TBPN Live - 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

Episode Date: July 9, 2025

(02:57) - Linda Yaccarino Steps Down as CEO of X (06:01) - Grok Spreads Antisemitic Rants on X (16:00) - Tariff Deadline Pushed to August (17:54) - F1's Red Bull Fires Christian Horner (26:54) - Cloudflare Locks Down AI Crawlers (30:07) - Timeline (57:51) - David Marcus, co-founder and CEO of Lightspark, has an extensive background in financial services and technology, including leadership roles at PayPal and Meta. He discusses his journey from founding companies in Europe to leading PayPal and Meta's messaging products, culminating in the creation of Lightspark to build modern payment infrastructure on Bitcoin. Marcus emphasizes the importance of an open, decentralized money network and introduces technologies like the Universal Money Address (UMA) and Spark, a new Bitcoin Layer 2 solution, to facilitate real-time, low-cost global transactions. (01:27:24) - Ben Thompson, founder of Stratechery, is a technology and media analyst known for his in-depth analysis of tech industry strategies and business models. In the conversation, he discusses his career trajectory, the evolution of his independent analysis platform, and the challenges faced by tech companies in adapting to new market dynamics. He also explores topics such as the impact of AI on the tech industry, the importance of maintaining independence in media analysis, and the strategic decisions of major tech companies. (02:07:17) - Scott Belsky is an entrepreneur, author, and investor, best known for founding Behance, an online platform for creative professionals, and serving as Adobe's Chief Strategy Officer and Executive Vice President of Design & Emerging Products. In the conversation, Belsky discusses the concept of AI safety layers, emphasizing how AI can act as a protective mechanism against scams and misinformation by detecting and alerting users to potential threats. He also explores the economic incentives behind AI development, suggesting that aligning these incentives with user safety can mitigate risks associated with AI technologies. (02:30:53) - Nathan Lambert is a machine learning researcher at the Allen Institute for AI, focusing on building and advocating for open language models. In the conversation, he discusses the competitive landscape between American and Chinese AI models, emphasizing the need for the U.S. to invest in open-source AI to maintain technological leadership. He also highlights the importance of transparency and accessibility in AI development to foster innovation and trust. (02:43:29) - Richard Socher, a prominent AI researcher and entrepreneur, is the founder and CEO of You.com, an AI-powered search engine, and managing partner at AIX Ventures. In the conversation, he discusses his journey from completing a Ph.D. at Stanford to founding MetaMind, which was acquired by Salesforce, where he served as Chief Scientist. He also explores the challenges of integrating AI into enterprise search, the current state of AI research, and the future of artificial general intelligence. (02:57:49) - Naeem Talukdar, co-founder and CEO of Moonvalley, leads a team combining AI researchers and filmmakers to develop advanced generative video models. He discusses the integration of AI into filmmaking, emphasizing the creation of tools that enhance, rather than replace, the creative process. Talukdar highlights the importance of ethical AI practices, noting that Moonvalley's models are trained exclusively on licensed data to ensure responsible use in the entertainment industry.

You're watching TBPN Today is Wednesday July 9th 2025. We are live from the TBPN 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. Yoccarino. 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 Wong, an absolute dog, and Diddy is on an absolute tear. They are the first company ever to hit a $4 trillion market cap. It's here for NVIDIA. Four, four. There we go.

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

Oh, seven. Okay, so they got a way to go. 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. Microsoft's down 16%. On June 27th, they were, Microsoft and Nvidia

were neck and neck. And then Jensen just ran away with it. And I have a feeling that he will be at the top spot 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 for treat 40 There we go. It looks good up there looks good 52 times price earnings ratio They're making 44 billion in revenue and can we do this funny to think about turn over? Do you want to do you want to own in video at 52? Yeah, or Tesla at 163 or meta at 29?

You know Zucks low there look at this so over the last year a little bit beaten up during the tariff run and then just Just a flesh wound nothing ever happens. It was all priced in. Always. Nvidia was correctly priced before the terror war, before the trade war. That's right. Fantastic. Well, we're working on our graphics here, so thank you for sticking with us. Anyway, in other news,

Linda Iaccarino 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 is overseen by Yakarino. X is expected to see ad revenue growth this year, so it seems like she did her job. She got advertisers back on board. There were tons of boycotts early on things yes she was somewhat surprising at the time because it felt like an interesting culture fit to win given

exes that Elon acquires it's this big rebellion yep and then she had a more traditional media yep 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 broadcaster. She really did it.

She studied telecom and then went on a generational run. Telecom, yeah, exactly. So she was ultimately the chairman of global advertising and partnerships at NBC Universal, and she unified linear and digital ad sales and launched Cross Platform One platform initiative. And then she went over the packs. 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, it's hard not to be impressed. And speaking of ads, 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 Save both, time is money, save both, go to ramp.com. Easy 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. Sheil 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 or the key of year coming in? A couple different things. One, the merger, it makes, you know, 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 error 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,

it was Buco Capital said, what's the saying? The Mecca Hitler that broke the camel's back or something like that because obviously, it's very possible that she had planned to leave the company 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 hard to really say

Yesterday grok went very off the rails erupted in anti-semitic mecha. You've seen some crazy Crashouts on the timeline. Yeah, I've seen one 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 XAI deleted the content and blamed an unauthorized modification. The repeated safety failure undermines the $10 billion startups promise

to police hate speech in real time. And so yeah, 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 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 advertisers, that's what she was brought in to do. It makes it much, much, much more difficult. 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 Grok

when it was going off the rails where clearly it had been updated to reference the event. And it said, somebody was like, Grock, what just happened? And why were you spewing anti-Semitic hate? And it goes, oh, that whole thing back in July? And people were like, Grock, it was 30 minutes ago. Can't sweep it under the rug yet. Yes, obviously, hopefully no one was seriously offended.

Obviously, it's just like the deranged rantings 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 very funny because clearly they had given it a set level of intelligence, so it wasn't making spelling mistakes.

It had a certain tone and was in this kind of snarky, grok tone, but then clearly got some 4chan data in there or something and was just going way too crazy. 4chan or just anonymous accounts on X. Totally, yeah, could've been filtered in. I mean, yeah, I saw a Rune posting about this saying basically it is such a challenge

to get a chatbot just to act like, you know, I am a bullet point producer. Centrist. Yeah, it's just 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. Never just get into a 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. 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, I don't think it was, oh, they were doing that too, so. That was rough. Of course, that was rough. This is a lot rougher because it was highly, it was socially charged. Totally.

