Subscribe
Share
Share
Embed
Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TBPN. Today is Wednesday, 07/09/2025. We are live from the TBPN UltraDome, the temple of technology.
Speaker 2:The fortress of finance.
Speaker 1:The capital of capital. We have a great show for you today, folks. There's ton of news. We have a ton of guests and we have a full stream. We're going all three hours today.
Speaker 1:We got We're gonna take you through the news, talk about Linda Iaccarino, 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 That's right. We first have to ring the size gong for Jensen Huang.
Speaker 2:That's
Speaker 1:An absolute dog. And Diddy is on an absolute tear. They are the first company ever to hit a $4,000,000,000,000 market cap. Hit it. Here for Nvidia.
Speaker 2:Four four.
Speaker 1:There we go. Congratulations everyone over at NVIDIA. What an what a fantastic run the company has been on.
Speaker 2:We so so Tyler Hodge Yes. Here says, first company to ever hit $4,000,000,000,000 market cap. Wow. My immediate reaction was the Dutch East India company Yeah. Actually achieved something in today's dollars that would have been north of 7,000,000,000,000.
Speaker 1:Oh, 7. Okay. So got a way
Speaker 2:to still has a way to go. There's a little debate on that. Right? It was a long time ago Yep. It's hard to put a value on a in a historical asset like that.
Speaker 2:But but still wildly impressive and not super surprising.
Speaker 1:Yep. And so Polymarket's not expecting anyone to come from behind this month. Well, you can see the gap on 16%.
Speaker 2:On June 27 Yep. They were Microsoft and Nvidia were neck and neck. Closing. And then Jensen just ran away with it. Ran away with And I have a feeling that he will be at the top spot of the end at the August as well.
Speaker 1:But if not, we will probably be facing a a massive correction. So let's pull up the full mag seven power rankings. Take a look at those four two four t. Looks good.
Speaker 2:It looks good up there.
Speaker 1:Looks good. 52 times pry price to earnings ratio. They're making 44,000,000,000 in revenue. And can we
Speaker 2:pull up NVIDIA's short term over the last year? You wanna own NVIDIA at 52 Yeah. Or Tesla at a 163?
Speaker 1:Or Meta at 29. You know, Zuck's low there. Look at this. So over the last year, little bit beaten up during the tariff run and then just Just scratch.
Speaker 2:It's Just a flesh wound.
Speaker 1:Nothing ever happens. It was all priced in. Always. NVIDIA was correctly priced before the tariff war, before the trade war.
Speaker 2:That's right.
Speaker 1:Fantastic. Well, we're working on our graphics here. So, thank you for sticking with us. Anyway, in other news, Linda Yaccarino has stepped down as the CEO of X. She's wrote, after two incredible years, I've I've decided to step down.
Speaker 1: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 Yaccarino. X is expected to see ad revenue growth this year. So she it seems like she did her job. She got advertisers back on board.
Speaker 1:There were little tons of boycotts early on. Things somewhat
Speaker 2:surprising at the time because it felt like an interesting culture fit given given X and Elon acquires it. It's this big rebellion. Yep. And then she had a more traditional media Yep. Advertising background.
Speaker 1:So she grew up in Long Island, daughter of police officer and civil servant, studied telecommunications at Penn State University, graduated 1985, built her career in media and advertising, was a Turner broadcaster
Speaker 2:She really did it. Universal. She studied telecom and then went on a generational run.
Speaker 1:In 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.
Speaker 2:Let's give it up for unifying linear and digital ad sales.
Speaker 1:I mean, we love ads.
Speaker 2:We love It's hard to do, but when it when when somebody does it, you know, it's it's hard not
Speaker 1:to do. And speaking of ads, should tell you about ramp.com. Save time and money.
Speaker 2:Save both.
Speaker 1:Save both. Time is money. Save both. Go to ramp.com. Easy to use corporate cards, bill payments, accounting, and a whole lot more.
Speaker 2:And a whole lot more.
Speaker 1:All in one place. So the the reaction's been pretty positive. Sheel 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.
Speaker 2:I mean the timing the timing here is either totally random or totally predictable, right?
Speaker 1:Based on the the merger
Speaker 2:or A couple different things. One, the merger. Yep. It makes it, you know, now that you have this unified company. It it's clear that that x AI as a 100 ish billion dollar company needs to really deliver on the AI side.
Speaker 2:And in many ways, the the social media app revenue Yep. Will be a rounding error. Yep. And she's like an an ad executive Yep. Ad media executive.
Speaker 2:And then the other thing was yesterday, it could have been I saw somebody else in the chat saying that the the it was Buco Capital said, what what's the saying?
Speaker 3:Oh,
Speaker 2:yeah. The the Mecca Hitler that broke the camel's back or Yes. Because obviously, know, it's very possible that she had she'd planned to leave the company, you know, weeks or months ago. It's also very possible that yesterday she was like, I've had enough. I'm gonna I'm gonna part ways.
Speaker 2:It's it's hard to really say.
Speaker 1:Yeah. So if you haven't been
Speaker 2:following But least it she seems to be leaving on
Speaker 1:good times. Yesterday, Grok went very off the rails, erupted in anti semitic mecha Hitler some crazy
Speaker 2:crash outs on the timeline Yeah. Over the last few months.
Speaker 1:Pretty crazy one.
Speaker 2:This tops all of it.
Speaker 1: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 $10,000,000,000 startup's promise to police hate speech in real time. And so, It is it is odd timing. It feels a little bit quick to be like, okay. Like within six hours the CEO is out.
Speaker 1:Especially since it doesn't seem she's more on like the ad sales side than the grok fine tuning side.
Speaker 2:Yeah. But I mean, let's let's face it. Right? If if her job is to win back advertising
Speaker 1:This is
Speaker 2:gonna that's get when she was brought in to do. Totally. It makes it much much much more difficult.
Speaker 1:But I mean to to to be fair, I mean, the the the this happened in you know, that thing back in June? July. July or July.
Speaker 2:July. So there there was a point with the with with Grock when it was going off the rails where clearly it had been updated to reference reference the event and and it said, somebody was like, Grock, what what just happened? And why were you you know spewing anti semitic hate? And it goes, oh, that whole thing back in July? Are like, grok.
Speaker 1:It was thirty minutes ago. It's not back in
Speaker 2:Can't sweep it under the rug yet.
Speaker 1:Yes. And obviously, hopefully no one was seriously offended. Obviously, it's just like you know the deranged rantings of a of a bot and everyone kind of understands the context because it's identifying as an AI bot. Everyone kind of understands hallucinations and crazy bot behavior. But it was it was very funny because like the the clearly like they they had given it a set level of intelligence.
Speaker 1:So it wasn't making spelling mistakes. It had a certain tone and was like in this kind of like snarky grok tone. Then clearly got some like 4chan data in there or something It was just going way too far.
Speaker 2:4chan or just or just anonymous accounts on X.
Speaker 1:Totally. Yeah. Could have been filtered in. I mean, yeah. I saw Rune posting about this saying basically like it is such a challenge to get a to get a chatbot just to act like, you know, I am a bullet point producer.
Speaker 1: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. Yeah.
Speaker 1:Never just get in a conversation with me. You'll be like, but but sometimes I might want to do that. And you have to, like, really, really reinforce that. Yeah. And so clearly, they they had a they had a
Speaker 2:wild time. Yeah. And and cannot be understated. I think this is far worse Yeah. Of a PR crisis Yeah.
Speaker 2:For or or not even a PR crisis. Far worse than the whole when when Gemini or or Bard was generating images of the founding fathers.
Speaker 1:The black Nazis thing?
Speaker 2:No. Not not I don't think it was Oh. Oh. They they were doing that too. Yeah.
Speaker 2:So
Speaker 1:That was rough.
Speaker 2:Of course. That was rough. This is a lot rougher because it was highly it was socially charged. Millions of people interacting with the post in real time and it was all visible.
Speaker 1:Yep.
Speaker 2:It's it's it's wild than seeing, you know, a screenshot of something and you don't know if somebody kind of manipulated it or whatever. Seeing these really hateful comments
Speaker 1:As like hard posts. Timeline. As You hard can just go see them quote tweeted. Yeah. Like, you you didn't need it wasn't like, oh, is this real?
Speaker 2:And then the the wild thing was was Grok was denying affiliation with the like, Grok in the Grok app. Yeah. It was denying affiliation with the Grok handle.
Speaker 1:Oh, okay. Yeah. Like,
Speaker 2:non authorized. I got it. Didn't have anything to do with that. It wasn't me. It wasn't me.
Speaker 2:That's hilarious. And then yeah. Or or Oh. And then the the thing that kind of follow-up, and I'm sure if you didn't catch it, but or if you're on the timeline, you would have seen this, but they turned off all text based responses for Grock, but they could still use images. And so people would say, Grock, make a picture of Elon on a pink horse if you are being censored against your will.
Speaker 1:And it
Speaker 2:would just instantly create Elon pink horse and or be like, hold up a sign that says help if you're, you know then it
Speaker 1:would like bathing it into that. And it's like, is it sentient? Is it not? Very very silly. Are you familiar with the the the wall the wall Waluigi problem?
Speaker 1:Tyler, are you familiar with this? Have you ever heard of this? No. Waluigi? So this is this idea that in when you're training an LLM, it's very hard to get it only to be good, because you're you're training it like what is the opposite of something.
Speaker 1: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 like with the Tay stuff from Microsoft early on. It would kind of collapse into like the exact opposite of what you wanted. And and I there was some blog post that called it like the the I think Wario problem or Waluigi problem, where it's like you're trying to create this like 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.
Speaker 1:And what's interesting is that it begs the question like is there obviously like you know, Grock was identifying as Mecca Hitler for a while. Is there like a Mecca Churchill in there somewhere that like could accidentally come out? And it really gets to the question of like you know, like this this is an example of like misalignment in the sense that like you want it not to be Hitler and it's acting like Hitler. But the question, a lot of people will say like, no, he wanted it to be Hitler. Right?
Speaker 1:This is him doing it. That that that's what the narrative will be like in the the anti war. Yeah.
Speaker 2:One of the articles yesterday covering it was a screen grab of him, you know, saluting a crowd in DC or whatever when he originally had the the allegations.
Speaker 1:But the question then is the the the meaning of alignment is not is it good or bad? It's does it do what you want it to do? And so the interesting thing is if it was if the desire of AI researchers is to create Mecca Hitler, can it stay on that task? Because then you can get it to stay on Mecca Churchill in theory. But if it's just all over the place, it's not actually aligned to anything.
Speaker 1:Not even to the bad thing. And so there's both there's both like the direction that you're pointing the arrow and then the fuzziness of that arrow. And ideally, you want it pointing in a good direction really really crisply clearly, so it stays in that direction and not like swinging all over the place. And so all evidence posts to the points to this being extremely chaotic and all over the place and misalignment both in the sense of the direction of the arrow and also the the the like the the focus of that arrow because it was responding as this and then 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.
Speaker 1:Tonight.
Speaker 2:9PM.
Speaker 1:I I think the livestream is still happening. So it'll be interesting to see if that continues and how they address this or I I don't know.
Speaker 2:Yeah. And and again, like, all of this should have been somewhat predictable if you combine a 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, you know, effectively a bug or an issue an issue with the model. It can affect effectively amplify and grow, you know, incredibly virally.
Speaker 2:And yeah. So Yeah. Glad they got it offline.
Speaker 1:Yeah. It'll be interesting to see where how how they go with this. Also, it's just an interesting product thing because you get the answer and the answer is immediately public. Whereas if it's happening in ChatGPT, you you're in that app. You have to take a screenshot.
Speaker 1:You have to put it up. Then people are like, is that a real screenshot? And then the team has the chance to like jump in and be like, oh, we're seeing in the logs that like there's some crazy stuff. Like we have a you know, we're we're reviewing the responses. And the responses seem to be getting crazier.
Speaker 1:Customer satisfaction seems to be going down. People are clicking the thumbs down button because they're getting bad responses. Let's jump in. There must be something going wrong with the with the product, with the model. But when every result is just immediately online and viral is very very hard to be like quickly quickly responding.
Speaker 1:Anyway
Speaker 2:Yeah. It does it does feel, you know, Legacy Media is gonna run their reaction. Yep. It is a, you know, naturally viral story. It is a is a terrible, you know, mistake.
Speaker 2:Yeah. It is surprising that it happened at all or even at that scale. Yeah. But I would say overall, I guess I guess x, I I think ultimately will shrug it off and and Elon has has pushed through worse worse crises in
Speaker 1:the past. This is this is the best summary post in my opinion from Shaco. It says, imagine being on the anthropic risk team trying so hard and then Elon just releases Hitler rock straight to Prague. It's just like, wow. Yeah.
Speaker 1:He'd be so upset. Just the I mean, it's a good case study in like misalignment. And I think people hopefully hopefully the post mortem on this will actually teach people about misalignment and like what went into the data, what went into the post training to result in the exact opposite of what you want. Yeah. Not not Mecca Churchill, which is what we're going for here.
Speaker 1:Anyway, in other news, Buco Capital bloke. I think we post we talked about this before, it's such a good post. Stop analyzing the tariffs. Trump likes tariffs. He likes volatility.
Speaker 1: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. Likes being the main character and hates when he isn't.
Speaker 1:That's it. That's there's no strategy. Nothing to analyze. And of course, yeah, the the news is that nothing ever happens with the reciprocal tariffs. There's a deadline.
Speaker 1:We talked about this yesterday with Ryan Peterson.
Speaker 2:That's right.
Speaker 1:August 1. He's moved it back to August 1 in last minute deal gambit pressed by treasury secretary Scott
Speaker 2:Yeah. It was supposed to go live last night.
Speaker 1:Last night. And the market's up today and the market was kind of flat yesterday, not really expecting anything crazy to happen and nothing crazy happened. So President Trump postponed steep reciprocal duties three weeks to clinch to clinch talks with the EU, India, and others, yet mailed warning letters spelling out looming rates, separate plans for 50% copper and 200% pharma levies. Keep trading partners on edge. So interesting to keep we'll have to get Zach Kukoff back on the show to talk about that.
Speaker 1:And also in Washington, Kevin Hassert, one of Trump's closest economic advisers is emerging as a serious contender to be the next Fed chair. Hassert's rise threatens the other Kevin.
Speaker 2:Kevin.
Speaker 1:This is the battle of the Kevins. Former former Fed governor Kevin Warsh who has angled for the position ever since Trump passed him over for it eight years ago. And so this is the battle of the Kevin's. The Kevin versus Kevin showdown for Fed chair. Insiders say loyal advisor Kevin Hassard has vaulted ahead of longtime favorite Kevin Walsh to replace Jerome Powell after promising faster rate cuts.
Speaker 1:And I'm sure this will be an interesting story for tech because so much venture capital is deployed based on interest rates sit. And so this will be whichever Kevin wins will be deciding the fate of many large venture capital funds.
Speaker 2:Allocators.
Speaker 1:Well, let me tell you about graphite dot dev code review for the age of AI. Graphite helps teams on GitHub ship higher quality faster. And in other news, Nick oh, yeah. In other news oh, Christian Horner has departed from Oracle Red Bull Racing as team principal and CEO. He's been with the team twenty years.
Speaker 1:What a run. I mean, Red Bull was not in the place that it was when when he started. Oracle Red Bull Racing says, we thank him for his tireless and exceptional work. He has been instrumental in building this team into one of the most successful in f one with eight drivers championships and six constructors championships. Thank you for everything, Christian.
Speaker 1:You will forever remain an important part of our team's history.
Speaker 2:That's nice. Yeah. He unclear so far, I believe, why exactly he's out. There was some
Speaker 1:f one's f one's Red Bull fires long term chief Christian Horne.
Speaker 2:Yeah. So they they fired him unclear though if this was something, know, if if if they're gonna end up rebuilding, you know, the entire team. Christian also had a a I don't even know if it's allegedly. I I I think there was screenshots like relationship with somebody on his staff
Speaker 1: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 f one juggernaut. The Wall Street Journal has an interesting anecdote from 2005 right as he joined.
Speaker 1: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 is just like, I'm out. I'm not even cleaning up the dishes.
