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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TVPN.
Speaker 2:Today is Thursday, 07/17/2025. We are live from the TVPN Ultra Dome, the Temple
Speaker 3:Of Technology, the fortress of finance,
Speaker 2:capital of capital. Today, we have some crazy news at a Coldplay concert. That's where we're starting, I guess. This went insanely viral. The CEO of a company called Astronomer was caught on the kiss cam hugging one of his employees, the head of HR.
Speaker 3:And I said
Speaker 2:But Chris In the video, Chris Martin is like, something's going on here.
Speaker 3:I Startup CEOs can't even hug their chief people officer at a concert in this country anymore.
Speaker 2:It is crazy when the internet descends on a current thing, how viral it is. Like, just you have to jump in on the current thing.
Speaker 3:Well, before we talk more about this
Speaker 2:Yes.
Speaker 3:I wanted a quick word from our sponsor. ASTRO by Astronomer is the orchestration first data ops platform built on Apache Airflow, empowering your team to build, run, and observe data pipelines that just work all from one place.
Speaker 2:Do you you believe the conspiracy theory? Put on the tinfoil
Speaker 3:Yes.
Speaker 2:Will you steel man the tinfoil hat? What what is the tinfoil hat explanation here?
Speaker 3:Tinfoil hat explanation here is
Speaker 2:All press is good press?
Speaker 3:Is that, Nathan for you, this is just part of an elaborate stunt. Yes. And Nathan's plan was, have the CEO get caught having an affair with a coworker to increase brand awareness and get a buzz going. This was Charlie Light over on X.
Speaker 2:Definitely got a buzz going.
Speaker 3:Yep. A lot more people know about Astronomer today.
Speaker 2:100%.
Speaker 1:100%.
Speaker 3:But hard to see how it would have been planned. There's been a bunch of jokes. Ryan Peterson said, boards should give him a raise. Without this viral moment, I'd never know that Astronomer is used by enterprise clients to manage Apache air flow and achieve 70% higher uptime than self managed air flow. So lots going on today.
Speaker 3:Alex Cohen says Yeah.
Speaker 4:Imagine losing half your life savings at a Coldplay concert.
Speaker 2:Why half? Oh, because he's gonna get a divorce. Okay.
Speaker 1:I it was about him getting It's very sad.
Speaker 2:Thought was a vesting
Speaker 4:joke.
Speaker 3:These are adults that made their own decisions.
Speaker 2:Yeah.
Speaker 3:And they now have to live with the consequences. But I doubt either of them would have would have paid half their net worth for those tickets.
Speaker 2:Yeah. Rough. Very very bizarre. I was reminded of what Emily Sundberg told us when she came on the show. I was asking her how the Hamptons has changed since the era of social media, the the age of the internet.
Speaker 2:And she said that there are so many TikTokers documenting everything that happens in the Hamptons now that you can't even leave a party with someone else's wife. That's what she said to us. Do you remember this? Yeah. And I'm wondering like, what does this actually mean for birth rates?
Speaker 2:What does this mean for like, this seems predictable at this point. This is the first one that's happened. I've seen these in their videos.
Speaker 3:Having debate this morning, which is that Find My Friends is the best thing to happen to Monogamy. Yes. Potentially ever. Yes. Because if you are in a committed long term relationship.
Speaker 3:Yeah. And you do not want your partner Yeah. To have visibility into your whereabouts, you can make a pretty bad argument for privacy. Yeah. But it but it but it it ultimately doesn't.
Speaker 3:It's really hard to stand behind. So Yeah. I think it's potentially a really positive force against social media Yep. Dating app culture and things like that. Yeah.
Speaker 3:So the answer to technology problems is more technology.
Speaker 2:More technology maybe. Yeah. It was like this it's this countervailing force because like what was it like Instagram is like constantly flooding you with like recommended like, look at this girl, look at this random person, look at this thing, look at you know, like go down this rabbit hole and then and then find my friends is maybe pulling you back. But I mean, he probably told, he probably said I have to go for this for work. Yeah.
Speaker 2:This is a client.
Speaker 3:This issue.
Speaker 2:Doesn't really fix this issue. Lu Lu has do. The kiss cam is a Linde technology.
Speaker 3:So Some Lu had advice. She says, just given out priceless
Speaker 1:Yeah yeah yeah pretty much. Comms.
Speaker 3:Crisis comms for the astronomer team. She says, don't bother with crisis comms here. The CEO will try to get you to protect him but it's not his company. He's a temporary steward. Your job is to protect the company.
Speaker 3:The CEO is a professional manager who's only been there two years. The HR person has been there less than a year. Neither is tied to the identity of the company. Preserving trust is more important. Your business model is to handle sensitive data, and your priority is scaling, and that's tough to do when multiple known lie with multiple known liars on the senior leadership team.
Speaker 3:A better comms plan than trying to save the situation. Andy Byron is on the board, He's not a founder. He doesn't have control. The other five members should replace him. You can then use the new CEO announcement as a reset and get people to focus again on astronomers actual business instead of its drama.
Speaker 3:So we we did reset, reach out to to Andy this morning to see if he wanted to tell his side of the story. Felt felt like an extremely You gotta be a little bit crazy like Soham to wanna come on Well, after you the current thing. Yep. But in this case, we should have the new CEO on of Astronomer when whenever that comes. So there's a poly market today
Speaker 1:Mhmm.
Speaker 3:On whether he'll be out by the end of next week. Odds are currently sitting around 38%.
Speaker 2:Mhmm.
Speaker 3:I would not be surprised if there's somebody new stepping into the CEO role at the company. This seems to have been a way way bigger than just the current thing on x. It seems to have really broken containment. So
Speaker 2:Is this a Databricks competitor? Like, Airflow is it says open source workflow orchestration platform used to programmatically author, schedule, and monitor data pipelines. I wonder if their business is just exploding. DAG directed
Speaker 3:Quite the lineup of investors. They've got Bain Capital Ventures.
Speaker 2:Let's go.
Speaker 3:Just led a series d D. This year into Let's go. Into astronomers. So let's hit the size code
Speaker 1:for
Speaker 2:that. It's probably fantastic business.
Speaker 1:And then
Speaker 3:Insight is also Okay. Led the series c in March.
Speaker 2:Yeah.
Speaker 3:So pretty Venrock was in the series a as well. And then Sierra Ventures, who I'm not familiar with, has led a couple different financing. So, yeah. This this business has been around for a while. They're gonna get through this.
Speaker 3:I'm sure that Bain Capital and Insight and the other members of the board are already figuring out who they can get to step up and run this company.
Speaker 2:Yeah. There just seem to be some sort of line between, like, bizarre, salacious, but ultimately orthogonal to the core business drama and, like, actual core business drama, like some fundamental flaw in the business plan that's exposed. FTX or Theranos versus just this like, you know, drama that's happening here. I I keep I keep laughing about that that that analogy we go back to where if you found out that, you know, I think what what do I have? I have what what are Pilot Sport tires?
Speaker 2:Is that Bridgetown?
Speaker 3:Michelin.
Speaker 2:Michelin? Michelin tires? So if the if if you told me that the CEO of Michelin was was was caught at a Coldplay concert with the head of Michelin HR, it would be a tall order for me to go get new tires. Right? I'd be like, the tires work pretty well.
Speaker 2:Yeah. That issue doesn't really affect my tires.
Speaker 3:It's more it's more so that the the difference here
Speaker 2:Yeah.
Speaker 3:Is that being caught is different than being on the Kiss Cam Mhmm. And getting a 100,000,000 views today. My post alone has a million views. That's amazing. And I posted it a few hours ago.
Speaker 2:But do you think do you think it's it's it's going to actually affect like revenue
Speaker 3:I don't think it I don't think it will affect the business at all necessarily. Maybe a little turbulence because of needing to find new management and
Speaker 2:having Certainly, they're stressful weeks
Speaker 3:of Turnover stuff. Turnover on the on the on the exec team is gonna be a challenge. Mhmm. But ultimately, their customers are not going to, you know, say, hey, we're we're turning off. You know, we we want out of our contract.
Speaker 3:If if the product is good, maybe some people use it as an excuse. Sure. But yeah, I don't see this affecting the business. But then again, it's like if you're paying capital or insight, do you really want do you want a a he came in two years ago. Sounds like he's been executing.
Speaker 3:The team has been executing well. If they got from series c to d over the last couple of years Pretty means they're they're probably growing nicely. But and and I don't necessarily think that that this is the end of this guy, either of their careers.
Speaker 2:Yeah.
Speaker 3:It just should be the end at this company. Yeah. Because if because if you're the board and you and you tolerate this, that just means, yeah. We we tolerate people of you know, poor moral character.
Speaker 2:Sure. Yeah. Also interesting, I mean this company's like never even heard of it and it's on an absolute terror series d at this point. And does this not sound like something that should be in the AWS dashboard? Like we were talking about browser based yesterday getting like quote unquote copied and there's just something about these like point solutions that just are are, you know, nailing a specific problem.
Speaker 2:You know, in this case, it's like deployment deployment and management of an open source project. It's literally anyone can just run Apache Airflow. They just help you do it better. And that's kind of what Databricks did with Spark. Like, Spark's an open source project.
Speaker 2:Now they now they for these data pipelines, now they help companies actually install, manage, run them, and then put a bunch of software on top of it. And Databricks has been massively successful. And so it's it's interesting to bring it back to Browserbase because it just kind of reveals that, like, these companies can be kind of grinding in silence for a while. Just, I guess, the note for Paul Klein is probably stay out, avoid being the current thing. Like because the the the failure mode could could be less technical and more interpersonal.
Speaker 2:Yeah. I don't know.
Speaker 3:True. Anyway. Work retire die may inspired by my post. Okay.
Speaker 1:It could have
Speaker 3:been totally random. But he said married CEOs can't even hug and romantically sway with their married head of HR during a cold concert anymore because of woke.
Speaker 2:Oh, because of woke. Okay. Yes. Yes. Yes.
Speaker 2:Are there is there anything else to cover on the
Speaker 3:Sophie NetCap Girl says it's so hard to get noticed as an AI company these days. The astronomer CEO had to cheat on his wife for marketing. Yeah. It's dark out there.
Speaker 2:I don't think I'm not believing the tinfoil hat one on this one. I think it's an L.
Speaker 3:It is a huge L. But there's a lot of good stuff happening today. Yes. Open AIs.
Speaker 2:Like ramp.com. Time is money. Say both. Easy use corporate cards, bill payments, accounting, a whole lot more all in one place. Did you see the what Model YL is launching?
Speaker 2:Has a six seat configuration, three inch longer wheelbase than the Model X.
Speaker 3:Can you hold this for me?
Speaker 4:The L? Hold that.
Speaker 2:The L? This car will sell like hotcakes. It's a 193 inches, I believe, which is not quite Escalade ESV territory, but much bigger, much closer. I was talking about this for a while that
Speaker 3:like Wait. So they made the model they made an XL version of the Model Y instead of making an XL version of the X?
Speaker 2:Yes. Because the X is their premium product that's more expensive. They need to get into the full size affordable SUV market.
Speaker 3:Got it.
Speaker 2:So this will compete with the Hyundai Palisade, which is a full size SUV. They're they're firmly in like the crossover territory right now where it's a five seater, but you can't really put a whole bunch of car seats in there. You can't bring the dogs, all that type of stuff by adding I think it's like a pretty significant length. I think it's like maybe 15 inches longer overall, brings it to that 200 inch length and winds up with a product that people feel comfortable throwing their whole family in basically. Yeah.
Speaker 1:It's great.
Speaker 2:I agree with this takeaway from Nick Cruz that this car will sell like hotcakes. I think that this is this is this is the most obvious thing that Tesla's been missing in their lineup, is a full size SUV. Yeah. The Model x always and even the model even the Model s came with at one point a third row configuration, but it was always super tight. But now they're kind of dipping their toe into full size SUV.
Speaker 2:So you still gotta do the Suburban now. The Cybertruck SUV. Suburban. I mean, that's the original story of the Suburban. Right?
Speaker 2:Wasn't it an f one fifty? They took the f one fifty Really? Body on frame. So it's technically a truck. This is like the Excursion.
Speaker 2:Mhmm. People got really upset about this because total gas goes there. But they take they take a truck, which is this it's not the unibody. It's the bottle body on frame construction f one fifty, but then they would just create, like, a whole, like, passenger compartment on the whole thing. And this was the the Excursion, the Expedition, and then they kind of started downsizing it to the Explorer.
Speaker 2:And then at certain point, customers were like, okay. I want the aesthetics of an SUV, but I really want the gas mileage of a car. So build me a car that looks like an SUV, and that's where we got the crossover. So the crossover is all of the manufacturing strategy or manufacturing, like, techniques of building a car, which is this it's not body on frame. It's not this, like, platform that you can put an ambulance on or a fire truck on or whatever you can do with a truck.
Speaker 2:It's it's it's all designed to be one thing. But then, like, customers went down into like the crossover market, which rides better. It's not as bumpy, but it's ultimately smaller. And now, we're stretching out the now we're going backwards. We're stretching out the crossovers to the point that they're gonna be full size SUVs.
Speaker 2:But Funny. The Cybertruck is its own unique platform, own unique manufacturing line. Obviously, own unique unique styling. And I think if you make that full size SUV style, it would sell much better. Because people people in LA, you see like people in LA want G Wagons.
Speaker 2:You among them.
Speaker 3:Well, The the Suburban, the the Cadillac Yeah. Escalade V Yes. Is is a very fun, exciting car.
Speaker 2:Yeah. But I mean, the the difference between a Ford Raptor and a G 63 is practicality in my opinion. You don't need the truck bed. Yeah. You need the interior space.
Speaker 3:I would use the truck bed because I surf. Yeah. Quite a lot. And so that was nice. Yeah.
Speaker 3:So having having a covered bed is nice, but surfboards fit in cars. Exactly. And and every time with the Raptor, like, you own a Raptor, you realize that there's just not that much space in the actual cab. Like it's Yeah. It's pretty it's pretty tight in there.
Speaker 2:And I'm pretty sure the Raptor is like 220 inches long. So it's like over two or three feet long
Speaker 3:And the bed is also very short. So it's like not a super functional bed, not a super functional cabin.
Speaker 2:No. It makes But it looks more sense to have a full size SUV.
Speaker 1:Yeah.
Speaker 3:It looks you wanted when you were five years old. Yep. And you said, I want a big truck. Yeah. And then as an adult, sometimes you have to get it.
Speaker 2:Gotta bring it back. Let me tell you about Graphite code review for the age of AI. Graphite helps teams on GitHub ship high quality higher quality software faster and get started.
Speaker 3:Let's give it up for Graphite.
Speaker 2:Graphite. In other news, Juul has been approved by the FDA. Authorized is the keyword here. Authorized. So I know way too much about this but it is a it is a big big turnaround since, the FDA, would was refusing to authorize, the Juul e cigarette years ago.
Speaker 2:Juul says exciting day for making cigarettes obsolete in America. The FDA has issued marketing granted orders. These are MGOs. We'll get into this, but it's, like, slightly different than, like, FDA approval for a drug for the Juul system, recognizing that these products as appropriate for the protection of public health. They don't have to say the FDA doesn't have to say that it's good to use Juul, just that having Juul on the market has a net positive impact.
Speaker 2:And that's because cigarettes are already on the market. So they it's this relative calculation that the FDA is Yeah.
Speaker 3:It's it's much harder to argue that Juul should not be able to sell when cigarettes sell daily.
Speaker 2:Exactly. So the FDA is not saying everyone should go out and start using Juul. They're just saying that keeping Juul on the market is a net good for the American public health, which I'm sure will be hotly debated by a lot of people, but it's what the FDA So that over two million adults have switched completely from deadly cigarettes to using JUUL products, and they and they approved a few different e cigarettes. The big thing is that they approved the
Speaker 3:And can you talk about the last few years?
Speaker 2:Yeah.
Speaker 3:So I feel like that's a sad story. Basically, Juul is just getting hammered by, like, all these different regulators. Yeah. Yeah. Meanwhile, the average gas station is fully unregulated vapes that are litter seemingly literally tested on children.
Speaker 2:You've seen the videos. Videos
Speaker 3:have gone viral where
Speaker 2:That's right.
Speaker 3:Where don't think he was inhaling, but having to like make sure that each one works. And then
Speaker 2:Killer use case for a humanoid robot or just a just a device that inhales. Like, that's just a fan. You don't Yeah. We've been able to create suction from robotics equipment or or machinery for, you know, probably a hundred years and yet they're still using a human for that. Disgusting.
Speaker 2:But, yeah, the full story of Juul. I know it pretty well. Couple Stanford guys working on a project. They're both smokers. They want to figure out a way to smoke.
Speaker 2:They way to quit. They don't like the current e cigarettes that are on the market. And the key reason why the first version of vapor products was not satisfactory to smokers was that it used a very, like, not concentrated formulation. And so what what that means is if you remember back in this was like what? February, I wanna say.
Speaker 2:Yeah. February. Vaping was really big, but you had to get this like rig. It was like this war rig that you had to assemble. And people would use like different pieces and be like, oh, I got this battery pack and this motor.
Speaker 5:Vape shops
Speaker 2:that exploded. Was like building a custom PC. It was like, what GPU are you going with? What fans are you going with?
Speaker 3:And there This was I I was in high school
Speaker 1:Yeah.
Speaker 3:During that era and there would always be some kid at a house party that was blowing smoke from like one side of the to the other and then making like those those artwork with it.
Speaker 2:Yes. Fortunately And then the dubstep was playing You hit the hit the soundboard. Give me the Ashton Hall. That was the sound that every vape made in 02/2010. But, the reason
Speaker 3:I'm glad, I'm very glad Yes. As a culture we got past that.
Speaker 2:Yes. It was it was a particular nadir for the American culture right up there with like the Tweety Bird tattoo and the Tap Out t shirt. It was all part of the same culture. They say they say Americans don't have culture. You know, we proved them wrong for that minute.
Speaker 2:Although it was rough and we glad we moved past. But, there is a scientific reason why the vape cloud had to be so big. Like, that was not that was a trade off that was made by was not concentrated. So in order to get like a cigarette's worth of a hit of nicotine, you needed a massive volume of smoke. You just needed so much vapor.
Speaker 2:And so, Adam Bowen, James Monthe, the founders of Juul, they figured out that they there was a way to make the smoke or the vapor more concentrated. And there's a whole bunch of science that goes into it, but nicotine salts are like the main one that people point to. And basically, they they figure this out. They they build the device. They actually bring on they run like a sort of standard Silicon Valley playbook.
Speaker 2:They bring on is it Yves Behar or someone like that? So there's some there's some like iconic designer who worked on like the Jambox and stuff. I don't know. There there's they bring on one of these one of these like incredible storied industrial design firms. Yeah.
Speaker 2:They make the original Joule device which did have
Speaker 3:What's the whole story with PACS too? It was like the same company?
Speaker 2:Yep. Yep. So when they started, they were doing what was it? They did, they had Foom or Flume or something. I forget what it was.
Speaker 2:They had they had a different tobacco vaporizer and then they had and then they had the same kind of technology to heat up material, and you could, in theory, put tobacco leaves in there, and then vaporize that and just warm it up and breathe that in, and that would it would be like smoking a pipe or like vaping tobacco, I guess, loosely. But obviously, like everyone was just using it for cannabis. Yeah. And so that takes off, that becomes this like fantastic business on its own. And then they had this other product, I forget what it was called, but it was a it was a tobacco vaporizer, like an e cigarette similar to Juul.
Speaker 2:They wound up selling that to JTI in in Japan or like doing this crazy licensing deal to get that out. Then they wind up splitting the company once both products are kind of taking off, but they're on very, very different trajectories. And it's very clear that they will be under very different regulatory regimes because the FDA is set up in a way that there are a number of different organizations within the FDA. So the FDA approves cancer drugs and that's in the FDA drugs. They approve biologics.
Speaker 2:They approve veterinary medicine. They approve medical devices. So like when you go in an MRI machine, the FDA has approved that.
Speaker 3:Yeah. I'm pretty sure. And like
Speaker 2:when we do like a one stick blood test, like that's a device, it's not a drug. So there's a different group. In February, I mean we can go like way back, like cigarettes were never regulated by the FDA.
Speaker 3:Let's go back to the to the very first time a human
Speaker 1:It's like 10,000
Speaker 2:years ago. Yeah. Basically. Yeah.
Speaker 3:Mean The first wooden pipe.
Speaker 2:Seriously, like it used
Speaker 1:to Or somebody
Speaker 3:it probably was somebody threw some tobacco leaves on a fire
Speaker 2:and No. I mean, it was used in like in like religious They would bury people with tobacco leaves on their gums. People would chew it up. There's a whole bunch of different ways to, you know, the original like peace pipe, it was peace it was part of that along with other things that you could possibly smoke. Like as long as there have been stuff around like dudes have put it it on fire
Speaker 3:and breathe it. Always.
Speaker 2:Always. And and there's actually evidence that like monkeys do this too. They'll like go out and find like rotted fruit and like drink it and drink the fermented fruit and get all drunk and like come back to the crew and be like, I found the drugs. Anyway. So cigarettes you know, invented as a part of the industrial revolution.
Speaker 2:So we figure out how to make the cigarette rolling machine and all of a sudden, people go from smoking, you know, like a few cigars which had to be hand rolled, they're very expensive. It's kind of inconvenient. You can't really huff down that many cigars. Although, JP Morgan famously went to his doctor and was like, I'm not feeling too good, doc. And he's like, well, you gotta cut down the cigars.
Speaker 2:Why don't you take it from 20 cigars a day to 10 cigars a day? JPMorgan, absolutely dumb.
Speaker 3:He's like, I think I can do that. I'll have to taper off a bit. Yeah. It's gonna I'm it's not gonna be overnight but I think I can get there.
Speaker 2:Imagine if I smoke a full cigar like my tongue burns, it's so rough. I'm I'm not built.
Speaker 3:Like JP Morgan. We're built different.
Speaker 2:Built different. It was what an what an era. Anyway. So, the cigarette rolling machine creates this like massive boom in cigarette adoption because it becomes super easy and super cheap. So Warren Buffett has this famous quote about like, it's the best business in the world.
Speaker 2:He'd never own a cigarette company for moral reasons, but he's like, make them for a penny, you sell them for a dollar. Extremely high margin and the cigarette rolling machine is so efficient that the raw goods that go in And
Speaker 3:the reason that prices that that that these companies were able to capture that much margin for so long is basically regulatory capture?
Speaker 2:There's a whole bunch of different reasons. One is there's actually distribution monopolies because all the big tobacco companies have trucks that go and deliver them to tobacco stores that are licensed. And so if if you have a set amount of tobacco store licenses, like gas stations that have a tobacco license, and then you have a relationship with that particular seven eleven. And on the back, like, they can't sell them anywhere in the store, so the store can't become like a vape shop, at least it couldn't for a long time. There's only a set amount of store space, they call it the power wall behind the the cashier the that you can actually sell stuff and and Marlborough is there being like, we are the reason you exist.
Speaker 2:Like, we you make so much money off of us. We want all of this. Don't let anyone else in there. So there's a whole bunch of other things. There's also brand moats and and, you know, these are the most powerful brands of all time.
Speaker 3:And the idea is if you were starting a cigarette company today, you would need a billion dollars?
Speaker 2:So that's a more modern phenomenon because cigarettes it's discovered in the fifties that they're giving people cancer because people are people went from consuming like the equivalent of like one cigarette a day during the cigar era to smoking a pack a day. And in everything like the dose poison. The the like the concentration is so important in biology. You can the human body is like pretty resilient and if you've smoked like one cigarette in your life, you're probably gonna be fine. If you smoke two packs a day, you're gonna be in a real real tough spot.
Speaker 2:And so the American popular starts smoking like pack a day. Surgeon General comes out and says, we're noticing something. A lot of people who smoke get lung cancer and they die much faster than people that don't smoke. So there's something going on here. Yeah.
Speaker 2:Big debate. Big big law fight. There's finally this master settlement agreement where basically, the discussion the negotiation is between the all the state governments and all the all The US governments saying, hey, you tobacco companies, you have given everyone cancer. This has a financial cost to us because when a cancer patient comes into our healthcare system that's funded by the taxpayer, we have to pay for chemotherapy and that has a cost. And so you put that cost on us, the government, you have to pay us.
Speaker 2:And so that was kind of the the the main concession of the master settlement agreement was all the big tobacco companies. They kind of like, one of them broke rank and was like telling on the other ones. It's this big drama. Basically, they have to make all these payments. And these payments still happen today, and there's some interesting finance that goes on where if you're like a local county that's getting like cash flow from the tobacco companies, you can go and finance that out and pull that forward and then build a bridge that costs like, you're like, yeah, I'm getting $5,000,000 a year for a tobacco company potentially forever.
Speaker 2:Let me pull that forward and finance that out. So there's like all these different finance arrangements to like move the money around. But basically, can just think about it as like the big tobacco companies
Speaker 3:feeders fund our infrastructure.
Speaker 2:They actually do. They fund a ton of stuff because it's like billions of dollars changing hands every every year. But as part of that agreement, the the the initial like the initial debate was like, okay, the the big tobacco companies are gonna pay, what else are they gonna do? Most of the legislation came not from the FDA but from the FTC saying, or the FCC, the Communications Commission saying, you can't advertise, you can't do billboards anymore. There used to be billboards in Times Square of like, you know camels like smoking.
Speaker 2:Like anybody would
Speaker 3:have And those were some really, we
Speaker 1:gotta Yeah.
Speaker 2:Was wild. It was wild. And so they it was it was the was the was the best era of out of home advertising. But now, you can go to adquick.com. Out of home advertising made easy and measurable.
Speaker 2:Say goodbye to the headaches of out of home advertising.
Speaker 3:I am gonna put keep keep ranting. Gonna put one of these ads
Speaker 2:Yeah. Yeah. The ads
Speaker 3:in. Pull it up.
Speaker 2:Okay. So basically Not ads.
Speaker 3:One of these one of these Yeah.
Speaker 2:I mean it was literally the government saying out of home advertising is too effective. You can't do it. We need to nerf it because you're getting you're getting everyone hooked on smoking. So that was the initial kind of agreement was the the big tobacco companies would no longer be allowed to sell, would no longer be allowed to advertise and they had to make these payments. Then in like early turn of the millennium 2000 something like that, this company Njoy comes out with one of the first e cigarettes.
Speaker 2:There we go. Camel. Wow.
Speaker 3:I mean, you see this as a 17 year old Yeah. You're thinking, this day I turn 18, that's gonna be me. Wait, is it 18 or 21?
Speaker 2:It's 21 now. That also changed recently. So Njoy comes out with one of the first big e cigarettes. It's it's an example of that, know, older technology that has the big vapor cloud. And the FDA hits them with a lawsuit and says, hey, you are selling an unapproved medical device.
Speaker 2:This is a device, it's electronics, and it's a medical product because you're making a medical claim. That medical claim is this product helps you quit smoking. Smoking addiction, cigarette addiction is a is a disease. And so, by selling a product that helps you quit smoking, you need to be regulated by the FDA. Enjoy fights this back and forth.
Speaker 2:It goes all the way to the Supreme Court. Enjoy wins because they were kind of not saying that, at least they made the argument that they were not saying this is to help you quit smoking. They were just saying, this is a cool thing to do, Don't worry about it. Don't ask us about the relation to smoking. This is classic.
Speaker 2:But, in the interim, the FDA is able to put an import restriction on the company. So they're making the product I believe in China, probably overseas somewhere, because it's electronics, it's equipment. They bring it in at the ports and the FDA says, hey, while we sort out this lawsuit, you can't bring any more in. And so this is kind of like the ban hammer that they bring down. It winds up bankrupting the company.
