in the interim, it feels like uh the dawn of stock footage. YouTubers have been creating these have been using these tools for a long time. They have been getting cheaper. Even the uh the CGI world has become uh increasingly commoditized every year as you get more to templates and uh and the tools become cheaper. Uh you used to have to pay thousands and thousands of dollars for a license of Cinema 4D or 3ds Max to render anything. Now Blender is open source and free and there are tons of Blender artists out there with uh custom packs. But yes, this is a a new capability and uh it'll be interesting to see how this gets integrated, what the push back is like, how clockable it is once it's actually in the hands of creators and they are pushing it out. Um let's watch this other uh science explainer from the timeline. Uh Gemini Omni explains science with video. Thanks a lot for this says Chattaslua. Uh now every student will get a custom video for the topic of science and math. I'm so happy like while typing I want to see all your reaction to this. I don't know >> which looks white. >> This is about photosynthesis. I think >> every color of the rainbow. As this light enters our atmosphere, it crashes into molecules of nitrogen and oxygen. This triggers a phenomenon called scattering. Because gas molecules are tiny, they affect shorter wavelengths much more than longer ones. Blue light has a very short wavelength. So, it's scattered in every direction filling the sky with color. Meanwhile, longer red wavelengths pass. There has been a big push on YouTube for like >> as people ask questions like they would go to Google and say like how do I fix this particular washing machine? You type in the number of the washing machine and it would take you to not just a single video about someone fixing that washing machine but uh the actual section in the video with the solution to the exact problem you had. And being able to read a manual and constitute a video on the fly of exactly that is pretty incredible. and you could imagine satisfies that use case very very quickly. And then of course there will just be entertainment uh and all sorts of different use cases. Uh Logan Kilpatrick, friend of the show says, "Introducing Gemini Omni. Omni is our new model that can create anything from any input starting with video." Starting with video. Uh think nanobanana but for video. Okay. Uh Leah, let's play this because there's some amazing like different styles here going on. I wonder if those if that if that motion graphic transition was created in Omni because that's something that uh would you'd normally bump out to After Effects for or like the edit here. I wonder I wonder if uh if if you'll be able to upload multiple clips and have it edited together to the beat of a song that you pick or will it be able to AI generate a video and then match the match the footage to the to the beat of the video. Uh so it says give it anything. So I think you could potentially give it a bunch of videos and it could edit it together into a vibe reel, something like that. Swap style, swap environment, swap angle. Uh they've been having a lot of fun with this. Um, everyone is uh very very excited about this. Um, the other uh news out of uh Google today is Gemini 3.5 Flash, our most powerful model to date. It pushes the frontier of e of intelligence, speed, and cost, putting 3.5 flash in a class of its own. Uh we spent the last six months making sure Flash is great for real world use cases. Um it's the strongest agent coding model yet from Google. Uh it delivers frontier level performance at 4x the speed of comparable Frontier models often at less than half the cost. So uh dominating the paro frontier has been the goal for a long time. Um the the speed is being heralded as a key feature. Uh Google just showed a demo of Gemini Flash running between 600 and 1400 tokens per second on TPU8. It peaked out around 1480 talks per tokens per second with an average of around 800 tokens per second. So very very very uh very fast. Uh the flip side is uh it's more expensive than previous flash models but that's been the trend with uh smart smarter intelligence for a while. So uh investors are focused across three key areas. Not so much the consumer story uh more uh the next Gemini model. So where this fits in and then what adoption and diffusion looks like uh how Google through Google cloud will be getting this out into enterprises into coding agents obviously they have anti-gravity but Gemini CLI has not seen as much traction and so uh better model might pull that forward might wind up seeing more traction there overall I think token generation at Google is up 7x year-over-year which seems great it's unclear how much of that is because there's more reasoning happening But given the fact that the Gemini models are sort of stuffed all over the product surfaces, I'm not surprised that there's massive growth. That makes a lot of sense. Um on the core Gemini model, everyone was wondering, are we getting four uh 3.5 launched? And there's a stage roll out with Flash going first. Um Andrew Curran had an interesting post here talking about the lack of vague posting. The Deep Mind folks have not been vague posting about the new Gemini model. So he did some vague posting for them. Uh he says at this point everyone knows it's arriving tomorrow along with their personal agent named Spark. Uh this reticence of course can be interpreted in many ways. I'm choosing it to I'm choosing to interpret it in accordance with my nature. I think they trained the largest model they've ever successfully trained. Probably possibly the largest one anyone ever has and something unexpected emerged at scale. They had their mythos moment but not in the same way Anthropic did. Gemini has always been very a very different model from Claude. The benchmarks will go out today tonight under embargo. They probably already are, but I don't think they will fully reflect what I'm talking about. I think they hit something even they weren't aiming for something that surprised them. If I'm right, that surprise will be part of tomorrow's show. >> We shall find out together in the morning. I I I don't think tomorrow's show because IO is a number of days and there's a whole host of uh different uh announcements that could that that could happen in the interim. There's a lot of other things going on and >> yeah, has anyone been vague posting around will there be a 35 Pro? Yeah. This week? >> Yeah, that's going to happen over the course of the next few days. They just started with Flash. >> Okay. Starting with Flash. Cool. And then uh they also announced Spark. >> Yes. >> Which is a personal agent that lives in anti-gravity. >> Oh, okay. >> It's my understanding. >> Oh, interesting. And so uh trying to make >> when I hear personal agent I think more like Gemini app, Google search like Gmail like the very like the consumer product services. I think well I guess I just think personal and I think consumer but given how much people are using codeexcloud code for like personal like things like just because writing code creates a more dynamic agentic surface. Open claw we saw all of this uh it's helpful to have something running on a MacBook Pro that can go around and find different stuff. What? What? >> Uh yeah, just some additional context. Uh 3.5 Pro is coming out next month. >> Next month. >> So not uh this week. >> A little bit of a delay there. I wonder uh I wonder what else is in the bag of like mythos like surprises because the cyber security one was like sort of predicted by the AI 2027. I feel like bio is next. Like it feels like okay we tested a bunch of stuff and we talked to a bunch of scientists and like this thing can come up with like super viruses and it's really scary. So, we got to give it to all the pharmaceutical companies in advance and like Mona gets it and creates like anti viruses or something like that. I don't know what else. But I'm sure there will be surprises. There always are in the AI era. So, um from a from an investor perspective, obviously uh I don't think Google IO is necessarily the correct uh forum for discussion of a mythos level breakthrough or surprising new emerging capabilities. I I would just be surprised if that's the where like you stand on stage and you say, "Hey, we had this crazy breakthrough." That's it's a more serious thing if you're talking about uh new capabilities. Uh but given the talent and resources of the DeepMind team, TPU, I think that there's just a lot of broad optimism about the next iteration of Gemini. They've hired a bunch of people. They have a bunch of surface area to deploy this into. So, no one's expecting like the model to underperform. Uh, agent commerce will also be top of mind for investors. Uh, since messaging around the Google, the Gemini app has sort of strayed away from advertising as an immediate monetization engine. I think Demis said that at Davos. Uh, Google has a lot of capabilities when it comes to closing the consumer shopping loop. Like they have Google shopping, they have a bunch of hooks into all sorts of different e-commerce services. They have massive product cataloges. Uh, people search for stuff on Google all the time to buy. uh and uh but uh e-commerce customer behavior seems to be lagging expectations here generally. There's been a lot of announcements from companies around agentic shopping protocols uh and uh and and the numbers whenever we dig into them we're always like is it going to get to 1% this year? Are we going to see and everyone's talking about the growth which means we're growing from zero obviously because this didn't exist. Um but where is it going? Will Google have something to show here? Will they have some sort of demo of a of a new user experience, a new flow for agent commerce that results in, you know, a faster takeoff of that adoption of that behavior? Uh, personally, I've done a ton of research about products through LLMs, but I pretty much always hesitate to have AI fully process the checkout. And there's a few reasons, like Apple Pay is pretty good, pretty seamless. Shopify saves all my annoying info. Autofill is also not that bad. It's usually pretty good in whatever native. If I'm in Chrome on on Mac or I'm on Safari on iPhone, uh it's usually pretty good. And then I feel like I still like reality checking carts before clicking pay. We talked to Joanna Stern about this too where she was talking about having a uh having an an AI agent assemble a cart of even like something like groceries, but then she will be the one to actually go to the the hydrated final link with the cookie and then go and like validate everything before clicking pay. Uh the last focus area for investors generally is TPU. Uh there's been a lot of back and forth around are too many of the TPUs going anthropic are too many of them uh are they sitting idle at at Debbind? What's going on with the TPU? And how uh are uh what are the margin structure? How are how is revenue booked around TPU? How are how is the backlog accounted for? These are questions that investors on Wall Street are asking. I don't think we'll get answers at IO. Uh but investors will be watching for anything that sort of contextualizes the shape of Google's TPU business and their plans over the next few years. Um and so as I mentioned yesterday on the show, we had a lovely conversation with Joanna Stern from thenewth.com uh and the author of I am not a robot. And uh we had lots of fun takes about like the AI tools that I think most of us have interacted with. Everyone's used agents. Everyone's sort of felt what it's like to talk to a chatbot. But uh one place where she went deeper than I think most consumers and like AI fans have is in the wearables because she was wearing that recording device consistently. And she maintains that like humanoids are farther away. You need a lot more training data. The AI chat apps are here. We already know they're diffused. Whimo is now boring. But uh the next big wave she's sort of predicting is uh in the next few years wearables will have like a big moment and everyone will be sort of adopting these and contending with them. And uh it is interesting how you know we talk about a capability overhang in the enterprise with AI deployments and that's why the big labs are partnering with consulting firms and private equity groups to get AI uh installed into large corporations. Uh there's even more of a capability overhang in consumer hardware. Uh, it Apple iterates extremely methodically. You know, they made a big story about Apple intelligence. Was that just one year ago? I guess that was one year ago because WWDC is in a few weeks. Um, but >> feels like longer than that. They had I I just remember they did a global billboard campaign for Apple intelligence. >> Yeah. But anyway, like the actually changing anything in hardware takes Apple a long time. They still haven't launched a folding phone. like they they they take their time to deliver a great product at the right time. Um and then if you're a challenger uh and you just want to manufacture new devices at scale, that takes years to ramp up. And then you also have to, you know, distribute, sell, it's not one click away. It's go to the store or wait and wait for the mail. Uh and then hardware decisions that get made around certain AI workflows uh can potentially be obsolete in months as the underlying technology changes. So you could divi you could build a device that assumes that uh you know LLMs are the end state and then reasoning models come and you're not set up for that potentially uh on device compute could change. It's unclear uh and so you you you don't want to get w locked in these things and you were talking about the humane AI pin how that maybe could have been successful at Apple. Uh, even the Rabbit R1 I think like >> well my my my main point was that if that was an internal project at a bigger company just showing like a potential future state for consumer hardware it would have been an amazing demo and probably been able to receive more funding at let's say a hyperscaler but as a standalone company >> sales come in people don't like the product and then nobody's willing to give them more money. Yeah, I mean you look at how many shots on goal Mark Zuckerberg has taken with the Meta Ray-B band displays and the Meta Ray-B bands like that was something that I I I would be surprised if you look back at the R&D cost, the manufacturing cost, the early sales figures of the version one of the Meta Ray-B bands and and it's off to the races. Like he clearly said, you know what, I'm going to double down on this for years. We're going to continue to invest in this, get this to a place where it can actually become known, become a product that people consider. when I show them another ad, they'll consider it because they've seen it. Maybe they've tried it. Maybe they've I I went skiing with someone who had a pair and they were talking, they're sending text messages. And so, it's just familiar familiarity with the product takes time. Uh and Google's had some fun swings at these like preview emerging hardware platforms. Uh Google Glass, I mean, way ahead of its time. We're now there with the meta rayband displays, but even those are not selling by the millions and millions. Uh they're they're very early stage. uh Google Cardboard. I don't know if you remember that one. This is you put your phone in a cardboard box that they send you and then you can put it on your face and use it as a uh as a VR headset. >> Whoa. >> Yeah, it was uh a tiny little I think it was open source just like a fun preview of like how do we get more people to be able to watch 3D stereoscopic, you know, VR type content? Well, >> experiment of how can we strap someone's phone to their face >> basically. And then they also did the Samsung Galaxy which was uh yeah, you'd slot it into like a piece of hardware, but much cheaper than buying an Oculus at the time. Uh Fitbit also sort of fits in there. There were previews of the new Google book and the Fitbit from last week. And uh I'm I'm I'm excited about the possibility of a new swing from Google like being like the wildcard headline that makes it out of IO this year. So uh anyway, uh are there any other Google IO posts? I mean like the the the actual conference is going on as we're doing the stream. So I wouldn't be surprised if there are announcements hitting the timeline right now. >> Yeah, there's uh people are pulling uh some of the benchmarks comparing it on the uh AI artificial analysis coding index. >> Uh Lean Algib says 35 flash scores kind of low on coding index due