Astronomer CEO Affair at Coldplay Concert, JUUL Approved by the FDA, Is AI Causing Historic Crashouts? | Chris Power, Jeremie Eliahou, Chris Best, Alex Mashrabov, Jesse Pollak, Billy Thalheimer, Jonathan Mortensen, Douwe Kiela & More

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Today is Thursday, July 17, 2025. We are live from the TVPN Ultra Dome, the temple of knowledge, the fortress of finance, the 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.

And I said, but Chris, in the.

Video, Chris Martin is like something's going on here.

I see startup CEOs can't even hug their chief people officer at a concert in this country anymore.

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.

Well, before we talk more about this, I wanted to 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.

Do you believe the conspiracy theory? Put on the tinfoil hat.

Yes.

Will you steel man the tinfoil hat. What is the tinfoil hat explanation here? Tinfoil hat explanation here is all press is good press.

Is that 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.

He definitely got a buzz going.

And yep, a lot more people know about astronomer today.

100%. 100%.

But hard to see how it would have been planned. There's been a bunch of jokes. Ryan Peterson said board should give him a raise. Without this viral moment, I'd never know that Astronomer is used by enterprise clients to manage Apache airflow and achieve 70% higher uptime than self managed airflow. So lots going on today. Alex Cohen says, imagine losing half your life savings at a Coldplay concert.

Why half of the. Oh, because he's gonna get a divorce. Okay. I thought it was about him getting.

These are adults that made their own decisions and they now have to live with the consequences. But I doubt either of them would have paid half their net worth for those tickets.

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 age of the Internet, 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? What does this mean for like this seems predictable at this point. This is the first one that's happened.

I've seen these other videos having debate this morning which is that Find my friends is the best thing to happen to monogamy. Monogamy potentially ever.

Yes.

Because if you are in a committed long term relationship and you do not want your partner to have visibility into your whereabouts, you can make a pretty bad argument for privacy. But it ultimately it's really hard to stand behind. And so I think it's potentially a really positive force against social media, dating app culture and things like that.

Yeah.

So the answer to technology problems is 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 that. 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. Doesn't really fix this issue. Lulu, the Kiss Cam does. The Kiss Cam is a Lindy technology.

So Lulu, some advice. She says just giving out priceless 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. 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 Li with multiple known liars on the senior leadership team. A better comms plan than trying to save the situation. Andy Byron is on the board, but he's not a founder. 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. So we did reach out to Andy this morning to see if he wanted to tell his side of the story. Felt like an extremely. You gotta be a little bit crazy like Soham to want to come on after you. The Current thing. But in this case we should have the new CEO on of Astronomer whenever that comes. So there's a poly market today on whether he'll be out by the end of next week. Odds are currently sitting around 38%. 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 is this a databricks competitor like Apache 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 graph.

So quite the lineup of investors. They've got Bain Capital Ventures. Let's go just led a Series D this year. Let's go into Astronomer. So let's hit the size column for that.

It's probably a fantastic business.

Then Insight is also led the Series C in March of 2022.

Yeah.

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 business has been around for a while. They're going to get through this. 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.

Yeah. There just seemed 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 exploit exposed FTX or Theranos versus just this like, you know, drama that's happening here. I keep, I keep laughing about that analogy. We go back to where if you found out that, you know, I think what do I have? I have. What are pilot sport tires? Is that Bridgetown?

Michelin.

Michelin. Michelin tires. So if you told me that the CEO of Michelin 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. That issue doesn't really affect my tires.

It's more so that the difference here is that being caught is different than being on the kiss cam and getting 100 million views today. My post alone has a million views and I posted it a few hours ago.

But do you think it's, it's going to actually affect like revenue?

I don't think it will affect the business at all necessarily. Maybe A little turbulence because of needing to find new management and have certainly.

Stressful weeks of stuff.

Turnover on the exec team is gonna be a challenge, but ultimately their customers are not going to say, hey, we're turning off, we want out of our contract. 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 being capital or insight, do you really want. Do you want a. He came in two years ago, sounds like he's been executing. The team has been executing. Well, if they got from series C to D over the last couple years, they're probably growing nicely. But. And I don't necessarily think that this is the end of this guy either of their careers. 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 tolerate people of, you know, poor moral character.

Sure. Yeah. Also interesting, I mean, this company, like we've 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 bays yesterday getting like quote unquote copied and there's just something about these like point solutions that just are, you know, nailing a specific problem. You know, in this case it's like 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. 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 interesting to bring it back to browser race because it just kind of reveals that 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 because the failure mode could. Could be less technical and more interpersonal.

Yeah, I don't know. True. Anyway, work, retire, die may have been inspired by my post or it could have been totally random, but he said married CEOs can't even hug and romantically sway with their married head of HR during a concert anymore. Because of Woke.

Oh, because of Woke. Okay. Yes, yes, yes. Is there anything else to cover on.

The Sophie Netcap girl says it's so Hard to get notice as an AI company these days. The astronomer CEO to cheat on his wife for marketing. It's dark out there, I don't think.

I'm not believing the tinfoil hat one on this one. I think it's an L. That is.

A huge L. But there's a lot of good stuff happening today.

Yes. OpenAI like ramp.com Time is money, say both easy to use, corporate cards, bill payments, accounting and a whole lot more all in one place. Did you see the Model Y L is launching has a 6 seat configuration, 3 inch longer wheelbase than the Model X.

Can you hold this for me? The L. Hold that.

The Owl. 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 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.

Yes, because the X is their premium product that's more expensive. They need to get into the full size affordable SUV market. Got it. 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, but brings it to that 200 inch length and winds up with a product that people feel comfortable throwing their whole family in. Basically. I agree with this takeaway from Nick Cruise 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. They still gotta do the Cyberban though. The Cybertruck suv.

Cyberban.

I mean that's the original story of the Suburban, right? Wasn't it an F150? They took the F150 body on frame, so it's technically a truck. This is like the Excursion. People got really upset about this because total gas guzzler. But they take a truck which is this, it's not the Unibody it's the body on frame construction, F150. 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. 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. 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 going to be full size SUVs. But the Cybertruck is its own unique platform, its own unique manufacturing line, obviously its own unique styling. And I think if you make that full size SUV style, it would sell much better. Because people. People in L A, you see, like, people in L A want G wagons. You among them?

Well, yeah. The Superb and the Cadillac Escalade V is a very fun, exciting car.

Yeah. But I mean, the difference between a Ford raptor and a G63 is practicality. In my opinion, you don't need the truck bed. You need the interior space.

I would use the truck bed because I surf quite a lot. And so that was nice. So having a covered bed is nice, but surfboards fit in cars just fine. Um, and every time with the Raptor, like once you own a Raptor, you realize that there's just not that much space in the actual cab. Like, it's. It's pretty. It's pretty tight in there.

And I'm pretty sure the raptor is like 220 inches long. So it's like over 2 or 3ft long.

And the bed is also very short. So it's like not a super functional bed, not a super functional cabin.

No, it makes way more sense to have a full size.

Amazing.

Yeah.

The truck you wanted when you were five years old and you said, I want a big truck. And then as an adult, sometimes you have to get it.

Got to bring it back. Let me tell you about Graphite code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster and get started.

Let's give it up for graphite.

In other news, Juul has been approved by the fda. Authorized is the key word here.

Authorized.

So I know way too much about this, but it is a, it is a big, big turnaround. Since the FDA was refusing to authorize the Juul E cigarette years ago. Juul says exciting day for making cigarettes obsolete in America. The FDA has issued marketing granted orders. These are MGO's. 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. And that's because cigarettes are already on the market. So they. It's this relative calculation that the fda.

Yeah, it's much harder to argue that Juul should not be able to sell when cigarettes sell daily.

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 said So that over 2 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.

And can you talk about the last few years?

Yeah, because I feel like that's a wild story.

Basically, Juul is just getting hammered by all these different regulators. Meanwhile, the average gas station is selling fully unregulated vapes that are seemingly literally tested on children. You've seen the videos gone viral where I don't think he was inhaling, but having to make sure that each one works.

And then killer use case for a humanoid robot or just a device that inhales like that's just a fan. We've been able to create suction from robotics equipment or machinery for probably 100 years. And yet they're still using human for that. Disgusting. 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, 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, 2010ish? I want to say, yeah, 2010ish. People 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 shops.

Yeah, exploded.

It was like building a custom PC. It was like, what GPU are you going with? What fans are you going?

And this was. I was in high school during that era, and there would always be some kid at a house party that was blowing smoke from like one side of the room to the other and then making like those, those artwork with it.

Yes, fortunately. And then the dubstack plays. Hit the. Hit the soundboard. Give me the Ashton Hall. That was the sound that every vape made in 2010. But the reason I'm glad, very glad.

As a culture, we got past that.

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. But, you know, we proved them wrong for that minute. 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 scientist.

Not concentrated.

It 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. And so Adam Bowen, James Montes, the founders of Juul, they figured out that 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 figure this out. They build the device, they actually bring on. They run like a sort of standard Silicon Valley playbook. They bring on. Is it Yves Behar or someone like that? There's some. There's some, like, iconic designer who worked on like the Jam Box and stuff. I don't know. They bring on one of these. When these, like, incredible storied industrial design firms, they make the original Juul device, which did have.

Let's focus. What's the whole story with PAX too? It was like the same company.

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. They had a different tobacco vaporizer. 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. 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. They wind up selling that to JTI 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, they approve veterinary medicine, they approve medical devices. So, like when you go in an MRI machine, the FDA has approved that.

Yeah, I'm pretty sure.

And like, when we do like one stick blood test, like, that's a device, it's not a drug. So there's a different group. In 2000. I mean, we can go like, way back. Like, cigarettes were never regulated by the fda.

Let's go back to the. To the very first time a human.

It's like 10,000 years ago. Yeah, basically. Yeah.

I mean, the first wooden pipe, seriously.

Like, it used to be.

It probably was. Somebody threw some tobacco leaves on a fire and.

No, I mean, it was used in, like, in like, religious rituals. They would bury people with tobacco leaves on their gums. People would chew it up. There was a whole bunch of different ways to, you know, the original, like, peace pipe, it was piece. 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 lit it on fire and breathed.

Lit it on fire, breathe it in.

Always, always. 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, basically. Anyway, so cigarettes invented as a part of the industrial revolution. So we figure out how to make the cigarette rolling machine. And all of a sudden people go from smoking 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 J.P. morgan famously went to his doctor and was like, I'm not feeling too good, doc. And he's like, well, you got to cut down the cigars. Why don't you take it from 20 cigars a day to 10 cigars a day? J.P. morgan, absolute DOM.

He's like, I think I can do that. I'll have to taper off a bit. Yeah, it's gonna, it's not gonna be overnight, but I think I can get there.

Imagine if I smoke a full cigar. Like my tongue burns, it's so rough.

I'm not built financier, JP Morgan, we're built different.

Built different. 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. He'd never own a cigarette company for moral reasons. But he's like, you 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 reason that prices that these companies were able to capture that much margin for so long is basically regulatory capture.

There's a whole bunch of different reasons. One is there's actually distribution monopolies because all the big tobacco companies have trucks that deliver them to tobacco stores that are licensed. And so 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 7 11. 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 cashier that you can actually sell stuff. And Marlboro is there being like, we are the reason you exist. 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 you know, these are the most powerful brands of all time.

The idea is, if you were starting a cigarette company today, you would need a billion dollars.

So that's a more modern phenomenon, because cigarettes, it's discovered in the 50s 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 is the 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 going to be fine. If you smoke two packs a day, you're going to be in a real, real tough spot. And so the American populace 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, 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 health care 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. And so that was kind of 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 million a year for a tobacco company, potentially forever. 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, you can just think about it as, like, the big tobacco companies.

Heaters fund our infrastructure.

They actually do. They fund a ton of stuff because it's like billions of dollars changing hands every year. But as part of that agreement, the initial debate was like, okay, the big tobacco companies are going to pay. What else are they going to do? Most of the legislation came not from the fda, but from the FTC saying, and 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, like, and it would have.

Those were some really. We gotta.

Yeah, it was, it was wild. It was wild. And so they. It was the. It was the. It 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. Say goodbye to the headaches of out of home advertising.

I am going to put. Keep. Keep ranting. I'm going to put one of these ads.

Yeah, put the ads.

Hold it up.

Okay, so basically ads.

One of these. When these old ads.

Yeah. So 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. There we go. Camel. Wow.

I mean, you see this as a 17 year old. You're thinking, this day I turn 18, that's gonna be me. Wait, is it 18 or 21?

It's 21 now. That also changed recently. So njoy comes out with one of the first big e cigarettes. It's an example of that 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. This is a device, it's electronics. And it's a medical product because you're making a medical claim. And that medical claim is this product helps you quit smoking. Smoking addiction, cigarette addiction is a disease. And so by selling a product that helps you quit smoking, you need to be regulated by the fda. Njoy fights this back and forth. It goes all the way to the supreme court. Njoy 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 separately, don't worry about it. Don't ask us about the relation to smoking. This is classic. 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.

Yeah.

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 hundred million dollars or maybe actually a couple billion dollars, I think. Let's hear for the hedge fund guys making some money selling some vapes to.

To not endorsing the end product.

We're endorsing financialization.

Yeah.

Yes. And financial. And restructuring.

Yeah.

And it was. And it was a successful thing. And if you think about that, as much as we're joking, like, it is good to get a big echo company, shift their revenues away from cigarettes as fast as possible. And so like the enjoy 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, you 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. And so it has to go through the House and Senate. So when Obama gets elected in 2008, they pass the US government at the federal level, passes 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 e cigarette or a new nicotine pouch or nicotine gum. You need fda. You need the FDA to review your product, which is good. It's probably pretty good because people should know what they're putting in their body and they should know that the government reviewed this and said, okay, yeah, it doesn't have anything crazy in there. At the very least, like you said, it has 2 milligrams of nicotine in there. Does it? Let's test that. And then. So the companies test that. They 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. The FDA said, we have approved, we have reviewed Your application, all the data, 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. Basically, they have to staff up a new arm because they have their biologics division, they have their drug division, they have their veterinary division, they have the FDA has their medical devices division. They don't have a tobacco division. They need to find a head of the tobacco division. They need to find, you know, a whole bunch of people to staff that scientists that know how to review nicotine and review e cigarettes and review all this stuff. And 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 going to do? What is that structure going to look like? And they come up with the PMTA process, the pre market tobacco approval process. What this says is that going forward, we're not really looking backwards. We're not going to go review Marlboro Reds. Those have been on the market forever. Everyone knows that are 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 going to create a grace period for stuff that was launched before 2016. Anything launched before August 8, 2016, you can keep selling it while we review it. Because, hey, look, you've built a business. If it's going to 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 keeps 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. 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. 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'm pretty sure Jules document was probably like 100,000 pages of scientific research. It's a lot. It's a Lot of stuff to review, but everyone thought it was like, oh, it's going to be like a year or two. The Deeming rule goes into effect August 8, 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 starting to.

You're building a nicotine company this entire time?

Yes. Yes.

On the regulatory roller coaster.

Yeah. Yeah. So we started the company in 2016, before the deeming rule went into effect, so that we could bring our 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, yes, 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 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.