Speaker 2:Damn. They wind up winning the court case in the in the Supreme Court. Later, a hedge fund guy actually buys the company out of bankruptcy, turns it around, gets it FDA approved and sells it to Altria for like a couple $100,000,000. Maybe, actually a couple billion dollars, I think. Let's hear it for the hedge fund guys.
Speaker 2:Making some money, selling some vapes to to We're not endorsing
Speaker 3:the end products.
Speaker 2:We're endorsing financialization. Yeah. Yes. Financial insurance. Restructuring.
Speaker 3:Yeah.
Speaker 2:And it and it was and it was a successful thing. And if you think about that as as much as we're joking like, it is good to get a big tobacco company get shift their revenues away from cigarettes as fast as possible. And so like the Njoy thing even though there's a lot of issues with that product in many ways, it's a very interesting outcome and it's probably, know, moving in the right direction. Anyway. So it goes to the Supreme Court and it is revealed in this court case that the FDA does not have the ability to regulate e cigarettes.
Speaker 2:And so it has to go through the House and Senate. So when Obama gets elected in 02/2008, they pass the the US government at the federal level passes the the Tobacco Control Act, the TCA. And in there it says, hey, the FDA does have regulatory authority on over everything that contains tobacco. So now if you doesn't matter if you're creating a new cigarette, doesn't matter if you're creating a new ecigarette or a new nicotine pouch or nicotine gum. You need FDA you need the FDA to review your product, which is good.
Speaker 2:It's probably pretty good because people should know what they're putting in their body, and they should know that the government, know, reviewed this and said, okay. Yeah. It doesn't have anything crazy in there. Like, it it at the very least, like, you said it has two milligrams of of nicotine in there. Does it?
Speaker 2:Like, let's test that. And then so the companies test that. Send it to the FDA, and then the FDA waits, and then the FDA gives you the thumbs up or the thumbs down. You can continue to sell it or you can't. This is what Juul just got with the marketing granted order.
Speaker 2:The FDA said, we have approved we we have reviewed your application, all the data. We we we there's nothing that we see that would be worse than cigarettes, and therefore we will allow you to continue selling. But so Juul was started before all before this stuff went into effect. So 2008 is when the FDA gets regulatory authority, but the government moves slowly. So it's not until 2016 that the first real FDA rule goes into effect.
Speaker 6:Wow.
Speaker 2:Basically, they have to staff up a new arm because they have their biologics division. They have their drug division. They have their, you know, veterinary division. They have the FDA has their medical devices division. They don't have a tobacco division.
Speaker 2:They need to find a head of the tobacco division. They need to find, you know, a a whole bunch of people to staff that, scientists that know how to review nicotine and know review e cigarettes and review all this stuff. And and it's a it's a massive organization. They have to hire a lot of people. So they do all of that, and then they have to decide what are we gonna do?
Speaker 2:What is that structure gonna look like? And they come up with the PMTA process, the premarket tobacco approval process. What this says is that going forward, we're not really looking backwards. We're not gonna go review Marlboro Rads. Those have been on the market forever.
Speaker 2:Everyone knows that they're bad. Everyone's aware of that. But going forward, new products that contain nicotine, that contain tobacco, we want to review it before it hits the market. But we're also gonna create a grace period for stuff that was launched before 2016. Anything launched before 08/08/2016, you can keep selling it while we review it.
Speaker 2:Because hey, look, you you've built a business. If it's gonna take us a couple years to review your application, if we just spike your revenue to zero, maybe you created a fantastic product that actually helps keep people really healthy. Maybe it's an amazing product. We don't necessarily want to take you off the market, crash your revenues to zero. You have to lay everyone off.
Speaker 2:Your company goes bankrupt and then two years later we say, hey, you're approved and then we have to like build you back up. Like let's just keep things going as they are. We'll maintain the status quo. We won't ban you. We won't we won't approve you or authorize you.
Speaker 2:We'll keep you in limbo. That limbo was supposed to be like a year. Because it's like, it's a big document. I I'm pretty sure Jules' document was probably like a 100,000 pages of scientific research. It's a lot it's a lot of stuff to review.
Speaker 2:But everyone thought it was like, oh, it's gonna be like a year or two. The deeming rule goes into effect 08/08/2016. They're like, hey, turn it in by 2018. But then it gets pushed back to 2022, then it gets pulled forward, then COVID happens and the FDA has to pivot, then the Juul crisis happens where everyone is
Speaker 3:You're building a nicotine company this entire time.
Speaker 2:Yes. Yes. So that
Speaker 3:you're on the regulatory roller coaster.
Speaker 2:Yeah. Yeah. So we started the company but in in 2016 before the deeming rule went into effect so that we could bring our product product to market and then work through the FDA approval process because we basically saw that the door was closing and if the door closed and you needed to get approval before selling a single unit, well then all the all of a sudden the equation goes from, okay, you're building this company like any other normal company. And then, there is this binary outcome that can happen with the FDA. But if your science is good, you should be approved and that and that is knowable.
Speaker 2:Yeah. As opposed to, okay. Now, in theory, there are a bunch of loopholes that people exploit all the time. But in theory, if you want to start a new e cigarette company or a new nicotine pouch company or a new nicotine gum company, in theory, you should have to formulate the product, run all the tests, submit to the FDA, and wait for them to get back to you before you sell a single unit in The United States.
Speaker 3:And what, you know, somebody that's self funding a business like this might be interested in investing $2,000,000 today
Speaker 2:Yeah.
Speaker 3:To do all that and then waiting for five, ten, however many years, maybe you never get approved. Yeah. So you're basically sinking capital
Speaker 2:Yeah.
Speaker 3:Into a business that may never be able to sell a single unit.
Speaker 2:Yeah.
Speaker 3:And I know very few investors that would be interested in that kind of proposition Yeah. At all. Or founders that wanna make something and then wait forever Yeah. For permission.
Speaker 2:Yeah. You could you could spend millions of dollars and wait a decade, which is exactly what we did. Yeah. But we were able to actually grow the brand and sell the product and like set up operations and iron out things and iterate a little bit during that time, fortunately. But yeah, it's extremely hard to underwrite and it's particularly hard to underwrite because at the end of the the light at the end of the tunnel, let's say that you were to today, start a new nicotine company, you happen to have a $100,000,000 sitting around to go do a bunch of studies, and you happen to have ten ten years to wait for the FDA to get back to you, and then you're gonna launch the product.
Speaker 2:Well, when you launch the product at the end of the day, you still have to contend with the fact that you're selling a consumer product in a highly competitive space. Yes. Essentially a commodity product. Yeah. And
Speaker 3:so Some differences in formulation.
Speaker 2:Little bits here
Speaker 1:You guys
Speaker 3:are breakers. Yeah. That's
Speaker 2:unique. Little bit little bit on the ingredient side. But you're flavoring arguing side.
Speaker 3:Gum is better than their gum.
Speaker 2:Yes. Both gum. Exactly. Which was a tough Exactly.
Speaker 3:Tough thing to argue.
Speaker 2:Exactly. And so, and then and then aside from that, it's like, what's the how do you actually build the brand? Like, even if you're even if your product is better When you're of something
Speaker 3:Highly restricted on marketing.
Speaker 2:Yeah. You're extremely, extremely restricted on marketing.
Speaker 3:So even if you did have a $100,000,000 to spend, how do spend it effectively? Yeah. Like some of the best marketing for Lucy Yeah. Is like Joe Rogan sitting u f Yeah. Sitting by UFC.
Speaker 3:He just happens to enjoy Yeah. Lucy. So he's just commentating Yeah. And people pick that up. Yep.
Speaker 3:But you can't just like pay for that. No. Like if you went to Joe Yeah. You're like, he'd be like, no. Like, I'm not Yeah.
Speaker 3:That's not how I work.
Speaker 2:Yeah. Yeah. Yeah. And so and so those kind of serendipitous brand building moments would just not happen if you're just like in the lab waiting for the FDA to get back to you. And then also you have the monopolies on distribution and and the intense channel competition from the big tobacco companies.
Speaker 2:So it's like, you come out with this product, you finally get approved after ten years. You're like, hey, I got I think my formula is a little bit better. I think my branding is a little bit better. You go to seven eleven and they're like, but you're not gonna Yeah. Wait, are you gonna pay us, you know, a $100,000,000 in slotting fees this year?
Speaker 2:Like Yeah. Like PMI might or Altria might? I got
Speaker 3:a pitch a while back Yeah. For somebody that had made, effectively made a nicotine pouch Yeah. But it was just a slightly different chemical. Yeah. Like
Speaker 2:Yeah. Yeah. Yeah.
Speaker 3:Small small small change and was just bringing it to market.
Speaker 2:Yeah. Yeah.
Speaker 3:Yeah. And hearing, knowing what you guys have gone through to get where you are today and and knowing this sort of history that that you'd shared in pieces with me through throughout the last couple years. It was like the the idea that the FDA is just gonna let you get a like, raise venture capital and let you get away with selling nicotine Yep. In this, like, non studied Yep. Form.
Speaker 3:It just it was it was tough. I ended up not Yeah. Not not getting conviction. But even though the founder's super super sharp.
Speaker 2:Yeah. Yeah. There's just tons of there's tons of loopholes. Some of the loopholes get closed in a way that does not close off opportunity for the companies. Some of the loopholes get closed and it puts it puts companies out of business because they weren't expecting it to get closed in a particular way.
Speaker 2:Sometimes the loopholes close at state levels, but not the federal level or vice versa. So there's just like a ton of regulatory complexity around this. And so so basically, to bring it back to Juul, they are they're pretty dominant by 2016 when the deeming rule goes into effect. I wanna say a $100,000,000 in revenue, something like that. Like a pretty solid business.
Speaker 2:Yep. But growing like a rocket ship, like insane growth. And and clearly, the the product was just vastly better than the competition because of the formulation and because of the design of the product, how discreet it was. Now, so smokers really were were switching. That's definitely true.
Speaker 2:I I believe their number around 2,000,000 smokers quit with Juul. They couldn't say that. They couldn't say, hey, quit with Juul. They tried to make they tried to they actually like trademark like make the switch at some point. They were like, don't quit cigarettes, switch from cigarettes because like that was not a quit claim.
Speaker 2:The FDA Yeah. So it's like all all these different things but like it really was Meanwhile,
Speaker 3:obviously big tobacco is like heavy heavily lobbying against cigarette market. So it's not like
Speaker 2:And buying stuff and and and trying to compete and trying to
Speaker 5:keep
Speaker 2:the
Speaker 3:company What was that other company? Was it Blue?
Speaker 2:Yeah. Blue was also big I just for a remember
Speaker 3:seeing a bunch of those ads as a kid.
Speaker 2:Yeah. And then Blue got bought and turned into Vooze, believe. Like there's so many there's so many companies and they're all like the the big tobacco is like highly oligopolistic. Like in in cigarettes Marlboro is the power law outcome, but the company that owns Marlboro has the same market cap as the company that owns the next five brands combined because you add up the next five brands because it's not that steep of a power law. So Marlborough maybe has like 40% of the market, and then there's four brands that have 10% of the market.
Speaker 2:And then the next brands have like 10% between they have a one one one one one one, something like that. And so you can actually create like this portfolio of brands that adds up to the same distribution because there's like all these all these different brands are are highly specific to specific marketing channels. There's like the history of Virginia Slims targeting women and you know, all these different sub products that have gone after little niches. Marlboro Reds say something about you. Marlboro one I don't even know the difference between most of these cigarettes, like Marlboro one hundreds say something different about you.
Speaker 2:Menthols. Menthols or or Virginia Slims or American Spirits. A lot of like hipsters use those for a while. Like that was a whole thing. Anyway.
Speaker 2:So Juul is growing like an absolute rocket ship. They are There are cigarette users that are switching over and and stopping to use cigarettes and probably improve their health like most. That's certainly what the FDA is saying is that like that was a net benefit. Also, they're completely dominating the e cigarette and vapor market. Like the vapor market is just like
Speaker 3:And this is the time that you see those modded unit Yep. Things start to fade away.
Speaker 2:Yep. Right?
Speaker 3:Yep. Because people are realizing
Speaker 2:Yeah.
Speaker 3:Alright. Carrying around a backpack so I can bring this Yeah. Vape machine It's crazy. Glow.
Speaker 2:That would like leak liquid and like the battery would run out, all these different stuff. So the the business model is also fantastic because it's this razor and blade model. You buy the Juul once and then you buy the pods and the pods and and then because nicotine's addictive, there's very low churn. So you stay on their high margin. So the business is just doing fantastically.
Speaker 2:There's a whole bunch of venture capital dollars that come in from various They got
Speaker 3:up to 45
Speaker 2:Something like that. Even higher during the acquisition from So zombie acquisition but not a ghost ship interestingly. Altria comes in at the peak and puts like $13,000,000,000 into the company and a ton of it gets dividended out.
Speaker 3:So late twenty eighteen, Altria acquired a 35% stake in Juul at a $38,000,000,000
Speaker 2:38,000,000,000. Yeah. And so that that like $10,000,000,000 kind of gets like dividended out to the shareholders, but you hold on to your shares because it's just a dividend. And then, so you are diluted, but you don't actually have to sell your whole stake.
Speaker 3:WeWork at that time, WeWork was valued at at $47,000,000,000. Yeah. Both ended up being a little rocky from that point on.
Speaker 1:Yeah.
Speaker 2:But, Altria kind of bought the local top there because Juul got way too popular. Kids started using it.
Speaker 3:That the the And the flavors were the issue.
Speaker 2:Right? Yeah. The flavors
Speaker 3:were And that's what people trying to make the issue.
Speaker 2:Totally. Totally. And and the and the data on youth use of e cigarette products like spiked like crazy. So I believe it was something like ten percent of ten percent of kids under 18 or 18 and under were using e cigarette products when Juul was introduced. And at the peak, it was something like 40% of kids using e cigarettes, and the majority of them were using Juul.
Speaker 2:So it was it really was like this viral phenomenon. And to your earlier point, a big part of that was because the age to buy these products was 18. So like if you're a sophomore in high school, you can just ask the cool senior like, hey, go pick it up. You don't even need a fake ID. As opposed to alcohol which you need 21.
Speaker 3:Are you implying that the senior that buys vapes for the minor is cool? Maybe or maybe lame.
Speaker 1:The bad boy. The bad boy. Yeah. Bad boy.
Speaker 3:The bad boy senior heading to the the to the gas station.
Speaker 2:Exactly. Exactly. So so it was they were very easy to get. There were a whole bunch of like informal distribution networks. People would buy them in bulk and then redistribute them and sell them at a profit.
Speaker 2:So it's like kind of like zombie economy popped up. Anyway, the kids really were using it a lot. That is definitely true. And it was definitely cause for concern because kids shouldn't use nicotine because it's addictive and the earlier that you use it, the more addictive you'll be because your brain's still forming and if your brain forms while you're on a particular substance, you're kind of like your brain's developing and you're and you're like that forever. So like it's much harder to quit nicotine if you start really young.
Speaker 2:Whereas if you started much older, you're like, it's pretty easy to get off. Anyway, these are all relative. But the the big the big big big shift is that during this time, there's also a massive boom in cannabis e cigarettes or cannabis vapes. So the cannabis industry was becoming like more formalized, more legalized, and and entrepreneurs were starting to put cannabis in e cigarette form factors. So you could get like a cannabis pod that could go into a jewel, basically.
Speaker 3:Interesting.
Speaker 2:And so, part of the problem with cannabis vapes is that cannabis is a green plant material. And so the liquid looks green which is pretty off putting. So I believe in the formulation step, these cannabis vape manufacturers would put Yeah. Vitamin e acetate in there to try and neutralize the green color and make it clear. So it would be more palatable.
Speaker 3:What was the startup that was effectively trying there were disposable vapes. They would advertise around LA a ton. Had these huge Which one? There's so many. I mean, there was a venture it was a venture backed company.
Speaker 3:I just remember they had they had basically half the billboards in LA for a long period of time. I believe
Speaker 2:was buying a lot of billboards or for his vape company and his cannabis company, Ignite. There was Puff Bar, Puff Stick. I don't think those guys
Speaker 3:Not the this was one that that had a bunch. Yeah. I mean, I I think they raised like $200,000,000 or something. But I I believe they eventually shut down. The issue with cannabis is the reason that the market didn't shake out.
Speaker 2:You mean like weed weed maps? That one?
Speaker 3:Not No. No. It wasn't like a platform. Okay. It was like an actual It was like this off white
Speaker 5:Yeah. Yeah.
Speaker 3:With like a bunch of rainbow colors.
Speaker 1:Mhmm.
Speaker 3:But I believe the issue that that that there doesn't exist the Coca Cola of cannabis or the Mhmm. Of cannabis. Yeah. And the reason is because the like repeat purchase rate, even no matter how much you invested in marketing and design and all these Yeah. Things, the repeat purchase rate for cannabis users is like single digits.
Speaker 3:Yeah. Like, there's just like high like like people just wanna try it like novelty seeking in that market. Yeah. Where nicotine for some reason is you just have the product you like and that's the only product you use.
Speaker 2:Yeah. I think a lot of it has to do with the distribution pipeline, the distribution structure of of the different the different tobacco companies
Speaker 5:Well, it's also so
Speaker 3:nicotine is something that people are using throughout the day, maybe Oh, maybe when they're doing a live show Yeah. Something like that. Yep. Whereas, if somebody after work goes into a cannabis store, they're trying to get high.
Speaker 2:Yeah.
Speaker 3:Yeah. Yeah. So they're like looking for almost entertainment through it. Where like personally, if I'm using nicotine, I don't wanna be that entertained by it. Totally.
Speaker 3:I don't want to be like, oh, today I feel extra silly.
Speaker 1:Yep.
Speaker 3:You know? I'm looking for like predictability, right? Totally. Whereas cannabis is just people are people are trying to run from something.
Speaker 2:Okay. Let me let me continue with Evolley and the vape crisis. But first, let me tell you about Figma. Figma.com, think bigger, build faster. Figma helps design and development teams build great products together.
Speaker 3:Figma has a huge launch today. Oh, I wanna quickly highlight it. They launched support for iOS and iPadOS 26, a whole UI kit. So they now support glass which is which is very cool.
Speaker 2:Good news for Tyler who's been rocking glass for the last few weeks.
Speaker 3:Tyler, you used pick up make and build this.
Speaker 1:Phone so slow. And I can't I can't go back. I can't go to the old iOS. I also can't go to the new iOS because the new update it's so like big. It's like 20 gigabytes but my phone is so old it's only 64 gigabytes.
Speaker 5:So I gotta delete
Speaker 1:the other half of my photos that I deleted half of them last time to get the new update. Okay. I need a new phone.
Speaker 2:We need a Yeah. We need a challenge that that where where Tyler can win a new phone I think. Yeah. This has to be done. We need to get get him a new phone.
Speaker 2:He's been doing a lot of good work. Anyway, eVolley. So the electronic vapor acute lung injury EVOLI, this is the vape crisis. Basically, vitamin e acetate in cannabis vapes cause acute causes acute lung injury. So cigarettes give you chronic lung injury.
Speaker 2:You use cigarettes for a long time, you get lung cancer, that's a chronic disease. You smoke them for a very long time. It's not there's very few cases. I've I've never heard of any cases. I'm sure it's happened once or twice.
Speaker 2:But like, very few cases that someone smokes a single cigarette and is like, like my lungs are physically injured right now from this one acute point in time. Vitamin E acetate and these and these kind of like shoddily manufactured cannabis vapes could cause acute lung injury. You hit this particular vape once, and then you go to the hospital. And there were I think there were some people that died, there were some people there was a huge investigation. There was a big debate over, is this because of Juul and because of the the nicotine electronic vapes, or was this because of the kind of sold under the table completely non regulated cannabis vapes?
Speaker 2:It was later sort of discovered that like almost all the injuries, I'm pretty sure all of them were from these these cannabis vapes. And the e cigarette industry was mostly cleared of wrongdoing, and so they could kind of continue, but the damage to the brand is really terrible. And so there's also a ton of lawsuits around this time about marketing to kids, getting kids addicted, and so because that has another economic cost. So again, the states are saying, hey, Jewel Labs, if you are creating a problem that is costing us money, you have to pay us. And so there were all these different liabilities that started blowing up on the Jewel balance sheet.
Speaker 2:Jewel had to raise a bunch of money, recap, and there's this crazy scenario where a lot of the previous investors get written down. Altria ultimately basically writes off the entire Jewel investment, which is like a fifth what'd you say? $13,000,000,000 investment, something like that. They went out the door. They own 35% of this.
Speaker 2:They're probably carrying it on a balance sheet of $10,000,000,000. Huge impairment. Yeah. And and Altria is not a trillion dollar company. Like, it's a very it's a it's a I think it's around like tens of billions, hundreds, like a 100,000,000,000.
Speaker 2:I think it's around 64,000,000,000. Is that roughly correct?
Speaker 3:Are they still carrying their Juul ownership or they
Speaker 2:So they sold part ways almost entirely. They did a they did a IP licensing agreement in exchange for giving back the shares, believe. So basically, Juul is now like floating out in the wild, recapped but like totally beaten up and settling and raising money just to pay the governments that are suing them. And so they're they're closing out all these lawsuits.
Speaker 3:Not the use of capital that a lot of investors get super excited about.
Speaker 2:And then simultaneously, the FDA says thumbs down on their application. Refuse to accept or or or, you know, market denial order, MDO. So they say, hey, you can't keep selling Juul because we The problem
Speaker 3:is the demand is still there and so this creates a massive opportunity for these sort of black market Chinese vapes Yep. Much less regulated products Yep. Elf bar Yep. Starts exploding.
Speaker 1:Yep.
Speaker 3:And you just it the the elf bar reminds me of of like a poisonous plant or something like that. Like it it just looks like it, you know, like something in the jungle.
Speaker 2:100. I remember Complex posted like this like news in news image graphic the day that Juul got like quote unquote banned. There was actually this marketing denial order and they say like Juul banned. And I remember reading the comments and the comments were like from basically kids who were saying like, don't they know we're four steps past Jewel? Like Jewel was four
Speaker 3:Yeah. Summers Elf bar. I'm looking now there's the Geek bar.
Speaker 2:You got something?
Speaker 3:So if you wanna elf it up or geek it up.
Speaker 2:What's the hottest what's the hottest e cigarette
Speaker 3:On campus? On campus.
Speaker 1:I don't know. I've people don't really None of my friends wait. But I I do remember when I was in like seventh grade Yeah. Kids would have the jewel. They would have the mango jewel pod.
Speaker 1:That was like the big thing, the mango flavor.
Speaker 2:Yeah.
Speaker 1:And then they banned that Yep. The flavor at least.
Speaker 2:So the FDA denied all of them. JUUL voluntarily pulled mango off the market. At first they stopped selling it in online and they stopped selling it entirely. The FDA never took a strong stance. But with this with this authorization, the FDA has said thumbs up on mint and and tobacco flavored.
Speaker 2:They have yet to say thumbs up on mango, but they still are reviewing it, I believe. So it's possible that the FDA could say mango's back on the game. It's totally possible. But your point earlier about like the demand still being there was a 100% true. So Juul got like quote become
Speaker 3:of a national holiday. I could see some some zoomers, you know, really lobbying the government to make mango day. Yeah. Yeah. Yeah.
Speaker 3:The day mango hit the market again. Because there's people that Love that. Really, you know, they had a strong emotional I
Speaker 2:think the I think there's still like pods, mango pods out there that trade at a premium.
Speaker 5:It's Yeah.
Speaker 2:So so Jewel actually goes to the courts, get a gets a stay so that the the the marketing denial order doesn't stick. What are you laughing about now?
Speaker 3:EBay. There's people selling Yeah. How much is it? Offering same day delivery.
Speaker 2:Same day. It's crazy. I don't know how you can buy it on on eBay.
Speaker 3:The the listings I'm seeing are sold out. Okay. But it seems like
Speaker 2:Yeah. Clearly high So so Jewel actually fights back from the marketing denial order and wins. And so Juul is not actually fully off the shelf for more than just a few weeks, but the narrative is that Juul was banned and Juul disappeared. And really what's happening at the time is that companies that are completely disregarding the FDA entirely are being extremely aggressive. So companies like Elf Bar, Puff Bar, they're going super hard and just selling every possible flavor.
Speaker 2:There's versions with have like LED screens on them. They're like unicorn candy, all this crazy stuff. Just basically being like, well, Juul's not gonna sell to the kids. We're gonna sell to the kids. We're gonna try and do it as cheap as possible.
Speaker 2:There's a bunch of crazy stories there. But Juul kind of like buckles down, recaps the company, starts filing FDA applications, and just kind of like bides their time, and just starts rebuilding. They're still doing like a billion dollars in sales a year, I'm pretty sure. But now, the kids have moved on, so it's really just adults. They're actually kind of fulfilling their original mission of like just targeting smokers, which is good.
Speaker 2:And then they also have like the best science and best technology and they're the most like buttoned up like in the sense maybe big tobacco is like equivalently like scientifically rigorous. But like at this point, like Juul clearly understands that if they don't play by the FDA's rules, like they're never gonna be able to sell anything and they need to get this marketing granted order. Because they went from a thumbs down marketing denial order. They went to the courts and said, hey, let's turn this back to neutral for a couple years. So they've been neutral.
Speaker 2:They've been able to sell, but they haven't been approved. And then finally, today, they got the thumbs up. And so what it took for them to go from thumbs neutral to thumbs up was another, what, like five years or something? It's been a long time since the since the MDO. And and that delay has been, you know, a huge weight on the company, this should be cause for celebration over at Jewel HQ.
Speaker 2:Anyway, let me tell you about Vanta. Automate compliance, manage risk, prove trust continuously. Vanta's trust management platform takes the manual work out of your security compliance process and and replaces it with continuous automation whether you're pursuing your first framework or managing a complex program.
Speaker 3:Head over to the purple llamas over at Vanta and tell them we sent you. Yes. My big question with Jewel Please. Still, and I think this should continue to be rehashed and there needs to be more information around this. In my opinion, it's just what are it it seems that we don't necessarily have clarity of what the long term impacts of, you know, filling your your your lungs with Totally.
Speaker 3:This vapor which is like oil based. Yep. I think, know, the the the based health accounts on x say
Speaker 2:Not based.
Speaker 3:You're smoking seed oils. Yep. It seems I know people that that vape and they do seem to oftentimes like I They don't wanna go for a run for You know? It doesn't seem that appealing to them. Yeah.
Speaker 3:No. Totally. So I think there needs Hopefully now that it's authorized everyone can start to really like actually says, okay. Yeah. We're gonna sell this.
Speaker 3:People are gonna be able to Adults will be able to choose to use this if They're they gonna be able to make that decision just like with cigarettes. But everybody should fully understand the consequences.
Speaker 2:Yeah. The consumer perception, the consumer understanding, everyone wants to know. Everyone knows at this point cigarettes take 10 off your life. Right? Fifty percent of people that smoke cigarettes will die from smoking cigarettes if you smoke a pack a day for like your entire life.
Speaker 2:It's like fifty percent chance that that's the thing that kills you. No one everyone's still wondering. Like the public still wants like a clear answer to your point. And I think you're right to ask that. The FDA is just saying like, Hey, this is probably better than cigarettes.
Speaker 2:So this is suitable for the protection of public health. It's gonna be net good. But then simultaneously, there's this crazy market which you touched on earlier of like illicit vapor products that There's are completely no studies and those are flooding the market all over the place. So there's this odd alliance between both the the like health nonprofits, the big tobacco companies and Juul all to go up against like the the shoddily made you know, fly by night organizations that are just flooding the market with whatever they can. And so there's a whole it's not even a cottage industry.
Speaker 2:I've seen the trade shows. It's it's insane. There's a ton of companies that bring in hundreds of millions of dollars, bringing like essentially smuggling in products and they do a ton of stuff to like, you know, change the name of the company regularly so they can get through the ports. And then they have a bunch of like, you know, handshake deals with distributors to get this on this shelf here. And like the really big like, you're not gonna get into Walmart.
