You're watching TVPN. Today's Monday, December 1st, 2025. We are live from the TVPN Ultra Dome, the temple of technology, the fortress of finance, the capital of capital ramp. Time is money. Save both. Easy to use corporate cards, bill payments, accounting, and a whole lot more. All in one place. We have a special guest today opening the show with us, Albi from the Land Down Under.
Probably saw him go viral recently, but why don't you introduce yourself?
Yeah. So I just I actually arrived in LA on Saturday.
Yeah, I'm from Sydney or Wollongong, so about an hour and a half from Sydney. And yeah, I've been building something called Finle which is basically Duolingo for life skills. And I just applied to YC as well with that post on X.
How many views did you get on the application video?
I think it got like 7.8 million. So, yeah.
Hit the Let's hit the gong. Pretty viral for Albi. Well done. Well done. So, give me an example of a life skill that you can learn with your app.
Yeah, I guess like entrepreneurship especially startups and stuff because like in Australia, I don't know about in the US, but school is very entry level. It's not hands-on. I feel like it's just not preparing us for life. Like you do need it for if you want to be a doctor or a lawyer or something, but some kids don't want to do that. And like yes, you do have commerce and computer science and stuff which I am doing as electives, but they're not hands-on and they're very like outdated and like textbook heavy. So I feel like actually learning life skills that you can apply now especially like with AI and everything like if you don't know how to use AI now you're sort of going to be left behind.
Very exciting. What are you hoping to get out of your trip? You're on summer holiday right now.
Well, like my exams just finished before I came, so there's still like two weeks left of school.
How do you think you did?
I think I got like a B in science and like a B in math.
There you go. There you go. Focus focus on the game. Focus on the game. There's really room to grow. But yeah, I guess what I'm trying to get out of it is just to like meet as many people as possible, make as many connections as possible because this trip probably won't a trip like this probably won't happen again for a while. So yeah, that's sort of my goal.
What's the status of the YC application? You've submitted it.
No, it hasn't. It's still like I'll need a recommendation.
We got a Yeah, we can we got we got a long If you're a YC watching this, please go leave a recommendation. Yeah. But congratulations. Thanks so much for coming by. What is the stage of development of the actual application? The product itself. Are you live? Can people go download demo right now?
We're getting like beta testers. But the beta should be launching soon, probably by like the end of this year.
Do you have a wait list? Are you doing email capture yet?
Yeah, like wait list beta testers. We've got like a couple hundred, but yeah.
Very cool. Incredible. Well, congratulations on all the attention. I'm sure you'll convert it into a lot of opportunity and have a great trip. Yes. Great to have you. And good luck with the YC application. Looking sharp in the suit. Looking sharp in the suit. Amazing. Have a good Thank you. Thanks for stopping by.
Before we move on to the rest of the show, let me tell you about Reream. One live stream, 30 plus destinations. If you want to multistream, go to reream.com. And it's been three years since ChatGPT launched. I wanted to reflect a little bit. Everything changed or maybe nothing changed or maybe some amount of change in between everything and nothing. You're more on the nothing changed camp. I sort of agree with you. I was sort of reflecting on like, okay, Thanksgiving's happened. It was Thanksgiving over the weekend. You know, how different is my world? Like there's not a humanoid robot that's cooking for me. And also, even if we had a humanoid robot, I think Thanksgiving would be the day we let the robot sit in the closet because we enjoy cooking. Cooking is a fun family experience. And so, of all the things, Thanksgiving is like the track day of cooking. Like even if you have the robot that does it, you still want to do it on Thanksgiving. You don't want to cook on a random Tuesday when you're busy, you got lunch, you know, all this other stuff. Thanksgiving is the Nurburgring. And I was doing some dishes after Thanksgiving and I felt like it was a good way to kind of like it felt like walking off the pie in a little way. I wasn't walking very far just kind of back and forth. And so yeah, so that hasn't really changed that much for me.
I was thinking I was reflecting more on the agentic commerce thing. It feels like ChatGPT and OpenAI they really are pushing to make revenue from agentic commerce like in this holiday season. And incredible speed of execution like clearly it's a big opportunity if you can figure out how to you know run ads commerce convert take a cut of that that's big. My experience actually demoing it it was kind of interesting like the actual product in ship is pretty good but you can see that the walled gardens are already going up so one place that I like to go to for reviews of products specifically around the holidays is the Wirecutter. Now the Wirecutter their whole twist was they wouldn't rate each product, what they would do is they would pick a category and then they would just tell you what their best product was in that category. Sort of like a cluster max of vacuums. So, they would give you the platinum tier vacuum and then a budget pick. And so, I've always liked the Wirecutter. I think they do a very rigorous job. They were acquired by the New York Times. The New York Times is currently in a lawsuit with OpenAI. And so, if you go to ChatGPT and say, 'Hey,' and I think they're about to be in a lawsuit with David Sacks, maybe. Which we will talk about on the show in a little bit. But if you go so I went to ChatGPT and I was like hey okay pull a deep research report just pull everything from the Wirecutter and tell me every category and every product that's top ranked because then I can just scan it really quickly and be like oh yeah I didn't even remember that that category existed. That would be a great gift. I'll get it and I'll go through the Wirecutter link. I'm fine with that. I'm paying ChatGPT. I'm happy to go and use their affiliate link on the Wirecutter. That's how the Wirecutter monetizes. But it couldn't do it. It couldn't do it. It said, 'Hey, we don't we can't touch the Wirecutter. Like, it's off limits. You got to head over there yourself. Get pop open a Chrome tab, brother, if you want to get over there.' Like, that's on you. Or maybe an Atlas tab. I don't know. But so that had not really changed that much for me.
But the one thing that did really change on Thanksgiving was the discourse. Like the AI narrative has fully arrived to just family and friends.
You mean in the home?
Yes. Yes. In people that don't work in technology that don't their job is not their favorite trough.
Not that more talking about is it a bubble? Where do you think all this stuff goes? The stuff that you know we've been talking about.
Sure.
You're not living in a bubble. You think the average family in America is talking?
I saw multiple newsletters where the whole conceit of the newsletter going into the holidays was how to talk to your family about the AI bubble and how to talk to your family about AI generally. And I think it's real because if you've been watching your 401k over the last year, you've seen a massive spike and then a recent selloff and if you've turned on any news or opened up any newspaper, you've been hearing about $1 trillion and you're like, 'What? A trillion dollars that ChatGPT app they need a trillion dollars to make that thing work right?' And so it is a really big narrative and so I wanted to reflect on like what has actually changed over the last three years and specifically in the Mag 7. The Mag 7 has been on an absolute tear just over the last three years the value as a whole has basically tripled it was a little under $8 trillion now it's over $21 trillion. It's a lot of value created in the last three years. Nvidia was second to last in the Mag 7 when ChatGPT launched. It was worth just $420 billion something there.
Today the stock is up over 10x. Basically, it's $4.36 trillion and up today.
And up despite all the chaos, Dylan Patel was trying so hard to bring that stock down, but he couldn't do it. He's coming on the show at noon. We're going to confront him about his bear posting and whether or not the market.
Funny enough Broadcom is down today.
Okay. Why is that the maker of the TPU?
Oh yeah. Well, I mean a lot of these things it's like it's already been priced in. I mean even when you read the SemiAnalysis piece, you know, a lot of it's like we've been writing about this for months. People have already put this trade on, etc., etc. But I do think that the Nvidia the 10x that's happened has really created some crazy zealots and just an entire industrial complex because there are so many people who heard AI they tried the ChatGPT thing and they were like this is big how do I get in on this I can't buy OpenAI. OpenAI is running away with it oh they need Nvidia chips that's the logical next step they went in Nvidia and they got a 10x and they could have gotten a 10x on like a million, $10 million. Like there's no amount of money because it was already a $420 billion company. So you could put your entire retirement savings in it. No problem. Complete liquidity, right? It's not oh you got to get some SPV. It was really easy.
Siki Chen from Runway was saying that back I think it was 2020 2021 he said he put an uncomfortable amount of his net worth into Nvidia. Yep. And obviously and in near cyan same same story right.
Still underappreciated the Nvidia 10-year fund all it does is buy Nvidia you just by investing in it you can't possibly sell.
God's chosen company.
Yes.
That's what the I think title of the fund was.
Oh really?
Yeah.
That's hilarious. And so I mean yeah there's been a ton of zealots. We're going to talk to Dylan Patel at noon about some of the zealots that have been attacking him. Previously the world's largest company in November of 2022 was Apple and at the time they had a sizable lead over Microsoft, Amazon and Google. Now that gap has closed a bit as the hyperscalers have grown more over the last three years on the back of the AI boom. And it's interesting. I mean, you can sort the Mag 7 by market cap and today you get the following ranking. Tesla, then Meta, then Amazon, Microsoft, Alphabet, Apple, and then Nvidia at the top. And the big question, I think that's on everyone's mind and kind of underpins the horse race that we cover every day on this show is what will that ranking look like in the next three years? Is Nvidia really a monopoly? Is it impervious to attacks from different suppliers?
What does Broadcom have to do to get into the Mag 7?
I don't know. Tesla's sitting at 10 on the market cap. Yeah. companiesmarketcap.com which we are not affiliated with which is just a fantastic website.
Fantastic.
Broadcom is sitting at number six above Meta currently. I don't know. I mean I think you know several years in the $1 trillion club like just being undeniable at that scale. There's also just like a bit of branding like some of the companies that made it into the Mag 7 were I feel like the Mag 7 leaned understandable like not that deep in the supply chain. Even Nvidia was the deepest. Nvidia had the least of like a consumer brand but still a lot of people used the gaming graphics cards. Broadcom is really tricky because there's no consumer angle whatsoever. Consumers can buy Tesla, they can use Meta products, they can buy on Amazon, have a Microsoft operating system, they can use Google, they can have an iPhone, and they can have an Nvidia gaming graphics card. The top 10 right now. Tesla sitting at 10, TSMC at 9, eight is Saudi Aramco, seven Meta, and then six is.
I also think you have to be an American company to be in this like Mag 7 or whatever the hot ranking is like FANG. FANG did not include oil companies, never included international companies because if you go there, then you could be like, 'Oh, well, let's include like the Chinese tobacco company that's worth a trillion dollars or something like that.' Like there are some crazy foreign-owned companies that are if they were independent might be worth a trillion dollars because they just have so much of these assets.