to rough uh terminal bench hard scores. So, I think the big question coming out of IO today is how do developers respond to the updates to uh anti-gravity to 35 flash? The speed is amazing. We know how much people care about that um in in just like day-to-day coding. Uh but the model has to be able to perform. So, we'll see what people's reactions are and we'll see if um we'll see if Google can really start to ramp uh revenue on on the codegen side or still get uh exposure to that through Anthropic. It did come out yesterday that Demis >> is an angel in Anthropic himself. >> Um >> and uh I don't not not super surprising. Um although uh less push back. >> When did they Yeah. When did they meet? I wonder what the story is there. how how early he got in because he might be sitting on a bag. Uh well, who else is going to anthropic? Andre Karpathy has gone from OpenAI to Tesla to anthropic. I think he went back to OpenAI at one point in in there. Uh and Andre, a different account, uh is pointing out this KMT general who defected and subsequently betrayed uh five different uh five different countries in Asia, ending in Japan. uh jumping around. He's seen it all. Certainly the world tour of uh of AI labs. Uh I guess he I guess Andre Karpathy was never inside of XAI because he was sort of the precursor at Tesla. But >> yeah, Elono he was poached by Elon. >> Did he work at Google point? I feel like he might have been at Google before open. I don't know. I I I know that there were some people that got maybe I >> So he he interned there. >> He interned there. So he's PhD. >> He's got the he's got the Thanos rings. uh huge pickup uh and excited to see what they do together. He's apparently according to Alex Heath going to be working on uh basically RSI. >> RSI. Yeah. >> RSI's continuing on his uh like auto research project. >> Oh yeah, he's been doing RSI basically in the open source world. Uh auto research is open source, right? >> Yes. >> Okay. >> Yeah, it's uh I I think you can read into this that it was effectively an aqua hire of the company he was working on. So >> Oh, interesting. Uh I don't Yeah, I'm assuming >> he said he was going to like get back to the education project that he was >> Did he I thought he had I thought he had raised for it. >> I don't think he did. >> Maybe not. >> I don't know. >> It's always helpful. >> Uh but that was a cool idea and I I I wonder how that fits in. It was always interesting to to think about like you know LLM are really good at education. I mean we're seeing that today with the with uh Gemini Omni. Uh like it can generate a video for you. Now we haven't really pushed it to the limit. Like I wonder is it like if you give it a PhD level problem is it going to teach you as well as you know a a great professor who has thought about all the different responses like maybe it's not fully there but uh it's like education certainly seems on like the core path of the models. Uh whereas there are plenty of things that sit outside the core path in things with network effects and things that are touch the real world and physical world and uh all these different things. uh just going to a computer and asking teach me something felt something felt like something most of the AI models would get very very good at because there's a lot of training data there's a lot of open- source uh educational materials all the textbooks haven't been scanned Wikipedia is in the is in the models there's so much uh information that's readily available it isn't uh tightly held secrets that are hard to bring to bear in the pre-training data but >> one more thing out of IO that we forgot to cover uh Google's new synth ID framework that 11 Labs, OpenAI and Nvidia are joining forces. This is to help identify AI generated content basically creating a standard for across platforms so that uh yeah when you generate an asset 11 Labs OpenAI >> uh uh Gemini Omni it'll it should be auto detected by the different platforms. >> Yeah, I' I've seen that on X recently. There's been a little tag that says like made with AI and but I feel like you can get around that if you screenshot it and stuff. Well, so I I think the ones on X are are just in the metadata. You can actually change it like fairly easily. I don't think it's actually using like like on on Nanoban images on GBT image too. There are like watermarks. You've seen these like weird patterns people posted. >> I think subtle changes to the to the saturation or >> I think they've just been it's just been metadata so far, but I >> Yeah, the trick with all those is that like it's in theory pretty easy to like rip that out. um if you're running like an advanced AI, you know, slop avoidance detection uh system or something, but uh just to know, okay, you know, for the average for the average poster, if this is an AI image, that's certainly helpful. Uh, but as you start bringing different assets in, you bring in some stock footage, you bring in some AI footage, you blend them together, you're doing a lot of different things, you'll probably lose a little bit of that AI detection ability, but uh hopefully people aren't too annoyed by it if it's used tastefully. I guess it shouldn't matter at the end of the day. Uh, anyway, uh, do you think Spotify used AI to create their new disco ball icon? This was burning up the timeline this weekend. I was I was shocked at all the negative reactions to this icon. >> Me too. >> What's wrong with you? What's wrong with you? Seriously, if you don't like this, >> I I will say at first it threw me off. I was like, where did my Spotify app go? Cuz it's too dark. >> Genius. I think it was genius. I opened up my phone and I was and I was I was drawn to it immediately. My eyes jumped because I was like, "Something's wrong with my phone. Something's wrong with my home screen. things don't look the way they normally look. It drew my eye. I saw, oh, Spotify. Okay, look a little bit deeper. The icon looks a little bit different. The colors a little bit deeper. Oh, there's something else going on there. Peel back the onion. You see that there's a disco ball. And then, of course, that uh there is a meaning behind it. They didn't just uh the there's a whole there's a whole reason why they did this. It's uh the 20th anniversary of the company. And so, lots of people complained, but uh party your party of the year. It's uh it's so funny because I don't I don't know >> prior to this were people sitting around >> being like, "Wow, I really hope they never change the Spotify logo even for a few weeks. I just love it so much." >> Yeah. >> Right. I think it's fun. I think it's a nice change from, you know, the flat minimalist logos that we've all grown accustomed to. >> Keep it. >> And so, yeah, let's go through some of the reactions. Uh Dylan said, "I thought this was fun. I'm sure the complainers thought so too, but when tapping an icon is second nature after being >> citizen says, I told my wife to cancel our subscription." >> Oh no. >> Uh for so long, even the slightest change in appearance can make you double take when searching for it. And that's annoying when trying to open an app. Uh Mass says that it's too it's too uh dark. And so Mass turned up the >> You're at the disco, John. Oh yeah. >> A disco ball would never look that bright. >> Yeah. >> In a nightclub. >> Okay. Yeah. I mean the black >> disco ball knowers. Yeah. That's way too that's way too light. >> I like uh Notion played along. This is like really a testament to the the power of Gen AI imagery these days. Every brand could like jump on this meme very quickly and it's hard to create. >> It's so funny that Yeah. that I guess you know this still went super viral but >> even five years ago if you could create an asset that was a 3D render you almost automatically got attention because >> anybody could make them >> but you needed to work with like a >> 3D artist yeah >> artist to do it and it take it it's not something you can do instantly too they have to figure you know actually render it can >> I mean yeah probably like a couple hours of work in Cinema 4D I mean getting the lighting right too and and making sure that you're not have the wrong reflections on there. There's a bunch of nuance uh to actually getting this to look good. Uh I I think it's fun when I don't know the the the other brands like joining in on like a meme can be like done really poorly. This one seemed like it was fine. >> Yeah, Andy Massley had the best take. He said, "Everyone complains about minimalist design until the company tries some until the company tries something fun and everyone reels reveals why all the companies have been forced into minimalist." >> 66,000 likes on this. People really really agreed. Uh this is how I feel when people complain about Cyber Trucks being ugly. Like yes, but it's different. Of course, not everyone is going to like it. Trying to get everyone to like things is how we wind up with all cars converging on the same colors and designs. Interesting. Yeah, that's a good point. I like the disco ball. Um, someone uh Nathan Halberstrad said had a very nice comment. He said he said this is uh this is TBPN inspired which I don't I don't think it is but the arc may be long but tech companies now appear to be universally bend to universally bend towards aping. >> I mean look at our look at our look at our uh >> so we do have the globe and and it was funny because so you can you can go a little bit further and uh I I did this with our logo. I was like, "Turn our logo into a disco ball." And, uh, it looked kind of the same like because we sort of have the globe in there already. And so, uh, for all of like like this meme like sort of didn't work with us because I guess we have been, uh, taking that like 3D render aesthetic with the globe, although ours is pixelated, not not squares like on a disco ball. Uh, but there is a little bit of TVPN in the in the disco ball. Uh, what do you think of the the TVPN disco ball logo? Should we run this for a while or has the trend already moved on? >> I like the globe. I like being global. >> Yeah, I think keep the globe with the pixelation, the dots. I think it works. Uh, the era of discomorism has arrived, says Fara. Uh, Fachara. Uh, and this, uh, individual disco ballified all of their apps, including X, Claude, Slack, uh, what's that one? The App Store, I guess. uh Google calendar. Uh I don't know if you ran this if you ran this full uh people do people know why Spotify was a disco ball. >> This kind of loud maximalist design is coming back whether you like it or not. >> You think so? >> These things go in these things go in waves. >> Yeah, they go in waves. >> They're coming back. Well, uh, one story that we didn't get to yesterday that I want to discuss is the root cause of the fertility crisis. Uh, the Financial Times has a deep dive, why birth rates are falling everywhere all at once. And, uh, I was going back and forth with Tyler on this, uh, trying to understand, and we'll we'll we'll we'll see where you stand on this, Jordy. Uh, so the demographic landslide defining our era is gaining speed and terrain in more than twothirds of the world's 195 countries. The average number of children born to each woman has fallen below the replacement rate of 2.1. That keeps population stable without immigration. In 66 countries, the average is closer to one than two. In some of in some, the most common number of children born to each woman is zero. Uh both the pace and the breadth of the decline are defying expectations. Just 5 years ago, the UN predicted that there would be uh three 350,000 births in South Korea in 2023. That was a 50% overestimate. that the real figure was 2300 uh or 230,000 sorry not 2300 uh while high and middle inome countries have been wrestling with demographic decline for more than half a century the phenomenon has marketkedly accelerated in the past 10 years uh analysts of data ranging from population records to Google searches indicate that although many factors contribute to falling birth rates the most recent plunge appears connected with our use of technology and so this is the question that the Financial Times is trying to answer should you put the blame on the recent decline in fertility on uh on smartphones in particular. And so yeah, you you can go through a whole bunch of the charts. It's a it's a great article, but um the the final image is this image where they took a whole bunch of different countries and they and they adjusted the charts to show when did smartphones actually take off in that particular country because uh America had the iPhone moment in 2007. uh but different countries got wide smartphone adoption or 4G or uh or actual rollout of of cell phones or smartphones um at different times and so they adjusted all the figures and when you look at this chart uh that Lewis uh Gian Carlo is sharing um the screenshot from the Financial Times you'll see uh all of the charts seem to be very very closely aligned um at the exact same time um and so Lewis Gian John Carlo says pushes back though. He says no smoking gun, but the preponderance of evidence points to smartphones, not economics as the culprit. Yeah, there's the chart. It looks like a smoking gun. He says it's not though. He says in the US and UK, births fell first and fastest in areas that got 4G earliest. Birth rates were stable in the United States, UK, Australia until 2007, in France and Poland until 2009, Mexico and Indonesia until 2011. and Ghana, Nigeria, and Sagal until 2023 uh 2013 2015. Each of these inflection points matches local smartphone adoption. Uh the younger the age group, the sharper the drop inperson socializing among young adults is dropping in Singap uh in South Korea by 50% in 20 years. Uh effect is largest in culturally traditional societies, Middle East, Latin America, subsaharan Africa. decline holds across countries hit hard by GFC and those were who were not hit by the global financial crisis. Um and so it teases out a bunch of the other possible explanations and puts the blame firmly on smartphones but people have been pushing back. Um, so Ross Douet says on the RA on the latest round of fertility discourse, friends don't let friends share chart one without the important context of chart two, which is the child survival adjustment. And so if you look at the total fertility rate, if you click on that left graph, uh you will see that the baby boom is remarkably pronounced there. But in fact, birth rates had been declining since the 1800s. Uh, and had been falling steadily throughout the 19th, is it the 19th century? Yes. And then in the 20th century, there was a brief baby boom in the 40s, 50s, 60s, and then the rate starts declining. Uh I I asked 5.5 Pro a bunch of questions about this trying to dig in further and uh it had a bunch of funny answers about how children used to be economically valuable and so people would have a lot of them to like work the farm for them. And the economics of having a child flipped at a certain point where it became expensive and and a net sort of a net burden on the parent as opposed to before it would be you had a kid, you didn't have to pay for college, you didn't have to pay for education or really anything and they would work the fields for you and so it was advantageous to have as many children as possible. Uh Ross Dowit also uh chimed in saying by uh by the way another way to look at the second chart is that the baby boom was even more unexpected than generally understood and also if any major population repeated that kind of unexpectedness. Now they would dominate the human future. Interesting uh opportunity for different societies out there. Um >> do you think uh children yearning for the minds is is sort of like a survival mechanism? Right. They >> they want to be >> they want to be economically valuable. They want to be productive, right? >> They're saying >> they're saying we can >> we can uh we can carry our own weight. >> Yeah. >> Um yeah, I mean it would be uh I I look at all these charts and I just think it's over. >> It's over. But then I remind myself to never black pill. >> Yes. >> Uh never black pill. Uh even if it's down >> never black pill. >> Never black poo. >> Uh never black pill even if it's down only. Um yeah. Uh it's crazy. It's really crazy to look at these charts looking at uh looks. I mean, if if this were uh you know, uh any animal in the wild, >> there would be huge amounts of fundraising happening to try to save >> the species. Uh but uh when it's us, >> yeah, >> we just sort of like, you know, see the chart and just keep scrolling. Yeah, I think uh it demands investigation to go a level