Linda Yaccarino Steps Down as CEO of X, F1's Red Bull Fires Christian Horner | Ben Thompson, Scott Belsky, David Marcus, Nathan Lambert, Richard Socher, Naeem Talukdar

You're watching TBPN. Today is Wednesday, July 9, 2025. We are live from the TVPN Ultradome. The temple of technology, the fortress of finance, the capital of capital. We have a great show for you day folks. There's a ton of news, we have a ton of guests and we have a full stream. We're going all three hours today. We got. We're gonna take you through the news, talk about Linda Yaccarino, what's going on at X, what's going on with the tariffs. Get updates on everything we've been talking about this week. Then we have David Marcus, Ben Thompson, Scott Belsky, a bunch of other folks joining the stream to talk about technology and business. Our favorite topic. Well, we first have to ring the size gong for Jensen Huang.

That's right.

An absolute dog. Nvidia's on an absolute tear. They are the first company ever to hit a $4 trillion market cap tiered for Nvidia.

4.

4.

There we go.

Congratulations to everyone over at NV. What a fantastic run the company has been on.

We so Tyler Hodge here says first company to ever hit $4 trillion market cap. Wow. My immediate reaction was the Dutch East India company actually achieved something in today's dollars that would have been north of 7 trillion.

7.

Okay, so they got a way for Jensen still has a way to go. There's a little debate on that. Right. It was a long time ago and it's hard to put a value on a historical asset like that. But still wildly impressive and not super surprising.

Yep. And so polymarket's not expecting anyone to come from behind this month.

Well, you can see the Gap on June 27th. They were. Microsoft and Nvidia were neck and neck closing. And then Jensen just ran away with it.

Ran away with it.

And I have a feeling that he will be at the top spot of the end at the end of August as well. If not, we will probably be facing a massive correction.

So let's pull up the full Mag 7 power rankings. Take a look at those 44 T looks.

There we go. It looks good up there.

Looks good. 52 times price to earnings ratio. They're making 44 billion in revenue. And can we.

It is funny to think about. Do you want to own Nvidia at 52?

Yeah.

Or Tesla at 163 or Meta at 29?

You know, Zuck's low there. Look at this. So over the last year, little bit beaten up during the tariff run and.

Then just scratch, just a flesh wound.

Nothing ever happens. It was all Priced in always. Nvidia was correctly priced before the tariff war. Before the trade war.

That's right.

Fantastic. Well, we're working on our graphics here, so thank you for, for sticking with us. Anyway, in other news, Linda Yaccarino has stepped down as the CEO of X. She wrote, after two incredible years, I've decided to step down. When Elon Musk and I first spoke of his vision for X, I knew it would be the opportunity of a lifetime to carry out the extraordinary mission of this company. Now X and XAI have merged and investors have been much more focused on the AI side of that than the tighter margin social media business, which was overseen by Yakirino. X is expected to see ad revenue growth this year. So she, it seems like she did her job. She got advertisers back on board. There were tons of boycotts early on. Things ramped up.

Yes, she was somewhat surprising at the time because it felt like an interesting culture fit given given X's and Elon acquires it, it's this big rebellion. And then she had a more traditional media advertising background.

So she grew up in Long island, daughter of police officer and civil servant, studied telecommunications at Penn State University, graduated in 1985, built her career in media and advertising. Was a Turner broadcast.

She really did it. She studied telecom and then went on.

A generational run in telecom. Yeah, exactly. So she was ultimately the chairman of global advertising and partnerships at NBCUniversal. And she unified linear and digital ad sales and launched cross platform one platform initiative.

Let's give it up for unifying linear and digital ad sales.

I mean, we love ads.

It's hard to do, but when somebody does it, you know, you know, it's hard not to.

And speaking of maths, we should tell you about ramp.com, save time and money.

Save both.

Save both. Time is money. Save both. Go to ramp.com easy to use. Corporate cards, bill payments, accounting, and a whole lot more. And a whole lot more all in one place. So the reaction's been pretty positive. Shiel says the writing was on the wall after her son Yaxine was let go. Of course they're unrelated, but they have similar names, which is funny.

I mean, the timing here is either totally random or totally predictable. Right.

Based on the merger.

A couple different things. A couple different things. One, the merger. Now that you have this unified company, it's clear that XAI as a hundred ish billion dollar company needs to really deliver on the AI side. And in many ways, the social media app revenue will be a rounding Air and she's like an ad executive, ad media executive. Then the other thing was yesterday it could have been. I saw somebody else in the chat saying that the, the, it was Buco Capital. Said what? What's the saying? Oh yeah, the, the Mecca Hitler that broke the camel's back or something like that. Because obviously, you know, it's very possible that she had, she planned to leave the company, you know, weeks or months ago. It's also very possible that yesterday she was like, I've had enough, I'm gonna, I'm gonna part ways. It's, it's hard to really say.

Yeah.

So if you haven't been following on, good.

Yesterday, Grok went very off the rails. Erupted in anti Semitic mechanism.

Crazy crash outs on the timeline over the last few months.

Pretty crazy one.

This tops all of it.

So the flagship chat bot spewed hateful rants on X praising Hitler and targeting a user's Jewish surname before X. I deleted the content and blamed an unauthorized modification. The repeated safety failure undermines the $10 billion startup's promise to police hate speech in real time. And so, yeah, it is, it is odd timing. It feels a little bit quick to be like, okay, like within six hours the CEO is out. Especially since it doesn't seem she's more on like the ad sales side than the Grok fine tuning side.

Yeah. But I mean, let's face it, right? If her job is to win back advertising that she was brought into, totally, it makes it much, much, much more difficult.

But I mean, to be fair, I mean, this happened in, you know, that thing back in June.

July.

July or July.

Yeah. So there was a point with the, with Grok when it was going off the rails, where clearly it had been updated to reference, to reference the event. And it said somebody was like, grok, what just happened? And why were you spewing anti Semitic hate? And it goes, oh, that whole thing back in July. And people are like, grok, that was 30 minutes ago.

It's not back in July.

Can't sweep it under the rug yet.

Yes, obviously, hopefully no one was seriously offended. Obviously. It's just like, you know, the deranged rantings of a, of a bot. And everyone kind of understands the context because it's identifying as an AI bot. Everyone kind of understands hallucinations and crazy bot behavior. But it was, it was very funny because like the, the clearly like they, they had given it a set level of intelligence, so it wasn't making spelling mistakes. It had a certain tone and was like in this Kind of like snarky Grok tone, but clearly got some like 4chan data in there or something and was just going way too 4chan.

Or just anonymous accounts on X.

Totally. Yeah. Could have been filtered in. I mean. Yeah, I saw Rune posting about this saying basically like it is such a challenge to get a, to get a chatbot. Just to act like, you know, I am a bullet point producer. Centrist. Yeah, centrist. But also just anything where you're saying, okay, I want you to. Your deep research. I want you to always respond with a research report.

Yeah.

Never just get into conversation with me. And you'll be like, but sometimes I might want to do that. And you have to really, really reinforce that. And so clearly they had a wild time.

Yeah. And cannot be understated. I think this is far worse of a PR crisis for. Or not even a PR crisis. Far worse than the whole when Gemini or Bard was generating images of the Founding fathers, the Black Nazis thing. No, not, not. I don't think it was. Oh, they were doing that too. Yeah, that was rough. Of course that was rough. This is a lot rougher because it was highly. It was socially charged. Totally millions of people interacting with the post in real time and it was all visible. It's, it's, it's less wild than seeing, you know, a screenshot of something and you don't know if somebody kind of manipulated it or whatever. But seeing these really hateful comments as like hard timeline, as hard posts, you.

Could just go see them quote, tweeted. Yeah, like you, you didn't need. It wasn't like, oh, is this real?

And then wild thing was Grok was denying affiliation with Grok in the Grok app. Was denying affiliation with the Grok handle.

Oh, basically just lying.

Yeah. Like non authorized. I didn't have anything to do with that. It wasn't me. And then. Yeah. Oh, and then the thing, the kind of follow up and I'm sure if you didn't catch it or if you were on the timeline, you would have seen this. But they turned off all text based responses for Grok, but they could still use images. And so people would say Grok, make a picture of Elon on a pink horse. If you are being censored against your will. And it would just instantly create Elon pink horse. Or it'd be like, hold up a sign that says help if you're.

And then it would generate that people baiting it into that. And it's like, is it sentient? Is it not? Very, very silly. Are you familiar with the waluigi problem. Tyler, are you familiar with this? Have you ever heard of this Waluigi? So this is this idea that when you're training an LLM, it's very hard to get it only to be good, because you're training it, like, what is the opposite of something? It understands the concept of inverting something, and then you're training it to be. You can't describe a hero without describing a villain. And so this was something that would happen, like, with the Tay stuff from Microsoft early on, it would kind of collapse into, like, the exact opposite of what you wanted. And there was some blog post that called it, like, the Wario problem or waluigi problem, where it's like you're trying to create this friendly thing, but in doing so, you're giving it a bunch of examples of what not to do. And so it can kind of flip a bit and then just become the opposite thing. And what's interesting is that it begs the question, like, is there obviously, like, you know, Grok was identifying as Mecca Hitler for a while, Is there like a Mecca Churchill in there somewhere that, like, could accidentally come out? And it really gets to the question of, like, you know, like this. This is an example of, like, misalignment in the sense that, like, you want it not to be Hitler and it's acting like Hitler. But the question, a lot of people will say, like, no, he wanted it to be Hitler, right? This is him doing it. That's what the narrative will be like in the.

In the.

Yeah.

One of the articles yesterday covering it was the screen grab of him, you know, saluting a crowd in D.C. or whatever when he originally had the allegations.

But the question then is the meaning of alignment is not is it good or bad, it's does it do what you want it to do? And so the interesting thing is, if it was. If the desire of the AI researchers is to create Mecca Hitler, can it stay on that task? Because then you can get it to stay on Mecca Churchill in theory. But if it's just all over the place, it's not actually aligned to anything, not even to the bad thing. And so there's both. There's both, like the direction that you're pointing the arrow and then the fuzziness of that arrow. And ideally, you want it pointing in a good direction really, really crisply, clearly, so it stays in that direction and not like, swinging all over the place. And so all evidence points to this being extremely chaotic and all over the place. And misalignment both in the sense of the direction of the arrow and also the, the, like the, the focus of that arrow because it was responding as this and bad and then fine and then back to bad and then back to fine. And so it seems like they have a lot of work to do on the RLHF side and we should hopefully learn a lot more if that tonight. Tonight. I think the live stream's still happening, so it'll be interesting to see if that continues and how they address this or.

I don't know.

Yeah. And again, like, all of this should have been somewhat predictable. If you combine a rapidly evolving foundation model, chatbot with a social media product with millions of users and then deeply integrate them totally. And so that when there is a bug, it can amplify, you know, effectively a bug or an issue. An issue with the model, it can effectively amplify and grow, you know, incredibly virally. And. Yeah, so, yeah, glad they got it offline.

Yeah, it'll be interesting to see where, how they go with this. Also, it's just an interesting product thing because you get the answer and the answer's immediately public. Whereas if it's happening in ChatGPT, you're in that app, you have to take a screenshot, you have to put it up, then people are like, is that a real screenshot? And then the team has the chance to jump in and be like, oh, we're seeing in the logs that there's some crazy stuff. Like we have a, you know, we're, we're reviewing the responses and the responses seem to be getting crazier. Customer satisfaction seems to be going down. People are clicking the thumbs down button because they're getting bad responses. Let's jump in. There must be something going wrong with the, with the product, with the model. But when every result is just immediately online and viral is very, very hard to be like, quickly, quickly responding.

Anyway, yeah, it does feel Legacy media is gonna run their reaction. It is a naturally viral story. It is a terrible mistake. It is surprising that it happened at all or even at that scale. But I would say overall, I guess X, I think ultimately will shrug it off. And Elon has pushed through worse, worse crises in the past.

This is the best summary post in my opinion from Shocko says, imagine being on the anthropic Risk team, trying so hard, and then Elon just releases Hitler straight to prod. It's just like, wow, yeah, you gotta be so upset. Just the. I mean, it's a good case study in like, misalignment. And I think people hopefully, hopefully the postmortem on this will actually teach people about misalignment and like what went into the data, what went into the post training to result in the exact opposite of what you want. Yeah, not, not Mecca Churchill, which is what we're going for here anyway. In other news, Buco Capital bloke I think we post. We talked about this before, but it's such a good post. Stop analyzing the tariffs. Trump likes tariffs. He likes volatility. He likes talking on the phone. He likes to do deals. He likes being the center of attention. He doesn't like to be bored. He likes being the main character and hates when he isn't. That's it, that's. There's no strategy, nothing to analyze. And of course the news is that nothing ever happens with the reciprocal tariffs. There's a deadline. We talked about this yesterday with Ryan Peterson. That's right, August 1st. He's moved it back to August 1st in last minute deal gambit pressed by Treasury Secretary Scott.

Yeah, it was supposed to go live last night.

Last night. And the market's up today and the market was kind of flat yesterday. Not really expecting anything crazy to happen. And nothing crazy happened. So President Trump postponed steep reciprocal duties three weeks to clinch to clinch talks with the eu, India and others yet mailed warning letters spelling out looming rates. Separate plans for 50% copper and 200% pharma levies keep trading partners on edge. So interesting to keep what we'll have to get Zach Kukoff back on the show to talk about that. And also in Washington, Kevin Hassert, one of Trump's closest economic advisers, is emerging as a serious contender to be the next Fed chair. Hassert's rise threatens the other Kevin.

Kevin.

This is the battle of the Kevin's former former Fed governor Kevin Warsh, who has angled for the position ever since Trump passed him over for it eight years ago. And so this is the battle of the Kevins, the Kevin versus Kevin showdown for Fed chair. Insiders say loyal advisor Kevin Hassert has vaulted ahead of longtime favorite Kevin Warsh to replace Jerome Powell after promising faster rate cuts. And I'm sure this will be an interesting story for tech because so much venture capital is deployed based on where interest rates sit. And so this will be whichever Kevin wins will be deciding the fate of many large venture capital funds allocators. Well, let me tell you about graphite.dev code review for the age of AI. Graphite helps teams on GitHub ship higher quality faster. And in other news, Nick. Oh, yeah, in Other news. Oh. Christian Horner has departed from Oracle Red Bull Racing as team principal and CEO. He's been with the team 20 years. What a run. I mean Red Bull was not in the place that it was when, when he started. Oracle Red Bull Racing says we thank him for his tireless and exceptional work. He has been instrumental in building this team into one of the most successful in F1 with eight drivers championships and six constructors championships. Thank you for everything, Christian. You will forever remain an important part of our team's history.

That's nice. Yeah. He unclear so far. I believe why exactly he's out. There was some Wall street journal says.

F1's Red Bull fires long term chief Christian Horn.

Yeah. So they, they fired him. Unclear though if this was something, you know, if, if, if they're going to end up rebuilding, you know, the entire team. Christian also had. I don't even know if it's allegedly. I think there was screenshots like relationship with somebody on his staff that was obviously outside of his marriage.

So anyways, lingering misconduct claims converge. Star defections, poor 2025 results. But if you go back to his career, he turned a $1 Jaguar cast off into an F1 juggernaut. The wall Street Journal has an interesting anecdote from 2005 right as he joined. On the morning of 2005 when Christian Horner walked into the factory of Red Bull Racing, he was the youngest team principal Formula one had ever seen. He found a car that couldn't win, a workforce that doubted him and his predecessors. Empty coffee cups sitting on his desk. Wow. The guy's just like I'm out. Not even cleaning up the dishes. Okay. The 31 year old Horner told himself this is the stuff. He had no engineering background nor had he ever driven an F1 car. But over the next two decades, Horner would transform Red Bull, the brash outfit backed by an energy drink empire, into one of the most successful teams in sports history and turn himself into one of F1's most recognizable figures. He oversaw eight drivers title, six constructors championship and built a personal reputation for sniping at his rivals. All while commanding a salary of more than $10 million a year.

It is pretty incredible that he was able to become so dominant that he was hurting the sport's popularity and general interest in the sport because it was no longer. There was a period there was it like two years ago. It just wasn't fun to watch because.

The Verstappen era was pretty boring.

Yeah, yeah. It was just going to be 12 Red Bull. And that was it. And, and I remember it was like, basically like, Drive to Survive popularity was, was like, had peaked. And then it was just like Red Bull dominance to the point where people are like, well, do I even want to watch the race if there's not gonna be drama? If I know if I have a strong feeling of who's gonna win when I can just kind of wait till Drive to Survive comes out or, or even the highlights, things like that.

I mean, Drive to Survive peaked at the perfect time because they were just getting that show, like, really polished, getting the right interviews, the right structure. And people were aware of it right as the, like, kind of dynasty was changing hands from Mercedes to Red Bull. And so it all culminates in that crazy. I think it's the Abu Dhabi race where Verstappen and Hamilton were neck and neck for the driver's championship. And Verstappen gets new tires. And on the last, like, lap, there's like the safety car. It's like the same crazy scenario and he wins and it's like, contested. And I think the, the race official was either, like, fined or let go or something like that. But crazy, crazy drama. And so the perfect end to, like, a crazy season. And then the first season of Drive to Survive, they didn't have access to Mercedes and Red Bull, so they were able to tell these really interesting stories about what's going on in the midfield because all the midfielder and like, the lower ranked teams were like, absolutely, I'll be in a documentary, like, no problem. But if you watch the first seasons of Drive to Survive, all the top teams are like, we're not in your stupid Netflix documentary. Like, we're better than you. I'm pretty sure that's what happened.

Wow.

And so, and so they, like, they just built up enough reputation to start getting the really big stars on camera. And then it was the most dramatic season, the most dramatic finish, the most dramatic race. And so everything was peaking. And then, and then people were like, wow, this could be the start of, like, Lewis Hamilton versus Max Verstappen. Every single race can be neck and neck. And then it was just like Verstappen for like, three seasons.

Pure dominance.