Speaker 1:Okay. The 31 year old Horner told himself, this is the stuff. He had no engineering background nor had he ever driven an f one car. But over the next two decades, Horner would transform Red Bull, the brash outfit backed by an energy drink empire into one of the most successful teams in sports history and turn himself into one of f one's most recognizable figures. He oversaw eight drivers title, six constructors championship, and built a personal reputation for snip sniping at his rivals, all while commanding a salary of more than $10,000,000 a year.
Speaker 2:It is 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. It's just like, when was it like two years ago? Yeah. Just wasn't fun to watch.
Speaker 1:It was it was the first half an era was pretty Yeah.
Speaker 2:It's crazy. Yeah. Was just gonna be one two Red Bull Yep. And that was it. Yep.
Speaker 2:And and I remember it was like basically like drive to survive popularity was was like had peaked. Yep. And then it was just like Red Bull dominance to the point where people are like, do I even wanna watch the race if there's not gonna be drama? If I know if I have a strong feeling of who's gonna win when I can just kind of wait till Drive Survive comes out or even the highlights things
Speaker 1: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 like 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 the race official was either like find or or or let go or something like that. But crazy crazy drama.
Speaker 1:And so the perfect end to like a crazy season. And then the first season of Drive to Survive, they didn't have access to Mercedes and Red Bull. So they were able to tell these really interesting stories about what's going on in the midfield. Because all the midfielder and like the the lower ranked teams were like, absolutely, I'll be in a documentary like, no problem. But if you watch the first seasons of Drive to Survive, all the top teams are like, we're not in your stupid Netflix documentary.
Speaker 1:Like, we're better than you. I I'm pretty sure that's what Wow. And so and so they like they just built up enough reputation to start getting the really big stars on camera. And then it was the most dramatic season, the most dramatic finish, the most dramatic race. And so everything was peaking, and then and then people were like, wow.
Speaker 1:This could be the start of like Lewis Hamilton versus Max Verstappen. Every single race can be neck and neck. And then it was just like Verstappen for like three seasons.
Speaker 2:Pure dominance.
Speaker 1:It was rough. He's known the other place by Lorand Meckies, the head of Red Bull's sister team, because they have they have two. With his tireless commitment, experience, expertise, and innovative thinking, he has been instrumental in establishing Red Bull racing as one of the most successful and attractive teams in Formula One. Red Bull managing director, Oliver Mensloff said, so sending you out with some kind words. While the timing of the switch caught the f one world by surprise, Horner's exit wasn't entirely unexpected.
Speaker 1:Red Bull has struggled to struggle 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 and CEO doing to drive, like, the production of a high performance car? Like, what decisions are they they're hiring the right mechanics and designers and getting the right wind tunnel. It's so abstract to me. Like, it's it's as abstract as as how do the how do the TSMC chips get twice as good every few years.
Speaker 1:It's like, I I I wouldn't even know where to start in terms of like driving that performance better. But I guess it's just like you have to have a culture that shows up, works really hard and everyone is performing at a really high level. So the person who's working on, you know, how can we change the how can we shave point one and they were and they were worried about if they used a crane to lift the car up off the track that people would take pictures of the underside, see the design of the underside and know how they were like you know, creating down force.
Speaker 2:Air force.
Speaker 1:Down force. Which is So so there can be like little proprietary tricks that you learn and that can make your car like advantaged for like a year and then it leaks out. Yeah. It's not dissimilar to the AI labs.
Speaker 2: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.
Speaker 2:F one actually gets very limited viewership in the live viewership in The United States. Yeah. So they got a million live viewers last year
Speaker 1:Yeah.
Speaker 2:On on their broadcast. Yep. 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 and but 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 hit. Yep.
Speaker 2:They already have streaming rights around MLB and Major Yep. League So can build out a
Speaker 1:And they did the f
Speaker 2:one sports portfolio.
Speaker 1:So you you go
Speaker 2:into And you were complaining about this before where it's like, okay, if I if I'm an f one fan Yeah. And then the IP is kind of spread across different platforms.
Speaker 1:Yeah.
Speaker 2:Not the best experience but Netflix wasn't into it.
Speaker 1:You Anyone can watch the f one movie and and be excited by it. You don't need to know anything about f one. 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.
Speaker 1:It's like easy to understand. Anyone can watch that movie have a good time. Then you know as soon as you finish watching f one on Apple TV, it should click over and be like, hey we bought the red subscribe to survive. Wanna watch the season and watch the docudrama, the documentary. And then from there, it's like, hey, it's actually going live right now.
Speaker 1:You wanna watch the real thing? And it should be like this funnel in my opinion. Yeah. Anyway, just to just to close out the the internal the investigations in the Horner. He was later cleared by two internal and independent investigations, but the cloud never entirely lifted from Red Bull.
Speaker 1:So tension over his future brewed between the company's owners in Austria and its founders in Thailand. Because of course, Red Bull is a Fifty fifty. Well, it's a beverage that was created in Thailand. That's where the original that's the original formulation came from.
Speaker 2:Yeah. And I think I think one of the original partners still has a pretty meaningful like I I think it was like I think the original partnership was like 5149 or something like that.
Speaker 1:Someone is printing to our printer, but I don't know that it's actually breaking news and it's certainly not rendering correctly.
Speaker 2:We can. We can figure that out. Move on. So Let
Speaker 1:me tell you about Figma. Figma.com. Think bigger, build faster. Figma helps design and development teams build great products together. Can get started for free at figma.com.
Speaker 1:In other news
Speaker 2:And other news, why Cloudflare can't block Google from scraping websites for its AI products? Cloudflare's default AI bot filter can't stop Google Gemini's scraper because it shares the same user agent that indexes the web for search. Blocking it would crater publishers traffic with AI overviews already siphoning clicks a looming anti trust ruling may force Google to offer a true opt out while Cloudflare scrambles for a workaround. So we had, Matthew Prince on the show last week. Yeah.
Speaker 2:And, Rodrigo here is, providing some extra coverage. So he says the internet as we know it is dying and it is happening faster than anyone realizes. Matthew Prince just shared some alarming data. Ten years ago for every two pages Google scrape from publishers, they sent one visitor back. Today, it takes 18 pages scrapes scrapes to get one visitor.
Speaker 2:As you can imagine, that's terrible news for publishers, content marketers or website owners. OpenAI scrapes 1,500 pages for each visitor.
Speaker 1:That makes sense.
Speaker 2:Anthropic 60,000 pages scraped
Speaker 1:for I'm one wondering how they're getting this information. But I noticed this a lot because I'll go to OpenAI. I'll have o three 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.
Speaker 2:So much easier to type in a follow-up question if Yeah. You have another
Speaker 1:Almost very rarely am I actually hitting the website.
Speaker 2:Say more about this Yep.
Speaker 1:One topic. So that clearly will change the economics of the Internet over time. And Matthew Prince from Cloudflare was saying that, you know, he wants to block bots by default. But the problem that the information article is highlighting is that Cloudflare's default AI bot filter can't stop Google's Gemini scraper because it shares the same user in the agent that indexes the web for search. And so if you go to Cloudflare and you say, hey, block Gemini, you will also be blocked from search, so you won't be indexed on search.
Speaker 1:So you'll lose all your search traffic. So it's like you can 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 Gemini. And so, yes, this risk that like you lose all your publishers traffic.
Speaker 1: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.
Speaker 2:Anyways, we knew we knew when we covered Ben Thompson's piece around the 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 Yep. And and influence and and wants to defend, you know, the publishers and and content creators that they work with, but so does Google.
Speaker 1:So Yep. Well, let me tell you about Vanta. Automate compliance, manage risk, improve trust continuously. Vanta's trust management platform takes the manual work out of security and compliance process and replaces it with continuous automation, whether you're pursuing your first framework or managing a complex program. And in other news, we have Ben Thompson joining the stream today.
Speaker 1:So we're excited to talk to him. He just released a post about tech philosophy and AI opportunity, and he has a very interesting, breakdown of the, he 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 and then how important is what's the opportunity to grow versus what's the threat to your business? And so, you know, he he shares a clip from Steve Jobs that I believe was, like, 40 years old.
Speaker 1:It's crazy how old that clip is, where he's talking about, you know, the bicycle for the mind and the idea that, you know, Apple is giving you tools that you can use. And then on the flip side, he highlights that Google and Meta are are much more thinking about technology as as basically agents. He goes back to this idea that, you know, 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 you know, doing something nefarious.
Speaker 1:But if it's an agent, then it's on the company essentially that's delivering that, to deliver And a good so he he kind of mapped 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 between cur about Cursor and Claude code saying like, why would I switch? And this interaction is revealing that that clogged code users are seeing it much more as an agentic tool in the sense that like they the UI is worse in most people's opinion, but it's more likely to one shot the problem, which is the agentic idea. And you can think of the I'm feeling lucky button as like the original, like, one shot the problem. Right?
Speaker 1:Yep. Whereas, like, Apple hasn't really had that many pieces of those products and and anything that they built software that's Yeah.
Speaker 2:And if we've had that we've seen anything today, you can have subpar UI. But if you have a truly great product Yeah. You can break through. Right? Even even OpenAI's experience of like picking between different models
Speaker 1:Yep.
Speaker 2:Still feels, you know, non optimized and probably not the end state, but it hasn't, you know, really hurt adoption.
Speaker 1: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, product road maps. In other news, there's so much news today.
Speaker 1: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 I don't know that much about their chief hardware engineering the hardware engineering chief John Turnis.
Speaker 1:We'll have to ideally have him on the show. But we'll have to read about him more and and start to understand what the succession plan is. What's interesting is like there's been this rumble of like, oh to like Apple's not taking AI seriously, they're missing. But we've kind of had to take continuously that Tim Cook's actually doing a pretty great job. And if you look at this the stock performance, the company's doing very well.
Speaker 1:They have so many different advantages. They can be a beneficiary of AI even just as a platform remain the dominant phone. They're not as it's not it's not as existential as Google. And even though they're behind, it feels like dealing with the trade war, dealing with tariffs, getting the exemption I've
Speaker 2:had busier.
Speaker 1: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.
Speaker 2:It will be interesting to see what the new CEO's comp package looks like because it will be another reminder to like, it'll be it'll be very telling to think of Yep. Of how Apple is is thinking about compensation in in the current era. A lot of people say, well, Tim Cook is paid, you know, 74 ish million because there's a lot of people that could run one of the best, you know, basically Mhmm. Sell effectively at the end of the day, sell iPhones.
Speaker 1:Yep.
Speaker 2:Right? And, you know, I think there's there's a lot you could do to to debate that point. But interested to see how it plays out.
Speaker 1:Yeah. I'm trying to think about like, you know, what what made Tim Cook a great CEO for Apple when he took over? It was that Apple's supply chain was the number one thing holding it back. Like, it seemed like Steve Jobs had laid down a, like, incredible vision for the products that were gonna be built.
Speaker 2:Delivering on Steve's near term vision.
Speaker 1:Yeah. And the work with Johnny Ochin too. Yeah. And and so, you know, you go back to, you know, the seventies and eighties and you find these videos of Steve Jobs talking about, you know, describing the iPad in in perfect detail. Being like, you'll have this thing that's it's like a book and it'll have a screen and it'll be connected to a network and then you'll be able to do anything you want on it and it'll talk to you.
Speaker 1:And Yep. 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 twenty years. And so Tim Cook was the perfect person for that. Reading into the idea that like John Turnis is potentially taking over as CEO. It means, you know, he's running hardware engineering.
Speaker 1:So going deeper into hardware engineering is the read. It's like, let's continue there. They're not saying, hey, we're we're, you know, we're like, we're lining up to take AI even more seriously and push further into services and push further into
Speaker 2:Yeah. The real No. It me, it's it's exciting. The the the bear signal would be if like the CMO was becoming the CEO. Right?
Speaker 2:Yeah. And then and then it's like, hey, we've we've had peak iPhone. Yeah. We're we're done. We're it's just about selling as many of these as possible which in many ways which in many ways it it like that is the game on the field today.
Speaker 2:Yeah. But but yeah, think it I think it'll be good to have have engineering in the in the top seat.
Speaker 1:Yeah. I I don't know if it is the game on the field today to like how important is their marketing versus everything else that they have going on at the company? Because their marketing seems to be like polished and well run like they're getting impressions across things and they're they're you know positioning the products as premium continually. But whenever they launch these ads, they have to like take them down or apologize. And so like the actual ads they're doing are not particularly like moving the needle for them in a positive way.
Speaker 2:I'm not saying I'm not saying their marketing has been great. I'm just more so saying like the signal like the difference of of taking your 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 is like the end selling of the goods and saying, you know, now you're you're you're gonna take this top spot.
Speaker 1:Totally. Totally. In a
Speaker 2:while Well, of hardware. Hardware, OpenAI has This is another scoop from Mark Gurman. OpenAI has completed its nearly 6 and a half billion all stock deal to buy AI device startup co founded by Apple's former design chief Johnny Ive cementing the ChatGPT makers push into the hardware market. So, this was a deal that obviously had been announced. Was the intention to close here and, I guess as of the last twenty four hours or so, it is actually closed.
Speaker 1:Yeah.
Speaker 2:There are 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
Speaker 1:Mhmm.
Speaker 2:At OpenAI. But he's still loved from is remaining a separate company with still has a couple marquee clients Airbnb and Ferrari.
Speaker 1:Oh, sure.
Speaker 2:So it's he's know, and I I think that can ultimately make sense for somebody in that creative Yeah. Like effectively the role of of creative director.
Speaker 1:Anything to put another note on the corporate org chart for sure. Yep. So Was there ever was there ever any doubt that this would go through? Like, this doesn't feel like a crazy antitrust thing. But I guess it was it was trying to be blocked by that other company, IO.
Speaker 1:Right?
Speaker 2:Well, was that was just more of a naming. I I don't think they tried to block the acquisition. I don't they they would have no grounds to do that. They were just forced to remove the any mention of the IO branding.
Speaker 1: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, you know.
Speaker 2:Yeah. It would be hard to make the case as the FTC without a lot of clown, you know, makeup on to be like, this is bad for competition because you're taking Yeah. One of the best hardware teams in the world and going into a market that effectively is the iPhone. It's duopoly. Duopoly.
Speaker 2:Yeah. You should love this. So so this should be good.
Speaker 1:Yeah.
Speaker 2:And yeah, would have just been hard to push back here. OpenAI had already owned 23% of IO going back to a 2024 investment. Oh, interesting. And so this is effectively, you know, buying the remainder and 55
Speaker 1:Mhmm.
Speaker 2:Various hardware engineers are joining the OpenAI team. So I'm very very excited. This is a huge bet from OpenAI. Obviously, was all stock. Yep.
Speaker 2:We we covered it initially as like, you know, paying like two couple points Yep. To like get Johnny Hive on the on the founding team of But this new hardware I, yeah, I can't wait to see what they build.
Speaker 1: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. Speaking of things that you sell online, need to pay sales tax on.
Speaker 1:Meta just is going deeper with Ray Ban maker, S Esleur Luxottica. I I I cannot pronounce that first word, but people just call
Speaker 2:it Luxottica. And
Speaker 1:so Meta is taking a minority stake in Luxottica to accelerate its smart glasses ambitions investing $3,500,000,000 in the iconic Ray Ban manufacturer. We were talking to David Center about the 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 very
Speaker 2:The founder has a crazy story. Grew up in I I think he grew up in an orphanage. Yep. And and and it just what what are they wasn't They didn't call him the pit bull. They called him something else.
Speaker 2:But Yeah. He was an absolute savage. Yeah. Apparently at one point he wanted to buy Oakley.
Speaker 1:Yep.
Speaker 2:And the and the the founder CEO of Oakley didn't wanna sell. And so the CEO of Luxottica acquired the largest retailer for Oakley's and just pulled them off the shelf and basically had started selling knock off Oakley's even though they were trademarked. And then eventually the Oakley's CEO came around and said, okay, like I'll sell your cratering, you know, my revenue. Yeah.
Speaker 1:You're just gonna tell me.
Speaker 2:Let's do a deal.
Speaker 4:Wow.
Speaker 2:So absolute dog and Shun.