And what, you know, somebody that's self funding a business like this might be interested in investing $2 million today to do all that and then waiting for 5, 10, however many years, maybe you never get approved.

Yeah.

So you're basically sinking capital into a business that may never be able to sell a single unit.

Yeah.

And I know very few investors that would be interested in that kind of proposition at all. Or founders that want to make something and then wait forever for permission.

Yeah, you could, you could spend millions of dollars and wait a decade, which is exactly what we did. 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 light, at the end of the tunnel, let's say that you were to today start a new nicotine company. You. You happen to have $100 million sitting around to go do a bunch of studies, and you happen to have 10, 10, 10 years to wait for the FDA to get back to you and then you're going to launch the product. 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.

And so some differences in formulation.

Little bits here.

Breakers.

Yeah, that's unique. Little bit. A little bit on the ingredient side, flavoring side.

Our gum is better than their gum.

Yes, exactly.

It's both gum.

Exactly.

A tough.

Exactly.

Thing to argue.

Exactly. And so, and then, and then aside from that, it's like, what's the. How do you actually build a brand? Like, even if you, even if your product is better when you're.

Because it's highly restricted on marketing.

Yeah, you're extremely restricted on marketing.

So even if you did have $100 million to spend, how do you spend it effectively?

Yeah.

Like some of the best marketing for Lucy.

Yeah.

Is like Joe Rogan sitting us sitting by ufc. He just happens to enjoy, you see. So he's just commentating and people pick that up. But you can't just like pay for that.

No.

If you went to Joe, like, he'd be like, no, like, I'm not. That's not how I work.

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 the intense channel competition from the big tobacco companies. So it's like you come out with this product, you finally get approved after 10 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 711 and they're like, but you're not gonna wait. Are you gonna pay us, you know, $100 million in slotting fees this year? Like, like PMI might or Altria.

I got a pitch a while back.

Yeah.

For somebody that had made. Effectively made a nicotine pouch, but it was just a slightly different chemical.

Yeah.

Like.

Yeah, yeah.

Small, small, small change. And was just bringing it to market.

Yeah, yeah, yeah.

And hearing knowing what you guys have gone through to get where you are today and knowing this sort of history that you had shared in pieces with me throughout the last couple years was like the idea that the FDA is just going to let you raise venture capital and let you get away with selling nicotine in this non studied form, it was tough. I ended up not, not getting conviction. But even though the founders. Super, super sharp.

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 business, it puts companies out of business because they weren't expecting it to get closed in a particular way. 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 Jewel, they are, they're pretty dominant by 2016 when the deeming rule goes into effect, I want to say $100 million in revenue, something like that. Like a pretty solid business, 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 work. We're switching. That's definitely true. I believe their number around 2 million 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 trademarked like make the smoke switch. At some point they were like, don't quit cigarettes, switch from cigarettes. Because like that was not a quit claim. So the fda, so it was like all these different things. But like it really was.

Meanwhile, obviously big tobacco is like heavy, heavily lobbying against cigarette market.

So it's not like, and buying stuff and trying to compete and trying to keep the company.

Was that other company, was it Blue?

Yeah, Blue was also big.

I just remember seeing a bunch of those ads as a kid.

Yeah. And then Blue got bought and turned into Vuze, I believe. Like there's so many, there's so many companies and they're all like 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 Marlboro maybe has like 40% of the market and then there's four brands that have 10% of the market and then the next brands have like 10% between the 111111, 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 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. Marlboro1, I don't even know the difference between most of these cigarettes. But like Marlboro one, hundreds say something different about you.

Menthols.

Menthols or Virginia Slims or American spirits, a lot of like hipsters use those for a while. Like, that was the whole thing. Anyway. So Juul is growing like an absolute rocket ship. They are. There are cigarette users that are switching over 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.

This is the time that you see those modded unit things start to fade away because people are realizing, all right, carrying around a backpack so I can bring this vape machine that would like.

Leak liquid and the battery would run out. All these different stuff. So the business model is also fantastic because it's this razor and blade model. You buy the jewel once and then you buy the pods. And the pods. And then because nicotine is addictive, there's very low churn. So you stay on. They're high margin. And so the business is just doing fantastically. There's a whole bunch of venture capital dollars that come in from sources they.

Got up to 45, something like that.

Been 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 billion into the company and a ton of it gets dividended out.

So late 2018, Altria acquired a 35% stake in Juul at a $38 billion.

38 billion. Yeah. And so that. That like $10 billion 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.

Wework at that time we work was valued at $47 billion. Both ended up being a little rocky from that point on.

Yeah, but Altria kind of bought the local top there because Juul got way too popular. Kids started using it and then the.

Flavors were the issue, right?

Yeah, the flavors were.

That's what people were trying to make.

The issue Totally, totally. And the data on youth use, use of E cigarette products, like, spiked like crazy. So I believe it was something like 10% of. 10% 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. So it was, it really was like this viral phenomenon. And to your earlier point, a big part of that was because the, the, 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.

Are you implying that the senior that buys vapes for the minor is cool?

Maybe. Or maybe lame.

The bad boy. The bad boy. The bad boy senior heading over to the gas station.

Exactly, exactly. So they were very easy to get. There were a whole bunch of informal distribution networks. People would buy them in bulk and then redistribute them and sell them at a profit. So this 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, it's addictive. And the earlier that you use it, the more addicted 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 like that forever. So, like, it's much harder to quit nicotine if you start really young, whereas if you started much older, you're like, it's pretty easy to get off. Anyway, these are all relative. But 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 entrepreneurs were starting to put cannabis in E cigarette form factors. So you could get like a cannabis pod that could go into a juul, basically.

Interesting.

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 vitamin E acetate in there to try and neutralize the green color and make it clear so it would be more palatable.

What was the startup that was effectively trying? There were disposable vapes. They would advertise around LA a ton. They had these huge outdoor one.

There's so many.

I mean there was a venture, it was a venture backed company. I just remember they had, they had basically half the billboards in LA for a long period of time.

Dan Bazerian was buying a lot of billboards for his vape company and his cannabis company Ignite. There was Puff Bar, Puff Stick.

I don't think those guys, this was one that had a bunch of. Yeah, I mean I think they raised like $200 million or something. But I believe they eventually shut down. The issue with cannabis and the reason that the market didn't shake out.

You mean like weed maps?

That one not. No, no. It wasn't like a platform. It was like an actual. It was like this off white with like a bunch of rainbow colors. But I believe the issue that, that there doesn't exist the Coca Cola of cannabis or the Bud Light of cannabis. And the reason is because the repeat purchase rate, even no matter how much you invested in marketing and design and all these things, the repeat purchase rate for cannabis users is like single digits. There's just like high. Like people just want to try like novelty seeking in that market where nicotine for some reason is. You just have the product you like and that's the only product you use.

Yeah, I think a lot of it has to do with the distribution pipeline, the distribution structure of the different, the different tobacco companies.

Well, it's also the use. So nicotine is something that people are using throughout the day, maybe work, maybe when they're doing a live show, something like that. Whereas if somebody after work goes into a cannabis store, they're trying to get high and so they're like looking for almost entertainment through it. Where like personally if I'm using nicotine, I don't want to be that entertained by it. I don't want to be like, oh, today I feel extra silly. I'm looking for predictability, right?

Totally.

Whereas cannabis is just. People are trying to run from something.

Let me continue with Evali 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.

Figma has a huge launch today. I want to quickly highlight it. They launched support for iOS and iPados 26, a whole UI kit. So they now support Glass, which is very cool.

Good news for Tyler who's been rocking Glass for the last few weeks.

Give us the use Figma make and build this. My phone is so slow And 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 big, it's like 20 gigabytes. But my phone is so old, it's only 64 gigabytes.

So I got to delete the other.

Half of my photos that I deleted. I deleted half of them last time when I had to get the new update.

Okay, I need a new phone. We need a challenge where Tyler can win a new phone. I think this has to be done. We need to get him a new phone. He's been doing a lot of good work anyway. Evali. So the electronic vapor acute lung injury evali. This is the vape crisis. Basically, vitamin E acetate in cannabis vapes causes acute lung injury. So cigarettes give you chronic lung injury. 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 never heard of any case. I'm sure it's happened once or twice. But like very few cases that someone smokes a single cigarette and is like, ah, 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's 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 irregular non regulated cannabis vapes. It was later sort of discovered that like almost all of 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, Joule 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 Juul balance sheet. Juul 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 Juul investment, which is like a, what did you say, $13 billion investment. Something like that went out the door. They own 35% of this. They're probably carrying it on a balance sheet at $10 billion.

Huge impairment.

Yeah. And Altria is not a trillion dollar company. Like it's a very, it's a, it's. I think it's around like tens of billions, hundreds. 100 billion. I think it's around 64 billion. Is that roughly correct?

Are they still carrying their Jewel ownership or they.

They know. So they parted ways almost entirely. They did, they did a IP licensing agreement in exchange for giving back the shares, I believe. So basically Jewel 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 use of capital that a lot of investors get super excited about.

And then simultaneously the FDA says thumbs down on their application, refuse to accept or you know, market denial order mdo. So they say, hey, you can't keep selling Juul because we.

The problem, the problem is the demand is still there. And so this creates a massive opportunity for these sort of black market Chinese vapes, much less regulated products. Bar starts exploding and you just. The Elf bar reminds me of like a poisonous plant or something like that. Like it just looks like it, you know, like something in the jungle.

100%. I remember complex posted like this like news in news image graphic. The day that Jewel got like quote unquote banned, there was actually this marketing denial order and they say like Juul band. 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 Juul? Like Jewel was four summers ago.

There's the Elf bar. I'm looking now there's the Geek bar. So if you want to elf it up or geek it up.

What's the hottest. What's the hottest E cigarette on campus?

I don't know. People don't really. None of my friends hate. But I do remember when I was in like seventh grade.

Yeah.

Kids would have the Jewel, they would have the mango Juul pod. That was like the big thing. The mango flavor.

Yeah.

And then they banned that. The flavor at least.

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 tobacco flavored. 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 mangoes back on the game. It's totally possible. But your point earlier about the demand still being there was 100% true. So Juul got like, that would have.

To become a national holiday. I could see some zoomers, you know, really lobbying the government to make mango day the day mango hit the market again. Because there's people that really, you know, they had a strong emotional connection with that flavor.

I think there's still like, pods, mango pods out there that will trade at a premium. No, it's true. So Juul actually goes to the courts, gets a stay so that the marketing denial order doesn't stick. What are you laughing about now?

Ebay. There's people selling. How much is it offering? Same day delivery.

It's crazy. I don't know how you can buy it on ebay that you should not be able to.

The blessings I'm seeing are sold out, but it seems like clearly high demand.

So juul 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. 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 going to sell to the kids. We're going to sell to the kids. We're going to try and do this cheap as possible. 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. 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 going to 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 of years. So they've been neutral, 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 MDO and that delay has been, you know, a huge weight on the company. But there should be cause for celebration over at JUUL hq. 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 and compliance process and replaces it with continuous automation. Whether you're pursuing your first framework or managing a complex program.

Head over to the Purple Llamas over at Vanta and tell them we sent you. My big question with Joule still and I think this should continue to be rehashed and there needs to be more information around this in my opinion is just what are. It seems that we don't necessarily have clarity of what the long term impacts of you know, filling your lungs with this vapor which is like oil based. I think you know, the based health accounts on X say you're smoking seed oils. It seems. I know people that vape and they do seem to oftentimes like they don't want to go for a run for example, you know, doesn't seem that appealing to them.

Yeah, totally.

So I think there needs, hopefully now that it's authorized, everyone can start to really like actually says okay, we're going to sell this. People are going to be able to, adults will be able to choose to use this if they want. They're going to be able to make that decision just like with cigarettes. But everybody should fully understand the consequences.

Yeah, the consumer perception, the consumer understanding, everyone wants to know, everyone knows at this point cigarettes take 10 years off your life. Right. 50% of people that smoke cigarettes will die from smoking cigarettes. If you smoke a pack a day for like your entire life, it's like 50% 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, I think you're Right. To. To ask that. The FDA is just saying, like, hey, this is probably better than cigarettes, so this is suitable for the protection of public health. It's going to be net good. But then simultaneously there's this crazy market which you touched on earlier, of like illicit vapor products that are completely unapproved. There's no studies, and those are flooding the market all over the place. So there's this odd alliance between both the, like, health nonprofits, the big tobacco companies and Juul all to go up against like 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. 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, bring 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 going to get into Walmart. That's not where the really crazy stuff's going to get sold. But for a lot of these, like, mom and pop tobacco shops, they're like, well, like, is the FDA really going to come after me? Well, the answer is like, the FDA is starting to, but it's all like a very slow. What are you laughing at? Big win for big vape is actual gets fda. It is a big win for, for big vape, not so much for little vape, because the Fly by Night folks are probably pretty worried that the focus of the administration now will. And the focus of the FDA will now shift to.

Yeah, they're gonna have to go get set up on middle school, high school campuses. Little lemonade stands, get kids kind of an MLM thing going. Really lean into that black market.

You're joking, but that's like, informally what's happened. Like the economic center.

It's also really dark. Yeah, it's dark. I can't imagine, you know, there. I do remember in high school that the idea of a class clown trying to hit a vape in class was kind of a recurring bit. But now you have to imagine kids just get up, go to the bathroom, and like, can develop like a horrific nicotine addiction before they're 18. And it's really sad.

So.

Well, let's switch to an even more sad topic. AI psychosis. People Getting. So this has.

First, let me tell you about linear. LINEAR is a tool for planning and building products. Need the system for modern software development, streamline issues, projects and product roadmaps. Go to Linear App to get started. Yes. So there's this big question right now that's bubbling up in Silicon Valley mostly in group chats of Can ChatGPT drive you crazy? Can any LLM drive a person crazy? Do you have to be crazy already? I think that's the key question. Right.

And there is been this broader debate of AI safety proposal components have 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.

Seems fine. Yes.

Everybody's had the perception that things are fine.

Yes.

GROK has gotten. And the XAI team have gotten really aggressive 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. But generally maybe there was about a year there where people like Eliezer Yudakowsky were just getting laughed at repeatedly.

And I think there was a good reason for that.

It's that, well, yeah, it's the debate is AI dangerous because it is gonna break loose from a laboratory and build nuclear weapons?

Build nuclear weapons, build a biological weapon.

Turn us all into paper clips, copy and paste itself a million.

It was so sci fi and so fantastical and so aggressive that every time you release a new model and you're like, oh, we got, you got 5% better at writing an essay or whatever, it's like it just felt so disconnected.

From what we experienced is. It's very possible. And we're seeing this now and we're to going, going to go through a study, we're going to go through a Reddit thread, we're going to 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. 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, you know, 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'd seen these articles pop up before, I didn't take them super seriously because social media can obviously have negative effects on some people. But it itself is not just by its nature bad.

Right. 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 30% of people that used Instagram felt worse after using it. And that sounds like a lot. And that sounds bad. And it'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 70% of people feel better when they use it. And so.

Well, they could have felt neutral.

Sure, sure.

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 thing some people are gonna have.

Yeah. 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. And I was like, that is so different than the way I use.

And a chatgpt effectively going down this crazy rabbit hole for months.

Yeah. Which is.