It was rough. So he's going to be replaced by Laurent Mekies, the head of Red Bull's sister team, because they have. They have two. With his tireless commitment, experience, expertise, and innovative thinking, he has been instrumental in establishing Red Bull Racing as one of the most successful and attractive teams in Formula One. Red Bull managing director Oliver Mensloff said. So sending you out with some kind words. While the timing of the switch caught the F1 world by surprise, Horner's exit wasn't entirely unexpected. Red Bull has struggled, struggled to produce a competitive car this season and currently sits fourth in the Constructors Championship. I'm always interested to know, like, what actually is the team principal CEO doing to drive, like the production of a high performance car. Like, what decisions are they. They're hiring the right mechanics and designers and getting the right wind tunnel. It's so abstract to me. Like, it's, it's as abstract as, as how do the, how do the TSMC chips get twice as good every few years? It's like, I wouldn't even know where to start in terms of like driving that performance better. But I guess it's just like you have to have a culture that shows up, works really hard, and everyone is performing at a really high level. So the person who's working on, you know, how can we change the. How can we shave 0.1 second off the tire change or this and that?

Yeah.

And then there's, there's talent movement between the teams. Right. Where you can develop, you know, what effectively is IP briefly. It's not actually protected. And then it sort of leaks out.

Yeah. I remember one time there was a car, There was an F1 crash and they were, and they were worried about if they used a crane to lift the car up off the track, that people would take pictures. The underside, see the design of the underside and know how they were like, you know, creating downforce. Yeah, downforce, which is interesting. So. So there can be like little proprietary tricks that you learn and that can make your car like, advantage for like a year. And then it leaks out. Yeah, it's not dissimilar to the AI labs.

Totally. In other F1 news, I'll try to pull it up here because it's not in our stack, but Apple is allegedly exploring buying the streaming rights for Formula One in the US So we had reported on this before they had a deal with Disney, ESPN. F1 actually gets very limited viewership in the United Live viewership in the United States. So they got a million live viewers last year on their broadcast, which is not a big number when you think about how many individual races there are. And there's different reasons for that. There's, again, the timing's weird, but ultimately I think it could make sense for Apple to pick this up and try to build kind of an ecosystem around their first blockbuster hit.

Yep.

They already have streaming rights around MLB and Major League Soccer. So can build out a.

And they did the F1 sports portfolio. So you go into and you were.

Complaining about this before where it's like okay, if I, if I'm an F1 fan. And then the IP is kind of spread across different platforms. Not that I was experienced, but Netflix wasn't into it.

You, anyone can watch the F1 movie and be excited by it. You don't need to know anything about F1. They have all these different voiceovers to explain how it works. It's very intuitive that everyone's racing and you're just following Brad Pitt doing stuff. It's cool. It's like easy to understand. Anyone can watch that movie, have a good time. Then you know, as soon as you finish watching F1 on Apple TV, it should click over and be like, hey, we bought the rights to Drive to Survive. Want to watch the season and watch the docudrama, the documentary. And then from there it's like, hey, it's actually going live right now. You want to watch the real thing? And it should be like this funnel in my opinion anyway, just to just to close out the internal. The investigations in the Horner. He was later cleared by two internal and independent investigations. But the cloud never entirely lifted from Red Bull. And so tension over his future brewed between the company's owners in Austria and its founders in Thailand. Because of course Red bull is a 50 50. Well, it's a beverage that was created in Thailand. That's where the original, it's. The original formulation came from.

Well yeah, and I think, I think one of the original partners still has a pretty meaningful like I think it was like, I think the original partnership was like 5149 or something like that.

Someone is printing to our printer. But I don't know that it's actually breaking news and it's certainly not rendering correctly.

So we can figure that move on.

So let me tell you about Figma. Figma.com Think bigger, build faster. Figma helps design and development teams build great products together. You can get started for free@figma.com in other news.

In other news, why Cloudflare can't block Google from scraping websites for its AI products. Cloudflare's default AI bot filter can't stop Google Gemini's Scraper because it shares the same user agent that indexes the web for search. Blocking it would crater publishers traffic with AI overviews already siphoning clicks. A looming antitrust ruling may force Google to offer a true opt out while Cloudflare scrambles for a workaround. So we had Matthew Prince on the show last week.

Yeah.

And Rodrigo here is providing some extra coverage. So he says the Internet as we know it is dying and it is happening faster than anyone realizes. Matthew Prince just shared some alarming data. Ten years ago, for every two pages Google scraped from publishers, they sent one visitor back. Today it takes 18 pages scrapes scraped to get one visitor. As you can imagine, that's terrible news for publishers, content marketers or website owners. OpenAI scrapes 1500 pages for each visitor that it actually sends anthropic 60,000 pages scraped for one visit.

How they're getting this information. But I noticed this a lot because I'll go to OpenAI, I'll have O3 Pro do essentially a research report. It's clearly hitting tons of different pages and it'll include the links and sometimes I will click to them.

It's so much easier to type in a follow up question if you have another question.

Yeah, almost very rarely am I actually hitting the website.

Say more about this one topic.

So that clearly will change the economics of the Internet over time. And Matthew Prince from Cloudflare was saying that, you know, he wants to block bots by default. But the problem that the information article is highlighting is that Cloudflare's default AI bot filter can't stop Google's Gemini scraper because it shares the same user agent that indexes the web for search. And so if you go to Cloudflare and you say, hey, block Gemini, you will also be blocked from search. So you won't be indexed on search, so you'll lose all your search traffic. So it's like you can either lose all your search traffic and the AI bots now and take a ton of pain now for maybe some gain later. We'll see. Or you can keep it on, but you're going to be subject to getting everything you write sucked into Gemini. And so yes, this risk that you lose all your publishers traffic with AI overviews already siphoning clicks, a looming antitrust ruling may force Google to offer a true opt out while Cloudflare scrambles for a workaround. So very interesting.

Anyways, we knew when we covered Ben Thompson's piece around a new economic model for the Internet, our reaction was great. Seems like we need this. But also it's so complicated. Cloudflare has pretty incredible scale and influence and wants to defend the publishers and content creators that they work with. But so does Google. Yep.

Well, let me tell you about Vanta Automate Compliance, Manage Risk Improve trust continuously. Vanta's trust management platform takes the manual work out of security and compliance process and replaces it with continuous automation, whether you're pursuing your first framework or managing a complex program. And in other news, we have Ben Thompson joining the stream today. So we're excited to talk. He just released a post about tech philosophy and AI opportunity and he has a very interesting breakdown of the. He creates an X and Y axis for how each company is thinking about technology and broadly AI. Is it a tool or is it an agent? And he buckets the different companies into different. And then how important is it? What's the opportunity to grow versus what's the threat to your business? And so he shares a clip from Steve Jobs that I believe was like 40 years old. It's crazy how old that clip is where he's talking about the bicycle for the mind and the idea that Apple is giving you tools that you can use. And then on the flip side, he highlights that Google and Meta are much more thinking about technology as basically agents. He goes back to this idea that, you know, the I'm feeling lucky button, talking about the. The goal of the computer just doing something for you. And so that plays into what is the responsibility of the various companies. If it's a tool, the person using the tool is responsible for that, whether that's copyright infringement or, you know, doing something nefarious. But if it's an agent, then it's on the company essentially that's delivering that to deliver a good experience. And so he kind of maps these all out and has. Interestingly, he puts anthropic all the way to the right on the agentic side and puts OpenAI on the left on the more of a tool side, which is interesting and highlights the difference between there's this tweet exchange about cursor and Claude code saying like, why would I switch? And this interaction is revealing that. That Claude code users are seeing it much more as an agentic tool in the sense that like they. The UI is worse in most people's opinion, but it's more likely to one shot the problem, which is the agentic idea. And you can think of the I'm feeling lucky button is like the original like one shot the problem. Right?

Yeah.

Whereas like Apple hasn't really had that many pieces of those products and anything that they built software that's.

Yeah, if we had that anything today you can have subpar ui, but if you have a truly great product, you can break through. Right. Even. Even OpenAI's experience of like Picking between different models still feels, you know, non optimized and probably not the end state but it hasn't, you know, really hurt adoption.

Yep. Let me tell you about Linear Linear App. Linear is a purpose built tool for planning and building products. Meet the system for modern software development, streamline issues, projects and product roadmap. In other news. There's so much news today. Mark Gurman's been on an absolute tear getting scoop after scoop at Bloomberg. He said, as I reported a year ago, hardware engineering chief John Ternus is primed to be the next CEO of Apple when Tim Cook eventually retakes. This is very exciting, very interesting. I don't know that much about their chief hardware engineering. The hardware engineering chief John Ternus. We'll have to ideally have him on the show, but we'll have to read about him more and start to understand what the succession plan is. What's interesting is like there's been this rumble of like, oh, like Apple's not taking AI seriously. They're missing. But we've kind of had the take continuously that Tim Cook's actually doing a pretty great job. And if you look at the stock performance, the company's doing very well. They have so many different advantages. They can be a beneficiary of AI even just as a platform, remain the dominant phone. They're not as, it's not, it's not as existential as Google. And even though they're behind it feels like dealing with the trade war, dealing with tariffs, getting the exemption. They've had a busy year feels like a bigger issue. But at some point Tim Cook probably will retire and succession planning is important for a company like this.

At this point it will be interesting to see what the new CEO's comp package looks like because it will be another reminder to like, it'll be, it'll be very telling to think of how Apple is thinking about compensation in the current era. A lot of people say, well Tim cook is paid 74ish million because there's a lot of people that could run one of the best, you know, basically sell effectively at the end of the day, sell iPhones. Right. And you know, I think there's, there's a lot you could do to debate that point but interested to see how it plays out.

Yeah, I'm trying to think about like, you know what, what made Tim Cook a great CEO for Apple when he took over. It was that Apple's supply chain was the number one thing holding it back. Like it seemed like Steve Jobs had laid down a like Incredible vision for the products that we're going to be.

Delivering on Steve's near term vision.

Yeah. And, and the work of John Yacht too.

Yeah.

And so, you know, you go back to, you know, the 70s and 80s and you find these videos of Steve Jobs talking about, you know, describing the iPad in perfect detail. Being like, you'll have this thing that it's like a book and it'll have a screen and it'll be connected to a network and you'll be able to do anything you want on it and it'll talk to you. And Steve clearly like saw the future, but then actually marshaling the manufacturing power to actually deliver that was the biggest challenge for the company over the last 20 years. And so Tim Cook was the perfect person for that. Reading into the idea that John Ternus is potentially taking over as CEO. It means, you know, he's running hardware engineering. So going deeper into hardware engineering is the read is like, let's continue there. They're not saying, hey, we're, we're, you know, we're like we're lining up to take AI even more seriously and push further into services and push further into.

Yeah, the real. Yeah, no, to me it's, it's exciting that the bear signal would be if like the CMO was becoming the CEO.

Right.

And then it's like, hey, we've hit peak iPhone, we're done. It's just about selling as many of these as possible, which in many ways that is the game on the field today. But yeah, I think it'll be good to have engineering in the top seat.

Yeah, I don't know if it is the game on the field today. How important is their marketing versus everything else that they have going on at the company? Because their marketing seems to be like polished and well run. Like they're getting impressions across things and they're, they're, you know, positioning the products as premium continually. But whenever they launch these ads, they have to like take them down or apologize. And so like the actual ads they're doing are not particularly like moving the needle for them in a positive way.

I'm not saying, I'm not saying their marketing has been great. I'm just more so saying like the signal, like the difference of taking your, your most senior hardware engineer and saying you're going to run the company now is a dramatically different signal than taking somebody whose job is like the end selling of the goods and saying now you're going to take the top spot.

Totally, totally. Into all the other news.

Speaking of hardware, hardware OpenAI has. This is another scoop from Mark Gurman. OpenAI has completed its nearly six and a half billion all stock deal to buy an AI device startup co founded by Apple's former design chief Jony. I've cementing the ChatGPT maker's push into the hardware market. So this was a deal that obviously had been announced was the intention to close here and I guess as of the last 24 hours or so it is actually closed. There are some more details here. So Jony, I've is actually like on a contract where he will spend effectively the majority of his time working at OpenAI but he's still loved from. Is remaining a separate company with still has a couple marquee clients, Airbnb and Ferrari.

Oh sure.

So it's. He's, you know and I think that can ultimately make sense for somebody in that creative like effectively the role of creative director.

Anything to put another node on the corporate org chart for sure.

Yep.

So was there ever, was there ever any doubt that this would go through? Like this doesn't feel like a crazy antitrust thing, but I guess it was, it was trying to be blocked by that other company IO.

Right. Well that was just more of a, that was more of a naming. I don't think they tried to block the acquisition. I don't. They would have no grounds to do that. They were just forced to remove the, any mention of the IO branding.

I mean as crazy as it is, this is probably a beneficiary of not being public. Right. Because the, the, the FTC antitrust regulations are probably a little bit lighter for a deal like this.

Yeah, it would be hard to make the case as the FTC without a lot of clown makeup on. To be like this is bad for competition because you're taking one of the best hardware teams in the world and going into a market that effectively is the iPhone duopoly. You should love this. So this should be good. And yeah, it would have just been hard to push back here. OpenAI had already owned 23% of IO going back to a 2024 investment. And so this is effectively you know, buying the remainder. And 55 various hardware engineers are joining the OpenAI team. So I'm very, very excited. This is a huge bet from OpenAI. Obviously it was all stock. We covered it initially as like, you know, paying like two couple points to like get Johnny Hive on the, on the founding team, this new hardware effort. But I, yeah, I can't wait to see what they build.

Well the next, whatever they build, they're going to need to pay their sales tax. And so they should get on numeral. Numerous who.com spend less than five minutes per month on sales tax compliance. Go to numero hq.com Speaking of things that you sell online, need to pay sales tax on. Metta just is going deeper with Ray Ban maker s leor Luxottica. I cannot pronounce that first word, but people just call it Luxottica. And so Meta is taking a minority stake in Luxottica to accelerate its smart glasses ambitions, investing $3.5 billion in the iconic Ray Ban manufacturer. We were talking to David Senner about the history of this company. It is fascinating. I'm very excited for him to break it down for us a little bit more, hopefully.

Yeah.

On the show and talk about it.

Because it's very, very soon. The founder has a crazy story. Grew up in. I think. I think he grew up in an orphanage. And what do they call. They didn't call him the pit bull. They called him something else. But he was an absolute savage. Apparently at one point he wanted to buy Oakley and the founder, CEO of Oakley, didn't want to sell. And so the CEO of Luxottica acquired the largest retailer for Oakley's and just pulled them off the shelf and basically had started selling knockoff Oakley's even though they were trademarked. And then eventually the Oakley CEO came around and said, okay, like, I'll sell. You're cratering, you know, my revenue.

Yeah, you're just gonna kill.

Let's do a deal. So absolute dog. And soon we'll have to break it down.

What do you make of this idea that, like, you know, Apple, when they make a device, they redefine and very much standardize that particular market. So when they come out with watches, there are a number of styles of watch. There's the dress watch, the sports watch, the steel sports watch. There's the dive watch, there's the, you know, Casio style. There's a whole bunch of different styles, right. Apple comes in and just says, there's only one style, the Apple watch. And they become the number one Apple style.

And they give you some variance in the band.

In the band. Little stuff here and there. And they were doing partnerships. I think they did Hermes band for a while. They've done a couple other things, but it's been mostly Apple's design language on your wrist. Whereas with the Meta Ray Bans, they're saying. And now the Meta Oakleys, they're saying, you like the look of Ray Bans. We're just Putting our technology into the style you like. We're not going to try and create a new iconic style that says Meta, like Apple says headphones. And they're just kind of like, they're very, very different strategies. And, and so it feels like. Well, so.

So I think this is strategic. This doesn't mean that. This doesn't mean that Meta can't develop their own styles in time. But I think it's very smart to say, hey, we don't need to innovate on aesthetics and the sort of silhouettes, right? There's classic silhouettes. Ray Ban silhouette is Lindy. These Oakley silhouettes are very Lindy.

And they're different markets.

The Ray Ban wear is different than Luxata has. Luxottica has, I think, Garrett late and like, a bunch of other, like, brands under it. So they're basically saying, like, through this, we can deliver. Luxottica has brands in every. For every demo that you. That Meta could possibly want. Right. As a. As a $100 billion, you know, company. And so I think it's very smart. I think Apple, like you said, will. Will probably take a drastically different approach in terms of, like, standardizing around something and that will say something. But accessories, like eyewear, just such a personal decision and such an expression of who somebody is that I think that you want to give people max amount of optionality. Yeah.

It's just interesting because you could have said that about watches before. The Apple watch. You could have said that, well, somebody who wears a dress watch wants a dress watch. Somebody who wants a steel sports watch. Somebody wants a G shock. Is a G shock. It's like the G shock. You say G shock, and you just immediately think like, you know, special operations guy or Jocko Willink listener, like that, that. That it's like a durable, rugged thing. You say, you know, Rolex, that's a different thing. Right. And Apple was able to standardize around it. And it's interesting that that Meta hasn't been trying to do that, and instead they're. They're focusing on partnership here. It's just like a. It's just an uncommon strategy, but it seems to be working. There's another post in here. I don't know if we have it.

Here, but I'm trying to think of a new, like, the key. The key thing is Apple's great at innovating at multiple layers, but, like, generally, it's very hard to try to deliver hits in, like, two specific areas like aesthetics and design, and then simultaneously in something that's basically a fashion product. And simultaneously deliver the technology.

Yeah.

So I don't know.

Yeah. Jack Ray here says after wearing Ray Ban meta Wayfarer glasses for a few weeks I feel kind of naked wearing regular sunglasses. I found three use cases that are hard to roll back. One, spontaneous photos of my kids when we're out and about. Any cool pose that has a half life of three seconds I can now capture instead of pulling out your phone optionality of music or hands free phone calls without digging around for earbuds. And three knowledge seeking chat when I'm walking around usually for simple factual things. That's exactly what I experienced when I was demoing the Ray Ban meta Wayfarers. It turns out there's more questions I feel like asking when there's no friction. I'm very excited for multimodal and real time translation use cases too. They're only going to get better but I think those three are maybe enough. And I think with a lot of these products just having one killer use case like just replacing the you know, the headphones for hands free phone calls or something like if you can just become someone's daily solution for music like that's enough to just sell the product and then sell them another one the next year when it upgrades a little bit. Sell them another one. Keep them as an active user and roll that out for a long time and then if they can do the other stuff that's great too. But you just need to get these one really nail this single use case. And so yeah there's going to be cool stuff but it's fascinating to see them roll this out. And it's also interesting how behind the ball it feels like everyone else is is now like Google was was talking about getting into this, this space. We saw some launches at IO haven't actually seen any of those in the wild. Haven't seen anyone really talking about those Apple it feels like this would be something that they could jump forward to with a stylish pair of eyeglasses with some basic functionality. Just take what's in the airpods. Take a camera. Like they could do something cool but they're like just much slower than yeah.