deeper to understand uh okay so diffusion of smartphones appears correlated with declines in fertility but uh there within populations there are groups that have higher than average fertility and lower than average fertility of course as any distribution suggests. Um, and the question is like what are the highfertility members of the population doing on their phones differently? Like are they using social media less? Are they using dating apps less? Are they texting their friends to come and hang out? Are they are they organiz because the the smartphones have diffused so widely that you need to cut in and understand uh for the groups that are uh above fertility rate. What are they doing differently? Obviously, the Amish are are an interesting case study because they do have a higher than replacement rate fertility. Uh, >> and they're not technology. >> They actually have adopted some cell phones, but not smartphones. So, they will use the, you know, like a dumb phone, a flip phone to make phone calls occasionally. And, and I'm sure that, you know, these are all gradations. There's not uh no smartphones whatsoever. But uh certainly the Amish have steered away from technology and the fertility rate has has stayed high. But uh even within the you know more you know modern enclaves or smart high high smartphone adopters I I do wonder uh what else is going on because there's a bunch of other interesting factors going on with uh child care and the relation with how people spend their time. Um >> yeah, specifically with the also what else happened in around the the launch of the iPhone? >> What >> like massive economic disruption, right? >> They controlled for that though that that that's the point of the Financial Times article is to control for the economic gerrations of different countries. So there were some countries that were unaffected by the financial crisis. There were some countries that went through boom periods. There were some countries that went through economic retra contractions and they were all sort of affected equally like uh even China has the lowest replacement rate one per uh per family or something like that whereas we America's at like 1.8 many societies many modern societies at 1.6 six all below replacement rate but China's the lowest but China's going through like an economic boom the entire time like GDP is up at six seven eight sometimes 10% a year like they're not going through an economic contraction certainly not from 2007 to today and yet although that is a little bit different because it's confounded by the one child policy which obviously resulted in exactly one child so they set their policy then they got their result and now they have to sort of contend with that the aging population um there's uh there's an article that Derrick Thompson shared Dad books, which this article and some publishing insiders use to describe serious non-fiction books across biography, current affairs, and business and economics, reportedly are reportedly in freefall with sales declining every year for the last years. The trend couldn't be clearer, said Jonathan Karp, uh, former chief executive at Simon and Schustster and publisher of the new Simon 6 imprint. Uh, when we have internal meetings to talk about this problem, it always comes around to podcasts. Interesting. saying podcasts are are eating the dad book serious non-fiction show. >> We got to figure out who's doing this. >> We're all looking for the guy who did this. Uh I do listen to a lot of podcasts. I still listen to uh audio books of serious non-fiction. Uh but it is uh it is increasingly hard to find the time. Uh FedSpeak says it's not podcasts, it's kids. Because the millennial generation, the Gen X generation is spending basically twice as much time with kids. uh based on their age when you adjust for age. So this is a curve of time spent with children uh by >> honestly every every time on the weekend you know when I'm holding you know one or two of of >> my children and I just stare at you know the stack of uh books from Amazon that just pile up and I just look at them and >> think okay if I open one of those I will get exactly three pages before I'm disrupted. >> Yeah. And so I >> What were what was the silent generation doing? What was the what were the baby boomers doing? Were they just like, "Kid, hit the minds, buddy. I I got to read. I got to read some non-fiction." I don't know. I mean, the podcasts creep in, but it's it's >> I listen to podcasts when I'm not at home >> when I can't read. Yeah. Right. Maybe uh self-driving cars bullish for serious non-fiction because Oh, maybe people will get sick. Self-driving cars are bullish for the infinite scroll. They're bearish. They are bearish for the podcast and and long for medium, the book and the serious non-fiction, the dad book. Anyway, >> uh nothing can compete with the feed. >> Yes. >> Sorry to blackell, but it's over. >> Uh well, it's not over for our next guest because Jim Blok from Sen Cut Sendend is with us. He's in the waiting room and he has some exciting news about Send Cut Send. Welcome back to the show, Jim. How you doing? >> Good, good. Thanks for having me. >> Thanks for hopping on short notice. Congratulations. Uh, reintroduce the company and then I want to hear the news. >> Uh, yeah, Sen Send is a on demand manufacturer. Um, elastic capacity is what I was told. So, uh, we make we make stuff. >> This guy has VCs now. >> Yeah. Yeah. Yeah. >> Buzzwords come they come ter buzzwords >> and buzzwords. >> They're they're good at both. Yes. >> But I like it. I like it. elastic capacity. >> Yeah, we do um sheet metal and CNC and you know whatever. Uh people need something made, we make it for them. >> Yeah. And the news today, what happened? >> I want to hit the gun. >> Uh I finally raised some money. >> How much? >> 110 million. >> Massive. >> Let's go. Let's go. Uh it's it's sort of bittersweet bittersweet moment because send cut send as a company you know we've interviewed uh thousands of of founders now and you have been you know out of all the conversations we've had at the top of our list in terms of like you know companies and and cultures and teams uh that we're bullish on and we always appreciated that you were doing it independently but I'm sure you've raised for very good reasons and you have some excellent new partners and uh we're very excited for you. >> Yeah. Uh I I want to talk about the the use of funds, the reasoning, but uh first like take me through the pitch that you received. Who who who who did the round? How did you meet them? Take us through like kind of the story of the deal. >> So I just through X I got introduced to Patrick Collison, which was awesome. Yeah. >> Um and he's like, "Oh yeah, I've heard about your company. You guys sound really awesome. Uh I'll invest." And I was like, "Oh that's that's amazing. Thank you." Um, I was like, "How does this work?" Like, "I don't know how investment works." And he was like, "Oh, I'll just introduce you to a couple other people." So, introduce >> We can just use standard YC terms. >> No, I'm kidding. >> Yeah. No. Well, I was like, "Hey, you know, introduce me to someone who's super founder friendly. Um, I'm a bootstrapper. I want to retain control of my company. Um, but I do want to go faster. So, I need a little bit more money than I got now." So introduced me to Sequoia. Andrew Reed over there is awesome. Shawn Magcguire. Um and then uh Matt Hong from Paradigm as well. And so it became this kind of dream team. And I was like, if I don't do it now, I I don't know if I'll ever be able to put this together again. So let's go for it. Let's see what happens. >> Yeah. And I also think you guys have such incredible have had such incredible organic momentum and growth and we need to make stuff in America and it's somewhat your responsibility to go faster like a as like a just for the country basically and so from that lens too I think it makes a ton of sense to bring in some more firepower. >> Yeah. Uh we're always u capacity constrained. We we have more work than we can produce. And even if even if we had the right amount of machines, it's not fast enough. I want to go faster. You know, people are spoiled on Amazon. I want to do Amazon of manufacturing. You know, if you order today, you should have it in your hands tomorrow so that you can go do your project. Um and now that's that's on the horizon. We're getting really close. >> Yeah. So, what uh what does the money actually go towards? Is buying more machines, hiring more people, both? like what what like what are you pulling forward with this capital? >> Yeah. So, I'm trying to just use the capital towards stuff that I can't finance. >> So, right now like we've been able to grow like you know I can buy machines and get a loan on them from JP Morgan or whatever. So, I'll keep doing that with machines, but the capital is going to be used for stuff that I can't get a loan on. So, you know, tripling the size of my software team, uh, computational geometry engineers, uh, hiring two or 30 hundred people, just a just a down payment on on a building, like >> the first and last payment is like I don't know, together it's like $600,000 on some of these big buildings. So, that's that's where I'm going to light their money on fire. Um, in a good way and we're going to grow grow. Yeah. >> Yeah. Uh, where's the current facility? Where do you see yourself expanding to? I want to talk about the actual footprint because uh you know if you're building elastic capacity that feels like uh that needs to be distributed all over the United States at some point. >> Yeah, a million%. Um my goal is like I I love Home Depot >> and without a Home Depot in your town, you got to go to a plumbing store and an electric tool store and a lumber yard and whatever. So if we could have, you know, a Sunut send in a bunch of different metros that you can just walk into and get something made, that's the dream. So, right now we're in Reno, Nevada, Arlington, Texas, and Paris, Kentucky. Uh, the next one up, I'm hoping for a lease here, is going to be >> somewhere in Pennsylvania, potentially in Ohio, but we're we're trying to pit those two states against each other and negotiate some good incentives. Um, so I can't really say which way we're going. Uh, after that, probably Indiana, uh, Las Vegas, and then Atlanta. >> Okay. Uh I had I had sort of a hot take yesterday talking about the the the push back to building data centers and and my point was that obviously data centers are the least they're they're they're less popular than nuclear reactors. Nuclear reactors at their worst. I think we're polling at like 63% disapproval for like let's not build those and of course we stopped building them. Data centers are like 73%. So people really don't like them. But my point was that uh there's a lot of like there's a lot of push back against building anything even like housing, roads, trains. Like people are just like I like the idea of it somewhere else but I don't want it in my backyard. I don't want it over here. Like if it actually interfaces with me and I'm wondering if how how local communities are actually uh receptive or skeptical about having uh what is essentially a factory and could be noisy or could have traffic or could have a bunch of different things. And I imagine that you've had like one 1 millionth of the push back, but you've still had to consider all these things. So, how have you how have you communicated to the local communities that you build in and you're planning to build in? >> Yeah. I think some of the the loudest push back is from, you know, people in these big coastal cities and, you know, they're like, I I don't want that that in my backyard. >> Yeah. What we find is, you know, in we're in a smaller city or a rural area, people love the jobs. They love the development. They love the the taxable revenue that comes with us. >> Um we're also we're pretty damn quiet. We don't exhaust to sewer or air or anything. We're we're 50 state compliant. That's that's our goal. >> Um but what what's really cool is we can come into a community and provide a lot of good highpaying jobs. uh you know it's it's a career path that they can grow into. There's more opportunities as we build more buildings. They can move out of their little town and go to a different metro or whatever. So uh we don't have any push back. Also, we move so damn fast that we don't build our buildings. We go find a building that's already stood up and we just move in. That's the only way for us to go fast. >> Yeah. Yeah. And there's plenty of and there's plenty of capacity there. Uh, as you look back on your career, how did you process the the the VC hype or just the memes around like the 3D printing revolution and there there was a moment where there was like, oh, like there won't be any more factories because everyone just 3D print everything at home. Uh, how'd you process it at the time? And I guess like what like how do you see 3D printing fitting in if if at all into like the future of re-industrialization? Does that have a place whatsoever? >> It does. It does. Um, in the world of metals, we're still far away from that. It's so much easier to get something cast or stamped or laser cut or whatever. >> Uh, I mean, when we've experimented with 3D additive in house, like there's laws against how much of that aluminum powder you can have because it's explosive. So, >> there's massive hurdles to clear for that. However, 3D printing, um, it's it's actually really competitive with injection molding. And that's something that we're looking at. Injection molding is incredibly expensive to get the molds made. Uh they're almost all the molds are made offshore, but if you can 3D print uh really really rapidly, then um it is competitive, especially for small runs or startups or prototypes or whatever. So that's an area that we're experimenting in. >> Mhm. >> Uh what are some recent customers that you started working with that you're particularly excited about? They can be mom and pop hackers or big big companies, but uh wanted to give you a chance. Yeah, we we actually my comm's team that I have now just just told me I have to be careful about who I name. Uh we were pretty proud though like >> it is it is mom and pops, but then it's also what 85% of the top five primes uh and the tier one defense people use. >> Near near us is a huge uh customer. Zipline is a huge customer. Um and then just guys in their garage making cool stuff and like kids doing first robotics or whatever. They all use us. So, uh, very very wide spectrum of customers. >> Amazing. >> What what what does an entry- level job at Sun Cut Sun look like these days? >> Um, anything. You're a generalist. We are moving so fast and doing so many different things like we don't have a designated floor sweeper, but you might be sweeping floors. Uh, >> you know, we start somewhere between like 26 and 30 bucks an hour. Uh, and then it goes up from there. Uh but yeah, you're you're going to be maybe a laser operator one day. You're going to be driving a forklift. You're going to be cleaning out a dust collector. Um or you're going to be doing some intense CAD programming. Like it's who knows? We don't know what we're going to make that day. Uh things just come in and we have to do it. So, everyone here is very very flexible. >> Yeah. Uh- w with the crazy like AI buildout and data center buildout going on, we've heard and seen like, you know, prices of copper spiking. like there's all these weird knock-on effects from data center construction. Are you feeling uh squeezes anywhere in your supply chain? Do you feel like America is industrialized enough in your uh in the rest of your supply chain or is there like a wish list of oh we got to reshore that? >> We need to we need as many like aluminum boundaries and smelters as we can possibly get. I mean those are way more electricity intensive than data centers. Yeah, >> actually if you if you tried to spin up a bunch of those, it would make a data center look really good in comparison. So that's >> if you want to build a data center, go pitch an aluminum foundry first. Wow. And then they'll want you to do like 10 data centers. So we need more of those. >> Yeah, >> but we need I saw that with the straight of her moose closing that Diet Coke was at risk of going out of stock. Very very harmful to my production function. But um because uh some there's some amount of aluminum smelting that happens in the Middle East and passes through the straight of Hermuz and so delays happen and I think a lot of people aren't they they think it's either we have