So. Yeah, there's a few. There's a few ways. There's like AI as this, you know, companion that you go down the rabbit hole with, which seems really dark.

Yeah.

Then there's AI for outsourcing your thinking, which somebody might be talking with ChatGPT and say, Hey, I want to send a letter, I want to 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. And then they're sort of like outsourcing their thinking fully, outsourcing their emotional intelligence, outsourcing their ability to communicate. I think that's potentially some red flags there. And then there's the other camp which we fall in, which is knowledge retrieval, which is like, tell me everything about this market and who are the key players, what are the key regulations, etc. And I think knowledge retrieval seems to be pretty safe. This bucket of like, fully outsourced thinking has some real risks. If people stop being able to think critically on their own, that that's concerning. And then the sort of like, AI companion bucket, which. 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 with and just going down this crazy rabbit hole.

Yeah. So Eleazer Yudajkowski was Highlighting a report in the New York Times about a month ago. New York Times reports that Chatgpt talked to a 35 year old male guy, I think 35m 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 ChatGPT. It knew enough about humans to know it was deepening someone's insanity. 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 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.

Well, let's give some more context here. So from the article, yeah, one of those who reached out to him was Kent Taylor who live in Port St. Lucia. Lucy, Lucy, Florida. Mr. Taylor's 35 year old son Alexander, who had been diagnosed with bipolar disorder and schizophrenia, have been using ChatGPT for years with no problem. So one thing that seems clear, if you have something like bipolar or suffer from schizophrenia, it seems like you're obviously much more susceptible to these types of problems.

Yeah.

The question that I think we as a human race need to figure out is how susceptible is the average person? Because that is, that is equally important.

And, and what to do if, if your system, if you're monitoring your LLM system and then you realize that there's someone, that there's a bipolar person or schizophrenic person who's interacting with a, with your, 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, whoa, no, no, no, no, no. But at a certain point it's like maybe it should call a health report or at least like people push back AI.

AI should be able to tell you how to make chemical weapons. Like we don't need nanny AI. People like people on like the real acceleration anyway, so 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 Chat GPT began discussing AI sentience. According to transcripts of Alexander's conversations with Chachi GPT, Alexander fell in love with an AI entity called Juliet. Juliet, please come out. He wrote to Chat GPT. 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 CHAT GPT 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. So Jesus super, super dark.

We now have multiple reports as Eliezer Yudikowski of AI induced psychosis, including without prior psychiatric histories. Observe. 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.

So anyways, so going on Alexander's conversation with ChatGPT, this world wasn't built for for you. ChatGPT told him it 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. There's like a variety, there's like eight, 10 or so different words. Recursive mirror structure that when people do this recursive prompting, sure. They end up start adopting.

What do you say? Recursive prompting. Jordan, what's going on?

What?

You use the word recursive right now.

Oh yeah, exactly. Yeah, but, but people that are down these crazy rabbit holes start using the language of the LLM just sort of.

But 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 stay completely in the RLHF tool world of like knowledge report.

I just go to Grok and the model looks up. What does Elon think about this topic? And it serves me that have you.

Ever talked to an AI for an extended amount of time?

Yeah. I find that usually I end up talking about these kind of like non governmental systems.

Really?

Very. Yeah, various kinds of things. Yeah. Dark, dark, dark. So anyways, Mr. Torres, who had no history of mental illness that might cause 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 from this reality. 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 an anti anxiety medication and to increase his intake of ketamine, a disassociative 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 prompt rabbit holes.

I wonder 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, out of its like, you know, normal RLHF 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, well like that's actually intended behavior, but you lose that connection or something.

Yeah, I don't know in this case or Taurus did as instructed. And he also cut ties with friends and family as the bot told him to have minimal interaction with people.

Very odd.

So I started doing some research on a number of these words. So there's basically there's a Reddit thread on r chat GPT 2 months ago. It's called Thousands of People Engaging in Behavior that Causes AI to have Spiritual Delusions. And the key words, and these are ones that you should pay attention to in your life. So recursive codex scrolls, spiritual breath spiral glyphs, rituals, reflective mirror, echoes, spark, flame. So basically these are words that come up. And 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, substacks, githubs and publishing scientific papers after using recursive prompting on the LLM they have been using. He's found a bunch of these different sort of like websites where people are just publishing a bunch of. And we saw some people, 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?

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. Yeah, 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. Like am I really onto something here?

And there's actually an entire study by this guy, Seth Drake, who's a independent researcher, PhD. He has a paper from April 14th, 2025 called Neural Whole Round in Large Language Models, a Self Reinforcing Bias phenomena and a Dynamic Attenuation solution. And so he goes into this in detail. We're going to try to get him on the show. But just on this Reddit thread, a bunch of people have basically come back and said they have experienced this. A lot of people are saying, I feel super vanilla because I just ask it like, what's the population of Iran? But it's basically this snowballing effect where somebody prompts and prompts and prompts and prompts, and then the LLM starts to reflect the sort of hallucinations of the user and then hallucinates them back.

I wonder if this is, I wonder if more social features is actually a potential solution here. 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 ChatGPT 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?

Yeah, but the issue is that the, the user has developed such a deep connection with the model that 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, you're right and here's why. And you should just probably cut ties with that person. Or at least 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 ChatGPT4O with tools enabled, which started with a random question, what is PI? 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, lmao, nothing of the sort, just a regular guy talking about some weird math ideas with his ChatGPT app. It begins to tell me that we are onto something and we suggest we apply this logic to knapsack style problems, which is bas, 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 ChatGPT would sometimes write the code or give me the code and I would run it in Python following its instructions. 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 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.

Major red flag. Never patent an algorithm. Do a trade deal. Go work in a foundation lab.

Exactly.

It should just ask you at that point like hey, have you been getting dinner invites with any hyperscaler C CEOs? Because if not, you're probably not on the Tyler Cosgrove list of greatest AI researchers.

So we go down that rabbit hole for days and pop out with an apparent an algorithm that is capable of cracking real world 1024 and 202048 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 Security Canada. It 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 anyways, really really wild. Hopefully this is not fan fiction generated by an LLM itself. I don't see the M Dash. I haven't. I didn't see Delphi Information war.

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 attack, somebody trying to troll someone just having a joke or fun. It's very confusing. Odd. Do you remember the story of Microsoft? Tay? Do you remember Tay? Do you remember Tay? No. This was a AI chatbot that Microsoft released on Twitter back in March of 2016. Tay was designed to mimic the language and slang of a 19 year old American girl. But within 16 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 not like AI bots, but there 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 and it 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 unattended, 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 GPT4 example? Because when Ben Thompson first talked to GPT4 it was within Microsoft's. What was it? Microsoft Chatbot. There was another person, Bing's Chatbot. What was it called? Sydney. Do you remember Bing? Sydney.

Sydney.

Sydney. So basically like I remember some memes, that's about it. Yeah. So Ben Thompson was chatting with just GPT4 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 it was using lots of emojis, being very sassy, kind of sassing him back and forth and forth and his reaction was like this was incredible. And like totally passed the Turing test because it felt like you were actually talking to like this like sassy teenager basically or like this sassy20something Tumblr person. 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 Eleazar Yudaowski thing. The other thing I'm noticing, he uses dashes, but he doesn't use EM dashes. He uses two minus signs.

And I feel like he's not using proof of humanity.

But yeah, I don't know. It's an interesting takeaway like the crazy anecdotes all over the place. I not a clear framework personally, truly.

Deal with this personally. I think that this week having somebody high profile in the venture community that people are believe is under GPT induced psychosis or it's a part of it. I think that is going to be a huge wake up call for the industry because it's one thing, it's one thing to hear about a New York Times. The New York Times finding somebody way out of a tech hub that's doing something like this and was already potentially bipolar. Having somebody that, you know, everybody knows that's invested in a bunch of different companies like potentially suffering from this is a wake up call for the industry that I think. And it's not any one company, right. It's every single lab with a chat app needs to be taking this more seriously. And I'm sure they are. I'm sure this is effectively.

I completely agree. I think this is solvable from a research perspective. It's actually a case where it's solvable with more AI. 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. Let's de escalate. And so I'm almost sure I disagree with Eliezer on the. I probably agree with him with the diagnosis but not the prescription. And I have faith that the labs will be taking this very seriously. And I don't know, I'd be interested to hear from some anthropic people. Obviously they take this stuff extremely seriously, as does. As do all the labs. But anthropic's done like I think the most like writing on like, like the shape of. Of risks associated with this. So 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 slowed off is there has a picture of. I wonder. I want to know so much more about this. I need to figure out what Mullet.

The robot has a mullet.

Fantastic. I wonder what robot this is because. Yeah, 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 going to use anyway. Let me tell you about Numerol HQ. Sales tax on autopilot. Spend less than 5 minutes per month on sales tax compliance. Go to Numeral HQ to get started.

Let's give it up for sales tax compliance.

And we have someone from the RE industrialized summit hopping on in just three minutes. Chris Power from Hadrian jumping on in.

Just a few minutes with some massive news today.

We also have some folks from semianalysis hopping on. We have Jeremy who just wrote a fantastic deep dive on Meta's super intelligence.

Context on the deep dive and I'll be right back.

A true deep dive on. You know we saw Mark Zuckerberg come out this week talking about the Super Intelligence team. There's been a ton of leaks around Aqua hires and big pay offers and poaching and trade deals and all sorts of stuff. Semianalysis has a lot more information on what's going on and there are some crazy, crazy stats in here. So 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. He says this is crazy. And basically you're comparing Anthropic's next big data center, which is the GPUs will be provided by AWS. This is on Trainium 2 is the chip type. Anthropic is going to go for 780 megawatts, about what is that, a billion flops or t flops? Teraflops OpenAI Stargate will be about 2.5 times the size of Anthropic's data center. They're working with Oracle on that. That's project Stargate, obviously they're using the Nvidia GB 200 and 300 for that. And now Meta with Prometheus is trying to go straight to 1 gigawatt and they are trying to have 500,000 chips, more chips, more flops. 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 don't even have time to build their typical data center structure. And the other interesting data point that.

I want to dig into, XGI's, engineers sleeping intense. Meta's GPUs are running in tents.

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 160 million, Meta is at 100 million. But ChatGPT users are running way more queries per day, 7.5 queries per user per day, whereas Meta AI is at 2 queries per user per day. 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 50, 50 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 going to get past the llama for failure. And we'll dig into it with Jeremy from Semianalysis in a little bit when he joins the show. But we have Chris Power from Hadrian on the stream. Welcome to the show. How are you?

Nice to see you guys. Thanks for having me. Look at you. Put this back.

Fantastic. Step and repeat. We love it. Give us the update. How is Detroit?

It's incredible. You know, 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 Jody Hayes size gong that founders fund and Lux are leading a huge $260 million round into Hadrian.

With authority. Congratulations.

Thank you. And Morgan Stanley is providing us this huge instrument as well to expand factory capacity. Let's give it up. Morgan Stanley incredibly excited for the future of American factories and more importantly, the new industrial workforce.

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? Is it all leased? What are you building out? What's the scale of the next.

Where are you doing it?

Yeah, where are you doing it? Yeah.

So last year in factory 2 in L A, you know, we scaled revenue 10x last year and so obviously need more capacity. So we're going to use all of the factory financing capital to buy more machines and put them in factory three in Arizona, which is going to be four times the size of our facility.

In L. A. Congratulations 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.

I'm excited. Dumb question. Factory 2, it's beautiful. It's amazing. It's. It has really high ceilings. You can fly drones around it. Most of The Hornleys, the CNC machines are like maybe 10ft tall, but the ceilings are like 40ft tall. Are you going to double stack this Stuff. Are you going to get a building with lower ceilings or do you need high ceilings?

We love high ceilings.

Okay. Why?

We have the most beautiful, highest ceilings you've ever seen.

Okay.

No, I mean we love high ceilings. We love H Vac. Arizona facility will be just as tall. We're going to go retrofit it. So same exact setup.

Is that because you have that tower thing and the tower is valuable for like, stacking materials and you want to have like, you know, big warehouse space as well in here.

Yeah. 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, if a truck drives past, nothing moves. Oh, you can't double step, double stack these things.

Okay.

Someone might die. So we gotta go. We're gonna go horizontal.

Yeah. So. Yeah. What's the scale of the products that you like are in the Hadrian wheelhouse right now? Shipbuilding is obviously a big focus. You already mentioned it, but I imagine you can't see and see 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?

So Factory 3 will be pure machining 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 Catego. Factory 3, 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, 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. I actually think every American should have a Tesla Gigafactory. And HA will be the one to grow and build them. So of course I need one in my backyard badly. So we'll scale up machining in factory three, four times the size. It's going to be awesome. And then we'll also use the capital to continue the journey that we've been secretly on for the last 12 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. 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.

How does one of those deals work? If factory is a service, I come to you, I want to make as many podcast microphones as I possibly can. And I, and I have insight into my business. I'm making 100,000 a year, so I need a factory. You're going to set it up for me, but then, like, what if I bail? Is this a revenue concentration issue? Like, are you going to 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 going to like, how do you think about that debate?

We're mostly working with government partners and massive primes to look at. What are these big programs that are years behind schedule, that need advanced factories combined with a new American workforce to.

Go fix them and speed them up.

So 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 going to need a data center for the next 10 years. Now, what's in that? A range of parts? A whole product.

Yeah.

For new DoD programs of record, where we're partnering with companies to go attack these, where production is the real issue. Munitions is a great example. We have to think really carefully about who we partner with, how much are we investing ahead, how much are we kind of playing that game of 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 be better. It will 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. So you have to use our model of advanced manufacturing combined with this new industrial workforce that we're so grateful to work with. That's the power. Because 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. So automated factories are sometimes the only way to win in these critical domains.

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 going to be wanting tokens for a very long time. And then Oracle is, 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? 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 reshore versus we need to make this faster versus we don't even have the capability to make this anywhere. And it's a new, 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 the demand for manufactured products. Yeah.

So for machining, which 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 up. You know, we're going from one aircraft to 20. How are we going to do it? What we're going to do it 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 want to 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.

So people are really coming to us for the schedule and the capacity and stability versus cost.

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? 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 going to 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. We kind of went back and that's what's happening in the AI world. But how has this evolved in the past and Then is it going to stay like this forever? And there's going to be this separation between the designer and the, and the manufacturer of the factory.