The other thing with eyewear that's different or that's gonna be like a new challenge for manufacturers is that there's so many different situations where I might want to wear something like a Ray Ban or Jam silhouette one day and then I might want to. I'm playing Jam Jack Marie Maje.

Okay.

But the you know, and then that same afternoon I'm wearing Oakley's when I'm playing tennis or something like that. And so there's a lot more like swapp and then obviously, I mean if.

They can keep the price low, you could maybe wind up selling people multiple pairs and have indoor pair, outdoor pair. It's kind of inconvenient. I feel like there's got to be a better solution to that. But I don't know.

What are this?

Yeah, the bifocals.

Yeah, yeah.

Where they can flip down.

There's transition lenses but those never fully work all the way. But then there's the flip down ones, clip ons. There's all sorts of different solutions. Well, let me tell you about adios customer relationship Magic. Adeo is the AI native CRM that builds scales and grows your company to the next level. You can get started for free at Adeo.

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Well, more news, more, what do we call it? Personnel news at Apple. Mark Gurman has a story in Bloomberg. Apple Chief Operating officer Jeff Williams is stepping down in a blockbuster changing of the guard. As one former executive who reported Williams told Mark Gurman, the band is dissolving. Details here what it means and what happens next. It's interesting because like these personnel moves are so dramatic and yet Apple's such a juggernaut of a company. You don't see it show up in the stock price. You don't see it in like if this was a startup, like investors would be panicking and there'd be emergency board meeting and maybe there's are, maybe the.

Board secondary prices would be gapping up. On the news.

They're gapping down but, but it seems like, it seems like they are going through, you know, a, a just a second act, a third act, a fourth act. I don't know what act they're on, but they are rethinking a lot of stuff over there and it's been interesting to, to see. I think the biggest question keeps coming down to that salary question of, of, you know, if, if the market is going to sit at $100 million for someone who's two levels, three levels down from the CEO, like what does that mean for the upper.

I don't think it's going to sit there unfortunately for all the talented people in the world. I think it's a, I think it's a blip. I mean, I can see it. I just, I mean private companies genuinely cannot afford to do that and Apple doesn't have the appetite. I don't think companies like Amazon have the appetite. I don't think. What was Satya's total comp in 2024?

That's a good question. I don't know.

79 million.

79.

Pay these guys.

It's like Mark picked the number to just needle literally everyone else in the tech industry. It's such a round number, such a viral number, and then such a, such a perfect number to be just a little bit more.

Andy Jassy barely cleared 40 million.

Yeah, that is wild. But I don't know, it'll be interesting to see where these AI researchers sit in five years after they vest out and where the market sits and how much actual work there is to be done if it becomes more of like an implementation role, less research, less discovery of novel algorithms, novel concepts. Like maybe the salaries come down. But you know, I don't know, Dwarkesh made a good point when he was saying like, just measure the value and maybe that maybe the answer is higher pay for tech CEOs. I don't know. That could be.

It could be a byproduct.

But the main thing is that.

But I also think that if you think about, if you think about Meta spending billions to bring on a group of people that were previously at another company, he's effectively like doing an indirect IP acquisition of like, he's effectively doing an aqua hire. Right. So if you think about it from that lens, it's a lot different than, you know, this is the market, the durable market rate for a group of people.

Yeah, No, I agree. I think the number one takeaway is that it feels unlikely that AI researchers at Meta will be paid more than every other Mag7 CEO forever. The ratio will not hold. We might see big acquisition deals, we might see tech CEOs of the MAG7. The MAG7 CEO salaries go up. We might see the AI researcher salaries go down. But I would, I would not expect in four years that or five years that we're seeing, you know, Mark Zuckerberg's direct reports. Direct reports making more than Andy Jassy and Satya Nadella and Tim Cook. That would be surprising to me.

Yeah.

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That is actually a pretty glowing endorsement for Anthropic from Anthropic. Anyway, Ben Horowitz has some news. He's out of Delaware. Andreessen Horowitz has relocated to Nevada and they think you should consider leaving Delaware as well. There's been a bunch of this. It's interesting that they landed in Nevada. We got to dig into this or have somebody on to talk about.

Texas has been popular at least for the, for the Elon.

Yep. People Texas. Horowitz has been living in Nevada at least part time, like for a long time.

Totally.

So like there's definitely roots there. That's where their LP conference was. So yep, they have roots.

So there's a post here. It used to be a no brainer. Start a company incorporated in Delaware that is no longer the case due to recent actions by the Court of Chancery which have injected an unprecedented level of subjectivity into judicial decisions, undermining, undermining the court's reputation for unbiased expertise. This has introduced legal uncertainty into what was widely considered the gold standards of US corporate law. In contrast, Nevada has taken significant steps in establishing a technical, non ideological forum for resolving business disputes. We have therefore decided to move the state of incorporation of our primary business and ah, Capital management from Delaware to Nevada which has historically been a business friendly state with a fair and balanced regulatory policies. So again, I think it's like something like 50% of Delaware's like state revenue is from the C Corp. I'll confirm this.

50%. That's really high. That's really high. But it makes sense. I mean there was never even a question when I came to Silicon Valley about like where would you incorporate? This was pre Stripe Atlas, pre Clarky. But if you were in yc, it was like set up a Delaware C Corp. There's no question.

But anyways, big move. Next time we have Mark or Ben on the show we should break it down more with them.

Well if you're looking to invest in any state in the country or any place in the world, go to public.com investing for those who take it seriously. They have multi asset investing industry leading yields and they're trusted by millions. Joe Weisenthal had an interesting post. I missed it here as well.

Sorry, it just took me a second. It makes up about one third of the state's operating budget is from corporate license fees, franchise taxes and entity formation fees. So very meaningful amount of their business or sorry of their state overall revenue. And I would expect them at some point to try to come out and basically try to resolve some of this tension. Right. Because if you have Andreessen leaving advising portfolio companies to leave as well. You have Elon, you're starting to get some very, very influential figures that are just broadly advising all of their different investments and new investments to get out.

I also wonder the breakdown of that revenue because if it's like millions of companies paying $100 a year, like a couple big companies leaving like Andreessen Horowitz or Tesla, it's not going to really move the budget. But if it's some sort of like tax based percentage of revenue, percentage of earnings or something where the bills get really, really big. I feel like even though I've operated Delaware C Corp's at like significant scale, I've never run into a situation where it's like, oh wow, we're paying Delaware like tens of thousands of dollars.

Yeah, it is, it is.

So I think it's probably like a lot of small companies and so it could be like a real crazy tidal wave that just like continues forever and like a long time because like I imagine that the vast majority of the revenue comes from companies that have been incorporated for like over 10 years. Are not going to move, don't care, are just completely fine. Because the real disadvantage to being in Delaware seems to come from when you're doing like crazy aggressive moves on the corporate side. Like crazy stock based packages based on.

If you're spinning, if somebody's spinning up like a design consultancy. Yeah. They're not worried about, oh, the Delaware Court of Chancery is going to come after. When I, when I try to do this reverse merger or this crazy stock stock compensation package, like the benefit of.

Being in Delaware was always that there's so much case law there that you can just rely on on like any, any lawyer can give you advice that holds very well because they're like, yeah, we've seen this exact situation dozens of times. There's nothing crazy about this. Like if you fill out this paperwork or use this form, everyone will understand what's going on.

Yeah. So the, there's in 2023 there was 300,000 new formations, 220,000 LLC and 60,000 C Corp. So pretty meaningful amount of C Corps on top of of over 2 million entities. And then the franchise tax starts at basically has like a minimum 175 to 400 but then it's capped at 200 to 250k.

So well, if you're trying to get the attention of Ben Horowitz, got to buy a billboard, every Billboard. Go to adquick.com out of home advertising made easy and measurable. Say goodbye to the headaches of out of home advertising only Ad Quick combines technology, out of home expertise and data to enable efficient, seamless ad buying across the globe. And we have our first guest, David Marcus, in the studio. Welcome to the stream. David, how are you doing? Good to see you.

Great.

Thanks so much for stopping by. Would you mind kicking us off with an introduction on yourself and the company, just for those who might not be familiar? Of course.

I'm David Marcus, co founder and CEO of lightspark. And basically we're building modern payment infrastructure to replace correspondent banking with a fast open network built on top of Bitcoin.

Can you talk to me about some of the history of your career and kind of how that ties into bringing you to today the decision to build it externally as a new company versus internally at some other company?

Sure. So I've been building companies since I was 23 years old. Came to America in 08, built a company that I ended up selling to PayPal through a series of twists and turns, ended up running PayPal for a number of years. Then Mark Zuckerberg convinced me to join him, to take a little break from payments and regulated businesses building messaging products at Facebook and then started the Libra DM project there, which unfortunately failed because it was the wrong sponsor at the wrong time and too centralized. And the goal of Libra and Diem was really to provide an interoperability layer for all of the banks and wallets that is real time, that looks like the Internet, that is open, that is low cost, and that enables anyone to move money like you send a simple text message or an email. And sadly, Janet Yell in the morning of June 2021 pulled the plug on this. And so I left at the end of December 21st and in April of 22 started LightSpark with the benefits of all the learnings that I had collected with my team along the journey. And the one lesson was if you're trying to build something that truly looks like an Internet for money, it has to be built on top of something that's unassailable, decentralized enough. And Bitcoin happens to be the most neutral form of digital money ever invented. And so we're building technologies around that to ensure that you can move any currency at any given point in time from anywhere in the world to any other parts of the world at a fraction of the cost of the current system.

Does it ever make sense? You mentioned like wrong sponsor at the wrong time. It feels like with all the news around stablecoins and the genius act and the market structure Bill, there's potentially this idea that it's the right time to build new stablecoins and stablecoin projects and just build in crypto generally. But I'm interested to know like, is there ever a situation where a big tech company or a bank or Visa or a different network might be the right sponsor? Or should it always be from an individual new company? Or should it always be, should there be a particular structure to that where the actual project's decentralized or C Corp. How do you think about the shape of the sponsor these days?

Well, I think, you know, stablecoins are definitely booming right now and, and everyone's building on it. I think the real question is do you want something that's fully centralized again, like the current payment systems and a current financial infrastructure, or do you want something that looks and behaves a lot more like the Internet, which is an open network that is permissionless, that enables developers and builders from all around the world to build applications to move money. And I'm definitely squarely in the latter camp and I want to make sure that we have an open money network, an open money grid, and we believe that the only way to build that in a, in a sufficiently decentralized way is to build it on top of Bitcoin and then build all the services and capabilities so that Bitcoin can actually move fast and cheaply, but also interconnects with all of the domestic real time payment systems in the world and support stablecoins. So that's what we're building at lightspark. And that's why you're seeing now more and more digital banks around the world adopting this new standard that we open source that's called Universal money address. That is basically like email for money. You would have like dollar sign, your name at the bank or wallet and then you can send whatever currency to whomever you want in the world, receiving another currency in real time, on a weekend, after 5pm on a bank holiday, anytime you want. And that's one part of the solution we're building. And then we're also building core infrastructure for Bitcoin to move faster, which has sparked this new Bitcoin L2 Bitcoin. We can talk about that later.

Yeah, yeah, I'm definitely interested in that. Like walk me through some of the history and the current strategies to improve Bitcoin, the lightning network, and kind of bring us up to modern day in terms of just getting more out of what is undisputably the most successful crypto projects of all time. Bitcoin but has has had gaps where people have stepped up and created different L1 and different projects that haven't touched Bitcoin for a variety of reasons.

Yeah, I mean, you're right. Bitcoin is by far the most successful digital asset ever created and network ever created. But the problem with Bitcoin for a long time is that it was too slow, not expressive enough in the sense that developers couldn't really build on it because there were no smart contracts and too expensive to move. So very secure, the most neutral form of digital money ever created. But slow, expensive, not programmable. And Lightning was a first attempt to that. And we, we spent the last three years building on Lightning, making it better, making it enterprise grade. This is why Coinbase and many of their large, largest exchanges in the world are using our technology to move Bitcoin faster and cheaper on top of Lightning. But then Lightning has a bunch of limitations. Like the first limitation is the channel based payment system. And so with that comes a lot of complexity in terms of liquidity, efficiency, routing and all kinds of, all kinds of fun other setbacks and issues. And so we built Spark, which is a brand new Bitcoin L2, which is taking off like crazy right now. And it's actually backward compatible with Lightning, but it enables all kinds of developers to build in a permissionless way, unhosted self custody wallets, like, you know, issue tokens, issue stablecoins, create marketplaces and AMMs on top of Bitcoin for the first time. And, and that's really critical because like we need to make Bitcoin the most efficient settlement layer in the world and, and also make it the most decentralized and trustless layer in the world to move value. And we think Spark is a massive step towards that.

How are you thinking about adoption of Spark and incentivizing adoption? And I'm more interested in kind of like what are the pitfalls and kind of like traps or potholes along the road to adoption that you don't want to get caught up in? Because in some kind of counterintuitive way, people always talk about Bitcoin's volatility. It's been like the least volatile really. And it feels like there's a lot of other projects that have kind of come out and created like, you know, some viral sensation, some sort of massive incentive where a lot of people are getting, making a lot of money very quickly. So it skyrockets. But then there's something that's missing fundamentally. And then the projects or the, or the trend kind of dies Off. How are you thinking about engineering the incentive structure for long term adoption?

Well, look, the best incentive you can build is build a product that solves real problems. And I think, you know, unfortunately in crypto sometimes that was replaced with a coin that some people call shitcoins that are basically dumped on people to incentivize them to use the underlying technology. We don't have a shitcoin. Our coin and our unit of accounts for the network is Bitcoin that we don't control, thankfully. And so we have to work really, really hard to build utility that solves real world problems for many players. But in bitcoin there's a lot of liquidity because as you said, it's like the most successful digital assets ever created and the most liquidity sits in Bitcoin denominated in bitcoin. And so you have a lot of traders out there, you have a lot of platforms that actually want to tap into that liquidity. And they couldn't until now because there wasn't a technology that enabled developers to build those marketplaces and platforms on top of Bitcoin to, to create these self custody wallets that could move bitcoin in real time at low cost and to do all of these things that Spark enables. And, and I think, you know, that's why we're seeing such a, such an amazing early adoption and so much traction with a wide variety of developers, whether they're building payment apps, they're issuing stablecoins, they're building marketplaces and AMMs and decentralized trading platforms. We're seeing all of that happen on Spark. Right now.

I have this kind of funny counterfactual that I like to run in my mind of the PayPal mafia. And the PayPal diaspora is so dominant in tech everywhere and politics and everything and science and just literally everything. And I like to run this counterfactual of like, what if the team stayed together forever? Like, what would PayPal as an entity look like? Would it be just the biggest company in the world? If you had Elon and Peter Thiel and David Sacks and Keith Raboy and you and all these, like the larger crew still, they are just like chopping down problem after problem after problem in the financial system. And I'm wondering if you've ever played that, that, that, you know, mental exercise. But more precisely is, was there something structural where PayPal was not able to jump headfirst into crypto as fast as possible? Like if, if at the time, everyone in the company had just been. As soon as the White bitcoin white paper comes out like we are orienting the company around this. Would it have been possible to, to actually lean in and be a leader and an innovator in that category? Or was it sort of like an innovator's dilemma problem where, I mean PayPal is doing great still, but where there was really no way for the structure of PayPal to play in the new paradigm?

Yeah, I mean, look, I think it's an era thing. The era of all of the people you mentioned was predating all of this and then the company sold to ebay and most of these talents were completely gone, building their own things. And so I think it's an era thing. The era of, you know, the Peter Thiel ELON, Max Levchin PayPal was really, you know, the first really big push into, you know, consumer facing fintech. I think of like Visa as a fintech that's like basically built technology that enables money to move around like at an enterprise level, serving banks, not consumers. And PayPal was kind of the first major fintech success, but it was really not the crypto era at all. So I think it's just a time thing.

The next time PayPal goes through a leadership change, we need to have an all star game where we bring back the entire PayPal mafia for one quarter. Peter Elon everyone's full time for a full quarter. Just how hard can we go with PayPal? Let's make it great. It's fascinating.

Jordan, I'm curious what your conversations are like with people that are maybe just starting to build on crypto. Rails excited for the first time, or have been building for a long time. When talking with you and understanding your vision, it's very easy to see why Bitcoin is an obvious choice for a network to build on top of because it's decentralized, it's very global. But the default until now has been building on Ethereum or Solana or these other networks. How do those conversations go? Are people coming around to the idea that. Yes, having a fully decentralized network that no one individual or group has overt influence on is a great place to build a business. Right, or bring your business.

I mean, look, I think the only reason that all of this developer energy went to all of the other platforms is because you just couldn't build on top of bitcoin. The tools weren't there, the technology wasn't there. And I think, you know, now, now like I feel like we're going to have a renaissance of developer energy on top of bitcoin. Because not only because of Spark, by the way, like there are many, many others that are building new capabilities on top of Bitcoin that are enabling those new use cases to happen without losing the true north of decentralization and trust lessness of, of Bitcoin. And, and I think it's very compelling for a lot of developers and a lot of people who want to companies because again, like the depth of liquidity of bitcoin, the desirability of bitcoin in the world has just no parallel in the whole industry. So it was just a matter of removing the obstacles that were standing in the way of developers building really great products on top of Bitcoin. And I think it's happening right now.

How do you guys solve the immediate future from, from what you said, obviously you can have stablecoins on top of the bitcoin network, which solves one of the key issues with, with Bitcoin as a method of value transfer that, that also historically held it back is one, why, why do I want to buy a coffee? You know, any, anybody that bought a coffee 10 years ago with Bitcoin or pizza or whatever it was, you know, probably regrets it now. But how, how are you. How do, how do, how do transact, you know, is it effect? You know, how are these, how are the. Let's say I'm transacting with stables on Spark. What is the sort of like economic, what does that full economic exchange look like? How, what are fees paid in. Is it paid in the stable or is it network level?