Yeah, exactly. But it doesn't really count because it's just sitting there out in the ether. Well, let me tell you about Gemini 3 Pro. Google's most intelligent model yet. State-of-the-art reasoning, next level vibe coding, and deep multimodal understanding. And speaking of that, Buco Capital Bloke has a post here. Gemini app downloads are catching up to ChatGPT and Gemini users now spend more time in the app than ChatGPT users. People are going back and forth on can Gemini catch up. You know the model clearly very good. The big bombshell in the SemiAnalysis piece over the weekend was this idea which I think has been bandied about before this idea that OpenAI has not done a proper pre-train since 4o and the o5 pre-train kind of got mothballed and so but there was this question about like is pre-training dead. Seems like the Google folks said no it's not and then they went and did a pre-train and Gemini 3 outperformed. Anthropic also pre-trained.
Yeah. I mean, yeah. I mean, we asked Cholto about this and he said, 'Oh, yeah, we're still bullish on scaling.' And he I think actually like Cholto kind of like in the subtext said like the reason Opus 4.5 was good is not because it was a new pre-train, it's because it was RL.
That's interesting. That was your reading. Yeah.
I feel like there's still juice in the lemon of pre-training, but it's not scale. Like we only have one internet. Ilya was correct about that. It's not scaling the size of the pre-train, which is what happened with o5 from GPT-4.5. That was just bigger, I guess. But it does seem like there's little optimizations that you can do on the pre-training, but I don't know. We'll have to dig into it. But I think the thing that no one is debating is the fact that the Gemini 3 as a model with Nano Banana Pro with V3 is just like the actual foundational intelligence is plenty good to be dominant in the consumer AI category. The question is can you actually get people to install the app, use it, can they enjoy it? Do they not churn and go back to ChatGPT? I've been fighting back and forth left and right going into one app and the other. I was getting a ton of disconnect errors with the Gemini app. Even though the model's great and there's some really cool features, I found.
You need to catch up on the product side.
Exactly. Yeah. Yeah. The product side. And so a lot of people are saying like, 'Oh, Gemini team should just the app team should just go and copy ChatGPT's homework and copy all these little features.' I've put out a post that the folks over at the Gemini team actually did turn into bug reports and I think are working on. But it really does seem like it's a sprint to actually create an app that is as sticky as ChatGPT because ChatGPT the app is fantastic and very very very well designed.
Yeah and there's some reporting from SimilarWeb is what the FT is using to track average user minutes. I always find those hard to I mean it must be like Nielsen ratings where they're like polling people or something because you can't get a pixel in OpenAI like you can't get a pixel into the Gemini app.
And are they counting user minutes if a tab is open but I'm not actually in and is this just desktop because that's like completely separate from mobile use.
Desktop and mobile web which I again I don't mobile web.
I don't know. I wouldn't read too much into this data specifically. I would much more look at like what are the structural advantages that we know exist and I mean with Gemini one of them is to that point about the Wirecutter you know where the Wirecutter shows up Google search results you know what company has one bot for scraping everything Google so the Google bot is identifies as one entity so you can either say I'm allowing Google or not and it's a tall order to be like yeah I don't want to be in Google results And so a lot of companies are saying, 'Yeah, I'm good with Google showing up in Google results, but that also shows up in AI search results.' And they can and there are things that companies can do to say, 'Hey, don't put me in the Gemini training data set necessarily, but in terms of just actually showing up.' You've seen it in the Gemini app, it says using Google search. And so if I go to Gemini and I say, 'Hey, head over to the Wirecutter. Find me the best vacuum cleaner.' Google probably can do that. Gemini probably do that. Yeah, test it. Whereas OpenAI is in a fight with the New York Times, whereas Google and the New York Times, like they might not love each other, but they definitely have like an uncomfortable truce, right?
A funny Gemini integration that I've used is that you land in a hangout and you just say, 'Who is this person? Is this real?' You can actually do that.
It is. It pulls up a sidebar. You can just ask like, 'Who am I meeting with right now?' and it'll give you like a.
It's clearly who am I meeting with? What should I say? What should I say to them?
What should I ask them?
What is my name? What do they want to know about me? What should I tell them about me?
Okay, so Gemini was able to pull Wirecutter recommendations.
Yeah.
I don't know. I feel like I wonder if Wirecutter is actually benefiting from this in any way yet.
I mean, I'm assuming I'm not sure because Gemini hasn't rolled out the agentic commerce stuff that would actually like scrape out the referral token. And so if I'm in Gemini and I'm saying I'm going to do some agentic shopping or whatever and I say, 'Pull me the best vacuum cleaner from the Wirecutter.' It goes over and does that. And then I land on the Wirecutter and then I click that link. That should give the Wirecutter the credit. Now, if I as a follow-up prompt go in Gemini and say, 'Okay, great. The Wirecutter told me the best vacuum cleaner is from James Dyson, of course, is the Dyson. Find me the Amazon link.' Well, Gemini's probably not giving the Wirecutter the attribution at that point. It might even be taking its own attribution. I don't know exactly how it's functioning right now, but I would imagine that that link does not get reinstantiated as the Wirecutter affiliate link. And so, we could see, I mean, these are all going to be pretty existential questions for the SEO crowd, anyone who's monetizing off of SEO. We saw some screenshots that apparently site traffic to Vox properties is down 50%. And I don't know how much of that is just the shift to social media versus the shift to.
Yeah. How much is it their business strategy just being like, hey, we want to do more video. Yeah. and that'll be distributed off our site for the most part.
I think a lot of people generally do not they consume more and more content on social media platforms. They go from YouTube to their RSS player to audiobooks to Twitter to Instagram and they kind of bounce around from one and the other and then every once in a while they will go in and actually land on a particular site.
Like you can if you go to tbpn.com you can get our newsletter in your inbox every morning. And we can you can also sign up for Cognition. They're the makers of Devin, the AI software engineer. Crush your backlog with your personal AI engineering team. Well, speaking of the New York Times, David Sacks is going to war with the New York Times. He says inside the NYT's hoax factory. He calls it a hoax factory because the New York Times posted a piece about David Sacks saying that the headline was Silicon Valley's man in the White House is benefiting himself and his friends and Ryan Mack was going back and forth with Sean Maguire. Ryan Mack says, 'Today has been a good example of what X has become. complaints from a subset of wealthy tech folks about a story that circulates more widely than the actual story itself. Musk bought the platform to control the message and he and his friends are getting just that.' And Sean Maguire says, 'You don't get to run this headline, then write an article that doesn't validate the claim and then get away with playing the victim. We see through the ruse.' And so, David Sacks has responded in full to the NYT's hoax factory. He says, 'Five months ago, the five New York Times reporters were dispatched to create a story about my supposed conflicts of interest working as the White House AI and crypto czar. Through a series of fact checks, they revealed their accusations, which we debunked in detail. Not surprisingly, the published article included only bits and pieces of our responses. Their accusations ranged from a fabricated dinner with a leading tech CEO to non-existent promises of access to the president to baseless claims of influencing defense contracts. Every time we would prove an accusation false NYT pivoted to the next allegation. This is why the story has dragged on for five months. Today they evidently just threw up their hands and published this nothing burger. Anyone who reads the story carefully can see that they strung together a bunch of anecdotes that don't support the headline. And of course, that was the whole point. At no point in their constant goalpost shifting was NYT willing to update the premise of their story to accept it. I have no conflicts of interest to uncover. No conflicts of interest. As it became clear that NYT wasn't interested in writing a fair story, I hired the law firm Clare Locke, which specializes in defamation law. I'm attaching Clare Locke's letter to the NYT. So readers have full context on our interactions with NYT reporters over the past several months. Once you read the letter, it becomes very clear how NYT willfully mischaracterized or ignored the facts to support their bogus narrative.'
Will says, 'Hiring Clare Locke for this is sick. Cruise missile to blow up a straw hut.'
He's a big fan of litigation. He loves litigation. Well, people have been supportive of this broadly in tech. Let's go through some of the reaction. Sam Altman says, 'David Sacks really understands AI and cares about the US leading in innovation. I'm grateful we have him.' Brian Armstrong.
Yeah. Here was my takeaway. If you believe that AI and crypto are industries that we should support in the United States, then you want to have a czar focused on those things that generally feels positively about those things and wants to create the best possible environment for those industries to thrive in the US. I think that there's actually a debate on both fronts, right? Like there's people on the left that think AI and crypto are just default bad. They want less of them. And there's people on the right that believe that too. But I think that ultimately there's arguments for why the US should lead in stable coins which is part of why the Genius Act is important and a lot of the AI action plan. There's going to be debates on individual points in that but in general I think creating an environment in the US where we can continue to lead in AI is important. So I think there wasn't I didn't see any sort of like smoking gun in any of this stuff. There were some allegations around the all.
I don't think they smoke very much at all. I think it's mostly tequila drinking.
That's true.
They do all in tequila. Although JCal does tow a gun regularly. Oh yeah. So maybe that's the smoking gun.
He's a Texan.
Yeah. No, I didn't see anything very specific. I mean it's all in like they are super connected if you partner with them in some ways. Like you would expect to get more of a read on where they're spending time in DC, what they're seeing. That seems like there are clear lines on what you can share like what turns you into a lobbying firm and what doesn't. I think that they've stayed out of becoming a lobbying firm and so they have clear clear rules on that. Yeah, I think Balaji distilled it pretty well. Before we read his post, let me tell you about ADIO, the AI native CRM. ADIO scales and grows your company to the next level. Balaji said, 'I don't know David Sacks, but I want more expertise in government. Experts tend to have made money in their area of expertise, have friends in their area of expertise. If people can't have history or friends in a field before leading it, then our leaders won't know anything.' And I thought this was a good distillation of like the core debate about like should you have someone who has never participated in an industry overseeing it or should you like someone who's purely academic, purely outside of it?
And I believe there's some readers and probably people at the New York Times that would like somebody that hasn't participated in either industry to be running in a role like that.
Yeah. And just blanket against both industries and sort of like hold them back.
So the reaction is interesting in the comments. I mean first top comment is somebody like beefing with Balaji over how he ran the Quest store. It's like clearly a VR aficionado who has an axe to grind over niche VR policies. But the second post is what I want to get to because it actually addresses the core claim here. And Alex says, 'The construct you're thinking of is called a council. It's been used for a long time to allow the elected with limited knowledge on a domain to get a consensus of options from a range of experts. This minimizes conflicts and prevents kleptocracy.' But like, isn't that what a czar is? I thought Sacks was a council. Like, he's not an elected official. The elected official is Donald Trump, the president, and like there's a variety of folks there and then Sacks is like appointed to this czar role that is just to give his like he doesn't have the right he doesn't have the ability to just like create legislation out of thin air, right? Like he is very much a.
I was trying to look up the history of czars, right? It is weird is like have we always had czars? I know there was a whole thing was Bernard Baruch appointed by President Woodrow Wilson to head the War Industries Board in 1918. The press dubbed him the industry czar because he had sweeping powers to coordinate wartime production. During World War II, President Franklin D. Roosevelt appointed several czars to manage the massive wartime economy, including a shipping czar and a synthetic rubber czar. These roles were essential.