So there was 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 you don't know if somebody kind of manipulated it or whatever But seeing these really hateful Comments like hard time line as hard post you just go see them quote tweeted Yeah, like you you didn't it wasn't like oh is this real and then the wild thing was was grok You you didn't it wasn't like oh is this real and then the wild thing was was grok

What was denying affiliation with the like grok in the grok app yes denying affiliation with the grok handle oh Yeah like non-authorized I got it I didn't have anything to do with that wasn't me And then Yeah, oh and then the, 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 and or it'd be like, hold up a sign that says help if you're, you know. And then it would generate that image. People are kind of 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? No, what is this? 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 in 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 like inverting something, and then you're training it to be like, you can't describe a hero without describing a villain. And so this was something that would happen with the Tay stuff from Microsoft early on. It would kind of collapse into the exact opposite

of what you wanted. And there was some blog post that called it 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 like 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. I didn't even this is him doing it That's what the narrative will be like in the in the end Yeah, one of the articles yesterday covering it was the screen grab of him saluting a crowd at DC 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 the desire of the AI researchers is to create Mecha Hitler, can it stay on that task? Because then you can get it to stay on Mecha 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 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 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, 8 p.m. I think the live stream is 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, 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's a bug, it can amplify effectively a bug, or an issue, an issue with's a bug it can amplify you know effectively a bug or an issue an Issue with the model it can affect 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 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, 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 product, with the model. But when every result is just immediately online and viral, it's very, very hard to be quickly responding. Anyway. Yeah, it does feel, you know, 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 I guess X I think ultimately will shrug it off and Elon has has pushed through worse worse Crises in the past this is this is the best summary post in my opinion from shocko Says imagine being on the anthropic risk team trying so, and then Elon just releases Hitler rock straight to prod.

It's just like, wow, yeah. You gotta be so upset. I mean, it's a good case study in misalignment, and I think people will, hopefully, hopefully the post-mortem on this will actually teach people about misalignment and what went into the data, what went into the post training

to result in the exact opposite of what you want. Not Mecca Churchill, which is what we're going for here. Anyway, in other news, Buco Capital bloke, I think 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 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, 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, August 1st,

he's moved it back to August 1st in last minute deal gambit, pressed by Treasury Secretary Scott Wesson. 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 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, we'll have to get Zack Kukoff back on the show to talk about that,

and also in Washington, Kevin Hasser, one of Trump's closest economic advisors, is emerging as a serious contender to be the next Fed chair. Hassert's rise threatens the other Kevin. This is the battle of the Kevins. 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. 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 share. Insiders say loyal advisor Kevin Hastert has vaulted ahead of long time 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. I'm sure. 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 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 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- The Wall Street Journal says F1's Red Bull fires long-term chief Christian Horton. Yeah, so they fired him unclear though,

if this was something, you know, if they're gonna end up rebuilding 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 predecessor's empty coffee cup sitting on his desk. Wow, the guy's just like, I'm out. I'm 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 the sports history and turn himself into one of F1's most recognizable figures. He oversaw eight drivers,

titled 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. Not bad. It is pretty incredible that he was able to become so dominant that he was hurting the sports 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.

The Versailles era was pretty boring. Yeah, it was just going to be one, two, Red Bull and that was it. And I because it was the first time the era was pretty boring. Yeah. Yeah. It was just going to be one to Red Bull. And that was it. 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 going to be drama? If I know if I have a strong feeling of who's going to win when I can kind of

wait till drives Just survive comes out or even the highlights things like that 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 Drivers' Championship. And Verstappen gets new tires and on the last lap there's like the safety car, it's like this crazy scenario and he wins and it's like contested. And I think 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 He's a midfielder and like the the lower ranked teams were like absolutely all 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, we're better than you. I'm pretty sure that's what happened. And so they just built up enough reputation,

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 people were like, wow, this could be the start of Lewis Hamilton versus Max Verstappen, every single race could be neck and neck.

And then it was just like Verstappen for like three seasons straight. It was rough. So he's been in other place by Laurent Mechies, the head of Red Bull's sister team, because 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 it 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 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, the CEO, doing to drive, like, the production of a high-performance car? Like, what decisions are they making? They're hiring the right mechanics and designers

and getting the right wind tunnel. It's so abstract to me. Like, it's as abstract as 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 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. Sure, sure, sure. And then it sort of leaks out. I remember one time there was a car, there was a F1 crash and they were worried about if they used a crane to lift the car up off the track, that people would take pictures of the underside,

see the design of the underside and know how they were creating downforce. Yeah, downforce, which is interesting. So there can be little proprietary tricks that you learn and that can make your car like an Advantage for like a year and then it leaks out. Yeah, it's not dissimilar to the ad 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, live viewership in the United States. So they got a million live viewers last year on their broadcast. But it's just 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. They already have streaming rights around MLB and Major League Soccer. So build out a and they did the F1 portfolio So you go into 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 Yeah, not I would love I would like 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 easy to understand. Anyone can watch that movie, have a good time. Then as soon as you finish watching F1 on Apple TV, you click over and be like, hey, we bought the Red Sea Drive to survive. Wanna watch the season and watch the docu-drama, the documentary, and then from there, it's like, hey, it's actually going live right now,

you wanna watch the real thing? And it should be like this funnel, in my opinion. Anyway, just to close out the investigations in 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 breod 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 time. That's where the original original formulation came from. We had 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 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 at 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's gemini scraper because it shares the same user agent that indexes the web for search. Blocking it would create our 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 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.

10 years ago for every two pages, Google scraped from publishers. They sent one visitor back. Today it takes 18 pages scraped to get one visitor. As you can imagine, that's terrible news for publishers, content marketers, or website owners open AI scrapes 1,500 pages for each visitor and Anthropic 60,000 pages scraped for one of their getting this information, but I noticed this a lot because

I'll go to open AI. 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. But personally. It's so much easier to type in a follow-up question if you have another question.

Exactly, yeah, almost, very rarely am I actually hitting the website. Say more about this one topic. And so that clearly will change the economics of the internet over time. And Matthew Prince from CloudFlare was saying that 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 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 gonna be subject to getting everything you write sucked into the 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. 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 to him. Very excited for that. 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 the I'm feeling lucky button talking about 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 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 Claude code users are seeing it much more as an agentic tool in the sense that 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 as the original one shot the problem, right? Whereas Apple hasn't really had that many pieces of those products and anything that they've built software that's yeah if we've had that if we see anything today you can have subpar UI but if you have a truly great product you can break through right even even open eyes

experience of like picking between different models still feels you know non-optimized and probably not the end state, but it hasn't 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 roadmaps.

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 Turnis is primed to be the next CEO of Apple when Tim Cook eventually retires. This is very exciting, very interesting.

I don't know that much about their chief hardware engineering, the hardware engineering chief John Turnis. 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 there's been this rumble of like, oh, 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 as existential as Google. And even though they're behind,

it feels like dealing with the trade war, dealing with tariffs, getting the exemptions there. it feels like Dealing with the trade war dealing with tariffs getting exempt. I've got a busy year feels like a bigger a bigger issue But at some point Tim Cook, you know 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 CEOs 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 74-ish million

because there's a lot of people that could run one of the best, basically, sell effectively at the end of the day, sell iPhones, right? And you know, I think 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 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 were gonna be built. Delivering on Steve's near term vision. Yeah, and the work of John Young too.