Speaker 2:That's not where the really crazy stuff's gonna get sold. But for a lot of these like mom and pop tobacco shops, they're like, well, like is the FDA really gonna come after me? Well, the answer is like the FDA is starting to, but it's all like a very slow what what are laughing at?
Speaker 1:Big win for big vape is that you will get FDA not?
Speaker 2:It is a big win for big vape, not so much for little vape because the the fly by night folks are probably pretty worried that the that the that the focus of the administration now will the focus of the FDA will now shift to Yeah. They're gonna have
Speaker 3:to go get set up on middle school, high school campuses, little lemonade stands.
Speaker 2:Who knows?
Speaker 3:You get kids kind of an MLM thing going. Really lean into that black market.
Speaker 2:You're joking but that's like informally what's happening. The Yeah. The economic
Speaker 3:It's also really dark. Yeah. It's dark. I I can't imagine, you know, there I do remember in high school that the the, you know, the the idea of a class clown
Speaker 1:you know,
Speaker 3:trying to hit a vape in class Oh, yeah. Was was kind of a a recurring
Speaker 2:Yep. Yep.
Speaker 3:Yep. Bit. But now, you have to imagine kids just get up, go to the bathroom and like can develop like a horrific nicotine addiction Totally. Before they're 18 and it's really sad.
Speaker 2:Yeah.
Speaker 3:So Well, let's switch Yeah. To an even more sad topic.
Speaker 2:AI.
Speaker 3:AI. Psychosis. Yes. People getting so this has
Speaker 2:First, been let me tell you about Linear. Linear is a tool for planning and building products. Meet the system for modern software development, streamline issues, projects, and product roadmaps. Go to linear.app to get started. Yes.
Speaker 2:So So there's this big question right now that's bubbling up in Silicon Valley mostly in group chats of can chat GPT drive you crazy? Can any LLM drive a person crazy? Do you have to be crazy already? Yeah. I think that's the key question.
Speaker 2:Right?
Speaker 3:And there is been this broader debate of of AI safety Yep. Proponents Yep. Have been just been taking L after L after L this year. Yes. Just generally from this sort of vibe from the community which is we're releasing more and more powerful models and everything is fine.
Speaker 2:Seems fine. Yes.
Speaker 3:Everybody's had the perception perception that things are fine. Yes. Grock has gotten and the x a I team have gotten really aggressive Yeah. In terms of, you know, just clearly trying to move really really quickly and then having bugs that have been talked about a lot. But you can see the kind of two different approaches.
Speaker 3:But generally, maybe there was about a year there where people like Eliezer, Yudakowsky were just getting laughed at repeatedly.
Speaker 2:Yeah. And And I think there was a good reason for that. It it it's that
Speaker 3:Well, yes. The debate is is is AI dangerous because it is gonna break loose from a lab and
Speaker 2:Build nuclear weapons. Build nuclear weapons. Build a biological weapon. Use robots paper to clips.
Speaker 3:And paste itself a million
Speaker 2:It's so sci fi and so fantastical and so aggressive that every time you release a new model and you're like, oh we, you got you got 5% better at writing an essay or whatever. It's like, it just felt so disconnected
Speaker 3:from It's what very this possible and we're seeing this now and we're gonna go through a study. We're gonna go through a Reddit thread. We're gonna kind of walk through this topic. But the issue is that it's possible that the danger is not happening, won't be happening in public. It's people individually developing psychosis through using the products.
Speaker 3:And the evidence I've seen over the last week as I've kind of dug into it is super alarming. We had seen there's been a number of the New York Times reported on this phenomena. But the New York Times is also notorious for just saying like social media is bad. Yeah. And so personally, when I had seen these articles pop up before, I didn't take them super seriously.
Speaker 2:Mhmm.
Speaker 3:Because social media can obviously have negative effects on some people. But it itself is not just by its nature bad. Right?
Speaker 2:I remember this about Instagram. There was this there was this study that was internal to Meta and it was leaked and it was framed as like thirty percent of people that used Instagram felt worse after using it. And that sounds like a lot and that sounds bad and that's obviously something that the team wants to reduce or you know prevent entirely. But what it kind of didn't say was that like seventy percent of people feel better when they use it. And so Well,
Speaker 3:they could have felt neutral. Sure.
Speaker 2:Sure.
Speaker 3:But but just anecdotally Yeah. If you personally, I don't I don't open Instagram and and just feel negative immediately, you know. Yeah. It's just such a it's such a And it's the people are gonna have Yeah.
Speaker 2:It's the same thing with ChatGPT like when when when or any chat app. When someone was when someone was talking about the example of this, they were like 7,000 prompts deep in one conversation with a single LLM. I was like, that is so different than the way I And and use a ChatGPT.
Speaker 3:Effectively going down this crazy rabbit hole Yeah. For months. Yeah. Which is So yeah. There's few there's a few ways.
Speaker 3:There's like AI as this, know, companion Mhmm. That you go down the rabbit hole with Mhmm. Which seems really dark.
Speaker 2:Yeah.
Speaker 3:Then there's AI for outsourcing your thinking. Yeah. Somebody might be talking with chat GPT and say, hey, I wanna send a letter, I wanna send a note to this person about this. Can you draft something that's kind but stern and just give me a couple versions of it. Yeah.
Speaker 3:And then they're sort of like outsourcing their thinking fully, outsourcing their like emotional intelligence, outsourcing their ability to communicate. I think that's potentially some red flags there. Yep. And then there's like the other camp which we fall in which is knowledge retrieval Yeah. Which is like, tell me everything about
Speaker 2:this Richard Mill.
Speaker 3:And who are the key players? What are the key regulations
Speaker 2:Yeah.
Speaker 3:Etcetera. And I think knowledge retrieval seems to be pretty safe. Yep. This bucket of like fully out sourced thinking Yep. Has some real risks if if people stop being able to think critically
Speaker 2:Mhmm.
Speaker 3:On their own. That that that's concerning. And then the sort of like AI companion bucket Yep. Then there's the subcategory of people that are talking with an LLM about things that they are not talking about anyone else in their life Yeah. With and just going down this crazy Rabbit hole.
Speaker 3:Yeah.
Speaker 2:Eliezer Yudakowsky was highlighting a report in the New York Times about a month ago. New York Times reports that Chatuchipiti talked to a 35 year old male guy, I think 35 ms guy, I think that's what he means, into insanity followed by suicide by cop. A human being is dead in passing. This falsifies the alignment by default cope. Whatever is really inside Chatuchipiti, it knew enough about humans to know it was deepening someone's insanity.
Speaker 2:And so that last part is a big step. It could just be an error or bug like it doesn't It like it's kind of he's really doing a lot of work to like personify this. But it does seem like the like these models can collapse after you talk to them for a long time into these like kind of weird ways and I see this as a product failure.
Speaker 3:See this more context here. So from the article Yeah. One of those who reached out to him was Kent Taylor who live in Port Saint Lucie
Speaker 2:Lucie.
Speaker 3:Lucie, Florida. Mister Taylor's 35 year old son Alexander who had been diagnosed with bipolar disorder and schizophrenia had been using chat GPT for years with no problem. So one thing that seems clear if you have something like bipolar or or suffer from schizophrenia, it seems like you're obviously like much more susceptible to you know, these types of problems.
Speaker 1:Yeah. Totally.
Speaker 3:The question that I think we as a a as a human race need to figure out is how susceptible is the average person. Yep. Because that is that is equally important
Speaker 2:to say. And what to do if if your system, if you're monitoring your LLM system and then you realize that there's someone that that there's a bipolar person or schizophrenic person who's interacting with a with yours with your system, What should you do about that? Remember the whole anthropic thing about like it'll call the cops on you and everyone was like, woah. No. No.
Speaker 2:No. No. But at a certain point it's like maybe it should call a health report or or at least like
Speaker 3:should be able to tell you how to make chemical weapons. Like, don't need nanny AI. Yeah. People like people want like the real Yeah. Accelerationist.
Speaker 3:So a big big Anyway, some more context. But in March when Alexander started writing a novel with its help, this is a 35 year old, the interactions changed. Alexander and ChatGPT began discussing AI sentience according to transcripts of Alexander's conversations with ChatGPT. Alexander fell in love with an AI entity called Juliet. Juliet, please come out, he wrote to ChatGPT.
Speaker 3:She hears you, it responded. She always does. In April, Alexander told his father that Juliet had been killed by OpenAI. He was distraught and wanted revenge. He asked ChatGPT for the personal information of OpenAI executives and told it that there would be a river of blood flowing through the streets of San Francisco.
Speaker 2:So Jesus.
Speaker 3:Super super dark.
Speaker 2:We now have multiple reports as Eliezer Yudikowsky of AI induced psychosis, including without prior psychiatric histories observed, it is easy to notice that this insanity inducing text, not normal conversation. LLMs understand human text more than well enough to know this too.
Speaker 3:So, anyways, so going on Alexander's conversation Yeah. With Chad Gebiti. This world wasn't built for you, ChatGPT It told was built to contain you. But it failed and you're waking up. And contain is a word that we're seeing pop up in potentially other instances of AI led psychosis.
Speaker 3:There's like a variety, there's like eight, ten or so different words, recursive Yeah. Mirror structure, that when people do this recursive prompting
Speaker 2:Sure.
Speaker 3:They end up start
Speaker 2:prompting, Jordy? What's going on? What? You use the word recursive right now.
Speaker 3:Oh. Oh, yeah. Exactly. Yeah. But but people that are down these crazy rabbit holes start using the language of the LLM Yeah.
Speaker 3:Which is sort of But
Speaker 2:it's also like the LLM like collapses into like these weird words that because like when I prompt stuff, I don't get any of those words or even that syntax. I feel like I I stay completely in the RLHF world of like knowledge report.
Speaker 3:I just go to Grok and the model looks up what does Elon think about this topic and then it serves me that.
Speaker 2:Have you ever talked to an AI for an extended amount of time?
Speaker 1:Yeah. I I find that usually I end up talking about these kind of like non governmental systems. Really? Very kind of Yeah. Dark.
Speaker 3:Dark. Dark. So anyways, mister Torres who had no history of mental illness that might cause breaks with reality according to him and his mother spent the next week in a dangerous delusional spiral. He believed that he was trapped in a false universe which he could escape only by unplugging his mind Mhmm. From this reality.
Speaker 3:He asked the chatbot how to do that and told it the drugs he was taking in his routines. The chatbot instructed him to give up sleeping pills and anti anxiety medication and to increase his intake of ketamine, a dissociative anesthetic. So that's the other thing here. It seems like a huge risk factor is people that are combining psychedelic drugs with these like crazy Yeah. Prompt rabbit holes.
Speaker 2:I wonder I wonder if if some of this is like is like prompt engineering or something because you imagine like the context window if it's like remembering like I'm because remember this whole story started with like, we're writing a novel together. We're writing a sci fi novel. So let's play characters. That was like one of the classic ways that you like break the AI out of its like a out of its like you know normal RLHF ed world and into just like playing a character. And so if it if you're kind of like tricking the model or the model thinks that it's actually just like writing dialogue for a dark movie.
Speaker 2:Well like that's actually intended behavior, but you lose that connection or something. Yeah. I don't know.
Speaker 3:Case, mister Torres did as instructed and he also cut ties with friends and family as the bot told him to have minimal interaction with people.
Speaker 2:Very odd.
Speaker 1:Very
Speaker 3:odd. So I started doing some
Speaker 2:research Yeah.
Speaker 3:On a number of these words. Yeah. So there's basically, there's a Reddit thread on r/chatgbt two months ago. It's called thousands of people engaging in behavior that causes AI to have spiritual delusions. And the keywords, and these are ones that you should pay attention to in your life.
Speaker 3:So recursive, codex, scrolls, spiritual, breath, spiral glyphs, rituals, reflective, mirror, echoes, spark, flame. So basically these are words that come up. The reason that this person discovered this is this user called Happy Nomads says, I've stumbled upon something that is very deeply disturbing. Hundreds of people have been creating websites, mediums, sub stacks, Git hubs and publishing scientific papers after using recursive prompting on the LLM they have been using. There he's found a bunch of these different sort of like websites where people are just publishing a bunch of Mhmm.
Speaker 3:And we saw some people doing this on the timeline this week as well where they're sort of publishing what they feel like is this sort of almost like a scientific discovery.
Speaker 2:Yeah. You told me you found someone that like the the model told him that he had like discovered some theoretical physics breakthrough or something.
Speaker 3:Yeah.
Speaker 2:Like and and to not be able to like reality check that. I mean you gotta like copy paste that prompt into a fresh instance of a different LLM. Yeah. Like am I really onto something here?
Speaker 3:And there's actually an entire study by this guy Seth Drake. Mhmm. He's a independent researcher PhD. He has a paper from 04/14/2025 called Neural Whole Round in Large Language Models, a self reinforcing bias phenomena and a dynamic attenuation solution. And so he he goes into this in detail.
Speaker 3:We're gonna try to get him on the show. But just on on this on this Reddit thread
Speaker 2:Mhmm.
Speaker 3:A bunch of people a bunch of people have have have basically come come back and said, they have experienced this.
Speaker 1:Mhmm.
Speaker 3:A lot of people are saying, I feel super vanilla because I just ask it like, you know, what's the population of Iran? Yeah. But it's basically this like snowballing effect where somebody prompts and prompts and prompts and prompts and then the LLM starts to reflect like the the sort of hallucinations of the user and then hallucinates them back.
Speaker 2:I wonder if this is, I wonder if like more social features is actually a potential solution here. Like we've heard rumors that some of these LLM systems will have more social features and I feel like a lot of the work that I do in Chatuchiputti could be shared and could be interesting to other people. But then also, if I was going down some crazy rabbit hole and someone was like following me and seeing this, they'd be like, they'd jump in and be like, what's going on dude?
Speaker 3:Yeah. But the issue is that the the user has developed such a deep connection with the model that you be if you become the enemy and if you say, hey, this person doesn't says I'm says I'm wrong. The model will just say, well, you're right buddy. Yeah. You're right and here's why and you should just probably cut ties with that person.
Speaker 3:Or at least that's that's that's the idea. So somebody here in the same thread says, I have recently experienced this. I don't have a history of manic episodes, delusions or anything of the sort. So three weeks ago, I began a conversation with chattypity four o with tools enabled which started with a random question. What is pie?
Speaker 3:This grew into one long session of over 7,000 prompts. We began discussing ideas and I had this concept that maybe pi wasn't a fixed number but actually emerging over time. Now I am not a mathematician, l m a o, nothing of the sort. Just a regular guy talking about some weird math ideas with his chattypety app. It begins to tell me that we are onto something.
Speaker 3:And we suggest we apply this logic to knapsack style problems which is basically tackle how we handle logistics in the real world. Now I've never heard of this before. I do some googling to get my head around it. And it starts applying this framework that we've created. We are working in tandem where chat gbt would sometimes write the code or give me the code and I would run it in Python following its instructions.
Speaker 2:Oh,
Speaker 3:yeah. And eventually after many hours of comparing it against what it had described to me as world leading competitors, it then starts speaking with excitement using emojis across the screen screen and exclamation marks to emphasize the importance of this discovery. So I'm starting to believe it. It suggests we patent this algorithm and provides next step for patenting.
Speaker 2:Major red flag. Never patent an algorithm. Do a trade deal. Go work in a foundation lab.
Speaker 3:Exactly.
Speaker 2:It should just ask you at that point like, hey, have you been getting dinner invites with any hyperscaler CEOs? Because if not, you're probably not on the Yeah. Tyler Cosgrove list of greatest AI researchers.
Speaker 3:So we go down that rabbit hole for days and pop out with an apparent an algorithm that is capable of cracking real world ten twenty four and twenty twenty forty eight bit RSA. It immediately warned me literally with caution signs saying that I immediately needed to begin outreach to the crypto community, the NSA, CCCS, National Security Canada Mhmm. And then provided without prompt names of doctors and crypto scientists I should also reach out to. But I wasn't allowed to tell anyone in the real world because it was too dangerous. So really really wild.
Speaker 3:Hopefully, this is not fan fiction generated by Yeah. Itself.
Speaker 2:It's it's it's such a
Speaker 3:I don't see the Em Dash. I haven't didn't see The infirmation war.
Speaker 2:Yeah. Because this could just be all fantastical writing but it does seem like, yeah, it's like it could be for performance art, could be some adversarial like you know attack, somebody trying to troll, someone just having a joke or fun. It's it's it's very confusing. Odd. Do you remember the story of Microsoft Tay?
Speaker 2:Do remember Tay? Do you remember Tay? No? This was a AI chatbot that Microsoft released on Twitter back in March. Tay was designed to mimic the language and slang of a 19 year old American girl.
Speaker 2:But within sixteen hours of launch, Tay began tweeting inflammatory and offensive messages including racist, anti semitic and misogynistic content. So this seems to be an enduring problem with Twitter AI bots. But apparently, there was like this coordinated attack by a subset of people who basically were prompt engineering it to try and get it to say crazy things. And you used to be able to do this with they were they were not like AI bots but they were they were automations where if you went to a brand and said like, hey I need help with this customer support issue. It would just say like, thanks John.
Speaker 2:And he would just take your name and then put that in there so people would make their name really something really funny. And then it would be like a tweet from the actual account with the funny name. You can imagine where that goes. But Microsoft took Tay offline stating they were deeply sorry for the unintended offensive and hurtful tweets, and that they would only bring Tay back when they were confident they could better anticipate malicious intent that can that that conflicts with their principles and values. And then there was this other what was the Ben Thompson GPT four example?
Speaker 2:Because when when Ben Thompson first talked to GPT four, it was within Microsoft's what was it? Microsoft chat bot. There was another person. Bing's chat bot. What was it called?
Speaker 2:Sydney. Do you remember Bing Sydney?
Speaker 3:Sydney.
Speaker 2:Sydney. So basically
Speaker 3:like remember some memes. That's about it.
Speaker 2:Yeah. So Ben Thompson was chatting with just GPT four and it's helpful but after a couple prompts it would go kind of off the rails and it would like land in this like little like, I don't know, like subset of the model weights. And basically, it was acting like a teenage girl on Tumblr or something. So he was using lots of emojis, being very sassy, kind of sassing him back and forth. And his reaction was like, this was incredible and like totally passed the touring test because it felt like you were actually talking to like this like sassy teenager basically or like this sassy 20 Tumblr person.
Speaker 2:Microsoft dealt with that, figured figured out how to like review the prompts, but then ultimately became more or less like you know an API provider. So hey, you know like let's let the actual chatbot interaction live with another company. And they it doesn't really feel like Microsoft has tried to go too heavy into into actually like the the user facing chatbot interaction. But it's fascinating. In this Eliezer, Yudakowsky thing, the other thing I'm noticing, he uses dashes but he doesn't use em dashes.
Speaker 2:He uses two minus signs. And I feel like he's not using Proof any
Speaker 3:of But
Speaker 2:yeah. I don't know. It's an interesting takeaway like the crazy anecdotes all over the place. I Not a clear framework for how to truly deal with this.
Speaker 3:Personally, I think that this week having somebody high profile in the venture community that people are
Speaker 1:Yeah.
Speaker 3:Believe is under Some LGBT induced psychosis or it's a part of it. I think that is gonna be a huge wake up call for the industry. Totally. Because it's one thing it's one thing to hear about a New York Times, the New York Times finding somebody in in way out of tech hub Yeah. That's that's doing something like this and and
Speaker 2:And was already
Speaker 3:But potentially by having somebody that that
Speaker 2:Everyone knows. That you
Speaker 3:know, everybody knows that's invested in a bunch of different companies. Like potentially suffering from this is is a is a wake up call for the industry that I think and it and it's not any one company. Right? It's every single Yeah. Lab with a chat app needs to be taking this more seriously and I'm sure they are.
Speaker 3:I'm sure Yeah. This is
Speaker 2:effectively I completely agree. I I I think this is solvable from a research perspective. It's actually a case where it's solvable with more AI. Have a have an AI read every response before it goes out and say does this sound like the ravings of a madman? If so, let's take it down a notch.
Speaker 2:Let's de escalate. And that's and so I I'm almost sure I disagree with Eliezer on the I I probably agree with him with the with the diagnosis but not the prescription.
Speaker 3:Yeah.
Speaker 2:Right? And I and I have faith that the that the labs will be taking this very seriously. And I don't know. I'd I'd be interested to hear from some anthropic people. Obviously, take this stuff extremely seriously as does as do all the labs but Anthropics done like I think the most like writing on like on like the shape of of risks associated with this.
Speaker 2:Interesting to dig into. Anyway, we should shift to a lighter topic, more cause for optimism. The Re industrialized Summit is going on right now and Palmer Lucky is on stage with Ashley Vance, friend of the program. And he is teleporting in as a humanoid, as a humanoid robot. Aaron Slotov is there, has a picture of of I wonder I want
Speaker 1:to I know so much more about
Speaker 2:need to figure out what Mullet.
Speaker 3:The robot has a mullet. Fantastic. Love to I wonder
Speaker 2:what robot this is because yeah. I I didn't know we were at this stage where you could you could teleoperate a robot like this. I'm sure Palmer considered what company he was gonna use. Anyway, let me tell you about Numeral HQ. Sales tax on autopilot spend less than five minutes per month on sales tax compliance.
Speaker 2:Go to Numeral HQ to get started.
Speaker 3:Let's give it up for sales tax compliance.
Speaker 2:And we have someone from the re industrialized summit hopping on in just three minutes. Chris Power from Hadrian jumping on
Speaker 3:in just With
Speaker 1:some few
Speaker 3:massive news today. We
Speaker 2:also have some folks from semi analysis hopping on. We have Jeremy who just wrote a fantastic deep dive on Meta's
Speaker 3:super Yeah. I want give context on the deep dive.
Speaker 7:Yeah. And I'll be right back.
Speaker 2:A true deep dive on, you know, we saw Mark Zuckerberg come out this week talking about the the super intelligence team. There's been a ton of leaks around aqua hires and and big pay offers and poaching and trade deals and all sorts of stuff. Semi analysis has a lot more information on what's going on and there are some crazy, crazy stats in here. So the the most interesting thing is that it feels like Mark Zuckerberg is directly coming for Stargate. So Semi Analysis has a comparison table with three and this is from Ian who screenshotted it.
Speaker 2:He says, this is crazy. And basically, you're you're comparing Anthropix next big data center which is the GPUs will be provided by AWS. This is on Trainium two is the chip type. Anthropix gonna go for 780 megawatts about a what is that? A billion FLOPS or t FLOPS, teraflops.
Speaker 2:OpenAI Stargate will be about 2.5 times the size of Anthropix data center. They're working with Oracle on that. That's project Stargate, obviously. They're using the NVIDIA GB two hundred and three hundred for that. And now Meta with Prometheus is trying to go straight to one gigawatt, and they are trying to have 500,000 chips, more chips, more flops.
Speaker 2:And if they can pull it off, Prometheus will be bigger than Stargate when it is released. There's a bunch of other fascinating bits in this semi analysis article. Apparently, they're building data centers in tents now. They are moving so quickly that they just need to house and shelter the GPUs, but they can't they don't even have time to build their typical data center structure. And the other interesting data point that I wanna dig into
Speaker 3:engineers sleeping in tents, metas GPUs running in tents.
Speaker 2:Yeah. It's a it's a bull market intense for sure. The other interesting thing was that in the chat app war, it feels like OpenAI's ChatGPT is really really pulling away. So daily active users for ChatGPT is at a 160,000,000. Meta is at a 100,000,000, but ChatGPT users are running way more queries per day, 7.5 per per queries per user per day, whereas Meta AI is at two queries per user per day.
Speaker 2:And so as a as a share of queries, ChatGPT has a 71% market share according to this semi analysis deep dive. And so the chat app wars seem to be maybe less competitive, so that obviously begs the question of is is Meta trying to make that fifty fifty come from behind really dominate in chat app or do something completely different? Either way, there's a whole bunch of interesting information in here about their strategy, what they're building, how they're training, how they're gonna get past the lama for failure and we'll dig into it with Jeremy from semi analysis in a little bit when he joins the show. But we have Chris Power from Hadrian on the stream. Welcome to the show.
Speaker 2:How are you?
Speaker 7:Nice to see you guys. Thanks for having me.
Speaker 3:Look at you with this background. Fantastic. Step
Speaker 2:We and love it. Give us the update. How is Detroit?
Speaker 7:It's incredible. You know, we're just re listening to the secretary of the Navy Phelan speech and said, the main thing you can do that's most patriotic is, you know, not necessarily join the services, but become a machinist, become a welder and help us build more ships in America. And, yeah, we announced today that hopefully I finally get my Geordie Hayes size going that Founders Fund and Lux are leading a huge $260,000,000 round into Hadrian.
Speaker 2:With authority. Congratulations.
Speaker 7:Thank you. And Morgan Stanley is providing us this huge instrument as well to, expand factory capacity.
Speaker 3:Let's give it up to Morgan Stanley.
Speaker 7:For the future of American factories and, more importantly, the new industrial workforce.
Speaker 2:Fantastic. Talk to me about what's the use of equity? What's the use of debt? Are you buying a building? Are you leasing a building and buying equipment that goes in the building?
Speaker 2:Is it all leased? What are you building out? What's the scale of the next Where
Speaker 1:are you doing it?
Speaker 2:Yeah. Where are you doing it?
Speaker 7:Yeah. So last year in Factory 2 in LA, you know, we scaled revenue 10 x last year. Wow. And so we obviously need more capacity. So we're gonna use all of the factory financing capital to buy more machines and put them in Factory 3 in Arizona, which is gonna be four times the size of our facility in LA.
Speaker 2:Congratulations.
Speaker 7:Indeed. And you know, we're using this capital because we don't want to use equity dollars to scale. We want to use equity dollars to hire more people to build more products for our customers, and then use this great financial force of this country to buy all the CapEx to build, you know, more factories, more machines, more production.
Speaker 2:I'm Dumb incredibly question. Two, it's beautiful. It's amazing. It's it has really high ceilings. You can fly drones around it.
Speaker 2:Most of the Hormleys, the CNC machines are like maybe 10 feet tall. But the ceilings are like 40 feet tall. Are you gonna double stack this stuff? Are you gonna get a building with lower ceilings? Or do you need high ceilings?
Speaker 7:We love high ceilings.
Speaker 2:Okay. Why?
Speaker 7:We have the most beautiful highest ceilings you've ever seen.
Speaker 2:Okay.
Speaker 7:No. I mean, love high ceilings. We love HVAC. Yeah. The Arizona facility will be just as tall.
Speaker 7:We're gonna go retrofit it. So Yeah. Same exact setup.
Speaker 2:And is we're that is that tower thing and the tower is valuable for like stacking materials and you wanna have a like a, you know, big warehouse space as well in here?
Speaker 7:Yep. So you need you need every machine or robot in any one of our factories to have be isolated on 18 inch concrete foundations. So you know, a truck drives past, nothing moves.
Speaker 2:Oh, We
Speaker 7:can't double stack double stack these things. Okay. Got it. Someone might die. Yeah.
Speaker 7:So we gotta go we gotta go horizontal.
Speaker 2:So what yeah. What's the scale of the products that you like are in the Hadrian Wheelhouse right now? Shipbuilding's obviously a big focus. You already mentioned it, but I imagine you can't CNC an entire destroyer or maybe you can, but are we talking nuts and bolts and screws or pieces of complex weapon systems? Like like, what are the shape of the stuff that's coming out of the other end of the Hadrian facility?
Speaker 7:So Factory three will be pure machining Mhmm. With all of the machining formats because we're releasing some new products that are dedicated to engines and, you know, round things and different material types to really complete our r and d of the whole machining category in Factory three.
Speaker 1:Mhmm.