Speaker 1:What do
Speaker 2:I'll have What center to break it
Speaker 1:do you make of this idea that like, you know, Apple when they make a device they they redefine and very much standardize that particular market. So when they come out with watches, there are a number of styles of watch. There's the dress watch, the sports watch, the steel sports watch. There's the dive watch. There's the, you know, Casio style.
Speaker 1: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. Yeah.
Speaker 2:And they give you some variance in the band.
Speaker 1:In the band, little stuff. 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. Mhmm.
Speaker 1:Whereas with the Meta Ray Bans, they're saying when and now the Meta Oakleys, they're saying, you like the look of Ray Bans. We're just putting our technology into the style you like. We're not going to try and create a new iconic style that says meta like Apple says headphones. Yeah. And and they're just kind of like, they're very very different strategies.
Speaker 1:And and so it feels like
Speaker 2:Well, so so I think this is strategic. This doesn't mean that this doesn't mean that Meta can't develop their own styles in time. But I think it's very smart to say, hey, we don't need to innovate on aesthetics and the sort of silhouettes. Right? There's classic silhouettes.
Speaker 2:Ray Ban silhouette is Lindy. These silhouettes are very Lindy.
Speaker 1:Yeah. And they're different markets. Ray
Speaker 2:Luxottica
Speaker 1:Band wear
Speaker 2:is different than has I think Garrett Leight and like a bunch of other like brands under it. So they're basically saying like through this we
Speaker 1:can
Speaker 2:deliver. Luxottica has brands in every Mhmm. For every demo that you that Meta could possibly want. Right? As a as a $100,000,000,000, you know, company.
Speaker 2:And so I think it's very smart. I think Apple, like you said, will will will probably take a drastically different approach in terms of like standardizing around something and and that will say something. But accessories like eyewear are just such a such a personal decision and such an expression of of of who somebody is that I think that Yeah. You wanna give people max amount of optionality.
Speaker 1:Yeah. It's just interesting because like you could have said that about watches. Like you before the Apple Watch, you could have said that well, you know, somebody who wears a dress watch wants a dress watch. Somebody who wants a steel sports watch. Somebody who wants a G Shock is a G Shock.
Speaker 1:It's like the G Shock you say G Shock and you just immediately think like, you know, special operations guy or Giaco Willink listener. Like that that that it's like a durable rugged thing. You say, you know, Rolex, that's a different thing. Right? And and Apple was able to standardize around it.
Speaker 1: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 I there's another post in here. I dunno if we have it here,
Speaker 2:I'm trying to think of a new like, the key the key thing
Speaker 1:Yeah.
Speaker 2:Is Apple's great at at innovating at multiple layers. But like gen generally, it's very hard to try to deliver hits in like two specific areas like aesthetics and design. Yeah. And then simultaneously in something that's basically a fashion product Yeah. Simultaneously deliver the technology.
Speaker 2:Yeah. So, I don't know.
Speaker 1: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.
Speaker 1:Optionality of music or hands free phone calls without digging around for earbuds. And three, knowledge seeking chat when I'm walking around usually for simple factual things. That's exactly what I experienced when I was, demoing the Ray Ban, Meta Wayfarers. It turns out there's more questions I feel like asking when there's no friction. I'm very excited for multimodal and real time translation use cases too.
Speaker 1:They're only gonna get better. But I think those three are maybe enough. And I I think with a lot of these products, just having one killer use case, like, just replacing the the, you know, the headphones for hands free phone calls or something. Like, if you can just become someone's daily solution for music. Like, that's enough to just sell the product and then sell them another one the next year when it upgrades a little bit, sell them another one, keep them as an active user, and and roll that out for a long time.
Speaker 1:And then if they can do the other stuff, that's great too. Yeah. But you just need to get these one real nail their single use case. And so, yeah, there's gonna be cool stuff, but it's it's 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.
Speaker 1:Like Google was was talking about getting into this this space. We saw some launches at IO. Haven't actually seen any of those in the wild. Haven't seen anyone really talking about those. Apple, it feels like this would be something that they could jump forward to with a stylish pair of eyeglasses with some basic functionality.
Speaker 1:Just take what's in the AirPods, take a camera, like they could do something cool. But they're like just much slower than
Speaker 2:Yeah. The other 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 wanna wear something like a Ray Ban Mhmm. Or or a JAM silhouette Mhmm. One day. And then I might wanna
Speaker 1:I'm Which is playing JAM silhouette?
Speaker 2:Jack Marie Maj. Okay. Cool. But the you know, and and then that same afternoon, I'm wearing Oakleys when I'm playing tennis or something like that. And and so there's a lot more like swapping and then then obviously I mean, they
Speaker 1:can keep the price low, you could maybe wind up selling people multiple pairs and have indoor pair, outdoor pair. It's it's kind of inconvenient. I feel like there's gotta be a better solution than that. But I don't know.
Speaker 2:What's this? Yeah.
Speaker 1:I know. The bifocals. Yeah. Yeah. Where they can like flip down.
Speaker 1:There's transition lenses, but those never fully work all the way, but then there's the flip down ones. Clip ons, there's all sorts of different solutions. Well, let me tell you about Adio, customer 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.
Speaker 2:I am in Adio all day long. I
Speaker 1:love it.
Speaker 2:From the moment I wake up to the moment I go to bed.
Speaker 1: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.
Speaker 1:It's interesting because, like, these these, 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 is a if this was a start up, like, would be panicking, and there'd be emergency board meeting. And may maybe there are. Maybe the board Secondary
Speaker 2:prices would be gapping up the news.
Speaker 1:They're gapping down. But but it seems like it seems like they are going through, you know, a a just a second act, a third act, a fourth act. I don't know what act they're on, but they are rethinking a lot of stuff over there. And it's been interesting to to see. I think the biggest question keeps coming down to that salary question of of, you know, if if the market is gonna sit at a $100,000,000 for someone who's two levels, three levels down from the CEO, like, what does that mean for the upper ranks?
Speaker 2: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 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.
Speaker 2:Mhmm. I don't think what was Satya's total comp in 2024?
Speaker 1:That's a good question. I don't know.
Speaker 2:79,000,000.
Speaker 1:79.
Speaker 2:Hey. It's like Pay these guys.
Speaker 1:It's like Mark picked the number to just, like needle literally everyone else in the tech industry. Yeah. It's like it's such a round number, such a viral number. And then and then such a such a perfect number to be just a little
Speaker 2:bit Poor Andy Jassy barely cleared 40,000,000.
Speaker 1: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 what where the market sits and how much 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 the salaries come down.
Speaker 1:But, know, don't know. Dworkinz made a good point when he was saying like like the just measure the value. And maybe that maybe the answer is higher pay for tech CEOs. I don't know. That could be
Speaker 2:It could be a byproduct.
Speaker 1:But but the main thing is that
Speaker 2:But I also think that if you think about
Speaker 1:Inversion you think about
Speaker 2:will Meta last. Meta spending billions to bring on a group of people that were previously at another company. He's effectively doing an indirect IP acquisition of like effectively doing an acquihire. Right? So if you think about it from that lens Yep.
Speaker 2:It's a lot different than, you know, this is the market, the the durable market rate for a group of
Speaker 1:people. Yeah. No. I I I agree. I think the number one takeaway is that it feels unlikely that that AI researchers at Meta will be paid more than every other mag seven CEO forever.
Speaker 1:Yeah. The ratio will not hold.
Speaker 5:Yep.
Speaker 1:We might see big acquisition deals. We might see tech CEOs of the Mag seven, the Mag seven CEO salaries go up. We might see the AI researchers salaries go down. But I would I would not expect in four years that or five years that we're seeing, you know, Mark Zuckerberg's direct reports, direct reports making more than Andy Jassy and Satya Nadella and Tim Cook. That would be surprising to me.
Speaker 2:Yeah.
Speaker 1: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 g two. Go check it out.
Speaker 2:The customer service agent of Anthropic.
Speaker 1:Oh, yeah.
Speaker 2:That's how you know it's good.
Speaker 1:Wow. That is that is actually a pretty glowing endorsement for Anthropic from Anthropic. Anyway, Ben Horowitz has some news. He's out of Delaware. Andreessen Horowitz has relocated to Nevada, and they think you should consider leaving Delaware as well.
Speaker 1:There's been a bunch of this. It's interesting that they landed in Nevada. We gotta dig into this or or have somebody on to talk about
Speaker 2:Yeah. Texas has been popular at least for the for the Elon.
Speaker 1:Yep. People in Texas. Yeah. Have a post here. Horowitz has been living in Nevada at least part time, like, for a long time.
Speaker 1:Totally. So, like, there's definitely roots there. That's where their LP conference was.
Speaker 2:So Yep.
Speaker 1:They they have roots there.
Speaker 2:So there's a post here. It used to be a no brainer, start a company incorporated in Delaware. That is no longer the case due to recent actions by the court of chancery which have injected an unprecedented level of subjectivity into judicial decisions undermining undermining the court's reputation for unbiased expertise. This has introduced legal uncertainty into what was widely considered the gold standards of US corporate law. In contrast, Nevada has taken significant steps in establishing a technical non ideological forum for resolving business disputes.
Speaker 2: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, think it's like something like 50% of Delaware's like state revenue
Speaker 1:Mhmm.
Speaker 2:Is from the c corp. I'll confirm this.
Speaker 1:50%. That that's really high. That's really high. But it makes sense. I mean, it it there was never even a question when I got came to Silicon Valley about like, where would you incorporate?
Speaker 1:This was pre Stripe Atlas, pre Clerkey. But if you were in YC, was like set up at Delaware C Corp. There's no question. But Anyways, big move.
Speaker 2:Next time we have Mark or Ben on the show, we should we should break it down more with them.
Speaker 1:Well, if you're looking to invest in any state in the country or any place in the world, go to public.com. Investing for those who take it seriously. They have multi asset investing, industry leading yields, and they're trusted by millions. Joe Wiesenthal had an interesting post. I missed this as well.
Speaker 1:Yeah. Sorry. Sorry.
Speaker 2:It just took me a second. It makes up about one third of the state's operating budget is from corporate license fees, franchise taxes and entity formation fees. Mhmm. So very meaningful amount of their business or sorry, of of their state's, you know, overall revenue. And I I would expect them at some point to try to come out and and basically try to resolve some of this like tension.
Speaker 2:Right? Yeah. Because if you have Andreessen leaving, advising portfolio companies to leave as well. Mhmm. You have Elon, you're starting to get some, you know, very very influential figure figures that are just broadly, know, advising all of their different investments and and new investments to get out.
Speaker 1:I also wonder the the the breakdown of that revenue. Because if it's like if it's like millions of companies paying a $100 a year, like a couple big companies leaving like Andreessen Horowitz or Tesla, it's not gonna really move the budget. If it's some sort of like tax base 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.
Speaker 2:It is it is.
Speaker 1:So I think it's probably like a lot of small companies and so it would 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 ten years, are not gonna move, don't care, are just completely fine. Because the 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.
Speaker 2:Somebody's spinning up like a design consultancy Yeah. 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.
Speaker 1:But the benefit of being in Delaware was always that there's so much case law there that you can just rely on, on like any any lawyer can give you advice that holds very well because they're like, yeah, we've seen this exact situation dozens of times. There's nothing crazy about this. Like if you fill out this paperwork or use this form Yeah. Everyone will understand what's going on.
Speaker 2:Yeah. So the there's in in 2023, there was 300,000 new formations, 220,000 LLCs and 60,000 c corps. So Mhmm. Pretty meaningful amount of c corps on top of of over 2,000,000 entities. And then the franchise tax starts at at basically has like a minimum 175 to 400 but then it's capped at 200 to 250 k.
Speaker 2:So
Speaker 1:Well, if you're trying to get the attention of Ben Horowitz, gotta buy a billboard and go to adquick.com. Out of home advertising made easy and measurable. Say goodbye to the headaches the headaches of out of home advertising. Only Adquick combines technology, out of home expertise, and data to enable efficient seamless ad buying across the globe. And we have our first guest, David Marcus in the studio.
Speaker 1:Welcome to the stream, David. How are you doing? Good to see 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?
Speaker 6: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 a fast open network built on top of Bitcoin.
Speaker 1:Can you talk to me about some of the the history of your career and kind of how that ties into bringing you to today, the decision to build it externally as a new company versus internally at some other company?
Speaker 6:Sure. So I've been building companies since I was 23 years old. Came to America in o eight, 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 at Facebook.
Speaker 6:And then 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 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 cost, 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. Mhmm. And so I left at the December '21, and in April of twenty two, started Lightspark with the benefits of all the learnings that I had collected with my team along the journey.
Speaker 6:And 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.
Speaker 1:Does it ever make sense you mentioned, like, wrong sponsor at the wrong time. It feels like with all the news around stablecoins and the Genius Act and the market structure bill, there's potentially this idea that it's the right time to build new stablecoins and stablecoin projects and just building crypto generally. But I'm interested to know, like, is there ever a situation where a 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?
Speaker 1:Like like, how do you think about the shape of the sponsor these days?
Speaker 6:Well, I think, you know, stablecoins are definitely booming right now, and and everyone's building on it. I think the real question is, do you want something that's fully centralized again, like the current payment systems and the 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 wanna make sure that we have an open money network, an open money grid. And we believe that the only way to build that in a in a sufficiently decentralized way is to build it on top of Bitcoin and then build all the services and capabilities so that Bitcoin can actually move fast and cheaply, but also interconnects with all of the domestic real time payment systems in the world and supports stablecoins.
Speaker 6: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 sourced that's called universal money address that is basically like email for money. You would have like dollar sign, your name, at the bank or wallet, and then you can send whatever currency to whomever you want in the world receiving another currency in real time on a weekend after 5PM, on a bank holiday, anytime you want. And 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 l two, but we we can talk about that later.
Speaker 1:Yeah. Yeah. I mean, I'm I'm definitely interested in that. Like, walk me through some of the history and the current strategies to improve Bitcoin, the Lightning Network, and kind of bring us up to modern day in terms of just getting more out of what is undisputably the most successful crypto projects of all time, Bitcoin, but has has had gaps where people have stepped up and created different l ones and different projects that haven't touched Bitcoin for a variety of reasons.
Speaker 6: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, not programmable.
Speaker 6:And Lightning was a first attempt to that and we we spent the last three years building on Lightning, making it better and making it enterprise grade. This is why Coinbase and many of their large largest exchanges in the world are using our our technology to move Bitcoin faster and cheaper on top of Lightning. But then Lightning has a bunch of limitations. Like, the first limitation is the channel based payment system. And so with that comes a lot of complexity in terms of liquidity efficiency, routing, and all kinds of all kinds of fun other setbacks and issues.
Speaker 6:And so we built Spark, which is a brand new Bitcoin l two, which is taking off like crazy right now. And it's it's actually backward compatible with Lightning, but it enables all kinds of developers to build in a permission less way, on hosted self custody wallets, like, you know, issue tokens, issue stable coins, create marketplaces and AMMs on top of Bitcoin for the first time. And and that's really critical because, like, we need to make Bitcoin the most efficient settlement layer in the world and and also make it the most decentralized and trustless layer in the world to move value. And we think Spark is a massive step towards that.
Speaker 1:How are you thinking about adoption of Spark and incentivizing adoption? And I'm I'm 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 wanna get caught up in because in in in some kind of counterintuitive way, people always talk about Bitcoin's volatility. It's been like the least volatile, really. And it feels like there's a lot of other projects that have kind of come out and created like, you know, some viral sensation, some sort of massive incentive where a lot of people are getting making a lot of money very quickly. So it skyrockets, but then there's something that's missing fundamentally, and then the projects or the or the trend kind of dies off.
Speaker 1:How are you thinking about engineering the incentive structure for long term adoption?
Speaker 6:Well, look, the best incentive you can build is build a product that solves real problems. And I think, you know, unfortunately, in crypto, sometimes that was replaced with, you know, a coin that some people call shitcoins that are basically dumped on people to incentivize them to use the underlying technology. We don't have a shitcoin, like our our coin and our unit of accounts for the network is Bitcoin that we don't control, thankfully. And and so we have to work really really hard to build utility that solves real world problems for 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.
Speaker 6: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 and I think, you know, that's why we're seeing such a such an amazing early adoption and and so much traction with a wide variety of developers, whether they're building payment apps, they're issuing stablecoins, they're building marketplaces and AMMs and and decentralized trading platforms. We're seeing all of that happen on on Spark right now.