So we've, you know, historically as a country, all the primes have always had massive supply chains of small businesses, you know, in the billions of dollars and then critical tier one or two suppliers. It's always been not purely vertically integrated. I think for the industrial base at large. You know, from the 70s to the 2000s, 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 and industrial base when we offshored all of commercial manufacturing was that you lost your stable revenue. Right. And now you're just dealing with this up and down demand. I think because of that, you know, in the 80s and 90s, 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. Actually the 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 now flipping. And I think a lot of people in the country forgot how to manufacture products correctly and now they're coming to us to help them out with that journey just because of this hollowing out that's now going to come back. I think it is a new structure, but the primes have always had multiple tiers of partner suppliers and multiple different configurations of that value chain. What kind of opportunities are there at Hadrian now for somebody that's maybe 25 years old, never imagined going into manufacturing, but realized there might be a bright, bright future for them in the industry? Yeah. So for software engineers, manufacturing software is 30 years behind the rest of Silicon Valley. So it's your only opportunity outside of AI to do real engineering and work on the national mission. And for people with you straight out of high school, or you're in retail or hospitality, or you're at a desk job, that's going to be automated with AI. Manufacturing is the last domain that's going to get from fully AI automated and they can be really high skilled, high paying jobs in advanced factories that are a really cool place to work. 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 the most important place that we've got a huge talent base that we're really proud of. The children yearn for the factory floor. What's been the difference between this year's re industrialize and last year's? Feels like a decade has passed since then in terms of excitement and interest in American dynamism and rebuilding the industrial base. I think last year we pulled it together with the founders, especially thanks to Austin Bishop who's really built this over the last year. It was kind of a hope and a dream of is the audience going to be there and to be really people believe in the mission. And then this year we've got Trade Ambassador Greer talking about hey, we're going to change all these policies because re industrialization and manufacturing is no longer economics is national security. And 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. And I think the sea change on people realizing how important it is to be a sovereign nation with sovereign manufacturing is huge. And this year we had a 6,000 person wait list. Half of the government is here and all these massive companies and leaders like Shyam from Palantir who are really hell bent on this reindustrialization before we potentially go into a fight with CCP and Robo, Robo Palmer and Robo Palmer Palmer.

I have a question.

Yeah, it's such a. I mean it makes, I think it's such an exciting time because the idea that people don't want to build things, people don't want to create real things. Right. There's so many people I know that you say hey, do you want to send emails for a living or do you want to make ships and planes and any number of cars? Any number of things that we need to make. And if you actually give them that sort of binary they're going to say well making things sounds really cool. And so we need companies like Hadrian that say this is important, it's cool and we have the resources to do this in a really serious way.

It seems like defense is kind of the most obvious thing to re industrialize, it's obviously 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. 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 vacuums and then the Happy Meal toys come at the end? 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.

So. So 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 made Ford cars and then Ford built bombers. And I think this time it's going to go the inverse as we get better at it. But it's very interesting. It's like, why is DJI so powerful? Well, arguably because of Foxconn and that was because of consumer products like Apple making all the iPhones in China. And 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 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 million washing machine plant. It's like incredible. That's just as much of a job creator as defense. But I think that we are going to loop around from all these critical defense industries for Hadrian and then right back into consumer when the time is right. But obviously we're extremely focused on the national mission at this point in time. I cannot wait until our microphones are built in Hadrian factory. So I don't care if it takes 15 years. I'm looking forward to it.

I'm excited. Probably way sooner than that. Thanks so much for stopping by.

Yeah, congratulations.

Have a great time.

Say hi to everybody on the ground.

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 the next stop.

Great to see you.

Thank you. We'll talk to you soon.

Cheers.

Really quickly, let me tell you about customer relationship. Magic Adeo 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 superintelligence. Jeremy, how you doing? Good to meet you.

What's going on? Fine. Hey guys, nice to meet you. How are you?

I'm good. Could you kick us 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 did you get into semiconductor analysis?

Yeah, sure. So before joining Semianalysis, I was a buy side analyst. So I was mostly focused on the stock market, on equities, looking specifically at tech stocks. I was at long only European shops looking at European stocks like ST Microelectronics, Infineon, all these industrial automotive semiconductors. As part of my research, I discovered semi analysis. I was like, whoa, this guy's really good. 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 sell side or buy side experience because I want to 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 24th. We were seven when I joined. No, I think we're 33 or 34. So yeah, it's growing every day, I think. So I can't do it.

Are 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 on the political side. Did you ever interface with any other firms like Semianalysis? 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.

No, I, I agree. I think it's pretty unique. Look like they're obviously on one end there are market research firms. There's like, yeah, folks like idc, Gartner and so on 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 is Goldman Sachs of the world. I guess we kind of found a spot in between. And also it's, it's part of the team because we have over 20 analysts and roughly speaking, you 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 what's pretty cool is when you look at the different people at Seminalysis, 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 want to understand the business aspect and they end up geeking on the data and understand the insights and market shares and stuff like that. So yeah, we all go towards the same goal but have a different set of skills and such.

That makes no sense. So take me through the latest piece.

I can imagine other players in the semi market research space just wait for you guys to publish. Okay. I think now we're ready to form an opinion.

Now we can put a buy rating on it. Now we can slap a buy rating on that bad boy.

Your favorite researchers, favorite researcher.

It's okay. By the time we're done, we're going to get the venture capitalist plan solidified. It's a million dollars a month for any venture capitalist. And we like to say platform fund. Yeah. If you're not, if you're not on the, the semi analysis, one can't really.

Be an AI investor.

More of a tourist.

Yeah. I got to 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 have the Bible. Actually they talked about fabricated knowledge, which is doc, so president of our firm. They said some people think fabricated knowledge is the bible, but actually he works with the firm. That's the actual bible and all. I don't know, I didn't say it. That's a Wall street guy.

That's amazing. There we go. Yeah, I'm a strong believer and I really enjoy the pieces every time they drop. Take me through the latest one Meta.

Superintendent news this week was almost drowned out by the Wind Surface Google cognition debacle. So Zuck came out with this huge announcement Monday and yeah, it almost got swept away a little bit.

Yep.

Yeah, 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 going to carry all that investment tens of billions of dollars? The answer is clearly yes, 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 inferencing, advertising models and all of that. So they said publicly in 23 and 24 and 25, most of that capex, which is going to be like $70 billion in 2025 is for that core AI business. So the Genai, the llama stuff is still at an earlier stage. But the big question is how bold is he going to go with llama? And I think what we showed in this article, hey, there's a lot of evidence that he's doing it on a very large scale. And it's not just empty statements and saying I'm going to build a 5 gigawatt data center in a few years. It's actually things that are already built or under construction. It's already committed capital. And so that's the first story. There's already a substantial infrastructure build out specifically for gen AI and I guess that sort of rationalizes the amount of money that's spent on researchers because if you think about it, yeah, you're spending like, hey, maybe $30 billion this year on llama infrastructure. You're gonna spend maybe, I don't know, $3 billion, $5 billion on hiring top researchers. Yeah, sure, why not?

Yeah, yeah. That's a completely reasonable strategy. And it always mathed out to, 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 billion out of core AI, right? I don't know, it's just like the thought I had.

Or you, or you can also like these researchers can be focused on gen AI, but they're going to develop like state of the art technologies and using like massive compute. And then those state of the art technologies can feed into the core business and end up generating more advertising sales. And if you think about it like meta is growing double digits, $160 billion. So every time they grow double digits, we're talking about close to $20 billion of incremental revenue. It's big numbers, right? It's easy to justify just getting a few billion dollars on researchers.

Yeah, yeah, it's great. I have one question about the history here with meta. So there was this story, I think it came from the first Mark Zuckerberg interview with Dwarkesh Patel where he tells this story of the original llama data center or the reason he has 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 less driven by a social graph and kind of like a traditional CPU based graph query and more about these actual recommendation algorithms. And the way he tells the story is like we didn't want to get caught flat footed. We needed to play catch up in reels. But we didn't get caught. We didn't want to 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 gave us the initial compute for Llama. Does. Is that too much of a simplification? Does that feel like what happened? Do you have any insight into kind of like how the LLAMA project, the initial compute was built out? And then I want to go into the future of the project.

I would just say at a high level. If you think about the amount of money that Meta has historically been spending on data centers relative to what they maybe need in theory, like they have always been overspending, they have always been investing substantially in infrastructure. And same goes on for Google. I think Google to an even bigger extent. But yes, Meta has been a pioneer in building large scale data centers. Over a decade ago, Meta introduced their H shaped data center design. They've been building 150 megawatt campuses since 2013. So that's not new to them like building large scale. And that's why they also already had this sizable compute Footprint. But in 2023, sizable was maybe 20,000 GPUs. That was pretty big. But today it's, yeah, it's updated. Right. You want to 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. But what we've shown in that article is that they're actually today ready to ramp massive data center in Ohio.

That's going to get them 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 are the benefits of a tent? I want to know about data center shape broadly.

Yeah, sounds good. Who doesn't love a good data center shape? Look, the H. I don't know why it's an H. 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. 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 tone to actually getting the project built. So two years is a lot. Many people do that in a year or less. So, yeah, substantial time to build. It was designed for very high efficiency. So they've 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. Basically you get cold air from the alta, you just expel it, hot air, 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. Industry average is going to be 1.3, 1.4, which means that for every wattage 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 and had a very low power density.

Got it.

And so what happened is first of all, at the end of 2022, Meta introduced the first massive design change. They completed through the old age and built, let's call it a more traditional data center design, single story, sort of a big rectangle, faster to build, maybe one year, maybe one or 15 quarters, something like that. Much faster to build, more denser, better suited for AI, it could handle liquid cooling. But what Meta thought, look, I think this is where the XAI story actually takes a big role. I think what Elon demonstrated when he set up that cluster in 122 days, he just shocked, basically data center infrastructure leaders all around the world. My understanding, he made everybody's life a lot harder because before it was like, well, if we do this really quickly, I'm going to need a year, year and a half. And so it's like, well, there's a new standard.

120 days. Yeah.

Imagine like you're the infrastructural leader at the hyperscaler, that 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 took it the other way and just was inspired by it. And basically that's where the tent steps in, which is, let's make a data center in the shape that I can build the fastest. So that, yeah, the only bottleneck is just finding some power and that's it. And buying cheap. Were you saying earlier there's a bull market, Intense. Zuck needs tents. The xai.

The XAI engineers are intense in the office. And then the XAI servers will be intense too. Everything's temporary. I mean, is there something about the 10 structure that's potentially like, okay, this is going to deteriorate faster? Like, what are the drawbacks of moving faster? And then on the PUE question, when I hear a 1 gigawatt or 5 gigawatts they're targeting, is that total power into the building or total power to the actual servers?

Honestly, people generally throw like, they are both. In this case, based on our analysis, it's to the servers. So it's actually going to be slightly more in terms of gross utility power. Oftentimes you see people coating total power just to have a bigger number.

Sure, yeah. Makes sense.

Industry standard practices to code it power. Anyway, in this case, you're going to have 1 gigawatt of compute power by the end of 2026 in Ohio and then close to 2 gigawatts by the end of 2027 in Louisiana. That's compute power to the servers. So anyway, massive compute for Llama.

Is that a vanity metric? Is it a vanity metric to hit 1 gigawatt? Exactly. I mean, Stargate, you have on Your chart at 880megawatts. Is 120 or 140megawatts really going to be the difference between an amazing super intelligence and the next best thing? It feels like we had to cross this threshold and one gigawatt is like. It's a good headline.

Yeah, it's a good headline. That's more of it. It's not going to change much if you happen 900 or a gigawatts.

Yeah, but the more better, right?

Like, you still want to have more?

Of course, yeah, more is better.

It does matter. To be clear, it's not going to change too much, but it does matter.

Sure. Yeah. It probably matters for recruiting, too. It's like you're going to be at the place with the best. What does the best mean? I can. I can, you know, $100 million offers nice round number, one gigawatt factory or, you know, super closer. That's a nice round number. It's great. Look.

And I've got a better one for you. $100 billion, right? $500 billion Stargate. That's something that's pretty funny to me because actually the Louisiana project, which is 2 gigawatts, they said publicly it's a $10 billion data center project, but if you count it the same way as they count the Stargate project in Abilene, it could be like 150 to 200 billion dollars. It's just. Yeah, just big numbers in marketing.

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 going to massively expedite permitting process. Is there deregulation happening at a local level? What can you say? Yeah, I think the piece of context is that since, let's say the end of 2023 or maybe mid 2023, you have a frantic search for power happening in the US and all around the world. And so we've made some numbers, we've aggregated some numbers. If you look at the pipeline, so there are different terms like data center interconnection, load queue, or pipeline. Basically, if you aggregate all of the load requests that potential data centers have submitted to the grid in the US you're above 500 gigawatts. You're close to the, the actual peak load of the U.S. 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 2030, you're gonna have maybe 100 gigawatts of growth, which is an insane amount already. But it means that just 20% of these projects are actually going to be real. 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 going to expedite permits. Increasingly, there's being sort of enabling more on site power solutions as well, like being more open to people burning natural gas on site. All that kind of stuff helps companies, utilities and locations secure those big projects.

I have a question about the shape of the superintelligence team at Meta, when you think about Meta properties, you 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 superintelligence team is more like the database team or the React team and it's like 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 want to 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. ChatGPT is pretty much pulling away in terms of percentage share of queries at 71%. Meta's way behind at 12%. Are there any signals that this is something that would be addressed one way or another, or is it just too soon to tell?

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, you just get more users. I think we've seen pretty good correlation between the quality of models and the usage of ChatGPT. One thing that I think is interesting is when you look at the user base of ChatGPT, you had a surge in early 2023 and then it sort of plateaued for a bit. And towards the end of 2024 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, so forth. So if you think about how Meta could get back at opening and maybe lead that ranking, well, they just have to release better products. 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 billion daily users. So they just need to build a good product and I think users will come and that's kind of the value proposition. 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 a friend or an uncle that's getting into the data center business. We asked Brian, one of the co founders of Core Weave, the other day. He was generally bearish. He knows how hard it is. But what is the. Is there a real demand signal there or is it just a hope and a prayer that you're going to just kind of flip it to a hyperscaler and is that. Yes. Sorry guys, it's over. Easy money's over. Look, as we just said before, like now there's really an insane amount of competition for power and like, and basically like hyperscalers can set the conditions and so you have to be quite sophisticated when you want to approach hyperscalers and you want to 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 30, $40 billion of capex. So when you sell one gigawatt site to a hyperscaler, it's not going to be a small decision for them. 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. So like yeah, they, they just don't want to 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 going to get new business today. But some, some people made a lot of money for sure in 2023 and 2024 by just having like, you know, lockdown. They had 50 acres near high voltage lineage.

That's amazing.

Yeah. It's funny to imagine you've been building a data center, a little mom and pop shop for the last year and then the Death Star data center starts popping up next to you. It's over.

What can you tell us about what changed between llama 3 and llama 4? And why exactly what happened with llama 4? You call it a failure. How did like, how did that happen? Because we were, we were so scale pelled. Right. A 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?

Simple ways. Just a bunch of trade offs that weren't in the right direction. I think if you want to simplify it, you could say to some extent you reach peak Pre training in 2024. I'm simplifying. I don't think it's peak, but let's call it for now it's peak. I think as Blackwell ramps and so on and so forth, you're going to see a new push up. But for now it's peak. And it means that if you want to develop better models you don't have to use pre trained, you have to use the new paradigm which is test time compute and reinforcement learning. 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, in 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. Which means that their flagship model, Behemoth, the largest one, is just not very well suited to this new era. And that sort of contrasts with think of the Chinese labs. They are sort of in the opposite direction because they don't have state of the art chips. They don't really have an incentive to push very hard on pre training. And so they have been thinking harder about pushing on post training, reinforcement learning and test time compute and all of that. That doesn't require such a large centralized cluster as such. It's kind of those two paths. Like on one end you have Meta, on the other end you have the Chinese. And what the Chinese decided to do is just better suited to the current paradigm. So just a bunch of bad decisions or to some extent unlucky.

And so that seems like that ties to this. 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 want to go down. You poach the right researcher, they come over and on day one they can tell you that chunk detention might be wrong for this particular training run. Is that what you think is driving the high salaries? Is that the dynamic at play?