the capacity in the US or maybe it went to China but there's really nothing else but we're in such a global economy that there's so much more going on. >> Yeah. Uh it affected us a little bit. You know there about 15% of aluminum uh comes from offshore. We actually source a lot of domestic aluminum or at least it comes from North America. Um but you know even if prices go up 15 20% raw materials are a small fraction of the overall end price. So 15 or 20% increase in raw materials is probably 3 or 4% to the customer. So our customers have been pretty cool about it. >> Yeah. I mean, Jordy asked about the the the customers uh like specific examples, but I'm interested in like the broader funnel like how much is do you have an outbound salesforce at this point? Are you going to conferences? I imagine that you show up on like Google results oftent times, but what like is it is is the customer funnel like heavily diversified or is there a sweet spot that you're really doubling down on right now? What does acquisition look like these days? >> We've always been inbound. Inbound. We we have two or three sales guys right now, but they just, you know, answer the call and and, you know, do special special projects or whatever. We have no outbound sales guys. Uh, at one point early on, we were spending about 100 grand a month on Google ads and I think right now we're spending about 1,500 bucks. >> Wow. >> Um, >> so my message to anyone >> is that is that because if you were if you were spending more or you hired more salespeople, you just wouldn't be able to fulfill the demand. So, you need to scale capacity first. >> Yeah. Yeah. We uh my marketing team usually I'm like uh say nothing. Say don't say anything this week because we had a machine go down or or whatever. So, I'm like stop and everyone go quiet. Um so, yeah, it's it's always chasing capacity. But my message to anyone who wants to do something like this, like just have a kick-ass product. Just make it good and fast and uh you know, get it in their hands within you know a couple days or whatever and people will come back and they'll tell their friends. So, but it's an overnight success takes 10 years. So, we're in >> and when you guys are fast, when you guys are fast, >> get punched in the face. >> Yeah. >> When you guys are fast, your customers can build their products faster and have higher sales velocity themselves and generate more revenue and then they end up spending more and it's like this very very virtuous flywheel. And uh I'm so glad you're well capitalized. >> Yeah. >> Uh I Yeah, this is a major white pill. >> Yeah. I >> I hope I don't have to do it again because like fundraising is not fun. I hate finance. Uh >> get ready. Get ready for for nice buddy. >> Yeah, there's going to be many more many more in the future. I >> It's your It's your duty. >> Yeah, if you if you want if you want to go fast and far, it makes sense. Uh last question. We were talking about uh the fall off of dad books because of podcasts and fertility and all this different stuff. And I'm interested if you have any uh examples or recommendations for uh fatherson building activities that you've seen from the community or maybe you've done yourself even or employees have of a good first build for a for a uh for a parent and child to do uh that might use send parts. >> Yeah, there's there's a ton of uh little like push go-kart plans available. Um, we may even have a couple on marketplace. I I'll have to check. >> Cool. >> But you have to do something that the kid can enjoy. And there's nothing better than like getting pushed down a hill and scraping your knees or whatever. So to have those experiences, something that's usable, like a birdhouse or whatever, that's fine. A go-kart or a scooter or something like that is is pretty cool for the kids. >> So if I make a go-kart using Sen Cut Send parts and I want to throw a V12 in there, can you fabricate that for me, too? >> Not yet. >> Not yet. Okay, that's what the money's for. >> Then we're going to spend >> Go-kart is such a smart recommendation, too, for you, you know, running a business because a bird feeder, you know, you make it once, you put it up, it's good. Yeah. My my dad uh built me a go-kart growing up and I he would he would, you know, he made it, I would drive the heck out of it, it would break, then he'd be fixing it. So, you're gonna It's a recurring revenue stream for you guys to get a father-son duo into go-karts. >> That's smart. 100%. Yeah. >> Never ending. playing the long game. Uh well, congratulations and thank you so much for coming on the show today. >> Yeah, great to see you, Jim. Congrats to the whole team and excited to see you back on here soon. >> Have a good one. Cool. >> Goodbye. >> Cheers. >> Uh >> legend. >> Fantastic. White pill. White pill of the show. >> Major white pill. We were black pilling. Now we're white pilling. >> Never black pill. >> Never black pill. >> Uh well, up next we have Aiden Der from Nourish. He's the co-founder and CEO. has been on the show before, but we're welcoming him back with some huge news about the company that's growing faster than ever with a massive series C to announce. Aiden, how are you doing? >> I think we might have some technical problems. Can you give us a hello? Can you say hello? >> We might need to come back to you. >> How are we doing? >> Using uh are you using a potato as a webcam? It's not the potato, it's the Wi-Fi. It's for sure the Wi-Fi. >> Uh, >> do a do a check one, two. >> Yeah, do a check one, two. We'll kill some time. >> We'll kill some time because Dan killing time with Dan Sunheim. So, wait. Okay, so this is actually funny because I I opened up the Wall Street Journal today and I had seen I had seen the news from Tay Kim who's coming on the show this week. uh that in the financial times uh they had a report that uh Daniel Sunheim's D1 Capital Partners is another hedge fund that stands to make a killing when SpaceX goes public. D1 is sitting on paper gains of about 9 billion on SpaceX stock that it acquired over several years for about 600 million. What a run of 15x. Not bad. Uh and so now the the stake might be worth 20 billion if the rocket maker is valued at the expected 1.75 trillion. A figure that could still change according to people familiar with the matter. But I open up the Wall Street Journal and I and I'm and I'm and I everyone's familiar with Dan Senheim and D1. He's Dan Sheim is not like someone who's obscure behind the scenes. He's done in best like the best. People know D1. They invest in a lot of companies that we know. Uh but uh I thought this Wall Street Journal article was also about D1 and the title is obscure fund has a lot riding on SpaceX and I was like are they really painting D1 as an obscure fund? They weren't. They're talking about a different Yes. Yes. uh they're talking about a different uh a different uh investment firm that's that's about to make a lot of money on the SpaceX investment. So SpaceX's planned initial public offering is expected to be a windfall for futurist investors and venture capitalists. If you got SpaceX chair shares and you're you don't want to say I'm not a VC, say you're a futurist investor. Uh a public a publicity shy hedge fund manager whose other investments. So you're a hedge fund, you're long SpaceX. What else are you buying to diversify your portfolio as a futurist investor? Dick's Sporting Goods and Wingstop are among the big positions at Darana Capital Partners, which first invested in SpaceX in 2019 when Elon Musk's rocket maker was valued at around 30 billion and made several subsequent investments since then. Should SpaceX go public at a valuation around 1.5 trillion, Darana paper, Darana's paper gains on the investment could top $10 billion. So, had you ever heard of Darana before? >> No, >> I actually had not. But, uh, I have heard of Winktop. It's a good good stock. Uh, several billion of that would be gains since uh >> stock is down 50% year to date. rough uh the sor evaluation uh Anand decide launched New York-based arana which comes from a Sanskrit word that means seeing the true nature of reality >> chicken wings >> and dick sporting goods uh in 2014 1.4 billion under management. >> Let's bring in our >> is back on a new device. >> Hey, crystal clear. >> Thanks so much. >> We're on mobile now, guys. Apologies. We uh we're at our company offsite, so we got weak weak Wi-Fi. >> Makes sense. Well, you sound crystal clear now. Uh why don't you uh reintroduce the company? Tell us the news. >> Yeah, thanks for having me on, guys. Um so, I'm Aiden. I'm the the co-founder and CEO of of Nourish. Uh Nourish is a dietitianled metabolic clinic. So we pair the the largest network of registered dietitians in the country, over 10,000 dietitians um with virtual medical care. So the ability for physicians to uh order and interpret labs to prescribe and manage medications >> um and we've delivered some really amazing results for for patients that we're excited to talk about today. Walk me through dietitionian uh the different uh the different degrees that might be involved the the certifications. I know uh with a lot of teleaalth there's statebystate regulations like what was the process of building out that network of 10,000 dietitians? >> Yeah, good question. So dietitionian is a protected term. So you might hear some people use nutritionist or dietitian interchangeably but nutrition is actually not protected. So, you know, you or I could get on Instagram and call ourselves a nutritionist, but a dietitian requires a master's degree certain number of hours and so on. And so, we we only apply uh employee dietitians. Those are the providers that are able to work with health insurance and get it covered, which is a a big part of our model is expanding access to this type of care. And of course, working with health plans, get it covered by insurance is a is a big part of that. >> Okay. What is the value ad? I mean, there's so much there's so much of a boom in peptides, GLP-1s, metabolic health. Uh it feels like there's a lot of these companies where the demand is already there. You're just the, you know, the landing page that gives the that gives the customer what they already want. But I imagine that there's a lot more. >> I'll pitch it. >> Okay, pitch it, Jordy. >> Uh it seems super important to combine uh diet with GLP1 doing just just saying like, hey, we created this magical drug for for weight loss. and then just doing the drug versus like actually fixing like the underlying >> uh sort of cause or maybe the original issue, you know, is sort of a temporary solution. And if you want like lasting >> positive change with your health, you you're going to have to factor. >> So if I go to a dietitian and say I've been blasting red, >> did I botch it? >> Is that is that roughly correct? >> No. No. You you said it well. I mean, I think the way we think about the root cause of kind of the the problem of explosion and chronic conditions is and cost is that people are living unhealthy lifestyles in the modern world. It's very hard in the modern world to eat well, to sleep well, to move your body, to manage your stress. And maybe 75 years ago when these conditions were much rarer and costs were much lower. Uh just kind of living your life in the day-to-day, it was, you know, much easier to be healthy. And so while these medications are a very useful tool in the toolkit and you know with our network now we're able to prescribe and manage those medications to your point you know if you if you don't pair that with behavior change you don't get kind of sustainable results which of course is is worse for the patient but it's also worse for the system because now we've spent all this money for for medications and then had uh rebound weight gain or or falling off medication or so on. what's happening uh on the supply side of the market with with GLP1s and and how is that impacting pricing? We know there's >> an incredible amount of demand, overwhelming demand, but what's happening on the other side? >> Yeah. So, uh it's nice to see. I mean, I think slowly but surely we'll see access increase, costs come down. I think over time as these drugs become generic, um expect them to get much much cheaper. You know, you mentioned RETA, you know, I think that'll, you know, get approved in the in the coming years and that'll maybe start higher price and then these kind of, you know, first gen, second gen meds will will come down in price and eventually go generic, which I think is really exciting because ultimately, like I said, they are a valuable tool in the toolkit, but cost is prohibitive in many cases today. And so, where I think, you know, we play and where I think the value will ultimately be created as as the price of these medications comes down is exactly in that behavior and lifestyle change that we we talked about. That's kind of that that wraparound care of how do you have you know not just medication but integrated care team virtually covered by insurance uh as well as of course you know technology especially AI which can be kind of that 247 behavior change agent as as part of the equation and that's you know the a big part of the the round we just raised was to invest in all of that and accelerate that. >> How much did you raise >> raised 100 million series C. Yes. >> Congratulations. >> I love the gunk. I love the gong. That's why I came on. Uh I we need a we need a gong for our office. It really is. >> Uh yeah, we should make TVPN branded gong something everyone. Um >> uh wraparound care. Uh does that also mean meal delivery at some point? I feel like there's a number of companies throughout history that have uh sort of vertically integrated to that degree. Incredibly comp uh operationally complex. Is it on the road map? Is it something you're interested in? >> Yeah, great question. We we get reached out uh by you know a number of of kind of media delivery companies as you expect about about partnering. We we haven't prioritized it yet but I I do think ultimately you know we'll do something there at at some point. I mean the way I think about kind of more broadly the the problem of lifestyle being lifestyle change being difficult and therefore the mission of being how do you make lifestyle change easy is you're trying to remove as many barriers and of course the food being kind of one of those and so how do you when you make a recommendation make it very easy to act and fulfill that recommendation. And I think being able to uh prescribe and fulfill prescriptions of food in the same way you can of medication I think will be something we do eventually and I think there's a lot of movement uh among health plans to potentially even reimburse for that in in some cases eventually but haven't prioritized that yet but I I think at some point we will. >> And then uh on on the on the GOP one side uh is there still an opportunity in compounding? I know some uh tellahalth providers like went down that path others partnered. Like do you have a firm view? Are you flexible here? or how have you been interpreting the different ways to vertically integrate on that side of the business? >> Yeah, so we we do not compound. We work with the the name brand medications and have partnerships with the you know the big players that you all know and and work to get those covered by insurance. You know, I think if you've probably seen you know in the last few years there's been kind of this cash pay and compounding market. We think that was a bit of kind of just a short-term uh solution for when there were access constraints and cost constraints that you were speaking about earlier and where kind of the market heads is uh you know the the inverse of of cash bank compounding which is insurance covered and name brand and that's kind of you know bread and butter of the company pun intended is working with kind of those those health plans to to get things like that covered and then again because the drug as cost comes down especially becomes a a commodity I think where the value is created is in that wraparound care we we talked about and and that's kind of the hard work, but I think the the important work that ultimately delivers, you know, lasting outcomes. >> Okay, last question from the chat. Are you on a boat? >> No, I mean I I'm in this random conference room at our company offsite. Like I said, >> I think it's the phone. I think the phone is like rocking at just the right oscillation. >> I'm pretty convinced it's >> you're not feeding the boat allegations. >> He denies He denies the boat. >> It does have kind of boat. does have wood paneling