Synthetic rubber czar.
One of the most iconic.
Stoked for that.
People don't talk about the need for our ongoing need for synthetic rubber czars.
These roles were essential because existing government bureaucracies were too slow to handle the urgent demands of total war. During the Nixon era the modern concept of the czar a policy specialist with a specific portfolio solidified under Nixon during the 1973 oil crisis Nixon appointed William Simon as the energy czar to manage fuel shortages. He also had a drug czar during the sort of like beginnings of the war on drugs. So anyways, again, I think unless you're just blanket against these industries, it's hard to argue that you want somebody that doesn't have any expertise in said industries.
Yeah, some of these claims here here's one it's sort of hard to track. Like so he says, 'Free from those this is from the New York Times from the actual article screenshot. Free of those restrictions, Mr. Sacks flew to the Middle East in May and struck a deal to send 500,000 American AI chips, mostly from Nvidia, to the UAE, the United Arab Emirates. The large number alarmed some White House officials who fear that China, an ally of the Emirates, would gain access to the technology, these people said. But the deal was a win for Nvidia. Analysts estimated that it could make as much as 200 billion from the chip sales.' And so like we've covered the debate around export controls and should Nvidia where should Nvidia be able to sell things, but it's never been an open and shut case in my mind. It's never been like, oh, it's so obvious that the UAE is completely off the table.
Yeah.
I don't know. Yeah, it was also just like painting the friendship between Sacks and Jensen as like something that felt wrong was a little bit rough considering it's the most valuable company in the world. Yeah.
One of the most important AI companies potentially the most important AI company if you just go by weight in various indexes. So.
I don't I mean, it's like it's clear that he doesn't have Nvidia bags directly. Like that's completely debunked. So, you have to do these like 25 different steps to get to some sort of conflict. It's a lot of like, you know.
I read this and I think like this is if you're the average New York Times subscriber, this is probably that you were they were probably like very excited by this story, right?
Yeah. Yeah, I mean a lot of I think a lot of people are definitely like yeah just riled up by the All-In podcast.
Charlie in the chat says All-In Pod about to be an all-time after this article. Do you think it's possible that David and Jason coordinated to get this hit piece done to grow All-In even further?
They said we're at such an insane that was thing. Yeah, Jason made a lot of good arguments about this, but one thing was he was like we would be smaller if we didn't talk about politics and that seems crazy to me. I feel like politics is like the ultimate TAM expander in the history of podcasting and media broadly.
Yeah. The audience for political content is like 10 times less.
I would think so. I do believe that Jason loves talking about TAM and like I think he's an OG. He's said that multiple times. But I would be shocked if politics was not a TAM expander for podcast broadly. And then the other thing is that you said that they lost money on the All-In events. I don't know how that's possible. Like those events obviously they're like big budgets, but you know I would imagine that the sponsors and the ticket sales they're not cheap tickets, right? I would imagine that they'd be making money off that. I certainly hope so. I mean, they've been running this thing for 5 years. It's incredibly valuable in the ecosystem. They should be able to capture some value there.
Maybe they set up their own data center to sort of manage.
They're just underwater. Yeah, we decided to bring it back podcast production on prem and we ordered 100,000 Blackwells. Nvidia really has us by the balls.
It's rough. Martin Scorsese here says, 'The Sacks piece illustrates the exact problem with the New York Times. Voters specifically want this type of person, not a bureaucrat who has never worked a real job.' So yeah, that's so the issue and the reason I think this article was written is that New York Times subscribers specifically want this type of article.
Mhm.
Yeah. Yeah, Whiskey Titan going back and forth here. Did you miss the entire part of the article? This isn't a quote, we can't have businessmen in government. This is a we can't have the government officials who host government summits and sell access to the president for $1 million via their podcast business. And Martin Scorsese says, 'I doubt it was Sacks who wanted to sell $1 million passes.' And Whiskey Titan says, 'I agree with you. I'm sure it wasn't, but letting Jason run rampant until Susie Wild steps in isn't a great look. I happen to think Sacks is doing fine at this particular role, but I also understand the general public feelings like there's a lot of graft. The New York Times isn't the right conduit for that argument, though.' And they're going back and forth. The timeline truly is in turmoil over this. Dan Primack had a good take. He had a whole breakdown of this, which I think was interesting. He said, let's kick this off. But first, let me tell you about Fal. Build and deploy AI video and image models. They're trusted by millions to power generative media at scale. So Dan Primack said, 'Lots of people are sending me the New York Times story on David Sacks. Outside of the All-In sponsorship proposal, which feels oblivious at best, corrupt at worst, I'm not seeing much in there that's new, at least to those who've been following.' Dan Primack says, 'As an aside, it's true that Sacks and Craft still have a ton of AI investments. Thing is, all tech investments at this point are AI investments. It's kind of like internet investments at this point. If you invest in tech startups, you de facto invest in AI startups.' And Jason says, 'We've lost money on the event.' The NYT knew this and deliberately published false information. And Dan Primack says, 'They included statement that you lost money on it. What did they print that was false?' And Jason says, 'They were somehow make that we are somehow making money in this or some gain.' And Dan Primack says, 'Just reread. Doesn't claim that All-In made money. Said you tried to generate revenue via $1 million sponsorships, including for VIP reception that didn't end up happening, but ads that you don't know what sponsors ultimately paid included the statement that you lost money. Am I missing something?' And Jason says, 'Mr. Sacks has raised the profile of his weekly podcast All-In through his government role and expanded its business.' Confused. I thought you were talking specifically about the White House AI summit pieces. Dan Primack talking in general. Don't know how you would not quantify Sacks role in White House defraised All-In profile at least among normies. As for role in biz expansion, guess you could stake your claim there.
I completely disagree with this. I feel like the All-In podcast put the White House on the map. I feel like a lot of people were like they found out about the White House and about the US government because of the All-In podcast. They were listening to All-In podcast and they were like, 'Wait, wait, wait. You're telling me there's people in Washington DC and they run this whole country. They create they're in charge of the rules. Yeah. They create sort of laws and framework over how our country should operate, which industries we want to support and grow. You're telling me that there's a group of people and one of my besties is they're running it. This is amazing. I got to learn more about this. I got to figure out what a bill is. I got to figure out how a bill turns into a law.'
Chat, what is a bill? Jason says, 'If anything, going deep into politics has been a net negative for All-In, at least in my opinion. We would be growing faster and wouldn't have lost some percentage of our left-leaning audience if we'd stuck to tech, markets, science, VC, etc.' That's an interesting take. I still think that politics.
It made it so big.
Well, yeah. And it made the content polarizing, which but I think that polarizing in media is good.
You actually get more attention. Not necessarily good from all points of view, but good from a pure just like reach.
I mean, yeah, I was looking at the I think the ratings are like the amount of viewers for CNBC is bigger than Bloomberg by like a pretty significant margin because Bloomberg's like extra wonky and CNBC is a little bit I mean it's like literally called Consumer Business News. Like that's what the C stands for I believe. And then you have Fox, which is even more like Fox News is political and it's much bigger ratings than CNBC or Bloomberg. And then ESPN is like by far the biggest. Yeah. Because it's like sports. Everyone loves sports. And so like maybe that's the final form. They should go full poker and then full sports. It should just become SportsCenter competitor.
I could see it. That might be the way.
AB says, 'I only learned about Trump because Chamath endorsed him.'
Yes. Exactly. I had never heard of this guy.
Who the vodka and social media entrepreneur? He's running for president.
Okay, so Dan Primack is weighing in again concluding it. He says this, the New York Times story was mostly a nothing burger, at least for those familiar with the situation. As for hoax, the story itself as published isn't being disputed. Obviously, the New York Times had info questions that Sacks lawyers answered, and disproven info wasn't included. That's how journalism works. The real complaint seems to be about the headline. Quote, 'Silicon Valley's man in the White House is benefiting himself and his friends.' I get the complaint, but it's really a matter of interpretation, not true, false, hoax. Imagine if you had a friend and they went to the White House and they didn't try and benefit you. You'd feel like you might not be friends with them. Sacks and the Trump White House are pursuing let them cook AI policy. I like that. That they believe will help us win the AI race and that the rewards outweigh the risks. Others disagree. Yeah, this is so true. It's like there is no like oh like we now know the correct way to win the AI war. Like we know that there's a correct way. It's very obvious. It's like no, everyone's debating this constantly even inside of tech. And Sacks has one view that I think has actually played out pretty well considering that he's been anti-doomer, anti-fast takeoff, more industrial capacity, more opportunity to grow GDP. You know, there are some elements of his takes that are a little bit more like TBDs, like what actually happens to jobs over the long term, how does it manifest in GDP growth over the long term? But so far I think he's been correct and I think that's what Dan Primack's saying here. He says only time will tell if Sacks is correct. What we know for sure though is that his deregulatory policies should help VC funds his those run by his friends those run by strangers etc. Thus the headline is defensible albeit pushing an agenda.
And that's the timeline in turmoil folks. Let me tell you about Graphite.dev code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster.
I can't read this AI amicus this name. This Ilya interview will be compulsory viewing for any future student trying to understand what misallocation of capital looks like in real life. See I completely disagree with this take. People were going back and forth on this. We talked about this a little bit over the holidays but fleeting in bit says can you say more just that he doesn't have any business direction or something else? And the original poster says, 'These are my intuitions, but for what it's worth on the micro level, he just seems to drift in a sea of possibility and not the kind of person.'
See, I originally read this as the misallocation of capital that I've seen is like the 10th, 11th, 12th.
Foundation model lab that has like a hundred to a billion dollars that is just like kind of iterating on what Ilya already worked on. And doesn't necessarily like if they just create a model that's not like there's going to be incredible value in that.
Meanwhile, I'm like, okay, you take the guy whose work led to ChatGPT and you give him a few billion dollars and let him, you know, continue to iterate. And he's not just like, you know, firing a single multi-billion dollar cannon and hoping he hits a target. It's like this incremental research that I think is still one of the best shots at like developing the next paradigm, whatever comes after LLM.
Um, I read this. I think that your reading of this was right, but I initially read it the other way and I was like, yeah, I do think this is, you know, somewhat bearish on the incremental large language model lab.
Yeah, I don't know. I mean, I can kind of steelman both. We're going to have Julian on the show, or we're having Vincent from Prime Intellect come on the show. And I was talking to him. We'll get more information from him. He's going to be on at 140. But Vincent was explaining that more and more companies and different business processes, they do need specific training runs. They do need the skill sets of a foundation model lab, but there's a lot of business to be done that's not purely AGI seeking, not purely paradigm shifting. So I do think that there's some value there if the business can be run well, which is a big if, but there is a path where a Thinking Machines or one of these companies is going to go and do specific reinforcement learning, specific model development for a specific company and task that can work out. It's a very different business than searching for the next paradigm doing science and maybe you shouldn't even call it a lab because you're not really even trying to do foundational science necessarily. You're more productizing a company.