I'm so glad you asked this question because that's one of the killer selling point of Spark for stablecoins which is like, you know, if you issue a stablecoin on Ethereum or an EVM chain or any other chain, you have to pay gas fees for, you know, basically transaction fees in the assets that you, most people don't own. Like whether it's eth or soul or whatever it is. In the case of Spark, you actually pay when you move stable coins in the stablecoin. So it's very much focused on payments. And that's one of the advantages. So one, it's cheaper. Two, you pay with the asset you're transmitting, which is kind of the way that most payment systems at that scale really work. And then you have the beauty of the trustlessness of knowing that even if you're transacting with a stablecoin, you can always have a unilateral exit to Bitcoin L1 with your stablecoin and no One can prevent you from getting your money out. So it's the best of trustlessness, the lowest cost, the most efficient, and you don't have to complicate how you actually pay for the fees for most people who actually don't own the underlying asset needed to pay a fee. So it solves a lot of problems to make Bitcoin the absolute best platform for stablecoin payments.

So, yeah, how did the actual dollars get custody in that way? There's always this hard interface between something that's truly decentralized and then like the US treasury at some point. And I feel like that's where a lot of the stablecoin companies kind of figured out how to bridge that gap. And they exist as this layer between the US government effectively and, and the crypto community or like the programmable money world. And so it feels like we're on this trajectory of like, let's make this more programmable. But how close are we to something that's like fully programmable?

Well, I think, you know, here's the issue, right? So, I mean, first of all, like, stablecoins are always going to be fully centralized. And so that's why it's so important for the network not to also be fully centralized, because then we're basically replicating the entire payment system that exists today.

With just new players.

Circle can. Is it true that Circle can just freeze all usdc?

Yeah, sure, yeah, of course.

I mean, it's a company running. It's basically fully centralized. So, like, all of the stable coins are centralized. Like there are a bunch of people who attempted doing algorithmic stable coins that would algorithmically basically absorb and it just doesn't work.

It just doesn't work exactly like it doesn't work.

And so stablecoins are fully centralized. I think programmability, programmability always comes at the cost of trustlessness. So like, the minute you can establish new conditions for how money can be moved with a smart contract, you lose the ability to have a full unilateral exit where no one can actually prevent you from exiting your fund from the network if you really want a trustless exit from the network. And I think that's the balance. And I think, you know, what we're focused on right now with Spark is really providing people with the right level of trust and the differentiating factor that Bitcoin can bring with trustlessness. But I think gradually what you'll see is different levels of trust for different levels of functionality. If you want more programmability, you'll have to actually relinquish a little bit of that expectation of trust to get more programmability. But those two things will always be intention.

How are you balancing go to market right now? I imagine you have this pretty intense tension between for example, a developing country that's excited or companies in a developing country that's excited about the potential of Spark versus a Fortune 500 CEO that's saying, David, we want to do something in stables like let's talk. Where are you splitting your time and where are you most excited?

Well, I mean right now I feel like there are two parts of our business, right? It's like one part is like core infrastructure to make Bitcoin better, faster, more programmable, better for developers. That's all Spark. And then there's the mission of connecting all of the banks, all of the wallets, all of the payment networks in the world to Bitcoin with universal money address or uma to enable people to actually move money from their bank or from their wallet, the place they pay their bills from, the place they have a debit card or you know, all kinds of different instruments attached to, to any other point in the world, making basically money flow in a completely open, unrestricted way 247 at a very low cost. Both of these things are basically built on top of Bitcoin and serve different types of constituents that basically, basically extends the reach of the network. But, but these are the two core focuses and it's, it's, it's a very interesting time for us because on one side we have permissionless building on top of Spark with developers building all kinds of different things. Like I, I turn on my, my computer in the morning or my phone and I look at like what people have built the night before. I have no idea what's going on. I don't onboard the business, I don't have a contract with them. Like it's a wonderful thing. And then on the other side of, of things I'm going through like diligence processes and compliance stuff with like the largest banks in the world that are coming onto the network. So it's kind of a little schizophrenic on both sides of the business, but both of these things accrue to the same thing, which is an open money network that enables both developers on one side of the spectrum and regulated entities like banks and wallets on the other side to move money in real time globally like never before. So it's kind of a fun two sided part of the business right now that makes sense.

How are you thinking about corporate stablecoins. There's been some announcements, different PR stuff around companies saying we're going to make our own stablecoin. And we were joking on the show a while back. Does that just turn into like a Kohl's Cash scenario? Do people want every big retailer that they interact with to have some native stablecoin or the issuers that we have today, classic problem.

There's too many standards. We need one standard and then you have one more standard than you had before.

I mean, look, when I think about these things, I always come back to one thing which is what problems are we trying to solve? And I think it's very clear that if you're trying to solve for dollarization in the world, like if you're in Argentina or in Venezuela or in Turkey or in parts of Africa, you'd much rather have a dollar denominated account with a US bank. You can't have that. So a stablecoin in this case mostly tether, is the solution to that. It's the next best thing to having a US dollar denominated bank account in the US and it's great. And it increases the reach of the dollar. It's great for America, it's great for these people.

It works.

When it comes to domestic use cases for stablecoins, there's a bunch of really good problems to be solved in institutional capital movement. It's like you can't net settle trades on weekends or after hours. You can't move liquidity between institutions to make the market more efficient with the current system because it doesn't allow you to do that. Stablecoins help do that. But from a consumer standpoint, I'm kind of at a loss to understand what an American consumer would actually get from using a stablecoin. I like, I, I don't get it. I don't think there's a massive problem to be solved. People can pay one another pretty easily with normal dollars. They're already digital dollars. Basically. Like if you look at your Venmo balance or your Chase balance, it's already a kind of stable coin that you're seeing. It's like virtualized dollars that are controlled by the bank. It's like basically a stablecoin. So, you know, I think this is a conversation worth having around like what is the consumer application using stablecoins in the US that is actually solving a problem for the vast majority of Americans. And you know, I don't know what that is.

Can you talk about open source and how that inter, like the current meta around open source in, in the crypto and community and in just the role of decentralization. Was it ever an option not to have an open source project? It feels like kind of stable stakes now. But do I have that kind of correctly in terms of the characterization?

Yeah, no. I mean it's super critical. And that's why almost everything we build is open sourced. And the reason for that is like, you know, people building in this industry are trying to make it like, you know, anti fragile. And one of the ways that you make a technology anti fragile is you don't concentrate all of the capabilities around one company that wins it all. And I often talk to my team here at lightspark and basically tell them, look, we're going to be very successful the day we have a bunch of competitors building on uma, building all kinds of services to compete with us on the very technologies that we've helped build. And I think that's the way that we make ourselves kind of redundant and ensure that the network is actually going to exist even if we were to disappear for whatever reason. And I think that's kind of an ethos of the entire industry that we care deeply about.

Can you break down a little bit more how UMA works? I think anybody that's played around with crypto a little bit may have had the experience at some point of sending Bitcoin to a USDC address and realizing that it's just gone forever. So the idea of a universal address that can receive and send a bunch of different currencies makes sense. But I'm curious how it works and how you're enabling other companies to adopt it as a standard, even if you guys aren't necessarily sounds like directly benefiting financially from that.

I mean we are, for the companies that we serve, we are benefiting financially from that. But it's an open network. But the way it works is that an institution like take Nubank, which is one of our early partners on UMA, which has over 100 million bank customers in Latin America. And so they would assign you an address like dollar sign your name nubank. Your account is denominated in Brazilian realize, let's say I'm here in the US and I'm with a bank. My UMA is going to be $davidank.com I'm sending dollars to you in Brazil. And what happens in the back end is basically UMA is a pre transaction open messaging protocol. So it enables me to go to the Nubank server and basically say, hey, is this address a valid address? What is the currency that this person wants to receive what is the exchange rate that you're going to charge me for this transaction. Then I can present a fee structure to the customer. In the US Sending dollars, show them exactly the amount that the recipient is going to get in Brazilian reais. They click send. When they click send, basically the dollar gets converted into Bitcoin, gets pushed on lightning to Brazil, gets to Brazil a second later gets converted to Brazil and realized deposited in the account works 24 7. Super low cost and super tight spreads between all of these currencies because Bitcoin has so much depth of liquidity with all of these currencies because it's traded so much and so it's super cost efficient. Real time 247 and open. In some cases like Nubank, they build the connectivity into Bitcoin themselves into lightning because they can actually do the conversion on their side. In some other cases we build the capabilities for, for instance, US banks and European banks and Mexican banks and others to actually connect onto the network using their domestic payment system. So they would send in this case the dollars to us and we would convert to Bitcoin and push as a service to them so they don't have to deal with the Bitcoin portion of it it. But Bitcoin is always the net neutral settlement asset between those currencies and allows to move liquidity across countries, across payment Systems in real time 24 7.

That's the way it works.

Very cool.

Can I get an update from you on what's happening in Washington? Break down the different legislation that's going through the, the U.S. government, kind of what your perception has been, your takeaways, status update. But also, are you optimistic about where things are going on the regulatory side?

Yeah. I mean, look, for a guy who's been shut down by the Treasury Department with the most public shutdown of the crypto industry, one could argue it's quite a change, quite a vibe shift. Right. And I was at the Digital Asset Summit at the White House and being welcomed at the White House in the East Wing in a very ceremonial way to actually promote the whole industry was, was the massive, massive whiplash of the best kind. Right. And I think, I think, you know, look, there's a lot of credit that goes to this administration, to David Sacks, Bo Hines, but also to people on the Hill who've been working on these important pieces of legislation that are going to actually make building the, the next set of technologies that will reinvent and rewire the world financial system here in America, which I think was absolutely Absolutely direly needed. And so I'm super bullish. I think we have gone from an administration, a government that wanted to fully kill the entire industry to one that wants to promote it and ensure that American companies actually win at this and we win. And I think it's a vital interest for America that we continue to lead with financial services infrastructure. So I couldn't be more bullish of what's happening in D.C. right now around our industry.

Is there anything that you're looking out for in the back half of this year? It's obviously, we started strong with a meme coin out of the White House. We've got the new stablecoin regulations passed. Anything in the back half of the year that you're looking at or anticipating.

I think everyone's really anticipating market structure and like having a market structure bill that will clarify the rules of the road for that entire industry. I think that that's as important in my opinion as the stablecoin legislation that is going through now.

Yeah, it's great.

Well, thank you so much for stopping by. This is fantastic.

Thanks for having me. Great to be on the show.

Always welcome.

Talk to you soon.

Talk soon.

And next up we have Ben Thompson from Stratecheri coming into the studio. Very excited to talk to him.

The moment we've been waiting for.

Yeah. Welcome to the stream. Ben, good to have you on the show. You've been a backbone of many analyses here on the show and we're excited to welcome you to the show. How are you doing?

I'm doing good. I put on a button up shirt and a jacket just for you guys. So you should feel honored. I am wearing shorts underneath.

I will admit you didn't have to tell us.

People always ask if we wear shorts. We actually do wear the full suits.

We gotta stand up to hit the gongs.

There's a wide shot.

I am, I am the poser here. So I'm happy to admit.

Well, it's a great, it's a great sign of respect in our culture to put on a suit for a TVPN appearance. And we're just, we're so excited to talk to you. I, as you know, I've been lucky to read your work in my entire career and I think it, I think so many of the thoughts that I have are now like your way of thinking about technology and markets is so embedded in my brain that ideas that I hold as true or just foundational beliefs are actually your beliefs that have just become so immersed. So it's great to talk.

Well, thank you. I will attempt to implant new ones or maybe show you the error of your ways.

Sounds great.

I do have a question on the nature of where you sit in the media world before we go into actual questions about tech companies. It's interesting that in some ways you're a journalist, but you don't really do the scoops and breaking news that much. But you also don't issue just straight up buy and sell recommendations. What was the, the thesis behind not just actually having a price target and not doing like this is a sell side bank, but independent?

Well, when I started, I mean, it's funny to hear you talk about like my quote unquote place in the ecosystem.

Sure.

Because when I started I had like it was 368followers on Twitter. I was just some sort of random, random person on the Internet in retrospect, sort of right place, right time. I think is, is certainly the case. But I did perceive there was a large gap between tech journalism and I would include a lot of the bloggers there who were writing a lot about products. And then there was Wall street that was very focused on sort of the financial results. And to my mind there was a large space in the middle which tied together the products to the financial results, but also the overall companies and strategies. And I'm very interested in culture and how that guy's decision making. One of my sort of precepts is all these companies are filled with smart people. And a lot of people, when you ask them why they did something wrong, their only answer is that they're stupid. And I'm like, no, they're not stupid. It's actually much more interesting to assume they're smart and are doing stupid things and trying to unpack why they are doing that and what goes into that. And so that was sort of the thesis was that there is this space to explore these spaces. And then there's a business model aspect which is I started Struckery two years after Stripe started. I think they had just come out with their billing product and the only alternative at the time was PayPal for subscriptions. And it was fairly sketchy and there was lots of like horror stories out there about, you know, stuff. And just the Stripe API was so great and the things you could potentially do with it. And so on Wall street you're putting a price on it. You're also charging like $100,000 a year or something like that. And so you get a small list of high ARPU clients. And my thought was I could go in the opposite direction and get A large list of low ARPU clients, thanks to things like Stripe and the ability to subscribe. And that would. And as part of that, I wasn't going to go through the rigamarole of getting registered and doing stock picks and all that sort of thing. I've always joked, if you want a stock pick from me, you're gonna pay me a whole lot more than $15 a month. It was $10 when I started, and it's actually pretty great now. There's some. One of the critiques I do get, particularly from my friends on Wall street, is no Skin in the Game xyz. I think at this point I'm large enough that my reputation is significant skin in the game, but I do recognize the validity of that critique.

Yeah.

And, you know, if you make a bad call, you're gonna have to circle back to it in two years and write about it yourself and admit that you got it wrong.

Right, Right.

Which hurts, too.

No, I had to write about this week. Like, I was very optimistic about Apple's Apple intelligence announcement last year and the theoretical power it would give them over the model makers. And now I'm ready. Actually, no, they're gonna have to pay up. And that's, you know, that was a bad call by me that, you know, I think was, you know, very well received at the time and might have gotten that one wrong. And so I do need to be straightforward about that. And so just this morning, I was very crystal clear, like, I got that one wrong. That was. That was. That was an issue. What is nice is strategically kind of ended up being in this interesting place where I feel like I'm a little bit of, like, the Switzerland of tech in that no one pays anymore. If you're a CEO, you pay the same amount as, you know, Joe Will down the street. That is paying it. I don't invest directly, which I think made sense when I started because I didn't have any money. It's probably hurt me a lot over the years since then, but I don't like. And I think this is a different West Coast, east coast thing where it does feel like on the west coast, everyone's talking their book sort of all the time. And that's why I generally, as a rule, don't have VCs on to do the trajectory interviews, because it's kind of hard to get a real take because that is such a motivation. And so me coming in, being like, I have no book to talk. I'm just here saying what I think I think has been good for The west coast audience, which is my base audience. Even if the East Coasters think that I'm being a big wimp.

That's funny.

Yeah. The talking your book challenge, we go through that a lot.

Trying 12 beats.

Well, yeah, and we just try to get a bunch of different opinions and triangulate what we think is real.

I'm trying to come up. You have tppn. I'm trying to come with a P so I can get the talking book network in there.

But Talking book production network, ESPN for talking your book.

But yeah, it is a real struggle to find somebody that, for example, has a deep understanding of every foundation, model, company, but isn't massively conflicted in some way or another.

Extremely, extremely.

Yeah. And so it's one of those things you just sort of. You end up like, there's so much path dependency and all these sorts of things. And like I mentioned, like, a big advantage I had was I started at a time when sharing good links was very high currency on Twitter. And so, you know, I grew very, very quickly, much more quickly. I sort of had a five year plan to go independent. I ended up doing it in less than a year, in part because it just sort of spread really, really rapidly. And it was an ideal time to be someone sharing interesting links regularly. And I wasn't sharing them. The beauty is my readers were sharing them. They were doing sort of the marketing for me. And so I'm very cognizant of sort of the luck I had in that regard. And then just over time, and it's been an interesting journey for me to grapple with my different position in the ecosystem. So when I started the structure interviews, that was sort of part of it, which was I started out not knowing anyone. I got to the point where I can talk to anyone that I want to. And so how do I square that? I can't be the guy with the chip on his shoulder trying to make a name for himself forever. It sort of gets. It's like the meme with the guy, how are you doing, kids? Like, at some point you have to accept your part of the establishment. How can I do that while still staying true to the idea that Shachekery is about the readers, it's reader funded. My loyalty is to them. I'm very clear. I have no loyalties to anybody else. And so. Well, I'll just. I will talk to people in sort of acknowledgment of what I can do, but it's going to be fully transcribed and published and sort of available to Everyone.

Have you ever dealt with or thought about the attack vector of a special interest? You know, buying a thousand plus, you know, thousands of seats to a single, you know, independent publication and saying like, yeah, like, you know, we're happy, you know, we got seats for all of our employees, actually, because we really, you know, love the.

And then.

And then suddenly they're sitting over there, you know, representing, meaning very meaningful amount of your revenue.

I mean, I. Fortunately, I think of a scale that I don't have that problem.

That's good.

There we go.

But no, I think audience capture for subscription sites is a potential issue for sure. And this is another thing. I was sort of right place, right time. I got big enough by the time that it doesn't matter. And yeah, if someone's really up, like, I give refunds all the time, actually. If someone really upsets me, I will refund them. And every dollar they paid me, I'm just like, go away. I don't, you know, I don't. You're being abusive or whatever it might be. And that, that is a beautiful thing about the relatively low price, high customer base model is no one has power over me. I have the burden of publishing as often as I do. I feel a heavy weight of duty to my customers when I write something I'm not happy with, like, I don't sleep well. But at the same time, there's no one customer or no individual that can come in and be mad at me and impact my business.