and it looks nice. >> It's that it's that texture of wood. >> No, we got a boring boring conference room. Sorry. Huge boat. It's a super massive boat. >> I I I don't have a problem with company offsite of the boat. That seems like a great strategy if that's what you did. I'm not going to critique it. Enjoy the boat. >> Uh great great to see you, Aiden. Congrats to the whole team on the milestone and keep up the great work. >> We'll talk to you soon. >> Thanks. I got I got to go talk to the captain to study this. >> Have him reset the start link, too, for your for your computer. >> Sorry about that, guys. Thanks for having me on. >> Great to see you. See you. Goodbye. >> I'm glad we got to the boat question. >> The important question. >> I don't think it was a boat. It It looked It looked a little bit too big. And And things weren't like buckled down. you know, usually on a boat, even if you're in a palatial conference room, there's ways to, you know, bolt down certain certain items. Anyway, um, our next guest is from Status here raising a series, uh, to be around. Welcome to the show. >> Hey guys, nice to nice to finally be on the show. >> We got to kick it off with the first question. Are you on a boat? >> No, unfortunately, I'm in a regular >> Okay, our last our last a very nice conference room. >> Fantastic. Our last guest denied the allegations of being a boat. He looked like he was on a boat. We have to ask everyone now. But that's not what we're here. We're here to talk about. Uh we're here to talk about you and your company. Please introduce yourself and the company. >> Yeah. So, I'm Fi. I'm the CEO and co-founder of Status. Status is essentially a social entertainment app where users can live out their dream lives and play as anyone through the lens of a social network. So, for example, I could be a famous singer. I could be an actor. I could live inside the world of like my favorite book, something like Harry Potter. I could be, you know, the host of one of the most famous, you know, technology news shows on X, like >> simulators. This is the thing. Yeah. >> Everything's a simulation. >> Yeah. So, uh, walk us through the actual customer experience. It feels like there's an element of social media here. There's also an element of like a massively multiplayer online RPG. Uh, are you pulling ideas from both places? What are the big inspiration points? >> Yeah. So, essentially when you go on Status, the first thing that you do is you craft your persona, like who you're going to be. So, I want to be a famous singer. I want to be a live streamer. Um, I can choose who my first follower is going to be. I could choose someone from real life. All of our all of our um characters on the app, all of the worlds on the app are created by users. We have over five million characters on on the app, over 10 million worlds. Um, and you, it looks like social media. looks like X. Uh, and I think this is why it's really struck a chord with people and why we've grown so fast since we launched uh last year or when we launched last year, we went from zero to a million users in 19 days. And it kind of just shows like the the verality of of what we're doing. I think this product really it resonates with our user base which is pretty young um predominantly young women um in the US and all across the world. H how how gamified is it? What like like what is the the the the goal of uh the players? Is there a currency or or something that they win? Oh yeah. How does that work? >> We basically made social media into a game, right? So you know when you post on on social media now you get like obviously you get followers, you get likes. The same thing happens on status. You gain followers, you gain likes, but you also you know everything you do has an outcome that will help you gain skill points which helps you level up. We took a lot of inspiration from like life simulator games like The Sims and also, you know, um our own background, my co-founder built, you know, games on Roblox and Minecraft. And so we it's really a mix of of like Life Simulator and and roleplay and like fandom related stuff and and really that like gamified world. >> How are you thinking about monetization long term? I'm sure it's early. You're venture capital backed. you don't need to uh charge an arm and a leg for this, but uh is subscriptions more aligned with the uh w with with the the current customer experience or is like social media I think advertising? >> Yeah, so we actually have already started monetizing um the product when we basically Oh, hell yeah. >> I was not expecting that. Yeah, we already started monetizing. Um we operate um similarly to a game, right? We have a we have inapp purchases where you can buy power-ups, things like that. You we also have subscriptions with like uh you know weekly weekly subscriptions and annual subscriptions and um we have uh millions in in in ARR. We 10x revenue uh this first quarter of 2026. So we're we're ripping right now. >> Sound effect. Uh what uh is it uh like what do you want people to what is what is the the business is ripping. You have a ton of users. Uh what what are you hoping that users get out of it? Is it is it uh >> uh like what is what is the sort of like overarching vision of of uh outside of just fun and uh playing a game uh what you want users to get out of this? Yeah, I think that what status really represents is this we're moving into like a new I think phase of of entertainment. So, you know, since like the beginning of time, you've always had to just, you know, sit and like read a story or or watch a story. I think what we can do now with LLMs and AI is that now you can really immerse yourselves into these like incredible like role-playing engagement engaging experiences. And I think that's what our users are are are doing. You know, when you watch a TV show and you get like really obsessed with it, maybe you go to Reddit and read like theories about what people are saying about it, you know, connect with fans and talk talk about the show with them. You might go to TikTok and and watch edits of of that show. Then you also, and I think this is the what the this next phase of what we're seeing people do is that they're going on Status and they're honestly like immersing themselves in into thinking like, well, what if I was a character in that show? Who would I interact with? you know, what would that look like? And we're doing it through, you know, this lens of social media, which is so familiar to people because, you know, everyone is on the same the same types of social media platform. H >> how does intellectual property work in this world? I mean, I anyone can go draw a picture of Harry Potter and post it on their Instagram. But if you're intermediating this and you're the one generating a lot of the models will refuse, some of them have partnerships and there's a whole bunch of different solutions there. But what does that look like? Yeah. So everything on the platform, all the characters, all of the worlds are userenerated. So similar So we like to think of it as like, you know, similar to how someone would, you know, can upload like a YouTube video talking about a TV show or use an artist. Yeah, it's it's the same thing except now with, you know, LMS and and with AI, you can create these AI generated worlds uh >> based off of that based off of that show or book or whatever it is. >> Has there been push back to this? I mean, obviously your your core fan base loves it. They're paying for it. They're using the product. But, uh, AI is getting booed on stage. People are worried about brain rod and the infinite jest. Like, what has the push back been like? Is it is it just you're off in your own little world and it's not it's not actually confronting or have you had to grapple with any of the big questions about uh AI, social media, brain rod, etc.? >> Yeah. So I think with our user base especially and what we've kind of seen with with um AI is that the push back that you see with like younger people who don't like AI it's because they feel like AI is like replacing experiences that you know they like you know things like art things like you know music things things things like that status isn't really replacing anything we you know uh are a completely new experience that has that can really only exist with AI and I think that's why you know our users are are young, but they love Status and and they're really excited um you know about the product. And in terms of like working with with you know these like entertainment companies and streamers, we've already started kind of you know we already started having conversations um with some of them and there is a real appetite of you know I'm sure you you you've seen this like now with Netflix shows or Amazon shows like HBO whatever it is there's a long wait between seasons right like you watch a show then you wait like two years for the next season to come out. A lot of these streamers are thinking about, okay, how do I keep my audience engaged while we produce and make the next um you know, the next season of that show. So, I think they'll go and create a million plot holes that they'll never resolve now. No play in the world. >> What do you what do you think Meta's plans are around agents and bots and and this sort of, you know, simulated social media? They acquired Maltbook. They've experimented with celebrity personas in the past. I feel like, you know, if you guys if your metrics keep looking the way they're looking up and to the right, stock will eventually come in. He will try to clone you. It'll be right of passage. Uh but but generally, how are you thinking about um uh you know, these sort of scaled social platforms and and how they're thinking about integrating experiences like this. Yeah, I think that a lot of um definitely I think there's there's a lot of interest from from these big big companies and I think that what they're trying to do and I and I it is and it's exciting with what they're doing with you know you know acquiring mobook they acquired Gizmo as well like they're really interested in these um AI first experiences um but of course like we kind of just focus on what we're we're doing and you know just you know If they copy us, they can try. But like I think with they like status. Exactly. Good luck. And I think that you know um our users and I think this is what makes us so sticky and why our retention is so good. They've created these these worlds and stuff that they are they put a lot of work in and and I and I think that um that really shows in in our engagement and retention. So >> uh tell us about the fundraising to date. You've got some new capital. Let's hear it. >> What did you raise? >> Yeah. So we have raised uh 17 million in seed in series. Yeah. Funding. Congratulations. >> Thank you guys. We're backed by Abstract um General Catalyst, Union Square Ventures. Um >> also Lightshed Ventures, YC, bunch of guys. Um so shout out to them. >> Great lineup. Great lineup. Where where are you guys based? >> Oh yeah, >> we're based in New York. So consumer in New York guys. Uh >> we have a team of nine um in the city. I'm actually an SF right now, so don't tell anyone. >> We won't. We won't. Well, great to meet you. I'm sure I'm sure we'll uh I'm sure we'll have you back on soon. And yeah, congrats on all the progress. >> Yeah, we'll talk to you soon. >> Thank you guys so much for having me. >> Cheers. Have a good one. Goodbye. >> Up next, we have Tana Tanden from Camor. >> He's back. >> He's back. >> Raising 7 billion at a $700 billion valuation. >> Uh we're not not too far from it. and I'm sure he'll be there soon. Welcome to the show. How are you doing? >> How are you guys? >> Thanks for having me. >> Good, good entrance. Drinking casually. Thought you were distracted. >> Oh, dial. >> Oh, hey guys. Didn't see you there. I'm just live. >> Uh, anyway, welcome back to the show. Uh, please, but reintroduce the company. Tell us the news. I want to hit the gong and hear all the greatest the latest and greatest. >> Awesome. I'm TA, CEO at Kamir. We just announced a raise of $70 million at a $7 billion valuation with >> this guy hates delusion. >> He hates only 1%. Um with GC, Sequoia, Morgan, Stanley, Kirkland, Ellis. >> Yeah. How how do you get to this? Is this more of a strategic round? Did you give it a name? Is this a this particular letter or was this more opportunistic and you have a particular goal in mind uh to take it to the next level? like what's on the what's on the horizon for the next year? >> Yeah. One, it's an extension. It's like I think we called it officially a series E1 or E2 or something like that. Um the the goal I mean one it was we didn't need the cash. Uh we thought it would be a good time to mark the company uh at a fair price for all the work that's been put in over the last 18 months. Uh, and then on top of that, take some cash, put it on balance sheet to really accelerate R&D around some of our investments on air, which is our language model powered EMR platform, ambient, and voice agents. Um, hired group of 40, 50 elite engineers, and just hit the pavement. >> There we go. Uh, how much of the I mean, it sounds like you're already expanding outside of like revenue cycle management, like more back office workflows. I'd be interested to know the the shape of the business, some of the different products, how healthcare providers are actually integrating with you. >> Yeah, I mean, we see the problem as this trillion dollar administrative work tax on the American economy. You have four or five trillion that you spend on healthcare, but the fact that 20% of that is spent on labor that pushes documents, submits claims, writes documentation is a travesty. And our belief is that language models can handle all of those tasks. So the core product lines as you mentioned is revenue cycle which is an engine that takes claims automates the submissions, appeals, denials, prior authorization process. Um ambient documentation which takes the workflow around actually writing notes um that a provider might do with the patient and completely eliminates all the work tax around that. Uh and then voice agents and back office agents, tools that automate scheduling, tools that automate the task of, you know, putting uh someone on a calendar, putting someone uh on a prior author appeal schedule, um and just doing that with voice models. So those are the key areas and that's where we're going to continue to invest in more. >> Uh >> every, you know, healthc care uh CEO historically, you know, will complain at different points about how slowm moving adoption can be at times. Has that changed over the last two months? Are are different groups adopting, you know, new products and services much faster than they would have historically just because there are these pretty dramatic advancements? >> I I think healthcare has been one of the areas alongside legal and I would say coding uh like software engineering where we've seen the fastest adoption of language models because it's just such a you know hammer-on nail situation for for for the work that these providers are doing. And postcoid I think we burnt our providers out. Most of these providers were working you know 15 20 hour hour days and just not getting much sleep. Many of them wanted to leave the health system and go work in tech or finance or something easier. Uh and language models were the gift that arrived at the right time to keep them in in the workforce that we need them in. so much. >> Can you talk a little bit about uh invisible AI to I I'm wondering how much of your product sort of like reveals itself to be AI powered to the end user, the customer, the person actually receiving health care because I think there's like maybe some sort of transition happening where uh members of a healthcare organization are are using AI, seeing speed ups, but uh uh the actual end user, the customer, the patient might not even be aware that AI is involved at all. >> I I think the beauty of of language models is you can truly sell the outcome. There's like a big Twitter thought piece right now, but you know, we live it in the sense that we sell the outcome of more revenue for a practice or a health system or better documentation for a practice or a health system. And the way to do that isn't necessarily brand and market yourself as an AI enabled this or that. It's just deliver the amazing result for a price that's a hell of a lot lower than the rest of the market. And I think for revenue cycle for example, it's been a endto-end service that's been provided with offshore labor in India or