Yeah, it's a business which is great. We love that. What's interesting about Ilya is that when we talked about this, like it is a venture style bet like let the scientist go experiment maybe it will work out. It's extremely high risk probably a zero but if it works it's huge, right? So the expected value is still high. What's crazy is that we're doing a venture style bet at growth scale and it's just massive amount of capital for something that I think the consensus here is that it's either he solves it and it's incredibly valuable and leaprogs everything and is just amazing or it's just you get lost in the sea of research and ideas and you never really produce anything. So I love the high-risk bets. I just understand why people are saying like at that scale that's a lot of money. But that has been happening internally at Google for a long time. They probably burned a lot of money on research projects hasn't been that big of a deal because they had the engine for it. And if the investors are significantly diversified, they should be fine.
Anyway, what else is in the timeline today? Finn.AI, the AI that handles your customer support, the number one AI agent for customer service. We did get a good meme. We got a couple good memes.
Cody says, 'When my wife asks what we should eat for dinner, but says no to my first two suggestions.'
We are back to the age of research. I like it. And then when she asks what I want for dinner from Beas Lord, the answer to that question will reveal itself. I think there will be lots of possible answers. Very true. It's a great new meme template. I like it. When my husband asks how many Amazon packages are still on the way, the answer to that question will reveal itself. I think there will be lots of possible answers, but I think that's actually true. Like, if he creates some new AI, like there's a bunch of different ways to monetize it. We know this is a fact. Of course, Ilya is now joining the ranks of Yann LeCun and Rich Sutton and Andrej Karpathy of sort of industry legends that are more or less saying that scaling is over and LLMs are dead. On the other side, Schultto is saying scaling maybe not over. So, we'll see.
This post is great. Scaling is over and LMs are a dead end. A you're sweet. Scaling is over and LMs are a dead end. Hello human resources.
I love this meme template because it's like Yann LeCun has been saying the same thing.
He says, 'For the record, my current BMI is 24.' This guy rocks. Very funny.
I thought he would have dropped the Meta tag on X by now. But I guess he's still wrapping them.
Oh, he's still wrapping them. Didn't he leave? Oh, he's like reporting to leave.
Okay. He's like on his way out more or less.
Another 1 billion to SSI. There's a bunch of this in the SSI bucket. Let me tell you about Profound. Get your brand mentioned in ChatGPT. Reach millions of consumers who use AI to discover new products and brands. Of course we are having Dylan Patel on the show in 12 minutes and we should do a little bit of a run through of the drama on the timeline. The timeline was in turmoil. Lots of people very upset with SemiAnalysis's latest post.
How dare you take a swing at the king, which was the name of their article. They said TPUv7 Google takes a swing at the king. The king is of course Nvidia. And they are asking is this potentially the end of the coup? Anthropic's, they're talking about Anthropic's 1 gigawatt TPU purchase. The more TPU, Meta, SSI, xAI, OpenAI, Anthropic buy, the more GPU capex you save, next generation TPUv8. And they're going into what the battle between TPU and the next generation GPU out of Nvidia will look like. And this upsets some people. There's a lot of folks who are long Nvidia. Either they have invested in Nvidia, they made a lot of money in Nvidia, or their whole business is tied to Nvidia or AMD even. And so...
Or they bought the local top a month ago.
Potentially. There's a whole bunch of reasons. You could also just disagree with this and you could just think that SemiAnalysis's takeaways are wrong. But I think it's a thought-provoking article. I think there's a lot of data here. They're extremely thorough and I think that they do leave you with a lot of new information that you can do with what you want. And I think in general the response to this article was very positive, but there were some folks who were very upset by it and went all over the place and on accounts that put a noun and then capital as their name.
And suddenly they're an expert on...
Yes. Yes. Yes. Yeah. It was a little odd seeing the credentialism come out from the anons because like I don't think we should get in the two can play that game camp. It's a little bit rough. But there's a little bit of interesting stuff in here. I want to read through some of this. Let's kick it off with the opening of the SemiAnalysis article. The two best models in the world, Anthropic's Claude Opus 4.5 and Google's Gemini 3 have the majority of their training and inference infrastructure on Google TPUs and Amazon's Trainium. Now Google is selling TPUs physically to multiple firms. Is this the end of Nvidia dominance? The dawn of the AI era is here and it's crucial to understand that cost structure of AI-driven software deviates considerably from traditional software. Chip microarchitecture and system architecture play a vital role in the development and scalability of these innovative new forms of software. The hardware infrastructure on which AI software runs has a notably larger impact on capex and opex and subsequently the gross margins in contrast to earlier generations of software where developer costs were relatively larger. Consequently, it is even more crucial to devote considerable attention to optimizing your AI infrastructure to be able to deploy software. Firms that have an advantage in infrastructure will also have an advantage in the ability to deploy and scale applications with AI. And as I say, we've long believed that the TPU is among the world's best systems for AI training and inference, neck-and-neck with king of the jungle, Nvidia. 2.5 years ago, we wrote about TPU supremacy, and this thesis has proven to be very correct. TPU's results speak for themselves. Gemini 3 is one of the best models in the world. And there's a very funny bit in here. I need to find it. Oh yeah, here. So, this is a very spicy line in here. He says, 'OpenAI hasn't even deployed TPUs yet, and they've already saved 30% on their entire lab-wide NVIDIA fleet.' This demonstrates how the Perf per TCO advantage of TPUs is so strong that you already get the gains from adopting TPUs even before turning one on. And so basically what he's explaining is that because of the competitive dynamic between Nvidia and Google with the TPU now, you can use TPU as a stalking horse. And say hey if you don't cut your prices Nvidia we know that you have really high margins.
Or not even cut prices but encourage an investment.
Exactly. And so that's what they're...
Nvidia would rather invest back into your business instead of cutting prices.
Yes. And so it says we think the more realistic explanation is that Nvidia aims to protect its dominant position at the foundation labs by offering equity investment rather than cutting prices which would lower gross margins and cause widespread investor panic. Below we outline the OpenAI and Anthropic arrangements to show how Frontier Labs can lower GPU total cost of ownership by buying or threatening to buy TPUs. And so OpenAI, Nvidia, the, you know it was $22 billion per gigawatt the rest of the system. So it's a $34 billion per gigawatt expense to Nvidia, but Nvidia is doing effectively an equity rebate of $10 billion per gigawatt in investment. And so how that works out is a 29% partner discount. Anthropic has similar math but a little bit higher at 44% partner discount because Microsoft is paying for a piece of it. And so it's an interesting thesis and it's unclear exactly like well you know if the claim that the investors will panic if it was actually just lower gross margins. Well, if you say the quiet part out loud like this and you do the math to show that there is basically a discount that margins might be coming down because of competitive dynamics. Does that wind up resulting in investor panic? I mean certainly it didn't today. Isn't Nvidia up today?
Yeah. Nvidia is up 1% adding a casual, you know, what, 10 trillion or 100 billion or something?
Yeah. Gigajillion dollars.
Yeah. And again, we said this earlier on the show, but Broadcom is down almost 4% today, which I would have expected it to be the other direction given that to actually buy TPUs physically, you need to go through Broadcom.
Yeah. So, a lot of people are going back and forth on, you know, can SemiAnalysis be trusted because they're writing about Nvidia and Dylan. I think some people didn't understand that he was joking. Zephyr here has a post. Dylan is being tongue-in-cheek, but he's not wrong. Nvidia was extremely dominant for the last three years. As we saw in the stock, it's up 10x over the last three years. New competitors will cause a reduction in market share and margin compression, but TAM is big, so revenue profits won't go down. 75% of GM is just unsustainable. Hyperscalers will also use the cheap TPU's threat to extract better deals from Jensen. Priority access for Ruben or discounts on GPUs. Jensen called Altman and initiated the $10 billion deal after he saw the information article about OpenAI testing TPUs. And so, this is in reaction to that point about OpenAI hasn't even deployed TPUs yet and they've already saved 50%.
There's a decent post here from just another pod guy. They say Dylan speedrunning through all the learnings of sellside research industry capture pissing off IR execs gatekeeping info based on client tier difficulty scaling beyond single star analyst distorted MSN representation of your notes eventually spending too much time marketing versus researching amazing biz content though obviously Dylan would push back on he did on a lot of this stuff if you actually read through the entire article.
There's nothing in this article should be that surprising because so much of the article is just referencing old SemiAnalysis research. Some of which they did before the paywall, some of which they did under the paywall. But it felt like a kind of a culmination of everything that they've been saying for a really long time. And I think that part of the surprise here is just how much faster this conversation has really come to a head than people may have expected. I think at least surface level on the timeline, people felt like the TPU threat was maybe like a 2026 2027 conversation versus being like it's a part of these buying discussions right now and negotiations.
Yeah. The other buried lead in the article was of course about pre-training. So there's a snippet in here. OpenAI's leading researchers have not completed a successful full-scale pre-training run that was broadly for a new frontier model since GPT-4o in May of 2024. And you know this is so interesting that if this was wrong you would imagine that there would be a whole bunch of reaction from OpenAI people or like proxies or surrogates right people quote and be like that's just not true wow something else is cooked but the fact that I haven't seen anyone respond to this and say like oh this is wrong like we actually did not that that's the north star for what the business is like the business's job is to create profit. Right? It's not to complete successful full-scale pre-training runs. That's not the goal. That's just something that they might do in service of making a better model, making a better product, but ultimately, it's whatever the customers want.
And if the customers are happy with 4o level base pre-train and a bunch of reasoning on top, that's fine. So, what else is in the back and forth? People are also I mean it really does make me happy that we didn't go deeper into ranking people because it does feel like when you create a list of tiers and rank a bunch of people you're just creating a big bucket of enemies down at the bottom of like people who want you dead because you ranked them low. But I'm sure we'll get into the discussion of ClusterMax and what how people are interpreting ClusterMax because there's a whole bunch of ways to read it. Like one way to read it is like which stock should you buy, right? But like that's not necessarily the read. The other read is like which product is the best to work with as a customer. But it's like what customer are you? There are some that are in the lower tiers that are fantastic for very specific use cases. Like this is the nature of every business. Like one of the Neoclouds that was particularly upset with Dylan is in a very niche market, but if you're in that niche market, it's probably a great product. It's probably great for you. If you satisfy this specific list of criteria and you don't need these features, you're probably fine then. But it's a lot of fun. People are going back and forth. They're also debating whether or not Dylan is independent given that he lives with Schultto from Anthropic.