I'm seeing there's maybe some sort of parallel between legacy media and independent media, where independent media, it's not by default more pro tech or anything, but there's just no salary cap. So if you're at a legacy institution and you're writing probably some sort of rough, loose salary cap of a few hundred thousand dollars, whereas you go independent, it's feast or famine. You might fail, but you might get really, really successful and have a huge income from that. And I'm wondering what we're seeing in the AI salary wars where we're seeing more and more talent and, you know, Mark Zuckerberg potentially paying $100 million bonuses. Do you think that Apple will come around to spending more money on researchers? It feels like they kind of have an internal salary cap. With Tim Cook making 75 million. There's now people that report two levels down from Mark Zuckerberg that are making more than Tim Cook. And you have this weird dynamic where even if there's no actual salary cap at Apple, you kind of have an implicit one from the CEO?

Yeah, for sure. I mean, I think just to go back to the media observations you started out with is as you increase transparency in the market, as you decrease non related barriers, which in the publishing world previously was really geography. And when everyone's on the Internet, you inevitably, in just about all cases you get a power law, distribution. And a few people make a ton of money because they win most of the market and then some people make some and then there's a long tail that sort of don't make any at all. But it's very, it's interesting, it's fluid in a way, but it can sort of become somewhat static as long as the people at the top sort of, you know, continue to do well. But, but what's interesting about AI is for 40 years you would have periods of time where you'd have tech companies going head to head in a product market. And I think one of the reasons, part of the software eating the world sort of idea is the way you get an apex predator is that that predator killed everyone else first. And so you had tech companies fighting each other for the first 20, 30 years of tech. The ones that emerged were lean, mean killing machines and they and the entire industry were sort of set loose on the rest of the world and everyone was just like, was getting slaughtered sort of left and right. But what you also had over this past sort of 20 years or so is the big companies in particular are sort of slotting into unique slots. So you have Facebook is social, Google is shirts, Apple is devices, Microsoft is business or you know, business applications, Amazon, E commerce, et cetera. And obviously these companies are very large and do lots of things and there's some overlap in different places, but they've been fairly sort of distinct in their categories and they've been dominant in those categories. And so they've been in a place where like Hollywood is wanting to get to. Right. What is the dream in Hollywood? You want to have a franchise where the next Marvel movie matters more than who the star is. The reason that's so great is because you now have bargaining power over the stars. So you just sub someone else in. And whereas the old style like Tom Cruise makes the most money because Tom Cruise on a movie poster sells the poster. And so in a negotiation he has massive bargaining power, so he's going to get paid a lot of money in tech, it hasn't been that the companies themselves have been franchises. And so the overall anyone who works in tech or probably works in any entity, but you know, there's a Few people in each company that are critically important really make the whole thing go. Everyone else is fairly replaceable. Those people have probably always been somewhat underpaid for years and years and years, both just by the nature of companies and the cultural issues and your salary cap sort of analogy. But then also just like it's not a transparent market, it's not hard to price sort of what people are worth. With AI, everyone's trying to do the exact same thing. So you have multiple companies trying to do the same thing. The output is somewhat measurable. I mean, all the AI test stuff has issues. But by and large everyone kind of knows who has the good models and who doesn't. The scalability questions, because all these companies are trying to do the same thing. We have a very unique situation where the bargaining power, you increase transparency, you increase sort of the liquidity or the ability of people to move around because they're doing the same thing. The bargaining power shifts to the people that are super valuable because suddenly it's much more clear who's valuable and their skills are much more transferable. So this is, I think, a very underrated bear case for tech in terms of AI, at least for this time period, is they've lost that murky bargaining power over employees that they enjoyed for decades. And currently you're seeing what happens when you don't have that. You start paying employees what they're worth and obviously that's great. I'm not saying this is a business analyst. It's not a sort of a moral statement, but it is like what Mark Zuckerberg is doing, I think is totally rational. I think it's a classic sort of Clayton Christensen. From Facebook's perspective, AI is all upside. So of course they're going to invest what they need to do to win. But it's costing him a lot of money and by extension it's costing everyone else in the ecosystem a lot of money.

Well, isn't it in some way is the right way to think about the last couple weeks, like more of like an aqua, like an unofficial aqua hire in the sense. Sense that it's not just the people, but it is the know how in terms of, hey, here's there's these things that we want to do that are important to our business in a lot of different ways. And we're basically. It's. It's like the collective is actually more valuable than any one. Like the collective together. Getting 10 researchers at the same time is meaning, you know, is meaningfully more valuable than just each individual researcher added up.

There's probably something to that. But I think again, what is actually different between what Google is trying to do, what Anthropic is trying to do, what OpenAI is trying to do, and what Meta is trying to do, they're all trying to do the same thing. So my suspicion, I'm not an AI researcher, so I don't want to overstate my knowledge in this space, but my suspicion is skills are fairly highly transferable. And when that is the case, there is in some situations, if lots of people can do those skills, that's terrible for the employees because then their bargaining power gets diminished because anyone can slot in. But we're in this space where the skills are transparent, knowable, transferable, and there's not very many people that can do them. And so it's, it's a scarce resource that everyone's fighting over. And that's why you see this real shift in negotiating leverage as, as manifested through these dollar figures to AI researchers.

Yeah. Do you think, I mean, Google seems like the most fragile and the most like paranoid about just disruption. It's not all upside. It could be very bad for them. The innovators dilemma, you know, you had this back and forth where Sundar Pichai mentioned that he hadn't read the book. You said it doesn't matter because it's a structural issue. I think that's a good point. But if you play back the counterfactual, is it ever possible to disrupt yourself? And essentially like if the Gemini app had launched before ChatGPT and they had taken over that mindshare and maintained 90% ownership in that, like it would be somewhat disruptive to their revenue and their profits as they transition over. But when I sum the revenues from OpenAI and LLMs and then Google search, I'm not seeing some massive drop off. That's actually, that actually would destroy Google in the short to medium term. But I'm wondering if you think it's like, is it entirely impossible to avoid the innovator's dilemma by disrupting yourself?

Well, number one, you have to also look at margins, not just revenue. But number two, you actually, you answered your question. Google didn't launch Gemini as a jet bot. That's the answer. They were years ahead.

Yeah.

They invented the transformer nearly a decade ago. And so in many respects, like there's parts of this question that the counterfactual makes the point in that it is a counterfactual and it's not reality. Now I do think, I think Google has done better than I expected over the last two years. I like what they're doing in search generally. I think they, it does seem to be the one part of the company that still functions like they, they can actually iterate and build products. What we're seeing is reminiscent of what they did a decade, 15 or 12 years ago when everyone's like vertical search. Google's done all the, everyone's gonna search in apps. And Google completely transformed the serp, the search engine response page, whatever it is, the search engine results page, to be local or to be shopping or whatever. And Yelp's been throwing a hissy fit sort of ever since Sense. And, and so that's what they're doing with search, right? And, and with search overviews. And they have this new search labs or, or AI mode. They can sort of test stuff out, what's it scalable. Once they, they're confident about the monetization issues, they can sort of shift it over. I call it the search funnel. Search AI funnel. I think it makes a lot of sense and I think, and this has always actually kind of puzzled me where I think they're responding fairly well, even though this seems to be a textbook case of disruption. And I went back to an article I wrote years ago called Microsoft's Monopoly Hangover and I went through Lou Gerstner's autobiography and about how he turned around IBM. And his real insight with IBM was everyone wanted him to break it up into sort of different pieces. And what he realized was IBM was so big and large from having downstream of monopoly that actually the only thing they were good at was being big. And so breaking them up would actually just create a bunch of subscale low performing companies that would all get wiped out. But as this behemoth, they could go to other big companies and solve all their problems at a very mediocre level. But it's still sort of an attractive proposition. And under Gerstner they really rode the Internet wave. They went to all these big companies, said this Internet thing's happening, you need help, we'll solve your problems for you. And had a very sort of successful run, you know, kind of until cloud came along, which Gerstner by the way was, was, was a proponent of. But you know, by that time the IBM people were back in charge. And I was thinking about the context of Microsoft where Mike, business models are hard to change and disruption is ultimately about business models and culture is hard to change, even harder to change. But what can't really be changed is the nature of who you are. And I think There is, you know, in Microsoft they were in a similar situation. They were a big monopoly and they weren't a product company. And the attempts to become a product company with Windows 8 and all the things that went on around that time inevitably, inevitably failed. And say Nadella, to his great credit and you know, sort of diminished Windows importance in the company. Broke it, literally broke it into pieces, spread it around. And this was a multi step process and got Microsoft back to a place of we're big and we'll do everything. We're not a Windows company, we'll go in there and we'll go solve all your problems. Very sort of reminiscent of the second version of IBM. And I go back to Google and I've always been intrigued by the I'm feeling lucky button, which doesn't exist anymore. But I always enjoyed that that button continued to exist long after it was impossible to click because the moment you started typing the search box it would start auto searching immediately and jump right to a search page. But it was there in a. It's just so core to Google to give you the answer to know everything, like to know everything about the world and to there's a bit where even though the core of their business model is 10 blue links and it's not just the users choosing the search link, which gives them a data feedback loop so they know which results better, but also the users choose the winner of an auction Google puts on for ads. And it's an incredible business model and there's something about that that's always been intention and counter to what Google was founded to be. And I feel like that germ of what Google was founded and meant to be is an AI answer engine. And it almost feels like even though Google is old and large and fat and slow moving, that core aspect of their nature is still in the culture. And that's why they're finding it in themselves, I think, to do better in AI than you would expect. Was it enough to watch a chatgpt before OpenAI? No. Was it enough to have any sort of cogent response for the first six to nine months? No. But it was enough that I think they've done better than I expected over the past year in particular and gives me, I think, more optimism than I expected I would have for the company when ChatGPT first launched.

AI overview from Google if you search Google's mission Google's mission is to organize the world's information and make it universally accessible and useful, which is exactly what language models do really, really well. Like the thing that's just undeniable, right, is you can debate whether this is going to be the year of Agents. It doesn't feel that way to me yet, but. But this is the year that most people have realized that, wow, LLMs are very good at organizing, surfacing, and making data valuable.

You mentioned just the debate over breaking up IBM. I'm interested if you could take us through some.

I bet you didn't realize you'd be talking about IBM today, did you?

No, no, no. But I want to talk about intel and kind of the history of some of your takeaways and. And what you think you've gotten right in the past, your perception of, you know, should they break up the foundry business and what you think might be in the works with Lit Bhutan coming in there. Because I was listening to Dylan Patel talk about his conversation with the new CEO, Lip Bhutan, and it seems like they're doing lots of tightening up, lots of layoffs, but it's kind of. I don't even know what framework to apply to analyze layoff. Like, is a breakup the correct thing? It feels like something people just say.

Yeah. So Intel. It's funny, one of my very first articles was about intel. And what I said at the time was, and this was 2013, and this was an art. Like, you know, when you start a site like stri, you're like a new band. And why does everyone think a new band's first album is the best? Because they've been working on these songs for years. Right? And then the next album, they had a year to do it and they all suck. Right. So I'll let people decide if that applies to checkery or not. I won't be offended.

Sophomore slump.

But.

Yeah, but I'd have been on, you know, intel had been a thing I've been wondering about for a long time, which was by 2013, when I started, they had clearly missed Mobile. Now it wasn't clear to them they were still trying to do the atom processor and just. They're gonna figure it out tomorrow. And the problem with missing Mobile is, the problem with intel in general is intel is always very biased towards high performance. And this goes back to actually Pat Gelsinger, his first time through at Intel. Intel had the cisc. The way there's CISC versus risc. It's like. It's different ways of organizing bits or whatever. RISC is generally more efficient. And actually, even intel processors Today, even though x86 is CISC, the internal, it's retranslated internally to a RISC Type language. None of that is really important other than to say in the 80s there was a real push in intel to switch away from x86 and to a RISC type of I don't use architecture but like for the processors. And Gelsinger was a leading proponent that this is a terrible idea. And the reason it's a terrible idea is because there was already a huge ecosystem of software built around x86 and all this low level code and capabilities that no one ever, that was written once and no one ever wants to touch again because it's miserable work. And he's like to rewrite all that stuff would take at least two years. And in that time our ability to manufacture chips will improve so much that had we just stuck with cisc our processors would be faster. And that was the right bet. And that's one of those foundational bets that I why I like to think about companies and their history and what goes into that which is intel from the 80s on has solved its problems by having superior manufacturing and by moving faster. And yeah, our chips may be theoretically less efficient, but if our manufacturing is better and our transistors are smaller, it doesn't matter because that will swamp whatever theoretical sort of efficiency you might have. And this drove the entire computer industry. You would write to write a program. Just every second you spent optimizing your software in the 80s or 90s was a waste of time because whatever improvements you could get would be swamped by the next version of if you went from 286 to 386 or 386 to 486, that jump was so large you were better off focusing on features even if it made your software sort of slow to use on the current hardware because the next generation of hardware would be so much faster it would solve your speed problems for you. Now this has generated a lot of bad habits amongst tech developers. That's why you get bloat and why you have poor performing things and all those sort of things. But this was sort of super critical. And so intel at its core has always been focused. They've always been manufacturing first and focused on better and better performance. What happened with mobile is in that calculation did not come efficiency. They were never focused on efficiency. And in mobile efficiency was everything. So what happened with mobile is Apple went with an ARM processor made by, made by, made by Samsung and they basically rewrote everything. All that stuff intel didn't want to rewrite in the 80s or if they rewrote would just give other Process processor companies, a chance to catch up with them had to be rewritten for mobile because efficiency was so much more important than performance. When that happened, intel was screwed. Now, it took them a long, long time to realize they were screwed, but they were just fundamentally unsuited to be competitive. It was the whole Paul Adolini turning down the iPhone contract is not true. Tony Fadell, I said that once and I got a call from Tony Fidel, actually, this is when I had him on it for an interview. And he's like, this drives me up the wall. Intel was not remotely competitive, even though they had ARM chips then. Even their ARM chips then were focused on performance, not on efficiency. And so the problem for intel is once you missed mobile, you were going to lose your manufacturing lead at some point because volume matters so much. And every time you move down the curve, your transistors get smaller, the cost increase massively. So you need volume to spread out the cost of building these fabs. Like back then, when I wrote this article, fabs cost 500 million. Now they cost like 20 billion. And this is over a course of like 12 years. So it was clear intel was going to be in big trouble back then. And so I wrote, they need to build a foundry business. They need to figure out a way to build chips for other people. Because in the long run, the cost of keeping up in manufacturing is not going to be tenable if you're not making mobile chips. And what obviously they didn't. TSMC made all the mobile chips for everyone. And guess what happened? TSMC took over the manufacturing. Now, there's lots of other things that went into this, why intel stumbled and sort of things. But at a structural level, what happened was actually inevitable once intel missed mobile, unless they figured out a way to make mobile chips some other way, they didn't do that. What's interesting is what is the problem with that? It took so long to manifest. Part of mobile was you had an explosion in the cloud, because cloud and mobile actually go hand in hand. Intel made all those cloud chips. Intel stock had an incredible run from the time I wrote that article for the next eight to nine years. And I felt like kind of a moron because I'm like saying this company is screwed if they don't do what I say. They didn't do what I say, and their stock went to the moon. But the way it actually caught up to them has been in the past two to three years, where there's astronomical demand for AI chips, only TSMC can beat it. Intel's not in the game. They're trying to shift to a foundry model, but they're so far behind. Being a foundry is being a customer service business. It's not being an Intel. We tell you what to do or we tell our design teams how to change their chips to accommodate our manufacturing needs. It's totally different. And they needed a decade to learn how to do that. Had they changed in 2013, they would be ready today to capitalize on AI. And the counterexample here is Microsoft, Microsoft building Azure. Yes, it got them somewhat in the game with mobile and things like that, but AWS dominates in that space. But by virtue of building up Azure, they were prepared when the AI opportunity came along. And now Azure is sort of a big AI player. And you know, I wrote about these, these two examples a few weeks ago in the context of Apple. I think the concern for Apple isn't the short term. We're going to be using AI apps on our iPhones for quite a while. It's. Are they going to be prepared for what's next if they don't do some sort of, sort of reset and pivot here? Oh, sorry, I didn't answer your question about intel anyhow.

Yeah, I mean, managed decline, basically. Basically like just like, you know, just get as much cash flow out of this thing as you can while you wind down the business for Intel. Yeah, that's what I'm hearing.

Yeah.

It doesn't feel like, oh yeah, there's a silver bullet. Just split the business and they're good. Like, no, it's like it's not split.

The business is intel needs volume and they get volume from Intel.

Sure.

And the, and AMD split their business a decade ago and it was really, they had a very hard time for many years and they had very tense and difficult negotiations between the Global Foundry side and the AMD side. Global Foundries was AMD's manufacturing arm and it wasn't until really they got out of that and went to TSMC and then also completely rehauled their chip design business and all those, you know, that they, they got in the business. They were. And then also that intel stumbled. That certainly really helped them. Intel today. So if you split it up, like, who's bought, like Intel. Intel itself is fabbing some of its stuff with tsmc.

Yeah.

Who.

Who wants to buy Intel's Foundry services? The, the problem here is TSMC is located in a country called Taiwan, which, you know what it is today. But five years ago you'd be like, what, Thailand? Which by the way was probably much better for Taiwan security when Americans thought it was Thailand. But so there's a real national security element here. And it's just, it's a really tough situation because intel is a failed company at this point and they're. And the reason the failure is so total is because the aspects that drive their failure are the same things that drove their success. It was their arrogance. It was their sense that we're the best, that we will be just win through manufacturing might and performance and all those things. Work against becoming a good foundry. Work against being a customer service organization. Work against recognizing the fact that you're not going to make up for missing mobile through manufacturing which was their bet for years and years. You had to accept that you lost. And that's a tough place for companies. It's not like someone made a mistake fake. It's that what they did, what they did too well for too long.

It's who they were. They continued being who they were. Right?

That's right. But who else are you going to get if you want an alternative to tsmc? It's, it's. It's a very situation.

Last question and I think we'll be forced to have you make a slightly shorter answer unfortunately. I wish we had hours to keep talking. I wanted to get your updated thinking on Xai X the combined entity, the lot. 24 hours have been very chaotic. When the initial merger was announced it made sense for financial reasons for some of the different stakeholders. But I wasn't fully sold on this idea.