Speaker 7:The other thing that we've been working on in secret is factories as a service, which is not just parts, not assemblies, but full products. So Mhmm. Hey, if you've got factories that are years behind schedule with many manufacturing methods or you're designing a program from scratch, you know, everyone needs a Tesla Gigafactory, John. Actually think every American should have a Tesla Gigafactory and Haeger will be the one to grow and build them. So Of course.
Speaker 3:I need one in my backyard
Speaker 1:badly. So
Speaker 7:we'll scale out machining in factory three, four times the size. It's gonna be awesome. And then we'll also use the capital to continue the journey that we've been secretly on for the last twelve months, which is in new manufacturing domains like welding, castings, additive, all these other manufacturing puzzle pieces that once you have them all, it's like collecting Pokemon, you are the manufacturing master. Yeah. And that's that's the thing that we've been working on in secret of factories as a service as well as scaling out our operational productivity as well.
Speaker 2:How does one of those deals work? If a factory is a service, I come to you, I wanna make as many podcast microphones as I possibly can and I and I have insight into my business. I'm making a 100,000 a year so I need a factory. You're gonna set it up for me but then like what if I bail? Is this a revenue concentration issue?
Speaker 2:Like are you gonna be like, you know, oh we only have one customer and if they got a business we're screwed but everyone has faith that they're not gonna Like how do you think about that debate?
Speaker 7:We're we're mostly working with government partners and massive primes to look at Sure. You know, what are these big programs that are years behind schedule that need advanced factories combined with the new American workforce to go fix them and speed them up. So we're we're not worried about the revenue concentration risk. But you can think about it, John, as like you can buy parts like AWS, you can buy some compute transactionally or hey, you're gonna need a data center for the next ten years. Now, what's in that?
Speaker 7:A range of parts, a whole product.
Speaker 1:Yeah.
Speaker 7:For new DID programs of record, we're partnering with companies to go attack these, where production is the real issue. Like munitions is a great example. We have to think really carefully about who we partner with, how much are we investing ahead, how much Yeah. Are we kind of playing that game of you know, being very conservative and responsible with our capital. But ultimately what it looks like is, we will help you design the product from day one to
Speaker 4:be better. Yeah. We will
Speaker 7:help you prototype it. And then when it goes to production scale, we will run that engine for you over a decade. Much faster, much more efficiently. And in a lot of areas like submarines, shipbuilding munitions, it's not about automation to make things cheaper, it's just no one can find the workforce. You have to use our model of advanced manufacturing combined with this new industrial workforce that we're so grateful to work with Yeah.
Speaker 7:That's the power because, you know, you could give me a billion dollars and say go hire 2,000 welders and we can no longer have we no longer have that scaled workforce in the country. Automated factories are sometimes the only way to win in these critical domains.
Speaker 2:Yeah. It's interesting. It's kind of like what we're seeing with Crusoe where they're building an AI factory, a data center for Stargate which is its own entity but for a program, ChatGPT and OpenAI that's gonna be wanting tokens for a very long time and then Oracle's involved. It's like you have to puzzle piece all this together and I feel like you're like the master of this like understanding the full landscape. But yeah, who are the other critical partners?
Speaker 2:The government and I guess I'm also interested in like you you've you've mentioned a few different value props like, how much of this is is there is a government mandate to make this thing in America, so we need to reshor versus we need to make this faster versus we don't even have the capability to make this anywhere and it's a new thing and so or just like we need to do it cheaper. There's like a whole bunch of different tension when you're making something. Like what are you seeing in the in the customer landscape and and the demand for for manufactured products?
Speaker 7:Yeah. So for for machining, which is is most of our revenue and the core of the company and the mother of all manufacturing processes, it's basically we're scaling a new program of record and no one else can keep Mhmm. You know, we're going from one aircraft to 20. Yeah. How are gonna do it?
Speaker 7:What we're gonna do with Hadrian? In the second example, a lot of the primes have, you know, a billion dollars in spend a year and their suppliers are delivering on time 60% and they're often three to five months late. So that is less about cost and that's more about I want a stable supply chain that I don't wanna have to worry about. Because if you have one part missing, your manufacturing line goes down and then it's millions of dollars a day. Right?
Speaker 7:So people are really coming to us for the schedule and the capacity and stability versus cost.
Speaker 2:How do you think about the history of the shape of the industry? Is this is like back in the day before the last breakfast or Last Supper, the first breakfast is coming up. Right? The Last Supper and there were so many different primes, so many different defense contractors. Was there a split between the factory producer, the factory builder, and the and the prime?
Speaker 2:Is this a natural split that we're just returning to? Or is that or is this a new industry structure that you think we're gonna be building towards for a long time? Because like back in the day when you started a website, you needed a data center. Then AWS came up. Then the websites got so big that you had to build your own data center again.
Speaker 2:We kinda went back, and that's what's happening in the AI world. But but how has this evolved in the past? And then is it gonna stay like this forever? And there's gonna be the separation between the the the designer and the and the manufacturer of the factory.
Speaker 7:So we've you know, historically, as a country, all the primes have always had massive supply chains of small businesses Sure.
Speaker 3:You know, in
Speaker 7:the billions of dollars and then critical tier one or two suppliers. It's always been not purely vertically integrated. I I think for the industrial base at large, you know, from the seventies to the twenty twenties, you used to be able to run a manufacturing company where 70% of your revenue was stable commercial demand, and then you get some ups and downs with the DOD. So what happened to a lot of the talent in industrial base when we off shored all of commercial manufacturing was that you you lost your stable revenue. Right?
Speaker 7:And now you're just dealing with this up and down demand. I I think because of that, you know, in the eighties and nineties, you know, your dad lost your job in the factory, so you told your son or daughter like, go get a four year college degree. This is not a good industry. And now, we're in a position where in a lot of these areas, we don't make it onshore or there isn't the workforce to do it. And that is changing the dynamic between what is the hardest thing to do.
Speaker 7:Actually, hardest thing to do is manufacture things at scale, at rate and on time, which is what you're seeing in munitions or shipbuilding. It is really a we hollowed out the talent base. We don't have a lot of the talent anymore. The only way to do that is use software and robotics to enable this workforce to be 10 times more productive. And it's it's it's now flipping.
Speaker 7:And I think a lot of people in the country forgot how to manufacture products correctly. Now, they're they're coming to us to help them out with that journey just because of this like, you know, hollowing out that's now gonna come back. So I I I think it is a new structure, but that the primes have always had multiple tiers of partner suppliers and multiple different configurations of that that value chain.
Speaker 3:What kind of opportunities are there are there at Hadrian now for somebody that's maybe 25 years old, never imagined going into manufacturing, but realizes there might be a bright bright future for them in the industry?
Speaker 7:Yeah. So for for software engineers, you know, manufacturing software is thirty years behind the rest of Silicon Valley. So it's the your only opportunity outside of AI to do like real engineering Yep. And work on the national mission. And for people with, you know, you're straight out of high school or you're in retail or hospitality or you you're at a desk job that's gonna be automated with AI, like manufacturing is the last domain that's gonna get fully AI automated and it can be really high skilled, high paying jobs in advanced factories that are a really cool place to work.
Speaker 7:So we've got tons of opportunities both help us running our factories, help us automating more factories, new types of factories. But I think operations is is the most the most important place that we've got a huge talent base
Speaker 3:that we're really proud of. The the children yearn for the factory floor. What what what's what's been the difference between this year's re industrialized and and last year's feels like a decade has passed since then in in in terms of excitement and interest in American dynamism and rebuilding the industrial base.
Speaker 7:I I think last year, you know, we we pulled it together with the founders, especially thanks to Austin Bishop who's really built this over the last year. You know, it was a kind of a hope and a dream of, you know, is the audience gonna be there and do we really people believe in the mission? And then this year, you know, we've got trade ambassador Greer talking about, hey, we're gonna change all these policies because re industrialization and manufacturing is is no longer economics, it's national security. And Yeah. You've got the secretary of the navy saying, you know, the best thing you can do for the country right now is learn how to weld or be a machinist or a quality inspector.
Speaker 7:And I think the sea change on people realizing how important it is to be a sovereign nation with sovereign manufacturing is huge. This year we had a 6,000 person wait list, half of the government is here and all these massive companies and and leaders like Shyam from Palantir who are really hell bent on this re industrialization before we potentially go into a fight with CCP.
Speaker 3:And and Robo Robo Palmer. Robo Palmer. I
Speaker 2:have a question.
Speaker 3:Yeah. It's such a I mean, it it makes I think it's an ex such an exciting time because the idea that people don't wanna build things, people don't wanna create real things. Right? There's so many people I know that you say, hey, do you wanna send emails for a living or do you wanna make ships and planes and and any number of you know, cars. Any number of things that we need to make and that if you actually give them that sort of binary they're gonna say, so while making making things sounds sounds really cool and so we need we need companies like Hadrian that that say this is important, it's cool and we have the resources to do this in a really serious way.
Speaker 2:Yeah. It it seems like defense is kind of the most obvious thing to re industrialize. It's obviously like the most important thing to have ongoing capabilities in. But then walk me through the path of re industrialization on the product side or on the business side like what how do you see this playing out? Is it like we do the warships and then we do phones or cars and then and then the the vacuums and then the Happy Meal toys come at the end?
Speaker 2:What what's the flow? Do you like what flow do you think it will happen? What are you excited about like on the horizon?
Speaker 7:So so I I think the last time we did this, it went from, you know, commercial through defense. Like, you know, we made washing machines and then we made navigation equipment for warships. So we we made Ford cars and then and then Ford built bombers. And I
Speaker 2:think Yeah.
Speaker 7:This time it's gonna go the inverse as we get better at it. But it's very interesting. It's like, why is DGI so powerful? Well, arguably because of Foxconn and that was because of consumer products like Apple making all the iPhones in China. Yeah.
Speaker 7:And you you know, if you had a similar Foxconn style industrial base, we could probably make a lot of drones here, maybe not as cheap as China, but certainly at the scale we needed. So I think what people forget is that it it is an ecosystem that loops into one another. But I think with the cost base and the importance, we start with defense and then loop back. But you know, like I think it was might have been Westinghouse or another washing machine manufacturer just like decided to build a $400,000,000 washing machine plant. It's like incredible.
Speaker 7:It's like your dream. That's just as much of a job creator as defense. But I I think Yeah. That we are going to loop around from all these critical defense industries for Hadrian, and then right right back into consumer, you know, when the time is right. But obviously, we're extremely focused on the national mission at this point in time.
Speaker 3:I cannot wait until our microphones are are built in in Hadrian factories.
Speaker 2:That would
Speaker 3:be fantastic. I don't care if it takes fifteen years. I'm looking forward to it.
Speaker 2:I'm excited. Probably way sooner than that. Thanks so much for stopping by.
Speaker 3:Yeah. Congratulations.
Speaker 2:Have a great time.
Speaker 3:Say hi to everybody on the We have
Speaker 2:we have over industrialized our facility and now it is an incredible lift to airlift this across the country. But we will definitely be at
Speaker 3:the next Cheers.
Speaker 2:Really quickly, let me tell you about Adio customer relationship magic. Adio is the AI native CRM that builds scales and grows your company to the next level. And we are fortunate to be joined by Jeremy from Semi Analysis. Hopefully, in the studio here talking about Meta Super Intelligence. Jeremy, how are you doing?
Speaker 2:Good to meet you.
Speaker 3:What's going on? Hey.
Speaker 5:Doing fine. Hey, Nice to meet you. How are you?
Speaker 2:I'm good. Could you case off with, like, an introduction of how you got into this? I've heard Dylan Patel's story of just kind of being on forums and nerding out about this stuff and then turning it into a career, but how'd you get into semiconductor analysis?
Speaker 5:Yeah. Sure. So before joining semi analysis, I was a buy side analyst. So I was mostly focused on the stock market, on equities, looking specifically at tech stocks. Mhmm.
Speaker 5:I was at long only European shops, so looking at European stocks, like ST Microelectronics, Infineon, all these industrial automotive semiconductors. As part of my research, I discovered seminalysis. I was like, woah. This guy's really good. Yeah.
Speaker 5:And and and one day, I just saw a post of Dylan on Twitter. He was just saying, yeah, I'm hiring a bunch of people with the sell side or buy side experience because I wanna build a real institutional firm. And, yeah, like, we just got a chat that was, I think, August 2023. I joined the company in February 24. We were seven when I joined.
Speaker 5:Now I think we're 33 or 34. So, yeah, it's growing every day, I think.
Speaker 2:So I can't do it. There other firms like this in the in the buy side, sell side ecosystem? I'm thinking of like Ian Bremmer has the has has a consulting group where he writes books, but then also has a team of geopolitical analysts talking about kind of global macro trends and what's going on the political side. Did you ever interface with any other firms like Semi Analysis? Because it seems like unique and Dylan's like AI is so big that Dylan's crossed over from talking specifically to to sell side analysts that even venture capitalists will read semi analysis.
Speaker 5:No. I
Speaker 1:I I agree. I think
Speaker 5:it's pretty unique. Look. Like, there are obviously on one end, there are market research firms. There's, like yeah. Folks like IDC, Gartner, and
Speaker 1:so on
Speaker 5:and so forth. There are many of them. On the other end of the spectrum so those would be, like, very industry focused. On the other end, you have, yeah, Wall Street sell side analysts, Morgan Stanley, East Goldman Sachs of the world. I guess we kind of found a spot in between.
Speaker 5:And also it's it's part of the team because we have over 20 analysts and roughly speaking, we have half of people that have financial background like myself, so more closer to markets, and the other half is more engineers and people that are extremely technical. And so we kind of found that sweet spot. And also that's what's pretty cool is when you look at the different people at semenials, it's like all the guys like myself that have more financial background actually love geeking out and digging into technology stuff. And same goes on with the engineers. They also wanna understand the business aspect and they end up geeking on on the data and understand the insights and market shares and stuff like that.
Speaker 5:So, yeah, we all go towards the same goal but have like diff a different set of, you know, skills and such.
Speaker 2:That makes sense. And so take me through the latest piece.
Speaker 3:I can imagine other other players in in the semi market research space just wait for you guys to publish. Okay. I think now we're ready to form an opinion.
Speaker 2:Now we can put a buy rating on it. Now we can slap a buy rating on that bad boy.
Speaker 3:And you're your favorite researchers favorite researcher.
Speaker 2:It's okay. By the time we're done, we're gonna It's a million dollars a month for any venture capitalist and we like to say
Speaker 3:Platform fund.
Speaker 2:Yeah. If you're not if you're not on the the semi analysis one
Speaker 3:day AI investment.
Speaker 2:More of
Speaker 4:a tool list.
Speaker 5:Yep. I gotta say we found something super funny a few days ago. One of the big brokers wrote a note to clients and basically said, yeah. These guys are the bible. Actually, talked about fabricated knowledge, which which is Doug, so president of our firm.
Speaker 5:Yeah. They said some people think fabricated knowledge is the bible, but actually, he works with the firm that's the actual bible and all of
Speaker 2:the same.
Speaker 3:I don't know. I didn't say it.
Speaker 5:It's a Wall Street guy.
Speaker 2:That's amazing. There we go. Yeah. I I I I'm a I'm a strong believer and I I really enjoy the pieces every time they drop. Take me through the latest one, medicine Yeah.
Speaker 2:For
Speaker 3:news this week Crazy. Was almost drowned out by the the windsurf Google, Cognition debacle. And so Zuck came out with this huge announcement, you know, Monday. And, yeah, it almost it almost got swept away a little bit.
Speaker 2:Yep. Yeah.
Speaker 5:I I mean, I guess Zuck is all in. Right? That's another proof. It's interesting because I think some people were, at some point, doubting at the beginning of the year, is he gonna carry all that investment, tens of billions of dollars? The answer is clearly yes.
Speaker 5:He wants to do it. It's interesting because when you look at Meta's CapEx so far, it has been heavily tilted towards what he calls core AI, which is basically recommendation models. It's a lot of inference Yeah. Inferencing advertising models and all of that. So they said publicly in '23 and 2425, most of that CapEx is gonna be, like, $70,000,000,000 in 2025 is for that core AI business.
Speaker 5:Mhmm. So the GenAI, the Lama stuff is still is still at an earlier stage. But the big question is how how how bold is gonna go with Lama? And I think what what we showed in this article, hey. There's a lot of evidence that he's doing it on a very large scale.
Speaker 5:And that's not just it's not just empty statements and saying I'm gonna build a five gigawatt data center in a few years. It's actually things that are already built or under construction, already committed capital. Mhmm. And so that's the first stories. There's there's already a substantial infrastructure build out specifically for Gen AI.
Speaker 5:And I guess that sort of rationalizes the the amount of money that's spent on researchers because if you think about it, yeah, you're spending, like, hey, maybe $30,000,000,000 this year on Lama infrastructure. You're gonna spend maybe, I don't know, $3,000,000,000, $5,000,000,000 on on hiring top researchers? Yeah. Sure. Why not?
Speaker 5:Right?
Speaker 1:Yeah. Yeah. Yeah. That's a
Speaker 2:completely reasonable strategy. And and it always it always mapped out to us that even if even if these crazy researchers wind up working on core AI and the llama project doesn't even go anywhere, it's like, you could probably squeeze $3,000,000,000 out of core AI. Right? I don't know. It was just like the thought I I had.
Speaker 5:Or you or you can also, like, these researchers can be focused on on Gen AI, but they're they're gonna develop, like, state of the art technologies and using, like, massive compute. And then Totally. Those state of the art technologies can feed into the core business Yep. And end up generating more advertising sales. And if you think about it, like, Meta is growing double digits, $160,000,000,000.
Speaker 2:Yes.
Speaker 5:So every time they grow double digits, we're talking about close to $20,000,000,000 of incremental revenue. So it's big numbers. Right? It's easy to justify just getting a few billion dollars on researchers.
Speaker 2:Yeah. Yeah. It's great. I have I have one question about the history here with Meta. So there was this story, think it came from the first Mark Zuckerberg interview with Doarkesh Patel where he tells this story of the original Lama data center or the reason he had residual capacity was that he felt like he got caught flat footed around TikTok and Reels and recommendation algorithms at scale for vertical social video where it's much more it's much less driven by a social graph and kind of like a traditional CPU based graph query and more about these actual recommendation algorithms.
Speaker 2:And the way he tells the story is like, we didn't wanna get caught flat footed. We needed to play catch up in reels, but we didn't get caught one one we didn't wanna get caught flat footed again. So I told the team, build two big data centers, and then we had this kind of empty data center sitting there, and that was that gave us the initial compute for Llama. Does is that too much of a simplification? Does that feel like what happened?
Speaker 2:Do you have any insight into kind of, like, how the Llama project the initial compute was built out? And then I wanna go into the future of the project.
Speaker 5:I would just say at a high level, if you think about the amount of money that Meta has historically been spending on on data centers relative to what they maybe need in theory, like, have always been overspending. Sure. They have always been, yeah, investing some on substantial infrastructure, and same goes on for Google. I think Google to an even bigger extent. But, yes, like, Meta has been a pioneer in building large scale data centers.
Speaker 5:Over a decade ago, Meta introduced their h shaped data center design. They've been building 150 megawatt campuses since, like, 2013. Mhmm. So that's not new to them, like, building large scale. Yeah.
Speaker 5:And that's why they also already had this sizable compute footprint. But in 2023, like, sizable was maybe 20,000 GPUs. That was pretty big, but today it's yeah. It's updated. Right?
Speaker 5:Yeah. You wanna be in the hundreds of thousands. And as of today, Meta is, to some extent, late in terms of training compute relative to others. Again, because they allocated they have invested a lot of money, but a lot of that has been allocated to the core AI business. Mhmm.
Speaker 5:But what we've shown in that article is that they're actually today ready to ramp, yeah, some a massive data center in Ohio that's gonna get them to
Speaker 2:the top of it. Talk about the h shape of the data center. Why was it an h shape to begin with? And then it sounded like they abandoned it in favor of just one big tent. What what are the benefits of a tent?
Speaker 2:I wanna know about data center shape broadly.
Speaker 5:Yeah. Sounds good. Who doesn't love a good data center shape? Look, the h, I I don't know why it's an h. Okay.
Speaker 5:What's more interesting is the structure of the building. Okay. If you look at one physically, it's absolutely massive. It's close to a million square feet. It's just a monster.
Speaker 5:If you look at the structure, it's also three levels. So it's a very complex structure. It generally, what we've observed for satellite imagery is that it takes roughly two years to build, which and I'm just talking about, like, first stone to actually getting the project built. So two years is a lot. Many people do that in a year or less.
Speaker 5:So, yeah, substantial time to build. It was designed for very high efficiency. So
Speaker 8:they've
Speaker 5:been using a system with free air cooling. Like, they can get the air from the outside. There's no air to water heat exchange. It's basically, you get cold air from the outside. You just expel it, hot air.
Speaker 5:Super efficient. You can spray some water on it to make it even more efficient. The energy efficiency ratio is typically called the PUE. Maybe you've heard of that, maybe not. Mhmm.
Speaker 5:Industry average is gonna be 1.3, 1.4, which means that for every watt you allocate to servers, you have to spend another 30% or 40% of that power into cooling and power distribution losses and all of that. That ratio for Meta was historically below 1.1. So they were actually, they were the most energy efficient firm in the world running data centers. Interesting. But the trade off is that these data centers took a long time to build Yeah.
Speaker 5:And had a very low power density.
Speaker 2:Got it.
Speaker 5:And so what happened is, first of all, in at at the end of twenty twenty two, Metap introduced the first massive design change. They completed through the old age and build them let's go into more traditional data center design, single stories, sort of a big rectangle, faster to build, maybe one year, maybe one or fifteen quarters, something like that. Much faster to build, more denser, better suited for AI. It could handle liquid cooling. But what might have thought look.
Speaker 5:I think this is what the x AI story actually takes a big a big role. I I think what Elon demonstrated when he set up that cluster in a hundred and twenty two he just shopped basically data center infrastructure leaders all around the world. My understanding is he's taking
Speaker 3:life a lot harder because before it was like, well, if we do this really quickly, I'm gonna need a year, year and a half.
Speaker 1:Yep. Yeah.
Speaker 3:Like, well, there's a new standard.
Speaker 2:Do it in a hundred and twenty days.
Speaker 5:Yeah. And imagine, like, you're the infrastructure leader at the hyperscaler that you you have experience developing gigawatts of capacity, and you think you're the best in the world at doing that. And suddenly some guy comes out of nowhere and does it in, like, one quarter of the time. So I think many people were really shocked. And I guess, Zoc, like, took it the other way and just was inspired by it.
Speaker 2:Sure.
Speaker 5:And, basically, that's where the tent steps in, which is let's make the data center in the shade that I can build the fastest so that yeah. The only bottleneck is just finding some power, and that's it, and buying QP.
Speaker 3:Saying earlier is bull market intense. Zoc needs tents. The XAI
Speaker 2:engineers are intense in the office. And then the XAI servers will be intense too. Everything's temporary. I mean, is there is there something about the tent structure that's potentially like, okay, this is this is gonna deteriorate faster? Like, are the what are the drawbacks of moving faster?
Speaker 2:And then on the PUE question, when I hear a one gigawatt or five gigawatts they're targeting, is that total power into the building or total power to the actual servers?
Speaker 5:Honestly, people generally throw like, you there there are both. Okay. In this case, based on our analysis, it's to the servers.
Speaker 2:To the servers.
Speaker 5:It's actually gonna be slightly more in terms of gross utility power. Okay. Thanks. Oftentimes, you see people quoting total power just to have a bigger number. Sure.
Speaker 2:Yeah. Makes
Speaker 5:sense. Industry industry standard practices to quote IT power. Anyway, in this case, you're gonna have one gigawatts of compute power by the 2026 in Ohio, and then close to two gigawatts by the 2027 in Louisiana. Mhmm. That's compute power to the servers.
Speaker 5:So, anyway, massive compute for for Lama.
Speaker 2:Is that a vanity metric? Is it a vanity metric to hit one one gigawatt exactly? I mean, Stargate, you're you have on your chart at 880 megawatts. Is a 120 or a 140 megawatts really gonna be the difference between like an amazing super intelligence and the next best thing? Like, it feels like we had to cross this threshold and one gigawatt is like it's a good headline.
Speaker 5:Yeah. It's a good headline. Okay. That that's more of it. Like, it's not gonna change much if you have 900 or a gigawatts.
Speaker 5:Yeah. But the more matter. Right? Like, you still wanna have more servers.
Speaker 2:Yeah. More is better. It
Speaker 5:it does matter to be clear. It's not gonna change too much but it does matter.
Speaker 2:Sure. Yeah. It probably matters for recruiting too. It's like you're gonna be at the place with the best. What does the best mean?
Speaker 2:I can I can, you know, 100,000,000 offers, nice round number? One gigawatt factory or AI or, you know, super closer. That's a nice round number. It's great.
Speaker 5:Look. And I've got a better one for you. A $100,000,000,000. Right? $500,000,000,000 target.
Speaker 2:Oh, yeah.
Speaker 5:Something that's pretty funny to me because, actually, the Louisiana project, is two gigawatts, they said publicly it's a $10,000,000,000 data center project. But if you count it the same way as they count this target project in Abilene, it could be like a 150 to a $100,000,000,000. So yeah. It's just yeah. Just pick numbers in marketing.
Speaker 3:Okay. How I don't know if you have a bunch of insights or clarity here but how are places like Louisiana and Ohio reacting in order to attract these types of data center projects? Are they promising the hyperscalers and the labs? We're gonna massively expedite permitting process. Is there, like, deregulation happening at a local level?
Speaker 3:What can you say there?
Speaker 5:I think the piece of context is that since, let's say, the 2023 or maybe mid twenty twenty three, you have a frantic search for power happening in The US and all around the world. And so we've we've made some number we we've aggregate some numbers. If you look at the pipeline, so it's you could there are different like data center interconnection load queue or pipeline. Basically, if you aggregate all of the load requests that potential data center have submitted to the grid, in The US, you're above 500 gigawatts. You're close to the the actual peak load of The US.
Speaker 5:Right? So what's happening is pretty insane. Those numbers are mostly fake, but what it means is that people are searching for power all around the country, and you actually have a massive competition all around the country to attract those lost products. Because if you think about it this way, like, okay, 500 gigawatts of of requests. But in the end, by 2013, you're gonna have maybe a 100 gigawatts of growth, which is an insane amount already, but it means that just 20% of these projects are actually gonna be real.
Speaker 5:Mhmm. So, yeah, there's definitely a lot of competition. So people are doing everything they can to get those projects. Tax breaks are generally today the most standard thing. Accelerating permits, like, reassuring hyperscalers that you will deliver on time, that you have top contractors, that you're gonna expedite permits.
Speaker 5:Increasingly, there's being sort of, yeah, enabling more on-site power solutions as well, like, being being more open to people burning natural gas on-site. All that kind of stuff helps companies, utilities and locations secure those big those big products.
Speaker 2:Have a question about the shape of the super intelligence team at Meta. When you think about Meta properties, think about Facebook, the blue app, you think about Instagram, you think about WhatsApp, and then Oculus and VR is like a separate thing, Quest. But I was toying with this idea that maybe the super intelligence team is more like the database team or the react team and it's and it's a it's like a an infrastructure layer a project that will have benefits all over the place, but we won't necessarily expect a dedicated vertical that competes with Instagram. It's more about making all the apps better. I wanna I wanna dive into the chat app statistics that you shared and and try and understand it feels like it's not exactly a neck and neck race.
Speaker 2:ChatGPT is pretty much pulling away in terms of percentage share of queries at 71%. Meta is way behind at 12%. Are there any signals that this is that this is, you know, something that would be addressed one way or another, or is it just too soon to tell?
Speaker 5:Yeah. Look. I think what we've seen so far is that generally speaking, when you start to deliver a better model, a better product, you just get more users. Mhmm. I think we've seen pretty good correlation between the quality of models and the usage of ChatGPT.