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, 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 Ternes is potentially taking over as CEO, it means 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 lining up

to take AI even more seriously and push further into services and push further into software. Yeah, no, to me it's it's exciting the bare signal would be if like the CMO was becoming the CEO and then it's like hey we've had peak iPhone we're done where it's just about selling as many of these as possible which in many ways which in many ways it did like that is the game on the field today yeah but yeah I think it 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 polished and well-run. They're getting impressions across things and they're positioning the products as premium impressions across things and 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 that they're doing are not particularly like moving the needle for them in a positive way. Like- I'm not saying their marketing has been great,

I'm just more so saying like the signal, like the difference of taking your most senior hardware engineer and saying, you're gonna 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 gonna take the top spot. Totally, totally.

In a while, in other words, speaking of hardware, OpenAI has, this is another scoop from Mark Gurman opening I has completed it's nearly six and a half billion all-stock deal to buy an AI device startup co-founded by Apple's former design chief Johnny Ive cementing the chat GPT makers push into the hardware market so this was a deal that obviously had been announced that was the intention to close here and I guess as of the last 24 hours or so, it is actually closed.

There were some more details here. So Johnny Ive is actually like on a contract where he will spend effectively like 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 he's, you know, and I think that can ultimately make sense for somebody in that creative, effectively the role of creative director. Anything to put another node on the corporate org chart for sure. Yep. So. 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. I yo right well That was that was just more on the act 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 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 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. It's duopoly. Duopoly. Yeah, you should love this. So this should be good.

Yeah. 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 opening I team. So I'm very very excited. This is a huge bet from opening I obviously was all stock. Yeah, we covered it initially

It's like, you know paying like two couple points to like get Johnny Hive on the founding team of this new hardware effort. But I, yeah, I can't wait to see what they build. Well, the next, whatever they build, they're gonna need to pay their sales tax and so they should get on Numeral. NumeralHQ.com. Spend less than five minutes per month

on sales tax compliance. Go to NumeralHQ.com. Spend less than five minutes per month on sales tax compliance. Go to numeralhq.com. Speaking of things that you sell online you need to pay sales tax on, Metta just is going deeper with Ray-Ban maker Eslil Luxotica. I cannot pronounce that first word, but people just call it Luxotica.

And so Metta 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 Center 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 he can come on the show and talk about it because it's a very fascinating founder. Very, very soon the founder has a crazy story Grew up and I think he grew up in an orphanage. Yep, and And it just what are they wasn't they didn't call him the pitbull they call them something else But yeah, he was an absolute savage. Yeah, apparently at one point he wanted to buy Oakley, yep, and the and this the founder CEO Oakley didn't want to sell and so the CEO of Luxottica acquired a 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 your cratering, you know my revenue. Let's do a deal so absolute dog and sell your cratering, you know, my revenue. Yeah, you're just going to tell me. Let's do a deal. Wow. So Absolute Dog and Shune will have center 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 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 Bands, they're saying, and now the Meta Oakleys, they're saying, you like the look of Ray Bands,

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 so it feels like, yeah. Well, so I think this is strategic. 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 those. Luxottica has, I think, Garrett Leight

and a bunch of other brands under it. So they're basically saying, through this, we can deliver. Luxottica has brands for every demo that Meta could possibly want as a $100 billion company. And so I think it's very smart. I think Apple, like you said, will probably take a drastically different approach in terms of standardizing around something, and that will say something.

But accessories like eyewear are 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 who wants a G Shock, it's like the G Shock, you say G Shock and you just immediately think like special operations guy or Jocko Willink listener. It's like a durable, rugged thing. You say Rolex, that's a different thing right and 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 I there's another post in

here I don't know if we have it here, but someone was talking about it. I'm trying to think of a new, the key thing is Apple's great at innovating at multiple layers, but generally it's very hard to try to deliver hits in two specific areas, like aesthetics and design, and then simultaneously in something that's basically a fashion product, and then simultaneously deliver the technology.

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 MetaWave errors. 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 gonna 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 headphones for hands-free phone calls or something.

Like if you can just become someone's daily solution the headphones for hands-free phone calls or something. If you can just become someone's daily solution for music, 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, nail their single use case. And so yeah, there's gonna 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 now. Like Google was talking about getting into this space. We saw some launches at I.O.

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 air pods take a camera like they could do something cool But they're like just much slower than then 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 or J.M. silhouette one

day and then I might want to I'm playing James Jack Marie ma okay but um 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 swapping and then obviously something's more important. 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 gotta be a better solution to that, but I don't know. It says what are this? Yeah, the bifocals. Yeah, where they can flip down. Well there's lens 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 adio

Custom relationship magic adio is the AI native CRM that builds scales and grows your company to the next level You can get started for free at adio. I am in Adio all day long. Love it. From the moment I wake up to the moment I go to bed. 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 to Williams told Mark Gurman the band is dissolving. Details here, what it means and what happens next. It's interesting because these personnel moves are so dramatic and yet Apple's such a juggernaut of a company that you don't see it show up in the stock price.

You don't see it in like, you know, if this was a startup, like investors would be panicking and there'd be an emergency board meeting, maybe there are, maybe the board's talking. Secondary prices would be gapping up on the news. You're gapping down. But it seems like they are going through, you know, 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 see. I think the biggest question keeps coming down to that salary question of, you know, if the market is gonna sit at $100 million for someone who's two levels, three levels down from the CEO Like what does that mean for the other? I don't think it's gonna 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 such as a total comp in 2024 good question I don't know 79 million 79 Hey like hey these guys it's like mark pick 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 perfect number. Just a little bit above every single.

Poor 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. It becomes more of like an implementation role, less research, less discovery of novel algorithms,

novel concepts, like maybe the salaries come down. But I don't know, Dworkash made a good point when he was saying like, just measure the value and maybe the answer is higher pay for tech CEOs. I don't know. That could be one way out. It could be a byproduct. But the main thing is that-

But I also think that if you think about- The inversion doesn't feel like the last. Meta spending billions to bring on a group of people that were previously at another company. Yeah, 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. Yeah, it's a lot different than You know this is the market that the durable market rate for Yeah, no, I agree. I, 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 Mag-7 CEO forever. The ratio will not hold. We might see big acquisition deals. We might see tech CEOs of the Mag-7, the Mag-7 CEO salaries go up. We might see the AI researchers' salaries go down.

But I would not expect in four years, or five years, that we're seeing, you know, Mark Zuckerberg's direct reports, direct reports making more than Andy Jassy and Sacha Nadella and Tim Cook. That would be surprising to me. Anyway, let me tell you about Fin.ai. The number one AI agent for customer service,

number one in performance benchmarks, number one in competitive bake-offs, number one ranking on G2, go check it out. The customer service agent of Anthropic. Oh yeah. That's how you know it's good. Wow, that is actually a pretty glowing endorsement for Anthropic, from Anthropic.

Anyway, Ben Horowitz has some news. He's out of Delaware. Andriessen 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 gotta dig into this or have somebody on to talk about. Yeah, Texas has been popular, at least for the Elon.