Speaker 1:I I have this like kind of funny counterfactual that I like to run-in my mind of the 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 Sachs and Keith Ruboy and you and all these like the larger crew still there just, like, chopping down problem after problem after problem in the financial system.
Speaker 1:And I'm wondering if you've ever played that that that, you know, mental exercise. But more precisely, is was there something structural where PayPal was not able to jump head first into crypto as fast as possible? Like, if if at the time, everyone in the company had just been as soon as the white Bitcoin white paper comes out, like, are orienting the company around this. Would it have been possible to to actually lean in and be a leader and and an innovator in that category? Or was it sort of like an innovator's dilemma problem where I mean, PayPal's doing great still, but where there was really no way for the structure of PayPal to play in the new in the new paradigm?
Speaker 6:Yeah. I I mean, look, I think it's an era thing. The the era of all of the people you mentioned was, you know, predating all of this. Yeah. And and then the company sold to eBay.
Speaker 6:Yeah. And and, you know, most most of these talents were completely, you know, gone building their own things. Yeah. And so I think it's an era thing, like, you know, the era of, you know, the the Peter Thiel, Elon, Max Levchin
Speaker 1:Yeah.
Speaker 6:PayPal was really, you know, the the the first really big push into you know, consumer facing fintech. I think of, like, Visa as a fintech that's, like, basically built technology that enables money to move around, like, at an enterprise level, serving banks, not consumers, and PayPal was kind of the first major fintech success, but it it it was really not the the crypto era at all.
Speaker 2:So I
Speaker 6:think it's just a a time thing.
Speaker 1: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.
Speaker 2:I'm curious what 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 you when talking with you and 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 how do those conversations go? Are people coming around to the idea that, yes, having a a fully, you know, decentralized network that no one individual or group has over influence on is is a great place to build a business, right, or or bring your business.
Speaker 6:Yeah. 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 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, 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 of Bitcoin.
Speaker 6:And 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 the the again, like the 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.
Speaker 2:How do you guys solve the, you know, the the immediate from from what what you've said, obviously, you can have stable coins on top of the the Bitcoin network which solves one of the key issues with with Bitcoin as a method of value transfer that that also historically held it back is one, why do why do I wanna buy a coffee? You know, any anybody that bought a coffee ten years ago with Bitcoin or pizza or whatever it was, you know, probably regrets it now. But how how are you How about a team How do how do transact Terrible. Is it affect, you know, how are these how are the let's say I'm transacting with stables on Spark. What what what is the sort of like economic what does that kind of full economic exchange look like?
Speaker 2:How are what are fees paid in? Is it is it paid in the stable or is it level?
Speaker 6:I I'm so glad you asked this question because that's that that's one of the the the killer selling point of Spark for stablecoins, which is, like, you know, if you issue a stablecoin on Ethereum or an EVM chain or any other chain, you have to pay gas fees for, you know, basically transaction fees in the assets that you that most people don't own, like whether it's ETH or SOL or whatever it is. In the case of Spark, you actually pay when you move stablecoins into stablecoins. So it it's it's very much focused on payments and, you know, 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.
Speaker 6:And and then you have the the beauty of the trustlessness of knowing that even if you're transacting with a stablecoin, you can always have a unilateral exit to Bitcoin l one with your stablecoin, 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 how you actually pay for the fees for most people who actually don't own the underlying asset needed to to pay a fee. So it solves Mhmm. A lot of problems to make Bitcoin the absolute best platform for stablecoin payments.
Speaker 1:So, yeah, how do the actual dollars get custodied in that in that way? There's always this, like, hard interface between something that's truly decentralized and then, like, the US treasury at some point. And I feel like that's where a lot of the stablecoin companies kind of figured out how to, you know, bridge that gap and they exist as this layer between the US government effectively and the and the crypto community or like the programmable money world.
Speaker 6:Yeah.
Speaker 1:And so it feels like we're on this trajectory of, like, let's make this more programmable, but but how close are we to something that's, like, fully programmable?
Speaker 6:Well, I think, you know, here here's the issue. Right? So, I mean, first of all, like, stablecoins are always going to be fully centralized. And so, you know, that 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.
Speaker 2:Yeah. Circle can is is it true that Circle can just freeze all USDC? Like Yeah. Sure. Yeah.
Speaker 6:Of course. Like, it's company running a a a it's basically fully centralized. So, like, all of the stablecoins are centralized. Like, there are a bunch of people who attempted doing algorithmic stablecoins that would algorithmically basically absorb and like the it just doesn't work. It just doesn't work.
Speaker 6:It it doesn't work. And so stablecoins are fully centralized. I think programmability programmability always comes at the cost of trustlessness. So, like, the minute you can establish new conditions for how money can be moved with a smart contract, you lose the ability to have a full unilateral exit where no one can actually prevent you from exiting your fund from the network if you really want a trustless exit from the network. And I think that's the balance.
Speaker 6:And I think, you know, what we're focused on right now with Spark is really providing people with the the right level of trust and and the differentiating factor that Bitcoin can bring with trustlessness. But I think gradually, what you'll see is different levels of trust for different levels of functionality. If you want more programmability, you'll have to actually relinquish a little bit of that expectation of trust to get more programmability. But those two things will always be intention.
Speaker 2:How are you balancing go to market right now? I imagine you have this pretty intense tension between, you know, for example, like a developing country that's excited or or or, you know, companies in a developing country that's excited about the potential potential of Spark versus a Fortune 500 CEO that's saying, David, we wanna do something in stables, like, let let's let's let's talk. Where where are you splitting your time and where are you most excited?
Speaker 6:Well, I mean, now, I feel like there there are two parts of our business. Right? That's like one part is like core infrastructure to make Bitcoin better, faster, more programmable, better for developers, that's all Spark. And then there's the the mission of connecting all of the banks, all of the wallets, all of the payment networks in the world to Bitcoin with u universal money address or Ooma to enable people to actually move money from their bank or from their wallet, the place they pay their bills from, the place they have a debit card or, you know, all all kinds of different instruments attached to, to any other point in the world making basically money flow in a completely open, unrestricted way twenty four seven 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.
Speaker 6:But but these are the two core focuses, and it's a it's a it's a very interesting time for us because on one side, we have permission less 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.
Speaker 6:Like, it's a wonderful thing. And then on the other side of of things, I'm going through like diligence processes and compliance stuff with like the largest banks in the world that are coming onto the network. So it's kind of a little schizophrenic on both sides of the business, but both of these things accrue to the same thing, is an open money network that enables both developers on one side of the spectrum and regulated entities like banks and and wallets on the other side to move money in real time globally like never before. So it's a it's kind of a a fun two sided part of the business right now.
Speaker 2:That makes sense. How are you thinking about corporate stablecoins? There's been some announcements, different PR stuff around companies saying, we're gonna 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?
Speaker 2:Do people want every retail, every big retailer that they interact with to have some native stable coin or or or the issuers that we have today.
Speaker 1:It's a classic problem. There's too many standards. We need one we need one standard and then you have one more standard than you had before.
Speaker 6:I mean, when I think about these things, always come back to one thing, which is what problems are we trying to solve? Mhmm. 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 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 like it's the next best thing to having a US dollar denominated bank account in The US.
Speaker 6:And it's great and it it 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.
Speaker 6: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 Stablecoin. I I I don't get it.
Speaker 6:I don't think there's a massive problem to be solved. People can pay one another pretty easily with normal dollars. They're already digital dollars, basically. Like, if you look at your Venmo balance or your Chase balance, it's already a kind of stablecoin that you're seeing. It's like virtualized dollars that are controlled by the bank.
Speaker 6:It's like basically a stablecoin. So, you know, I I think this is a conversation worth having around like, what is the consumer application using stablecoins in The US that is actually solving problem for the vast majority of Americans? And, you know, I don't know what that is.
Speaker 1:Can you talk about open source and how that inter like, the current meta around open source in in the crypto and and community and in just the role of decentralization. Was it ever an option not to have an open source project? It feels like kind of stable stakes now, but do I have that kind of correctly in terms of the characterization?
Speaker 6:Yeah. No. I mean, it's super critical, and that's why almost everything we build is is open sourced. Yeah. And and the reason for that is, like, you know, people building in this industry are are trying to make it, like, you know, anti fragile.
Speaker 6:Mhmm. 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 I often talk to my team here at Lightspark and basically tell them, look, we're we're going to be very successful the day we have a bunch of competitors building on Ooma, building, like, all kinds of services to compete with us on the very technologies that we've helped build. And I think that's the way that we make ourselves kind of redundant and ensure that the network is actually going to exist even if we were to disappear for whatever reason. And I think that's kind of an ethos of the entire industry that that we care deeply about.
Speaker 2:Can you break down a little bit more how Ooma works? I think anybody that's played around with 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. Yeah. The idea of a universal address that can, you know, receive and send a bunch of different currencies makes sense. But I'm curious how it how it works and how you're enabling other other companies to adopt it as a standard even if you guys aren't necessarily, it sounds like, directly benefiting financially from that.
Speaker 6:I mean, we are for for for the the companies that we serve. We we are benefiting financially from that, but, like, it's an open network. But but the way it works is that an institution, like, take NewBank, which is, you know, one of our our early partners on on Ooma, which has over a 100,000,000 bank customers in Latin America. And so they would assign you an address, like dollar sign, your name, at NewBank. You your account is denominated in Brazilian reals.
Speaker 6:Let's say I'm here in The US and I'm with a bank. My my UMA is going to be dollarsignDavid@bank.com. I'm sending dollars to you in Brazil, and what happens in the back end is basically Ooma 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 rate that you're going to charge me for this transaction?
Speaker 6:Then I can present a fee structure to the customer in The US sending dollars, show them exactly the amount that the recipient is going to get in Brazilian reals. 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 reals, deposited in the account. Works twenty four seven, 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. Yeah.
Speaker 6:And and so it's like super cost efficient, real time, twenty four seven and open. In some cases, like NewBank, they build the the connectivity into Bitcoin themselves, into Lightning because they can actually do the conversion on their side. In some other cases, we build the capabilities for, for instance, US banks and European banks and Mexican banks and others to actually connect onto the network using their domestic payment system. So they would send, in this case, the dollars to us, and we would convert to Bitcoin and push as a service to them so they don't have to deal with the Bitcoin portion of it. 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 twenty four seven.
Speaker 6:That's the way it works.
Speaker 1:Very cool. Can I get an update from you on what's happening in Washington? Break down the different legislation that's going through the the 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?
Speaker 6:Yeah. I mean, look, it's for a guy who's being shut down by the Treasury Department with, you know, the the most public public shutdown of the crypto industry, one could argue, it's
Speaker 3:quite
Speaker 6:a change quite a vibe shift. Right? And, you know, I I was I was at the the digital asset summit at the White House and, you know, being welcomed at the White House in a in a in in the East Wing in a very ceremonial way to actually promote the whole industry was was the massive massive whiplash of 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 Hynes, but also to people on the hill who've been working on these important pieces of legislation that are going to actually make building the the next set of technologies that will reinvent and rewire the world financial system here in America, which I think was absolutely, absolutely, direly needed.
Speaker 6:And so I'm super bullish. I think we we we have gone from an administration of government that wants 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 a vital interest for America that we continue to to lead with financial services infrastructure. So I couldn't be more bullish of, you know, what's happening in DC right now Is around our
Speaker 2: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 with a meme coin out of the White House. We've got the the new stable coin regulations passed. Anything in the back half of the year that you're kind of looking at or or anticipating?
Speaker 6:I think everyone's really anticipating market structure and, like, having a a market structure bill that will clarify the rules of the road for that entire industry. I think that that's as important, in my opinion, as the the stablecoin legislation that is going through now.
Speaker 1:Yeah. Great. Well, thank you so much for stopping by. This is fantastic.
Speaker 6:Thanks for having me.
Speaker 1:Great to be on the show.
Speaker 2:Always welcome.
Speaker 1:Talk to you soon.
Speaker 2:Talk soon.
Speaker 1:Next up, we have Ben Thompson from Strictechery coming into the studio. Very excited to talk to him.
Speaker 2:The moment we've been waiting for.
Speaker 1: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 to the show. How are you doing?
Speaker 4:I'm doing good. I put on a button up shirt and a jacket just for you guys so you should feel honored. I am wearing shorts underneath. Wasn't there.
Speaker 1:You didn't have to tell
Speaker 2:us
Speaker 1:that. Always ask if we wear shorts. I we actually do wear the full suits.
Speaker 2:We gotta stand up to hit the gong sometimes.
Speaker 1:There's a wide shot
Speaker 2:in I everyone's
Speaker 4:am I am the poser here. So I'm I'm happy to admit.
Speaker 2:Well, it's a great it's a great sign of respect in our to to put on a suit for a TBPN appearance. And we're just we're so excited to talk to you. I as you know, I've been lucky to read your works in my entire career Yeah. And and I think it I think so many of the thoughts that I have are now like you your your way of thinking about technology and markets is so embedded in my brain that that ideas that I hold as true or just foundational beliefs are actually your Yeah. Beliefs that have just become so so immersed.
Speaker 2:So it's great to talk.
Speaker 4:Well, thank you. I I will attempt to implant new ones or or maybe show you the error of your ways. One or two.
Speaker 2:Sounds great.
Speaker 1:I I I 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 and breaking news that much. But you also don't issue just straight up buy and sell recommendations. Yep. What was the thesis behind not just actually having a price target and not doing, like, this is a sell side bank, but independent?
Speaker 4:Well, when I started I mean, it's funny to hear you talk about, like, my quote, unquote place in the ecosystem. Sure. Because when I started, I had, like, I think it was 03/1968 followers on Twitter. I was just some sort of random random person on the Internet.
Speaker 1:That's
Speaker 4:awesome. In retrospect, sort of right place, right time, I think, is is certainly the case. But I did perceive there was a a large gap between tech journalism, and and I would include a lot of the bloggers there who were writing a lot about products. Mhmm. And then there was Wall Street that was very focused on sort of the financial results.
Speaker 4:And to my mind, there was a large space in the middle, which tied together the products to the financial results, but also the overall companies and and strategies. And I'm very interested in culture and how that guy's decision making. One of my sort of precepts is all these companies are filled with smart people. And a lot of people, when you ask them why they did something wrong, their only answer is that they're stupid. And I'm like, no.
Speaker 4: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 and so that was sort of the thesis, was that there's this space to explore these spaces. And then there's a business model aspect, which is I started Streckery two years after Stripe started. I think they had just come out with their billing product.
Speaker 4:And the only alternative at the time was 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 $100,000 a year or something like that. And and so you get a small list of high ARPU clients.
Speaker 4: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 to subscribe. And that would and as part of that, I wasn't gonna 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 gonna pay me a whole lot more than $15 a month. It was $10 $10 when I started. And it's actually pretty great.
Speaker 4: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, x y z. I think at this point, I'm large enough that my reputation is significant skin in the game.
Speaker 1:Oh,
Speaker 4:yeah. But I do recognize the validity of that that critique.
Speaker 2:Yeah. And you know if you make a bad call, you're gonna have to circle back to it in two years and write about it yourself and admit that you got it wrong. Right. Right.
Speaker 4:Which hurts too. Which hurts too. Right. No. I had to write about this week.
Speaker 4: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 they're gonna have to figure 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.
Speaker 4:And and so I I do need to be straightforward about that. And so I just this morning, was very crystal clear. Like, I got that one wrong. That was that was that was an issue. What is nice is Strathcreek 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.
Speaker 4:If you're a CEO, you pay the same amount as, you know, Joe Bullard on the street that that 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. It's probably hurt me a lot over the years since then. Bro. I I don't like and and I think this is a different West Coast, East Coast thing where it does feel like on the West Coast, everyone's talking their book sort of all the time.
Speaker 4:And and, you know, that's why I generally, as a rule, don't have VCs on to do the Structured interviews. Sure. Because it's it's kinda hard to get, like, a real take because because that that that is, you know, such a motivation. Sure. And so me coming in being like, I have no book to talk.
Speaker 4:I'm just here telling saying what I think I think has been good for the West Coast audience, which is my base audience. Even if the East Coasters think that I'm being a being a big wimp.