And we got to ask him why he has roommates. Not even I'm not even concerned about a conflict.
Yeah, it's roommate gate. But what about this other tinfoil hat post from JCON? My theory is that Meta deliberately leaked the story to the information about acquiring Google's TPUs. For Meta, it's a classic risk-free power play. The moment Jensen Huang catches wind of Meta using Google silicon, Nvidia is likely to rush in with an investment. They might even be negotiating as we speak. This allows Meta to secure capital and shift from burning their own cash to potentially getting discounts or effectively buying Nvidia chips with Nvidia's own money. Plus, if they actually do secure Google TPUs, they solve their compute shortage. It covers all bases. I wonder when other hyperscalers will catch on to this magic wand. All you have to do is hint at using TPUs.
But the issue is how many red flags would be waving if Jensen was like, 'Yeah, we're investing $20 billion in Meta. We're very excited about Meta and owning a piece of...'
So he's in a position where I don't know what kind of leverage Jensen has in those conversations with Meta because he doesn't want a discount and it's not like OpenAI where he can just announce an investment or Anthropic etc. So how does any type of rebate actually happen is the question.
Yeah. Well, before we bring in our next guest, let me tell you about Turbo Puffer serverless vector and full text search built from first principles and object storage. Fast, 10x cheaper, and extremely scalable. Let's read through some more TPU stuff to set the table. So, Clive Chan says, 'I keep seeing stuff about TPU. Has anything materially new happened? There's no evidence Google has ever trained Gemini on non-TPU hardware going back to pre-GPT models like BERT. TPUs predate Nvidia's own tensor cores. Anthropic and Character and SSI and Midjourney have long used TPUs. I'd be surprised if Meta weren't looking at them. Nvidia's moat has never been deep for the big labs. See OpenAI deciding it could do better than CUDA and investing in Triton instead. Regularly edging out cuDNN on benchmarks. There's nothing magical or structural about any of this. Just good engineers doing good work. TPUs are not that much more efficient than GPUs and small performance per watt difference are dwarfed by whether Meta has the right kernels and systems engineering to pull it off. Both Nvidia's and Google's moats are small and we are still at the point where individual good engineers can flip the entire balance. Why was this not priced in? This is all super old public info.' I have a feeling that Clive Chan, who I guess is over at Tesla and then OpenAI is a little bit of like first time in the public markets, first time realizing that the people who trade this stuff are not necessarily on the super inside of the labs actually understanding the decisions that are being made inside the labs like it's a completely separate ecosystem. And that's why organizations like SemiAnalysis exist. And I believe we have Dylan Patel from SemiAnalysis in the waiting room. Let's bring him in. Dylan, how are you doing?
I'm doing fantastic. How about yourself?
You know, I saw the meme image that you guys put out there for me, so I had to wear the tank.
We need a bigger screen for that bicep. We'll work on it.
Let's go. Where in the world are you?
I'm in Florida. I was spending Thanksgiving with my family here. I'm trying to chill out a little bit. It's nice to have the family pamper me a little bit because I broke my foot a couple weeks ago.
I'm sorry. How'd you break your foot?
Family reunion playing football in Texas. We're American as we can get.
There you go. There you go. Well, we were just running through a little bit of the TPU article. Can you actually set the table for me on like what do you think is new about it versus what has SemiAnalysis already been saying and this is more just like tying everything in a bow.
Yeah. Half of the article is just referencing recent... we've been saying this for two years. We've been saying this for one year and even referencing Google's own content about the TPU dating back even further. So yeah, I would say the majority of this piece was if you're a client, it's already been pretty much all published. But it hasn't been tied together. It hasn't had a narrative around it, right? Because when we think about what we put out on the paid side versus what we put out on the newsletter, our clients sort of get what changed, what happened, here's the numbers. That's about it, right? We don't explain the technology that much because our clients are sophisticated, right? They're either in the industry or they're finance pros who don't give a shit about the technical stuff. And so it's either of those two, right? And so we're just explaining here's what's happening. Here's the change. Here's the numbers, right? So for months we've been saying Google's selling TPUs. For months we've been saying, hey, here's TPUv7 versus Blackwell. We've even put out updates on here's what we think TPUv8 is versus what we think Ruben is. And so generally it was making it into a narrative and explaining the technology and the corporate politics or dynamicism around it. So that's, you know, I think there has been bits and pieces put out by other folks. I think The Information has done great reporting on some of the stuff after we did but in the public space I think for as an example, other people have put out bits and pieces surrounding this but they haven't put out the full picture. So as far as what's new it depends on where you sit in the stack. But Anthropic and Meta and folks like that have been talking to Google about buying TPUs for many months, right? Whereas people externally are last week when Gemini 3 was launched or two weeks ago, people were just learning that TPUs are training Google's models, right? So it's where are you in the information spectrum, right?
Yeah, totally. So, on that information spectrum, the finance bros, they can probably just like if they read into this, oh, bullish Google or bearish Nvidia or whatever, like they can kind of trade in and out as they please. But what on the more technical side, like are people using SemiAnalysis research to understand like, okay, I'm a Neocloud. What do I want to rack for next year? Maybe I need to be putting in a TPU order. Is that how people interpret your research? Like what happens on the technical side of the house.
Yeah. So as far as some of the paid stuff we do, we have one model called the TCO model, right? Which is calculating the TCO of all these different hardware performance building up the entire cluster cost, you know, breaking out into like a dozen plus different things whether it's storage or networking and breaking down the cost of everything. So there we put out research on TPUs because as soon as Neoclouds started getting offered, hey, you want to buy TPUs? We're like, okay, we need our own ground-up model. So when you're negotiating a big contract, what you do is called a should cost, right? You go and calculate what it costs for the company versus what it costs for me to deploy. And then you think about like, oh, what's the margins they have? What is ridiculous to offer them? What is not, right? Because everyone always wants to know like, hey, what margin are they making off of me? Can I push that down a little bit? What is ridiculous to demand in a negotiation versus what's not? So we've already been working through this TCO model. We've put out four different updates on the TCO of TPUs v7 and v8 because there are Neoclouds out there as well as labs who are purchasing TPUs that are using that to understand what's the cost. Now Anthropic I will say just already knew and figured it out because they've hired so many Google people but other labs are also looking at it, right? And so when you say hey on the cost side of things on the technical side of things, there's a lot of network engineers now out there who have never deployed Google hardware that are now like okay I need to figure out how to do TPUs, right? Like, you know, so there's people who have DM'd me that are like, 'Oh, we've been thinking about deploying Neoclouds, but your material on this is technically better and teaches me more than Google's own material, right?' So, it's like this is helpful to people on multiple factors.
Yeah. What about the software side? Google's built their own internal stack to compete with CUDA. How much of that are they going to actually give to their customers who are buying TPU? Because that feels like potentially you could overrotate on oh well Gemini 3 is really good but why is it good is it just because of the hardware or is it also Google's incredible prowess multi-data center training all this fancy stuff that they have that they won't be giving you when they sell you the TPU.
Yeah, so that's the interesting thing is some of the stuff software will remain closed source but you can still use it right and then some of the software they are trying to open source aggressively and then some of the software they're never going to get out there anywhere, right? So, it sits in three kind of buckets, right? The interesting newer thing that we did in the piece was we looked across all these different open source AI software, right? Whether it's PyTorch, whether it's vLLM, whether all these different open source libraries and we calculated and counted up how many Google commits there were, right? And you can see there's a chart in the article where the number of commits that Google's doing on TPUs has exploded over the last handful of months, right? As they've decided to shift their strategy, sell TPUs externally. They also recognize software has to be open for this, right? Only the gigabrain types like Anthropic can figure out how to do everything themselves, right? It's those people outside of Anthropic types that need a bunch of open source software that builds on top of it, right? And what's interesting is when you look at like, hey, Nvidia, the biggest argument that Nvidia doesn't really make for GPUs, but they should, is that about 40% of the software that's open sourced is actually just from China, right, on CUDA, and that's the CUDA mode, right? It's like 40% of the software is just like open source stuff, whether it's people committing to vLLM or PyTorch or all these other libraries, right? ByteDance open sourcing stuff, DeepSeek open sourcing stuff. And Google, they don't have people open, you know, Anthropic is not going to open source software. So Google needs to catch up not just by, hey, here's all the software we have internally, let's open source it. They also need the ecosystem to build a ton of software on top of TPUs. And so that's the real big challenge there. And there's an element of software there that Nvidia's happy to open source. And customers of Nvidia are happy to open source that Google will never open source because Google Cloud is selling the TPU. Gemini is the one actually using it and developing a lot of the software and these two groups are not always going to be aligned.
Yeah. Isn't that like I mean what are the other kind of problems with Google becoming an actual seller of TPU? It feels like there's obviously an opportunity because Nvidia has high margins, there's demand, it's a great chip, but culturally, structurally like Google tries a lot of different things. They have a lot of advantages, but occasionally like they fall flat on their face with just like they can't even get an RSS reader out or something like that. So like are there other risks to the TPU not really finding its footing for reasons that aren't just the laws of physics?
Yeah. So the biggest challenge I see with them is everything is non-standard, right? Google for years, they developed liquid cooling first, right? For AI computing. They deployed rack scale architectures, right? Everyone's talking about GB200 rack scale architecture. Google did it first with TPUs, right? But when they did all of this stuff, they didn't give a crap about, hey, this has to go in 50, 100,000 different people's data centers, right? This has to go in my data centers that I designed myself. So everything is super vertical. The entire liquid cooling supply chain is super vertical. The racks aren't even the standard width, right? So when I look at like a data center, it's like the loading bays because they're so much wider. The Google racks are like three times as wide. It's like maybe it might not even fit into the data center like physically through the doors. So there's like all sorts of random like I wouldn't say random, it's Google from first principles design stuff.
Totally. Yeah. But if you're a Neocloud and you're like the hot thing is going to be TPU next year or the year after and I want to be able to sell into that market. It's not just flip a switch, drop in, replace with TPU. You have to maybe build a whole new building like it might be that significant.
Right, or knock down some walls and then like I need to go get liquid cooling not from Dell and Super Micro and HPE who service me already. I need to go get it from some random supplier who's only ever sold to Google. And usually they're sitting across the table from like some gigabrain engineer who has a team of 20 people working on liquid cooling instead of like my one guy who does liquid cooling procurement and negotiations and also does procurement of network stuff.
Yep. There was a tinfoil hat theory floating around that Meta leaked their TPU interest to try to gain some leverage over maybe some negotiations with Nvidia. I don't know if you see any possibility in that. But how do you think those conversations are going? Jensen doesn't want to discount and compress his margins, but at the same time, he can't do this kind of equity rebate thing. If he took a big position in Meta, he'd be very suspicious. I'd be very concerned.