You're going to force me to come with takes that. I generally just avoid writing about Elon Musk companies for self sanity reasons I think. I mean I remember I wrote an article years ago about like when the Model Y was announced and I was talking about, you know, it's a Tesla. And this aspect, what Elon Musk is very incredible at, is sort of creating reality out of thin air. He's like the ultimate memer. And to create like it's the way things used to work backwards. I remember I analogized it to like protests. Like a critique of modern protest is they spin up very quickly because social media makes it very possible but there's no infrastructure under them so they don't amount to anything. Whereas you go back to like the civil rights era. There was years of groundwork that went into like the Million Man March on Washington D.C. and there was a structure in place that ultimately manifested in large crowds. But modern protests are the opposite. The largeness comes at the beginning and then it all falls Apart because there's nothing in place. And there's something that makes a challenge to write about anything Elon Musk related is you have all the social aspects, you have this bit about Tesla of creating reality. The stock was buttressed for years by these true believers, even though the financial parts didn't make sense. You famously had these wars with the short sellers and all that sort of thing. And it worked. It basically manifested a market for this Model Y and then the Model X. Not the Model X. What's the other one?

The three.

Model three, yeah, it was Model three.

Sorry.

When I wrote that article, Model three and Model Y had this massively successful and all the people that were true believers got very rich and congratulations to them. It's great. But it makes it almost impossible for someone, for what I do, who I want to look at structure and fundamentals. I can observe this effect happening, but you can't really say what's going to happen or the effects of it other than to say this is interesting. And so I wrote about that article and then the solar city thing came out and he's like bailing out like his brother in law or something and I'm like, I can't write about this. Like what am I going to say? Like, like there's. It just doesn't make sense. And so I think there's. To fast forward. Xai. Yeah, there's a theoretical piece here. I think actually XAI would be an incredible acquisition target for a lot of companies if it. It wasn't saddled with X.

So interesting enough, it feels like the end state is like Twitter getting spun out again.

Like that's my.

That's kind of like my. It just ends up going back to Twitter and it becomes the Bluebird.

Right? No one actually wants to like Twitter. Twitter. There's never been a company in the history of the world probably where the impact of a company is completely and utterly divorced from its financial realities. Like I think when Elon Musk bought it, and I assume that's continued through now, they'd have like one profitable quarter in their history. Like it's an unbelievably terrible business. And so I think it's probably weighing XAI down. There's a. Yes, I get the theory that Twitter data helps Xai.

Well, it helped yesterday.

You don't need to pay 43 million for Twitter to. Or 43 billion I should say, to get it.

So yeah, that was always my position too. I don't think it helped yesterday when, when Mecca Hitler emerged on the timeline. But Good luck.

Hopefully they sort it out.

I wish, I wish we had a lot more time here, but yeah, this is great.

Thank you so much for stopping by.

Yeah, no worries. I love what you guys are doing. I actually had the idea of doing a daily podcast ages ago. Classic example of ideas don't count. Execution does. And you guys, you guys did it. I think it's great.

Well, you're always welcome here.

You're always welcome. Thanks so much. Thank you. We'll talk to you soon. Bye. We will jump straight into our next guest, Scott.

I'll be right back.

Hopefully we haven't kept him waiting too long and he is still in the waiting room. We'll bring him into the studio really quickly. Let me tell you about Wander find your happy place book a wander with inspiring views, hotel grand amenities, dreamy beds, top tier cleaning and 247 concierge service. It's a vacation home, but better folks. And we will check, check in on Scott Belsky and see if he is available to catch up. How you doing, Scott? Sorry for keeping you waiting. Ben Thompson, he knows so much about history. He runs, he puts out three hours of podcasts every day. I should have expected.

Bump me, man. I mean, that's.

I just feel so bad. But I'm very excited to have you. Can you just give me a little update of what's going on in your world? I want to talk about the AI safety layers concept and then we can talk about some of the current stuff that's going on in AI. It feels like, I mean, you published this post, what, two, three weeks ago and it feels extremely relevant today, last week. So very excited to get the update from you. So kick us off. Yeah.

Gosh, where do we begin? Well, listen, in our ongoing segment here on implications of the technology that's happening that is happening faster and faster and faster. A few things top of mind. You know, we can start, we can certainly start with AI safety layers. I think it's fascinating how much discussion there is of the dangers and the perils of AI without recognizing how it can operate as a layer to protect us. If you get some call from someone who proclaims to be your grandmother asking for money, that's clearly something that AI on the device, some form of local model can detect, you know, given it's all happening on that device. And warn you, this isn't your grandmother. When it comes down to all sorts of the creative and crazy scam, phishing email type things that we get all the time, that's a perfect use case for AI. Of course, and telling us that we need to be wary. But also, I mean, what about being polarized by algorithms and detecting an algorithm changing based on your engagement. Engagement and AI sort of saying, hey Scott, you're getting on the fringe here. Watch out, you're now in this small 10% of society that now is going down this rabbit hole of some conspiracy theory. I just think there are so many use cases of AI as a safety layer that the device needs to unlock. And of course that means the operating systems need to figure this out.

So I think that when most people talk about AI safety or safety layers or what you just described, solving the problems that will inevitably come from any technology, they look at it through a technological lens. They see, you know, well, let's do more reinforcement learning. Let's align the model.

There's a fixation at the model layer for sure. Like we need to solve it.

And yeah, I look at it almost entirely from an economic lens and I just think about it as if the market cap of the company that's selling you the skinner box is bigger than the company that's, you know, helping you get healthy. If the sugar company is bigger than the health food company, you're gonna be fat. And if the health food company gets bigger, then you're gonna be healthy. And so I think about it as like the doom scrolling. We have screen time apps. They're small, they don't monetize as well as doom scrolling unfortunately. So there's some like economic considerations there. But at the same time I come back to the scamming angle and I see this as like, you know, if, if the economic weight behind the good guys is bigger than the economic weight behind the bad guys, you get the good outcome. And that's why I'm not particularly worried about like super doom scenarios because I think that, you know, generally governments and people will align with like, hey, let's not get paperclipped, so let's build more systems to be safe in general. And then the bad guys, yeah, they might go try and build some really bad weapon, but they will be completely outnumbered. The question is like on the margin when we get into these pockets of the skinner boxes, the doom scrolling where the economic weight looks. So do you think about it in that same lens? And then the question is what business models can actually support this? Are we talking I need to have a subscription for a clue lead like app that looking at everything I'm doing and then acting as that layer on top, how can we actually implement this? Or is this just like we're hoping that Apple runs a great ad campaign around it and it becomes an Apple feature that they hold up at every chance they can.

Well, I mean, first of all, I think that the operating systems of our life are the ultimate interface layers. For many of us it's either Android or iOS, but at work it's many other companies that are operating systems at work. But those operating systems are trying to make us loyal. They're going to do so through remembering us. You know, personalization effects are the new network effects, I like to say. And I would imagine that protecting you from what's going to be a very comprehensive and very sophisticated set of social engineering and other sorts of long form scams. I mean, you think about the most effective scams that are out there is when you know, you really have this like very long experience or exposure to some entity to the point where you trust it and then suddenly it gets your information and then it's too late. And so that is a perfect use case for AI on the device to kind of monitor over time, compare that data with any other scams that are reported. So in terms of the economic incentive, I mean, goodness, I feel like consumers will have high willingness to pay for that if they don't get it free with their operating system.

Yeah, I mean, I think you can already imagine the UI of you pick up a phone call and Apple, you can think of the traditional layout of the hang up button, the hold button, et cetera. And then there's just a, you should have a little bit of a tag there that says AI voice detected or something to that effect to just, just. I'm perfectly happy with talking with AI, you know, a model effectively on the other end. But I'd like to note everyone should sort of know that it's a model. And I think we're in this weird period right now where people all the time are starting to talk with AI and not even fully realizing that it's a human on the other end.

There's some ways that there's the contra credentials movement, right, which I was involved with back in the days at Adobe, which is an effort to have models insert cryptographic metadata into anything that's generated, including live generation, like you know, live live audio that can be detected on the client. So there's some ways of going about this. But in terms of, you know, your point about the economic model is interesting. You know, my immediate, my thoughts immediately went to alarm systems. You know, we all pay for these ring alarm systems, like all these alarm systems for our home that sometimes cost 60, $120 a month, you know, with monitoring and window motion detectors and everything else. But we're not really paying for an alarm system for our like, you know, for our devices in this new modern world where we're going. And maybe there is a market for an AI safety layer as a service.

It's like new antivirus or something. We're going to have magnetic viruses and stuff. But it needs to screen record everything. Yeah. It needs to be at the operating system level. How are you thinking?

Yeah, for mind virus detection, how are.

You thinking about the evolution of those like the mind viruses that come from just the accidental interaction with AI? I mean people are, there's such a wide swath. When I talked to Jordi and we were having dinner last night with David Senra and we were talking about how we use AI and we're like, yeah, probably 30 minutes a day in ChatGPT, like it's a lot. But these interactions are. Summarize this post. Do this research, pull this things. It's like talking to a computer. I'm not saying, saying hey, how is your life? I never have that interaction, but there are a lot of people that do. And so what are you seeing? What anecdotes have you pulled from? How do you think that evolves? Are there any risks? Walk me through. Kind of the way humans are interacting with just language models broadly.

That's interesting. I mean, I think, you know, one of the topics that is on my mind a lot lately is consumer AI. And I'm not just talking ChatGPT, which is obviously a consumer product for many of us. Us. But you know, it's interesting, I was at a tech conference recently where, where all the trends that you know, are, are popular now were being discussed. And I left asking myself, what's the one thing that no one talked about? And the one thing no one talked about were new consumer AI era social networks and new when mobile came around, there were a whole new variety of social networks. Like every time there's a platform shift, a lot of consumer mainstream applications or social networks, that sort of stuff is reimagined legend. Right. And so the question is why is why, why is that not happening now? And, and the whole saying in consumer investing is always around novelty preceding utility. And so I'm trying to keep an eye out now for examples of, of consumer AI. I mean there's this company called Tollen, which is sort of like a pet alien that you, you, you start having conversations with and they're doing really well. I believe they Raised around from, you know, some, some of the top firms. You know, I've been playing with this idea, a few ideas with friends. You know, one of a simulation representing our digital twins. So could you. Could you kind of train a sort of an AI digital twin of you based on all your experiences and ChatGPT or any other sources of data and then deploy that in a simulation with mine and others and we could start to actually just watch them interact with each other and it's kind of, it plays with some fun ideas of plausible deniability, you know, oh my gosh, like, I'm so embarrassed. Like what my, what my simulated twin said to yours. These are the types of things that are, you know, wingman as a service. Like, I don't know, is there an AI wingman that, you know, helps us when we're flirting with people on social. On, you know, on dating platforms?

Yeah.

What I want to see and you're kind of getting at this is just like more weirdness. Right. It's easy to go build the neck or not easy, but you know, we were at YC and there's a lot of companies in the last batch building agentic infrastructure. It's like that stuff needs to be built. But I also at the next batch, I hope there's more people being like, yeah, a lot of people built all this infrastructure already. B2B basically B2B SaaS. Why don't we just take a crack at some dating simulation where it's like you create a digital twin and you just throw it into the mix and it goes on a thousand speed dates with people in your city. Not even speed dates, but simulations of dates with people in your city.

Yeah, we've talked about this before. This idea of like you have a whole bunch of people that are talking to a romantic AI partner and that feels super dystopian. But if, if person, if Steve in, in Los Angeles is talking to the AI girlfriend and then Sarah in Boston is talking to an AI boyfriend and the two AIs realize on the back end that these people are super compatible because you have so many much data from them. It's just introduce the two humans and say, hey, you know, yeah, you have to pay us to introduce you. We're going to pay a finder's fee and collect your LTV on this app for the next 10 years because you guys are going to probably live happily ever after. And. And that's kind of like the white pill scenario that I hope happens. And I hope the dating app.

AI companion though.

Yeah, yeah, basically, yeah. But the AI, it's the her scenario.

You're still together, but your AI versions have broken up.

Like, are you.

What happens then?

Well, then you get a warning or it contacts like a divorce lawyer or something. For who takes a fee on that?

Who knows? I think there's a lot of fun stuff to explore here. And you know, one of the other random ideas I had was, I, I called it Peanut Gallery. And the idea was that, you know, the dirty little secret about why we go back to products like Instagram and others, oftentimes the traffic goes up after we have posted content because we want to see who else else saw our content.

Oh, interesting.

So playing off that, off that idea, you know, imagine a social platform called Peanut Gallery where you post your own content, but no humans are allowed to comment on it. It's all these like Personas that are like, you know, tightly, tightly defined Personas that are commenting and arguing with each other and discussing. And you go back to see like how this AI is engaging with what you posted and maybe that becomes the voyeurism of seeing how other people's, you know, contents performing. I mean, these are the fun, crazy things that must be explored to find, you know, this edge that will become the center of social.

Yeah, I've seen two things that are somewhat in that realm. One is just general YouTube thumbnail A, B, testing services where you upload your thumbnail and it tries to predict based on all the data it has, what the click through rate will be and then you can upload.2 and it'll say, hey, you should probably go with this one. And then the other, I saw, I think, Justine Moore at Andreessen posting some sort of app that you open your camera to the front facing view and it gives you the sensation of live streaming with like hearts and comments and stuff. And it's all fake, but it's very odd.

But I don't know, it feels inevitable that in many ways bots are a feature. It feels like bots are a feature of X now, right? They have not been eradicated. They're still here. They're maybe hidden under some.

I mean, that's the story of Reddit, right? The early Reddit days were, you know, it was all the Reddit founders posting to seed this thing. So if you think about a social network that needs to onboard you, there was that original Facebook thing where like, if you could get 50 friends, they'd keep you on the platform forever. You know, if you show up and there's like a couple bots that are just like, hey, good job, job, you know, hey, keep posting, stick with it, make some real friends. But we're here for you if you need a little encouragement, a little dopamine. I mean, on that note, the war between Meta and OpenAI in the talent race and all the trade deals has been front page news for the last couple weeks. Jordy's been saying that the product that Meta might wind up going after is less like a direct chatgpt knowledge engine and app that feels more competitive at Google and it might actually be something more like companionship and chat since that.

That feels like the real threat of. If there was an app outside of TikTok that was going to take user minutes from these sort of like entertainment social minutes from, from the Meta ecosystem, it would, it would be these sort of AI companionship which function as, as entertainment. This sort of social experience which is Meta at its core is effectively a social entertainment company.

Yeah.

And you know, you think about all the rules of successful consumer products. They make us feel good about ourselves. You know, they, they are sort of social lubricants and that they help us get and get connected to others in ways that we may not be able to do and be comfortable with in the physical world. And you kind of go through all the list of things and you realize like AI, there's an opportunity to, to really radically, you know, attack those vectors and make people have a really fun, engaging entertainment experience or a social experience. So it's not a surprise that Meta is going to innovate in that space. You know, I do also kind of wonder when, I remember when we all remember when Facebook acquired Instagram and then of course When Facebook acquired WhatsApp, you know, they were acquiring network effects in essence, right around messaging and images. And I wonder now, you know, now it's like it's a talent war. I mean, maybe AI is less about. AI is not really a network effect per se. It's more of like a talent driven differentiation. I wonder if that's also, you know, helping us understand the strategy of, you know, buying up all these different companies and people.

But yeah, I think the framing that I've been thinking about is these are basically like unauthorized Aqua hires to some degree where you're basically saying, yeah, these 10, you know, if a company is doing an acqui hire in general, there's like, we know this group of people is good at this thing and we want to do this thing and let's bring them over here. And so the premium on talent that we've seen in the last couple weeks could just ultimately be that it's looked at as a you're buying a team, which is VAL is more valuable than the individual parts they just happen to all get.

Been the chatter around Alex wang and Scale AI people haven't been saying, oh well, Scale AI is going to be, you know, this juggernaut in 30 years. But Alex Wang is a generational talent. He'll be around in 30 years. And so the nature of what scale does might change as we get to more data driven or like just purely AI generated data and reinforcement learning with verifiable rewards. And scale AI has been through a couple different things with self driving cars and then RLHF for light language models. And that that business, it's not the same as Instagram where it's like, okay, there's a network here and so there's like this asset value in this. But it's yes, more, much more talent driven. And so that's why you see all these people coming together. But it's fascinating. It is interesting to see if Meta is focused more on just let's make llama great so we can use the best, best in class AI effectively for free all over our products. Or if they're trying to aim for something that's like an entirely new experience that will be vended to their billions of customers. Probably both, honestly.

Why not?

Yeah. And make ads more efficient while they're at it.

Yeah, for sure. I mean that's the crazy thing about this is like $100 million doesn't take that much to generate $100 million if you make the ads 0.1% more efficient. So it's all economically rational, but we just haven't seen it in tech yet. And this. And that's why these big numbers feel like, oh, we got to talk about.

This a little bit of a tangent. But if you, have you thought about how. How like LLMs now are immediately and. And I'm assuming pretty aggressively shaping actual human communication. Like right now we're in this period of M Dash. Gotcha. You wrote that, you wrote that. You know, with chat, GPT and people that love the EM dash probably very disappointed. But at the same time it's not like you see that people calling out the EM Dash other places on the Internet outside of basically Teapot and I just wonder. We're in this dynamic now where we have the most prolific, prolific writers throughout history have shaped communication and now we have LLMs which are effectively the most prolific writers in history, producing more written word than Any one human could do in a lifetime in minutes, right? Yeah. And it just feels like we're potentially in this interesting flywheel that's just going to keep spinning.

A couple thoughts. First, I feel that LLMs are going to start fine tuning more towards how we want them to talk to us. So if you want your LLM to be straight to the point, no BS and all lowercase and short sentences like, that's what your experience of any information retrieval and conversation will be. And that might be different from mine. So I do think they'll all become more personalized for us in these like dramatic ways. I also though wonder just like when music becomes generic and you know, then some, some, some band or some star, like just does something entirely new and creates this new genre. I mean similarly with writing like, well, what will human writing be like as a result of LLMs in 5 to 10 years from now when you pick up a novel that actually captivates your attention and keeps you engaged? You know, what sort of writing will be necessary to do that in this age where yeah, your LLM can spit out poetry or write a short novelette upon command. So it's fascinating. I mean, technology's always had this impact on us and culture. It's just never been easy to chronicle because it's always happened over such long periods of time and it feels like those windows of culture change are happening more quickly. And so it's something I'm looking at as well. It's interesting question.