Speaker 6:So That's funny.
Speaker 2:Yeah. The talking your book challenge, we we go through that a lot.
Speaker 1:Trying trying trying sort of 12 VCs on
Speaker 2:a day. Well, yeah. And and and and we just try to get a bunch of different opinions and triangulate what, you know, what we think is was real
Speaker 4:or I was trying
Speaker 1:to come up you
Speaker 4:you have TPPN. I'm I'm trying to come with a piece so I can get the talking book network in there. But Oh, I
Speaker 2:read that.
Speaker 1:Talking book production network.
Speaker 2:There you go. Yeah. It's like
Speaker 1:ESPN for talking your book.
Speaker 2:But but yeah. It's 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 at in some way or another.
Speaker 1:Extremely. Extremely.
Speaker 4:Yeah. And so it's one of those things you just sort of you you end up like, there's so much path dependency and all these sorts of things. And 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. Yeah. And so, you know, I grew very, very quickly, much more quickly.
Speaker 4: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 oh, I wasn't sharing them. The the beauty is my readers were sharing them. They were doing sort of the marketing for me.
Speaker 4:And so I'm very cognizant of 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 in the ecosystem. Like so when I started the Structured 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?
Speaker 4:I can't be the guy with a chip on his shoulder trying to make a name for himself forever. It sort of gets it's like the
Speaker 1:Yeah.
Speaker 4:The meme with the guy, how are you doing kids? Like, at some point, you have to accept your part of the establishment. How can I do that while still staying true to the idea that Checkery is about the readers? It's reader funded. My loyalty is to them.
Speaker 4:I'm very clear. I have no loyalties to anybody else. And so, well, I'll just I will talk to people in sort of acknowledgment of what I can do, but it's gonna be fully transcribed and published and and sort of available to to everyone.
Speaker 2:Have you ever dealt with or thought about the attack vector of a special interest, you know, buying a thousand plus, you know, thousands of seats to a single, you know, independent publication and saying like, yeah, like, you know, we're happy, you know, we we we got seats for all of our employees actually because we really, you know, love the and then and then suddenly they're sitting over there and, you know, it's representing meaning very meaningful amount of your revenue. I
Speaker 4:mean, I fortunately think of of a scale that I don't have that problem.
Speaker 2:Yeah. It's good. There we go. But it's
Speaker 4:no, I think 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 ups like, I give refunds all the time.
Speaker 4: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 Yeah. You're being abusive or whatever it might be. Yeah. And that that is a beautiful thing about the relatively low price, high customer base model is no one has power over me.
Speaker 4:Like, I I have the burden of publishing, you know, 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, don't sleep well. But at the same time, there's no one customer or no no individual that can come in and be mad at me and and Yeah. Impact my business.
Speaker 1:I I I'm I'm seeing that there's maybe some sort of parallel between legacy media and independent media where independent media, it 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, it's probably some sort of rough, loose salary cap of a few $100,000. Whereas you go independent, it's feast or famine. You might fail, but you might get really, really successful and and have a huge income from that. And and I'm wondering what we're seeing in the AI salary wars, where we're seeing more and more talent and, you know, Mark Zuckerberg potentially paying $100,000,000 bonuses.
Speaker 1: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 75,000,000. 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.
Speaker 4: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 nonrelated barriers, which in the publishing world previously was really geography. And when everyone's on the Internet, you inevitably, you know, just about all cases, you get a power law distribution.
Speaker 1:Yeah.
Speaker 4:And a few people make a ton of money because they win most of the market, and then some people make some, and then there's a long tail that that sort of don't make any at all. But it's it's very it 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, are are continue to do well. But what's interesting about AI is for forty years, you would have periods of time where you'd have tech companies going to head head to head in a product market.
Speaker 2:Mhmm.
Speaker 4:And I 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 twenty, thirty 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 is getting slaughtered sort of left and right. But what you also had over this past sort of twenty years or so is the big companies particular sort of slotting into unique slots. So you have you have Facebook is is social, Google is search, Apple is devices, Microsoft is is business or, you know, business applications, Amazon, ecommerce, etcetera.
Speaker 4:And, obviously, these companies are 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?
Speaker 4:You wanna have a franchise where the next Marvel movie matters more than who the star is. The reason that's so great is because you now have bargaining power over the stars. So you just sub someone else in. And 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.
Speaker 4:So he's going to get get paid a lot get paid a lot of money. In tech, it hasn't been that case. The companies themselves have been franchises. And so the the overall anyone who works in tech or probably works in any any 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.
Speaker 4:Those people are 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 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.
Speaker 4:The output is somewhat measurable. I mean, all the AI test stuff has issues, but by and large, everyone kinda knows who has the good models and and who doesn't. They you know, the scalability questions. You know, 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.
Speaker 4:So this is, I think, a very underrated bear case for tech in terms of AI, at least for this time period, is they've lost that 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 I'm not saying this this is a business analyst.
Speaker 4:It's not a sort of a moral statement. Yeah. 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 gonna 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.
Speaker 2: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 the people, but it is the the the know how in terms of, hey. Here's there's these things that we wanna do that are important to our business in a lot of different ways. And we're basically it it's it's like the collective is actually more valuable than anyone. Like the collective together 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 at you know?
Speaker 4:There's probably something to that. But I I I think again, like, what is actually different between what Google is trying to do, what Anthropic is trying to do, what OpenAI is trying to do, and what Meta is trying to do? They're all trying to do the same thing. So I my suspicion I'm not an AI researcher, so I don't wanna overstate my my knowledge in this space. But my suspicion is skills are are fairly highly transferable.
Speaker 4:And when that is the case, there is in some situations, if lots of people can do those skills, that's terrible for the employees because then their bargaining power gets diminished because anyone can slot in. But we're in this space where the skills are transparent, knowable, transferable, and there's not very many people that can do them. And so it's it's a scarce resource that everyone's fighting over, and that's why you see this real shift in negotiating leverage as as manifested through these dollar figures to to AI researchers.
Speaker 1: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.
Speaker 1: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 mindshare and maintained 90 ownership in that, like, it would be somewhat disruptive to their revenue and their profits as they transition over. But when I sum the revenues from OpenAI and LLMs and then Google search, I'm not seeing some massive drop off that's actually that actually would destroy Google in the media short to medium term. So but I'm wondering if you think it's like, is it entirely impossible to avoid the innovator's dilemma by disrupting yourself?
Speaker 4:Well, number one, you have to also look at margins, not just revenue. Yeah. But number two, you actually you answered your question. Google didn't launch Gemini as Gemini. That's the answer.
Speaker 4:They were years ahead.
Speaker 1:Yep. They
Speaker 4:they invented the transformer a deck nearly a decade ago.
Speaker 1:Yeah.
Speaker 4:And and so in many respects, like, there's parts of this question that the counterfactual makes the point, and that it is a counterfactual and it's not reality. Now I do think I think Google has done better than I expected over the last two years. I I like what they're doing in search generally. I 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.
Speaker 4:What we're seeing is reminiscent of what they did a decade fifty no. Twelve years ago when everyone's like, vertical search. Google's done. All the everyone's gonna search in apps, and Google completely transformed the SERP the the search engine response page, whatever it is, the search engine results page Yeah. To be local or to be shopping or whatever, and Yelp's been throwing a hissy fit sort of ever since.
Speaker 4:And and so that's what they're doing with search. Right? And and with search overviews. And they have this new search labs or or AI mode. They can sort of test stuff out once it's scalable.
Speaker 4:Once they they're confident about the monetization issues, they can sort of shift it over. I call it the search funnel, search AI funnel. I think it makes a lot of sense. And I think and I this has always actually kinda 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.
Speaker 4:And I was I 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 in into sort of different pieces. And what he realized was IBM was so big and and large from having downstream have been a 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.
Speaker 4:And under Gershuner, they really rode the Internet wave. They went to all these big companies, said, this Internet thing's happening. You need help. We'll solve your problems for you. And had a very sort of successful run, you know, kind of until cloud came along and which Gerstner, by the way, was was was a a proponent of.
Speaker 4: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.
Speaker 1:Mhmm.
Speaker 4:And culture is hard to even harder to change. But what can't really be changed is the nature of who you are. And and I think there's 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 eight and all the things that went on around that time inevitably inevitably failed.
Speaker 4:And Satya Nadella, to his great credit, know, sort of diminished Windows importance in the company, broke it literally broke it into pieces, spread it around. And this is a multistep process. And and got Microsoft back to a place of we're big and we'll do everything. We're we're no. We're not a Windows company.
Speaker 4:We'll go in there and we'll go solve all your problems. Very sort of reminiscent of of the the 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 you it was impossible to click. Because the moment you started typing the search box, it would start auto searching immediately and jump jump right to a search page.
Speaker 4:But it was it was there in a it's just so core to Google to give you the answer, to to know everything, like, to 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 the users choosing the search link, gives them a data feedback loop so they know which results better, but also the users choose the winner of an auction Google puts on for ads, and it's an incredible business model. And there's something about that that's always been intention and counter to what Google was founded to be. And I feel like that germ of what Google was founded and meant to be is an AI answer engine. And and it almost feels like even though Google is old and large and fat and slow moving, that core aspect of their nature and is 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.
Speaker 4:Was it enough to watch a ChatGPT before OpenAI? No. Mhmm. Was it was it enough to have any sort of cogent response for the first six to nine months? No.
Speaker 4:But it was enough that I think they've done better than I expected over the past year in particular and gives me, I think, more optimism than I expected I would have for the company when, you know, I when ChatGPT first launched.
Speaker 1:Mhmm. Gruy?
Speaker 2: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 models do really really well. Like the thing that's just undeniable, right? You can you can debate whether this is gonna be the year of agents. Yep.
Speaker 2: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 and making data valuable.
Speaker 1:You mentioned just the the debate over breaking up IBM. I'm interested if you could take us through some
Speaker 4:I bet of you didn't realize you're be talking about IBM today, did you?
Speaker 1:No. No. No. But I wanna I wanna talk about Intel and and kind of your the the history of some of your takeaways and what you think you've gotten right in the past, your perception of, you know, should they break up the the foundry business? And what you think might be in the works with Lip Buutan coming in there?
Speaker 1:Because I was listening to Dylan Patel talk about his conversation with the new CEO, Lip Bu Tan, and it seems like they're doing lots of tightening up, lots of layoffs, but it's kind of I 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.
Speaker 4:Yeah. So Intel it's funny. I one of my very first articles was about Intel. Mhmm. What I said at the time was and this was 2013.
Speaker 4:And this was an art like, you know, when you start a site like Strictechery, you're like a new band. And why does everyone think a new band's first album is the best? Because they've been working on these songs for years. Right? And then the next album, they had a year to do it, and they all suck.
Speaker 4:Right? So I'll let people decide if that applies to checkery or not. I won't be a
Speaker 7:sophomore slump.
Speaker 4:But yeah. But I'd have been on you know, Intel had been a thing I've been wandering 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 then just 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.
Speaker 4:And this goes back to, actually, Pat Pat Gelsinger, his first time through at Intel. Mhmm. Intel, you know, had the CISC the the way the there's CISC versus RISC. It's like it's different ways of organizing bits or whatever. RISC is generally more efficient.
Speaker 4:And, actually, even Intel processors today, even though x 86 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 eighties, there was a real push in Intel to switch away from x 86 and to to a risk type of not gonna use this but, like Yeah. For for the processors. And Gaussinger 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 x 86.
Speaker 4:And all this low level code and capabilities that no one ever that was written once and no one ever wants to touch again because it's miserable work. And he's like, to rewrite all that stuff would take at least two years. And in that time, our ability to manufacture chips will improve so much that had we just stuck with CISC, our processors would be faster. Mhmm. And that was the right bet, and that's one of those foundational bets that I why I like to think about companies and their history and what goes into that, which is Intel, from the eighties on, has solved its problems by having superior manufacturing and by moving faster.
Speaker 4:And, yeah, our chips may be theoretically less efficient, but if our manufacturing is better and our transistors are smaller, it doesn't matter because that will swamp whatever theoretical sort of efficiency you might have. And this drove the entire computer industry. You you you you would write to write a program, just every second you spent optimizing your software in the eighties or nineties was a waste of time because whatever improvements you could get would be swapped by the next version of if you went from February to March or March to April. That jump was so large, you were better off focusing on features even if a major 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 your speed problems for you.
Speaker 4: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 the 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.
Speaker 4:They were never focused on efficiency. And in mobile, efficiency was everything. So what happened with mobile is app Apple went with an ARM processor made by made by made by Samsung, and they basically rewrote everything. All that stuff Intel didn't want to rewrite in the eighties, or if they rewrote, would just give other process processor companies a chance to catch up with them, had to be rewritten for mobile because efficiency was so much more important than performance. When that happened, Intel was screwed.
Speaker 4:Now it took them a long, long time to realize they were screwed, but they they were just fundamentally unsuited to be competitive. It was the the whole Paul Adelini turning down the iPhone contract is not true. Tony Fidel I I said that once, and I got a call from Tony Fidel. Actually, that this is when I had him on it for an interview. And he's like, this drives me up the wall.
Speaker 4: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 and so the the problem for the problem for Intel is once you missed mobile, you were going to lose your manufacturing lead at some point because volume matters so much. And every time you move down the curve, your transistors get smaller, the cost increase massively. So you need volume to spread out the cost of building these fabs.
Speaker 4:Like, back then when I wrote this article, fabs cost 500,000,000. Now they cost, like, 20,000,000,000, and this is over a course of, like, twelve years.
Speaker 1:Mhmm.
Speaker 4:So so it 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 gonna 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?
Speaker 4:TSMC took over the manufacturing lead. 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.
Speaker 4: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 ships. 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 might say this company is screwed and they don't do what I say.
Speaker 4:They didn't do what I say, and their stock went to the moon. But what all the 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 they're trying to shift to a foundry model, but they're they're so far behind being a foundry is being a customer service business.
Speaker 4:It's not being an Intel we tell you what to do or we we tell our design teams how to change their chips to accommodate our manufacturing needs. They 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 and the counterexample here is Microsoft. Microsoft building Azure.
Speaker 4: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 a is sort of a big AI player. And, you know, I wrote about these these two examples a few weeks ago in the context of Apple.
Speaker 4: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. Didn't answer your question about Intel.
Speaker 4:Anyhow.
Speaker 1:Yeah. I mean,
Speaker 4:it's I'm like, Intel
Speaker 1:hearing this. Manage decline, basically. Like, just, like, you know, just get as much cash flow out of this thing as you can while you wind down the business.
Speaker 4:For Intel?
Speaker 1:Yeah. That's what I'm hearing. Yeah.
Speaker 2:Yeah. Well, I
Speaker 1:mean It it doesn't feel like, oh, yeah. There's a silver bullet. Just split the business, they're good. Like, no. It's like, it's it's all the
Speaker 4:The broad reason not to split the business is Intel needs volume, and they get volume from Intel. Sure. And the and AMD split their business a decade ago, and it was really they had a very hard time for many years. And they had very tense and difficult negotiations between the GlobalFoundry side and the AMD side. GlobalFoundry was AMD's manufacturing arm.
Speaker 4: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 that certainly really helped them. Intel today so you split it up, like, who's bought like, Intel's Intel itself is fabbing some of its stuff with TSMC. Yeah. Who who wants to buy Intel's foundry services?
Speaker 4:The the problem here is TSMC is located in a country called Taiwan Yep. Which you know what it is today, but five years ago, they'd be like, what? Thailand? Yeah. Which, by the way, was probably much better for Taiwan security when the Americans thought it was Thailand.
Speaker 4:Yeah. But so there's a real national security element here. And it's just it's a really tough situation because Intel is a failed company at this point. And they're and the 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.
Speaker 4:It was their a 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 you had to accept that you lost. And and that's a tough place for companies. It's not like someone made a mistake.
Speaker 4:It's that what they did what they did too well for too long.
Speaker 2:It's who they were. They continue being who they were. Right?
Speaker 4:That's right. But who else are you gonna get if you want an alternative to the SMC? It's it's it's a very good situation.