I totally get the OpenAI investment. That seems like it makes much much more sense than saying, 'Hey, we're going long Meta,' you know, is a $4 trillion company. At the end of the day, TPUs have like a set of maybe 10 customers, right? Because you have to be super sophisticated. And so what really is challenging here is Meta looks at the numbers, you know, it's like, okay, OpenAI I'm getting 30% off because they're investing in me as a result. Obviously, they get equity, but they're investing in me and I get 30% off on these GPUs as a result, right? Meta, you can't do that. So Meta, I don't think that they're just negotiating, right? Like are they just negotiating with Nvidia when they buy AMD? No, they're engineers, right? They're developing all the software. They're actually deploying Llama 405B was exclusively on AMD for a number of months, right, for inference, right? So when you look across, hey, is Meta just like playing around trying to negotiate? It's like no, no, no. Like they're looking out for what is best, right? And Meta is power constrained and TPUs are currently way more power efficient. Meta is compute constrained. And TPUs are potentially higher performance per watt and higher performance per dollar, right? At least that's what we believe for TPUv7 that it is. So, they'd be dumb not to look at it, right? And they have the time, they have the people, they have the team. Now, Nvidia at the same time has to play the game of chicken, right? Sure, they could discount the pricing somewhat. And because what's funny is Nvidia is more vertically integrated than Google is when selling hardware, right? Google has to pay Broadcom who pays TSMC, whereas Nvidia gets to pay TSMC directly, right? There's this vertical integration challenge where Nvidia could drop the price a little bit and they'll be fine, but they don't want to, right? You know, the whole point is you charge the highest price possible. And then the last thing is they've got this view about antitrust right you don't want to cut deals for specific customers because that looks bad right instead you want right now Dell pays the same price for a GPU as Gigabyte as Meta. Now the networking hardware there's different pricing because there's a lot more competition and Nvidia can cut a lot more there but on the GPUs themselves Nvidia's pricing is very fair right fair in the sense that they're making a shitload of money off of everyone.
How talk about kind of Jensen's leverage that he has around Ruben allocations as some of these customers start to at least consider TPUs.
Yeah. So as far as next year's TPU deployments, it's pretty set in stone for the vast majority of the volume, right? Anthropic's got a bunch and then there's some sprinkled elsewhere. But as we go into 2028 where Google can actually ramp, the flip side is Ruben is also ramping and at least based on our research looking throughout the supply chain, over a year ago when OpenAI started their TPU team they poached like 15 Google people overnight right in one week like someone I knew I heard was like oh yeah I'm joining OpenAI I text like another three people I know and they're like oh yeah I'm also joining OpenAI like what the fuck. So Google's a lot of their best TPU engineers have left right they also have a ton left and so what that's done is, you know, chip timelines are so long, that didn't affect TPUv7, that's affecting TPUv8. At the same time, Google's trying to diversify their supply chain, get from not just Broadcom, but also MediaTek. And so, Google's got a real challenge on TPUv8 in that it's good. It's an improvement, but then when you go look at what Nvidia is doing with Ruben, Ruben is so much better because Nvidia is just pedal to the floor, paranoid as fuck. We have to be the best and we have to be way way way better than everything because how much better I am than everyone else is my margin, right? And so Nvidia has the sort of like at least currently we think Nvidia is going to be so much better that they'll be fine and they'll be able to maintain margins. Right now things can happen. Ruben can delay or TPUs can delay and the position looks better or worse, right? There's a lot of unknowns to go through, but as far as what is Jensen's leverage is look, I'm going to make the best hardware and plus my software advantages and I'll be able to continue to be dominant and dominate the market, right? There's curveballs I could go which is like oh Google software they could open source enough software that actually their software ecosystem is not far behind Nvidia maybe they don't want to right or hey they could execute everything and Nvidia has a three six month delay now all of a sudden they're a lot more competitive right and so all these things are still open questions but Nvidia can play the allocation game as well of course right hey I'm going to give all of the GPUs initially to companies that probably could buy TPUs but that ends up all the AI labs and hyperscalers, right? At least, you know, like Meta, right? And ByteDance, people that would actually be willing to buy TPUs. And then you end up with this like weird situation where okay, well that's like 75% of the GPU market anyways when I look at the AI labs through the Neoclouds, right? When there's, you know, Nebius and Iris Energy and all these other, you know, CoreWeave and all these folks are deploying for OpenAI anyways, right? This sort of ends up being like, well, sure, I could stiff some people on the allocation, but at the end of the day, everyone who was a potential customer for TPUs is sophisticated enough to be where they were going to be on the beginning of the allocation anyways, right?
What how are you framing ClusterMax these days? Is it for customers who want to buy services from Neoclouds? Is that the primary goal of ClusterMax? Because I feel like some people look at it and they're like, 'This is a buy rating. This is a sell rating on the stock.'
So the funniest thing is like ClusterMax v1, the title of it was ClusterMax, how to rent a GPU, right? Because we discussed all of that and then in ClusterMax v1, I believe we put Iris Energy under perform, right? At the same time, the research side of the business, we explicitly were like, 'Dude, they've got these data centers. It doesn't matter if they suck at running GPUs. They've got these data centers. They've got this power. If you just value them on a watts per how much money they could make it's a long.' So like at the same time as like Jordan right Jordan he's running ClusterMax is like Iris kind of sucks and it was other people in the technical team before him you know it's like Jeremy who's running the data center side and I think he's been on TVPN is like dude Iris Energy is a stock right so it's kind of like what the technical side of the house does versus what the research side of the house does yes they talk to each other right Jeremy did ask the team like, 'Hey, what do you think of Iris Energy? I think it's a long.' And the team working on ClusterMax is like, 'I don't know.' Like, it's a bad cloud. And it's like that doesn't matter. So, ClusterMax has nothing to do with the stock, right? Now obviously there's going to be some correlation with how good is a stock versus who's going to want to rent from them. But at the end of the day ClusterMax is the goal purpose sole purpose and what we explicitly say in there is it's for people renting anywhere from like hundreds of GPUs to right below the AI lab scale right the AI lab scale there's different considerations but in that range tens of thousands of GPUs all the way down to hundreds of GPUs that's who we're targeting plus we're saying we're giving a bunch of feedback for people to make the cloud ecosystem better.
The unsung hero between ClusterMax v1 and v2 is that we move the bar up right? You know what it required to be in gold.
Like what it required to be in silver was much more because everyone improved so much, right? And as we continue to increase the requirements, make it harder and harder to keep moving the goalpost, right? People keep improving the ecosystem and actually, this is the funny thing. It's like ClusterMax is evil. It's like when we look at the quotes and we've got hundreds of quotes on clustermax.ai, all these companies are like, 'Dude, I love this. This one specific bug that this Neocloud had, they fixed it as soon as you wrote about it.' Right. Or like, hey, help me understand the reliability, help me understand this or that. People are like, 'Love ClusterMax.' And altruistically, like I think we're generating billions of dollars in value just from hey, like all these clouds are more efficient and there's less failures and it's easier to get your workload running on any random GPU cloud and the market is more efficient. Now I'm not making any money off of that. How am I making money off of ClusterMax? I'll be very clear is people who hire us to do due diligence, right? So, people who want to acquire a Neocloud, people who want to sign a massive deal that's not just like thousands of GPUs, but tens of thousands of GPUs, and then lastly, it's people who want to invest in Neocloud. Those are the three areas where we're making money off of quote unquote ClusterMax, but not really. We're not selling ratings. We're not, you know, in fact like a customer will do a consulting project with us or want to buy some research from us and I'll explicitly put in our Slack share Slack or I'll send an email to the CEO like, 'Dude, just so you know, the people working on this are not the people who are doing ClusterMax rating, right? The people who are buying the research on like these data centers are there and this is the power ramp or here's the accelerators or here's the TCO. That's not the people doing ClusterMax, right? And I don't care about whether you buy it or not. At the end of the day Google and Amazon and Microsoft are way bigger customers than you know Flipstack and those kind of companies right and yet some of those are ranked in silver and some of those are ranked in platinum and gold and that's because technically what matters not hey obviously when we talk about who buys our research the biggest companies in the world are going to pay me more than the mid-size companies in the world.
Okay, question from the chat.
And the price has discriminated based on that.
Would you change the rating of a Neocloud if Schultto promised to do the dishes for two weeks straight?
You know, there was an argument. I saw someone was like, 'Who does the chores?' And it's like, 'Brother, we live together by choice, you know, we pay someone to come once a week. If you cook something, you do your own dishes.' But like, you know, frankly, we're working so much and I think like, you know, I think Dores Ces has ordered pizza from the same spot three nights in a row before, right? Like it's...
Is being an adult man with roommates underrated?
So I haven't lived with people in years and then when I moved to SF...
This is crazy. I moved to SF this year, you know, I'm like, 'Oh, you know, I should live with friends just so it's more fun.' And the first house kind of fell apart, so I moved into this house with these guys and we've been talking about it for months. I love it, right? It's like, look, if you think about, oh, what if we all rented our own places that were good and then we pulled that budget together? We have a nice place. Right. And then in...
We have plenty of space for ourselves. We pay for someone to come and clean once a week. So, at the end of the day, what is the negative here? We're living with our friends, but we have enough space. And the beauty is if you do bunk beds, you have more room for activities.
Anyway, no, no, sorry, sorry. Actual question from the chat. When is TPU going on Inference Max? We got to know.
So, we're working on it, right? We're working with Google technical folks. Funnily enough, we triggered a security warning for this Google engineer. Kimbo went to a Jax conference. Jax is the opposite, it's like PyTorch but for TPUs. It's Google's own internal thing that people do use externally. He went to this Jax conference. A Google engineer presented something. He's like, can I get the slides? They send it to him and then Google security alert locks him out of his computer because he sent us some technical information. For three days the guy can't work and he's freaking out. I emailed Jeff Dean. I'm like, bro, do not fire this guy. He sent me stuff that you presented at a public conference. And he's like, oh okay yeah I'll get that fixed. But anyways, we're working with, we're trying to implement it. We have access to some TPUs.
The software stack is different, right? So you basically have to rewrite or reimplement Inference Max, like the code that actually...
I won't say it's that much work, like completely redoing Inference Max, but there's a ton of work. So we're moving as fast as we can. Internal target is this year.
Then the obvious question is, I feel like Inference Max is my north star for TCO relative in AMD versus Nvidia land. There was a bar chart of TCO for GPU versus Nvidia. It looked like TPU was doing really well on that chart. The bars were very low. Where did those numbers come from? Do you have confidence in those numbers or do you think the numbers will change once you actually get TPU on Inference Max?