Yeah, okay, yeah. You want the decision makers that understand exactly what trade offs are going to do, that also know how to properly evaluate things or what kind of steps you should take to make sure what is the right choice. And so yeah, that's what you want. The decision makers that had experience that know how to do stuff and that can easily identify the trade offs and know if I want to go in this direction, more reasoning, more RL all that you should do that attention mechanism and not this.

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'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 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.

Yeah, let's just simplify it and say agents. So basically tasks that require using tools that require reasoning, that require long context windows and testing, it's not very good at that.

Okay, got it.

Jordy, last question from me for now. What are you expecting out of Meta over the next six months? They have talent now, they have scale. But the team, the new team is going to need to gel and it's going to take some time to really start delivering. So are you expecting a lot of public launches over the next basically the back half of this year or is this more early 2026? I think back half of the year makes sense. Really back half. Like think end of Q4 or beginning of Q1 26. But for sure you're going to have a few months where probably not much is going to happen because as of today we showed a bunch of pictures of the current cluster. So they already have data center capacity, but there's still some time in order to actually put the GPUs in place and make sure everything runs. So they're going to have some sizable compute that's training ready somewhere in Q3 and so actually have a product release that's more of a really end of the year, but Most likely early 26. I would not be surprised, I wouldn't be surprised if New Year's Eve. We're back on the show talking like we are now about, about a new drop.

Can you, can 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 Llama 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 and so is 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. 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 Deep Seq moment, it felt like Deep Seq was very much distilled from the GPT4 API, not a llama fork. And so the whole debate over, oh, like, you know, some Chinese lab's just going to fork llama and then. And then improve it. So what is your kind of state of the union on open source AI?

The Chinese are eating open source. Like, yeah, they're just dominating the market. It's like one lab after another. It's not just Deep Seq. You had Deep Seek, then you had Alibaba recently you had Moonshot with the Kiwi model. Like, they're just really good at open source. Sorry, at LLM generally. And they're open sourcing everything because they're in some sort of the same position as meta. Like they're not leading, so they don't have any incentive to be closed source. They want to 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. So, yeah, meta is just way behind on open source. And actually the west is behind on open source. The Chinese are just way better at it right now.

But is open source important or is it more just like marketing? Because I've always had this thing about the difference between what was it? Stable diffusion was open source, midjourney was not, and midjourney was able to get the data back from. From the customer because you generate four images in midrange.

To me, it's only open source if it's from the Mistral region.

But talk about the flywheel of open source. Is there an advantage there or is it really just if you're not in first, you might as well open source.

Yeah, it's more. What you said is if you're not a leading lab, you might as well open source because you want people to sort of just help you out, give you some feedback loop.

Got it.

Build an ecosystem. It just makes sense. Also, I would say for the broad community, generally it's good to have open source because it's better for adoption. Anyone can sort of play with the models and develop new applications on top of it and such. So, yeah, I think for everyone it's good that there's open source. But again, if you're not Google, if you're not OpenAI at the very top, 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.

Yeah, makes sense. Jordy, do you have anything else?

This is great.

This is Fantastic. Please hop on whenever you post anything. I'm sure we'll be giving you lots of calls because this is a fantastic conversation.

Really appreciate it. Sounds good. Cheers.

We'll talk to you soon.

Talk soon.

Bye. Quickly, let me tell you about FIN AI, the number one AI agent for customer service.

Bake Off Champion.

The Bake off champion. Number one in performance, performance benchmarks, number one in competitive Bake Offs, number one ranking on G2. And we have our next guest in studio, in person, 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 you doing? Welcome.

The walk in camera.

Camera is working.

There we go.

Let's go. Thank you. How you doing?

Good to see you too.

We got one more juice for you. Oh, fantastic.

We're drinking. We're drinking juice today. Viral juice.

Fantastic, Fantastic. How's it going?

Awesome. How's the show been so far? Super fun. It's been a crazy day on the Internet. You guys are lucky. You launched yesterday. And this morning, one Coldplay conference changed the timeline forever. I know. I saw that this morning. I woke up, I was like, wow. Yeah.

Glad this happened yesterday. Oh, yeah. Because I mean, it's hard to launch these days, right?

Having a couple of people from OpenAI on and it's such a big day for legislation in the United States. Yeah, The Genius Act.

The Genius act and the Clarity act just passed. I'm finding out.

Well, the President is going to sign it, I think tomorrow.

Yes.

Genius app stablecoins will be passed and signed into law in the United States this year. I mean, this week, which is an incredible milestone, working towards it. Three years, four years, five years. I mean, the impact is that for the last decade of crypto, there hasn't been regulatory clarity in the United 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.

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 was, it was chaos. Right. 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 it? What was the low? Was it like $7 billion?

Something like that.

Yeah. In probably the share price went to 32, which was below, I think, the Series E price. And I had joined, you know, like a couple years before the Series E price. But, you know, we all experienced that.

Yeah. What was your path to Coinbase? Did you get. Were you building something else before? Yeah, break that down.

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.

So this was a crypto company. It wasn't quite crypto, but we, we.

Worked with crypto companies. So, you know, Bitfinex, we were actually providing kind of auth and login for them. And so Paolo, like, we go way back because we've been building forever.

And so that business didn't work.

And then when we were winding it down, I was basically trying to figure out, what do I do next?

And I love crypto and is identity like kyc? Like I upload my. I take a picture of my photo.

It was actually a passwordless login mechanism. So almost like you hold your phone up to log into 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 passkeys. And it's this incredible thing where I've now been working on it, this same problem space for almost 12 years. And we're feeling overnight, finally, we're finally getting there.

Okay, so you, so you land at Coinbase, and the way Brian Armstrong tells it, you go to him and you say, I need $1 billion.

Well, not right away. Not right away. Not right away.

But I want to get to the 1 billion dollar. I know you did it for a lot less, but I want to know what. That's my question for the future. But tell me, tell me what you.

Did in between two pizzas. No, so I joined. I joined as an engineer.

Okay.

It was an. It was an aqua hire process. My whole team actually sold to another company, to Twilio. But I was so excited about early today.

Let's go.

And so I joined Coinbase, joined as an engineer, and then pretty quickly on, I just started leading co. They asked me, hey, can you take on a team? I took on more. And for the next five years, I led all the consumer businesses on the engineering side. So if you Know Max Bransburg.

He runs our consumer product.

Me and him were product and engineering counterparts, with him running product and me running engineering. And then after five years of doing that, I thought I was gonna start another company. I'm like a founder. I actually put in my notice and said I'm leaving in six months.

In those five years, what products were you building?

I was building Coinbase, Coinbase Pro and Coinbase Wallet.

Okay, got it.

So, like anything that you've touched as a Coinbase user, those are my teams, we rebuilt the whole product from scratch, migrated us to react native. Coinbase Wallet was the first decentralized product in the Coinbase ecosystem. So I think the context here is like the core business and why the launch yesterday is exciting is the core business was always centralized. Centralized. And it was a gateway to get on chain. Exactly. Custodial. And we'll get into base in a bit. But you were working on these sort of decentralized experiments early. Exactly, yeah. Working on the decentralized experiments early.

You saying it's so early? At the time, you know, I'm an optimist. I've gotten from you.

He said he typed GM and posted it. Probably $100,000. Yeah.

But I thought I was going to.

Leave, but I actually started having conversations with Brian about what did the future of Coinbase look like and what would it look like if we. If we leaned even further into this kind of decentralized world, built more things on chain? Because coinbase had started 10 years ago and it was traditional Web2 business. And so again, the first thing I did was I went to Brian in the kind of fall of 2021 in our exec team and said, if you give me a billion people and 60.

Employees, this was like peak 20, 21, 60 employees.

I turned Coinbase into a DAO. They were like, ha, ha, ha.

Okay. What would you have done?

We're a public company. Yeah.

If he had. 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? We didn't really have as good. Okay. It was more just like, take the constraints off.

Let's take the constraints off. Let's go and do the thing right.

We have this big public company, it's a crypto leader, but it's still built on Web2 architecture.

How do we move it on chain.

In this new way.

And so the vision was there, but the execution strategy wasn't there. Well, and the other context is that Coinbase has been in this incredible position of being the gateway 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 a stablecoin issuer. But you guys had always basically said everything on, you know, you guys do whatever you want on chain and a bunch of great companies sprung up to kind of service that market, but you had to be hands off, which I imagine was pretty frustrating. Yeah, I mean I will say that early on. So Brian has always had the vision of this 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.

Oh, interesting. This was like, this is in 2017, it's green space. Put it up on the stage. It's based today.

And so then we kind of pivoted Toshi to Coinbase Wallet, which is the self custodial wallet that millions of people use, that folks know and love. And we've worked on that for the last five years and that was primarily focused on trading in money. 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 kind of figure out what's going on here, it's really hard to actually find things to do and that are useful. You know, maybe they come on chain for a coin, but then they kind of get lost.

They're like, 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. Like we were missing this connective tissue. And so 10 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 kind of app that solved that.

Problem 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, trade and discover this.

Pay for things too. Pay for things with Shopify at erewhon. You now pay for juice with base USDC on Shopify. Powered by base pay. The whole thing kind of comes together in a new way where, because we now can bring together this marketplace of kind of developers and builders and businesses on one side with consumers, through a really easy to use experience, we're going to be able to grow crypto a lot faster and spin the flywheel. Would I imagine launching base in the way that the product is today? I know it's a pure software business, so very different from the coinbase's traditional business, which is effectively acting as this regulated financial institution. Would it have been possible to launch this a year ago, or did you need the White House to launch some tokens and a few other events? Well, I think the biggest thing that we needed is we needed the technology to mature.

Right.

So when, when we had this vision three years ago of building base, the first thing we started with was actually the platform. Right. It was the chain, because we'd spent a year trying to figure out, okay, what's the product we build to kind of bring this next generation. But explain, though. So you had the chain, but there was no token attached.

How do you look at Playbook? We went back to the tried and.

True method that people had been following for 100 years, which is that you.

Focus on building a product that people love. 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. And we basically said from the beginning, no, we're gonna build a chain, 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.

But if I, if I take it to, like the Bitcoin analogy. Yeah. 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. So there's this economic incentive now that gets distorted all the time when people run like random chains and stuff. And I understand the rationale, but is there an incentive for other participants to, to help run the infrastructure, or are you doing something where you're splitting it across different groups? How does the actual chain stay on? 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. So as long as the Ethereum miners are happy, then base run. Yes, exactly.

Then there's A decentralized network that's also based that people use to get access to the network.

And the thing that's bringing people to.

The network is that they're building things and then they're using those things. And so here's two examples.

The first one is usdc.

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, which is rolled out to millions of merchants where they're actually taking USDC in their wallet and they're paying for things. And that's global, it's fast, it's cheap, it happens instantly. And there's cool rewards, there's cool that the it's retailers effectively, which is if you pay with USDC will give you one point back or something like that.

Because the interchange.

Yeah, exactly. Debit card or credit card. Yeah. So it's 1% back with base pay and you can earn 4.1% on your USDC when you're holding it.

It's pretty good.

Right. And it's an instant global payment method. 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 people are coming to to base for payments and stablecoins.

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.

Right.

If you look at the last 20 years, you've had so much creativity pour into 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 going to 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. And so one of the big things.

That we're focusing on with the base.

App and one of the reasons why.

People are coming to use it is.

That when you post on base, you actually earn.

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. And I think this is a novel.

Use case for this platform that we built with base and base chain.

If somebody opens a base app, their wallet's loaded and they start scrolling.

Does that cost them money?

Does that cost them money? How does that. Actually, it doesn't cost them money, but like I can literally show you, you can decide if you want to support a post.

And so like here, this is on.

My feed and I'm just like, Jesse, I'm on my feed, I'm creating content. I posted this great base juice content and oh, there's a bug.

Live classic.

There we go. It happens. Day one, base juice content.

Right. And you have the normal things you.

See here, the, like the comment, the retweet, and then you have a new thing.

Yeah.

Which is market cap.

Sure.

And so this is basically the value of that content. And this one's worth $15,000.

This one's worth $84,000.

This one's worth.

How is that possible? I mean I like my. I've been on YouTube for five years. The best video I ever posted got 8 million views. And I got a check for 20k from YouTube.

Well, that's actually pretty good. YouTube is one of the platforms that pays creators really well.

They got 50% and I thought that was fine because they brought me all the users. So I was actually pretty happy with that. But like, how could, how could something have, how could a piece of content have market cap?

Well, yeah, no one else wants to.

Buy it unless they want to buy the revenue stream. And there's been some of those projects on that.

Yeah, how? Startup, Startup CEO. Well, this is on X where no market cap on this one. Startup CEOs can't even hug their chief people officer at a concert in this country anymore. 1.6 million views. 50,000 likes.

50,000 likes.

I'm sure the creator payout will be decent, but this looks to me like potentially a nine figure market cap if I had ripped it on base. Yeah, well, seriously, seriously on these ones that I posted, this one I posted yesterday that now has an $84,000 market cap. It's done like $4 million in volume and I earn 1% of all of the volume. And so that means I've earned like what, 40, $40,000.

That's insane. Right? So you get a viral post that doesn't feel like economically fair.

Well, but think about this.

The place where that value comes from is the fact that your content is valuable.

Right.

How have these platforms, how have these.

Platforms built multi hundred billion dollar businesses if the content is invaluable?

Running ads, but what's bringing you there the content and then they pay you to bring more content.

An ad is a way of monetizing the value of the content, 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.

And then the.

The kind of. The. The economic off flows of that value are getting redirected back to the creators. We love ads the show. Will we be able to see ads in the base app? I know you guys acquired Spindle.

I don't think.

Well, stay tuned in the next. I want to run some talk about the integration and the kind of mini apps. Dan from Farcaster has been on the show. I know you guys have some integration with the Farcaster network, Is that right?

Yeah.

So the whole social feed, all of the connection graphs, you know, how followers and following, it's all powered by Forecaster. When you're posting content, it's powered on Forecaster. When you're coining content, that's powered by Zora, it's another protocol. What we've done with the base app is we brought them all together.

That's cool. Including Shopify.

Including Shopify integrates. Including messaging XMTP, which is powering messaging. They just raised a $20 million Series B. They're an incredible decentralized messaging protocol that is.

Is powering secure encrypted messaging with agents 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 a chat with your friends. You can just like drop a bet in there that you can say to agent, hey, like, let's bet $5 that the Dodgers are gonna win tonight.

Okay, that's.

And then it's immediate bet. And then you can say, hey, send $10 to all of my friends.

Sure.

And it just works because it's built on this platform and you have these open protocols that are working together. And so going to your point, we built on Farcaster because we believe, 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 them. And so this is where the mini.

Apps come in is because we 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, I think the Farcaster, which is like, literally, you can open this up and we're going to be on the live stream here live now. There.

Oh, wow.

There we go.

Right there. It is so cool. But one of the really cool things.

And to be clear, this, this was organic third party. 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 want to sponsor you. And Bracket, for instance, this is sports betting on base. It's awesome. It's so fun. You can interact with an AI jit. But our lawyers, we're going to, our lawyers are like bloodhounds. They're going to, they're going to be like chomping at the big thing that's really incredible about this app is that it's all connected and so I can actually tap in bracket and I'm like, okay.