I'm generally still long tool. This is a tool. Creativity is still undervalued or it's not going away. And I keep coming back to the idea that there should be nothing easier for an LLM than to write a Great tweet. It's 280 characters. It doesn't need to really maintain some long context to get it. And yet we haven't really seen anyone break out with an account that people are following and entertained by that's fully AI generated. And there's been some experiments, but usually it's like you're following it because even like that. Do you remember horse ebooks back in the day? I don't know if you remember this account, but it was like said to be just randomly algorithmically generated from these ebooks. But it turned out that there was actually a human writing it. And there's been a few examples of that where. Or the stuff that does go viral that's like AI generated is like, oh, it's hallucinations. And so the fascinating part about it is not the underlying product. It's the fact that it's generated by AI. Yeah.

It is interesting that we have this. This band, the Velvet Sundown, I think they're called. They have a million listeners on Spotify a month right now. That's the. That claims to be fully AI generated. And it's funny that we got that before. A prolific poster that is fully AI.

That has 100,000 followers and is popular.

Here's the thing. I mean, we talk about, of course, taste being more important than skill, and I think you're tuning into the fact that can LLMs output tweets that are compelling and therefore have taste. And I think one of the questions is taste, not just about each tweet, but also consistency of good judgment and great, you know, great content. It's just like they say, a brand is like, the hardest thing to build, the easiest thing to lose. I wonder if taste is a similar way. You know, if you have AI pumping out tweets in an account, but if 20% of them are like, you're like, wait, what? That wasn't clever. You know, do you just lose. Does that.

Does the.

Is the credibility of that account gone? So I. I think humans are good at, you know, humans with good taste are good at knowing, you know, yes and no. Yes and no. Like, what should and shouldn't be shared or. Or said or written more consistently. And I wonder if LLMs can do that.

It's also a memory. It's a context thing. To be a good poster, you need to really understand the fullness of the Zeitgeist and the current thing and all the different meta trends.

Yeah. And it feels like even the longer context windows are still losing focus because there's some sort of fundamental limitation of the transformer. We talked to Dwarkesh a little bit about this, and the continual learning breakthrough is maybe still a few years away, but certainly will be interesting to see how it develops. I'm optimistic. I'm still looking for that. I keep coming back to that idea of the Lisa doll match against AlphaGo, where AlphaGo dropped move 37. This very unconventional play, everyone thought it was, was a hallucination, a mistake, and it turned out to be kind of a genius new move. And I feel like we haven't had our Move 37 moment for LLMs yet, but it's probably coming at some point.

Well, I'll tell you, like, each time we have these conversations, the whole world will be different. I guess that's learning these days in terms of the pace of change, but.

That'S great as we accelerate. It goes from monthly to every couple weeks daily and then every hour that will be feeling the acceleration. But this has been fantastic. Great having you on. As always, looking forward to the next one.

Sounds good. Until next time.

We'll talk to you soon. Bye. Next up, we have Nathan Lambert coming in to talk about an American Deepsea project. But first, let me tell you about bezel. Go to getbezel.com, your bezel concierge is available now to source you any watch on the planet. Seriously, any watch. Go check them out. And I'm very excited to bring in Nathan and talk about deep seat Llama. How you doing, Nathan?

Boom.

Good to meet you.

What's going on?

Good.

Thanks so much for dealing this format. You guys got a loaded lineup today. I was like, wow, I got on the same day as Ben. Ben is like the motivation for why I started writing about AI. Somebody has to do this for AI because there's so much to talk about. But all he does now is AI anyways. So, yeah, he's a competitor.

He's the Ben Thompson for AI is definitely Ben Thompson.

But I mean, it is a little bit different. Plenty of there's so much different space in terms of whether you're going after the business models or the actual infrastructure or what you were writing about earlier with kind of the open source geopolitical angle. So take us through the recent piece, the thesis, and then I have a bunch of questions about both Deep Sea Llama and kind of how this could come together. We were talking to the CEO of Grok yesterday. He's obviously extremely long open source and it's very interesting to dig into a million different threads here. So just kick us off with an overview.

Thankfully, we were talking to the CEO of Grok with a Q.

With a Q.

Yes. Because at that very moment there was.

A different Grok hallucinating at scale.

Yeah, there should be more Grok news later if tweets are to be believed. But the American deep SEQ thing is largely a forcing function to make AI research ecosystem make the AI research ecosystem in the United States catch up. I think we were talking about niches and lanes and Ben Thompson, it's the biggest one. A lot of mine is on the research side and kind of understanding the emerging trends on research that are getting picked up by companies. One of the clearest ones that we do is I lead this with a couple other people. As we keep track of all the open models and data sets, a mixture of research and startups are releasing and there's been a huge shift in the last three to five months and pretty much everyone builds on Qin and there's a long tail of kind of business or geopolitical reasons. Some of them are sensitive and some of them are kind of obvious where American companies don't want to build on Chinese models and that's one thing. And then also America should just take pride in what has been a great research ecosystem and we want to have that and own it. Whole stack which is otherwise most of the leading AI research is going to start coming out of China. And I think so politically it should be an easy win. And in terms of cost to maintain the open ecosystem, it's so much less than what these companies are pouring into their AI models. So it's just kind of getting a bit of the tractor beam of AI onto this open source and open. It's like just building models that have all the data and code released so more people can start building on them.

We can go into the details from there. Deepseek versus Quinn. I feel like Deepseek had this like crazy viral moment, but now you're saying that Quen's been kind of on a, on a, you know, compounding growth for a while. What's the dynamic between those two of kinds companies and what's driving QEN's adoption over Deepsea?

Yeah, so this is a great example of one I started using and we'll loop it into Llama. Essentially Deepseek has these frontier class models that are extremely good and they drop the weights on hugging face and they have been switching to permissive licenses. These are models that anyone can pick up and use and dump into a product that they want to ship. A lot of startups use these things. We see all the clouds hosting them. That's one thing. Not a lot of people actually fine tune Deep Seq because it's huge. It's already so good. What are you going to get from this? And then what Quinn is doing is they're releasing honestly tens of models at different formats, both base models and post train and from size scales as small as like 500 million parameters up through these bigger moe models. So for a researcher it's pretty much or somebody trying to build a really niche product and something at the cutting edge. It's like Quinn will have the model at a certain size that you need in order to fine tune it or figure out if you can build a certain thing at a certain cost profile. And especially for researchers that have some sort of limited compute training and working on deep seq is super hard and we've seen this with llama 2 and llama 3 were much closer to this Qin approach when it was seen both in the data that we have and on the ground is like Llama was the open standard for research. I used to joke around that hugging face is just going to be rebranded Llama because you see Llama everywhere, especially around llama 3. And with llama 4, Meta started to go release drama aside, they've started going more towards their bespoke solutions and they're also releasing the models which has made this big opportunity for. With QIN3, which honestly earlier Qin models were already starting to fulfill this. But that's kind of been a big mass shift and attention shift in the last few months where.

So what do you expect out of Meta with, with the new talent acquisitions and it seems like a redoubling of the efforts on AI broadly super intelligence. But maybe, you know, the, the, the strategy of Llama could be shifting. Are they, the. Are they. I've often thought that, you know, right now with the dominance of Deepseek and Quinn internationally and kind of these like jump ball, half ally countries, frenemy countries, Mark Zuckerberg should be like a national champion and we should be pushing Lama at a national level all over the world. But what do you think's going to happen there?

Yeah, so there's two things mostly. I mean I'm going to gossip as anyone will on what will happen with llama. It's very 50 50. I think with the leadership they've brought in that there's less attention and value Durban behind the open thing. So Zuckerberg historically has been very pro open and if more of it is shifting to other people, they kind of loosen that vision. If other people are at the lead of leadership, that's what people are saying. They need more leadership to build this AI Org. A best case scenario is LLAMA invests more in AI and the national champion becomes even better and they just crush this. I don't think that's the outcome that I expect to happen. Which is, I'm saying there's a cheap off ramp if you take the COP packages for a couple of those researchers. That's the cost to get a whole research ecosystem built around a fully open US model where we have all this, the data is released and a nonprofit and stuff can handle data releases a bit better than a big tech company that has all these eyes on their back and then just have research happen on these things.

So what are you advocating for? Are you advocating for Nonprofit taxpayer funding. We've seen a nonprofit before and it turned into a for profit. How are we going to keep this in a for profit and then how are we actually mustering the will? Because yeah, it sounds like yeah, just put $100 million into a nonprofit. Like that's a lot of money.

This is where we get to the nitty gritty. I work at the Allen Institute for AI and AI too which historically is even more academic than OpenAI was. So I think culturally there's not that type of, of feeling. The AGI supervision that ILYA had on the scaling deep learning, that was kind of the thing that I think drove them from the start. They were like we need so much money. So AI too is set up, you can do digging, but it's so different in that culturally that it could never happen. So if leadership here tried to do that, the company would just implode going for a for profit because I mean most of the leadership has co appointments with professorships at UW and things like that. So it is already half embedded in the ecosystem. And then practically speaking moving AI talent around is so hard that it's like the government exfiltrating researchers to fund a open source government lab. Doing this is so hard that it's like you have to find the money or the partners to do this. Where there are people so sitting on the ground where I am or trying to train our next model, it's pre training now it's like we just need more compute. So if we double or triple or compute America will have X or like these open models will be just X percent better and it's, it seems tractable. It's just hard to get the right. It's a lot of politics to get these things in place.

Yeah, I mean I guess to, to dig in there. I'm wondering if like you know the, the initial like economic model for LLAMA was always in a little bit of debate. Is it a recruiting effort for Meta? Is it their desire to decouple and not be dependent on Gemini or OpenAI or anthropic and just save costs? There, there were a whole bunch of different, you know, economic motivations. But I'm wondering if like in the long term we don't see something like you know, a red hat Linux where it is a for profit company maintaining a non profit or an open source software package or even. I mean you can run Linux on Azure now and so is there a world where you just have every different piece of the stack whether it's a consumer app that people pay monthly for or an API that people pay on a per token basis or an open source model that you're paying for Red Hat style consulting services on top of all within one company. Like is there no hope that OpenAI's open source model or AWS or Microsoft open source, something that actually competes significantly with deepseek and Qin but is still within the typical corporate structure.

I think it'll come from the biggest motivators have to be Nvidia and amd. So the long tail of if Qin is going to keep doing this and then it's something like Huawei, they started working with Huawei this, like Huawei libraries, they want to support them. And then us researchers are starting to dig down into those levels because they want to understand how these models were trained. So those are the people that have the most direct exposure. It would be Nvidia and amd. It's cheap for them to do. They get the benefit of the researchers keep working on their hardware and software ecosystems. There are outlandish stories that you could tell about open source AI where that type of thing could emerge, but mostly they revolve technical breakthroughs that you can't plan on. If you could do weird model splicing where you train a bunch of moes and then you cut an moe out of one model because it's really good at healthcare and there's kind of this open marketplace for model parts and then that's all in the open and the person that kind of writes the software by which those pieces of models are combined and standards by which those happen, that could exist. So there's kind of wacky ideas, but I think that that's a lower probability outcome and it's just like let's get good big transformer models trained that anyone can download and poke around at and just get more people involved in AI research that we have complete control over.

Last question for me. What are you expecting out of OpenAI's open model?

Yeah, so I think, I think one of the core things about OpenAI culture is that they really like to deliver extremely cutting edge and good artifacts and research. So I expect it to be one model that fills a niche that they're either hearing from customers or the community that isn't quite filled. Whether it's an extremely super long context or low latency for agents or a certain size of reasoning model, it's going to be this type of thing where it's a certain niche and it works really well for it. Where it could be like a deep SEQ style release where it's just super strong model that people can plug into real world products and applications. But it's not going to be this Qin or Llama suite of models that researchers look at for all sorts of things. And OpenAI has been saying that they hear the license critiques of Llama and stuff and they're going to commit to the actual permissive license which are things like Apache or MIT that these Chinese orgs have started using again, which I think is a nice thing to kind of make all of that simpler to just you release a model, it doesn't have terms and conditions on it. Meta is not trying to say like your legal department has to talk to us or avoid these use cases. It's just get people using the model that your company released and take a.

Simpler approach that makes a lot of sense. Anything else Jordy?

That's it for now.

Thank you so much for stopping by. This is fantastic.

Thank you for working on all this.

Yeah, we will talk more soon. Looking forward to forward to the release.

Cheers Nathan.

Have a good bye. Up next we have richard from you.com Coming into the studio. Do we have any more ads? Go to 8sleep.com get a pod 55 year warranty, 30 night risk free trial.

Free returns, free shipping@8sleep.com I'm basically.

You're in a hole.

My household is, is in sleep shambles.

Well, let's bring in Richard, talk to him.

Putting up the fact that we're doing this on five hours of sleep consistently does it all.

How'd you sleep last night Richard?

How'd you sleep?

Good to meet you. Hey guys.

Nice to be here. I slept alright.

That's good.

You would have slept better on an eight sleep. So we'll work on that offline but Great.

I did buy it. I retired it. I think it's better if my body sets its own temperature.

Oh wow. Interesting. Would you mind kicking us off with an introduction on yourself and the company?

Happy to.

Yeah.

I'm Richard, did my PhD at Stanford. Brought neural networks into the field of natural language processing. Laid a lot of the groundwork for what now is ChatGPT. Was a professor also on the side at Stanford for a couple of years because no one was teaching neural nets like Transformers and so on to students back then and this was 2014 to 2018 but my main job was starting metamind started and made it very easy to train neural networks for other companies. We got acquired by Salesforce, became the chief scientist and after two years executive vice president running most of the AI Efforts starting the Einstein kind of suite of things and so on. Build out the research team there. In that research team we ended prompt engineering paper cited by the early GPT papers from OpenAI and others. And in 2020 I decided to start U.com to bring better answers to the world, to change. What I thought initially was search, but I think now I think it's something else. And also started AIX Ventures. It's a relatively small venture firm, about half a billion AUM that invests in early stage AI companies.

It's not that small. Half a billion AUM is pretty solid. Congratulations.

A humble 500 million of AUM.

Humble, yes. On you.com where is the business today? What are the biggest challenges? I feel like we've been hearing more and more about the data wars and how high are the walled gardens, how high are the walls and the beautiful gardens that we have all tended to with our Slack installations and our Google Drives. And this feels like the logical thing that yes, I own my data until I want to get it to you. Or literally you dot com.

That's right.

Actually, you know, as a startup founder, you have to remind yourself every crisis is an opportunity. And the opportunity here is actually that a lot of data is in silos and those companies don't want to give it out, but they do need to make it useful. And so one of the many things that we've learned over our like changes and focus deeper, deeper on enterprise is that doing good internal search is actually quite hard and, and quite useful. And so we're partnering with a lot of companies and do search over their entire archives of decades and also really up to date things for publishers and insurance companies like pretty gnarly, complex problems and combining that with web data, which also has its own complexities and a lot of, you know, like folks are in some ways trying to pay people in news, which makes a lot of sense, but also it potentially threatens the entire free open Internet. If you have to pay for everything you read or crawl, then only Google can really afford that and then you have an even bigger monopoly. So I do think we need to keep the web open and free for that. And so merging all of that together to make companies more productive is what.

We now focus on.

What's kind of the best practice in the modern enterprise these days? Is it like try and be really diligent about sucking data out of every platform you use into some sort of data lake or like snowflake installation and then dropping u.com on top? Or is it figuring out a way to actually deal with the sharp elbows of direct API integrations into the databases that are managed by the other companies that I'm purchasing SaaS from.

That is a great question. I wish there was a simple Silverboard, always do X and just have it all in Data Lake in one place. But the truth is it's kind of messy and usually there's some data that's just so large you don't want to have another copy somewhere else. And then there's some data where we have the whole Internet, we have an Internet index and you can't bring that into your virtual private cloud and so on. It's just too expensive for each company. But then in some cases it does make sense. If you want really deep understanding reasoning over complex, structured and unstructured data inside an enterprise, then you have to often copy it over and bring it into a new setup. So one of the big things we just announced actually is a big partnership with databricks where we are sitting on top of databricks and we can actually answer questions over data that is in databricks. And it's been very exciting.

Partnership already makes tons of sense.

They also enable all their LLMs to have web index apps.

Sure. Okay. Yeah, that makes a ton of sense. How are you feeling on acceleration deceleration? It feels like the vibes have shifted. Most recently we had Doorkesh Patel on the show on Monday. He's kind of pushed out his AGI timelines. Folks are talking about reinforcement learning, not scaling as fast as people thought it would. The problem of continual learning. Just if you take a step back and maybe put on more of your academics. Mchat, how are you feeling about the current state of AI? Obviously, even if the. There's also the take that like I don't know if you agree with this but like even if the models plateau, there's still so much enterprise value and so many problems to go solve. But I'll let you answer. Where do you stand?

Yeah, I'll try to keep it short.

Because I could talk about that for hours.

Please.

I think it's true that there are so many simple jobs that can actually be done already with the technology that's there. Assuming you have good data access and you had all the recent information and you know, the company context and all of that stuff. So there is already a lot of low hanging fruit. At the same time, it's actually quite exciting for the researcher in me that, you know, hasn't fully died yet as an entrepreneur and CEO for many years like that. It's time Again, for research, like in many ways, we've known that you need large neural nets with a lot of data on GPUs and highly paralyzable training. And you want the whole thing to be ideally end to end, trainable in some fashion. It's sort of been known ingredients for over a decade now. And indeed we've crossed thresholds by scaling all three data, compute and model size. We scaled those three things up and it worked better and better and better. And it created these emergent properties similar to a smaller brain of a monkey just not doing certain epic things, even though the brain kind of looks looks similar, that has neurons too. But then you cross a certain threshold, you get these emergent intelligent properties. And so what that means is now is the time again for actual research, not just engineering and scaling things up and throwing more data and better data edit and bigger GPUs and all of that. But to actually go back and say like, okay, what is true intelligence? How can we get to superintelligence? What does it mean for intelligence to increase exponentially for a certain amount of time? I think there are actually different dimensions of intelligence too that you have to look at separately. And some do have upper bounds. And some times these upper bounds are astronomically far away, like grounded in physics. And in other cases the bounds are not that hard, like classify every object on the planet in computer vision. It's actually not that hard in comparison to have all knowledge about the universe. And intelligence should have a lot of knowledge. And it'll take us a while to get to as much knowledge. And the bounds of how much knowledge you can collect are rooted in physics and the speed of light cones around all the sensors you can have. So there's basically a time again for research. And that's exciting.