Yep. People in Texas. Yeah, they have a post here. 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 they have roots. So there's a post here. It used to be a no brainer. Start a company, incorporate 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 the court's reputation for unbiased expertise. This has introduced legal uncertainty into what was widely considered the gold standards of U.S. 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 in 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 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-Clerky, but if you were in YC, it was like set up at 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-esset investing industry leading yields and they're trusted by millions Joe Weisenthal had an interesting post. Yes, I'm here. Well, sorry Yeah, 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's 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 gonna 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-Corps 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. So I think it's probably like a lot of small companies.

And so we need to 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 gonna 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 incentives. If somebody's spinning up like a design consultancy, they're not worried about, oh, the Delaware court of chancery is gonna come after me when I try to do this reverse merger or this crazy stock compensation package. The benefit of being in Delaware was always

that there's so much case law there that you can just rely on. 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. If you fill out this paperwork or use this form, everyone will understand what's going on.

Yeah, so in 2023, there was 300,000 new formations, 220,000 LLCs and 60,000 C-Corp. So pretty meaningful amount of C-Corp on top of over two 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. Well, if you're trying to get the attention

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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, 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 in to bring 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 DM 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-, and that enables anyone to move money

like you send a simple text message or an email. And sadly, Janet Yellen, the morning of June 2021, pulled the plug on this. And so I left at the end of December 21. 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 stable coins and the genius act and the market structure bill, there's potentially this idea that it's the right time to build new stable coins and stable coin projects and just building crypto generally. But I'm interested to know,

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 stable coins are definitely booming right now 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 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 stable coins. 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 5 p.m., 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, but 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 had gaps where people have stepped up

and created different L1s 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 and too expensive to move so very secure the most neutral form of digital money ever created but slow expensive, expensive, not programmable. And Lightning was a first attempt to that. And we spent the last three years building on Lightning, making it better, making it enterprise grade. This is why Coinbase and many of their 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. 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 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 that's really critical because like we need to make Bitcoin the most efficient settlement layer in the world 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 in in some kind of counterintuitive way people always talk about bitcoins volatility. It's been like the least volatile really And it feels like there's a lot of other

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 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, 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 shit coin, like 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 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 I think that's why we're seeing such an amazing early adoption and so much traction with a wide variety of developers whether they're building payment apps, they're issuing stable coins, 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 like 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 there just like chopping down problem after problem after problem in the financial system? And I'm wondering if you've ever played that, you know, mental exercise, but more precisely, is, was there something structural where PayPal was not able to jump head first into crypto as fast as possible? If at the time everyone in the company had just been,

as soon as the 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, people was doing great still, but, um, where there was really no way for the structure of PayPal to play in the new, uh, 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, like the era of the Peter Thiel, Elon, Max Left-Chin,

PayPal was really the first really big push into consumer-facing fintech. I think of 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 over 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 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 trustlessness of Bitcoin. And I think it's very compelling for a lot of developers and a lot of people who want to build very successful companies because, again, 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 a way of developers building really great products on top of Bitcoin. And I think I think it's happening right now.

How do you guys solve the, you know, the immediate from from what you've said, obviously, you can have stable coins on top of the Bitcoin network, which solves one of the key issues with Bitcoin as a method of value transfer that also historically held it back is one, why do I wanna buy a coffee? Anybody that bought a coffee 10 years ago with Bitcoin or pizza or whatever it was, probably regrets it now. But how are you, how do transact, is it affect, how are these, how are you about how to how to how to transact?

Terrible. Is it effect? You know, how are these how are the let's say I'm transacting with stables on Spark? What what is the sort of like economic what is that I can't full economic exchange look like? How what are fees paid in? Is it is it paid in the stable or is it? Yeah, level. I'm so glad you asked this question because that's that that's one one of the killer selling point of Spark for stablecoins, which is if you issue a stablecoin on Ethereum

or any VM chain or any other chain, you have to pay gas fees for basically transaction fees in the assets that most people don't own, whether it's ETH or Sol or whatever it is. In the case of Spark, you actually pay when you move stablecoins 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 scale really work and And then you have the the beauty of the trustlessness of knowing that even if you're transacting with a stable coin You can always have a unilateral exit to Bitcoin L1 with your stable coin and no one can prevent you from getting your money out So it's the the best of trustlessness the lowest cost the most efficient and you don't have to complicate 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 custodied in that way? There's always this like

hard interface between something that's truly decentralized and then 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 the crypto community or the programmable money world. And so it feels like we're on this trajectory

of let's make this more programmable, but how close are we to something that's fully programmable? Well, I think here's the issue. So first of all, 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. Is it true that Circle can just freeze all USDC? Yeah sure, yeah of course. 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 like and it just doesn't work it doesn't work and so stable coins 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 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 in tension. 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 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? One part is 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 all kinds of different instruments attached to, to any other point in the world making basically money flow in a completely open unrestricted way 24-7 at a very low cost. Both of these things are basically built on top of Bitcoin and serve different types of constituents that basically extends the reach of the network. But these are the two core focuses.

And 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 turn on 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 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 retail every big retailer that they interact with to have some Native stable coin or or are the the issuers that we have today a classic job. There's too many standards We need one 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 you know it's very clear that like 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 know, you can't net settle trades on weekends or after hours, you can't move liquidity between institutions to, you know, 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 like what an American consumer would actually get from using a stable coin. 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 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 stable coin so you know I think this is a conversation worth having around like what is the consumer application using stable coins in the US that is actually solving a problem for the vast majority of Americans and I don't know what that is. Can you talk about open source and how that,

the current meta around open source in the crypto and in 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, people building in this industry are trying to make it anti-fragile. And one of the ways that, 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 Umah, 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 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 an ethos of the entire industry that we care deeply about. Can you break down a little bit more how Umah works? I think anybody that's played around with crypto a little bit may have had the experience at some point of like 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 we serve, we are benefiting financially from that, but it's an open network. The way it works is that an institution like Take New Bank, which is one of our early partners on UMA, which has over 100 million bank customers in Latin America.

They would assign you an address like dollar sign your name at New Bank. Your accounts is denominated in Brazilian Reis. Let's say I'm here in the US and I'm with a bank. My UMA is going to be dollar sign David at bank.com. I'm sending dollars to you in Brazil. And what happens in the backend is basically UMA is a pre transaction open messaging protocol so it enables me to go to

The new bank 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 rates that you're going to charge me for this transaction? Then I can present the 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 Brazilian Reais, deposited in the accounts. 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 like super cost efficient, real time 24-7 and open. In some cases, like Newbank, 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 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. 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 US 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, it's for a guy who's being 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 an 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 Sachs Bo Heinz, 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 next set of technologies that will reinvent and rewire the world's 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 of government that once that wanted to like 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 to lead with financial services infrastructure. So I can be more bullish of you of what's happening in DC right now around our industry. Is there anything that you're looking out for in the back half of this year? It's obviously, you know, we started strong with a meme coin out of the White House. We've got the new stable coin regulations passed.