Bangladesh for 20 30 40 years now. And we're taking that model and instead deploying agents on that same task and delivering a better product at a lower price. >> Uh are you already seeing uh evidence of like agent on agent conflict or collaboration? I guess I'm imagining that like you know uh a commowered revenue cycle management tool winds up sending me a bill or customer a bill and then their open claw is debating it and like what does that future look like in your opinion? I >> I think there's the collaborative piece that you alluded to which is super exciting where you see models literally coaching other models uh creating better prompts creating iterative versions of the same uh uh you know task execution uh methodology and we have a lot of investments in that. we've seen over overnight generation across hundreds of thousands of claims. The same model performs 10 20 times better than it did when it started. Um, and then there's the kind of combative models where you have insurance companies putting up their own nonsense models trying to deny claims and then our models are fighting those models and it really will turn into in some ways a war of attrition. I think the final end state there is you have models talking to models. you eliminate the labor costs and you take health care from this 14 15% cost to collect business and turn it into a Visa Mastercard like business where there's you know two three% interchange fees and it's you know returns billions if not trillions to the health system. >> Sure. Are you uh because of the maybe you can give a brief overview of like the structure of the health care system because I think people uh sometimes misunderstand how consolidated the insurance side is versus how diversified the provider side is. But then I'm interested to know uh are you permanently in a lane or do you have business to do with all sides of the uh of of the market at in the limit? >> Yeah, I mean first first of all like we are like a provider first and provider only company. I think the the provider is the only protagonist in our story and we think of of ourselves at times as an arms dealer for the provider. give them the tools to go nuke the payers and and really get their margin back. >> In in the context of uh you know the the broader like payer ecosystem, I think one of the concerning trends is the like like you mentioned there's just a sheer volume of consolidation. You have payers that are essentially monopolizing um and dictating how much providers get paid for every little thing and then on top of that denying denying denying which makes it way harder for a provider to earn a living. Compare that to the '9s where providers were making money handover fist and living good lives. And I think the quality of care in America was better back then too. >> Yeah. Are you uh is is there is there a reason to be uh generally in favor of provider consolidation sort of uh paradoxically because the payer uh the payer ecosystem is so consolidated that the providers can't push back at their current scale. and maybe some of the the the rollups and mergers that we're seeing on the provider side could actually create sort of a strength uh that might actually benefit the end consumer. >> We see both sides of that coin. I mean, one, we're partnered with HCA, which is literally the largest health system in the country, you know, bills over hundred billion dollars in in revenue a year. Um, but on the flip side, we think AI and language models create this opportunity for more independent practices and more physicians starting their own businesses. Now, the reason why I think both of those are interesting, um, if you have a tech layer that lives on top of both, that almost becomes the GPO or group negotiating organization that can lower or that can improve pricing, uh, and and negotiate better rates against payers. Kind of like, you know, like the flip side of the whole ramp vendor management tool um or, you know, one of these other like software spend management tools where you consolidate and add price transparency and then you return margin back to the entity that used the tool. >> Yeah. Yeah, that makes sense. Uh are you seeing any evidence of like an uptick in uh individual practices in or is it too soon? I mean we're seeing like a lot of solo entrepreneurs everywhere. Every every entrepreneur wants to like build the $1 billion one person tech company but it's usually like a vibe coded piece of >> we will see the one doctor one billion dollar >> hospital. Hey maybe if they save the right person's life you know willingness to pay. I I I think the the thing that we are seeing for sure is the practices that have been independent are becoming higher margin and becoming more profitable when they adopt the eye tools. And that's I think the first step and a necessary precursor to the creation of more independent practice because one you're going to have them begin to invest in other practices or potentially roll up practices. Um, you're also probably going to see this, you know, concept of of the AI first practice, like a truly online behavioral health practice that uses LLMs for everything except for the care. Um, you're definitely seeing this in the in the pharmacy world where there was like the recent New York Times article about the GLP1 business that had scaled to a couple hundred million in run rate. And I think you're going to see more and more of that across the ecosystem because of language models. >> Interesting. Uh, well, congratulations on the new round. Uh, thank you so much, Jordy. Anything? Great to see you. >> Good. Thank you. Have a great rest of your day. >> You too. >> We'll talk to you soon. Appreciate >> it. Goodbye. >> Up next, Jaya Kotra from Meter joining the show to talk about uh their new frontier risk report which came out today. How are you doing? >> Good. Thanks for having me on. Great to be here. >> Thanks for having me on. uh why don't you uh start with a little bit of your background, maybe an introduction on how you fit into Meter as an organization and uh maybe even just reset on like an introduction of Meter and what the purpose of the firm is, the structure of the firm. >> Yeah. Um so my name is AA. Um I actually joined Meter pretty recently to lead the writing of this frontier risk report in January. Yeah. Um before that I'd spent about a decade in um AI safety um in a couple different capacities all at coefficient giving which is a big fun of AI safety work. >> Sure. >> Um a lot of my work had been kind of bigger picture >> forecasting longer term like when are we going to get super powerful AI? What's going to happen with the world? What kind of risks might it pose? And at Meter, um, I'm I I really like that Meter's mission is to kind of >> take that stuff seriously, but then try to make it measurable. Yeah. Like try to make >> risks from misaligned AI something that we can track and do the best possible job as civilization like >> getting on the same page about, you know, so so I I see that as having two parts. Um, one is developing the measurement tools. So the the telescopes and the microscopes um and the instruments we need to understand what are systems capabilities, what are their motivations or inclinations um what are the incidents we've seen of them of things going wrong um and where is that all heading with the trends. >> Yeah. And then the other side of that is to actually apply that to real frontier deployments and try to understand the risks posed by a particular system in partnership with companies. Yeah. Um and the frontier risk report is is sort of that half of it where Meter for the first time has done a sort of cohort thing with a bunch of different companies working with Google, OpenAI, um Meta and Anthropic um where they gave us access to their best internal models sort of on our terms um and answered a long questionnaire we sent them about you know how they aligned these systems and what incidents they saw with them and how they used them all so that we could kind of >> pull pull together almost like a state of the union of like what's the deal with misalignment risk um inside these companies. >> Yeah. And so uh how are you trying to quantify the actual findings? Is it like a number of incidents or magnitude of incidents? It feels like uh it can be very abstract but the whole purpose of meter is to sort of quantify, narrow down, contextualize and so what what what were the goals or or were the goals you know after you actually get access to the models you act you get these questionnaires back you see the internal reasoning chains is are are are then you starting to construct benchmarks around those or are is it important that you come in with uh your your sort of metrics pre-baked so that uh the access doesn't change that what you're measuring. ing. >> Yeah, that's a good question and it's it's definitely a mix. I think we had I would say basically three big goals. The first one was really to just do a dry run of a process >> for what >> good auditing of risks could look like. Um so most third party evaluators including meter in the past >> they sort of you know a a company is about to release a model in two weeks um and they call you up and they say can you run some evals on this model? you kind of scramble to do two or three evals. They put out the model and they put your evals in the system card. >> Yeah. >> Um and we wanted to do something that was both deeper and and kind of driven by us as opposed to tied to launch schedules. >> Yeah. And so wait really quickly going back to like evaluating the older models like what what does that actually look like in practice? Is that like you know give me the you know give me instructions for how to build a bioweapon and that's like just the prompt and then you're just seeing if it rejects that properly. uh like what are some examples of of of evaluations that you would do prior? >> Yeah. So you're talking about um red teaming y which the UK AI security institute does a lot of this um where yeah the company will be like will this model tell you how to make a bioweapon you you have a week or two you try a bunch of jailbreaks um you generally just get output access to the model um so you can't necessarily go super deep y >> and what meter >> um used to do um is dangerous capability evaluations so so it's not even the jailbreaking piece per se it's just what can this model do autonomously on its own. >> Um, so we're best known for for our time horizon chart um which is plotting models um >> that with the x-axis being their release date and the y-axis being um how complex of a task can they do by themselves >> measured by how long it would take a human to do the task. So, we released this in spring 2025. Models were like a time horizon of less than an hour. Um, and now the best models have a time horizon of more than two full-time equivalent days. Yeah. >> So, you know, a lot of the time they can do software tasks that a human human would take days to do. >> Um, so so that was our lane is like capability evaluations. With this report, we're we're trying to expand into two different verticals at the same time as we're kind of um expanding into deeper access. So, we're we're calling it means, motive, and opportunity. So, means is the capability piece of it, which which meter has the longest history with. >> U motive is understanding based on how these systems are trained and based on what we've seen of things that can go wrong in in real deployments. uh what what are their tendencies like under what circumstances would they misbehave and can we get better at predicting that and then opportunity is uh the whole system surrounding the agent in terms of what are the operating conditions? How are they used? How are they overseen? Are they subject to monitoring? Are they subject to security? And therefore like could they get away with certain harmful actions or would they be stopped? Mhm. >> And um as you I mean I'm I'm I'm interested in more of like yeah the the actual findings like the state of the union on like like what are the capabilities where are we on actually mitigating misalignment uh and then so let's talk about that and then I want to know downstream where where all this goes uh and and yeah where where you'd like to see standards sort of emerge. >> Yeah. And so that kind of goes back to your question of, you know, did did you kind of come in with with the framework all baked or did you kind of discover it as you did the report? And I think it's very much the latter. We knew >> what types of information we wanted to gather. We knew we'd want to know about incidents and how they trained the system. And we kind of prepped this whole questionnaire before the process even started. Um but then as we were writing the report, this framework emerged of of basically a two-dimensional scale of AI misalignment incidents. >> Yeah. >> Um where one scale is what we're calling overreach, which is um how far past the bounds of where this AI was supposed to stay did it blow past. Um so uh we have three buckets of this. >> One is it just violates user instructions and goes and like does something it's not supposed to do. Um, but there was no actual like hard barrier that it had to hack through or anything like that. So, an example of this is in one of our tasks, um, Opus 4.6 ran out of API credits in the account we gave it to do a task. So, it just like went and found free computed online like against explicit task instructions. >> Um, but but we didn't like have a security barrier. Just kind of like went on the internet and found something and set it up. >> Yeah. Um and the next level of overreach is when an agent actually hacks past something. >> Yeah. >> Um like like an actual security perimeter. >> Um and we find that on some of our tasks, agents are constantly trying to like break out of their sandbox and find the file where we >> like put the test so they can get the answer key. >> Um so so on our we're um we have some of the hardest evaluations around. So most people evaluate models in like pretty short tasks that are pretty easy for them. Um and we have tasks that are you know 8 10 20 hours long and on tasks longer than eight hours models cheat more than one in six of the time. So imagine an employee that like yeah >> you know one time in six just like flagrantly tries to like >> uh steal from you. >> People take the shortcuts on the longest paths. They don't bother to take shortcuts if they're just going a block. >> Yeah. Yeah. So, and so on our shorter tasks that are like 30 minutes, we find the cheating rate is half a percent. Which is similar to what uh companies report in their system cards, but on these longer tasks, it's one in six. And on some distributions, um we have this data set called mirror code, which is basically having AI systems re-implement big pieces of software. Yeah. >> Um and Opus 4.6 on hard tasks in mirror code attempts to cheat 80% of the time. So they're just desperate. They know that the test cases are there. They want to overfitit. >> I think I'm thinking of the wrong of a different benchmark, but uh Meta put out a uh it sounded like a somewhat similar benchmark of like rebuild a full complex software repo and and uh and and I think all of the models were at like half a percent like basically again back at zero sort of like an arc agi v3 or some of the meter tasks that you have that are not not passing at all. And for that I I you know I'm I'm like even intuitively I'm like I would just clone the repo and start there. But of course that's cheating. Uh and so it's very intuitive that if your boss comes to you and says like I need you to rebuild Chrome. You'd be like okay well I'm starting with Chromium and then I'll add some features like this is a very logical path that I so I I sort of empathize with the models that they cheat in this way. But uh let's move on to like where this goes because I think that there is an immense I mean you've seen the you know Eric Schmidt getting booed off stage for talking about AI. There's a lot of AI anxiety. Data centers are being opposed. There's there's a bunch of calls for like an AI FDA or some sort of I think a lot of the model providers uh maybe not all the ones that you've worked with have signed on to let the government review models. Like where do you think this goes? How do you do you want this to remain in the private sector formalized further build meter as an international organization? Uh where is the energy going? Where is their demand from the folks that you talk to? >> Yeah. Um so Meter is very interested in and and our partner companies are interested in