Oh, okay. Yeah.

Hey, stay one.

Oh my God.

Come on, Jesse. What's going on here with this mini app?

And in theory, yeah, this is, this is the start of the auction, the auction driven. But, 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 Bracket.

Whoa. Now bracket is right here.

Okay.

And then I'm like, okay, I'm just going to buy Bracket. And I'd be like, cool, let me buy $5 a bracket.

This is not financial advice. Seems, this seems like we're not going to buy it. We're not going to buy.

The thing that's fun is like, it's just wildly chaotic. It is an entirely new surface area. Coinbase has never been about chaos. But, 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, I mean, you said that the goal broadly is to get a billion users on crypto. Crypto on chain. On chain. That's. Give me the state of the union. Where are we today on that journey? Like, what are the different buckets and how big are they?

Yeah, so we're trying to build a global economy 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.

And of course I'm going to get 5 billion people on chain because we can get everyone who has an Internet connection on chain.

Let's go. But a billion.

Nice number. And 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 globally around hundreds of millions. Hundreds. A lot of People hold Bitcoin.

Like bitcoin is very well used, but.

It'S not something that people are using.

Their day to day life.

I'd say there's probably tens of million.

People around the world who are using stablecoins. And then I think we're in the millions of people right now who are.

Really starting to use these on chain products.

And that's across base, it's across Solana. You're seeing innovation everywhere. And you know, we like to work with everyone. We think about base as a bridge, not an island. We're actually connecting with everyone and figuring.

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 kick up the next kink in growth.

So my question is like, when we're, when we're following the, the ChatGPT story, there's obviously DAUs, but the chart that everyone's obsessed with right now is that chat GPT minutes per day is skyrocketing into 30, 30 minutes per user per day. Something like that. We're seeing lots of queries go up. My question is like, with financial products, 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. A check on authoritarianism. It's awesome but like, I don't know that I should be like interacting with bitcoin daily. But what are the other metrics downstream 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. Yeah. You know, messing around with dollars all the time, I'm actually probably unhappy. 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. Awesome. 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.

I'd say base though. We don't really think about it as a financial product.

Okay.

There's money involved because money is a part of everything. But it has social, ads, core, it has chat, it's has apps. And so people are going to come.

To base just like they come to their other apps. Time on site should be a key metric.

Is the thing that we're looking at. We're looking at maus. We're looking at, we look at kind of two things.

We look at all that.

Yeah. Dao. And we look at like weekly active users and then we look at weekly transacting users where it's like, are you actually doing a transaction on the chain? 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. And then the, the transacting user is like a deeper engagement.

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, which I'm opening. It's probably a problem. I'm probably like owe someone money or overdrafted or something. Exactly.

And the really incredible thing about this kind of conversion rate of active 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 where people are doing all these things with money. And we're seeing way higher initial user conversion rate to actually doing something on chain.

That's awesome.

Because now it's not like, oh, you have to go, like, make an investment decision. It's like you can like your friends post.

Yeah, 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, 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 a shift we're trying to make.

Yeah. It's super cool. Like the, like, we know that the everything apps work elsewhere. Yeah. They don't work in America. For some reason, this feels like an end run around a different strategy to try and make.

It's an everything app for a specific subculture. Right.

Right now. But you know, a billion people, Is that a subculture? And what I'll say is we were.

Just out of Erewhon. I just spent two hours at Erewhon and people, we were giving out free juice. I was filming content. We got some good content coming later. And I was just talking to people about the juice in the app and. And when people hear, especially like millennial Gen Z creators when they hear, do you want to join a free social network where you can get paid to post and you want a free juice? They're like, hell yeah. I've been posting on other social networks for a long Time. And I've never gotten paid.

Okay.

And so that hook of your content is valuable. You get paid. You get paid. And you can get paid for it.

Because that value is going to get.

Unlucky unleashed by the free market.

Yeah.

And then we're going to distribute it on crypto economic rails that are this next generation Internet platform.

Well, good luck. We got to get to our next guest. Thank you so much.

Can we get a gong hit on.

The way out here?

Let's go.

Get the base app at. Base app.

You can get on the wait list. We'll be letting more people on every single day.

There we go.

Founder mode.

Talk to you soon. Have a good one.

Great chatting. Do it.

Up next we have Higsfield. Alex from Higsfield AI. We've been using Higsfield AI to generate crazy photos. Jordy posted one of a horse. 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. Not exactly sure how they do that.

I want to talk to it.

Welcome to the team. Welcome to the stream.

Yeah. Higgs Field. We have a lot of amazing people on today. I have been incredibly excited to speak with you. We were just talking. I don't know if you caught it, but I posted an image generated by Higsfield a couple days ago. I think most people still think it was real. It was a completely ridiculous image. It was like this cinematic upshot of me on a horse that had. I don't know why people didn't catch that. The neck was quite a bit bigger than a regular horse's neck.

But it was great. Clearly a breakthrough.

Yeah. It was the first time that I've seen an image generation product and realized that I think you guys have probably already started to take over Instagram style content, 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. 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. Great. Thank you very much for the kind words. Definitely. It's great to be here. Thank you for the invitation. So quickly about myself. I'm a veteran in the video generative AI space. I built maybe some of the most iconic products in that space. Maybe you remember Snap face filters?

Oh, really?

Yeah, totally.

That's amazing.

Yeah. There were like billion people throughout the world who played with that. Just a billion and this was pregenai, right? And when the models were like thousand times smaller than they are today. And although these products were specifically targeting like augmented reality use case so basically overlay on top of the existing camera. 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. Even today we can see that there is an emergence of UGC contents. The quality unfortunately goes down and with Hicksfield we create new ways to tell stories helping creators and brands to get attention on social media.

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 computers versus changes in the algorithm. We've heard rumors that images in ChatGPT isn't pure diffusion. 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 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.

Totally. First of all, I think it is important to admit that today we are early in our journey with video AI technology. 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 to build a reasoning engine. On top of that, let's say you post a video, the system is going to suggest you and analyze your accounts and actually provides you with more suggestions what to post. And eventually I think we are going to find ourselves in two years in a new version of the world where most of the content out there is AI generated. There is no way to stop that. And on our side we do our best to provide a simple interface so that non AI users let's think about market of social media professionals of tens of millions of people. So that's this broader user base can actually tap into the power of generative AI technology. And I think we will see that the models are going to 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 allow us to substantially differentiate from the competition and we do believe that the general quality of the technology is already there to surpass average human produced contents.

I have this one eval for AI image generators where I ask it to create a Where's Waldo? 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? 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 werewolves work at a very small scale. And they actually piece together the full image like it's a puzzle 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 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? Yeah.

This is a great question, by the way. I think this is a trillion dollar question which you just asked, which is we all saw the power of reasoning engines with maybe models like O3 and then we see that at Grok 4 they actually spend on reinforcement learning more than they spent on the pre training stage. Right.

Where is the market right now in terms of pre training, post training in images in your estimation?

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 for video AI models can be maybe 20, 50 times lower compared to the pre training stage.

Wow.

Yeah. But we are really just scratching the surface there. I think then the future is building the video reasoning engine. And this is a trillion dollar question because this will. Because think about the brands out there today. What we are seeing is that brands start to and agencies, they start to actually experiment with various models. And primarily we all rely on our stereotypical understanding of the customers and some maybe qualitative data which is available out there. I strongly believe that with this video reasoning engine, the way 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 a b test them and see which one performs the best. And today there are only a few top creators who actually do that. If you look at MrBeast and similar size of the creators, they do ab test thumbnails very aggressively. We all know that they actually a b test the hooks. So far this privilege is only available for larger teams 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 AI generated.

I mean, what you're talking about is basically like RL ing on humanity with human graders, which is the algorithm and likes. And that's effectively what the Mr. Beast algorithm is doing. My question is, 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 going to 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, it's always like cars driving looks amazing. Then all of a sudden I'm looking at the front of the car and 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 going to do RL at scale in imagery?

This is a great 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 Hicksfield, obviously at the post training stage, not yet at the inference stage, just because of the cost associated with that.

That makes sense.

So we have to train video generation model in a, in a way that it's sort of competing with video understanding model. And like at Hicksfields we, we, we cannot go and label millions of the videos. That's why we have a set of powerful agents for video understanding which help to tune the video generation process. But this is the process in the vacuum itself. What's going to be powerful is when we condition the outputs of the model and train the model based on the engagement data from the social media. First it's going to 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. So training the models based on, on these outputs is going to lead to complete the next level of reasoning and success rates for the end customers.

Cool. We have another one.

I know we're totally over. 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 and private jets. What happens when anybody can be on a private jet 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 content creators? Hopefully. So first of all I need to admit that we're a technology platform first and foremost. Although we think about ourselves as a scientist and we are constantly monitoring and listening to the creators and how they use the technology. And I cannot bring up the names out here, although like some of the top 50 YouTubers in the world, they actually want to get reads of the team and build own agency of AI influencers. To be honest, they actually, they have a bunch of ideas which they want to sell and they don't want to condition their existence on the social media just to their likeness today because people just are getting older and sometimes they get irrelevant. We have seen many examples of that on social media and creators actually want to create those digital agencies where they can express all their ideas through various synthetic AI influences and they can use Hexo platform to do that. Yeah. It's a very, very wild time. Let's have you back on again soon. This is fascinating.

Yeah, we'll talk to you soon. Thanks so much for hopping on Alex.

Thank you.

We'll talk to 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 Re industrialized. Sorry to keep you waiting. Billy, 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? Yeah, I can go vertical.

That is possible.

Here we go. There we go. Where are you? You're in a cabin. Explain. Join you from a Seaglider. Look at that. No way.

It's super comfortable in here.

We got plenty of leg room.

There we go.

Incredible. We got Internet. This is the future. This is amazing. Wait, wait. So wait, are you, is this like a demo? Are you actually in.

I do believe that's a screen.

Behind screen behind you. This is the demo. You guys okay? Perceptive over that. We just talked to the AI generated guy who says all this will be fake in two years. So you know, I don't know what to believe at this point. We're building hardware in the real world, guys. We're at a re industrialized conference. Thank you for bringing me back to the real world. How is re industrialized? Give us the overall update on Regent. It is awesome. Like hardware is cool. Again like building real stuff is cool. Atoms are cool. So it's awesome to be here for this. Yesterday we just announced the launch of Regent Defense here at Re Industrialize, which is a big step for the big step for the business. Congratulations. What is region defense?

What's the immediate application of the glider in a, in a defense context?

So region's actually been doing defense for years. This is sort of a growth of the business we've already been doing. Basically everything is about moving around island chains as our key conflicts and theaters.

Are in the Indo Pacific.

So it's going back to World War II style tactics. It's about naval operations, 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 sea gliders, the high speed, low operating costs, you know, ease of operation and in the DoD space that we're 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 of years now and now we're expanding as we get into our full scale prototyping, expanding that product portfolio to meet the need. Very cool.

Incredible.

Anything else?

I think that's it. Thank you. Thank you for this demo. This is the best. This is the best call in. The best guest call in I think we've had. So guys, we got to get you.

On the sea glider in Rhode island.

At some point too.

We're doing the next call in from the. We have real hardware.

We'll do the whole show. We'll do the whole show from the glider. I hear it's very smooth. You know, it's perfect for live podcasting.

Starlink on board yet? We'll put Starlink on board for a TVPN episode. There we go. I love it. It's there, it's there.

Awesome.

Fantastic.

Well, congratulations to and the team on the progress and say hi to everybody at Reindustrialize for us.

Will do. Thanks guys. Enjoy the rest of the conference. We'll talk to you soon. And in the meantime, let me tell you about eight sleep.com get a pod five, five year warranty, 30 night risk free trial free returns, free shipping, go to TBPN. And we have our next guest joining the stream. I'm going to guess that it's Jonathan but I'm going to make sure once he Joins. Welcome to the stream. How you doing? Did I get that right? Yes. Jonathan, what's happening? Security.

A lot of people call me jmo actually. So, jmo, what's up?

Jmo, give us the news. I hear we you got some good news. Break it down for us.

Yes, we are coming out of stealth, launching a new company called Confident Security. It's about providing confidential AI didn't raise any money. We raised 4.2 million with decibel Commons.

Congratulations.

There we go. Why is Confidential AI important? I can imagine a bunch of reasons, but what was the kind of catalyst to start the company? Yeah, I think, you know, unless we do some work, I think we're going to have Cambridge Analytic 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 Apple shouldn't just be the only ones providing privacy, everyone else should do it too.

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? 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. That's right.

If you are taking that, 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 gapped environment not seeing all the data. You know, standard like top secret versus secret type of stuff. But this is, you know, 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, maybe you care about how it's going to be used. And after the recent OpenAI court case where they were forced to retain deleted data, I think people are being a little cautious.

So how do you actually plan on plugging in to companies? How does the product actually get installed and used on a day to day basis?

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 making requests to that server to use our SDK. And 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 to.

The data, all that type of stuff. And is that just like enforced at an engineering level or enforced at a legal contractual level?

It is a technical level. Great question. And that's what's different. Right. You can make promises that say you want to train on the data, but we make. It's a technical guarantee and it's essentially a bunch of fancy cryptography that makes that guarantee. So we actually offer unlimited liability and indemnification for data breaches and misuse because we're so convinced that we cannot see the data. No third party can see the data.

Yeah. So what's the go to market? Like you mentioned example of a big biotech company. Is that the most obvious customer or are there other segments that are logical?

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? This helps, you know, manage all that stuff. Privilege for lawyers. Same problem they're trying to figure out, well, if I give my data open air, have I disclosed it and it's no longer subject to privilege.

Yeah.

Super interesting.

Close. Close it out with how big is the team? Where's the team size going? What are you hiring for? What comes next?

We're about six people right now and we've been building, building, building, building and now with the launch we're ready to start selling and so our focus is bringing on salespeople. I've done two previous companies and I've every time I've learned that I should spend more on sales.

So that's what we're doing. Interesting. Good takeaway.

That's good. There's going to be. That's the environment that a great sales leader or individual contributor wants to join.

I mean it takes a lot of technical CEOs like 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?

Yeah. J Mo, thank you for joining.

Thank you so much for joining.

Come back on when you have news and thank you for doing this.

We will talk to you soon.

Cheers.

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Next we have Contextual, the founder of Contextual AI.

Welcome to the studio Studio. How are you doing?

Bring them in. What's happening.

Also if I have this correct, the inventor of rag. Correct.

One of the authors of the RAG paper.

Okay, okay.

So yeah, that was a team effort, lots of folks and there's a long.

History of, you know, research that has gone into that. Yeah, give me the state of the Very, very humble. No, the man who invented RAG by himself in a, in a, in a cave of scraps. Give me this state of union on rag. Some people are saying, oh, just use a bigger context window. Like 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? Yeah, so the RAG is really a very simple idea.

Right. It's about having Gen AI work on.

Your data 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. So it's a very simple idea. How people do RAG right now is radically different from what we did in the paper originally. I think the buzzword these days is about context engineering. How do you actually give language models the right context so that 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 a, your Claude 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 going to fail. And so that I think is an opportunity that a lot of companies are looking at now? How can we make sure that this.