Anything in the back half of the year that you're kind of looking at or anticipating? I think everyone's really anticipating market structure and having a market structure bill that will clarify the rules of the road for that entire industry. I think that's as important, in my opinion, as the stablecoin legislation that is going through now. Yeah.

That's great. Well, thank you so much for stopping by. This is fantastic. Thanks for having me. It's great to be on the show. Yeah, always welcome. Talk to you. Talk soon. Thank you.

And next up, we have Ben Thompson from Strutechery 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. Please feel honored. I am wearing shorts underneath. I wasn't there. You didn't have to tell us that.

People always ask if we wear shorts. We actually do wear the full suits. We've got to stand up to hit the gongs sometimes. There's a wide shot everyone's saying. I am the poser here. So I am happy to admit. There are definitely shorts on right now. It's a great sign of respect in our culture

to put on a suit for a TBPN appearance. And we're just so excited to talk to you. I've been lucky to read your work in my entire career. I think so many of the thoughts that I have are now, 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 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 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 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 What I started I had like it was 368 followers 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 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 is 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. 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 Stripecory 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 a hundred thousand dollars 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 as part of that, I wasn't going to go

through the rigmarole 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 going to 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 you know, friends on Wall Street is you know? No skin in the game XYZ. I think at this point. I'm large enough that my reputation is significant skin in the game Oh, but I do recognize the validity of that that critique Yeah

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? 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 and so I do need to be straightforward about that and so I 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 strategic kind of ended up being in this interesting place where I feel like I'm a little bit of like the Switzerland of tech and that no one pays anymore. If you're a CEO you pay the same amount as you know Joe will it on the street that that is paying it. I don't invest directly which I think made sense when I started because I didn't have any money has probably hurt me a lot over the years since then

But I don't like it 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 And you know, that's why I generally as a rule don't have VCs on to do the structure interviews And that's why I generally, as a rule, don't have VCs on to do the Shrekery 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

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. The talking your book challenge, we go through that a lot. Yeah. Trying to 12 VCs on a day. 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 piece so I can get the Talking Book Network in there. But Talking Book Production Network. Yeah, yeah, yeah. That's the 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 are 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. Like so when I started the Struckery 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 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 will still staying true to the idea that's checkery 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 acknowledgement 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 her 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 because we really, you know, love the,

and then suddenly they're sitting over there and you know, it's representing meaning, very meaningful amount of revenue. I mean, I fortunately, I think of a scale that I don't have that problem. That's good. There we go. But it's, 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 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 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 that 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 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, well, I think just to go back to, to, to the media observation 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 ton of money because they win most of the market and then some people make some and then there's a long tail that that

sort of don't make any at all but it's it's very it's interesting it's 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 what's interesting about AI is for 40 years you would have periods of time we'd have tech companies going to head 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 sort of slotting into unique slots. So you have Facebook is social, Google is search, Apple is devices, Microsoft is business or you know business applications, Amazon, e-commerce, etc. 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? 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 star 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 to get paid a lot of money.

In tech, it hasn't been that case. 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. They, you know, the scalability questions, you know, like 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, bare 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 that you're it's 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 anyone like the collective together getting ten researchers at the same time is they're getting 10 researchers at the same time is meaning, you know, is meaningfully more valuable than than than than just each individual researcher added up There's probably something to that, but I think Again, like what is actually different between what Google is trying to do what anthropics trying to do what open eyes trying to do And what met 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 wanna 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 a scarce resource that everyone's fighting over. And that's why you see this real shift in negotiating leverage 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 innovator's dilemma, you know, you had this back and forth where Sundar Pichai mentioned that he hadn't read the book. He 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 mind share 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 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 innovators 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. That's the answer. They were years ahead. They invented the transformer a

decade, 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's done better than I expected over the last two years. Uh, I, 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 or 12 years ago when

everyone's like vertical search, Google's done, all the, everyone's going to 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 has been throwing a hissy fit sort of ever since. And, and so that's what they're doing with search, right? And, and, and with search overviews and they have this new search labs or AI mode. They can sort of test stuff out, what's it scalable. Once 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, this has always actually kind of puzzled me, where I think they're responding fairly well even though this is 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 was I 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 the

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 things 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 and which Gershner by the way was was a proponent of but you know by that time the IBM people were back in charge and I was

thinking about the the context of Microsoft where Mike you business models are hard to change and disruption is ultimately about business models and culture is even harder to change but what can't really be change 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 Cy 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 the data feedback loops, 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 chat GPT 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 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 ChatGPD 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. The thing that's just undeniable is you can debate whether this is going to be the year of agents. It doesn't feel that way to me yet, 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 of the-

I bet Ken Riser would be talking about IBM today, did you? No, no, no, I wanna talk about Intel and kind of the history of some of your takeaways and what you think you've gotten right in the past, your perception of should they break up the foundry business, and what you think might be in the works with Liputon coming in there. Because I was listening to Dylan Patel talk about

his conversation with the new CEO, Liputon, 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, 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 Strzhekary, you're like a new band.

And why does everyone think a new band's first album is the best? Cause 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 mean, I'll let people decide if that applies to Czech or not. I won't be a sophomore slump, but yeah, but I had been on Intel. 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 they're gonna figure it out tomorrow and The 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 Pat galsinger his first time through at Intel Intel, you know had the CISC Gelsinger his first time through at Intel. Intel, you know, had the CISC, the way there's CISC versus RISC. It's like 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 risk type of, I don't know if you use architecture, but like for the processors. And Galsinger 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 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 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. 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 like 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 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 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 Ottolini turning down the iPhone contract is not true. Tony Fidel, I said that once and I got a call from Tony Fidel, actually this is when I had him on it for an interview. 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 increased 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 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 and 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 just 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 counter example 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 I wrote about 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 gonna 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, it's, I'm hearing the managed decline basically has a managed decline, basically, like just like, you know, just get as much cashflow out of this thing as you can while you wind down the business. For Intel?

Yeah, that's what I'm hearing. Yeah, I mean, 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 all bad. The problem with 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 ship 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 you split it up like who's bought like Intel's Intel itself is thabbing some of its stuff

with TSMC. Yeah. Who wants to buy Intel's Foundry services? The problem here is TSMC is located in a country called Taiwan, which you know what it is today, but five years ago it'd been like, what, Thailand? Which by the way, was probably much better for Taiwan's security when Americans thought it was Thailand. But, so there's a real national security element here.

And it's just a really tough situation, because Intel is a failed company at this point. 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 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 and that's a tough place for companies. It's not like someone made a mistake. It's that what they did, what they did too well for too long. Who they were. They continue being who they were. Right. Right. But who else are you going gonna get if you want an alternative to SMC? It's it's a very last 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 X AI X the combined entity the last 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 gonna force me to come up with takes that I generally just avoid right about Elon Musk companies for self sanity reasons, I think.. I mean 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 protests 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, you know, on Washington DC 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, there's nothing in place. And there's something that makes it 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 Model 3. It was Model 3, sorry, when I wrote that article. Model 3 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 wanna 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 bailing out his brother-in-law or something.