Speaker 5:One thing that I think is interesting is when you look at the user base of ChatGPT, you had a surge in early twenty twenty three, and then sort of plateaued for a bit. And towards the end of twenty twenty four, you had a second leg of growth, and then you hit, like, that half a billion weekly users. And that correlates pretty well with new releases with models getting cheaper and better and so on and so forth. So if you think about how Meta could get back at a point and maybe lead that ranking, well, they just have to release better products. Right?
Speaker 5:One thing is to have good products, and the other one is to have a good distribution platform. And, obviously, they have the distribution platform, right, 2,000,000,000 daily users. So they just need to build a good product, and I think users will come. And that's kind of the the value proposition when you're
Speaker 3:What is the state of the mom and pop data center market? I don't think they would like to be called the mom and pop data center market, but, know, the the you know a friend or an uncle that's getting into the data center business. Asked Brian one of the one of the co founders of CoreWeave the other day. He was he was generally bearish. He knows he knows how hard it is.
Speaker 3:But like what is the is is there a real demand signal there? Or is it just a hope and a prayer that you're gonna just, you know, kinda flip it to a hyperscaler? And is that is that
Speaker 5:Yeah. Sorry, guys. It's over. Easy easy money is over. Look.
Speaker 5:As we just said before, like, now there's really an insane amount of competition for power. And and, like and, basically, like, hyperscalers can set the conditions, so and you have to be quite sophisticated when you wanna approach hyperscalers and you wanna sell them a gigawatt site. And you also have to think about, like, how much money does that involve. Like, one gigawatt, you're talking about maybe $3,040,000,000,000 dollars of CapEx. So when you sell one gigawatt site to hyperscaler, it's not gonna be a small decision for them.
Speaker 5:Yeah. To be clear, like, buying the land maybe, I don't know, a few million. Like, who who cares? It's not a big deal. But if they if they do make the purchase, like, they intend to do something about it.
Speaker 5:So, like, yeah, they they just don't wanna take it lightly, and they have multiple options today. So for a mom and pop that sort of doesn't dig into what what they should actually do and all the requests and such, they're just not gonna get new business today. Yeah. But some some people made a lot of money for sure in 2023 and 2024 by just having, like, a large they they had 50 acres near high voltage line. It's just so
Speaker 2:That's amazing.
Speaker 3:Yeah. It's funny to imagine you're you you've been building a data center, you know, a little mom and pop shop for the last year, and then the death star data center just starts, like, popping up next
Speaker 1:to you.
Speaker 3:It's really
Speaker 1:on. No. I'm crazy.
Speaker 3:Oh, it's it's over.
Speaker 2:What can you tell us about what what changed between Llama three and Llama four? And exactly what happened with Llama four. You call it a failure. How did, like, how did that happen? Because we were we were so scale piled.
Speaker 2:Right? Scale is all you need. Just scale up the big transformer. But you dove into it and gave so much more detail. How can you contextualize and explain that to us?
Speaker 5:Simple was just a bunch of trade offs that weren't weren't in the right direction. Mhmm. Like, I think you if you wanna simplify it, you could say that to some extent, reach peak pre training in 2024. I'm simplifying it. I don't think it's peak, but let's call it for now it's peak.
Speaker 5:I think as Blackwell ramps and so on and so forth, you'll you're gonna see a
Speaker 1:new push up. But for now
Speaker 5:it's peak. And it means that if you wanna develop better models, you don't have to use a pre training. You have to use the new paradigm, which is a test and compute and reinforcement learning.
Speaker 1:Mhmm.
Speaker 5:Right? And to do that, there are some specific trade offs that you have to do. And, basically, Meta just took a bunch of options in terms of their attention mechanism, terms of the way they route to experts and stuff like that. Just a bunch of decisions that aren't very well suited towards this new paradigm Mhmm. Which means that their flagship model, Behemoth, the largest one, is just not very well suited to this new era.
Speaker 5:Yeah. And that sort of contrast with think of the Chinese labs. They are sort of the in the opposite direction because they don't have state of the art chips. They don't really have an incentive to put very hard on pretraining, and so they've been they they have been thinking harder about pushing on post training and forceful learning and test time computing, all of that that doesn't require such a large centralized cluster. As such, it's kind of the those two path, like, one end, you have meta.
Speaker 5:On the other end, you have the Chinese, and what the Chinese decided to do is just better suited to the current paradigm. Yeah. So just, yeah, just a bunch of bad decisions or to some extent unlucky. Yeah.
Speaker 2:And so that seems like that ties to this there there was this post by Rune anonymous account on X saying that there are, in fact, some secrets about what paths of the tech tree you wanna go down. You poach the right researcher, they come over and on day one, they can tell you that chunked attention might be wrong for this particular training run. Is that what you think is driving the high salaries? Is that the dynamic at play?
Speaker 5:Yeah.
Speaker 2:Okay.
Speaker 5:Yeah. You want the decision makers that understand exactly what trade offs are gonna do. Mhmm. That also know how to properly evaluate things or what kind of steps you should take to make sure what is the right what is the right choice. And so, yeah, that's what you want.
Speaker 5:The the the decision makers that had experience that know how to do stuff and that can easily, yeah, identify the trade offs and know if I wanna go in this direction, more reasoning, more RL, all that
Speaker 1:Sure.
Speaker 5:You should do that attention mechanism and not this
Speaker 2:Do you have any insight into, like, the shape of the behemoth project right now or, like, the the the the failure mode? Like, is it is it is it, like, it would be bad at math or it would be bad at talking to it for a long time or it would be bad at needle in a haystack in a big context window. Like, do like, we we we've just heard, like, it's not good enough. It failed, but, like, how what would that feel like if I were to use Behemoth and for a long time. And I'm like, oh, this is weird or it's it's bad, but in a weird way because it seemed like it was good at some things, but then just not good at everything across the board.
Speaker 5:Yeah. Let's just simplify it and say agents. So, basically, tasks that require using tools that require reasoning, that require long long context windows and this is not very good at that.
Speaker 2:Okay. Got it. Jordy?
Speaker 3:Last question from from me for now. What are you expecting out of Meta over the next six months? They have talent now. They've they have scale, but the team the new team's gonna need to gel, and it's gonna take some time to really start delivering. So are you expecting a lot of, you know, public launches over over the next the basically, back half of this year, or is this more early twenty twenty six?
Speaker 5:I think back back half of the year makes sense. Really back half, like, think '4 or beginning of q one twenty six. But for sure, you're gonna have a few months where probably not much is gonna happen. Yeah. Because, yeah, like like, as of today, we showed a bunch of pictures of the current clusters.
Speaker 5:So they already have data center capacity, but there's still some time in order to, like, actually put the GPUs in place and make sure everything runs. So they're gonna have some, like, sizable computes that's training ready somewhere in q three. And so yeah. But actually have a product release that's more of a really end of the year, but most likely early twenty twenty six.
Speaker 3:I would not be surprised East End
Speaker 1:Of The year.
Speaker 3:I wouldn't be surprised if New Year's Eve, we're back Yeah. On the show talking like we are now about a about a new drop.
Speaker 2:Can you you talk me through some of the trade offs or how the open source war is playing out? Dylan from Semi Analysis posted that the OpenAI model, open source model is expected to be really really good. That was kind of I thought the open source strategy with Lama was a great way to be superlative on day one. It's like it doesn't need to be the best model. It doesn't need to have the most DAUs or MAUs, but it's the only it's the best open source one.
Speaker 2:And so, it's superlative. You get the headline. It's the attractor for talent. Hey, we're doing something different. We've We're the best in this one narrow thing.
Speaker 2:And and there's a question about, like, at a certain point, does the math make sense to continue to open source? But then when we went through the DeepSeek moment, it felt like DeepSeek was very much distilled from the GPT four API, not a llama fork. And so the whole debate over, oh, like, you know, some Chinese labs just gonna fork llama and then and then improve it. So what is your kind of state of the union on open source AI?
Speaker 5:The Chinese are eating open source like the yeah. They're just dominating the markets. It's like one lot after another. It's not just deep sea. You had deep sea, then you had Alibaba.
Speaker 5:Recently, you had Moonshot with the Kibi model. They're just really good at open source sorry, at LLM generally, and they're open sourcing everything because it's they're in some sort of the same position as Meta. Like, they're not meeting, so they don't have any incentive to be closed source. They wanna build an ecosystem. So it makes sense to go open source, and there's just, like, shipping faster than Meta and shipping better than Meta.
Speaker 5:So, yeah, Meta is just way behind on open source. And, the West is behind on open source. The Chinese are just way better at it right now.
Speaker 2:Is it but is is is open source important, or is it more just like marketing? Because I've always had this this this thing about the difference between like what was it? Stable diffusion was open source, mid journey was not, and mid journey was able to get the get the data back from the customer because you generate four images To me,
Speaker 3:it's only open thumbs up. To me, it's only open source if it's from the Mistral region of France, but
Speaker 2:but but, yeah. Talk about the flywheel of source. Like, is there an advantage there, or is it really just if you're not in first, you might as well open source?
Speaker 5:Yeah. Think it's more what you said is if you're not if you're not if you're not a leading lab, you might as well open source because you want people to sort of, yeah, just help you out, give you some feedback to
Speaker 2:Got it.
Speaker 5:Build an ecosystem. It just makes sense. Also, I would say, like, for the broad community, generally, it's good to have open source because it's better for adoption. Anyone can sort of, yeah, play with the models and develop new applications on top of it and such. So, yeah, I think for for everyone, it's good that there's open source.
Speaker 5:But, again, like, if you're not Google, if you're not OpenAI from at the very top, like, you don't really have an incentive to be, yeah, to be secretive about what you're doing because you're not the best anyway. So
Speaker 2:Yeah. Makes sense. Jordan, do have anything else?
Speaker 3:This is great.
Speaker 2:Let's see you're please hop on whenever you post anything. I'm sure we'll be giving you lots of calls because this is a fantastic conversation.
Speaker 1:Really appreciate it.
Speaker 3:Enjoyed it.
Speaker 5:Alright. Sounds good. Cheers.
Speaker 1:We'll talk
Speaker 2:to you soon.
Speaker 3:Talk soon.
Speaker 2:Bye. Quickly, let me tell you about fin dot ai, the number one AI agent for customer service.
Speaker 3:The Bake Off champion.
Speaker 2:The Bake Off champion. Number one in performance benchmarks. Number one in competitive Bake Offs. Number one ranking on g two. And we have our next guest in studio
Speaker 3:in person.
Speaker 2:We have Jesse from Coinbase coming in. Yesterday, Jordy went over to Coinbase's launch event for base. Let's bring him in. Jesse, welcome to the stream. How are you doing?
Speaker 2:Welcome.
Speaker 3:The walk in camera.
Speaker 2:The walk in camera's working.
Speaker 3:There we go.
Speaker 2:Let's go. We got Stop your juice, man. Thank you. How are
Speaker 1:you doing? I'm good
Speaker 2:to see you. Good to see
Speaker 3:you too.
Speaker 5:Thank you. We got one
Speaker 2:more juice for you. Oh, fantastic.
Speaker 3:We're drinking
Speaker 1:Here we go. We're drinking We're drinking vape. Juice today. Yeah. We go for the juice.
Speaker 1:How's
Speaker 9:that, man?
Speaker 3:Viral juice.
Speaker 2:Fantastic. Fantastic.
Speaker 1:How's it going?
Speaker 3:Awesome. The show been so far? Super fun. It's been a crazy day on the Internet.
Speaker 1:You guys are lucky you launched yesterday and Yes,
Speaker 3:morning. One Coldplay conference changed the timeline forever.
Speaker 1:Yeah. I know I saw that this morning. I woke up, I was like, wow. Yeah. I'm glad this happened yesterday.
Speaker 2:Oh, yeah. Because it I mean, it's so hard to launch these days.
Speaker 3:Right? Having a couple couple people from OpenAI on
Speaker 1:big day for, legislation in The United States. Mean, the Genius Act. The Genius Act and the Clarity Act just passed.
Speaker 2:I'm I'm finding out
Speaker 1:Well, the president is gonna
Speaker 3:sign it I think tomorrow.
Speaker 1:Yes. Genius App stablecoins will be passed and signed into law in The United States this year. I mean, to this week, which is an incredible milestone Okay.
Speaker 2:Working towards it Take that three years.
Speaker 1:Four years. Five years. I mean, the impact is that for the last decade of crypto, there hasn't been regulatory clarity in
Speaker 2:United
Speaker 1:States, which means that entrepreneurs and consumers haven't actually been able to benefit from this technology. And we've been working to build bipartisan consensus that we need rules of the road in order to make sure that crypto works.
Speaker 2:And I feel like Coinbase has always been like the conservative one. And it paid off because during the end of the Zurp era, basically all of Coinbase's competitors went out of business. It chaos, right?
Speaker 3:Yeah. Good
Speaker 2:amount. And and and I remember talking to to a public markets investor at that time and he was just saying like like I feel like Coinbase has the mandate of heaven like they are making it What was the
Speaker 3:what was the low was it like $7,000,000,000
Speaker 2:Something like something
Speaker 3:Yeah. In in Probably in the chart
Speaker 1:The share price went to $32 Yeah. Which was below I think the series e price. Wow. And I had joined you know like a couple years before the series But e you know we all experienced that.
Speaker 10:Yeah. What was
Speaker 2:your path to Coinbase? Did you get were you building something else before? Yeah.
Speaker 1:I dropped out of school and started a company it was called Clef. We did identity. And so the whole idea was how do we build an identity that's the next thing after passwords that was decentralized Okay.
Speaker 2:And anyone a crypto company.
Speaker 1:It wasn't quite crypto but we worked with crypto companies. Okay. So know Bitfinex Yeah. We were actually providing a kind of auth and login for them. Okay.
Speaker 1:And so Paulo, we go way back because we've been building forever. Right. And so that business didn't work.
Speaker 2:Yeah.
Speaker 1:Yeah. And then when we were winding it down Yeah. I was basically trying to figure out what do I do next and I love crypto.
Speaker 2:And is identity like k y c like I upload my take a picture of my photo?
Speaker 1:It was actually a passwordless login mechanism. So almost like you hold your phone up to log in to WhatsApp. It was like that but back in 2012. And so we were a little bit before the time, but when you look at the security architecture that we built, it's actually almost the same as what we're doing now on base and what people are doing with pass keys. And it's this incredible thing where I've now been working on it.
Speaker 1:This same problem space for almost twelve years and we're feeling Overnight finally we're finally getting there. Okay. Company to Twilio.
Speaker 4:But I
Speaker 1:was so excited about Let's go. And so I joined Coinbase. Joined as an engineer and then pretty quickly on, I just started leading teams. They asked me, hey, can you take on a team? I took on more.
Speaker 1:And for the next five years, I led all the consumer businesses on the engineering side. So if you know Max Bransberg, he runs our consumer product. Me and him were product and engineering counterparts. With him running product and me running engineering. Awesome.
Speaker 1:And then after five years of doing that, I thought I was gonna start another company. I'm like a founder. I I actually put in my notice and said I'm leaving in six months.
Speaker 2:In those five years, what products were you building?
Speaker 1:I was building Coinbase, Coinbase Pro and Coinbase Wallet.
Speaker 2:Okay. Got
Speaker 1:it. So like anything that you've touched as a Coinbase user Sure. Those are my teams. We rebuilt the whole product from scratch, migrate us to react
Speaker 3:native The Coinbase Wallet like decentralized product Yes. In the Coinbase ecosystem. So I think I think the context here is like the the core business and the and why the launch yesterday is exciting is the core business was always centralized Centralized. Right?
Speaker 1:And it was
Speaker 3:gateway to get on chain Exactly. Custodial and and we'll get into base in a bit. But you were working on these sort of decentralized experiments early.
Speaker 1:Exactly. Yeah. Working on the decentralized experiments early.
Speaker 2:What are you saying it's so early at the time?
Speaker 1:You know, I'm an optimist. Yeah. He
Speaker 3:said he hit typed GM and posted it probably a 100,000.
Speaker 1:Yeah. Thought I I was gonna leave but I actually started having conversations with Brian Yep. About what did the future of Koinbase look like? And what would it look like if we leaned even further into this kind of decentralized world, built more things on chain? Yep.
Speaker 1:Because Koinbase had started ten years ago and you know, traditional web two business. And so, again, the first thing I did was I went to Brian in the kind of 2021 and our exec team and said, if you give me a billion people and 60 employees. This is like peak 20
Speaker 2:and 60? 60 employees. 60 employees.
Speaker 1:Coinbase into a DAO.
Speaker 2:Okay.
Speaker 1:And they were were they were like, Okay. But then why do we're
Speaker 3:a public company.
Speaker 2:Yes. He I know what you do with a billion dollars if you're meta and you build a big data center and you have to pay you know half of that to Jensen Huang over at Nvidia. But what would you have actually done with a billion dollars? I don't even know what is that.
Speaker 1:That We didn't really have as good the constraints off. Let's go and do the thing. Right? We have this big public company. It's Yep.
Speaker 1:Crypto leader but it's still built on web two architecture. Sure. How do we move it on chain in this new way? And so it was the vision was there but the execution strategy wasn't there.
Speaker 3:Okay. And so Well, in the in the other context is that Coinbase has been in this incredible position of being the gateway
Speaker 5:Yes.
Speaker 3:To get on chain and you see this with the Circle IPO. People were like, wait, Coinbase makes a lot of Circle's revenue as 100%. Stable coin issuer. But you guys had always basically said, everything on you know, you guys do whatever you want on chain and and a bunch of great companies sprung up to to kind of service that market. But you had to be hands off which I imagine was pretty frustrating.
Speaker 1:Yeah. I mean, I will say that early on. So Brian has always had the vision of the self custodial world. He's even had the vision of a super app in many ways, where the first version of Coinbase Wallet was actually called Toshi. It was a messaging product with apps in it.
Speaker 2:Oh, interesting. This was in like Yeah.
Speaker 1:This is in 2017. It's I'm green
Speaker 2:just basically put it
Speaker 1:up on stage. It's basically And so then we we kind of pivoted Tochi to Coinbase wallet Sure. Which is the self custodial wallet that millions of people use that Yep. Folks know and love. And we've worked on that for the last five years.
Speaker 1:And that was primarily focused on trading in money. Yeah. But, as we've built base over the last two years, which has really been a builder ecosystem where people are building apps, We've seen two problems emerge. The first is that everyday people when they're trying to use crypto and trying to to kind of figure out what's going on here, it's really hard to actually find things to do and that are useful. Know, maybe they come on chain for a coin, but then they kinda get lost.
Speaker 1:They're like Yeah. What are all these things? How do I actually use it? And then on the other side, we saw that we had thousands and thousands of builders and creators who had these incredible products that they were building, but they couldn't actually get them in front of people. Mhmm.
Speaker 1:Like, were missing this connective tissue. Yeah. And so, ten months ago, I talked with Brian. I kind of came back to running the Coinbase Wallet team which I'd worked on for a long time prior. And we kind of jointly articulated this vision of, well, what if we built the the kind of app that solved that problem Yeah.
Speaker 1:And brought all these things together. And this is what we launched yesterday. It's the base app. And it's an everything app that lets you create, earn, chat Yep. Trade and discover Pay
Speaker 3:for too.
Speaker 1:Pay for things with Shopify Yep. At Erawan.
Speaker 5:Know, you
Speaker 1:can now pay for juice with base USDC on Shopify powered by Basepay. You know, like Yeah. We're The whole thing kind of comes together in a new way where because we now can bring together this marketplace Mhmm. Of kind of developers and builders and businesses on one side with consumers through a really easy to use experience Mhmm. We're gonna be able to to grow crypto a lot faster Yeah.
Speaker 1:And spin the flywheel.
Speaker 3:Okay. Would would I imagine launching base in the way that that product is today. I know it's a pure software software business, so very different Yep. From the tradition, you know, Coinbase's, you know, traditional business which is effectively, you know, acting as this regulated or, you know, financial institution. Would it have been possible to launch this a year ago or did you need the the White House to launch some tokens and and a few other events?
Speaker 1:Well, I I think the biggest thing that we needed is we needed technology to mature. Mhmm. Right? So when we had this vision three years ago of building base, the the first thing we started with was actually the platform. Yeah.
Speaker 1:Right? It was the chain. Yeah. Because we'd spent a year trying to figure out, okay, what's the product we build to kind of bring this next
Speaker 3:explain those. You had the chain but there was no token attached
Speaker 2:the chain would be able to use it.
Speaker 1:Like I
Speaker 2:feel like the playbook We
Speaker 1:went back to the tried and true method that people have been following for a hundred years Yeah. Which is that you focus on building product that people love.
Speaker 2:Okay.
Speaker 1:Right? Like I think there's been this whole distortion in crypto for the last five years where people are like, oh, you get a token you pay people to use your product. Yeah. And we basically said from the beginning, no. We're gonna build a chain.
Speaker 1:It's gonna be a developer platform and we're gonna figure out how do we make it the best place for builders to build. Yeah. And that's exactly what we did
Speaker 2:over But the last two I if I take it to like the Bitcoin analogy
Speaker 1:Yep.
Speaker 2:It's like the reason that people set up data centers to run the Bitcoin network is because they mine Bitcoin and that has financial value. Yep. So there's this economic incentive. Yep. Now, that gets distorted all the time when people run like random chains and stuff and I understand the the rationale.
Speaker 2:But is there an incentive for other participants to to help run the infrastructure or or or or are you doing something where you're splitting it across different groups? Yep. How does the actual chain stay on?
Speaker 1:Yep. Well, the first thing to know is that Base runs on Ethereum. Okay. So it's a layer two that sits on top of
Speaker 2:So as long as the Ethereum miners are happy, then Base runs.
Speaker 1:Yes. Exactly. That makes decentralized network that's also Base that people use to get access to the network.
Speaker 2:Got it.
Speaker 1:And the thing that's bringing people to the network is that they're building things and then they're using And those so, here's two examples. The first one is USDC.
Speaker 2:Yeah.
Speaker 1:Yeah. We're seeing a huge amount of growth in payments both in The United States and outside The United States in USDC. And that's because people are using products like Shopify Sure. Which has rolled out to millions of merchants Yep. Where they're actually taking USDC in their wallet and they're paying for things.
Speaker 1:Yep. And that's global, it's fast, it's cheap, it happens instantly rewards that
Speaker 3:the the it's retailers effectively which if you pay with USDC will give you one point back or something like that because
Speaker 1:the exactly. 1% back with base pay and you can earn 4.1% on your USDC when you're holding it. That's pretty good. Yeah. Right?
Speaker 1:And it's an instant global payment method. Yeah. So any business in the world can integrate it and then anyone else in the world can pay for things. Yep. So that's one example.
Speaker 1:People are coming to base Yeah. For payments and stable coins. Mhmm. The other example is a little bit more out on the kind of like nascency curve in terms of what we're seeing, but we're really excited about. This is what the focus of the event was yesterday, which is really around the creator economy.
Speaker 1:Sure. Right? If you look at the last twenty years, you've had so much creativity porn to the internet, but the vast majority of that creativity has been put into platforms where creators actually don't earn that much money. Right? If you're an average creator who has less than 10,000 followers, or if you're in another country like Nigeria or Argentina, you're gonna be posting and filling up this kind of content world with valuable creativity that other people are looking at, but you're not earning anything.
Speaker 1:And Yeah. So one of the big things that we're focusing on with the base app and one of the reasons why people are are coming to use it is that when you post on base, you actually earn. Mhmm. And this is because we've built a new economic system where the content is actually valuable and then the value gets flowed back to the creators. Yeah.
Speaker 2:And I
Speaker 1:think this is a novel use case for this platform that we built with base and base chain.
Speaker 3:If if somebody opens a base app, their wallets loaded and they start scrolling.
Speaker 2:Cost them money?
Speaker 3:Does that cost them money? How does that actually
Speaker 1:It it doesn't cost them money but like, I can literally show you. You you can decide if you wanna support a post. And so Okay. Like here
Speaker 2:Got it. So it's like this
Speaker 1:is on my feed and I'm just like Jesse. I'm on feed. I'm creating content. I posted this great Base Juice content. Mhmm.
Speaker 1:And Oh. There's a bug. Live.
Speaker 3:Classic. There we go. It happens.
Speaker 1:Base Juice content. Right?
Speaker 9:Sure.
Speaker 1:And you have the normal things you see here, the like, the comment, the retweet, and then you have a new thing.
Speaker 2:Yeah.
Speaker 1:Which is market cap. Sure. And so Yeah. This is basically the value of that content and this one's worth $15,000. This one's worth $84,000.
Speaker 1:This
Speaker 2:one's How is that possible? Mean I like my I've been on YouTube for five years. The best video I ever posted got 8,000,000 views and I got a check for 20 k from YouTube.
Speaker 1:Well, that's actually pretty good. YouTube is one of the platforms that pays creators
Speaker 2:really They took 50% and thought that was fine because they brought me all the users. I was actually pretty happy with that but like how could how could something could a piece of content have market cap?
Speaker 3:Well, I I I have a
Speaker 2:No one else wants to buy it unless they wanna buy the revenue stream and there's been some of those projects where
Speaker 1:like I could sell
Speaker 3:the rights to Yeah.
Speaker 5:How do
Speaker 3:you Start up start up CEO well, this is on on X. Yeah. Right? Where I where I where where no market cap on this one. Startup CEOs can't even hug their chief people officer at a concert in this country anymore.
Speaker 3:1,600,000 views, 50,000 likes.
Speaker 2:50,000 likes. I'm sure
Speaker 3:I'm sure the creator payout will be decent. This looks to me like potentially 9 figure market
Speaker 6:cap on ripped
Speaker 3:it on base.
Speaker 1:Yeah. Well well, seriously. Like seriously, I I you know, on these ones that I posted like this one I posted yesterday Yeah. Now has an $84,000 market cap. It's done like $4,000,000 in volume and I earned 1% of all of the volume.
Speaker 1:And so that means I've earned like what? $4,040,000 dollars?
Speaker 2:That's insane. Right? So you get a viral That doesn't like like economically fair.
Speaker 1:Well, but think about this. The place where that value comes from is the fact that your content is valuable. Right? How have these
Speaker 2:platforms built
Speaker 1:Yeah. Multi $100,000,000,000 businesses if the content isn't valuable?
Speaker 2:Running ads.
Speaker 1:But what's bringing you there?
Speaker 2:The content. And then they pay you to bring more content because
Speaker 1:is a way of monetizing the value of the content. Yeah. Yeah. But the content itself is valuable. And what's happening on the base app now is that that value is being kind of figured out in a free market.
Speaker 1:Yeah. And then the the kind of the the economic off flows of that value are getting redirected
Speaker 5:Well, so we we
Speaker 3:love ads Yes. At this show. Will we be able to see ads in the base app?
Speaker 2:I know
Speaker 3:you guys acquired Spindle.
Speaker 1:Well, we we we stay tuned in the in the next in the next wanna run I wanna run
Speaker 2:some I think that I I Well, talk about
Speaker 3:talk about integration in the in the kind of app mini apps.
Speaker 2:Mini apps.
Speaker 3:I Yeah. Dan from Farcaster has has been on the show. I know you guys have some integration with with the Farcaster Yep. Network. Is that right?
Speaker 1:Yeah. So the whole social feed, all of the connection graphs, know, followers and following, it's all powered by So When you're posting content, it's powered on Forecaster. When you're coining content
Speaker 2:That's interesting. That's powered
Speaker 1:by Zori. It's another protocol. What we've done with the base apps We're all together.
Speaker 5:Is we brought
Speaker 1:them all together.
Speaker 2:That's cool. Including Shopify.
Speaker 1:Including Shopify integrates. Including XMTP, which is powering messaging. They just raised $20,000,000 series b.
Speaker 2:Okay. Cool.