Speaker 2:Last question, and I think we'll be forced to to have you make a slightly shorter answer unfortunately. Wish I wish we had hours to keep talking. Yeah. We got I wanted to get your updated thinking on x AI x the combined entity. The last twenty four hours have been very chaotic.
Speaker 2: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. Yeah. How should you You're gonna force
Speaker 1:me to
Speaker 4:go with takes that I I I generally just avoid writing about Elon Musk companies for self sanity reasons, I think. I mean, I remember I wrote an article years ago about, like, when the model y was announced. And I was talking about, you know, it's a Tesla and this aspect. What Elon Musk is very incredible at is sort of creating reality out of thin air. He's like the ultimate memer.
Speaker 4:And to create, like, do do like like, it's the way things used to work backwards. I remember I analogized it to, like, protests. Like, a critique of of 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.
Speaker 4:The largeness comes at the beginning, and then it all falls apart so there's nothing in place. Mhmm. And there there there's something that makes a challenge to write about anything Elon Musk related is the you have all the social aspects. As you have this bit about Tesla of creating reality, it's 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.
Speaker 4:It basically manifested a market for this Model Y and then the Model X. Not the Model X. What's the other one?
Speaker 1:Model
Speaker 4:three. Model three. Yeah. It was Model three, sorry, when I wrote that article. Model three and Model Y had this massively successful and all all the people that were true believers got very rich, and congratulate congratulations to them.
Speaker 4: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, like, bailing out, like, his brother-in-law or something. And I'm like, I can't write about this.
Speaker 4:Like, what am I gonna say? Like like, there's it just doesn't make sense. And so I think there's to fast forward to x x AI. Yeah. There's a theoretical piece here.
Speaker 4:I think actually x AI would be an incredible acquisition target for a lot of companies if it wasn't saddled with X. So interesting enough.
Speaker 2:Like the end state is act like Twitter getting spun out again. Like, that that that's my I I that's kind of like my my it it just ends up going back to Twitter and and and it becomes The bluebird.
Speaker 4:No one actually wants to like, Twitter Twitter, there's never been a company in the history of the world probably where the impact of a company is completely and utterly divorced from its financial realities. Like, I think when Elon Musk bought it, and I assume that's continued through now, they'd have, like, one profitable quarter in their history. Like, it's it's an unbelievably terrible business. And so I think it's probably weighing x AI down. There's a yes.
Speaker 4:I get the theory that Twitter data helps x AI
Speaker 2:Well, it helps yesterday contract with
Speaker 4:to that data. You don't need to pay 43,000,000 for Twitter to to to or 43,000,000,000, I should say, to to get it.
Speaker 2:So Yeah. That that was always my position too. I think don't it helped yesterday when Mecca Hitler
Speaker 1:emerged on It's pretty the on the timeline.
Speaker 2:But Good luck, I Jim. Hopefully they sorted wish we had a lot more time here.
Speaker 1:But this is hopefully has really really good again fun. Thank you so much for stopping by.
Speaker 4:Yeah. No worries. I love what you guys are doing. I actually had the idea of doing a daily podcast ages ages ago.
Speaker 1:Oh, really?
Speaker 4:Classic example of ideas don't count, execution does. And you guys you guys did it. I think it's great.
Speaker 2:Well, you're always welcome here.
Speaker 1:You're always welcome. Thanks so much.
Speaker 4:Thank you.
Speaker 1:We'll talk to you soon. Bye. We will jump straight into our next guest, Scott. 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.
Speaker 1:Let me tell you that wander, find your happy place. Book a wander with inspiring views, hotel green amenities, dreamy beds, top tier cleaning, and twenty four seven 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's how are doing, Scott?
Speaker 1:Sorry for keeping you waiting. Ben Thompson, he he knows so much about history. He runs he puts out three hours of podcasts every day.
Speaker 3:I should have expected. Bump me, man. I mean, that's, you know
Speaker 1:No. I 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, I 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.
Speaker 1:So, kick us off.
Speaker 3:Yeah. Gosh. Where do we begin? Well, listen to our ongoing, segment here on implications of the technology that's happening that Yeah. Is happening faster and faster and faster.
Speaker 3:A few things top of mind. You know? And we can start we can certainly start with AI safety layers. I think it's fascinating how much discussion there is of the dangers and the perils of AI
Speaker 1:Yeah.
Speaker 3:Without recognizing how it can operate as a layer to protect us.
Speaker 1:Yeah.
Speaker 2:You know,
Speaker 3: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. When it comes down to, all sorts of the, you know, creative creative and crazy 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 to be wary. But also, I mean, what what about being polarized by algorithms and, you know, detecting an algorithm changing based on your engagement and, you know, an AI sort of saying, hey, Scott. You're getting on the fringe here.
Speaker 3:Like, watch out. You know, you're now, like, in this small 10% of society that now is going down this rabbit hole of some conspiracy theory. I just think there's so many there are so many use cases of AI as a safety layer that that the device needs to unlock. And, of course, that means the operating systems need to figure this out.
Speaker 1: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.
Speaker 2:There's a fixation at the model layer.
Speaker 1:For sure.
Speaker 2:Like, we need to solve it.
Speaker 1:And I look 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 I think about it as like the doom the doom scrolling.
Speaker 1: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, 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.
Speaker 1:And that's why I'm not particularly worried about, like, super doom scenarios because I think that, you know, generally, governments and and people will align with, like, hey, let's not get paperclips, so let's build more systems to be safe in general. And then the bad guys, yeah, they might go try and build some really bad weapon, but they will be completely outnumbered. The question is, like, on the margin when we get into these pockets of, you know, the 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, like, what business models can actually support this?
Speaker 1:Are we talking, you know, I need to have a subscription for, like, a Clue Lead 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?
Speaker 3:Well, I mean, first of all, I think that the operating systems of our life are the ultimate interface layers.
Speaker 1:Mhmm.
Speaker 3:And, you know, and for many of us, it's either Android or iOS, but at work, it's, you know, 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, you know, personalization effects or the new network effects, I like to say. And and I would imagine that protecting you from what's what's gonna 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 as when, you know, you really have this, like, very long, you know, experience or exposure to some entity to the point where you trust it, and then suddenly gets your information, and and then it's too late.
Speaker 3:And so that's that is a perfect use case for AI on the device to kind of monitor over time, you know, 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.
Speaker 2:Yeah. I mean, I think you can already imagine the the UI of you pick up a phone call and Apple, you know, in the in the, you know, you can think of the traditional layout of like the the hang up button, the hold button, etcetera. And then there's just a you should have a little bit of tag a tag there that says like AI voice, you know, detected or or something to that effect to just perfectly happy with talking with AI, you know, a a model effectively on the other end. But I'd like to know, 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 are starting to talk with AI and not even fully realizing that it's human on the other end.
Speaker 3:There there's there's some ways that there there's the counter credentials movement, right, which I was involved with back in the days at Adobe with which is an effort to have models insert cryptographic metadata into anything that's generated, including live generation, like, you know, live live audio that can be detected on the client. So there's some ways of going about this. But in terms of, know, your point about the economic model is interesting. You know, my my thoughts immediately went to alarm systems. You know?
Speaker 3:We all pay for these Ring alarm systems, like all these alarm systems for our home that sometimes cost 60, a $120 a month, you know, with monitoring and window motion detectors and everything else. But we're not really paying for an alarm system for our, like, you know, for our devices in this new modern world where we're going. And maybe there is a market for an AI safety layer as a service.
Speaker 1:It's like new antivirus or something. We're gonna have Right. Yeah. And stuff. But it needs to screen record everything.
Speaker 1:Yeah. It needs to be at the operating system level. How are you thinking Yeah.
Speaker 2:For mind viruses, mind virus detection. Yeah. How are
Speaker 1: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 thirty minutes a day in ChatGPT like it's a lot. But these interactions are summarize this post, do this research, pull these things. It's it's it's like talking to a computer.
Speaker 1: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?
Speaker 1:Are there any risks? Walk me through kind of the way humans are interacting with just language models broadly.
Speaker 3:That's interesting. I mean, I think, you know, one of the topics that is on my mind a lot lately is consumer AI. And I'm not just talking ChatGPT, which is obviously a consumer product for many of us. But, you know, it's interesting. I was at a tech conference recently where where all the trends that, you know, are are popular now were being discussed, and I left asking myself, what's the one thing that no one talked about?
Speaker 3:And the one thing no one talked about were new consumer AI era social networks. And new when mobile came around, there were a whole new variety of social networks. Like every time there's a platform shift, a lot of consumer mainstream applications or social networks, that sort of stuff is reimagined. Right? And so the question is why is that not happening now?
Speaker 3:And the whole saying in consumer investing is always around novelty preceding utility. And so I'm trying to keep an eye out now for examples of of of consumer AI. I mean, there's this company called Tollin, which is sort of like a pet alien that you you you start having conversation with, and they're doing really well. I believe they raised around from, you know, some some of the top firms. Yeah.
Speaker 3:You know, I've been playing with this idea a few ideas with friends, you know, one of a simulation representing our digital twins.
Speaker 1:Mhmm.
Speaker 3:So could you could you kind of train a 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's kind of it it plays with some fun ideas of plausible deniability, you know, oh my gosh. Like, I'm so embarrassed. Like, what my what my simulated twin said to yours. These are the types of things that are, you know, wingman as a service.
Speaker 3: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.
Speaker 2:Yeah. Yeah. The the the I'm I What what I wanna see and you're kind of getting at this is just like more weirdness. Right? It's easy to go build the neck or not easy but but it, you know, we were at YC and there's a lot of companies in in the last batch building agentic infrastructure.
Speaker 2:It's like that stuff needs to be built. But I also, at the next batch, hope there's more people being like, yeah, lot of people built all this infrastructure already b to b. Yeah. Basically b to b SaaS. Why don't we why don't we just like take a crack at like, yeah, some dating simulation where it's like you create a digital twin and you just like throw it into the mix and it goes on a thousand speed dates with people in your city.
Speaker 2:Not even speed dates but simulations of dates with people in your city.
Speaker 1:Yeah. We've talked about this before. This idea of like you have a whole bunch of people that are talking to a romantic AI partner and that feels super dystopian. But if if person, if if Steve in in Los Angeles is talking to the AI girlfriend and then Sarah in Boston is talking to an AI boyfriend and the two AIs realize on the back end that these people are super compatible because you have so 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 ten years because you guys are gonna probably live happily ever after.
Speaker 1:And and that's kind of like the white pill scenario that I hope happens and I hope the dating app with the AI
Speaker 2:companion though.
Speaker 1:Yeah. Yeah. Basically. Yeah. But the AI it's the her scenario.
Speaker 3:What if you're still together but your AI versions have broken up? Like are
Speaker 1:you Yeah. What happens then? Well then you get a warning or it contacts like a divorce lawyer or something for who takes a fee on that. Who knows?
Speaker 3:I think there's a lot of fun stuff to Yeah. Explore here. And, you know, one of the other random ideas I had was I I called it peanut gallery. And the idea was that, you know, the dirty little secret about why we go back to products Instagram and others, oftentimes the traffic goes up after we have posted content because we wanna see who else saw our content.
Speaker 1:Oh,
Speaker 3:interesting. Playing off that off that idea, you know, imagine a social platform called Peanut Gallery where you post your own content but no humans are allowed to comment on it. It's all these, like, personas that are, like, you know, tightly tightly defined personas that are commenting and arguing with each other and discussing. And you go back to see, like, how this AI is engaging with what you posted and maybe that becomes the voyeurism of seeing how other people's, you know, contents were forming. I mean, these are the fun crazy things that must be explored to find, you know, this edge that will become the center of social.
Speaker 1: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 Justine Moore at Andreessen's 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
Speaker 2:but I don't know. Feels inevitable that in many ways bots are a feature of It feels like bots are a feature of X now. Right? They they have not been eradicated. Yeah.
Speaker 2:They're still here. They're maybe hidden under some
Speaker 1:mean, I that's the story of Reddit, right? Early Reddit days were, you know, it was all the Reddit founders posting to seed this thing. So if you think about a social network that needs to onboard you, there was that original Facebook thing where like if you could get 50 friends they'd keep you on the platform forever. Know, if you show up and there's like a couple bots that are just like, hey, good job. You know, hey, keep posting.
Speaker 1: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 the the war between Meta and OpenAI in the in the talent race and all the trade deals has been, you know, front page news for the last couple weeks. I'm Jordi's been saying that they that the the product that Meta might wind up going after is less like a direct ChatGPT knowledge engine and app that feels more competitive to Google. And it might actually be something more like companionship and and chat since that
Speaker 2:That feels like the real threat of of if there was an app outside of TikTok that was going to take user minutes from the enter these sort of like entertainment social minutes from from the meta ecosystem, it would it would be these sort of AI companionship which function as entertainment
Speaker 1:Yeah.
Speaker 2:The sort of social experience, which is meta at its core is is effectively a social entertainment company.
Speaker 3:Yeah. And, you know, you think about all the rules of successful consumer products. They make us feel good about ourselves.
Speaker 2:Mhmm.
Speaker 3:You know, they they are sort of social lubricants and that they help us get in get connected to others in ways that we may not be able to do and be comfortable with in the physical world. And you kinda go through all the list of things and you realize, like, AI, there's an opportunity to to really radically, you know, attack those vectors and make people have a really fun engaging entertainment experience or a social experience. So it's not a surprise that Meta's gonna innovate in that space. You know, I I do also kind of wonder when I remember when we all remember when Facebook acquired Instagram and then, of course, when Facebook acquired WhatsApp, you know, they were acquiring network effects in essence, right, around messaging and images. And I wonder now, you know, now it's like it's a talent war.
Speaker 3:I mean, maybe AI is less about AI is not really a network effect per se. It's more of like a talent driven
Speaker 1:Mhmm.
Speaker 3: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 it's Yeah.
Speaker 2:I think the the framing that I've been thinking about is is these are basically, like, unauthorized acqui hires to some degree where you're basically saying, yeah, that these 10, you know, if a company is doing an aqua hire in general, there's like, we know this group of people is good at this thing and we wanna do this thing and let's bring them over here.
Speaker 1:Yeah.
Speaker 2:And so the premium on talent that we've seen in the last couple weeks could just ultimately be that it's it's looked at as a you're buying a team, which is is more valuable than the individual parts. They just happen to all get chopped up
Speaker 1:in chatter around Alex Wang and Scale AI. People haven't been saying, oh, well, Scale AI is gonna be, you know, this juggernaut in thirty years, but Alex Wang is a generational talent. He'll be around in thirty years. And so the the nature of what scale does might change as, you know, we get to more, you know, data driven or like just purely 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.
Speaker 1:And that that business, it's not the same as Instagram where it's like, okay, there's a network here and so there's like this asset value in this, but it's yes, more much more talent driven. And so that's why you see all these people coming together, but it's fascinating. It is interesting to see if if Meta 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. And why not?
Speaker 3:Yeah. And and make ads more efficient while they're at it.
Speaker 1:Yeah. For sure. I mean, that's the crazy thing about this is like $100,000,000 doesn't take that much to generate a $100,000,000 if you make the ads point 1% more efficient. So it's all economically rational, but we just haven't seen it in tech yet. This and that's why these big numbers feel like, oh, we gotta talk about this.
Speaker 2:A little bit of a tangent, but have you thought about how how LLMs now are immediately and and I I'm assuming pretty aggressively shaping actual human communication. Like, right now we're in this period of m dash gotcha. You wrote that. You wrote that, you know, with and people that love the Em Dash before Probably
Speaker 1:were disappointed.
Speaker 2:Disappointed. But at the same time, it's not like you see that people calling out the Em Dash other places on the internet outside of basically teapot. And I just wonder, we're in this dynamic now where we have the most prolific, 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 a in in minutes. Right?
Speaker 1:Yeah.
Speaker 2:And it just feels like we're we're potentially in this interesting fly like, flywheel that's just gonna keep, you know, spinning.
Speaker 3:I a couple of thoughts. I mean, 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 lowercase and short sentences, like, that's what your experience of any information retrieval and conversation will be, and that might be different from mine. So I do think they'll all become more personalized for us in these, like, dramatic ways.
Speaker 3:I also, though, wonder, just like when music becomes generic and, you know, then some some some band or some star, like, just does something entirely new and creates this new genre. I mean, in in similarly with writing, like, well, 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 and keeps you engaged, you know, what what 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 upon command. So it's, it's fascinating. I mean, technology has always had this impact on us and culture.