And I'm like, I can't write about this. What am I going to say? It just doesn't make sense. And so I think there's, to fast forward to 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 wasn't saddled with X. So interesting enough. Yeah, it feels like the end state is like Twitter getting spun out again like that that that's my

That's kind of like my my it just ends up going back to Twitter and and and it becomes the bluebird 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 an early divorce 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 X AI down there's a yes I get the theory that Twitter data helps X AI well it helps yesterday you don't need

to pay 43 million for Twitter to or for three billion I should say to get it so that was always my position too I don't think it helped yesterday when when Mecca Hitler emerged but I wish I wish we had a lot more time here, but Thank you so much for stopping by yeah, no worries. What would you guys are doing? I actually had the idea of doing a daily podcast age 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 will jump straight into our next guest Scott Belsky. 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 24-7 concierge service. It's a vacation home, but better, folks. And we will 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. Pump me, man. I mean, that's, you know. I'm sorry. No, 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 wanna 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 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, you know, that's clearly something that AI on the device, you know, 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. Um, when it comes down to, uh, all sorts of the, you know, creative, creative and crazy, uh, scam phishing, email type things that we get all the time, that's a perfect use case for AI, of course, you know, and telling us that we need to be, uh, to be wary, but also, I 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 and an AI sort of saying, hey, Scott, you're getting on the fringe here. Like, 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 new 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 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 if the sugar company is bigger than the health food company you're gonna be 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 doom scrolling we have screen time apps they're small they don't monetize as doom 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 paper clipped. 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 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 like a Cluelite like app that's 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, you know, 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.

And 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 gonna do so through remembering us, personalization effects are the new network effects, I like to say. And I would imagine that protecting you from what's, what's going to be a

very, you know, comprehensive and, and, and very sophisticated set of, of social engineering and other sorts of, you know, long, long form scams. I mean, you think about the most effective scams that are out there is when, you know, you really have this very long experience or exposure to some entity to the point where you trust it and then suddenly gets your information and then it's too late. And so that is a perfect use case for AI on the device to 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, in the, you can think of the traditional layout of like the hang up button, the hold button, et cetera. And then there's just a,

you should have a little bit of tag there that says like AI voice detected or something to that effect to 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 are some ways that there's the Contra Credentials movement, 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 live audio

that can be detected on the client. So there's some ways of going about this. But in terms of, your point about the economic model is interesting. My thoughts immediately went to alarm systems. We all pay for these ring alarm systems, like all these alarm systems for our home that sometimes cost 60, $120 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 moment of viruses and stuff. But it needs to screen record everything. Yeah, it needs to be at the operating system level. How are you thinking about the- Yeah, for mind virus detection. Yeah, yeah, 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 Jordy 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 chat GPT, 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, 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 chat GPT, which is obviously a consumer product for many of us. But, you know, it's interesting, I was at a tech conference recently, where, where all the trends that you know, 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 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 re-imagined, right? And so the question is, why is that not happening now? And then 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 consumer AI. I mean, there's this company called Tolan,

which is sort of like a pet alien that you start having conversations with and they're doing really well. I believe they've raised around from some of the top firms. I've been playing with this idea, a few ideas with friends, one of a simulation representing our digital twins. So could you kind of train sort of an AI digital twin of you based on all your experiences in 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 plays with Some fun ideas of plausible deniability, you know, oh my gosh, like I'm so embarrassed like what my what my simulated twins and viewers 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, the I'm what I want to see admit you're kind of getting at helps us when we're flirting with people on dating platforms. What I want to see, and you're kind of getting at this, is just more weirdness. Right? It's easy to go build the next. Not easy, but we were at YC, and there's a lot of companies in the last batch building agentic infrastructure.

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 have built all this infrastructure already b2b Yeah, basically b2b sass. Why don't we why don't we just like take a crack at like yes? I'm dating simulation where it's like you create a digital twin and you just like throw it into the mix and it goes on 1000 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 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 Steve 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 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 gonna pay a finder's fee and collect your LTV on this app for the next 10 years because you guys are gonna probably live happily ever after, and that's kind of like the white pill scenario that I hope happens, and I hope the dating app companies explore. But who knows?

Did you have to break up with the 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. Yeah, what happens then? Well then you get a warning or it contacts like a divorce lawyer or something for you,

takes a fee on that, who knows? I think there's a lot of fun stuff to explore here. And one of the other random ideas I had was, I called it Peanut Gallery. And the idea was that, 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 saw our content.

Oh, interesting. And so playing off that idea, 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 contents were forming. I mean, these are the fun, crazy things that must be explored to find 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 two and it'll say, hey you should probably go with this one. And then the other I saw, I think Justin 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. Yeah, I mean 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 Yeah, they're still here. They're maybe hidden under some I mean that's the story of reddit right? 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. You know, hey, keep job. 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 of weeks. Jordy's been saying that the product that Meta might wind up going after is less like a direct chat GPT knowledge engine app that feels more competitive at Google and it might actually be something more like companionship

and chat since that interaction. 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 the meta ecosystem, it would be these sort of AI companionship, which function as entertainment, this sort of social experience, which is meta at its core is effectively

a social entertainment company. Yeah, and you think about all the rules of successful consumer products. They make us feel good about ourselves. They are sort of social lubricants and that they help us 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 really radically attack those vectors And you kind of go through all the list of things and you realize like AI, there's an opportunity to really radically attack those vectors and make people have a really fun, engaging entertainment experience or a social experience. So it's not a surprise that Metta's gonna innovate in that space.

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, they were acquiring network effects in essence, right? Around messaging and images. And I wonder now, 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 acquihires to some degree, where you're basically saying, yeah, these 10, you know, if a company is doing an acquihire 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 big It's looked at as a you're buying a team which is valid is more valuable than the individual parts They just happen to all get chopped up individually. This has been the chatter around Alex Wang and Scale AI. People haven't been saying, oh, well, Scale AI is gonna be 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 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 business, it's not the same as Instagram, where it's like, okay, there's a network here and so there's this asset value in this, but it's, yes, much more talent-driven. And so that's why you see all these people coming together, but 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. Uh, it is interesting to see if, if Metta is focused more on just let's make llama great so we can use the 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 .1% more efficient, so it's all economically rational, but we just haven't seen it in tech yet.

And that's why these big numbers feel like, oh, we got to talk about this. A little bit of a tangent, but have you thought about how LLMs now are immediately, and I'm assuming pretty aggressively, shaping actual human communication? Right now we're in this period of M-Dash, gotcha. You wrote that with ChatGPT.