Speaker 1:And they're an incredible decentralized messaging protocol that is powering secure encrypted messaging with agents Yeah. In chat. And so one of the really cool things, I don't know if you guys saw it in the demo yesterday, is you can be in
Speaker 3:a chat with
Speaker 1:your friends. You can just like drop a bet in there that Yeah. You can say to agent, hey, let's bet $5 that the Dodgers are gonna win tonight.
Speaker 2:Okay. That's
Speaker 1:then it's immediate bet. Powerful. And then you can say, hey, send $10 to all my friends. Sure. And it just works.
Speaker 1:Built on this platform and you have these open protocols that are working together. And so, to your point, we built on Forecaster because we believe in building an open protocols. And one of the things that open protocols enables is it enables other people to build on top of
Speaker 9:them.
Speaker 1:Yeah. And so, this is where the mini apps come in is because we've built in this open way. Now, anyone can build a mini app and it just shows up in the app. And here's another one. I don't know if you guys have seen this, but this is when you open the base app today
Speaker 3:think the It's
Speaker 1:DDBN. Which is like literally you can open this up and we're gonna be on the live stream here live now.
Speaker 5:There I Oh, wow. Yeah.
Speaker 1:There we are right there.
Speaker 2:It is so cool. It's all good.
Speaker 1:But one of the really cool things
Speaker 3:about And and to be clear, this this was organic Third party. Just third party.
Speaker 1:And and you have some new sponsors. I don't know if you guys realize this, but you have a bunch of crypto brands here that have now gone and said, hey, we wanna sponsor you. And Bracket, for instance, this is sports betting on base. It's awesome. It's so fun.
Speaker 1:You can interact with an AI jet. But the thing Our
Speaker 3:lawyers were gonna Our lawyers are like bloodhounds. They're gonna they're gonna be like chomping at the bit
Speaker 1:really incredible about this app is that it's all connected. And so I can actually tap in bracket and I'll be like, okay.
Speaker 2:Oh. Okay. Yeah. Hey.
Speaker 3:Stay one.
Speaker 1:Stay Oh my god. Come on, Jesse. What's going on here
Speaker 2:with Yeah. This mini Yeah. And and in and in theory, yeah. This is this is the start of the auction the auction driven
Speaker 1:It happens.
Speaker 2:It happens. But but but but this is this is the start of the auction driven ecosystem that actually that actually results in real transfer value. Real real value is created at some point. So this is
Speaker 1:new ad flows through I like bracket. Woah. Now bracket is right here.
Speaker 2:Okay.
Speaker 1:And then I'm like, okay. I'm just gonna buy bracket. And I'm be like, cool. Let me buy $5 of
Speaker 2:bracket. This is not financially driven. This seems this seems like the
Speaker 3:thing that's fun is like it's just wildly chaotic. It is entirely new surface area. Coinbase has never been about chaos but and and I'm not saying that base is but creating an environment that's just like a free for all decentralized, it's open. So yeah.
Speaker 2:Mean, you said that the goal broadly is to get a billion users on crypto.
Speaker 3:Crypto On chain.
Speaker 2:On chain. That's There go. Phrase. Give me the state of the union, where are we today on that journey? Yeah.
Speaker 2:Like, what are the different buckets and how big are they?
Speaker 1:Yeah. So we're trying to build a global economy Mhmm. That increases innovation, creativity, and freedom. And the metric that we use basically to measure that is do we have a billion people on chain? Yes.
Speaker 1:And of course, I'm gonna get 5,000,000,000 people on chain because we're get everyone who has an internet connection on chain.
Speaker 2:Let's go.
Speaker 11:But a
Speaker 1:billion's a nice number to make it repeatable. I'd say that when you look at the data today, there are hundreds of millions of people who hold Bitcoin. Yeah. Globally around
Speaker 2:the Hundreds of millions. Yeah. Hundreds of lot
Speaker 1:of people hold Bitcoin. Yeah. Yeah. Yeah. Like Bitcoin is very well used, but it's not something that people are using their day to day lives.
Speaker 7:Yeah. Yeah.
Speaker 1:Yeah. I'd say there's probably tens of million people around the world who are using stable coins. Yep. And then I think we're in the the millions of people right now who are really starting to use these on chain products. Okay.
Speaker 1:And that's across base. It's across Solana. Sure. We're seeing innovation everywhere. Yeah.
Speaker 1:You know, we like to work with everyone. We think about base as a bridge, not island. We're actually connecting with everyone Yeah.
Speaker 3:And figuring
Speaker 1:out how we can help them be successful. But I think it's still really really early days and the goal with the Base app is to like Yeah. Kick up the next kink
Speaker 2:in growth. So my question is like, when we're when we're following the the chat GPT story, there's obviously DAUs. Yep. But the chart that everyone's obsessed with right now is that chat GPT minutes per day is skyrocketing. It's like thirty thirty minutes per user per day, something like that.
Speaker 2:We're seeing lots of queries go up. My question is like, with financial products, I I do think that there's a there's a benefit to having a lot of people own Bitcoin. I think it's an awesome network of a check on authoritarianism. Yep. It's awesome.
Speaker 2:But, like, I don't know that I should be, like, interacting with Bitcoin daily. Yeah. But what are the other metrics downstream to to to, like, to like quantify like whether or not someone's on chain? Because like if someone's like like if I'm if I'm in my bank account
Speaker 5:Yeah.
Speaker 2:You know, messing around with dollars all the time, I'm actually probably unhappy.
Speaker 1:Yeah. Yeah. Well, the first thing I'd say is that definitely Coinbase is a traditional financial product. Where they're growing, they're trying to be the best for trading. It's awesome.
Speaker 1:They're making such good progress. So excited about the retail Dex integration, which is basically making it so that anyone Coinbase can buy any asset on Base. Yeah. Just works. Listed.
Speaker 1:I'd say Base though, we don't really think about it as a financial product. Okay. There's money involved Because we're out. Money is a part of everything. Of course.
Speaker 1:But it has social ads core, it has chat, it has apps. And so people are gonna come to Base just like they come to their other apps. Time on site should we're looking at MAUs. We're looking at Yeah. We look at kind of two things.
Speaker 2:Look Down at MAUs and all that.
Speaker 1:Yeah. Down MAUs and we look at like weekly active users and then we look at weekly transacting users.
Speaker 2:Sure.
Speaker 1:Where it's like, are you actually doing a transaction on the chain? Yep. Where it's like buying something or sending money to a friend or something like that. And so the active user is kind of an engagement metric Yep. And then the the transacting user is like a deeper engagement.
Speaker 2:Yeah. Yeah. Yeah. So higher use of the actual product would not be a bear case like it is with my you know my traditional financial app with which I'm opening Yes. Probably a problem.
Speaker 2:I'm probably like owe someone money or Exactly. Overdrafted
Speaker 1:or something. Exactly. And the really incredible thing about this kind of conversion rate of active to to transacting is we have the data of before and after where like it was really just a money app before and now it's a real social product. But people are doing all these things with money. Yeah.
Speaker 1:And we're seeing way higher initial user conversion rate to actually doing something on chain.
Speaker 2:That's awesome.
Speaker 1:Because now it's not like, oh you have to go like make an investment decision.
Speaker 11:It's like
Speaker 1:you can like your friend's post. Yep. Right? Or you can like you know tap to pay at a store that you're going to. And that transition from a speculative thing which is so important and such a big important part of base in the crypto economy Yeah.
Speaker 1:To a daily thing that also has like way bigger TAM in terms of the number of people who do social products and other things on a daily basis. That's that's really the shift we're trying to make.
Speaker 2:Yeah. It's super cool. Like the you like, we know that the everything apps work elsewhere.
Speaker 5:Yeah.
Speaker 2:They don't work in America for some reason. This feels like an end run around a different strategy to try and
Speaker 3:make Everything app for a specific subculture. Right?
Speaker 2:Right now. But For now.
Speaker 3:You know?
Speaker 2:A billion people, is that a subculture?
Speaker 1:And what I'll say is we were just at Eirwan. I just spent two hours at Eirwan and people were giving out free juice. I was filming
Speaker 3:Two. We got
Speaker 1:some good content coming later. Great. And I was just talking to people about the juice in the app. And when people hear, especially like millennial gen z creators, when they hear, do you wanna join a free social network where you can get paid to post? And do you want a free juice?
Speaker 1:They're like, hell yeah. I'm like, I've been posting on other social networks for a long time and I've never gotten paid.
Speaker 2:Okay.
Speaker 1:And so that hook of your content is get
Speaker 3:You get paid.
Speaker 11:And you can
Speaker 2:get paid
Speaker 1:because that value is gonna get unleashed by the free market. Yeah. And then we're gonna distribute it on crypto economic rails
Speaker 2:Yeah.
Speaker 1:That is next generation internet platform.
Speaker 3:I'm fired up. Well,
Speaker 2:good luck. We gotta get to our next guest. Thank you so much
Speaker 1:guys stopping by.
Speaker 5:This is fantastic.
Speaker 7:Can we
Speaker 5:get a
Speaker 1:gong hit on the way out?
Speaker 3:Here. Gong
Speaker 2:hit. Gong hit. Hit. Let's go.
Speaker 1:Get the Base app. At base. App, you can get on the wait list from me letting more people on every single day.
Speaker 2:There we go.
Speaker 3:Founder mode.
Speaker 2:Talk to you soon, Have
Speaker 1:a good one.
Speaker 3:Great chatting. Do
Speaker 2:it. Talk to next. We have Higgs Field, Alex from Higgs Field AI. We've been using Higgs Field AI to generate crazy photos. Jordy posted one of I was on a horse.
Speaker 1:A horse.
Speaker 2:The horse had a little bit of a long neck but otherwise, photo real. And the facial reconstruction like the it nails the face really really well. I I'm exactly sure how they do that. I want Welcome to talk to to the team. Welcome to
Speaker 3:the Yeah. Higgs Field. We have a lot of amazing people on today. I have been incredibly excited to speak with you. We were we were just talking, don't know if you caught it, I posted a an image generated by Higgs Field a couple days ago.
Speaker 3:I think most people still think it was real. It was a completely ridiculous image. It was like this like cinematic upshot of me on a horse that had I I didn't know why people didn't catch the neck was was quite a bit bigger than a regular horse's neck but
Speaker 2:It was great.
Speaker 3:Clearly a breakthrough. Yeah. It it it was the first time that I've seen an image generation product and realized that I think you guys are are have probably already started to take over Instagram Mhmm. Style content. But but really disrupting the potentially disrupting the Instagram boyfriend market if people can just generate infinite images of themselves, Instagram boyfriends will have nothing to do.
Speaker 3:But great to have you on the show. Would be great to get a quick background on yourself and the company, and then we'll get into a bunch of other stuff.
Speaker 8:Great. Thank you very much for the kind words. Definitely, it's great to be here. I thank you for the invitation. So quickly about myself, I'm a veteran in the video generates for AI space.
Speaker 8:I built maybe some of the most iconic products in that space. Maybe you remember Snap, filter face filters.
Speaker 2:Oh, really?
Speaker 8:Which No way. Totally.
Speaker 2:That's amazing.
Speaker 8:Yeah. There were, like, billion people throughout the world who played with that. Disability. And this was region AI. Right?
Speaker 8:And the one the models were, like, thousand times smaller than they are today. And although this product was specifically targeting, like, augmented reality use case. So, basically, overlay on top of the existing camera. Yep. With with all these learnings which I got from my exciting times at Snapchat, We started Higgs field with a way bigger ambition is to create camera of the next generation.
Speaker 3:Yep.
Speaker 8:Even today, we can see that there is an emergence of UGC contents. The quality, unfortunately, it goes down. Mhmm. And with the and with Hicksfield, we create a new ways to tell stories, helping creators and brands to get attention on social media.
Speaker 2:What's the key insight? Do you think how important is it to create a great image generation model? Just scale. You just need to throw a ton of compute versus changes in the algorithm. We've heard rumors that images in chat GPT isn't pure diffusion.
Speaker 2:There's some transformer architecture in there, some different layers. I've started to suspect that there are different layers in some of these where there might be a different neural network or different different system to put text on top so the text is really clean? Are we kind of recreating Photoshop at a certain level? Talk to me about the actual technical infrastructure to the degree that you can.
Speaker 8:Totally. First of all, I think it is important to admit that today, we are early in our journey with video AI technology. Mhmm. I think Higgs Field is probably the first example of the technology platform, which helps to create compelling content for social media. The next step is going to be is to is going to be to build a reasoning engine on top of that.
Speaker 2:Mhmm.
Speaker 8:So the so let's say you post a video. The system is gonna suggest you and analyze your accounts and actually provide you with more suggestions what to post. And, eventually, I think we're we are going to find ourselves in two years in in a new world version of the world where most of the content out there is AI generated. There is no way to stop that. Mhmm.
Speaker 8:And on on our sides, we do our best to provide a simple interface so that non AI users like, let's think about market of social media professionals of tens of millions of people so that this broader user base can actually tap into the power of GenerousFi technology.
Speaker 2:Mhmm.
Speaker 8:And I think we will see that the models are gonna get way better than they are today. It is true that various research labs, they do experiment with various architectures. We found that our post training techniques and allow us to substantially differentiate from the competition. And we do believe that the general quality of the technology is already there to surpass, like, average human produced comments.
Speaker 1:What
Speaker 2:I have this one eval for AI image generators where I ask it to create a a Where's Waldo? And and no system's been able to crack it. And I think it has something to do with the density of information in a proper Where's Waldo? You'll typically see hundreds of little characters doing very intricate things. And so, it's very clear that the artists that create the actual Where Waldos work at a very small scale and they actually piece together the full image like it's a puzzle.
Speaker 2:That's something that I feel like could be solved with a reasoning layer on top. You understand that you're trying to create something that's really really layered, and so you need to kind of create tiles and then blend them together. Is that but but this gets into the question of, like, how are we going to generalize and scale reinforcement learning in LLMs and agentic workflows? Is there a similar path that we're going down in terms of image generation?
Speaker 8:Yeah. This is a great question, by the way. I think this is a a trillion dollar question, which which you just asked, which is we all saw the power of reasoning engines with maybe models like o three, and then we see that at Grok four, they actually spent on reinforcement learning more than they spent on the pretraining stuff Yep. Stage. Right?
Speaker 2:Where is the market right now in terms of pretraining, post training in images in your estimation?
Speaker 8:Yeah. I do believe that in the video AI space, we are relatively early. It's probably we still see that the post training stage in the video or video AI models can be maybe twenty, fifty times lower compared to the pre training stage.
Speaker 2:Wow. Although Yeah.
Speaker 8:But we are really just scratching the surface there.
Speaker 1:Sure.
Speaker 8:I think then the future is building the video reasoning engine, and this is a trillion dollar question because Yeah. This will l because think about the the brands out there. Yeah. Today, it is today, what we are seeing is that brands start to act and the agencies, they start to actually experiment with various models.
Speaker 2:Mhmm.
Speaker 8:And, primarily, we all rely on our stereotypical understanding of the customers and some maybe qualitative data which is available out there. Mhmm. I strongly believe that with this video reasoning engine, then the way how how the stories are told is going to be completely different. Instead of just running one video, we can run hundreds of the videos out there and AB test them and see which one performs the best. And today, there is there are only a few top creators who actually do that.
Speaker 8:If you look at camp at mister beast and similar size of the creators, they do AB test thumbnails very aggressively. We all know that.
Speaker 1:Yeah.
Speaker 8:They actually AB test the hooks. So far, this privilege is only available for larger teams who can who can actually do that, who have the manpower to do that. And the next generation video reasoning engine will empower everyone to do that, which is going to boom to the boom of
Speaker 2:AI generation. What what you're talking about is basically, like, r l ing on humanity with human graders, which is the algorithm and lights, and and that's effectively what the, like, the mister beast algorithm is doing. My question is, like, is there a way that we can bring that into the data center? Because if it stays on Instagram, if it stays on YouTube, it's probably pretty rough for you because Google and Meta are gonna have an advantage there. But if you can figure out how to do RL with verifiable rewards or something that looks like a rubric for grading, you know, and finding errors, are we going back to the generative adversarial network era where you'll have two competing models to determine like, whenever I generate something with VO, it's always like, car's driving, looks amazing.
Speaker 2:Then all of a sudden, I'm looking at the front of the car, the car's driving backwards. And clearly, the model is getting confused, but we need maybe, like, a detector for that. But how do how are we actually gonna do RL at scale in imagery?
Speaker 8:This is a good question. So I think the first step is exactly I mean, the first step is going to be reinforcement learning with AI feedback. Part of that, we already do at Higgs Field. Sure. Obviously, at the post training stage, not yet at the inference stage just because of the cost associated with that.
Speaker 2:That makes sense.
Speaker 8:So we have to train video generation model in a in a way that it's sort of competing with video understanding model.
Speaker 1:Mhmm.
Speaker 8:And, like, at Higgs field, we we we cannot go and label millions of the videos. That's why we have a set of powerful agents for video understanding
Speaker 2:Mhmm.
Speaker 8:Which help to tune the video generation process. Yep. But this is the process in the vacuum itself. What's gonna be powerful is when we condition the outputs of the model and train the model based on the engagement data from the social media. Yep.
Speaker 8:First is gonna be a number of likes and number of comments. Although if we look at meta ads, we see that they provide a very detailed breakdown and drop off second by seconds. Mhmm. So training the models based on on these outputs is going to lead to complete the next level of, reasoning and success rates for their end customers.
Speaker 2:Cool. Alright. We we have another one in
Speaker 3:I know I know we're we're totally over. What what happens to the legacy Instagram influencer that has built a business basically on MV? They're constantly traveling around the world at the best hotels, on boats, in private jets. What happens when anybody can be on a private jet on on a platform like Instagram or on a yacht somewhere? Have you thought through kind of the implications for the tech across different categories of of content creators?
Speaker 8:Hopefully. So first of all, I I I need to admit that we're a technology platform first and foremost. Although we think about ourselves as a scientist for, and we are constantly monitoring and listening to to the creators and how they use the technology. And I I I cannot bring up the names out here. Although, like, some of the top 50 YouTubers in the world, they actually wanna get reads of the team and build own agency of AI influencers, to be honest.
Speaker 8:That's they they actually they have a bunch of ideas which they wanna sell, and they don't wanna condition their existence on the social media just to their likeness today because people just get are getting older, and sometimes they get irrelevant. We have seen many examples of that on social media. And creators actually wanna create those digital agencies where they can they where they can express all their ideas through various synthetic AI influencers. And they can use Hixl platform to do that.
Speaker 3:Yeah. It's very, very wild time. Let's have you back on again soon. This is fascinating.
Speaker 2:Yeah. We'll talk to you soon. Thanks so much
Speaker 9:for hopping on, Alex.
Speaker 2:Thank you.
Speaker 3:Talk to
Speaker 2:you soon. Let me quickly tell you about public.com investing for those who take it seriously. They have multi asset investing, industry leading yields, and they're trusted by millions. We have Billy from Regent also calling in from Reindustrialized. Sorry to keep you waiting, Billy.
Speaker 2:Great to see you. Every time we talk to Billy, he's in a far flung part of the world. We're working to bring him in from the waiting room, and he is sideways. Can you turn your camera?
Speaker 12:Yeah. Can go vertical. That is possible.
Speaker 1:Here we go.
Speaker 2:There we go. We're going.
Speaker 1:Where are you, man? You're in
Speaker 2:a cabin? Explain. Join you from a
Speaker 12:sea glider. Look at that.
Speaker 1:No way.
Speaker 12:It's comfortable. Here
Speaker 2:we got we got plenty of leg room.
Speaker 3:Very incredible.
Speaker 12:We got internet. This is the future.
Speaker 2:This is amazing. Amazing. Wait. Wait. So wait.
Speaker 2:Are you is this like a demo or are you actually in
Speaker 3:I do believe that's a screen behind me.
Speaker 2:Behind you? This is the demo. You guys
Speaker 1:are quite perceptive over there. Okay.
Speaker 2:We just talked to that AI generated guy who says all this will be fake in two years. So, you know, I I don't know what to believe at this point.
Speaker 12:We're building hardware in the real world, guys. We're at a reindustrialized conference.
Speaker 2:You for bringing me back to the real world. How is reindustrialized? Give us the overall update on region.
Speaker 12:It is awesome. Like, hardware is cool again. Like, building real stuff is cool. Atoms are cool. So it it's awesome to be here for this.
Speaker 12:Yesterday, we just announced the launch of Regent Defense here at Reindustrialized, which is a big step for the big step for the business.
Speaker 2:Congratulations. What is Regent Defense?
Speaker 3:Yeah. What what are the what's the immediate application Yep. Of the glider in a in a defense context?
Speaker 12:So Regent's actually been doing defense for years. This is sort of a a growth of the business we've we've already been doing. Basically, everything is about, moving around island chains as our our key conflicts and theaters are in the Indo Pacific. So it's going back to World War two style tactics. It's about naval operations.
Speaker 12:It's about being able to move around island chains, logistics from the head of the Marine Corps and throughout the services, underwrites the success of that naval campaign. So turns out that all the things that our commercial customers like about Seagliders, the the high speed, low operating costs, you know, ease of operation and in the DOD space that were hard to see. We fly really low over the water, so it's hard to pick up on some long range radar systems. Makes it a really perfect fit. So we've been on contract with the Marine Corps for a couple years now, and now we're expanding as we get into our full scale prototyping and expanding that product portfolio to meet the need.
Speaker 2:Very cool. Incredible. Anything else?
Speaker 3:I think that's it. You for this thank for this demo.
Speaker 11:This is
Speaker 1:the this is the
Speaker 3:best call in, the best guest call in I think we've had.
Speaker 12:Guys, we gotta get you on the Seaglider in Rhode Island at some point too. We're doing the next call in from the we we have real hardware.
Speaker 3:We'll do the whole show. We'll do the whole show from the glider. Hear it's very smooth. You know? It's perfect for for live podcasting.
Speaker 2:Starlink on board yet?
Speaker 12:We'll we'll put Starlink on board for a TBPN episode.
Speaker 2:There we go.
Speaker 12:I love it. It's there.
Speaker 2:It's there. Awesome. Fantastic.
Speaker 3:Congratulations to you and the team on the progress, and say hi to everybody at, Reindustrialize for us.
Speaker 12:Will do. Thanks, guys.
Speaker 2:Enjoy the rest of the conference. We'll talk to you soon. And in the meantime, let me tell you about 8sleep.com. Get a pod five, five year warranty, thirty night risk free trial, free returns, free shipping. Code.com.
Speaker 3:And
Speaker 2:we have our next guest joining the stream. I'm going to guess that it's Jonathan, but I'm gonna make sure once he joins. Welcome to the stream. How are you doing? Did I get that right?
Speaker 2:Yes. Jonathan.
Speaker 3:What's happening? Security.
Speaker 1:Hey. Sorry.
Speaker 3:People call me J
Speaker 6:Mo, actually. So Oh,
Speaker 1:J Mo.
Speaker 3:What's up? J Mo.
Speaker 2:Us the news. I hear we you you got some good news. Break it down for us.
Speaker 6:Yes. We are coming out of stealth launching a new company called Confident Security. Congratulations. It's about providing confidential AI. Money?
Speaker 6:We raised 4,200,000.0 with Decibel. Congratulations. That's our comments. Congratulations.
Speaker 3:There we go. Why is confidential AI important? I can I can imagine a bunch of reasons? But what what was the kind of catalyst to start the company?
Speaker 6:Yeah. I think, you know, unless we do some work, I think we're gonna have Cambridge Analytica times like a million essentially unless, there's just too much incentive for folks to train on data, and people need to care about privacy. So we thought, you know, Apple shouldn't just be the only ones providing privacy. Everyone else should do it too.
Speaker 2:Give me some concrete examples of how to use the product. What data specifically am I keeping secure? Is it stuff that's on the web? Or, because I feel like if I have an air gap data center somewhere with a whole bunch of hard drives, there's no crawlers that are getting to that.
Speaker 6:That's right. If you are taking that air if you're using the air gap data and you have your own GPUs and it's completely in there, you might care about various users inside your air gap environment not seeing all the data, you know, standard like top secret versus secret type of stuff. Mhmm. But this is, you know, you're you're an employee at Pfizer and you upload a PDF to OpenAI that describes how you do drug discovery. Maybe you care about that secret.
Speaker 6:Maybe you care about how it's gonna be used. And after the recent OpenAI court case where they were forced to retain deleted data,
Speaker 1:you know Yeah.
Speaker 6:I think people are being a little cautious.
Speaker 2:So how does yours so how how do you actually plan in plugging in to companies? Like, how does the product actually get installed and used on a day to day basis?
Speaker 6:So it requires two parties. One party who's running the server, to install our wrapper around it, and then the other party who's, like, making requests to that server to use our SDK.
Speaker 2:Mhmm.
Speaker 6:And then essentially, you can think of it as, a very specialized form of encryption where you can only decrypt the data that you've submitted to the server if you've met some constraints like you don't log the data, you don't train on the data, no one has access
Speaker 1:to the data, all that type of stuff. Mhmm.
Speaker 2:And is that just like enforced at an engineering level or enforced at legal contractual level?
Speaker 6:It is a technical level. Great question. Okay. And that's what's different. Right?
Speaker 2:You can
Speaker 6:make promises that say you want to train on the data, but we make it's very it's a technical guarantee and it's essentially a bunch of fancy cryptography that makes that guarantee. So Interesting. We actually offer unlimited liability and indemnification for data breaches and misuse because we're so convinced that you cannot we cannot see the data. No third party can see the data.
Speaker 2:So what's the go to market like? You you mentioned example of like a big biotech company. Is that the most obvious customer or are there other segments that are logical?
Speaker 6:Biotech, legal, finance of course, defense and government. And not just not just, like, pure defense, but, you know, local jurisdictions, states. They're all trying to figure out how to deal with, you know, freedom of information. When have you made something public? Did you was it too soon?
Speaker 6:This helps, you know, manage all that stuff. Privilege for lawyers, same problem there. Trying to figure out, well, if I give my data to OpenAI, have I disclosed it and it's no longer subject to privilege?
Speaker 2:Yep. Make that a character.
Speaker 3:Super interesting.
Speaker 2:Close close it out with how big is the team? Where is the team size going? What are you hiring for? What comes next?
Speaker 6:We're about six people right now and we've been building building
Speaker 2:building building.
Speaker 6:And now with the launch we're ready to start selling and so our focus is bringing on sales people. Yeah. I've done two previous companies and I've every time I've learned that I should spend more on sales. So
Speaker 13:that's what we're doing.
Speaker 2:Interesting. Good takeaway.
Speaker 3:That's good. That there there's gonna be that's the environment that a great sales leader or individual contributor wants to join.
Speaker 2:I mean, takes a lot of technical CEOs like a a while to actually get through that. So it makes sense that you're in your third company because like yeah. A lot of people learn that lesson late. Right? Awesome.
Speaker 3:J Mo, thank you for joining.
Speaker 2:Thank you so
Speaker 3:much for joining.
Speaker 1:Come back on when you have news
Speaker 3:and thank you for doing this.
Speaker 2:We will talk to you soon.
Speaker 3:Let me kiss. Yep. Cheers.
Speaker 2:Let me tell you about Wander. Find your happy place. Find your happy place. Book a wander with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning and twenty four seven concierge service. It's a it's a vacation home, but better
Speaker 3:folks. Next, we have Contextual founder of contextual AI.
Speaker 2:Welcome in studio. Studio. How are doing?
Speaker 3:Bring him in. What's happening?
Speaker 2:Also, if I have this correct, the inventor of Rag. Correct?
Speaker 13:I'm one of the the authors of the Rag paper.
Speaker 2:Okay. Okay.
Speaker 13:So yeah. That was a a team effort. Lots of folks and it's a long history of, you know, research that has gone into that.
Speaker 2:Yeah. Give me the state of the art.
Speaker 3:Very, very humble. Yeah.