Yeah. So, Inference Max shows performance TCO. Guess what? TCO of a Raspberry Pi is incredible. It's like five bucks versus a GPU is $50,000. Performance divided by TCO is what matters. So that bar chart is saying look, TPUs are cheaper and at least on quoted specs. Now let's make some assumptions around utilization. In the article we explicitly said look, we don't know what the utilization is, it's going to change customer to customer. Here's a range: worst case it's a little bit worse than GPUs, best case it's way better than GPUs. And so Inference Max will tell us what the actual performance is in inference because we don't know yet. Currently the open source software for TPUs is not good enough for us to just take the open source software and say that's the performance, because that's obviously not real. Anyone who is actually buying TPUs is going to spend engineering hours to work on it. And so we're trying to work with Google to get a real performance number that is achievable by people and will be upstreamed into the open source software because this is an in progress thing. No one cares what TPUv7 can do today. It's about what it does in six months. And so, obviously we don't want to be, today TPUs, if you're using VLM, are worse performance TCO than GPUs without a doubt, but the target is moving very fast. And there's a ton of low-hanging fruit for us to implement before we actually put a number out there. And so where does Google sit there? We'll see. I personally believe the TCO side of things, the total cost of ownership, is based on what we know on supply chain. How much do the chips cost? How much do the racks cost? How much does the liquid cooling cost? How much does the memory cost? How much do the cables cost? That's based on our estimates up and down. So, I think the TCO side of things we're pretty confident. It's the performance side of things where we don't know. There's a wide range and that's what we sort of tried to state in the article. Performance is a wide range.
Can you explain more about Google and Broadcom's relationship? Max Hodak from Neuralink and Science was asking on the timeline last week why have Broadcom as a middleman. Couldn't Google do the design and place the orders from TSMC themselves? What's your read on that relationship and how durable it is?
Yeah. So, when you think about chip design, there's a few different stages. There's defining the architecture and then there's actually implementing that architecture onto a process technology. There's laying out that architecture into gates on the chip and then there's the whole supply chain side of things. Negotiating contracts, getting allocations, etc.
That takes like 18 months, right? Isn't that like an 18-month process basically?
Yeah, 18 months or more. I would say Nvidia is faster on that side and Google's on the slower side just because Nvidia's been doing it for longer. They have a bigger team. But at the same time Intel has the biggest chip design team and they move even slower than that, they take like four years at least. That's what they did a year or two ago. We'll see what the new CEO can get into. But as far as Google, when they first started the TPU it was a very few people and they relied heavily, heavily, heavily on Broadcom to do everything. They just defined the top level architecture and Broadcom did everything I said below: negotiating with supply chain, figuring out how to lay out the gates, everything. As time has moved forward, Google has taken on more and more of this. Right now, they've talked a lot about AlphaChip where they use AI to help floor plan the chip. Once you have the architecture, how do I physically lay it out onto the chip? They've done more and more there. They haven't taken over everything yet, but that's sort of the point. But Google Broadcom has this super big advantage. Nvidia, they acquired Mellanox, call it five, six, seven years ago. Huge acquisition. Who's the biggest networking company in the world? Broadcom. Broadcom is the biggest networking company in the world. And when you talk about AI, it's the architecture of the actual processing elements, it's memory, which you're buying from the memory companies, Samsung and Micron, and then it's networking. When you try and boil it down to the most simple things, and software. The networking side of things is so important and the technical competence of everyone around the world besides Broadcom and Nvidia in networking is just not as good as them. They're actually good, but Broadcom and Nvidia are just so good and Broadcom is better than Nvidia in many ways at networking. So when you think about what is Google doing, yes, they're defining how the network topology is, but when you're talking about the physical networks, how packets get transferred, all these different things, Broadcom has heavy, heavy influence there. So, to this day, Broadcom is still charging margins like they did three, four years ago, even though Google has taken up more and more of the work. But at the same time, Google can't leave until they figure out how to do the networking and supply chain themselves or with a partner. And so what are they doing on TPUv8 that is potentially a distraction that's slowing down their execution is they're working with MediaTek. MediaTek at times has helped Cisco with their network chips. MediaTek has a lot of work on some of this networking stuff. They're nowhere close to Broadcom. On revenue, that's one metric, on technical competence, that's another metric. I think MediaTek is good, but they're just nowhere close to Broadcom. So now Google is having to work with inferior vendors to Broadcom.
And that's just to increase their margin on TPUv8.
I would even say their angle when they started this project was never we're going to sell TPUs externally. It was, dude, we're paying a 3x markup to Broadcom. And half the cost of this chip is memory. What the hell are we doing? At the same time it's like well sure physically the cost for the networking is not that much but what value does the networking bring is sort of Broadcom and then Broadcom's also doing the game theory of well you can't really leave us so we're going to charge you what we think is fair or what we think we can charge and Google's like oh no we're stuck to you. So MediaTek is taking way, way, way less margin, they're not passing the memory through them. And so this ends up being a huge advantage for them. Flip side is they've got to engineer all this work that Broadcom was doing. Instead of working on a way better architecture, they've got to work with a worse vendor, objectively worse, although MediaTek, like I said, is very good, to try and implement TPUs more directly with TSMC with less Broadcom sort of in the middle.
And Google, because it's risky, is going down both paths. They're continuing to work with Broadcom on TPUv8 and then a separate TPUv8 project they're working with MediaTek. Because they can't risk, fine, whatever 30 points of margin, 40 points of margin, 50 points of margin. I can't risk the TPU being late because ads runs on that. Gemini runs on that.
Yeah. Can you give any takes on Nvidia's $2 billion investment in Synopsys that got announced this morning? I don't know if you saw it. I'm assuming you did.
Yeah. So, in a time where the two biggest chip makers, Broadcom and Nvidia are making more money than ever and everyone else in the supply chain and all the hyperscalers are trying to design more and more chips. Everyone's sort of working on that. The EDA vendors are at the lowest valuations they've had on an earnings multiple basis for a long time. And this is on the eve of hey, objectively are there going to be more chip designs or less chip designs in five years? A lot more. Now the flip side is AI chip design is coming. There's 20 plus companies doing AI chip design. And we've got a really long article coming on that soon that will sort of explain the landscape. But AI chip design is going to shake up everything.
AI helping chip design, whether it's for AI chips or for like power chips.
And so the question is, Nvidia has a lot of tools internally. The dirty thing about EDA is that there's three companies that own 95% of the revenue but at the same time Google and Nvidia and Broadcom and all these guys also design a lot of their tooling internally although they are massive customers of all three vendors. So it's kind of like an oligopoly where the customers also contribute a lot. And so Nvidia's whole goal here is how do I get every EDA flow working on GPUs because today a lot of it is running on FPGAs, a lot of it's running on CPUs. And AI chip design is going to get a lot more AI influenced. How do I get everything working on GPUs? In terms of the operation of it, even if it's helping people design not GPUs. And I don't have enough engineers to work on all the software. They've open sourced a lot of software. Like KLayout, it's software for lithography. And they've got all this software up and down the chain all the way from lithography to laying out chips and all these other things. They just want to make it all run on GPUs. And so that's what their goal here is. And now they've given Synopsys a huge, huge, they're buying Synopsys at the lowest valuations that Synopsys has ever had with all this cash that they were going to give away in dividends or buybacks anyways. And they're getting Synopsys to now make GPUs first class. And so I think this is a win-win for Synopsys and Nvidia.
Well, we could go way longer, but I know what's on your calendar. You got to hit the gym. Thank you so much for coming by and chatting with us. This is really, really helpful. Have a great rest of your day. Enjoy the holidays with your family. Great catching up. We'll talk to you soon.
See you.
Let me tell you about public.com investing for those who take it seriously. They got multi-asset investing and they're trusted by millions. We have Ro Khanna in the waiting room. Let's bring him in to the TVP Ultradome. Ro, good to meet you. Welcome to the show. How are you doing?
I'm doing well. You guys have become quite the celebrities in my district. Everyone is tuning in to your podcast.
I'm glad to hear it. I'm glad to hear it and we're happy to have you on the show. Thank you so much for the time.
Are the All-In guys jealous or do they respect you?
I think that they have left, they're in the stratosphere. They have left the scraps.
Yeah, we're picking up the scraps compared to them.
I think like any great Silicon Valley startup, you're nipping at their heels.
It's funny. We had a New York Times piece around us. It was a very nice, just like here's what TBPN is doing. Just kind of an explainer piece. David Sacks, of course, got a little bit more of the investigative journalism treatment. Got five reporters. We only got one. And so I think that tells you about the relative importance of the shows. But anyway, I'm sure we'll get into that. I would love for you just to kind of set...
Normally when our guest joins and they're wearing a suit, we say thank you. But I think this is, I'm assuming it's one of your daily drivers. So yeah.
Well, you know, I'm not back in my district. It'd be the only way I'd lose my seat is if I started to show up with a suit to the place. But in DC with the uniform,
It's the uniform in DC. But I was hoping you could sort of take us through a little bit of the prehistory since it's the first time on the show. Just explain how you wound up in this position, a little bit of your backstory, and then obviously there's so many hot topics that I want to talk about in artificial intelligence and tech broadly. And I want your opinion on everything that's going on, but I'd love to kick it off with a little bit of like how you wound up in Congress.
Sure. Well, I am the son of immigrants. My parents came from India in the late 1960s. My grandfather spent four years in jail alongside Gandhi as part of the Indian independence movement. And that really inspired my love of public service. When I came out to Silicon Valley, I had a professor, Larry Lessig. He said, if you care about policy, go out to Silicon Valley. That's where the interesting things are happening. That's where the big things are happening. So I went out and I ran when I was 27 against the Iraq war and I got killed. I got crushed 71 to 19 but came to the attention of folks as someone willing to stand up against the war. And then I worked as a tech lawyer. I supported President Obama. I got to go work for President Obama. And then I wrote a book about what we needed to do to build new manufacturing across this country in 2012. What we needed to do to really have the modern economy in different parts of the country.
You're one of the first American, beginning of the American dynamism movement. Would you say?
Yeah. I was going to say to President Trump, he stole all my ideas in terms of manufacturing, but you know, he...
Well, that's good. That's good though, right? We just want...
No, no. Look, I support the American dynamism movement. I'm a fan of sort of what Marc Andreessen wrote in a Wall Street op-ed about how do we not make masks in America? How do we not make basic things in America? When my parents came to this country in the 60s, we were the place to be. We were humming. We were brimming with confidence. Kennedy said to go to the moon. And my first book was about why manufacturing still matters. I think it was a colossal mistake to let China eat our lunch on so many key industries, especially now with rare earth metals and magnets. I mean, we should have a Manhattan project to do that in the United States or New Zealand, Australia, Chile. But, you know, so after my time in the Obama administration, after I wrote this book, I said technology is going to shape so much of the future of this country. I have a vision of how we can make sure that it helps everyone in my district and around the country. And maybe I have something to offer to Congress. So, I ran against an incumbent again, lost again. California is a machine dominated state. It's very hard to break in and I persisted and won on my third try.