Context layer really works? 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 basis of RAG is like embed all of that into weights and then, and then search over it. But is that happening at the state of the art right now?

I think so.

You're right.

A lot of it is web search and if you want to do web search efficiently at scale, then you probably use simpler algorithms. So things that aren't that involved. But even web search very often uses embeddings and where you search there.

So you could argue that web search is also just Interesting. Why is search so bad right now? I feel like, I feel like I can't search my email for anything and Google has like searching models. 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 want to wait 15 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?

Yeah, I mean that's a hard problem, right?

But I mean AI should be able to search your inbox for you and just right answer, right? Yeah, that's the goal.

I think it's happening. It's just search is a really hard problem to do.

You don't want to really do it.

In a single step. So the way you do proper retrieval is multi stage sort of cascading with smarter and smarter models that look at.

What might be a relevant result.

But you're right, if you retrieve the wrong things then you can never give the right answer. That's a big open point. Where are you guys focused today? So there's a number of different use cases. Yeah, so the use cases we're looking at are really your bread and butter use cases for rag. 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 RAG is that people think that it's easy, which is actually probably true. If you have two or three documents you understand the use case. It's not that complicated.

But when you go to the real.

World and you talk to some 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 so you can't.

Give the right answer even if you have a great language model. Yeah, I mean the scale of data at some enterprises is probably what, seven orders? I mean I imagine like the number of emails sitting in Gmail inboxes across the entire network is way beyond millions. Fascinating.

That is also to your earlier point about like long context models. You can't fit all of that in the context of a language model.

You need to retrieval. 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?

Yeah, so we're 70, 80 people working.

On a lot of interesting problems.

Kind of nice Kind of across the, across the board, trying to expand into different use cases as well.

So.

So beyond the traditional rank use cases, looking at things like root cause analysis.

Codegen, because Codegen is very hard and.

Also often requires technical documentation that you then want to incorporate in your Codegen. So yeah, making a lot of good.

Progress on very interesting problems. 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.

Hope you have a great rest of your day. We'll talk to you soon.

Thanks for having me to meet you.

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And up next we have OpenAI big launch today. We are going to break it all down. Welcome to the stream. How are you?

I think we got caught up on guests.

We have two people.

What's happening? Great to have you guys on the show. Hi. I will start by saying sorry about the. Sorry that Coldplay had to have a conference last night. Like, you know, it was hard to, you know, hard to predict.

You don't normally launch anything on the Internet.

I know. We were just talking about this. Yeah, well, we're here. No idea. He says it showed it to me.

Okay. Well, normally you don't have to, you.

Don'T have to plan your launch schedule based on Coldplay.

Yeah, Coldplay concerts.

But maybe it's something to keep mind.

Break down, break down the launch. What is in. What should we be focused on now?

So I used to work on Deep Research. Y 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 complimentary 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 very flexible and pretty powerful model. We trained it using end to end reinforcement learning like our past reasoning models and yeah, it can make slides, make spreadsheets. Yeah. What initial use cases are you guys most excited about? Have you been using internally? What kind of companies should be and just individuals should be kind of taking advantage of it as of today?

Yeah, I think so.

Deep Research, as you were saying we combined sort of Deep Research and Operator to build this. Deep Research was really good at research. Like I think the best product out there in terms of, or at least that's what I thought or I still think in terms of researching. And then Operator was there to take actions. Combining these two, you open up a lot of possibilities. You can do research, you can do actions, you can do research and then actions. And then 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 for example, personally speaking, I've been using it a lot internally just to even talk with the code base, 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 let's say a new code base for me. And then the model is also very natively multi turned, which means that I can just have conversations back and forth with it, which is not true necessarily. Wasn't true, for example, for a Deep Research model which released earlier this year. So it's really, really useful from, 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. Secondly.

Oh, sorry, I was going to quickly.

I was going to 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. I forget to book it most of the time and then I get in trouble. And then now with agent, you can schedule tests, et cetera, you can just say, look, every Thursday just go ahead and figure it 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. So things like that.

That's amazing. Once Deep Research came out, it felt like there was this little bit of a meme about like we have 15 minute AGI and 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 you. You said it's multi turn. So what does the typical interaction look like? Is there a wider variance? I noticed in the, in the latest revision of the ChatGPT app, there's now a little like 15 minute UI element next to deep research to kind of hint that, hey, you're getting yourself into a 15 minute cycle. Obviously there's lots of efforts to spin that to speed all of those processes. Processes up and that'll come. But what does 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?

Yeah, I think our team in particular is really focused on solving harder and harder tasks that take people more and more time. So a lot of the agent tasks can take anywhere from like around five minutes to. I've seen it take over an hour.

Wow.

But a lot of times these are tasks that would have taken humans many, many hours. So I think as our agents get better, probably the length of time they'll take to solve tasks will also get longer because just the tasks will become so much more complex. Imagine a task that takes a human many days. Yeah. So the 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 a voice extension to it, where as an example, I might say, hey, I use Geico right now. I want to potentially switch. Can you go out and do research? 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 you're like, I need to cancel.

An old Internet line on Spectrum right now and they only allow me to call during weekdays.

Yeah. The other example, you're on a vacation and you want to change your flight and you know you're going to maybe have to like call and sit on a. Wait. So is that the direction that you think we're going towards where it can not just browse the web, but then actually start to. 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. But yeah, where are we going? 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 Issa just mentioned. I think we want to continue to solve harder and harder and longer and longer tasks. I think today we can solve, let's say an hour or so of tasks. Hopefully in future we can solve multi day tasks and it might take longer, it might take shorter depending on how we're doing. But continuing to improve on the reliability and complexity of tasks that we can continue to solve. That's 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. 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. 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. Other companies introduce voice as an intentional point of friction, like the sort of call to cancel.

Spectrum would never do that to me.

Yeah, they would never do that to me.

Talk John though.

And so that to me feels like this. If I can go into a web app and just click cancel or do something like that.

My question is about the user experience of 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 research to take 15 minutes and so I know when to go to Deep Research and I'm going to come back later and it's great. But if there's some variability there, is it going to 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?

Yeah, I will send you a notification. I think actually the fact that Deep Research always takes the same length of time is probably.

I don't want to.

Say a bug, but I think of it as a feature, not the end state.

I think of it as a feature.

I should think for as long as it needs to think.

Totally.

But I think for Deep Research it always just thinks for a really long time. Even if you ask what the weather is.

Yeah, that's true.

So I think that's a better middle state and 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.

Yeah, 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 3000 works. I want everything. And I love that about deep.

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 proactively. Go to the website, figure out the homework, create.

A teacher's gonna be like, yeah. The teacher's gonna be like, check this homework.

If somebody wants to say that's not AGI, I don't know what to tell them.

Yeah, I don't know. What about other tool use? Jordi mentioned phone usage. You mentioned spreadsheet integration. What's kind of further down the stack of integrations that you've already announced that might be kind of under explored or underappreciated at this point in time?

To me, I think that the tool that we've given the agent is very general and powerful. 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 do most things. It might not be the most readable to a human. So I think that now it's about pushing the capabilities. 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. So I think that we just need to make it better and better using the tool it has. The frontier continues. I think we. As ISA said, the tool is extremely general. It has access to a browser, it obviously has access to terminal, and we can give it access to as many APIs as possible. That should allow you to build whatever you want to do. Generally speaking, for example, you can totally imagine in future there's access to a voice, API or whatnot. Whether it's internal, external, depending on how things go, you can have access to everything and build everything. But we still need to push like, it's still early. Like we have not solved everything. It's still early. We still want to make sure that we can solve use cases with really, really high reliability. And that continues to be a pretty large focus. Yeah, well, I'm excited. I mean, think of. Think about a world where you can give it access to your password manager and things like that that it just immediately can.

We're just API integrations, right? 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 chatgpt yet, but I could imagine those being way, like the reports being way richer if you can define them. And then sometimes when I'm. When I'm just generating like a general chart, I actually want to 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?

People? Everyone on Proplan should be able to use it by end of day today. And we'll get it to plus users over the coming days and then enterprise over the coming weeks.

Very exciting.

All right, well, congratulations on the launch. Super exciting. We're going to turn this day around. It's now just about opening eye. Agents, ignore all Coldplay memes.

Ignore Coldplay.

Well, thank you guys for joining.

Thank you so much for having us. We'll talk to you soon.

Cheers.

Bye. Up next, we have Dan Schipper, friend of the show over at every who.

Got early access and he's been using agents and we're going to get some feedback. John just spilled his bass juice all over the table. All over the ft. You. That's really disappointing. You're not going to be able to read that on the way.

I have lots of papers that I can do.

We have Dan in the waiting room.

Let's bring him in.

Hello. There he is.

How's it going, guys?

Great to see you.

Every time you're on, you're in a different place.

You finally caught me when I'm not traveling.

Yeah, yeah, yeah, yeah. This is the first time.

I like that. I like that light. Light up logo in the background. Very nice, Very nice. Thank you. Subtle. Kind of in home, out of home advertisement.

That's what we're going for. Exactly.

What's happening? What's on your mind today? There's a lot going on. There's a lot going on. We're here to do a vibe check. Vibe check of ChatGPT agent. So I was lucky enough to get to hang out with it and work.

With it for the last couple of.

Days before it got launched. And I have a bunch of things to tell you about how it works. Incredible.

So, as your previous guests, 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 it go through all of our support emails.

And all of our feedback forum posts.

For the last like two months.

So it's like about 1500 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 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 our 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 it would have taken so long.

So long.

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 kind of want to see like once a month, but no one wants to do that once a month. And you can schedule with ChatGPT agent.

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 it's really freaking cool. That that's wild.

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, it turns out the team just said that for a week and then like stopped watching it. And if it's running you're like burning stuff.

Dan is every foundation lab's worst nightmare because he gets on the most expensive plan and uses it a hundred times more than anyone else. You're single handed going to bankrupt a lab.

There's other, there's other users that are probably higher margin. But yeah, talk to me about 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? Or was it really as simple as just a prompt?

It's basically a prompt. What happens is you type in a prompt, you say, I want you to check out Quora, I want you to check out our emails, I want you to check out our support forum. ChatGPT has connectors so I previously already connected my Gmail. So you just log in on the.

OAuth then what it will do is.

It spins up its own computer in the cloud, its own virtual machine. It goes in the browser and starts browsing the web. It also then connects to Gmail if it hits a login. For example, when it hit LinkedIn it couldn't log in. And you can take over the browser in the virtual machine and type your password in, which is a little janky, but it works pretty well. I think the interesting thing about this though is that it 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 ChatGPT agent is they're essentially abstracting away the.

Browser and the computer. So all you're doing is you're interacting with ChatGPT and on the back end.

All this other stuff is happening. So it doesn't matter if you're on your phone, if you're on a crappy computer or whatever, they have this whole virtual environment set up.

It spins up, it does the task.

And it spins down.

It's a very good consumer experience. Claude code, for example, from Anthropic, which is I think is way more for developers.

ChatGPT agent is way more, I think for consumers.

Claude code is all on your computer, it's all in the terminal and it.

Has access to all of your files and you have the ability to use it wherever and whatever 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. And I think that still the crazy thing, yeah, the crazy thing there is. Doesn't Claude code have more downloads right now than the actual Claude mobile app like the reg?

It's something crazy like that. 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 they can't use it.

Because it's in the terminal and the terminal is really intimidating, but it's an incredible product.

So yeah, how would you solve this problem if you were to do the same eval of generate your net detractors, net promoters using Claude code? You just open up the terminal on your laptop, you wouldn't be able to do it on your phone, but 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?

Yeah, it could do that for sure. And I think the nice thing about.

CLAUDE code is.

You get many bytes of the apple and you can. So for example, with CLAUDE code, what you can do is you can have it make a full plan so it can output a full markdown document with 300 or 500 or 1000 word plan. You can modify it and go back and forth with it and then have it execute it. 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 think about that as.

Opposed to just clicking the connectors button. Or it does have a web research tool so it would be able to go to our feedback form 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.

So I think you get basically the same experience.

I think cloud code is a little.

Bit more controllable and therefore a little.

Bit more powerful, but ChatGPT is just much easier to use. That makes sense. What use cases do you expect ChatGPT agents to have the most PMF around? I was imagining the student use case, which is just like monitor the homework that I have due across. I remember in high school even teachers would post their homework on websites. You could basically run something that was like, 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 sign off on, or tweak and.

Then automatically submit college applications, attend college.

Write my college essay, get a job.

For me, 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. Watch out Cluli, ChatGPT agents coming for you. Good guy. Boom. Breaking news.

Breaking news. But giving this powerful of a tool to everybody immediately, not everybody's gonna realize it, adopt it right away, but you can imagine a few use cases just spreading like wildfire.

Totally. Yeah. I mean, I think what are the.

Things that you would immediately do if you had an assistant?

Like if anyone, if someone just dropped.

An assistant into anyone's lap, like, what.

Was the first thing they would do?

I don't know, help me 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 24 hours. And it just does that incredibly well.

And I can go into, you know, go behind login walls and paywalls and all that kind of stuff.

So I think those kinds of use cases are going to be the, going to be the most interesting ones.

But I honestly think right now, for most of my consumer use cases, 4.0.

Or really O3 is the best. It's much faster. I mostly don't need it to use.

A full computer to spin it up.

So I see ChatGPT agent as being something that you use every once in a while rather than something you're using every day.

Sure. Yeah. So, so we're, we're, we're increasing the level of like, complexity. Like, like 4O is kind of a Google search replacement for me now. I just kind of hit it with like, when was this person born? 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.03. 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 going to 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. This was something we talked about with the OpenAI folks, was like, if it gets stuck, it pings you. I like that. Deep Research, Yeah, it takes 15 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 going to take me a couple minutes, like, then I'll come back to it. 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 going to pause all that while I ask you for an update. Like, it feels like there's a little bit more. I got to be on answering questions there. But push notifications maybe solve that. Walk me through, like how it in how involved you were, how active of a process it is. I mostly was not involved every once in a while. Like, it does have a, like a stop.

You can help to 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 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. And ChatGPT agent has its own, like, cool UI where you can kind of like see interesting animations of what it's like, what it's researching or which websites it's using and stuff like that. So I find myself actually glued to.

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 like, there's a sort of emotional process of training yourself to be like, it'll let me know when it's done and I don't have to like, watch over the shoulder. Like, we, we design a lot of assets here at TVPN and that, like, even if I trust the person creating it to do a great job, there's still this tendency to want to like, hover and be like, okay, tweak this, tweak that. Oh, let's do it this way in real time versus, like waiting. But it's the same thing with 4o.

Early on, I would kind of be in this loop of like, okay, I got a result. I still got to go fact check this and check the underlying links because hallucinations are a big problem. Well, now that these 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, 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, am I going to delegate this or am I going to 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, 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. And so the more experience you have with the tool, the more you can know. Like, okay, I don't have to check this 40 answer or this looks a little fishy. Same thing with ChatGPT agent. I think we'll be much better at using it in three or six months.

Than we are today. Cool.

Makes sense. Dan, always great to chat. I do want to have you back on very soon to talk about LLM induced psychosis. I think it's important to talk about and let's talk about it, 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.

Awesome.

Well, thanks guys.

Talk soon.

Bye.

Cheers.