And people that love the M-Dash before are disappointed. But at the same time, it's not like you see that people calling out the M-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, like 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 were potentially in this Interesting fly like flywheel that's just gonna keep you know spinning No a couple thoughts me first. I feel that LLMs are gonna start

Fine tuning more towards how we want them to talk to us. Right. So if you want your LM to be straight to the point, no BS and all lower case 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 then some band or some star just does something entirely new and creates this new genre, similarly with writing, what will human writing be like as a result of LLMs in five to ten 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 LM can spit out poetry or write a, you know, a short novelette, you know, upon command. So it's fascinating. I mean, technology has 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 an interesting question. I'm generally still long tool. Like this is a tool, creativity is still undervalued or it's not going away. And I keep coming back to the idea that like, 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 e-books 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 e-books, 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 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 band, the Velvet Sundown, I think they're called. They have a million listeners on Spotify a month right now that claims to be fully AI generated and it's funny that we got that before a

prolific Poster. Yeah, that is fully AI like it has a hundred thousand followers and is like popular I mean we talk about of course like taste being more important than skill and I sure you're tuning into the fact that can LLMs like output tweets that are compelling and therefore have taste. And I think one of the questions is, is taste not just about each tweet, but also like 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 the, is the credibility of that account gone? So I think humans are good at 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 said or written more consistently. And I wonder if, I wonder if, uh, you know, LMS can do that. It's also a memory. It's a context thing You to be a good poster you you need to really Understand the fullness of the zeitgeist and we're in the current thing and and and all the meta trends and yeah Yeah, 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 door cash a little bit about this and the continual learning still losing focus because there's some sort of fundamental limitation of the transformer.

We talked to Dorkesh 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 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 like learning these days in terms of the pace of change. But that's great as, as we accelerated, it goes from monthly to every couple of weeks, weekly, daily, weekly, daily, and then, 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. Till next time. We'll talk to you soon. Bye. Uh, next up we have Nathan Lambert coming in to talk about an American Deep Seek 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 Seek Llama. How you doing, Nathan?

Boom. Good to meet you. What's going on? Good. Thanks for joining. Happy to be on 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. That's amazing. 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 awesome. The Ben Thompson for AI is definitely Ben Thompson.

But I mean, it is a little bit different in terms 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 DeepSeek, 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 yesterday because at that very moment

there was a different Grok. Yes, hallucinating and at scale. Yeah, there should be more Grok news later, tweets are going to be believed. But the American deep-seek thing is largely a forcing function to make the AI research ecosystem in the United States catch up. I think we were talking about niches and lanes,

and like 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. And 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 and make sure 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 Quinn.

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. That's one thing. Then also, America should just take pride in what has been a great research ecosystem. We want to have that and own it a 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. So we can go into the details from there.

DeepSeek versus Quinn, I feel like DeepSeek had this crazy viral moment, but now you're saying that Quinn's been kind of on a compounding growth for a while, what's the dynamic between those two companies and what's driving Quinn's adoption over DeepSeek? Yeah, so this is a great example of one I started using and we'll loop it into Lama. 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 DeepSeek because it's huge. It's already so good. Like, what are you going to get from this? And then what Quen is doing is they're releasing, honestly, tens of models at different formats, both base models and post-terrain and from size scales and small, it's like 500 million parameters, up through these bigger MOE models. So for researchers, 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, like training and working on DeepSeq is super hard. And we've seen this with LAMA 2 and LAMA 3, we're much closer to this QUEN approach, when it was seen both in the data that we have and on the ground, it's like LAMA was the open standard for research. I used to joke around that like hugging face, it's just going to be rebranded LAMA because

you see LAMA everywhere, especially around llama three. And with llama four meta started to go, like 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 Quen with Quen three, which honestly earlier Quen 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 the new talent acquisitions and it seems like a redoubling of the efforts on AI broadly, super intelligence, but maybe the strategy of Llama could be shifting.

I've often thought that 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 llama at a national level all over the world. But what do you think is going to happen there? Yeah, so there's two things. Mostly 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 driven 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. Like that's what people are saying, like they need more leadership to build this AI org. And so a best case scenario is Lama 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, like 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? You know, we've seen a nonprofit before and it turned into a for-profit. How are we going to keep this into for-profit? And then how are we actually mustering the will? Because yeah, it sounds like, yeah, just put $100 million into a nonprofit. That's a lot of money. That's it. This is where we get to the nitty-gritty.

Yeah. I work at the Allen Institute for AI and with AI2, which historically is even more academic than OpenAI was. So I think culturally there's not that type 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 AI2 is set up, it's like you can do digging, but it's so different in that culturally that it could never happen. So if the 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 like 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 it's sitting on the ground where I am or trying to train our next model. It gets pre-training now. It's like we just need more compute. So if we double or triple our compute, America will have x, or these open models will be just x% better.

And it's intractable. 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 dig in there, I'm wondering if the initial economic model for Lama was always in a little bit of debate, is it a recruiting effort for Metta? 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 economic motivations, but I'm wondering if in the long term, we don't see something like 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, you know, 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 Quinn, but is still within the typical corporate structure? I think it'll come from, the biggest motivators have to be Nvidia and AMD. The long tail of if Quen is going to keep doing this, and then it's something like Huawei, they start working with Huawei, this 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 cheaper 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 can tell about open source AI where that type of thing could emerge, but mostly they revolve technical breakthroughs that you can't plan on. Like 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 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 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, like 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-seek 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 Quen 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 that simpler. You release a model, it doesn't have terms and conditions on it. Meta's 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 was fantastic. Thank you for working on all this.

Yeah. We will talk to you soon. Looking forward to the release. Cheers, Nathan. Have a good one. Bye. Up next, we have Richard from U.com coming into the studio. Do we have any more ads? Go to 8sleep.com. Get a pod five five year warranty. 30 night risk free trial free returns free shipping at eight sleep.com basically you're in a hole. My household is is 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. Impressive. 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.

I can't complain. 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. Interesting. Would you mind kicking us off with an introduction on yourself and the company? 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. 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 chat.ubt.

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. This was 2014 to 2018. But my main job was starting MetaMind. Started to make 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 U.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, you know, yes, I own my data until I want to give it to you or literally you.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 inside those. 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 changes and focus deeper, deeper on enterprise is that doing good internal search is actually quite hard 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-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 potentially threatens the entire free, open internet. You know, 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 you.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 silver bullet.

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, like we have an internet index, right? 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 a very exciting partnership already. They also enable all their LLMs to have web index access. Oh, sure.

OK. Yeah, that makes 10 cents. How are you feeling on acceleration, deceleration? It feels like the vibes have shifted most recently. We had Dorkesh 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 academic hat, 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 model's 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 can talk about that for hours. Please. There's, 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 research and 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 hasn't fully died yet as an entrepreneur and CEO for many years. It's time again for research. In many ways, we've known that we 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 like a smaller brain of a monkey just not doing certain epic things even though the brain kinda looks similar that has neurons to but then you cross a certain threshold you get these emergent intelligent properties and so. 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 super intelligence? 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 sometimes 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, you know, 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, 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 open AI. Do we think that the next Transformers coming 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 like 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 opening eye by just building an LM. The LM was the one thing that worked out for opening after they spent hundreds of millions on robotic hands and on 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 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, like in a much larger capacity as a GP. And so those are the kinds of folks that I think will need to rely more on again. And many of those are also moving out of academia in into kind of labs that pushed frontier research forward. What I have to ask, because it's so current, what's your thesis on what happened yesterday with Grok?