There you go. Third time's a charm.
And so, for this year, in 2025, how would you frame your top priorities? There's this weird disconnect that we've been tracking on like how relevant is AI? It's so dominant in tech and yet if you talk to somebody at Apple, they'll be like, we didn't want to focus on AI this year at all. We wanted to focus on battery life because that's what helped us sell phones and AI was actually not a driver of iPhone sales, for example. It's a deeply pervasive discussion point. And yet it's widely used, but also widely hated. It's such a unique technology, but just in terms of political priorities, what's been on the top of the stack for you this year?
I want to answer your question on AI, but obviously in the last few months, what's been a highest priority is getting these Epstein files released. Thomas Massie and I passed the Epstein Transparency Act. It was my bill, passed 427 to one, 100 to zero in the Senate and Donald Trump signed it. Most urgently, it's about justice for these underage girls, over a thousand victims who were raped at Epstein's Island. But it's also about this kind of idea of elite impunity that these rich and powerful people, I call them the Epstein class, don't play by the rules, which you and I have to play by and people are tired of it. And it also is a story of how in the world you get some things done in Washington. How did a Bay Area progressive congressperson end up getting Donald Trump to sign his bill and getting 427 people in the house to vote for it and 100 senators? So that has been the immediate priority. But what I say to folks...
So are you optimistic that the American people will ever get a truly cohesive narrative on the Epstein story or will it be our generation's JFK assassination?
I'm confident we're going to get far more than we've had so far. The release is now mandated by law December 19th or December 20th. I think more names are going to fall. You've already had some high-profile names fall because of their affiliation with Epstein, covering up for him or being inappropriate. There are going to be other names that come out. Now, do I think that it's going to satisfy everyone? No. There's always going to be some sense that we didn't get a full justice, but it's going to be much better than these women who were denied justice for decades, which was not partisan. I mean, they were shafted by a justice system that didn't work. And there are a lot of rich and powerful people who got away with it.
But look, what I tell people is that AI is going to matter even more than anything. And to your point about Apple, it's not AI literally as just AI as Grok or ChatGPT or a technology that detects patterns and can predict the future based on patterns. It's more that AI has become a symbol for a technology revolution that people know is changing everything about their way of life and the economy and where they feel like they don't have control, that they don't have a full say in what that's going to mean. They don't have a full say in what that's going to mean for their kids in terms of having good paying jobs and they're unsure if their kids are going to have as good a life as their parents had. They don't know what that's going to mean culturally for them as citizens. Are they going to have the same sense or are they just going to be manipulated by algorithms? And they don't know what that means culturally as their kids are on phones in school and becoming creatures with machines. And so this whole concept of how technology is going to be something that empowers people and that people feel comfortable about as opposed to fearful of is the challenge in my view of our time. And I've gotten attacked from some people in Silicon Valley saying, oh, it's kind of a Luddite. And I was like, no, I'm not a Luddite. Of course, I believe AI can do a lot of great things in medicine, in coming up with new disease and lowering costs, but I don't think we can be oblivious to people's concerns about keeping jobs and keeping social cohesion and making sure their kids are going to have a good economic future. And so I've tried to be thoughtful about how we adopt AI, how we adopt technology in a way that keeps the American dream alive and benefits folks.
And I mean that's such a wide remit, how we adopt AI technology, because you can see it implemented from a chatbot that some random person uses or kids are using AI all the way down to deeper in some the bowels of some enterprise software product that no human was ever interacting with to begin with and then it's just streamlined a little bit with some AI dropped in the middle of some big system. How are you thinking about creating some sort of taxonomy around AI? Do you like a divide between generative AI and more traditional machine learning workloads? Do you see a divide between consumer and B2B applications, self-driving versus what happens in a chatbot? Like how are you thinking about actually breaking apart that problem? Because there's so much there when we say AI.
I would say that the key distinction is is AI going to enhance human capability or eliminate human beings. That is the distinction and that we need to figure out as a society how we get more AI that is enhancing human beings as opposed to just eliminating them.
Let me share two thoughts on this. Both of people who influenced me. Steve Jobs described a computer as a bicycle for the mind. He didn't say computers would eliminate the mind. He just said it would make the mind go really faster and better.
Right. And my view is how does AI do that? And then Daron Acemoglu won the Nobel Prize at MIT, has this idea of total factor productivity. Let me try to explain it simply. If you just had AI replacing human beings and those human beings then becoming not productive, not only would you have frustration in our society, who wants to just get a check without contributing? People have pride, but you also wouldn't actually maximize total production because you have all these people who could be doing things who are not productive and not being able to earn a living and spend money. And so what he says is that there is some savings of that for consumers and for shareholders if a technology just eliminates labor. But the best technologies like electricity, like automobiles don't just eliminate people. What they actually do is they increase people workers ability to produce, that they are technologies that increase human capability. And so you have the benefit of the synthesis of the technology and the worker and that is actually what transforms lives and he calls it total factor productivity. And so my ideas around this has been how do we do that? How do we make sure we just don't eliminate four million commercial drivers? How do we make sure that the adoption of things is actually making us more productive and that it's being done with respect to workers and capability.
Okay. But so let's make it more specific because I agree at a high level with a lot of that. But let's talk about like a specific role or job like truck driving. You've generally come out against or have concerns around AI based job displacement with long haul trucking and truck drivers. On the other side of that, if I'm running a trucking company and I want to deliver the best possible service for my customers, it's possible that AI would be able to support that. What kind of policy do you think is right in order to create, you want some guardrails around the industry how AI should be used in trucking? I'd love to kind of understand more.
Yeah, I would say have a human in the loop. And so, what does that mean? When I'm on a plane, a lot of it is automated, but we still have a pilot there. And I'm glad we have a pilot. I wouldn't want to just fly in an automated plane. And so, does this mean that a truck driver's job may become more appealing? Because right now, as you know, we have a shortage actually of truck drivers and more demand. But if they have an assist from a technology that maybe allows them to rest more, that's less taxing. They're there for the edge cases if something is possibly going wrong. They're there to deal with maintenance. They're there to make sure that you have loading and unloading happening. We can reimagine what the role of a truck driver is going to be. And we can certainly have a temporary view that for the next five years that you should have the driver there. Now that doesn't mean that at some point there may not be jobs or certain parts of things that don't require a driver, but it doesn't seem unreasonable for five years to say you want a driver in the loop and let's rethink the types of jobs that will be. And if we need the government to be helping invest in developing of this technology, fine, but do it in a way that's going to be complimentary with drivers.
Yeah, this is kind of happening already with Waymo where there is a human in the loop and it's but you know the ratio of remote operators to cars on the road is potentially higher than one to one right now according to some reports. But over time I think the Waymo team expects there to be fewer and fewer humans in the loop over time. The question is how fast does that happen? And you're sort of proposing maybe try and make that as gradual as a process as possible because I mean you go back to like the elevator operator used to be a human now we use buttons and no one's really missing those jobs. They phased out over time. I think the main thing is everyone is concerned about rapid job displacement. Not necessarily the if I told you your grandson can't be a truck driver, you'd say, oh, you know, he'll find a different job. But if it's like every truck driver out of the job next year, that's obviously much more disengaging to the US economy. Is that how you think about it in terms of just timelines more than strict rules forever?
I think that's thoughtful. There's a famous economist who once said, jobs for the father, not for the son. And by that, he meant, look, we've got to make sure that people in their 30s, 40s, 50s, 60s have jobs. That doesn't mean that that's exactly what their kids are going to do or their grandkids are going to do. But a lot of these human in the loop legislation, we're talking about five years. We're not talking about 15 years. And we're talking about roles evolving. It may be that these evolve and then there's less of a need to hire folks down the line and you have a natural transition of folks, but you're taking people who are workers and making sure that they're productive and they have a good life. Let me explain why I think this matters. Phone operators, which people often give an example, and Alex, who's at Chicago, had a great point about this. That was 2% of the workforce. Commercial drivers are 10% of the workforce. You already have an anger in the country of so many people displaced by globalization, displaced by the concentration of wealth in some areas. And you really want to throw into this mix a rapid mass job displacement and then what? Just compensate them and have people stay at home and just get a check. Like is that the society that we think is going to be productive or do we rather figure out how they have some role and some say in the transition be managed in a way that considers their interests as well. And that's, you know, and I get that this is a good natured debate and people say, okay, Ro, you're adding some costs to the issue. And if all you cared about was shareholder profits and minimizing consumer costs as your only holy grail and you didn't care about jobs and you didn't care about communities, then people have a legitimate critique of me. But I would argue that that was the mentality during globalization and it's what's led to so much of the polarization not just of our politics in the United States but in the western world, led to things like Brexit, led to anti-immigrant sentiment and maybe we should consider jobs and communities not as dispositive but as a factor just like we consider consumer costs and shareholder profits.
Yeah. What's your look back on how the Uber story played out? Because that was a weird moment where there was a big push back from the taxi cab drivers. Those jobs still exist, but they're just way less profitable because the medallion system has kind of been undone. But if you want to make money driving someone, you can, but you're making less money. Like do you think that we should have handled that differently if we could run back the time or do you think it happened slowly enough that it was actually okay and delivered enough value to the consumer? Because Uber is one of those weird examples where the amount of taxi cab like activity, ride sharing activity, it 10x'd and more people take these rides than ever before in the taxi era. And yet it did have remarkable impact on the market structure of that industry.
Well, I'd be hypocritical for saying I'm against Uber. I take Ubers all the time.
A expose, you know, next time I get into an Uber. But I'll say this, we should have done more for the medallion owners. I tried actually in New York. This is before Zohran Mamdani became Zohran Mamdani when he was an assembly member, he was really focused on a lot of these taxi drivers who had lost their medallion value and were underwater and what could we do to compensate them. And I had actually reached out to Jamie Dimon who tried to do something to his credit through JP Morgan and it ended up not working out. But you know, we should have as a government done more to help those folks who had medallions who lost all their value. And that's an example of something where we could have been more proactive. And then there's a huge debate about Uber drivers and whether they're getting enough value and have enough say over their lives. I would argue that we need that. And I'd argue we need national health insurance. This is the biggest area where if you're not going to be employed as a traditional employee, it would really help if people didn't have to buy healthcare on an exchange that has soaring premiums. So, there are better things we need to be doing to help that Uber driver. But am I glad that there is a technology like Uber? Yes, I am. I think it has created jobs and it has made life easier for many people.