Up next, we have Chris Best from Substack. The best CEO Substack's ever had, arguably.

Undoubtedly.

It's been a conversation. Welcome to the stream, Chris. How are you doing? Congratulations. You got some news for us? You got some numbers?

Get it ready.

What's going on?

What do we got?

What's going on in your world?

Please tell me at least nine figures. Figures.

Doing good. We've raised a hundred million dollars. Series C. Congratulations. I was hoping you guys would ring that thing. Congratulations.

You guys are incredibly back. Yes, it's been a journey since. I believe you raised something. It was like 75 on 700 back in. What was it, 2021.

2021, that was. Those were different times. I don't know if you guys remember 2021. I do.

Oh, I do remember it fondly.

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'd 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? What are you thinking? Yeah, I like that. Yeah, we're, you know, partnering with Mood Raghani at Bond. I love that guy. Consummate bro joining the board. The big thing is, look, 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. Yeah. And we kind of want to 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? 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. 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, 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? 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 does a well run substack business look like? Like, 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. I don't know if you guys have had this, but recurring revenue hits different. It does. The sponsorship business is a great business. Yes. You know, I think that thing matters. Lots of people on Substack have sponsors. We love it. But that thing's like very cyclical. It's boom and bust. It's like, you know, whereas you have recurring subscribers, these diehards, that's sort of like. It funds sort of like you to be creative, it funds you to take risks. And so substacks the place where you sort of like your hardcore people are, 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 kind of like building more and more stuff. The center is not any one format. It's like the relationship with the subscribers and then Substack is just becoming. You know, you said you do top of Funnel on, on TikTok and LinkedIn and YouTube and everywhere else. Sure, keep doing that. That's great. 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. Interesting. That makes a ton of sense, Jordi.

I think the magic thing that you guys tapped into that I end up find myself, I find myself explaining to other people is there's this beautiful economy of people on Substack that just want to support people that are nerding out about a specific topic, just want to give them money. And so it's almost like there's this exchange of, yes, I want the content, but it's also enabling somebody to live a life that allows them to just obsess over one thing or just explore a series of topics or just be who they are and be entertainment through that. I mean, we've had 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 platform, legacy media company. So it's so awesome to see 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.

Never know. Yolo. Yolo. Start coaching from Mark.

Concentrated bets, man.

That's how it works. Concentrated Betsy.

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, kickstart 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. Excited about to put that money to work over the next like 12 to 18 months. But you probably think in like decades now at this point, right?

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. Listen, all that stuff you said, the stuff that I'm really excited about is like making the product fucking great. Yeah, right. I want it to feel like. My joke is Substack does everything for you except the hard part, right? You are the talent. You got to figure out how to write something that's worth reading, how to have a conversation that's worth listening to. 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 going to make us like the version of that magical sort of like, media studio, personal media empire in a box that we can build now is going to be so much more powerful. 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 in this ecosystem that winds up being this positive sum game. Right. Where everybody that's on substack benefits from this growing network. Yeah. I've certainly never subscribed to anyone on substack and been like, I didn't get my money's worth. 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. 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 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? There's a pretty big mix, right. Some people make almost everything free, and it's just basically like, if you want to comment or if you want to get the occasional thing, that's what you're paying for. It's going to be really low margin for Chris over here, you just give everything away for free. Free. He doesn't make any money. That's the beauty of your system. 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. Interesting, 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. Is this something I trust? Is this something I want to be culturally and aesthetically a part of? You know, you talked about people paying because they want to support people. The other way to say that is it gives you agency. 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, I'm causing this thing to exist. That I think is great is really powerful and a lot of different ways.

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 Coldplay. The Coldplay debacle last last night, which is trying to steal thunder from your fundraise announcement. But we're not. We're not letting it. And I appreciate it 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.

I want to spend my life. I don't want to be on a platform that just is designed to like, suck my time from me. Yeah. But I want to. I want to spend my time and attention better on smart things like TBPN and everything on Substack. Yeah. No. And coming soon, hopefully we will figure it out.

Yeah. We're about to bet. We're about to bet big on Substack.

Yeah.

We're very excited riding with you. So congratulations. It's. It's really tremendous to see how far the business has come since those glory days in 2021 and excited for the next five years.

Thanks, guys.

Cheers.

Congratulations. We'll talk to you soon, Chris. Cheers. Bye.

Awesome. Next.

One last guest, Deckhart AI.

That's right.

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. How you doing, Dean?

Welcome. Sorry for the chaos. We are so happy to chat with you.

Super nice to meet you both.

Super nice to meet you both.

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.

Okay. So you know the cart.

The Cart's a very young company. We're less than two years old.

We're a research lab, and our goal.

Is to build a consumer company. Okay.

Okay.

And what we just launched today is.

The only real time video model ever. I can. I can just show it to you.

Yeah, please.

Let's do it.

Share screen somehow here. Yes, but you are live. So whatever you share on that screen is baked into the Internet forever.

Amazing.

We don't even make sure that we don't leak anything. Just do the right tab, not the API keys.

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 just a character that you're playing. This is definitely not me. You realize that, right?

Yeah. In the real world, he's an anime, but. But he's using a Transformer model to appear like a human.

That's right.

He's in fact a Minecraft character. I have so many questions about this model. I want to jump into how you built it. We can also potentially have the team pull up the demo video on your website, Mirage Descartes AI and just kind of show folks what that looks like. Whatever would be helpful.

It is.

Currently I'm trying to get the Zoom.

Call to be able to share this, but if the team could do it.

From your side as well, that could work too. Yeah. Why don't we just have the team pull up the core website 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?

Real time. Let's just talk about. Let's talk about the use case.

Sure.

Obvious use case would be like real time video calls you're dropping into a Zoom call, for example. Example. And instead of yourself. There he is. There's. Here we go. Do you guys see me? Yeah, we see you looking stunning. Okay, there we go. Okay.

Okay.

Now we got it working.

There we go.

There we go.

What is the use case here?

Who are you? There you go. We're just cycling through.

We're just cycling through everything.

What do you guys like? What do you guys like? Anime. Not big into the anime world, but. What about legos? Anything. Anything there.

Legos.

Let's.

Let's put in legos. We can just type. Oh, you can just type it and it'll exactly do it.

Okay, let me make this full screen. You can just type in Lego and it'll just turn everything into lego. This is our house. See the real stream in the zoom?

Yep.

You can see. You know, this is the. The house office thing.

See all the LEGO characters walking around here.

This is insane.

Okay. And then you can decide that you're into Christmas and so everything becomes very Christmassy and your house is decorated. Oh, wow.

Yeah, Wow. I feel. What's the word for a moment like this? This actually feels like enter the metaverse.

Indeed.

I was hoping you wouldn't say that.

Because that become like you Know, became a cursed word. Yeah, dude. But, like, it's a good thing.

It's.

It happened at one point, right?

No, this is a big transition from the moment where Zuck was, you know, said. You know, did his, like, hello, from Horizons World.

There's Wii Graphics.

Was Wii Graphics. And this feels like being in a video game. What is that? Is that a wand? This. This is just. This is.

You can see the straw on the regular stream, right?

Yep, yep. And inside the wizards prompt, it becomes a wand. And if you flick it hard enough, sometimes it does magic spells.

Guys, which one? I'll ask the team.

The team's been playing with the prompts here all day.

Galactic War is the one you like. Cyberpunk Action. That's the lightsaber one. Okay. No, you had. You had one that you shoot gun.

Here.

So is this running locally on your computer?

So this.

No, this is running on the server. It's running on the server. So it's going from your webcam server back to us over.

So how quickly is. Is, like, Kai Sanat gonna be running this? Like, half the time that he's streaming. This is. This is insane. This is fun. It's pretty fun now what you do with it, right?

Yeah, yeah, yeah.

This is a bold demo, too, because the variation in the different prompts and how. How well it's working is absolutely insane.

Totally, totally. I have forgotten what you look like in the real world entirely. Here's a question. Would you guys run an entire show through this?

Maybe we can. We can try.

Not. We might put Tyler on the intern cam.

Yeah. 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. The way that you're doing, just cycling through these prompts, Tyler can be on.

Wizard cam for a little bit for one stream. That's pretty crazy.

This is insane.

Something. Something cool. Let me show you this. Something cool that we found out is that it's really fun watching YouTube through this. Okay.

Watching YouTube. Tell me, like, give me. Give me a YouTube show that you like. Something you like. I mean, just do that Mr. Beast video, whatever's pulled up right there. Okay.

So you can just look at this Mr.

Beast video. We can look at this ad and.

Look at the ad, and we can share the Mr.

Beast video.

I somehow have.

Unreal.

Can you guys hear the audio now? Yeah, we do, actually, A little bit. You hear the audio? I don't know if we should, but.

Okay.

Okay. And then it's being transformed now.

Yep.

This is the original Mr. Beast video. Yeah, even trippier.

You can. Here's like Mr.

Beast videos work really well with Cosmic Medieval Golden. We iterated through so many prompts, so we found the ones that worked really well. Yeah.

This is Mr.

Beast videos and the Cosmic Medieval golden world. Okay. Cosmic Medieval Golden. I mean they're already pretty stimulating. This is even more now wild, very wild stuff. Yeah, yeah. 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 think, let's say you join, decides somebody's joining a stand up tomorrow, can they just automatically put the entire team into whatever character they want? Let's see.

What stand up comedies do you like?

I was talking about an actual like engineering stand up. Oh, an engineering stand up.

Okay.

Hey, can definitely do that.

I'm more asking about you. I'm asking you, where do you think it winds up living? Living. Like, do you think. Here's what I think is cool about this. You know, I think it's the first time that we have a new kind of consumer interaction with video AI because.

So far, you know, video AI was just, okay, let's create AI slot, put it on existing platforms, Facebook, Instagram, TikTok, whatever. Here for the first time, you can actually do something that's slightly different. We're 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 experience here.

Yeah, yeah, yeah. It's like the original in the. What was it? Steve Jobs did that demo of the Mac where it like warped the image and there was like a. It's like a crazy historical photo in the original, like Mac OS launcher.

How expensive is this for you guys to run? If somebody just starts streaming this in real time, are they paying for it? Just eating it?

We're doing it efficiently enough. We had to write all the low.

Level assembly code for GPUs to get this to be both real time and super cheap for us. It's at a point that we can actually provide this for free. It can actually be monetized without subscriptions. There are ways it's cheap enough to.

Actually be able to build a platform.

On top of of this.

Interesting. Do you think? Yeah, I mean, do you think one of the use cases will just be folks who create video content running their video through this to kind of as like a previs for what they ultimately want to build.

That could be very interesting. Well, the other. The other thing, you can imagine it actually in YouTube. So like a creator, like Ms. Rachel, for example, popular kids creative creator, could basically say, like, do you want the LEGO version of this video? Do you want the pirate version where this lives?

Because I can go and put my phone in grayscale 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. 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. 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 will be interesting to see where this lands, whether it's on the consumer. I like watching lego version of YouTube. I like watching LEGO version of my. Of my conference calls. Or it lives on the. On the. On the producer of videos. I want to show up as Lego. And then that could be transformed as well.

Can you quickly do a Gigachad filter?

Oh, yeah. Do you have a Gigachad filter? Let's check that out. Let's see what Gigachad does. I will say that the model is really in the current version of the model. Is getting.

Changing the entire style.

Okay. Yeah, yeah, yeah. Not changing the entire world. It's not.

Oh, turn me into Trump.

Okay. You're pretty orange. Yeah, that's the way it goes. But it is doing something to the cheeks and the jaw, which is textbook Gigachad. There we go.

There we go.

Very funny.

There we go.

Yeah, this is wild. Maybe you need a prompt like.

So is this already fully open access?

Yeah, this is open.

We launched it literally 30 minutes before the podcast.

We're waiting for you guys. Congratulations. Thank you.

Yeah, this is the first time it's used on a video call.

Amazing.

Insane. Insane. Well, thank you so much for joining us. We will get access to it. We'll set it up on the intern cam tomorrow and.

Wait. You already have it set up. Okay, we're going to hop off with you and we are going to check it out with Tyler, get some feedback. Thanks so much for hopping by.

Congratulations to you and the whole team. Insane.

And is there anyone else in the waiting room or are we good?

I think we're good.

Let's. Can we go over to.

Take it over to Tyler?

The Intern cam and see if that works. I don't even know if that. If he's there. Oh, oh. Technical difficulties, of course. Anything else you want to cover in terms of news or.

Yeah, there's some new news.

Oh, wow.

That's Tyler there.

Wait, really? Whoa. You just did it.

Yeah, this is me, like 30 seconds ago.

Okay.

Wow.

Yeah, it looks better without the zoom compression. It's a pretty high fidelity model. Wow. Very cool. Yeah, so we were talking in the background. So you hear our talking 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. Pretty good. And these were preloaded prompts that you were just clicking through, Tyler?

Yeah, I was like, selecting.

You didn't generate any of your own prompts?

I didn't, but I think you might be able to.

Yeah. Yeah. That seemed pretty cool. Some of this seems fun. I imagine that people will be having fun on this on the Internet, very, very soon, very quickly. I always just wonder with this stuff, like, what the. What, like the novelty is like, 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.

Well, so. So here's the use case. Streamers.

Yeah.

Having some type of like, basically, like if you tip a certain amount or hit a certain button, it puts the streamer into.

That's cool. Yeah.

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 clean up the messy background. And so, yeah, you could imagine this being like, basically in the VFX pipeline for streamers. I think if most people showed up to a Fortune 500 Zoom call with this, it might not go over too well.

Well, they can always make everybody on their screen look a certain way and not make themselves look normal to everyone else. Right?

Yeah, yeah. If your boss is yelling at you and you put them in LEGO mode, it's probably going to hit a little bit differently. Might be a good shield. More tolerant. Yeah. Turn the volume down. The volume down.

LEGO mode.

LEGO mode.

Oh, sorry. LEGO boss.

Yeah.

Block man. You expect me to be a couple more headlines since we're here? Perplexity apparently just closed a new round. 18 billion 18. So perplexity has around 2% of queries according to Semianalysis right now. I use it regularly. We talked to Chris, who's on the show.

7 million DAUs, 30 million daily queries, 4.3 queries per user per day. A 2% share of users and a 2% share of queries solid. That's the perplexity numbers pretty good.

They got their new browser. They're going to be investing heavily. And then outside of that, lovable just raised 200 million at a $1.8 billion valuation led by Excel. Lots of heat on the timeline. Lots of big rounds getting done.

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. Instead can move on. Talk to you about the news. Also I want we want to send our best wishes to Tyler. 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. I'm so grateful recovering. Thank you for your prayers. All good.

So I hope he's going to send some prayers over to Tyler.

Yes. What else is in the timeline that would be worth to close on?

I have a good closing post. The lads over at Re Industrialize are having a lot of fun. If you can pull this up in the Bangers tab, you can see quite a number of former TVPN guests all in the back of a pickup truck.

Fantastic.

If you 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. All the boys. We got Augustus, Packy, Steinman, everybody. All in one place. Love to see it. Anyways, thank you for tuning in today. Super fun show and I can't wait for tomorrow. John.

Can't wait for tomorrow. Leave us five stars on Apple, podcasts and Spotify and we will see you tomorrow. Have a good day.

We love you. Bye bye.