How do you have that big of a general, I don't know, alignment in prod? You know, I think when you ship very fast, these things are bound to happen, right? 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. Makes sense. What are you expecting since it's in six-ish 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 round ship 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, like to avoid 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, you know, an expected value stage risk with a late stage return in many cases. And that, you know, 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, and Windsurf. Congratulations.

Those are great companies. Yeah, these are all like companies invested in this T round, invest in perplexity and flow and whisper, told that ambient's like a 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 in the 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. 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 to have you back later. I love this. I'll have you back on again soon. That's awesome. Have a good one. We'll talk to have to have you back later. I love this. Happy background again soon. Happy. Have a good one. Cheers, Richard. Thanks for joining.

Good, Chetan. Next up, we have the founder of Moon Valley coming on the show, talking about generative imagery. We're gonna pull up a website. Excited for this. Very, very cool stuff. So welcome to the stream. Hopefully we can pull up this website

because we've fully passed the uncanny valley. Don't you agree? I mean, 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 like after effect stuff on top of it, but yeah, it's basically all AI, Mary generated. It's remarkable. And I some like 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 in the company because this is yeah, absolutely Thanks for having me great to great to meet you guys So I'm Naeem. I'm one of the founders of Moon Valley You know 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 we have a movie studio in LA. It's it's one of the oldest, most well preserved sound stages 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, you know, 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 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, um, and, 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 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, you know, it feels a little bit maybe it's like a bit of a post-chat GPT phenomenon, but I do think that increasingly foundational companies quote-unquote are having to think a lot more about the application layer

and and I think that that's only going to continue to be the case like I think a layer. And I think that that's only going to continue to be the case. Like I think a foundational research, which, you know, and you kind of alluded to it in your chat with Richard, but like, there's an element of commoditization that's happening, right? 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 like 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 GPT-4 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 so such a general technology, I think

that makes sense. But in our case, you know, we're building tooling that filmmakers will ultimately use that like 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, you're going to with one prompt just be like, make me a new Top Gun movie and it'll just one shot it. Clearly going to be a while till we get there. Where are you actually seeing value or demand

from Hollywood, from filmmakers, because 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 it's a good point where, especially in video, I think more than other kind of fields, there has been this like, when it first started, there was a sense of like, well, you know, 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 content comes from. Um, 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 Chad GPT, you know, publish literature. The problem is nobody's going to read that literature. And like, that's the, that's kind of the missing piece. You know, I think people have done it. People have,

and if you go on the Kindle store, barely it's like swamped with AI. Yeah. But like, and every once in a while these things break out, but it's more of like a novelty. Like, oh, wow, somebody actually did this thing. Like, let me leaf through it. Wow, yeah, 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 only AI artists 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 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 doing the stunts. And even if, yeah, we know who he is. We know the story behind the story.

And that's what drives a lot of value in art is like, oh, this painter really spent years doing this thing and he then got caught off his ear. 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. But anyway, yeah. 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 like kind of lowest common denominator content, like what, you know, what you don't see as much anymore is like blog spam. That was just like crazy in the 2010s, right? Yeah, that's just replaced with AI. Yeah, exactly I think that with AI music it's like there's certain strands of like top 40 kind of radio

You know where it's like it's already a very commoditized, you know sort of form. That's what it does Well, but I I just don't see a world where a transformer model replaces, you know, Kendrick Lamar. Like that's, it's so, you know, there's such a big gap there. So we think about it like internally, it's the same way we, you know, like John Carmack calls it like power tools.

And that's largely the model we use. I think in film as well, it's very acute because to your point, like, unlike other spaces in film as well, it's very acute, because to your point, unlike other spaces, it's actually, it's a continuation. Like, a lot of the things that AI video enables, it's not novel. Like, you'll hear studios that we talk to, they'll say, 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? models, and they have to remind them that, no, we can do all of these things. Like what we're talking about here is potentially doing them in an easier, more flexible, more powerful way. But with VFX, there's nothing you

can do today in terms of the output that you're creating that you couldn't do with VFX. It's a workflow thing. We're just making that process easier, that process more affordable, and that kind of thing. So it's yeah, we look at it. We're selling we're selling SAS. 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 lot of it ends up being stuff that's getting shared on TikTok

or other platforms. And there's been this idea of 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 this sort of what's considered the slop, like the Italian brain rot, all that stuff.

What about, do you expect to see an entirely new class of filmmakers, in basically 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, you know, the internet was beautiful because it lowered the cost of distribution to zero and you know, mobile devices lowered the cost of content creation to zero or effectively zero and now the cost of producing films

is not gonna 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. So, you know, we, like, Moon Valley models, because we have clean models or models that have been trained on licensed data, there have been the first models that studio legal teams have really allowed them to use. That's been part of why when you heard about Sora 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 like the point where the technology is capable of doing that kind of thing, we've already reached and there's places, 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 here, right? 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. And that's not necessarily like, you know, we have one of our alpha users is this, he's a filmmaker in Senegal and like 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 Afro beat style, West African kind of flavor. And now he suddenly started making those music videos using generative AI. And like the production quality of these have soared. And he's had a number, like he went from being just like a very obscure, you know, 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 like I haven't heard before. And you know, 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, obviously this individual is one example, but for instance,

we have somebody like Natasha Lyonne who we work really closely with. She's an industry insider. She's one of the 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 she just couldn't. She talked to the major studios and it's like, hey, it's going to cost us 30 million dollars 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 dollars, now I can, you know, I can make this thing happen. Right. And so it's there's there's there's this like 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. Directors aren't 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 a hundred million dollar 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's like high level 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, you know, I think it's totally justifiable fear, but I do think that ultimately it's the artistry that wins out more than like, you know, budget requirements or budget constraints.

Yeah, and the, 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 a $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, this is awesome., you know, better margins themselves. So very exciting. 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 news. 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 wanna share with the team? Breaking news, Brandon Jacoby says, well, I guess now's a good time as any for some personal news after 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 dot dot dot Brandon has been a dear friend for a long time and I'm excited for his next chapter You do and I'm gonna miss being able to text him when I have bugs. But Tyler, you're up next. I 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 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-shotting 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 heavily Meta has invested in the Lama project or product. This move officially acknowledges that Anthropic's 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 Lama 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. Anyway.

Theropic is cooking. Last post to end it from at Jarvis Best, he says he's sharing a screenshot of Linda Iacarino saying, after two incredible years, I've decided to step down as CEO of X. Obviously, as a much longer post which we covered earlier and Elon just comments Thank you for your contributions Jarvis says Alamay Oh cold as dry ice

Anyways Corjul yeah, at least they were cordial leave us five stars on Apple podcasts in Spotify and stay tuned for our stream tomorrow Can't wait and hope you have a great summer. Have a great evening. Cheers