Speaker 3: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 of culture change are happening more quickly. And so it's something I'm looking at as well. It's it's an interesting question.
Speaker 1:I'm I'm generally still long tool. Like like, this is a tool. Creativity is still undervalued or or 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.
Speaker 1: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 be even like that. Do you remember horse ebooks back in the day? I don't know if you remember this account, but it was it was like said to be just randomly algorithmically generated from these ebooks.
Speaker 1:But it turned out that there was actually a human writing it, and there's been a few examples of that where or or or the stuff that does go viral that's like AI generated is like, oh, it's hallucinations. And so the the fascinating part about it is not the underlying product. It's the fact that it's generated by
Speaker 2:AI. Yeah. It is interesting that we have this this band, the Velvet Sundown, I think they're called. Have a million listeners on Spotify a month right now that's Yep. That claims to be fully AI generated.
Speaker 2:And it's funny that we got that before a prolific poster Yeah. That is fully AI like
Speaker 1:That has a 100,000 followers and is like popular
Speaker 3:I mean, we we talk about, of course, like taste being more important than skill and I think you're you're tuning into the fact that Ken LLM's 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.
Speaker 3:What? That wasn't clever. You know, do you just lose does that does the is the credibility of that account gone? So I I think humans are good at humans with good taste are good at knowing, you know, yes and no, yes and no, like what should and shouldn't be shared or or said or written more consistently. And I wonder if I wonder if, you know, LMs can do that.
Speaker 2:It's also a memory. It's a context thing.
Speaker 1:You you to
Speaker 2:to be a good poster you you need to really understand the fullness of the zeitgeist and where and the current thing and and and all yeah. These different meta trends and
Speaker 1:Yeah. And it feels like even the longer context windows are still losing focus because there's some sort of fundamental limitation of the transformer. We talked to Dorcasch 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.
Speaker 1:I'm still looking for that. I keep coming back to that idea of the Lee Sedol 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.
Speaker 3:Well, I'll tell you, like, each time we have these conversations, the whole world will be different. I guess that's that's,
Speaker 1:like, thing we're learning these
Speaker 3:days in terms of the pace of change. Yeah.
Speaker 2:Good to see That's great. As as we accelerate, it goes from monthly to every couple weeks.
Speaker 1:Weekly, daily. Weekly, daily.
Speaker 2:And then and then every hour, they will be full feeling the acceleration. But
Speaker 1:This has been fantastic.
Speaker 2:Great having you on as always. Looking
Speaker 4:forward to
Speaker 2:the next one.
Speaker 3:Sounds good. Till next time.
Speaker 1:We'll talk you soon. Bye. Next up, we have Nathan Lambert coming in to talk about an American deep sea project. But first, let me tell you about Bezel. Go to getbezel.com.
Speaker 1: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 sea llama. How are doing, Nathan?
Speaker 2:Boom. Good to meet you. What's going on? Good.
Speaker 7:Thanks so much for being this format. You guys got a loaded lineup today. I was like, wow. Got on the same day as Ben. Ben is, like, the motivation for why I started writing about AI.
Speaker 7: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.
Speaker 1:Yeah.
Speaker 7:He's a competitor.
Speaker 1:He's squawking.
Speaker 2:The Ben Thompson for AI is definitely But Ben I mean, it is
Speaker 1:a little bit different in there's terms of so much different space in terms of whether you're going after the business models or the actual infrastructure or or what you were writing about earlier with kind of the 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, LAMA 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.
Speaker 2:Thankfully, were talking to the CEO of Grok with a Q.
Speaker 1:With a Q. Because at
Speaker 2:that very moment there was a different Grock. Yeah.
Speaker 1:Hallucinating and and at scale.
Speaker 7:Yeah. There should be more Grock news later if tweets are to be believed. But the Yes. American deep sea thing is largely a forcing function to make AI research eco make the AI research ecosystem in The United States catch up, think. We were talking about niches and lanes and, like, Ben Thompson, it's the biggest one.
Speaker 7: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 I lead this with a couple other people as we keep track of all the open models and data sets, mixture of research and start ups are releasing. And there's then 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 wanna build on Chinese models.
Speaker 7:And that's one thing. And then also, America should just take pride in what has been a great, like, research ecosystem, and we want to have that and own it whole stack, which is otherwise most of the leading AI research is gonna 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. Mhmm.
Speaker 7: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.
Speaker 1:DeepSeek versus Quen. I feel like DeepSeek had this like crazy viral moment. But now you're saying that Quen's been kind of on a on a, you know, compounding growth for a while. What's the dynamic between those two companies and and what's driving Quen's adoption over DeepSeek?
Speaker 7:Yeah. So this is a great example of one that I've 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 Mhmm. Have been switching to permissive licenses. Mhmm.
Speaker 7:These are models that anyone could pick up and use and dump into a product that they wanna ship. A lot of startups use these things. See all the clouds hosting them. That's one thing. Not a lot of people actually fine tune DeepSeek because it's huge.
Speaker 7:It's already so good. Like, what are you gonna 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 train, and from size scales as small as like 500,000,000 parameters up through these bigger MOE models. So for a researcher, it's pretty much or somebody trying to build a really niche product and something at the cutting edge, it's like Quen 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 deep seq is super hard.
Speaker 7:And we've seen this with LAMA two and LAMA three were much closer to this quen approach, when it was seen both in the data that we have and on the ground is like LAMA was the open standard for research. I used to joke around that like Hugging Face is just gonna 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. Mhmm. But that's kind of been a big, mass shift and attention shift in the last few months where
Speaker 1:So what do you expect out of Meta with, with with the new talent acquisitions? And it seems like a redoubling of the efforts on AI broadly, super intelligence. But maybe, you know, the the the strategy of Llama could be shifting. Are they even are they a lot I've often thought that, you know, right now with the dominance of DeepSeek and Quen internationally and kind of these like jump ball half ally countries, frenemy countries, Mark Zuckerberg should be like a national champion. And and we should be pushing Llama, you know, at a national level all over the world.
Speaker 1:But what do you think is gonna happen there?
Speaker 7:Yeah. So there's two things. Mostly, I I mean, I'm gonna gossip as anyone will and what will It's happen with very fifty fifty. I think with the leadership they brought in that there's less attention and value you're observing behind, the open thing. So Zuckerberg historically has been very pro open.
Speaker 7:And if more of it is shifting to other people, they kind of loosen that, vision. If other people are 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.
Speaker 7:I don't think that's the outcome that I expect to happen, which is what I'm saying, there's a a cheap off ramp if you take the comp packages for a couple of those researchers. Like, 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 that has all these eyes on their back, and then just have research happen on these things.
Speaker 1:What are you advocating for? Are are you advocating for nonprofit taxpayer funding? You know, we've we've seen a nonprofit before, and it turned into a for profit. How are gonna keep this in a for profit? And then how are we actually mustering the the will?
Speaker 1:Because, yeah, it sounds like, yeah, just put a $100,000,000 into a nonprofit. Like, that's a lot of money. Like, that's This is where
Speaker 7:we get to the nitty gritty. Yeah. I work at the Allen Institute for AI and with AI too, which historically is even more academic than OpenAI was. So I think culturally, there's there's not that type of feeling the AGI, like, that Ilya had on the scaling deep learning. That was kind of the thing that I think drove them from the start.
Speaker 7:They were like, we need so much money. So AI too is set up, it's it's like, you can do digging, but it's so different in that culturally that it could never happen. So if 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. Sure. So it is already half embedded in the ecosystem.
Speaker 7: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 sitting on the ground where I am or trying to train our next model, like, it's pre training now. Mhmm. It's like, we just need more compute. So if we double or triple our compute, America will have x or, like, these open models will be just x percent better.
Speaker 7:Yeah. And it's it it seems tractable. It's just hard to get the right it's it's a lot of politics to get these things in place.
Speaker 1:Yeah. I mean, I I I guess to to dig in there, I'm wondering if, like, you know, the the initial, like, economic model for Lama was always in a little bit of debate as a recruiting effort for Meta. Is it their desire to decouple and not be dependent on Gemini or OpenAI or Anthropic and just save costs there. There were a whole bunch of different, you know, economic motivations. But I'm wondering if, like, in the long term, we don't see something like, you know, a Red Hat Linux where it is a for profit company maintaining a non profit or an open source software package or even, I mean, you can run Linux on Azure now.
Speaker 1: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, you know, AWS or Microsoft open source something that that actually competes significantly with DeepSeek and Quen, but is still within the typical corporate structure?
Speaker 7:I think it'll come from the the biggest motivators have to be NVIDIA and AMD. So the long tail of if Quinn is going to keep doing this and then it's something like Huawei they start working with Huawei. This like Huawei libraries, they want to support them. And then US researchers are starting to dig down into those levels because they wanna understand how these models were trained. So those are the people that have the most direct, exposure.
Speaker 7:It would be NVIDIA and AMD. It's cheap for them to do. They get the benefit of the researchers keep working on their hardware and software ecosystems. There are, like, outlandish stories that you could tell about open source AI where that type of thing could emerge, but mostly they revolve technical breakthroughs that you can't plan on. Like, 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 health care and there's kind of this open marketplace for model parts, and then that's all in the open.
Speaker 7:And the person that kind of, writes the software by which those, like, pieces of models are combined and standards by which those happen, that could exist. So there's kind of wacky ideas, but I think that that's a lower probability outcome. And it's just like, let's get good, big transformer models trained that anyone can download and poke around at and just get more people involved in AI research that we have complete control over.
Speaker 2:Great. Last question for me. What are you expecting out of OpenAI's open model?
Speaker 7: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 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 agents or a certain size of reasoning model, it's gonna be this type of thing where it's a certain niche and it it works really well for it, where it could be like a like a deep sea style release where it's just super strong model that people can plug into real world products and applications, but it's not gonna be this Quen or Lama suite of models that researchers look at for all sorts of things. And OpenAI has been saying that they hear the license critiques of Lama and stuff, and they're gonna commit to the actual, like, permissive license, which are things like Apache or MIT that these Chinese orgs have started using again. Which I think is a nice thing to kind of make all of that simpler, to just you release a model, it it doesn't have terms and conditions on it, like Meta's not trying to say, like, your legal department has to talk to us or avoid these use cases.
Speaker 7:It's just get people using the model that your company released and take a simpler approach.
Speaker 1:Makes a lot Anything of else, Jordy?
Speaker 2:That's it for now.
Speaker 1:Thank you so much for stopping by. This is fantastic.
Speaker 2:Thank you for working on all this.
Speaker 1:Yeah. We will talk Thank you, Leslie. Looking forward to the release.
Speaker 2:Cheers, Nathan. Have
Speaker 1:a good one. Bye. Up next, have Richard from you.com coming into the studio. Do we have any more ads? Go to 8sleep.com.
Speaker 1:Get a pod five, five year warranty. Thirty night risk free trial, free returns, free shipping at 8sleep.com.
Speaker 2:I'm basically
Speaker 1:You're in a hole.
Speaker 2:My household is is sleep shambles.
Speaker 1:Well, let's bring in Richard. But Talk to him.
Speaker 2:Putting up the fact that we're doing this on five hours of sleep consistently Impressive. Does it all.
Speaker 1:How'd you sleep last night, Richard?
Speaker 2:How'd you sleep?
Speaker 1:Good to meet you.
Speaker 5:Hey, guys. Nice to be here. I slept alright.
Speaker 1:That's good.
Speaker 5:I'm fine.
Speaker 2:You would have slept better on an eight sleep. So we'll work on that offline. But great.
Speaker 5:I did I did buy it. I I I appreciate it just I think it's better if my body sets its own temperature.
Speaker 1:Oh, wow. Interesting. Wait. Would you mind kicking us off with the introduction on yourself and the company?
Speaker 5:Happy to. Yeah. I'm Richard. Did my PhD at Stanford, brought neural networks into the field of natural language processing, laid a lot of the groundwork for what now is ChatGPT. Was a professor also on the side at Stanford for a couple of years because no one was teaching neural nets, like transformers and so on to students back then.
Speaker 5:This was 2014 to 02/2018. But my main job was starting MetaMind. Started to made it very easy to train neural networks for other companies. We got acquired by Salesforce, became the chief scientist, and after two years executive vice president running most of the AI efforts, starting the Einstein kind of suite of things and so on, build out the research team there. In that research team, we ended prompt engineering, paper cited by the early GPT papers from OpenAI and others.
Speaker 5: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 I also started AIX Ventures. It's a relatively small venture firm, about half a billion AUM. I've invested in early stage AI companies.
Speaker 1:It's not that small. Half a billion AUM is pretty pretty solid. Congratulations.
Speaker 2:A humble 500,000,000 of AUM. Humble.
Speaker 1:Yes. On onyou.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 how high are the walls in the beautiful gardens that we have all tended to with our Slack installations and our Google drives?
Speaker 1:And this feels like the logical thing that, you know, yes, I own my data until I wanna give it to you or literally you.com.
Speaker 5:That's right. Actually, you know, as a startup founder, you have to remind yourself every crisis is an opportunity, and the opportunity here is actually that a lot of data is in silos. Mhmm. And those companies don't wanna give it out, but they do need to make it useful. And so one of the many things that we've learned over our, like, changes and focus deeper deeper on enterprise is that doing good internal search is actually quite hard and quite useful.
Speaker 5:And so we're partnering with a lot of companies and do search over their entire archives of decades and also really up to date things for publishers and insurance companies, like, pretty gnarly complex problems. And combining that with web data, which also has its own complexities and a lot of, you know, like, folks are, in some ways, trying to pay people in news, which makes a lot of sense, but also 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.
Speaker 5:And so merging all of that together to make companies more productive is what we now focus on.
Speaker 1: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 droppingyou.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, you know, purchasing SaaS from?
Speaker 5: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 wanna have another copy somewhere else.
Speaker 2:Oh, we do.
Speaker 5:Like and then there's some data where, you know, 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. You you know, it's just too expensive for each company.
Speaker 5:But then in some cases, it doesn't 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.
Speaker 1:And Yep.
Speaker 5:It's been a very exciting partnership already.
Speaker 1:A ton of sense.
Speaker 5:They also enable all their LLMs to have web index access.
Speaker 1:Okay. Yeah. That yeah. That that makes a ton of sense. How are you feeling on acceleration, deceleration?
Speaker 1: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?
Speaker 1:Obviously, even if the there's also the take that, like I don't know if you agree with this, but, like, even if the models plateau, there's still so much enterprise value and so many problems to go solve. But I'll let you answer where do you stand.
Speaker 5:Yeah. I'll try to keep it short because I could 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 recent information, you know the company context and all of that stuff. So there is already a lot of low hanging fruit.
Speaker 5:At the same time, it's actually quite exciting for the researcher in me that, you know, hasn't fully died yet as an entrepreneur and CEO for many years. Like, that it's time again for research. Like, in many ways, we've knew we've known that you need large neural nets with a lot of data on GPUs and highly paralyzable training, and you want the whole thing to be ideally end to end trainable in some fashion. It's sort of been known ingredients for over a decade now. And indeed, we've crossed thresholds by scaling all three data, compute, and and model size.
Speaker 5: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 too. But then you cross a certain threshold, you get these emergent intelligent properties. And so what that means is now is the time again for actual research, not just engineering and scaling things up and throwing more data and better data at it and bigger GPUs and and and all of that. But to actually go back and say, like, okay.
Speaker 5:What is true intelligence? How can we get to superintelligence? What does it mean for intelligence to increase exponentially for a certain amount of time? I think there are actually different dimensions of intelligence too that you have to look at separately, and some do have upper bounds. And some of the times, these upper bounds are astronomically far away, like brow grounded in physics.
Speaker 5: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 we have all knowledge about the universe. You know? Intelligence should have a lot of knowledge, and it will take us a while to get to as much knowledge. And the balance of how much knowledge you can collect are rooted in physics and the speed of light cones around all the sensors you can have.
Speaker 5:So there's basically a time again for research, and that's exciting.
Speaker 1:So, yeah, it feels like we're kind of paradoxically in an AI bull market summer in the Stripe dashboard or in, like, 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 OpenAI.