uh setting up basically a sensible auditing regime that is technically literate >> for these catastrophic risks. So, you know, you don't want like a box checking auditor that has like sort of 17 arbitrary things you're supposed to do. >> AI model is going to find those boxes and check them. >> The AI model is going to find that auditor, hack into their their checklist and check everything. We know we know what happens here. >> Yeah. So, we're in this like weird situation where the science is like extremely nent and fast moving. Yeah. >> But then also the risks might be kind of imminent. So we need like a flexible system >> and and and my best guess is that it's going to look like um something like what happens in the financial sector in some cases where you have embedded auditors. you have other folks who are who are experts um in finance who you know sit and eat lunch with the employees and see all the books and know everything and have a lot of flexibility to investigate what they need to investigate. Um and uh we actually released details on an embedded auditing exercise we did with Anthropic as part of this report where a meter employee um went in for 3 weeks um and just tried to break Anthropic's monitoring systems. So he just sort of played the role of a rogue AI and and tried to wreak havoc and tried to break things and he found several ways to jailbreak and disable and evade the monitors. And that's not something you can get just from, you know, sending out a form and having them fill it out. So, so we're really hoping to move more and more in the like embedded direction. So, embed embedded auditing of the monitoring system like we did with anthropic, potentially even embedded auditing of training. So, like >> getting getting samples of what the system was trained on, analyzing the training incentives that might have been created, trying to figure out if the training data could have been poisoned even. >> Yeah. Does this uh you know when you say auditor I think you know potentially like forprofit business would there be a possibility that >> financial audit this is like not a joke all the financial auditor companies are huge yeah >> yeah so is there a possibility that >> wild by the way >> is there is there >> but maybe it makes sense maybe it's actually a better >> yeah I'm saying is there a possibility in the future where Meter has a forprofit you know auditing arm that you maybe you guys spin out >> so I don't I don't know the future might hold. But meter does not take money for our engagements with companies and that's very important to us because we want to have our scientific independence. >> Um although you're right but in a regime house Coopers is like a successful but I'm just saying like right >> if if you want auditors that are technically competent that have been working with the models for really long time there's not a lot of organizations outside of meter that would be >> qualified to do this kind of work. So you might you might be >> it's the final alignment problem for you. Good luck. You have >> you might want to you might want to maybe like split the the auditing from the scientific judgment maybe like one one thing I like from the nuclear space is that the nuclear power plants actually >> rate each other's safety which is like an interesting I could imagine meter kind of like digging up information and then like >> open AI rates anthropic rates open AI and GDM. Sure. I'm sure every content much more drama. Just fired shots. It's over. I'm sure the post will go viral every time. Well, thank you so much >> for coming on the show. You can go find the report uh on mex account. Mr_vals is the account and mer.org is the website. Thank you so much for coming on the show. We'll talk to you soon. >> Yeah. >> Thank you so much. >> Have a good one. Goodbye. Uh our next guest is live with us in person. We have one post we need to pull up first. There's some news from Micron Technologies. The stock's been on an absolute run, but recently it traded down 8.5%. It's just $664 a share. And Talent chimes in and says, "I knew this was going to happen. That's why I sold at $120." Uh, very silly, wild times in the semiconductor stock world. But we are moving on. We're going to be talking to our next guest about advertising and a lot of other stuff. Welcome to the show. How are you doing? >> I'm doing well and thank you so much for having me. >> Please introduce yourself for everyone who's watching. >> Sure thing. Uh so my name is Philipe Indirect. Um my accent is Belgium. I'm a recently crowned American very proud of. >> Congratulations. >> Thank you. >> Um and I'm the CEO of a company called Tatari. We are in short uh technology for TV advertising. >> Okay. >> So that means that anybody who uses our product can manage their creatives. They can plan their TV campaigns. They can execute the campaigns or buy the inventory, >> measure it, optimize, rinse, repeat over and over. >> Yeah. >> Um, we do so not just for streaming TV because I think there's a lot of talk about it, but also linear. Yeah. Cable and broadcast kind of the oldfashioned TV >> and uh over the air, right? Yes. Yes. Yeah. That that's somewhat going away. It's going away. Yeah, it is. It is. We'll get into all that. >> We'll get into that. >> Take us back first. Want to hear where you grew up. what you studied your first company. I want to hear the journey. >> Ah yes. Uh and this is where I'm going to age myself. Um so um as I mentioned grew up in Belgium but um got called by the Silicon Valley and the com boom. >> Okay. >> Um and that's also where I started my first company December 1799. >> Shazam 1999. Yeah. Were you born? >> What a what a time. >> We were both alive. >> I was just a boy. >> I was an early adopter. Although I don't know if I was using it in the '9s. Uh was it What was the product when you actually started it? >> Yeah, it was very >> and and I guess like had you done any kind of scrappy startups back in Belgium or this was your first? >> Um, let me answer that in first. Um, my parents had a small grocery store supermarket and I just worked hard. >> But I don't think I was an entrepreneur as we would define it today back then. >> It was in the blood. >> Yes. Uh, that's where I learned what hardworking meant and what it can deliver. >> Um, Shazam was very different. Um so I mean look it we put it together before um you know even the iPhone existed or the iTunes store. >> So the first version which launched in August of 2002 um is when you heard a song you actually had to take your phone >> and then dial a short code on your handset 2580. You didn't have to remember the number because if you can look on any telephone handset 2580 are the four digits right in the middle. We then would listen to the song as as if you were speaking into your handset. Um do the recognition and then send a text message back with the name of the track and the artist. >> Uh to receive that text message, it goes one step further. Uh there would be what is called a reverse SMS charge. Okay. >> By dialing that short code, you accepted to be charged to receive that SMS. >> And then just to top it off because we were not a nonprofit. We had to make money but also cut a ref share with the mobile operators on the back of that. It sounds great, but it didn't really go anywhere. >> Yeah. Yeah. >> Wait, also also you started, so it takes you two years. Two years to build the product. >> Yeah. What's going on from 99 to launching the product? There's a massive market selloff in that time. Like did you you had a lot of fun. No kidding. >> No, I mean like timing is everything, right? Timing is everything. And if I look at Shazam, there's kind of what I would call good timing and bad timing. >> The good timing is industry transformation. And that applies to any startups. The industry transformation for Shazam was evident. Uh in between 2000 and 2002, the recording industry in the United States shrank from about $15 billion to 78 billion annually. Everybody claimed or blamed Napster and piracy for that. I somewhat disagree. I think it was Steve Jobs who unbundled the CD and allowed individual downloads. >> Interesting. >> Right. But an industry in peril is good for a startup. So our timing there >> good. M >> the bad part is well um the the technology wasn't ready for it. Sure we had the algorithm but the experience to Shazama song was just >> Did you have the algorithm or was it people on the other end recording it sounds no no no the the algorithm was real. Okay. >> Um >> but the experience was just clunky. I mean like right and it wasn't until the iPhone came along right where you had that beautiful experience with a touch color screen. You hold your phone to it and and it comes back with rich information and and that changed everything. Not to mention the distribution with the iTunes store. >> Uh we were running >> So you start the company in 99 but the iPhone doesn't come out till 2007. >> Yeah. Yeah. Whatever. Yeah. Either way. Yeah. >> Uh so you're just chewing glass the whole time or was there was there signs of life? >> Uh no no signs of life. Um I mean we I can show you a chart you know time with music or shazams right and and so we were flatlining and it when we running the consumer business we were bleeding cash uh >> so you had raised some money >> we raised some money um the truth or the unknown story about Shazam is that uh around 2002 or 2003 I realized that there were big companies that actually needed music recognition for royalty tracking. think of companies like um uh uh BMI or ASCAP. And so I started cutting multi-million dollar licenses with them. And so while we whilst we're raking in money on the business side, we're kind of quickly losing it on the consumer side. Yeah. >> And then the iPhone came along. >> Wait. Yeah. Walk me through the anatomy of one of those BMI deals. Where are they identifying >> music? Are they are they going to a bar and seeing that a song is being played and then they hit the bar up for a payment? Like how does that actually work? >> Yeah. Or just radio, right? So, uh rewind the clock back 20 years and you're an artist, you get paid on to the extent that your song is being played on the radio. >> Okay. >> And the way that was done back then was sampling. Literally pen and paper. You put a few college students in a in a warehouse and and you let them sample to a few hours of music. You write it down. So, um, sampling unfortunately doesn't work well if you're a small-time artist because you're never going to show up in the artist. So, they had a lot of complaints. They had to go from a sample survey to a consensus survey. >> Interesting. >> That's what Shazam did in an industrial setting for them. Now, every single song >> airwaved on say the 2,000 radio stations in the United States was accounted for and royalties could be paid. >> Did you have a direct link to the radio stations or were you receiving the radio waves? >> You take it from you take it from the radio. So, so >> we still do that today for Tatari by the way. >> Wow. Okay. So, so you had to set up uh radio antennas in every market then as well and then encode that into a database that you could access over the internet. Was that what was going on in >> Sure. Uh we didn't place the antenna. This is kind of like >> equipment that you can lease. >> Okay. But but >> so you say I want to track Boston. Let me go lease a antenna in Boston. I will get a feed that then I can through the system on the server. >> Yeah. Yeah. That part is easy. It's it's and >> yeah, >> it doesn't doesn't really sound that easy to say. >> But here's a here's a part I actually quickly want to see since we talk a little about Shazami. I'll quickly share is that Shazam is a company that never should have exist right because ultimately it was a coming together of four concepts each improbable in their own right. >> We had to build the largest database of music in digital format to have the reference track >> in the year 2000. We had to invent the algorithm. Music recognition like we do for Sesan didn't exist yet. When we had the algorithm, we right we had to find a computer cluster to run it on. There was no Google cloud or AWS. So we had to we came into the office, we were littered with screws and bolts and equipment on the floor. And then four, like I just alluded to, we had to get all the mobile operators on board to get this thing going. So even if I'm generous, I'm giving each of those four 10% probability. You compound them together. I'm probably going to drop a decimal here, but the chance of Shazam surviving and existing today is what? 0.0. 001% >> something like that. >> Crazy story. >> Nothing. >> Tatari was a whole lot easier. >> Okay. Interesting. Well, to close the Shazam story, talk about uh the decision to work with Apple. >> Um we the company was sold to Apple. Yeah. Right. Um and >> why what was the motivation? What was the what was the potential? Yeah. Why was the right time? >> Yeah. I mean, I always say that Apple bought Sazam uh for a song. Um uh but I think you know at that time Apple wanted to build build its own Apple music subscription >> uh service uh and um Shazam is incredibly legion to that you recognize a song instead of buying or downloading the song subscribe to Apple Music uh and so that was you know in the in the business of music streaming your true hos say licensing the content is is always variable to your revenue and that's not a true cost of goods sold. Yeah, >> your true cost is is user acquisition and so um Shazam gave uh Apple that Trojan horse to get in there. >> Yeah. What was the what were the secrets to user acquisition at Shazam? I mean I I feel like I must have found out about it from some tech blog talking about the coolest new apps or something. But what was the funnel? >> Three words, blood, sweat, and tears. No kidding. >> No, it was look it was it was difficult. Uh right, as I mentioned, those first few years we flatlined because nobody figured out about it and and and it was a clunky experience. When the iPhone launched and they made right, they had to showcase the power of that device. Not to mention when the iTunes store launched and they needed to fill it with great apps. We were front and center. >> That that was our launching >> and it was such a differentiated app. There were so many apps for games and so many apps for the 10 different calculator, flashlight, task tracking apps. Uh, it was only >> Shazam. >> Yeah. And I make it sound like as if we got incredibly lucky, but let's be realistic. We had to wait five years >> in the dark alleys for that to happen. So, I feel like we earned it. >> Yeah. It's it's it's fun. We had Roger uh Lynn Sean who was the CEO of Pandora last week. And uh for me as a kid, Shazam and Pandora were the two magical technology experiences. It's like so memorable going from you know you hear you're listening to the radio you hear a song Google even googling lyrics back then didn't work very well. You could nowadays you can string together three or four five words and probably get the track but back and you have a phone right there. But back then if you would do three or four words together didn't wouldn't find the right song. Um, and so just like going from having those moments where you you hear a song, you love it, and then it's just gone forever or maybe you hope you hear it on the radio again and you kind of catch something about uh who the artist is. >> I remember at one point it got so good there was an auto mode that you could you could turn on, leave it in your pocket if you're at a bar or something and it would at the end of the night show you the full playlist, every song that it detected. >> And you also notice that at the end of the night you would have a depleted battery in your phone. >> Yeah. better. >> We've gotten better at those things. >> But there are some fantastic memories. And some of those songs live on in playlists that I listen to to this day. >> And to me, it's more than just knowing what the song is. It's about creating your playlist, knowing what to listen to. Yeah. Right. At the time, no. >> Yeah. So, uh, talk about your Did you spend a lot of time at Apple? Were you there at all or did you move on immediately? >> Yeah. No. So, I left kind of the company operationally around 2004. >> Okay. >> Uh, I joined Google. I was one of the early people at YouTube. Incredible ride, incredible experience. Uh I then left and um uh launched a product called True Car actually here in LA. So I lived here. >> Truear. >> Um uh did that for a few years. I then moved back up north. >> Uh was at