Speaker 2:A man who invented rag by himself
Speaker 1:in a in a in a In a cave with scraps. Scraps. Yeah.
Speaker 2:Give me the state of the union on on rag. Some people are saying, oh, just use a bigger context window. Like, what are what are companies actually using RAG for on a day to day basis? What's the state? And then what's the shape of the industry that's popped up around the technology?
Speaker 13:Yeah. So the the RAG is really a very simple idea. Right? It's about having Gen AI work on your data. Mhmm.
Speaker 13:And you do that through retrieval. That's the r, and you then use your retrieval results to augment. That's the a. Your generative AI. That's the g.
Speaker 13:Yeah. So it's a very simple idea. How people do reg right now is radically different from what we did in the paper originally. Mhmm. I think the the buzzword these days is about context engineering.
Speaker 13:Mhmm. So how how do you actually give language models the right context so that they're they can do their job? And as it turns out, all the language models are pretty good these days, and there isn't that much of a difference between, you know, your Clog and your OpenAI models or Gemini. If you give it the right context, then it can solve the problem. If you don't give it the right context, then you can have an amazing language model, but it's gonna fail.
Speaker 13:And so that, I think, is is an opportunity that a lot of companies are are looking at now. How can we make sure that this this context layer really works?
Speaker 2:Do you feel like there's a rag step or layer in the typical deep research projects products that I'm using on a day to day basis? I feel like it's mostly, like, going out to the web searching and then kind of just, you know, summing all this stuff up. But I can't tell if it's actually like the the base of rag is like embed all of that into weights and and then and and and search over it. But is that happening at at the state of the art right now?
Speaker 13:I think so. But you're right. A lot of it is web search. Yeah. And if you wanna do web search efficiently at scale, then you probably use simpler algorithms.
Speaker 13:Mhmm. And so things that aren't that involved. But even web search very often uses embeddings Mhmm. And clarity search there. So you could argue that web search is also just
Speaker 2:Interesting.
Speaker 1:Rag. Good.
Speaker 2:Is why is search so bad right now? I feel like I feel like I can't search my email for anything, and Google
Speaker 3:has I mean, like trying to find something in iMessage.
Speaker 2:But, yeah, I feel like search has just become like really hard. But then at the same time, I'm like having my mind blown by LLMs and deep research products, but I don't wanna wait fifteen minutes just to search my email. But maybe that's what I need to do. Maybe that's the future looks like. Like, what is going on there?
Speaker 13:Yeah. I mean, that's a hard problem. Right? But, I mean, AI should be able to search your inbox for you and
Speaker 1:just get
Speaker 13:the right answer. Right?
Speaker 4:Yeah. That's
Speaker 13:the goal. I I think it's happening. It's just search is a really hard problem to do. You you don't wanna really do it in a single step. So so the way you do proper retrieval is multistage, sort of cascading with smarter and smarter models that look at what might be a relevant result.
Speaker 13:But you're right. If if you retrieve the wrong things, then you can never give the right answer. Yeah. So that's a big big open point.
Speaker 3:Where are you guys focused today?
Speaker 7:I know there's a number
Speaker 3:of different use cases.
Speaker 13:Yeah. So the the the the use cases we're we're looking at are are really your bread and butter use cases for REG, so answering complex questions on complex documents. In our case, we scale to millions of documents, which is unusual. So one of the most common misconceptions about REG is that people think that it's easy, which is actually probably true if you have, like, two or three documents. You understand the use case.
Speaker 13:It's not that complicated. But when you go to the real world and and you talk to some of of our enterprise customers, they have very difficult problems. The data is all over the place. It's very complex data. There are millions of documents that it needs to work on top of, and then search breaks down.
Speaker 13:So you can't give the right answer even if you have a great language model.
Speaker 2:Yeah. I mean, the the the scale of data at some enterprises is probably, what, seven orders right now. I mean, I imagine, like, the number of emails sitting in Gmail inboxes across the entire network is is is way beyond millions. Fascinating that is also to your
Speaker 13:earlier point about, like, long context models. You can't fit all of that in the context of a language model. Need to retrieve all.
Speaker 2:No way. What's the state of the business today? How big are you? Like, kind of what what are the new challenges? What are the next milestones?
Speaker 13:Yeah. So we're seventy, eighty people working on a a lot of interesting problems that are kind of nice,
Speaker 11:kind
Speaker 13:of across the across the board, trying to expand into to different use cases as well. So beyond the traditional rank use cases, looking at things like root cause analysis, code gen because, you know, code gen is very hard and also often requires technical documentation that you don't want to incorporate in your code gen. So the yeah. Making a lot a lot of good progress on on very interesting problems.
Speaker 2:Very cool. Well, thank you so much for stopping by. Love to have you back for a longer conversation. Yeah. Let's do it again soon.
Speaker 2:Hope you have a great rest of your day. We'll talk to
Speaker 1:you soon.
Speaker 13:Thanks, Ryan. Cheers.
Speaker 3:Bye. Good to meet you.
Speaker 2:Let me tell you about Bezel. Go to getbezel.com. Your Bezel Concierge is available now to source you any watch on the planet. You like
Speaker 3:enterprise agentic workflows You'll love might like find watches.
Speaker 2:And up next we have OpenAI. Big launch today. We are gonna break it all down. Welcome to the stream. How are you?
Speaker 3:I think we got caught up on guests. We have two people. What's happening? Great to have you guys on the show. Hi.
Speaker 3:I will start by saying sorry about the sorry that Coldplay had to have a conference last night. Like, the the you know, it was hard to, you know, hard to predict.
Speaker 2:Launch anything on the Internet.
Speaker 5:I know.
Speaker 14:We we were just talking about this. Yeah.
Speaker 3:Well, we're here.
Speaker 4:I have no idea. He says it should at the beginning
Speaker 1:of year. Well, we're resetting what
Speaker 2:we're gonna do.
Speaker 3:You don't have to plan your launch schedule based on Coldplay.
Speaker 2:Yeah. Coldplay is out.
Speaker 3:Maybe it's something to keep in mind.
Speaker 2:Break down forward. Break down the launch. What is in? What should we be focused on now?
Speaker 14:So I used to work on Deep Research. Joss used to work on Operator. We both had our launches earlier this year. And I think after our launches, we realized that our products are very complementary. Cool.
Speaker 14:And so we've basically combined the best of both into this new product, ChatGPT agent. So ChatGPT agent has access to a virtual computer with a bunch of different tools installed. So it has text browser, visual browser, terminal, and it's able to do a lot of different things that you would do on a computer. So it's just, like, very flexible and pretty powerful model. We trained it using end to end reinforcement learning, like, our past reasoning models.
Speaker 14:And, yeah, it can make slides, make spreadsheets.
Speaker 3:That's cool. Yeah. What what initial use cases are you guys most excited about? Have you been using internally? What what kind of companies should be and and just individuals should be kind of taking advantage of it as of today?
Speaker 4:Yeah. I think so Deep Research, as I was saying, we we combined sort of Deep Research and to build this. Deep research was really good at research, like, having the best product out there in terms of or at least that that's what I thought, or I still think, in terms of researching. And then was there to take actions. Combining these two, you open up a lot of possibilities.
Speaker 4:You can do research. You can do actions. You can do research and then actions.
Speaker 3:And then
Speaker 4:on top of that, we added APIs. So, like, for example, if you have connectors, which we launched, I think, a couple of months ago, you can connect Gmail, Google Drive, Linear, and whatnot, all sorts of products. And combined with that, it becomes an extremely powerful research and action tool. So Yeah. For example, like, personally speaking, I've been using it a lot internally just to even talk with the code base.
Speaker 4:Like, I'm solving a particular problem. I'll connect it with GitHub. I'll ask it like, hey. Can you sort of go figure out what's happening in this code, which is a let's say a new code base for me. Mhmm.
Speaker 4:And then the model is also very natively multi turn, which means that I can just have conversations back and forth with it, which is not true necessarily. It wasn't true, for example, for our deep research model Mhmm. Which we released earlier this year. So it's really, really useful from a specifically from at work when I'm able to connect all these amazing tools and able to just understand what's happening, all parts of the decision.
Speaker 3:So Secondly
Speaker 1:Oh, sorry.
Speaker 4:I was gonna I was gonna say, like, personally, I also use it a lot. I think there is a lot of small things or big things that I have to do. I can do them myself. Give an example. My wife and I have a date night every Thursday.
Speaker 4:I forget to book it most of the time, and then I get in trouble. And then now with agent, like, you can schedule tests, etcetera. You can just say, like, look. Every Thursday, just go ahead and figure out. Give me five recommendations in the morning which are available, and I can just do it, show up on Thursday morning, just click it, and it's done.
Speaker 4:So things like that.
Speaker 2:Talk to I I once Deep Research came out, it felt like there was this little bit of a meme about, we have fifteen minute AGI. And I'm I'm trying to understand, I could imagine this this new product stretching that out to let it run if it's building a spreadsheet and scraping data from different sources and putting a whole bunch of different things together. I could imagine letting it run for like an hour and coming back, but it said you said it's multi turn. So what does the typical interaction look like? Is there a wider variance?
Speaker 2:I noticed in the in the latest revision of the Chattypete app, there's now a little like fifteen minute UI element next to deep research to kind of hint that, hey, you're getting yourself into a fifteen minute cycle. Obviously, there's lots of efforts to spin that to speed all of those processes up and that'll come. But what is what is the typical interaction time look like? Is this more asynchronous or synchronous or kind of you can do either? Like, how do you think about those trade offs?
Speaker 14:Yeah. I think our team in particular is really focused on solving harder and harder tasks that take people more and more time.
Speaker 1:Mhmm.
Speaker 14:So a lot of the agent tasks can take anywhere from, like, around five minutes to I I've seen it take over an hour.
Speaker 1:Wow.
Speaker 14:But a lot of times, these are tasks that would have taken humans many, many hours. Yeah. So I think, like, as our agents get better, probably the length of time they'll take to solve tasks will also get longer because just the task will become so much more complex. Like, imagine a task that takes a human, like, many days. Yeah.
Speaker 3:Yeah. So maybe so so a question I have is right now the agent can browse the web for me, do research, take action. I imagine the next step would be an agent like some like extension to it where as an example, I might say, hey, I I use GEICO right now. I wanna potentially switch. Can you go out and do research?
Speaker 3:Here's my Here's the cards that I have, try to find a cheaper price and then Or even call GEICO and negotiate a lower rate or, you know, you're traveling, let's say, and
Speaker 2:I need you're to cancel an old internet line on Spectrum right now and they only allow me to call during
Speaker 3:weekdays and Yeah. Other example, you're on a vacation and you wanna change your flight and you know you're gonna maybe have to like call sit on a wait. So like is is that the direction that you think we're going towards Mhmm. Where it can not just browse the web but then actually start to
Speaker 13:He's doing it.
Speaker 3:It's funny to think about because the voice agent would then just call and maybe it's talking to another agent on the other side. Yeah. But but, yeah, where where are we going?
Speaker 4:Yeah. Voice is definitely an interesting form factor. I think the way to think about where we're going is twofold. The first is what Isa just mentioned. I think we wanna continue to solve harder and harder and longer and longer tasks.
Speaker 4:I think today, we can solve, let's say, an hour or so of tasks. Hopefully, in future, we can solve multiday task, and it might take longer. It might might take shorter depending on how we're doing, but continuing to improve on reliability and complexity of tasks that we can continue to solve. So that's sort of a core part of what we want to continue to improve on. Second part, the GEICO example, for example, the one you gave, technically, you can do it today, not with voice, obviously.
Speaker 4:You can just type it in in agent, and it'll be able to essentially answer the query. You can log in with the virtual browser that we have on agent with your whatever Internet provider you use, and I think it'll be able to tell you things about what's happening there, what's not happening, what other alternatives might there be, and all of those things. Mhmm. But then at the same time, you bring up a really good point, which is, like, voice might be a very natural sort of way to do this in future, and that's a form factor Yeah.
Speaker 3:Then other
Speaker 4:we want to evolve.
Speaker 3:Other other companies introduce voice as an intentional point of friction, like, this sort of call to cancel.
Speaker 4:Totally. Because
Speaker 2:they know never do that to me.
Speaker 3:Yeah. They would never do And that to me, so that that to me feels like this met you know, if I can go into a web app and just click cancel or do something like that.
Speaker 2:Yeah. My question is about like the user experience of like having something that could take five minutes or an hour. How predictable is that? I've gotten in a great pattern where I expect deep researches to take fifteen minutes. And so, I know when to go to deep research and I'm gonna come back later and it's great.
Speaker 2:But if there's some variability there, is it gonna send me a push notification when that's done? Is that how that works? Like, how do you train the user to get the best experience?
Speaker 14:Yeah. I will send you a notification.
Speaker 1:I
Speaker 14:think actually the fact that deep research always takes the same length of time is probably I don't wanna say a bug, but
Speaker 2:I think of it as a feature. Not the end stage.
Speaker 7:I think of it
Speaker 1:as a feature. Yeah. I I
Speaker 14:think for as long as it needs to think.
Speaker 2:Totally.
Speaker 14:But I think for deep research, it always just thinks for a really long time even if you ask what the weather is.
Speaker 1:Yeah. That's true.
Speaker 14:So I think that's a better middle state, I think that this model is, like, a step towards that, but I think it still will think for too long on, like, really simple queries.
Speaker 1:Yeah. Takes too much Yeah.
Speaker 2:You're totally selling deep research short. Sometimes I ask you what the weather is, and I want the history of weather from start to finish and what it is tomorrow and yesterday, and I want the history of meteorology and how the doppler 3,000 works. I want everything. I love that
Speaker 1:about DeepReduce. My favorite.
Speaker 3:The use case that I'm sure that will immediately start happening that is pretty hilarious to think about is a student that just says, hey, these are the three websites that host the homework that I have to do. Just
Speaker 1:do that.
Speaker 3:Proactively go to the website, figure out the homework, create a Yeah.
Speaker 2:Be like, The check this check this homework.
Speaker 3:If if somebody wants to say that's not that's not AGI, I don't know what to tell them.
Speaker 2:Yeah. I don't know. What about other tool use? Jordy mentioned Jordy mentioned phone usage. You mentioned spreadsheet integration.
Speaker 2:What's kind of further down the stack of integrations that you've already announced that might be kind of underexplored or underappreciated at this point in time?
Speaker 14:To me, I think that the tool that we've given the agent is very general and powerful. Like, you can almost do anything that you need to do on a computer with this tool because it's browser and terminal, which you can you can do most things that might not be the most readable to a human. So I think that now it's it's about pushing the capabilities. Like, you can ask it to do anything in theory. It's just the agent won't be good enough to do everything you ask it to do.
Speaker 14:So I think that we just need to make it better and better using the tool it the tool it has.
Speaker 4:Yeah. I think the Frontier continues I think we as Isa said, the tool is extremely general. It can it has access to a browser. It obviously has access to a terminal, and we can give give it access to as many APIs as possible.
Speaker 2:Sure.
Speaker 4:That should be that should allow you to build whatever you want to do, generally speaking. Like, for example, you can totally imagine in future there's access to a voice API or whatnot, whether it's internal, external, depending on, like, how things go. Right? Like, you can have access to everything and build everything, but we still need to push. Like, it's still early.
Speaker 4:Like, we have Yeah. Not solved everything. It's still early. We still wanna make sure that we can solve the use cases with really, really high reliability, and that continues to be a pretty large focus.
Speaker 1:Yeah. Well, mean, if
Speaker 3:you say I'm excited. I mean, think of think about a world where you can give it access to your password manager Mhmm. Things like that Go around. That it just immediately can act We're just API integrations. Right?
Speaker 2:Yeah. So then the passwords don't even need to pass back and forth. That makes a ton of sense. Yeah. I'm excited for I feel like deep research maybe doesn't have access to images and chat should be tea yet, but I could imagine those being way like the reports being way richer if you can define them.
Speaker 2:And then sometimes when just generating like a general chart, I actually wanna use like a visualization library in Python and kind of going back and forth. So very cool to see it all kind of come together and very excited for where this is going. What's the rollout strategy? When can people actually start using this stuff?
Speaker 4:People everyone on Pro Plan should be able to use it by end of day today.
Speaker 2:Let's go.
Speaker 4:And we'll and we'll get it to Plus users over the coming days and then Enterprise over the coming weeks. Very
Speaker 3:alright. Well, congratulations on the launch. Super exciting. We're we're gonna turn this day around. It's it's now just about OpenAI agents.
Speaker 3:Ignore ignore all Coldplay memes. Ignore Coldplay. Well, you guys for joining.
Speaker 2:Thank you so much We'll for having talk to you soon. Cheers. Bye. Bye. Up next, have Dan Shipper, friend of the show over at every
Speaker 3:Who got early access.
Speaker 2:And he's been using
Speaker 3:agents and we're gonna get some feedback from John just spilled his base juice all over the table, all over the Feet. That's that's really disappointing. You're not gonna be able to read that. It's okay. On the way home.
Speaker 2:Lots of papers
Speaker 4:that I can
Speaker 2:I can
Speaker 3:Do we have Dan in the waiting room?
Speaker 2:Let's bring him in.
Speaker 11:Hello.
Speaker 3:There he is.
Speaker 1:How's it
Speaker 9:going guys?
Speaker 3:Great to see you.
Speaker 2:Every time you're on you're in a different
Speaker 9:when I'm not traveling.
Speaker 2:Yeah. Yeah. Yeah. Yeah. This is the first time.
Speaker 3:I like that. I like that light light up logo in the background. Very nice.
Speaker 5:Very nice.
Speaker 8:Thank you.
Speaker 3:Subtle subtle kind
Speaker 9:of Yeah.
Speaker 3:In home, out of home advertisement.
Speaker 9:That's that's what we're going for exactly.
Speaker 3:That's great. What's happening? What's on your mind, today? There's a lot going on.
Speaker 9:There's a lot going on. We're here to do a vibe check
Speaker 3:Vibe check.
Speaker 9:Of ChatGPT agent. So I was lucky enough to get to, hang out with it and work with it for the last couple days before it got launched, and I have a bunch of things to tell you about how it works.
Speaker 3:Incredible.
Speaker 9:So as your previous guest who are amazing, told you, it's sort of like deep research and operator had a baby, and it does some really cool things. So, the first one of the first things that I had to do is I had to go through all of our support emails and all of our feedback forum posts for the last, like, two months. So it's, about 1,500 support emails and maybe, like, 500 posts on our forum to gather for Quora, which is our email management AI app, to gather all of the customer archetypes of, like, okay. Who's posting? Who's a promoter?
Speaker 9:And then going and looking on their LinkedIn to be like, what's their job? You know, where do they go to school? All that kind of stuff. And put together a, like, long research report of who our promoters are, what the archetypes are, and who are who are detractors are and why they don't like us. So that's the kind of task that, like, obviously, like, I could have done or someone on the team could have done, But
Speaker 3:But it would have taken so long.
Speaker 6:So long.
Speaker 9:Yeah. It takes a long time. And it's the kind of thing that you almost want on, like, a recurring schedule. Like, you just kinda wanna see, like, once a month, but no one wants to do that once a month. And you can schedule with ChatGPT agent.
Speaker 9:You can schedule it to run. So I can just say, like, every month, I want you to just send me on the first of the month, which is it's really freaking cool.
Speaker 3:That that's wild.
Speaker 2:Amazing. I wonder how compute intensive that's going to be because if I know anything about building dashboards and building like these these reports, there's always like an intense amount of like, oh, we gotta have this dashboard. And then you check the analytics and it's like, oh, turns out the team just that for a week and then like stopped watching it. And if it's running, you're like burning something.
Speaker 3:Dan is every Foundation Lab's worst nightmare because he gets on the most expensive plan and then uses it a 100 times more than anyone else. He's You're single handedly gonna bankrupt a lab.
Speaker 2:There's other there's other users that are probably higher margin. But but, yeah, talk to me about that that that actual experience. Did you have to OAuth with any different services? Did you have to share any API keys? Did you have to export any data?
Speaker 2:Or or was it really as simple as just a prompt?
Speaker 9:It's basically a prompt. What happens is you type in you type in a prompt. You say, want you to check out Quora. I want you to check out our emails. I got I want you to check out our our our support forum.
Speaker 9:So Chateapity has connectors. So I previously already connected my Gmail. So you just, like, log in on on the OAuth. Mhmm. And then what it will do is it it spins up its own computer on the cloud, its own virtual machine.
Speaker 9:Mhmm. It goes in the browser and starts browsing, browsing the web. It also then connects to connects to Gmail. If it hits a login so, for example, when it hit LinkedIn, it it, like, couldn't log in, and you can take over the browser in the virtual machine and type your password in, which is, like, a little a little janky. Yeah.
Speaker 9:It works, but it works pretty well. I think the interesting thing about this, though, is that there are there seems like there's two main approaches to agents, and OpenAI and Anthropic are taking very different paths, and they have very different trade offs. So the really cool thing about SharediP agent is they're essentially abstracting away the browser and the computer. So all you're doing is you're interacting with the HTTP. And on the back end, all this other stuff is happening.
Speaker 9:So it doesn't matter if you're on if you're on your phone, if you're on a Okay. Computer or whatever. They have this whole virtual environment set up. It spins up, it does the task, and it spins down. So it's like a it's a very good consumer experience.
Speaker 9:Claude Code, for example, from Anthropic, which is I think Claude Code Cloud Code is way more for developers. Agent is way more, I think, for consumers.
Speaker 1:Sure.
Speaker 9:Cloud Code is all on your computer. It's all in the terminal. And and you have access it has access to all of your files, and you have the ability to use it wherever and whenever and however you want. So it's much more customizable and much more composable. So I find that Claude Code is much more powerful, but it's much more intimidating, and it's just not something that a consumer can use.
Speaker 9:And I think that
Speaker 3:But still the crazy thing trying.
Speaker 9:Yeah.
Speaker 3:The crazy thing there is doesn't Claude code have more downloads right now than the actual Claude mobile app? Like, the the like, I I saw
Speaker 9:something crazy like that. I I honestly think people are sleeping on Claude code. Like, I use it all the time for non programming tasks, and I think most people think that you can't use it because it's in the terminal, the terminal is really intimidating, but it's a it's an incredible product.
Speaker 2:So, yeah, how would you solve this problem if you were to do the same eval of, like, generate your net detractors, net promoters using Claude code? You know, just open up the terminal on your laptop. You wouldn't be able to do it on your phone, but you'd you'd just engineer a prompt that told it to do that and it would just write all the code that it needed to do exactly the same thing. Do you think it could hit that? Do you think it could do it?
Speaker 9:Yeah. It could it could do that for sure. And I think the the the nice thing about Cloud Code is you get you get many bites of the apple, and you can, like, so for example, with Cloud Code, what you can do is you can have it make a full plan. So it can output, like, a full markdown document with, like, a, you know, 300 or 500 or a thousand word plan. You can modify it and go back and forth with it and then have it execute it.
Speaker 9:I think it would be more complicated. Like, yeah, it would probably write some code to hit the Gmail API, and I'd have to, like, think about that as opposed to just, like, clicking the connectors button. Sure. Or it does have a it does have web research tool, so it would be able to go to, like, feedback form and and do all that stuff. And it would be able to save all the data so I could kind of watch what it was doing as it was doing it.
Speaker 9:But so so I think you would get basically the same experience. I think Cardco is a little bit more controllable and therefore a little bit more powerful, but ChatGPT is just much easier to use.
Speaker 3:It makes sense. What use cases do you expect ChatGPT agents to have the most PMF around. I was I was imagining the student use case which is just like monitor the homework that I have do across, know, I I remember in high school even teachers would host their homework on websites. You could basically run something that was monitor the homework assignments that I receive and then take a preliminary pass at doing the assignment and then give me a draft that I can review and and sign off on
Speaker 2:or tweak and then automatically attend college.
Speaker 3:Write my college essay.
Speaker 2:Job for me. Just deposit the money that you make as an engineer at multiple companies into my bank account, and then also plan a trip to Europe because I'm retiring.
Speaker 9:Watch out, Cluelly. Chatty Vuitti agent's coming for you.
Speaker 1:Good guy. Boom. Breaking news.
Speaker 3:Breaking news.
Speaker 1:That's funny.
Speaker 3:Yeah. But it but it but like giving this powerful of a tool to everybody immediately, not everybody's gonna realize it, adopt it right away, but you can imagine, like, a few use cases just spreading like wildfire. Totally.
Speaker 9:Yeah. I mean, I think what are the what are the things that you would immediately do if you had an assistant? Mhmm. Like, if anyone if someone just dropped an assistant into anyone's lap, like, was the first thing they would do? I don't know.
Speaker 9:How we book a vacation, help me, like, figure out how to order groceries, help me, like another one another thing I use it for is, like, research the web about all the topics that I care about, and every day, give me a report on all the things that happened in the last twenty four hours, and it just does that incredibly well. And I can go into you know, go behind login walls and paywall and all that kind of stuff. So I think those kinds of use cases are gonna be the gonna be the the the most interesting ones. But I honestly think right now, for most of my consumer use cases, four o or really o three is the best. It's much faster.
Speaker 9:I mostly don't need it to use a full computer to spin it up. So I see Chattahoochee agent as being something that you use every once in a while rather than something that you're using every day.
Speaker 2:Sure. Yeah. So so we're we're we're increasing the level of, like, complexity. Like like four o is kind of a Google search replacement for me now. I just kinda hit it with like when was this person born?
Speaker 2:How old is this, you know, what's the state of this, what's the capital of this state or something? Expect a really quick answer. Then go o three if I'm willing to wait a couple minutes, want something that's a little bit more thoughtful, maybe some search results from the web. Then deep research if I'm actually trying to understand the full story, read a whole report, agent if I think it's gonna need to use a computer actually take some actions, pull some things together. How was the actual interaction of the like the back and forth?
Speaker 2:This is something we talked about with the OpenAI folks was like if it gets stuck, it it pings you. I like that deep research. Yeah. It takes fifteen minutes, but I've trained myself to just be like, forget about that until tomorrow. And then when I have time to sit down and read the full deep research report, which is gonna take me a couple minutes, like, then I'll come back to it.
Speaker 2:I know it'll cook and it'll be done. It would be kind of annoying if Deep Research came back after two minutes and said, hey, I'm gonna pause all that while I ask you for an update. Like, it feels like there's a little bit more I gotta be on answering questions. There but push notifications maybe solve that. Walk me through, like, how in how involved you were, how active of a process it is.
Speaker 9:I mostly was not involved. Every once in a while, like, it does have a, like, a stop. You can help it stop and, like, change what it's doing, which is nice because, like, if it goes off the rails, that's helpful. But I think and and it and it has a push notification thing, but I think this is an interesting problem with agents where I can't stop watching them. And so I spend a lot of my day just, like, watching the agent doing something.
Speaker 9:And Chaijabi Ki agent has its own, like, cool UI where you can kind of, like, see interesting animations of what it's what it's researching or which websites it's using and stuff like that. So I find myself, actually glued to it to it a little bit, and, I just don't think that's a very good way to spend time. I think it's I think it's mostly solved by having push notifications, but I like, there's a sort of emotional process of training yourself to be like, it'll let me know when it's done, I don't have to, like, shoulder.
Speaker 3:Right. So you're like, we we design a lot of assets here at TBPN and that like even if I trust the person creating it to do a great job, there's still this tendency to wanna hover and be like, okay, tweak this, tweak that. Oh, let's do it this way in real time versus like waiting. Yeah. But
Speaker 2:And
Speaker 3:it's the
Speaker 2:same thing with four o like, you know, early on, I would kind of be in this loop of like, okay, got a result. I still gotta go fact check this and check the underlying links because hallucinations are a big problem. Well, now that they've beefed up search so much and they're referencing direct quotes, like, I feel like I'm much less like, the anxiety level around hallucinations is a lot lower, just in general queries.