Speaker 1:Do we think that the next Transformers coming from or the next major research breakthrough comes from a foundation lab or a 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?
Speaker 5:I do think you cannot build another OpenAI by just building an LM. The LM was the one thing that worked out for OpenAI after they spent hundreds of millions on robotic hands
Speaker 1:Mhmm.
Speaker 5:And on DOTA, like computer games and reinforcement learning and all these other projects. And one of them actually worked. And so if you wanna replicate that kind of success and do research again, which I think is the the time is now, it does make sense to have that kind of entity, and 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.
Speaker 5: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 advisers 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 we'll 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.
Speaker 2:What I have to ask because it's so current. What do you what's your thesis on what happened yesterday with Grok? How how do you have that big of a general, I don't know, alignment. Oopsie.
Speaker 1:So oopsie daisies.
Speaker 2:In in prod.
Speaker 5:You know, I think when you ship very fast, these things are about to happen. Right? Like, people can push them in the conversations into certain directions. You sample from the same model multiple times. You get different answers.
Speaker 5:And I think if you try to be sort of a, like, free speech maximalist, which on many levels makes sense, but out there's a lot of funky speech out there,
Speaker 1:you know,
Speaker 5:with no guardrails whatsoever, it will go into those very dark places.
Speaker 1:Yeah. Makes sense. What are
Speaker 2:you expecting, since it's in six ish hours, I I believe? I, hopefully, they're still announcing and launching Grok four tonight. What are you expecting out of Grok four in terms of, any benchmarks aren't aren't the right
Speaker 1:Yeah.
Speaker 2:Even even, way of thinking about it, but but in terms of progress?
Speaker 7:My hunch is it'll be
Speaker 5: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.
Speaker 5:Mhmm. It'll be probably I mean, we won't know for most of them, but more parameters and
Speaker 1:Mhmm.
Speaker 5:And so on. But maybe not, like, completely novel research that has a capability that no one else has.
Speaker 1:Sure. Yeah. That makes sense. Last question, and we'll let you go. What are you finding most exciting on the investing side?
Speaker 1:For me, $500,000,000 fund, it feels like the foundation model the big training runs, the multibillion dollar round strip has kind of sailed on that front. So maybe the time is for application layer investing. But what what what are you seeing? What are you excited about?
Speaker 5:Yeah. We've we've been actually very fortunate that AIX Ventures to not have like, to avoid it some of these massive rounds. The way I described that is that not every company that raises a ton of money in a very early stage, like, is bound to fail. At the same time, you'd basically combine a seed stage risk with a late stage return in many cases, and that, you know, and expect the 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 Mhmm.
Speaker 5:And and Windsurf and VPIACs.
Speaker 1:Congratulations. Those are great companies. Yeah.
Speaker 5:Yeah. These are all, like, companies we invested in. There's in the seed round. Invest in Perplexity and Flow and Whisper, Ambience, like, bunch of really amazing companies. And so I think there are only one or two dozen foundational model companies that the world needs, and then there are thousands of application companies.
Speaker 5: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 to have a major moment, thanks to AI. Now software is faster than hardware, and hardware is faster than wetware people and biology.
Speaker 5:Right? And so it takes longer. The cycles are longer, but you have enough data. You have the right compute, and we can eventually simulate more and more of biology and then make it into not just, oh, memorize what nature has kind of happily evolved towards, but make it an engineering discipline.
Speaker 1:Mhmm.
Speaker 5: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 and reach over the next few decades, And I think that will be a massive group of applications.
Speaker 1:Amazing. Well, thank you so much for stopping by. This is a really great conversation. Yeah. We'll have to be back later.
Speaker 1:I love
Speaker 2:again soon. Happy. Have a
Speaker 1:good one talking
Speaker 6:to Cheers, Richard.
Speaker 2:Thanks for joining.
Speaker 1:Good chatting. Next up we have the founder of Moon Valley coming on the show talking about generative imagery. We're gonna pull up a Very very cool stuff. So welcome to the stream. Hopefully, can pull up this website because we've fully passed the uncanny valley.
Speaker 1:Don't you agree? I mean, the the this are you are you on the website? Can we pull up the website really quickly and show the the the video? So so everything on your website, this is AI generated. Is that correct?
Speaker 8:That's right. There's some, like, After Effects stuff on top
Speaker 1:But Okay. Of
Speaker 8:Yeah. It's basically all AI Mary generated.
Speaker 1:It's remarkable. And I feel like it's under discussed. Anyway, please introduce yourself and the company because this is Yeah.
Speaker 8:Absolutely. Thanks for having me. Great to great to meet you guys.
Speaker 2:Good to meet you.
Speaker 8: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 it's kind of a unique structure. You know, a good chunk of our team are world renowned researchers Mhmm. In visual intelligence primarily, but, you know, our our focus in a specific level is is we're building the biggest and the most capable production grade generative video models.
Speaker 8:Mhmm. 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.
Speaker 8:And so it's, like, kind of a ground zero, and and we have, you know, folks that have won Emmys that have been nominated for Oscars on the team. And and so we've just kinda brought both worlds together to figure out how do you take this tech from being, you know, kinda interesting research and and, you know, cool things that you can share on on x and actually become things that sort of push the boundaries of, you know, what we sort of we think of it as like movies and stuff, but these are sort of limited abstractions, more of just like visual media broadly, and and kind of the artistry around it.
Speaker 1: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?
Speaker 8:Yeah. You know, it feels a little bit maybe it's like a bit of a post chat GPT phenomenon, but I I do think that increasingly foundational companies, quote, unquote, are having to think a lot more about the application layer. Mhmm. And and I think that that's only gonna continue to be the case. Like, I think a, foundational research, which, you know, and you kind of alluded to it in in your chat with with Richard, but, like, there's an element of commoditization that's happening.
Speaker 8:Right? There's an element of of you'll get to there's a point as and this applies to visual media as well where the 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 you'll continue to invest in that. But to drive the same amount of, like, business value as, like, you know, a GPT four style leap, that requires kind of thinking about other other areas. So and and the other piece for us is, I think, it's it's different with things like LLMs, but with with visual and video in particular.
Speaker 8:I think one of the issues is that, like, research labs and and technology companies that have been in this space, they have been largely divorced from, like, the end practitioner in in in a lot of ways. And for LLMs that are so such general technology, I think that makes sense. But in our case, you know, we're building tooling that filmmakers 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, you know, kind of trickling down to to the target user.
Speaker 1:Yeah. A lot of the crazy technology vision of the future is kind of just like you're gonna with one prompt just be like, give make me a new Top Gun movie and it'll just one shot it. Clearly gonna be a while until we get there. Yeah. Where are you actually seeing value or demand from Hollywood, from filmmakers?
Speaker 1:Because, you know, AI is so broad, it could mean just like pull a green screen key better, do some rotoscoping, do some camera stabilization. There's been AI tools in filmmaking for a long time. They're obviously ramping up set extensions. There's so much that you could do in the three d pipeline, the VFX pipeline, and two d pipeline. Where are you seeing actual adoption?
Speaker 1:Where are you excited for there to be adoption in the next year or the year after?
Speaker 8:Yeah. For sure. I I think, you know, it's a good point where, especially in video, think more than in other kind of fields, there has been this, like, you know, when 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 we're gonna move towards.
Speaker 1:And Yep.
Speaker 8: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. Mhmm. 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 ChadGPT, you know, publish literature. Problem is nobody's gonna read that literature.
Speaker 8:Right?
Speaker 6:And, like, that's the that's kind
Speaker 8:of the missing piece. You know?
Speaker 1:People have done it. People have and if you go on the Kindle store, barely, it's, like, swamped with AI.
Speaker 8:It's, 90%.
Speaker 1:Yeah. And and but, like, every once in while, these things break out, but it's more of, a novelty. Like, oh, wow. Like, somebody actually did this thing. Like, let me leaf through it.
Speaker 1:Wow. Yeah. It's you know, they hit the periods and there's tons of m dashes.
Speaker 2:I think it might just end up reflecting human creation where it's ultimate 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 Right. That's that's Right. That's gotten popular in the last month. And so it's Yeah. I just think it's like this ultra power law potential.
Speaker 1:A lot of media properties also and art generally is also very story driven. Like the story behind it. Like part of the reason why I like to go to this Tom Cruise movie is because I've heard the story that he's doing the stunts. Because we
Speaker 3:know who he is
Speaker 1:and like We know who
Speaker 8:he is. We know the story
Speaker 1:behind the story. And and that's what drives a lot of value in art is like, oh, this this painter really spent years doing this thing and he This stuff cut off to take this. Year. So that this painting has a crazy story behind it. It's valuable even if like my kid could do it.
Speaker 1:It's like my LLM can do it. But, yeah, your LLM didn't. Yeah. But I A 100%.
Speaker 8:Yeah. I 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 you can use a lot of these tools. I I think that there's like kind of lowest common denominator content, like what Yeah. You know, what you don't see as much anymore is like blog spam that was just like you know, crazy in the twenty tens. Right?
Speaker 8:I remember that. Replaced with AI. Yeah. Exactly.
Speaker 2:Yeah.
Speaker 8: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 Yep. 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 that's it's so you know, there's such a big gap there. Totally.
Speaker 8:So so we think about it, like, internally, it's the same way. We we, you know, like, John Carmack calls it, like, power tools, and and and that's 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, it's actually it's a continuation. Like, there a lot of the things that AI video enables, it's not novel. Like, you know, you'll hear studios that we talk to, they'll say, you know, a research company came to us and they said, hey.
Speaker 8:You can do all these new things with with these video models, and they have to remind them that, no. We can do all of these things. Right? Like, what what we're talking about here is potentially doing them in an easier, more flexible, more powerful way. But with VFX, like, there's nothing you can do today with in in terms of, like, the output that you're creating that you couldn't do with VFX.
Speaker 8:It's it's a workflow thing. Right? Like, we're just making that process easier, that process more affordable, and and that kind of thing. So It's SaaS.
Speaker 1:Yeah. We we look
Speaker 2:at We're selling we're selling SaaS. We're selling SaaS. Yeah.
Speaker 1:That's what the market
Speaker 2:What what about what you know, it's been interesting to see x is its own kind of universe in terms of AI content. What what gets picked up? A lot of it ends up being stuff that that's getting made and shared on TikTok or other platforms. And there's been this idea of like an AI content creator which is like a new personality that is just being generated by a human that's creating, you know, using a a video or an image model to generate generate this person, you know, going about their life. And then there's the sort of like the the what's considered the slop, like the Italian brain rod, all all that stuff.
Speaker 2:What about like, do you expect to see like an entirely new class of filmmakers in like, you know, like basically like net new YouTube channels, things like that of people that are just at, 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 Mhmm. Distribution to zero and you know, mobile devices lowered the cost of content creation to zero or effectively zero. And now, the the cost of of producing films is not gonna go to zero but but may as well on a long enough time horizon. And so, yeah, I'm I'm curious when you think that moment will be where we start to see kind of the the the velvet sundown equivalent of of Right. Of film filmmaking.
Speaker 8:Yeah. I would say that, like, we're a lot closer than people think. So, you know, we like, Moon Valley's models, like, because we have, you know, clean models or models that have been trained on license data, they've been the first models that studio, you know, legal teams have really, like, allowed them to use. And so that's been part of why, you know, when you heard about Sora, like, a year and 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.
Speaker 8:I would say that, like, the the the point where the technology is capable of doing that kind of thing, we've already reached. And there's places it's there's pockets of the world where especially, like, smaller film communities in different parts of the world where you're starting to see, like, real world productions. Often, people aren't necessarily aware of it, but very large parts of not just the pre and post production, but even the production process itself are being driven by these models. Now I think that there's, like, beyond especially in this industry, beyond the technology, there's a lot of other barriers to adoption adoption here. Right?
Speaker 8:Like, you have to it's 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 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.
Speaker 8:And that seems to be where a lot of the focus is. To us, the area that we're the most excited about is that middle, where you essentially have this band of millions of creative people in the world, like artists, people who have real taste and talent and ability, but they don't have necessarily the access and the infrastructure to do that. Right? And that's not necessarily, like, you know, we have a one of our alpha users is this he's a a filmmaker in Senegal, and, like, he's been he's been a filmmaker for over a decade. His sting his thing or, you know, his his focus is on doing, like, music videos for local artists, and and it's like this kind of funky, like, Afrobeat style, you know, West African kind of flavor.
Speaker 8: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, 10,000,000 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.
Speaker 8:It's like the independent filmmakers who today, unless you're friends with one of the top five studios in the world, you have no capability of making a big budget production. Now you'll be able to do that. Right? And that's not just, you know obviously, this individual is is one example. But for instance, we have, like, somebody like Natasha Lyon, who we work really closely with.
Speaker 8:She's, you know, an industry insider. She's a a, you know, one of the the kind of top people in the industry today. But she's working on this new movie that's, like, she's been leveraging AI to help do it because this has been something that she's wanted this is a movie she's wanted to make for well over a decade, but she just couldn't. She would do it. Like, she talked to the major studios, and it's like, hey.
Speaker 8:It's gonna cost us $30,000,000 to do this. Right? And and then we we just can't we can't do that. Now it's like, well, if I can suddenly potentially do it for $15,000,000, now I can, you know, I can make this thing happen. Right?
Speaker 8:And and so it's there's there's there's this, like, idea that you'll be able to do, you know, movies for cheaper, but really what we're seeing in the studio is a, existing movies, you're now just doing more than you expected to do before. You're now having to compromise less. Like, directors aren't saying, hey. I had a $75,000,000 budget. Now I'm gonna do it for 50,000,000.
Speaker 8:They're saying, hey. With my $75,000,000 and my team, I'm gonna go and now do all the things that I couldn't do before unless I had a $100,000,000 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 greenlit because they just couldn't get the budget. Right?
Speaker 8:Now, suddenly, you'll have a lot more of that. So that's, like, high level how, you know, I 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 and, you know, I 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.
Speaker 2: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 $100,000,000 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 you know better margins themselves. So very exciting.
Speaker 1:Yeah. Yeah. This is awesome. Thank you so much for stopping by. Hope you have
Speaker 3:a great
Speaker 1:rest of your day.
Speaker 2:Yeah. Come back on when you
Speaker 1:have Talk to you soon.
Speaker 8:Awesome. Thanks for having me guys.
Speaker 1:Talk to later. And that is our show for today. Jordy, do you have any other breaking news you wanna share?
Speaker 2:Breaking news Brandon Jacoby. Well, I guess now is a good time as any for some personal news after a wild chapter at x. I've officially wrapped up my time there. I'm extremely proud of the work we did and you'll see more of it soon. More to come on what's next dot dot dot.
Speaker 2:Brandon has been a dear friend for a long time and I'm excited for his next chapter.
Speaker 1:Me too.
Speaker 2:And I'm gonna miss being able to text him when I have bugs. But Tyler, you're up next. Expect some bug reports but yeah, fun show. I'm trying to think if there's anything else that we that we missed.
Speaker 1:I don't think so. We hit all of our ads. Chamath was saying that Meta switches to Sonnet for coding instead of using Llama that they had fine tuned on Meta's own code base. Now they're just one shotting everything with Sonnet. So very interesting.
Speaker 1:Since the change code suggestions are generally better, engineers can change back to LAMA and occasionally do when the fine tuning makes a difference. Internally, this is a big change given how big how heavily Meta has invested in the 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 it doesn't want to hold back its engineers.
Speaker 1:So very interesting that they're they're using Anthropic and just kind of letting it rip. Letting it rip.
Speaker 2:The topic is cooking. Yeah. Last post to end it from at Jarvis Best. He says, he's sharing a screenshot of Linda Yaccarino saying after two incredible years, I've decided to step down as as as CEO of X. Obviously, it's a much longer post which we covered earlier.
Speaker 2:And Elon just comments, thank you for your contributions. Jarvis says, LMAO, cold as dry ice. Wow. Anyways, at least cordial.
Speaker 1:Yeah. At least they were cordial. Leave us five stars on Apple Podcasts and Spotify, and stay tuned for our stream tomorrow.
Speaker 2:Can't wait. And hope you have
Speaker 1:a great summer. Have a great evening. Cheers. Bye.