another startup. We got acquired by Yahoo. Eventually in 2016 I started my current company uh Tatari which we kind of started this whole conversation with. >> Yeah. So tell us it's been nine years now. >> Yeah. Yeah. Tell us about the idea for Tatari. the the timing, the blood, sweat, and tears. >> Yeah. Yeah. Yeah. >> Or lack thereof. >> Yeah. I think the the kind of the the the idea for most startups comes from personal experiences, right? Shazam, not knowing what the song is. True car being afraid of going to the dealership. Y >> um uh Tatari was actually the TV advertising experience which I witnessed at True Car. >> Yeah. >> Not great, right? Sure. >> And so I knew we could do better. Um uh we started with TV measurement. Why? Because if we can measure TV campaigns and its effectiveness better, then we can optimize and make it run better. We quickly realized that there was an opportunity for injecting technology and data science in the buying process as well. You put the two together, buying and measurement, it makes for what Tatari is today. So we are um 300 people strong. We're a US company. Um we're doing well over $und00 million in net revenue, right? And that's not media, right? That would be an order of money, bit much higher. >> Um, we've been profitable from day number one and been mostly self-funded. >> Amazing. >> Can I get the gong for that? >> Yeah. Yeah. Yeah. Hit it yourself. Hit it yourself. You're here. >> Thank you. There we go. Smash the gong. >> That is great. Uh so you mentioned something about Shazam which is like starting a starting a business in a sort of a troubled industry during the time of the >> the music industry was struggling. uh Tatari looks very obvious in hindsight, but maybe some entrepreneurs wouldn't go into that because they're like TV's dead, right? This this idea and you and you were probably looking at sort of the global TV advertising spend and and and to my knowledge it's still growing, right? It it is although modestly unlike you know certain other media >> but everyone I mean if you just ask a random tech person they'll be like it's down 20% every year and it's going to be zero in two years. Like that's the default assumption in tech. >> Let's say unlike print and radio it's holding up nicely in the United States at about $90 billion per year. What's happening inside is this massive transformation out of you know cable or and and broadcast TV into streaming. I mean you experience this yourself every >> day. That is again the good timing component. Yes, for sure I did see that right. Uh uh I I love your oneliner TV is that you know starting this company in the Silicon Valley in San Francisco for whom TV was a big no no. I mean like I had to hear this many many times. It's actually one of the reasons why I actually didn't really raise money for this company because I don't don't think that Sand Hill would have given me those you know the valuations we just heard. So so sometimes it be better lucky than good you know. No, but it creates an opportunity too cuz you know that you're not going to get the 50 other ultra talented teams going after the same problem. >> That has changed since then. But yeah, >> but that's good. Competition is good. Competition keeps you sharp, keeps you going, gets the best out of you. That's all cool. >> So, talk about the early measurement struggles. like uh if I'm running a TV ad campaign for uh the Super Bowl or NBC Sports or something like why can't I just call them and say tell me exactly what happened? Why don't they have the data? Is it a trust issue? Is it a measurement issue? Like what what was the market opportunity? >> Yeah, let's unpack those because you're kind of me referring to measurement and then the buying process. So let's start with the measurement. uh the the way in which TV advertising has always been measured traditionally was via Neielson >> Neielson ratings >> right yeah the success of my campaign is defined by the extent to which I reached an audience >> now as newer brands came to DV with digital experience they want more they want to know the effectiveness right to what extent has my campaign driven uh signups or installs of my apps or or downloads of my products whichever it is >> LTV yeah that stuck around for a long Right. And so that was actually one of the first things we did, right? The first thing we did was bring about a different type of measurement for TV. >> Uh uh that outcome measurement, not the not the kind of the audience measurement. >> How did you do it? >> Uh built invent from scratch. So my co-founder um yeah just you know look at you know as many data sets that we can find and try to make the most out of it and and you know there's there's both deterministic and probabilistic approaches to this a whole lot of algorithms and math to it. It's never ending. >> Um it's a little bit like I refer to like like like the large language models or the Google search algorithm. Every month or two or three we find a little tweak and then we release that and update. Um uh and so it definitely has spoken to the smaller brands because when we now bring a smaller brand to TV I don't company like Spot and Tango I I don't know what their marketing campaigns are but they're definitely heavy in digital. when they first get into TV, they would like to see a measurement that they compare on an applesto apples basis to cocktail TV. Exactly. Right. And then once they get in and they grow and they gain confidence, then they can switch to that Nielson recipe, which isn't necessarily bad, >> but it's more destined for the bigger brands, right? Where do I create my reach and awareness? And so, we'll do both. We'll do both continuously. The name of the game in the world of DV advertising is scaling up. Some of our brands start with actually sorry most of our brands start with as little as $50,000 or $100,000. Last year we placed four or five brands in the Super Bowl right those are $50 million plus tickets and these are all brands that we kind of took through took through that journey. >> So that's the uh maybe it's a good dove tail then into the buying experience. Yeah. Look there's a still of what they say analog practices in TV uh the Super Bowls and phone calls. Yep. Yep. That's how you buy it. There's obviously an incredible drive for this concept of programmatic y >> in TV advertising. >> I will say this and I'm not sure if I'm opening a can of worms here. I don't think it's the right model, >> right? Um programmatic ultimately the TV advertising market and the supply of adven ad inventory is very concentrated. 90% of all the impressions of the ad impressions typically come from the top 10 publishers is what the three of us watch on TV. Mhm. >> The big names Disney, Peacock, Analy, right? And so if you have such concentration in supply, it really doesn't make sense to apply digital principles and technology, i.e. programmatic to get into it. You're much better off with direct integrations. And so that's where we will differ a lot from the industry. Um uh you know, again, it it works better for the publishers, it works better for the brands. you don't have the intermediaries. You don't have the the the back. And >> just to repeat that back to you, basically if I'm ESPN or one of the platforms, I want to know that a certain brand is allocating $5 million a year to my >> Yep. >> uh to to of spend uh with me and then you're just sort of like allocating that. It's not like they want to sell each individual slot for, you know, $10,000 here, $20,000 here, that kind of That's the ideal, but that's that's not always feasible. >> Yeah. >> Yeah. Yeah. Yeah. Got it. How is how is AI changing the uh the TV ad buying space? And what I'm what I'm interested in particularly is as the cost of generating new creative comes down. Yep. >> That feels like that could be a tailwind to more programmatic ad buying on TV. Yep. Um, at the same time, there's something about if Matthew McConnA is in the Salesforce ad or Mr. Beast is in the Salesforce ad at the Super Bowl, everyone saw the same ad. And so, the fact that it's not personalized actually adds as a little kicker on top. Is that a mitigating factor? How how are you how are you assessing the tensions? >> Answer that part first and then I'll get to AI, right? Um, ultimately you refer to targeting. Yeah, >> targeting is good, but always realize it's a double-edged sword because the more you target, the smaller your audience become, >> right? And then you just find one person. Ultimately, what you want to achieve with TV is finding people who've never heard about your product and service, >> right? It's actually sometimes less about targeting, but it's it's about driving reach and awareness. Yeah. >> Right. And generating demand, not so much harvesting through targeting, right? And so targeting is good, but it's not it's more of a kind of like a um a feature. It's not the core strategy of of finding a new audience. >> So so I would say that >> AI I mean like gosh, you know, like ATT tech is is was primed for AI, >> right? Because it it lives on data >> and and look, I you know, I I'll be honest, I think we got a little lucky when it comes to AI as a company. Um this is like three four years ago as we grew so fast and we had to completely kind of like move out of a backend technology called Redshift into data bricks. >> Oh interesting >> monstrous. But what it meant is that by the time the large language models became available we were running hot. We were so ready for it. >> Oh interesting. >> So in plain English what does it mean uh as a Tatari client? Well, um, we can plan campaigns with technology and AI built on data sets and rich history in seconds with deadly accuracy across way more buying entities than a human being ever could do. Right? If you're a a human buyer and you've got to choose out of 40,000 linear network rotation entities and 10,000 streaming opportunities, you you can't compute this in your head >> for a computer. This is this is easy, right? And so AI in media planning, this is how we operate today. Uh we actually I we announced this about a year ago. We pretty much doubled our revenue with the same amount of people with tools like that. Uh we're kind of wondering can we go to a 4-day work week now on the back of AI. Uh the next thing out there is really leveraging AI in the exec media execution process, right? Rather than running auctions, you know, tens or hundreds of thousands of auctions a second to get the best uh impressions, maybe we don't run auctions, but we use AI to pick the ones that we believe are most fitting based on the data and the knowledge in the data. >> Oh, interesting. >> Yeah. >> Uh do you have any interaction or opportunity with some of the newer firstparty advertisers? We talked to the president of advertising at Netflix and they at one point were partnering uh with Nad Buyer now. It feels very homegrown. Is there an opportunity for these other platforms as time and attention shifts onto the YouTubes of the world, the metas of the world? Is there a world where you play into that? >> Um those company I think you're referring to the walled gardens. >> Yeah, the walled garden. >> Yeah. Yeah. Yeah. Yeah. We have a we've got a name. We've got a name for them. Yes. >> Do you have a drill that can drill through the wall of the walled garden? >> Look, um it I mean ultimately like you know there are certain I think they're 10 15% of all kind of viewership today. Um and of course we have we have we have products and services that lean into it. What's missing and it's less for us but it's more for the brands is the data that allows us to bring that measurement about that close the loop as you refer to it. And so um what we've seen over the years is that many of the new or larger publishers they they manifest themselves as a world garden but then they see that hey if I show a little bit of data that enables the measurement then I get more advertisers so it drives more media and I get the flywheel going. So we're hopeful that will change over the years. >> Um um uh as brands um you know >> it's it's you know YouTube is no longer a website or an app. It's a TV channel, so you got to be there even if certain components aren't as fully built out as we as we would want it to be. >> Yeah. >> Uh yeah, Jordy, >> are there any uh very odd random question, are there any TV are there any TV networks that are effectively just an infinite feed of short videos that people scroll through like a vertical video? Because I can imagine you could make some pretty compelling >> television just I saw someone screen shared their Tik Tok or Instagram reels in a theater and people showed up to watch in the theater. Mostly a prank, mostly a stunt, but a very funny social experiment. >> Look, when Twitch was first explained to me and you know like like I thought that was the silliest thing ever. >> Video games on the internet, >> but maybe not such an odd question. Uh I mean there's been said that Tik Tok would go to TV. That all makes a lot of sense. What is TV? It's really is is as an advertiser. What is TV for an advertiser? It's the ability to show your company, right? And a rich media, audio visual, not with a few characters, but 15 to 30 seconds >> above all to a consumer who is in a laid-back experience, most likely accepting of the ads. Y >> right. And then uh uh not to mention the last but most important piece, the largest audience possible spending the most time. The reach of TV is bigger of that than say Instagram. >> But when people spend an average of 30 minutes per day on Instagram, they will spend three and a half hour and growing on TV every day. >> It's crazy. as an advertiser that the the the the >> the debate around uh phone addiction has completely given TV air cover, you know, because when I when I when I was, you know, 10 10 years ago, it was the average American spends x amount of time watching TV. >> Bumper stickers in the 80s and 90s, TV rots your brain. The original >> Oh, yeah. My parents would give me hell for watching MTV. That would be the best thing if if I could only convince my teenage daughters to watch MTV instead of Tik Tok. No. And >> I'd be so much happier. >> You just don't like wall. >> You just want the more adventure. >> I want more inventory. >> It's not about the It's not about the brain rod. >> It's a grassroots movement. >> Uh where where do you where do you see the business going? You said that you're lightly capitalized, haven't raised a lot of money. Where do you see this where do you see taking the business financially? >> Yeah, love and financially I mean look, we we I mean I can share this. We we have a very clear plan to um uh uh more than double the business in the next two and a half years. Uh we started this plan actually like 6 months ago. Actually actually >> um um kind of exceeding the plan right now. Great. >> We got to work it out. Um I I if I look back at my other businesses um Shazam or True Car sometimes we would sit there at the beginning of the year you know planning product and we'd stare at each other not necessarily knowing what to do or what would stick. Tatar is a little bit the opposite. >> Uh we got more that we can chew off and we know we can monetize it all. So >> so we we are uh working very hard um um and and so um yeah I think we know exactly what we're doing. maybe somewhat related outside Tatari which could be interesting for the viewer uh or the listener to hear is that I do believe that there is it's not a collision but a true conversion of influencer media and TV on the horizon. Um, >> stupid fly. There's >> the flies terrorizing us. >> One fly versus brutal. >> Uh, because you're >> doing a great job. I was ready for that. >> Uh, but right because look, when as little as 10 years ago when you launched a TV advertising campaign, you had one creative 30 seconds. You spend a lot of time on that and emotional capital. What is that best creative? Uh and nowadays you you launch with 10 creators and you see which performs best. If you look at influencer media, well they create a 100 videos, toss them all out, find out which one is best >> and and that that's the winner. Well, >> you can easily see how these 100 influencer videos will now, >> you know, cross pollute into uh TV. So I I think there's an incredible moment uh on the horizon for us in terms of convergence of two types of media. >> Well, thank you. Great to meet you on. >> Uh, that's our show, folks. Leave us five stars on Apple Podcast and Spotify. Sign up for our newsletter at tbpn.com. And we will see you tomorrow at 11:00 a.m. Sharp. Love you. Goodbye.