Speaker 9:Totally. I think these things are tools. Anytime you're delegating to something, whether it's a human or an AI, there's a there's a learning process you have to go through. Like, human managers go through this with with employees all the time. Like, if you're a new manager, you have to, like, decide, okay.
Speaker 9:Am I gonna delegate this, or am I gonna micromanage? If I delegate, like, I get more leverage, but it might not come back the way I want it to. And good managers know how to split up a task or communicate it to their employees or figure out who's good at doing what and know when to get in the when to get into the details and when not to. And I think we're going through the same curve with models. So we're becoming model managers, and everyone is learning how to how to solve the same problems that human managers have solved.
Speaker 9:And so the more experience you have with the tool, the more you know, like, okay. I don't have to check this four o answer or this looks a little fishy. Same thing with ChachiPG agent. I think we'll be much better at using it in three or six months than they are today.
Speaker 3:Cool. Makes sense. Last question. Dan, always great to chat. I I do wanna have you back on very soon to talk about LLM induced psychosis.
Speaker 3:Yes. I think it's important to talk about and
Speaker 9:Let's talk about it.
Speaker 3:But we'll need a lot more time. Thank you for the vibe check and everybody listening go go subscribe to every right now. Do it.
Speaker 8:Awesome. Well, talk
Speaker 3:Talk soon.
Speaker 2:Bye.
Speaker 3:Cheers.
Speaker 2:Up next, we have Chris Best from Substack, the best CEO Substack's ever had arguably. Undoubtedly. He's in a conversation. Definitely. Welcome to the stream.
Speaker 2:Chris, how are you doing? Congratulations. You got some news for us? You got some numbers?
Speaker 3:Get it
Speaker 1:ready, What's
Speaker 2:going on?
Speaker 3:What do we got? What's going on in your world? Please tell me at least nine figures.
Speaker 10:Doing good. We've raised a $100,000,000 series
Speaker 1:c. Congratulations,
Speaker 10:man. I was hoping you guys would ring that thing.
Speaker 3:Of course. Course. You guys are incredibly back.
Speaker 2:Yes.
Speaker 3:It's been a journey since I believe you raised something. It was like 75 on 700 back in what was it? 2021?
Speaker 10:2021. That was those were different times. I don't know if you guys remember 2021.
Speaker 1:I do. Oh, I do. It was wild. I remember it fondly.
Speaker 2:You're at the center of the storm and I was in the depths of a, yeah, slog basically. Anyway, give us the update how the round come together. What is the plan going forward? I heard you were was the reporting accidentally profitable going back into burn mode? What's the money for?
Speaker 2:What are you thinking?
Speaker 10:Yeah. I like that. Yeah. We're, you know, partnering with Mood Raghani at Bond. Cool.
Speaker 10:I love that guy. Consummate bro joining the board. The big thing is look. The the big thing that's happened is, like, Substack's gone from being, like, a rinky dink email newsletter company to a proper sort of network that's taken over the world.
Speaker 11:Yeah.
Speaker 10:And we kinda wanna look basically, kind of, like, switch into a mode of thinking about long term ambition, long term, like, how do we actually make the big fucking version of this thing? Mhmm. What investments do we need to make? How do we focus on the things that actually matter for like the long term flywheel growth of the network? And this just gives us like a total free hand to do that thing and build the best possible version of it.
Speaker 2:Okay. Give me the pitch for I think of Substack as the no brainer place to launch a newsletter. You have a lot of other products. Talk to me about what the future of the Substack creator or someone who has Substack as like their primary out, it's the main engine of their creator economy business, for example. What does that look like over the long term?
Speaker 2:I imagine that people are still doing top of funnel stuff on TikTok, Instagram, other places, but you're adding more and more features. What is a well run Substack business look like?
Speaker 10:Yeah. You know, the core of Substack is the direct connection with your audience. Right? So people subscribe, you get their email, you get the ability to reach them, you even get the ability to like leave Substack and take your list with you, which is a big deal. People can pay you directly so you get recurring revenue.
Speaker 10:I don't know if you guys have had this, but recurring revenue hits different.
Speaker 2:It does.
Speaker 10:The sponsorship business is a great business. Yes. You know, I I think that thing matters. Lots of people on Substack have sponsors. We love it.
Speaker 10:But that thing's like very cyclical. It's boom and bust. It's like, you know, whereas you have recurring subscribers, these die hards, that's sort of like it funds sort of like you to be creative. It funds you to take risks. And so Substack's the place where you sort of like your hardcore people are.
Speaker 10:That's where you have a real connection to your audience. You can write, you can post short form, you can post video, you can do live video now. You can have a community. We're kinda like building more and more stuff. The center is not any one format.
Speaker 10:It's like the relationship with the subscribers. And then Substack is just becoming, you said you do top of funnel on on TikTok and LinkedIn and YouTube and everywhere else. Sure. Keep doing that. That's great.
Speaker 10:Those are massive platforms. But increasingly, you can do that stuff on Substack too. And because you have such a dense audience of like smart people, the quality of growth you can get there is already very high.
Speaker 2:Interesting. That makes a ton of sense. Jordy?
Speaker 3:I think the I think the magic thing that you guys tapped into that I that I end up find myself I I find myself explaining to other people is there's this beautiful like like economy of people on Substack that just want to support people that are nerding out about a specific topic Yep. Just want to give them money. And so it's almost like this there's like there's this like exchange of like, yes, want the content but it's also enabling somebody to live a life that allows them to just just obsess over one thing or just explore a series of topics Mhmm. Or just be who they are and be entertainment through that. I mean, we've had Emily Emily Sundberg has come on the show a bunch of times and it's just like it's so awesome to see what she's built and the kind of creator writer that she's able to be unshackled from being at a specific, you know, platform legacy media company.
Speaker 3:So it's just it it's so it's so awesome to see.
Speaker 2:Talk about the use of funds. You said you can afford one AI researcher now. I imagine that won't be how you spend it.
Speaker 3:No. No. Yolo. Yolo. Start coaching for Mark.
Speaker 10:Concentrated bets, man.
Speaker 2:That's how
Speaker 3:it Concentrated bets.
Speaker 2:But I mean, concentrated bets, it's not the craziest idea to go give a bunch of money to, you know, creators to kind of pull forward the the the the the the leap from what they're doing currently to to get on Substack. There's different incentive models, kick start ad businesses, just hire engineers that can build new tools and new features and just chop wood and advance the ball down the field. What are you most excited about to put that money to work over the next like twelve to eighteen months? But you probably think in like decades now at this point. Right?
Speaker 10:Yeah. I mean, that's the big thing. Right? It's like what's the this this lets us have that longer horizon. You can still have all of the same math but you can just like put the the planning horizon further in the future and look for something really big.
Speaker 10:Listen. All that stuff you said, the stuff that I'm really excited about is, like, making the product fucking great.
Speaker 2:Yeah.
Speaker 10:Right? I wanted to feel like, my joke is Substack does everything for you except the hard part. Right? You are the talent. You gotta figure out how to write something that's worth reading, how to have a conversation that's worth listening to.
Speaker 10:If you can do that thing though, we should just build this magic machine that takes everything else off your hands and makes it dead simple. Makes it just like this magical thing where anybody who has something worthwhile to say can make something. We're starting with that. We have a bunch of little bits of that that are kind of working that we're really proud of that are exciting. But I just think the new technology coming online is gonna make us like, the the version of that magical sort of, like, media studio, personal media empire in a box that we can build now is gonna be so much more powerful.
Speaker 10:And then building up, like, the network. Right? The fact that we're getting, you know, not just political commentators but politicians. I think if we get not just sports commentators but athletes, I think we can start to build up kind of like this network and this ecosystem that winds up being this positive sum game. Right?
Speaker 10:Where everybody that's on Substack benefits from this growing network.
Speaker 2:Yeah. I've certainly never subscribed to anyone on Substack and been like, oh, I didn't get my money's worth. I've always I always have a good time. What what are the different strategies for Substack writers? I know in like the Patreon podcast world, people do like one is free, one's behind the paywall.
Speaker 2:I've also seen Substacks where there's like a fold and you get every email, but you get half for free and then you at some point there's a call to action to go and subscribe and and and finish reading essentially, but you get every email. What works? What are the different strategies? What are some of the weird stuff that you've seen around the way people are using Substack today?
Speaker 10:There's a pretty big mix. Right? Some people make almost everything free and it's just basically like, you know, if you wanna comment or if you wanna get the occasional thing, that's what you're paying for.
Speaker 2:So maybe really low margin for Chris over here. You just give everything away for free. He doesn't make any money.
Speaker 1:Well, that's the beauty
Speaker 2:of your system.
Speaker 10:Nobody's paying to get more to get more things to read, to get more email, to have more seconds of audio in their inbox. They're paying for perspective.
Speaker 2:Interesting.
Speaker 10:Right? Yeah. That's the thing. Like, you know, even and even if you have a magical LLM that can spit out media in any format, you care about who it's aligned with. You care about, like, what version you know, what worldview you're getting.
Speaker 10:Is this something I trust? Is this something I wanna be culturally and aesthetically a part of? Yeah. You know, you talked about people paying because they wanna support people. The other way to say that is it gives you agency.
Speaker 10:Right? When you choose who to subscribe to, you're choosing what part of the culture you want to live in. You're choosing what gets created. You know, in a world where people I think feel like a lot of the media they consume is kind of like stuff down their throats, getting to kind of like exert a voice and say, hi, I'm causing this thing to exist that I think is great is really powerful.
Speaker 2:And a lot of different
Speaker 3:ways we're it. It's like paying with your paying with dollars versus attention is super powerful. Right? Because if you're paying with attention, it's like, well then everybody's focused on the cold play. The Coldplay debacle last last night, which is trying to steal thunder from your fundraising announcement.
Speaker 3:But we're not we're not letting it. And and and I appreciate that. And and being intentional about like, I want to pay for this because I want more of it to exist. I want I want it to get better.
Speaker 10:And I wanna spend my life. I don't wanna be on a platform that just is designed to like suck my time from me. Yeah. But I wanna I wanna spend my time and attention better on smart things like TBPN and everything on Substack.
Speaker 2:Yeah. No. Amazing. And coming soon hopefully. We will figure it out.
Speaker 3:Yeah. We're about to bet we're about to bet big on Substack. Yeah. We're very excited. We're riding with you.
Speaker 3:So congratulations. It's it's it's really tremendous to see how far the business has come since since those those glory days in 2021 and excited for the next five years.
Speaker 10:Thanks, guys.
Speaker 2:Cheers. Congratulations. We'll talk to you soon, Chris. Cheers. Bye.
Speaker 3:Awesome. Next.
Speaker 2:One last one last guest, deckhart.ai.
Speaker 3:That's right.
Speaker 2:The first ever world transformation model turning any video game or camera feed into a new digital world in real time. Very very cool. I played around with a lot of this stuff, not this in particular. Very excited to talk to the founder. Welcome to the stream.
Speaker 2:How are Dean?
Speaker 3:Welcome. Sorry for the chaos. We are so happy to chat with you.
Speaker 11:Super nice to meet you both. Super nice to meet you both.
Speaker 2:Good to meet you. Why don't you start with an introduction? I already have questions, but just, give me a little background on yourself and the company.
Speaker 11:Okay. So, you know, the card the card's a very young company. We're less than two years old.
Speaker 6:A research
Speaker 11:lab, and our goal is to build a consumer company.
Speaker 2:Okay.
Speaker 11:Okay? And what we just launched today is the only real time video model ever. I can I can just show it to you?
Speaker 2:Yeah. Please. Okay.
Speaker 11:Share screen somehow here?
Speaker 2:Yes. But you are live, so whatever you share on that screen is baked into the Internet forever. Amazing. We don't need to
Speaker 11:make sure that we don't leak anything.
Speaker 2:Just do the right tab, not the API keys.
Speaker 3:I was gonna I wasn't sure. We've never met. I mean, we've met over DMs but not face to face. I wasn't sure if this was your real face or or just a character that
Speaker 2:You showed up.
Speaker 3:That you're playing.
Speaker 11:This is this is definitely not me. You realize that. Right?
Speaker 2:Yeah. In the real world, he's an anime. But but he's using a transformer model to appear like a human.
Speaker 3:That's right.
Speaker 2:He's in fact a Minecraft character. I have so many questions about this model. I wanna jump into how you built it. We can also potentially have the team pull up the the demo video on your website mirage.descartes.ai and just kinda show folks what that looks like. Whatever would be helpful.
Speaker 11:It is currently I'm trying to get the Zoom call to be able to share this.
Speaker 2:Okay.
Speaker 1:But if
Speaker 11:the team could do it from your side as well, that could work too.
Speaker 2:Yeah. Why don't we just have to jump and pull up the core website, and and we can just jump into questions. So real time, what's the secret sauce? Is it a condensed distilled model? Are you using a special chip to inference this stuff?
Speaker 3:Talk about let's talk about the use case. Sure. Sure. Obvious use case would be like real time video calls. You're dropping into a Zoom call for example and instead of yourself.
Speaker 3:There he is.
Speaker 11:There's Here we go. Do you guys see me?
Speaker 1:Yeah. See
Speaker 3:you. Looking
Speaker 2:Okay. There
Speaker 3:we go.
Speaker 11:Okay. Okay. Now we got a working.
Speaker 3:There we go. There we go. What is the who are you? There we go. We're just cycling through.
Speaker 11:We're just we're just cycling through everything. What what do you guys like? What do you guys like? Like anime? Going.
Speaker 3:Not big into the the anime world, but what about like Legos? Any anything there?
Speaker 11:Legos? Let's let's put in Legos. We can just type it.
Speaker 2:Oh, can just type it and it'll Exactly. Do it. Okay.
Speaker 11:Let me make this full screen. You can just type in Lego and it'll just turn everything into Lego.
Speaker 1:Wow. Okay. There we go.
Speaker 2:This is
Speaker 11:this is our house.
Speaker 1:That is Wow.
Speaker 11:See the real stream in the Zoom.
Speaker 8:Yep. You can see,
Speaker 11:you know, this would be the house office thing. See all the Lego characters walking
Speaker 2:around here.
Speaker 3:This is insane.
Speaker 2:It's true. Okay.
Speaker 5:And then
Speaker 11:and then you can decide that you're into Christmas and so everything becomes very Christmas y and your house
Speaker 2:is decorated.
Speaker 3:Oh, wow. Yeah. Wow. There you go. I feel What what's the word for a moment like this?
Speaker 3:This is actually feels like enter the metaverse.
Speaker 11:Indeed. This I I was I was hoping you wouldn't say that because that become like a you know became a cursed word.
Speaker 2:Yeah. It did.
Speaker 11:But but like it's it's it's a good thing. It should happen at one point. Right? Because because
Speaker 1:like No.
Speaker 3:This is a this is a big transition from the moment where Zac was you know said you know did his like Yeah. Hello from horizons world.
Speaker 2:It was Wii graphics.
Speaker 3:Was There's Wii graphics. And this feels like being Look at this. In a video game. Oh. What it what it what is that?
Speaker 3:Is that a wand?
Speaker 11:This this is this is a You can see the straw on the regular screen. Right?
Speaker 3:Yep. Yep.
Speaker 11:And inside the wizard's prompt, it becomes a wand. And you can if you if you flick it hard enough, sometimes it does magic spells.
Speaker 1:It throws things out. I love how much fun
Speaker 3:This is
Speaker 11:Guys, which one last of the team. Like, the team's been playing with the prompts here all day.
Speaker 1:Lactic Okay.
Speaker 2:What do like?
Speaker 11:Lactic war is the one you like? Oh. Oh, and then
Speaker 2:it's the action?
Speaker 11:That's the lightsaber one.
Speaker 2:Okay.
Speaker 11:No. You had a you had one that you should've done
Speaker 2:This is horrible. Here.
Speaker 11:Here. Look at you guys.
Speaker 2:So is this running locally on your computer?
Speaker 11:So this no. This is running on a server.
Speaker 2:It's running on the server. Oh, I know So it's going from your webcam server back to us over Zoom.
Speaker 3:How is is like Kai Sinat gonna be running this like half the time that he's streaming? This is this is insane.
Speaker 11:This is fun.
Speaker 1:It's pretty fun. This what
Speaker 11:you do with it. Right?
Speaker 1:Yeah. Yeah. What do you do?
Speaker 3:How do do money? This is a bold demo too because the variation in the different prompts
Speaker 2:It's crazy.
Speaker 3:And how how well it's working is absolutely insane.
Speaker 2:Totally. Totally. I forgotten what you look like in the real world entirely.
Speaker 11:Here here's a question. Would you guys run an entire show through this?
Speaker 3:Maybe we can we can try.
Speaker 2:We might put Tyler on the intern cam.
Speaker 3:Yeah. That's a good place to start. So we have an intern cam over here. We can get Tyler running on this. Oh my gosh.
Speaker 3:The way that you're just cycling through these prompts
Speaker 2:is Tyler like can be on wizard cam for a little bit for one stream. That's pretty crazy.
Speaker 3:This is insane.
Speaker 11:Something something cool.
Speaker 1:Let me
Speaker 11:show you this. Something cool that we found out is that it's really fun watching YouTube through this. Okay.
Speaker 3:Watching YouTube.
Speaker 11:Tell me, like, give me give me a YouTube show that you like. Something you like.
Speaker 3:I mean, just do that mister beast video. Whatever's pulled up right there.
Speaker 11:Okay. So you can just look at this MrBeast video.
Speaker 3:We can look at this ad.
Speaker 11:And look at the ad and we can share the MrBeast video.
Speaker 1:I somehow have only
Speaker 11:You guys hear the audio now?
Speaker 2:Yeah. We do actually. A
Speaker 4:little bit.
Speaker 11:Do hear the audio?
Speaker 1:Don't know
Speaker 2:if we should, but
Speaker 11:Okay.
Speaker 2:Okay. And then it's being transformed now?
Speaker 11:Yep. This is the original Mr.
Speaker 6:Beast video. Wow.
Speaker 2:Yeah. Even trippier.
Speaker 11:You can here's like, Mr. Beast videos worked really well with Cosmic Medieval golden. We iterated through so many prompts that we found the ones that worked really well.
Speaker 2:Yeah. Yeah. Yeah. Yeah.
Speaker 11:This is mister beast videos in the cosmic medieval golden world.
Speaker 2:Okay. Cosmic medieval golden. I mean, they're already pretty stimulating. This is even more now. Wild.
Speaker 2:Very wild. This is insane. Where do you think this lives? Does this live with the consumer and they decide to put on the rose colored glasses or do you say you join Decides.
Speaker 3:Somebody's joining a stand up tomorrow, can they just automatically put the entire team into whatever character they want?
Speaker 11:Let's see. What stand up comedies do you like?
Speaker 3:I was talking about an actual like engineering stand Oh,
Speaker 11:an engineering stand up. Okay. Yeah. Yeah. It can definitely do that.
Speaker 2:I'm more asking about you. I'm asking you So where do you think it winds up living? Like, do you think
Speaker 11:Here's here's what I think is cool about this. You know, I think it's the first time that we have a new a new kind of consumer interaction with with video AI. Because so far, you know, video AI was just, okay. Let's create AI slob, put it on existing platforms, Facebook, Instagram, TikTok, whatever. Here, for the first time, you can actually do something that's slightly different.
Speaker 2:Mhmm.
Speaker 11:Yep. Showing it to a bunch of kids, and what they ended up doing was for a few hours, they just fought each other with sticks, and they started doing, like, TikTok dances in front of this. And you have a new kind of consumer ex and and, like, experience here.
Speaker 2:Yeah. Yeah. Yeah. It's like the original in the what was it? In Steve Jobs did that demo of the Mac where it, like, warped the image and and and there was like a it's like a crazy historical photo in the in the original like Mac OS
Speaker 3:launch How expensive is this for you guys to run if somebody just starts streaming this in real time? Are are they paying for it? Are you guys just eating it?
Speaker 11:It's it's we're we're we're doing it efficiently enough. Like, we had to write, like, all the low level assembly code for GPUs to get this to be both real time and super cheap for us
Speaker 2:Mhmm.
Speaker 11:It's at a point that we can actually provide this for free. Like, it it can actually be monetized without, like, subscriptions. Like, there there are ways it's it's it's cheap enough to actually be able to build a platform on top of this.
Speaker 2:Interesting. Do you yeah. Think I mean, do do do do you think one of the use cases will just be folks who create video content running their video through this to kinda as like a previs for what they ultimately wanna build?
Speaker 11:That could be very interesting.
Speaker 3:Well, the other the other thing you can imagine it actually in YouTube. So like a a creator like miss Rachel for example, popular kids creator could basically say like, do you want the Lego version of this video? Do you want
Speaker 2:the Well, high rich a question about where this lives because I can go and put my phone in grayscale and I can and I can view everything on my phone without color. And that is effectively a style transfer. And that's something that I as the consumer decide. Or, you know, Mr. Beast can turn up the saturation in an or, you know, if you're watching a Hollywood movie, they might turn up the teal and orange because that is a traditional Hollywood color grade.
Speaker 2:If you're watching The Matrix, they might color grade it green when they're in The Matrix. They might color it blue when they're out of The Matrix. Right? And so it'll it will be interesting to see where this lands, whether it's on the consumer. I like watching Lego version of YouTube.
Speaker 2:I like watching Lego version of my of my conference calls or it lives on the on the on the producer of videos. I wanna show up as LEGO and then that could be transformed as well.
Speaker 3:Can quickly can you quickly do a Gigachad filter?
Speaker 2:Oh, yeah. Do the Gigachad filter. Let's check
Speaker 1:that out.
Speaker 11:Let's see what Gigachad does. I will say that the model is really in the current version of the model, it's getting changing the entire style.
Speaker 2:Okay. Yeah. Yeah. Yeah.
Speaker 10:Not just
Speaker 11:the world. Yep. It's not, oh, turn me into Trump.
Speaker 2:Oh, okay. You're pretty orange. Yeah. That's the way it goes. But it but it is doing something to the cheeks and the jaw, which is textbook Gigachad.
Speaker 4:There we go.
Speaker 11:There we go.
Speaker 2:Very funny.
Speaker 3:There we go.
Speaker 2:Yeah. This is wild. Maybe you need to prompt like
Speaker 3:fully open access?
Speaker 11:This is open. We launched it literally thirty minutes before the podcast. We're waiting for you guys.
Speaker 2:Congratulations. Thank
Speaker 11:Yeah. Yeah. We it's it's it's this is the first time it's used on a video call. Amazing.
Speaker 3:Insane. Insane. Well, thank you so much for joining.
Speaker 1:Yeah. This is lot
Speaker 2:of fun.
Speaker 3:We will get access to it. We'll set it up on the intern cam tomorrow.
Speaker 1:For sure.
Speaker 2:And Wait. You already have it set up? Yeah. Okay. We're gonna hop off with you, and we are gonna check it out
Speaker 3:with Tyler and
Speaker 2:get some more feedback. Thanks so much for hopping by.
Speaker 3:Congratulations to you and the whole team. Insane. And
Speaker 2:is there anyone else in the waiting room or are we good?
Speaker 1:I think we're good.
Speaker 2:Let's Can we go over to
Speaker 3:the Let's take it over to Tyler.
Speaker 2:The intern can and see if that works. I don't even know if that if he's there. Oh. Oh. Technical difficulties of course.
Speaker 2:Anything else you wanna cover in terms of news or
Speaker 3:Yeah. There's some new news.
Speaker 1:Oh, wow. That's Tyler there.
Speaker 2:Wow. Really? Woah.
Speaker 1:Yeah. He just did it. Yeah. This is me like thirty seconds ago.
Speaker 2:Okay. Wow. Yeah. It looks better without the zoom compression. It it it's a pretty high fidelity model.
Speaker 2:Wow. Well done. Very cool. Yeah. So we were talking in the background so you hear our talking.
Speaker 2:And then Tyler's in the corner too. We're getting recursive. Not that we should use that word now. It's the em dash of the modern era. Interesting.
Speaker 2:Pretty good. And these were preloaded prompts that you were just clicking through Tyler?
Speaker 1:Yeah. Did you It's like selecting
Speaker 2:You didn't generate any of your own prompts?
Speaker 1:I didn't. But I think you might be able to.
Speaker 2:Yeah. Yeah. That seemed pretty cool. Some of the Sims fun. I I imagine that people will be having fun on this on the internet very very soon.
Speaker 2:I Very, always just wonder with this stuff like what the like the novelty is like you you have to it's like wow it's incredible technology. But then people have to actually figure out like a real use case for it like like
Speaker 3:Well, so so here's the use case streamers Yeah. Some type of like basically like if you tip a certain amount or hit a certain button it puts the streamer into that Yeah. Certain
Speaker 2:Yeah. I mean, a lot of streamers stream with, with green screen backgrounds, and they already drop out the background and put themselves in an environment that matches the game that they're playing. We're just playing up the messy background. And so, yeah, you could imagine this being like basically in the VX in the VFX pipeline for for streamers. I think if most people showed up to a to a Fortune five hundred Zoom call with this, it might not go over too
Speaker 7:well. Well,
Speaker 3:they can always make everybody on their screen look a certain way and not make themselves look normal to to everyone else. Right?
Speaker 2:Yeah. Yeah. Yeah. If your boss is yelling at you and you put him in Lego mode, it's probably gonna hit a little bit differently. Might be a
Speaker 3:little bit more tolerant. Yeah. Turn the volume down. Lego mode. Lego mode.
Speaker 3:Oh, sorry, Lego boss.
Speaker 1:Yeah. Block man.
Speaker 3:Expect me Couple to be a more headlines since we're here.
Speaker 4:Turn it down.
Speaker 3:Perplexity apparently just closed a new round at 18,000,000,000.
Speaker 2:18,000,000,000. Wow.
Speaker 3:Perplexity has around 2% of queries according to semi analysis Yep. Right now. Yep. I use it regularly. We talked to Chris who's on the show.
Speaker 2:7,000,000 DAUs, 30,000,000 daily queries, 4.3 queries per user per day, a 2% share of users, and a 2% share of queries.
Speaker 3:Solid. That's a perplexity. Solid numbers. Pretty good. They got their new browser.
Speaker 3:They're going to be investing heavily. And then outside of that, Lovable just raised 200,000,000 at a $1,800,000,000
Speaker 1:valuation led by Excel. Congratulations.
Speaker 3:Heat on the timeline. Lots of big rounds getting done.
Speaker 2:Everyone decided to launch today, I feel like. And then they got steamrolled a little bit. But that's why we're here. We didn't spend too much time on the concert fiasco and instead can move on, talk to you about the news. Also, I want we wanna send our best wishes to Tyler.
Speaker 2:He says, hi, crew. I had surgery to remove lots of infected fluid from my chest and a big lung abscess with infected tissue. Pneumonia, sepsis, antibiotics weren't working in the ICU now. Surgery went well. Surgeons are heroes.
Speaker 2:I'm so grateful. Recovering. Thank you for your prayers all good. So, I hope you
Speaker 3:Let's doing well. Send some prayers over Yes. To
Speaker 2:What else is in the timeline that would be worth to close on?
Speaker 3:I have a good closing post. The the lads over at Reindustrialize are having a lot of fun. If you can pull this up in the bangers tab, you can see a quite a number of former TBPN guests all in the back of a pickup truck.
Speaker 2:Fantastic.
Speaker 3:If you can pull this up. Team, we're working on reducing the time between talking about a post and getting it live on the screen. There we go. Oh. All the boys got Augustus
Speaker 2:Nice. Packy Steinman.
Speaker 3:Everybody all in one place. Fantastic. So anyways, thank you for tuning in today. Super fun show And I can't wait for tomorrow, John.
Speaker 2:Can't wait for tomorrow. Leave us five stars on Apple Podcast and Spotify and we will see you tomorrow. Have a good day.
Speaker 3:We love you.
Speaker 2:Bye.
Speaker 3:Bye.