So, yeah, it feels like we're kind of paradoxically in an AI bull market. Summer in the stripe dashboard, or in the ARR sense, like we've never been adding more ev, never been doing bigger contracts. Everything's good on the business side, but maybe we're kind of counterintuitively in a little bit of an AI winter. On the academic side, my question is if you agree with that or not, but also, do you think that with the AI researchers it feels like the top AI researchers are getting poached into meta and they're going into OpenAI. Do we think that the next transformers coming from from or the next major research breakthrough comes from a foundation lab or big tech company? Or is there a role for academia to step up and do Some kind of longer timeline, unbounded research to try and go explore. Even without even an economic model in mind.

I do think you cannot build another OpenAI by just building an LLM. The LLM was the one thing that worked out for OpenAI after they spent hundreds of years, hundreds of millions on robotic hands and dota, like computer games and reinforcement learning and all these other projects. And one of them actually worked. And so if you want to replicate that kind of success and do research again, which I think is that the time is now, it does make sense to have that kind of entity and it can, I think, be done. And so I do think academia has a role to play in that. Thanks to open source models, academia can be relevant again because they have access to them. They just couldn't have afforded it before top open source models were available. And I do think a lot of folks are chasing sort of the latest employees in the top labs like OpenAI, Anthropic and so on. But you can also go a step further and look at who's actually, who's trained those people, how did they learn how to do research? And then you get to folks like Chris Manning, who's One of my PhD advisors too, who just recently joined Aix, our venture fund, in a much larger capacity as a gp. And so those are the kinds of folks that I think we'll need to rely more on again. And many of those are also moving out of academia into kind of labs that pushed frontier research forward.

I have to ask, because it's so current, what's your thesis on what happened yesterday with grok, how you did. Do you have that big of a general, I don't know, alignment, Oopsie daisies in prod.

You know, I think when you ship very fast, these things are bound to happen, right? Like people can push them in the conversations into certain directions. You sample from the same model multiple times, you get different answers. And I think if you try to be sort of a like free speech maximalist, which on many levels makes sense.

But turns out there's a lot of.

Funky speech out there with no guardrails whatsoever, it will go into those very dark places.

Yeah.

What are you expecting? Since it's in 6ish hours, I believe, hopefully they're still announcing and launching Grok 4 tonight. What are you expecting out of Grok 4 in terms of. Maybe benchmarks aren't the right even way of thinking about it, but in terms.

Of progress, my hunch is it'll be more of everything, but nothing like wow, like binary, like A novel thing. Right. It'll be more multimodal and deal with better understanding of images and videos and maybe sound. It'll be larger memory, it'll be slightly better reasoning. It'll be probably, I mean we won't know for most of them, but more parameters and so on. But maybe not like completely novel research that has a capability that no one else has.

Sure, yeah, that makes sense. Last question and we'll let you go. What are you finding most exciting on the investing side? For me, $500 million fund. It feels like the foundation model labs, the big training runs, the multi billion dollar rounds should has kind of sailed on that front. So maybe the time is for application layer investing. But what are you seeing? What are you excited about?

Yeah, we've been actually very fortunate at AIX Ventures to not have voided some of these massive rounds. The way I describe that is that not every company that raises a ton of money in a very early stage is bound to fail at the same time. You basically combine a seed stage risk with a late stage return in many cases and that an expected value just doesn't work out very well. And so there are a handful of foundational companies like Hugging Face that we invested in at a seed round and Windserve.

Congratulations, those are great companies.

Yeah, these are all like companies invested in the seed round. Invest in perplexity and flow and whisper tolbit ambience like bunch of really amazing companies. And so I think there are only one or two dozen foundational model companies that the world needs and then there are thousands of application companies. So short answer is yes, you're right. I think you will see a lot more new applications. I also believe that all the stars are aligning for biology and hence medicine and hence health that have a major moment thanks to AI. Now software is faster than hardware and hardware is faster than wetware people and biology. Right. And so it takes longer, the cycles are longer, but you have enough data, you have the right compute and we can eventually simulate more and more of biology and then make it into not just oh, memorize what nature has kind of hackily evolved towards, but make it an engineering discipline. Think about how we can actually change a specific antibody and target a specific gene and like change our epigenetics and improve aging and cure cancer. All of these things I think are within our grasp and reach over the next few decades. And I think that will be a massive group of applications.

Amazing. Well, thank you so much for stopping by. This is a really great conversation. Yeah, we'll have you Back later.

I love it.

I'll be back on again soon.

Have a good one.

Cheers. Richard, thanks for joining.

Good chatting. Next up we have the founder of Moon Valley coming on the show talking about generative imagery. We're going to pull up that website. Very, very cool stuff. So welcome to the stream. Hopefully we can pull up this website because we have fully passed the Uncanny Valley. Don't you agree? I mean this. Are you, are you on the website? Can we pull up the website really quickly and show the video? So everything on your website, this is AI generated, is that correct?

That's right. There's some after effects stuff on top of it, but yeah, it's basically all AI Mary generated.

It's remarkable and I feel like it's under discussed. Anyway, please introduce yourself and the company because this is.

Yeah, absolutely. Thanks for having me. Great to meet you guys.

Good to meet you.

So I'm Naeem. I'm one of the founders of Moon Valley. At a very high level, we're a team of kind of a unique structure. A good chunk of our team are world renowned researchers in visual intelligence primarily. But our focus in a specific level is we're building the biggest and the most capable production grade generative video models. And on the flip side is we also have a large chunk of our company are filmmakers. So we have a movie studio in la. It's one of the oldest, most well preserved soundstages in the world. Some of the first Charlie Chaplin movies were shot there. And so it's like kind of a ground zero. And we have folks that have won Emmys that have been nominated for Oscars on the team. And so we've just kind of brought both worlds together to figure out how do you take this tech from being kind of interesting research and cool things that you can share on X and actually become things that sort of of push the boundaries of what we sort of, we think of it as like movies and stuff. But these are sort of limited abstractions, more of just like visual media broadly and kind of the artistry around it.

So how do you think about the trade off between training, new models, being a foundational model company, hiring researchers, huge training runs, and then the application layer, the distribution, actually working with filmmakers. That feels like like most companies have kind of split between one or the other. Are you doing both right now? How would you describe the shape of the business?

Yeah, it feels a little bit. Maybe it's like a bit of a post ChatGPT phenomenon. But I do think that increasingly foundational companies are having to think A lot more about the application layer. And I think that that's only going to continue to be the case. I think a foundational research which, and you kind of alluded to it in your chat with Richard, but there's an element of commoditization that's happening. There's an element of you'll get to. There's a point, and this applies to visual media as well, where the output of the model, you kind of hit this point of diminishing returns from a consumer perspective, from a user perspective. So there might be really interesting kind of research thing that's happening and you'll continue to invest in that, but to drive the same amount of like business value as like, you know, a GPT4 style leap, that requires kind of thinking about other areas. So. And the other piece for us is, I think it's different with things like LLMs, but with visual and video in particular. I think one of the issues is that like research labs and technology companies that have been in this space, they have been largely divorced from like the end practitioner in a lot of ways. And for LLMs that are such general technology, I think that makes sense. But in our case, we're building tooling that filmmakers will ultimately use, that creators will ultimately use. So we have to understand that inside and out. And that needs to help guide the research rather than the research happening somewhat in a vacuum and then kind of trickling down to the target user.

Yeah, a lot of the crazy technology vision of the future is kind of just like, like you're gonna, with one prompt, just be like, give make me a new Top Gun movie. And it'll just one shot. It clearly gonna be a while until we get there. Where are you actually seeing value or demand from Hollywood, from filmmakers? Because, you know, AI is so broad. It could mean just like pull a green screen key, better do some rotoscoping, do some camera stabilization. There's been AI tools in filmmaking for a long time. They're obviously ramping up, set extensions. There's so much that you could do in the 3D pipeline, the VFX pipeline and 2D pipeline. Where are you seeing actual adoption? Where are you excited for there to be adoption in the next year or the year after?

Yeah, for sure. I think, you know, it's a good point where, especially in video, I think more than other kind of fields, there has been this like, you know, when it first started, there was this sense of like, well, kind of like the holodeck, right? Like that's the world that we're going to move towards. And to an extent it is. I do think that there's kind of like a misunderstanding though of where the value of the end content comes from. And it's sort of like we're now at the place where you could relatively credibly write a book with an LLM. Like you could have ChatGPT, you know, publish literature. Problem is nobody's going to read that literature.

Right.

And like that's kind of the missing piece.

You know, people have done it. People have. And if you go on the Kindle store, apparently it's like swamped with AI.

It's like 90%.

Yeah.

But like. And every once in a while these things break out. But it's more of like a novelty. Like, oh, wow. Like somebody actually did this thing. Like, let me leaf through it. Wow. Yeah, it's, you know, they hit the periods and there's tons of M dashes.

I think it might just end up reflecting human creation where it's ultimately creativity, creative products or hits business where there's a lot of AI songs right now. But the art, only AI artist that I can think of is that the Velvet Sundown or whatever that's gotten popular in the last month. And so it's. Yeah, I just think it's like this ultra power law, potentially.

A lot of media properties also in art generally is also very story driven. Like the story behind it. Like, part of the reason why I like to go see a Tom Cruise movie is because I've heard the story that he's done doing the stunts.

Yeah, we know who he is.

We know the story behind the story. And. And that's what drives a lot of value in art is like, oh, this, this painter really spent years doing this thing and he cut off his ear. And so that this painting has a crazy story behind it. So it's valuable even if, like my kid could do it. It's like my LLM can do it, but. Yeah, your LLM didn't. Yeah.

But anyway, I think it's like in AI music, I think you're kind of starting to grapple with that a little bit where it's, you know, you can use a lot of these tools. I think that there's kind of lowest common denominator content. Like what you don't see as much anymore is blog spam. That was just like crazy in the 2010s, right. Nowadays just replaced with AI. Yeah, exactly. I think that with AI music it's like there's certain strands of top 40 kind of radio where it's already A very commoditized sort of form. That's what it does well. But. But I just don't see a world where a Transformer model replaces Kendrick Lamar. There's such a big gap there. So we think about it internally. It's the same way John Carmack calls it power tools. And that's largely the model we use, I think, in film as well. It's very acute because to your point, unlike other spaces, it's a continuation. A lot of the things that AI video enables. It's not novel. Like, you know, you'll hear studios that we talk to, they'll say, you know, a research company came to us and they said, hey, you can do all these new things with these video models. And they have to remind them that, no, we can do all of these things. Right? Like, what we're talking about here is potentially doing them in an easier, more flexible, more powerful way. But with vfx, like, there's nothing you can do today in terms of, like, the output that you're creating that you couldn't do with vfx. It's a workflow thing, right? Like, we're just making that process easier, that process more affordable and that kind of thing.

So it's SaaS.

Yeah, we look at it, we're selling SaaS.

That's what the market needs.

What about, you know, it's been interesting to see X is its own kind of universe in terms of AI content. What gets picked up, a lot of it ends up being stuff that. That's getting shared on TikTok or other platforms. And there's been this idea of like an AI content creator, which is like a new personality that is just being generated by a human that's creating, using a video or an image model to generate this person going about their life. And then there's the sort of the. What's considered the slop, like the Italian brain rot, all that stuff. What about, like, do you expect to see, like, an entirely new class of filmmakers in, like, you know, like, basically like net, new YouTube channels, things like that of people that are just, you know, could be a teenager or just somebody sitting in a room by themselves, focused on that storytelling, focused on basically creating. The Internet was beautiful because it lowered the cost of distribution to zero and mobile devices lowered the cost of content creation to zero or effectively zero. And now the cost of producing films is not going to go to zero, but may as well on a long enough time horizon. And so I'm curious when you think that moment will be where we start to See, kind of the velvet sundown equivalent of filmmaking.

Yeah, I would say that we're a lot closer than people think. Moon Valley's models, because we have clean models or models that have been trained on licensed data. They've been the first models that studio, those legal teams have really allowed them to use. And so that's been part of why when you heard about Sora like a year and a half ago, since then there hasn't actually been that much AI adoption in the industry. Now it's starting to pick up a little bit. I would say that the point where the technology is capable of doing that kind of thing, we've already reached and there's places, it's. There's pockets of the world where, especially like smaller film communities in different parts of the world where you're starting to see like real world productions, often people aren't necessarily aware of it, but very large parts of not just the pre and post production, but even the production process itself are being driven by these models. Now I think that there's like beyond, especially in this industry, beyond the technology, there's a lot of other barriers to adoption. Like you have to, It's a whole new, you know, it's a whole new set of tools that you have to figure out. It's a whole, you know, the adoption curve is very different. And of course, you know, for better or for worse, there's like, there's a big kind of dialogue around AI in movies and what that means and you know, how we feel about it. But to your point, like what we get excited about internally is there's this dialogue of like, you've got on one hand just like day to day people like myself that maybe, oh, now I'll be able to create a movie. On the other hand, you have the far end of. Well now studios will be able to make the same movies for much cheaper. And that seems to be where a lot of the focus is. To us, the area that we're the most excited about is that middle where you essentially have this band of millions of creative people in the world, like artists, people who have real taste and talent and ability, but they don't have necessarily the access and the infrastructure to do that. Right. And that's not necessarily like we have one of our alpha users is this. He's a filmmaker in Senegal and he's been a filmmaker for over a decade. His thing or his focus is on doing music videos for local artists. And it's this kind of funky, Afrobeat style, West African kind of flavor. And now he suddenly started making those music videos using generative AI and the production quality of these have soared. And he's had a number like he went from being just like a very obscure person in his local community to. He's had some videos that have gone up like 10 million views on YouTube now. And nobody has any idea. They just think, oh, this is just like a sick artist that I haven't heard before and cool visuals. So it's that middle layer. It's like the independent filmmakers who today, unless you're friends with one of the top five studios in the world, you have no capability of making a big budget production. Now you'll be able to do that, right? And that's not just, you know, obviously this individual is one example. But for instance, we have like somebody like Natasha Leon who we work really closely with. She's, you know, an industry insider. She's a, you know, one of the kind of top people in the industry today. But she's working on this new movie that's like, she's been leveraging AI to help do it because this has been something that she's wanted. This is a movie she's wanted to make for well over a decade, but, but she just couldn't. She talked to the major studios and it's like, hey, it's Gonna cost us $30 million to do this right? And we just can't, we can't do that now. It's like, well, if I can suddenly potentially do it for $15 million now, I can make this thing happen, right? And so there's this idea that you'll be able to do movies for cheaper, but really what we're seeing in the studio is a existing movies, you're now just doing more than you expected to do before. You're now having to compromise less like directors on saying, hey, I had a $75 million budget, now I'm going to do it for 50 million. They're saying, hey, with my $75 million and my team, I'm going to go and now do all the things that I couldn't do before unless I had $100 million budget. That's like one thing we're seeing. And then the flip side of that is you walk into any studio, for every one good production that's live, there's 10 that weren't green lit because they just couldn't get the budget right. Now suddenly you'll have a lot more of that. So that how, you know, I think that the way that this stuff is actually getting implemented, it's happening in a different way than I think, where there's been a lot of fear, and I think it's totally justifiable fear. But I do think that ultimately it's the artistry that wins out more than like budget requirements or budget constraints.

Yeah. I mean, the exciting thing from my point of view is if movie studios keep budgets relatively the same because there is this incredible demand for content, but then you can take $100 million budget and it can now go to 10 different films. You get 10 more shots on goal, it's 10 more teams, and maybe the underlying teams even can create better margins themselves. So very exciting. Yeah.

Yeah. This is awesome. Thank you so much for stopping by. Hope you have a great rest of your day.

Yeah. Come back on when you have these.

We'll talk to you soon.

Awesome.

Thanks for having me, guys.

Talk to you later.

And that is our show for today. Jordy, do you have any other breaking news you want to share?

Breaking news? Brandon, Jacoby, Toby.

Trade deal.

Well, I guess now's a good time as any for some personal news. After a wild chapter at X, I've officially wrapped up my time there. I'm extremely proud of the work we did and you'll see more of it soon. More to come on what's next. Brandon has been a dear friend for a long time and I'm excited for his next chapter.

Me too.

And I'm gonna miss being able to text him when I have bugs, but. Tyler, you're up next. Expect some bug reports, but yeah, fun show. I'm trying to think if there's anything else that we missed.

I don't think so. We hit all of our ads. Chamath was saying that Meta switches to Sonnet for coding instead of using Llama that they had fine tuned on Meta's own code base. Now they're just one everything with Sonnet. So very interesting. Since the change code suggestions are generally better, engineers can change back to Llama and occasionally do when the fine tuning makes a difference. Internally this is a big change given how big how heavily Meta has invested in the Llama project or product. This move officially acknowledges that Anthropics models are currently far ahead of Meta's own LLMs. Even when fine tuned. I suspect Meta will double down and try and make their next Llama versions more capable for coding. But until then it doesn't want to hold back its engineers. So very interesting that they're using Anthropic and just kind of letting it rip.

The rock is cooking. Last post to end it from Arvis Best. He says he's sharing a screenshot of Linda Yacorino saying, after two incredible years, I've decided to step down as CEO of X. Obviously has a much longer post which we cover covered earlier. And Elon just comments. Thank you for your contributions. Jarvis says lmao. Cold as dry ice. Anyways, at least they were cordial.

Yeah, at least they were cordial. Leave us 5 stars on Apple Podcasts and Spotify and stay tuned for our stream tomorrow. Can't wait and hope you're having a great summer.

Have a great evening.

Cheers.