I see a large IPO on the horizon.
You're surrounded by jungle. Hold your position.
That's misinformation.
>> According to clearing order, let's just roll.
We are surrounded by jungle. Hold your position. Come on. Get up.
Trust the experts.
We are founder.
I see multiple journalists on the horizon. Stand by.
>> UAV online. >> Blaze. >> Double blaze. Triple blaze. Double kill.
Michael is w team deathmatch.
We are experts. Triple blade. That's just wrong. Right.
Hockey clearing order inbound. Get up.
>> We are surrounded by journalists. Hold your position. Strike one. >> Strike two.
Activate golden retriever mode.
>> Mark clearing order inbound. Five cook founder.
>> You're watching We are not a car. >> We are not a car. >> We are not a car. It is Thursday, April 16th, 2026, and we are live from the TBPN Ultradome, >> the temple of technology, the fortress of finance, the capital of cars.
>> The capital of cars. Absolutely wild podcast between Nvidia's Jensen Huang and Dwarkesh Patel. So many clips, so much debate. We're going to kick it off with the question of whether or not Nvidia is a car. First, let me tell you about our lineup because we have an insane group of guests joining us today.
Kicking it off with Ben Smith from Semaphore. I think it's his third time on the show. He's live from the Semaphore World Economy Summit. He has convened a massive group of policymakers, CEOs, investors. He's going to give us the update on what conversations are happening on the ground. Then Jonathan Criss is coming on to talk about Starlink for water. Former SpaceX employee just raised $24 million to enable off-grid desalination. One of my favorite topics these days. We talked a little bit about it with Peter Diamandis. Then Paul Scherer from IEN raised $15 million from Benchmark. James Morrissey and Kevin Hart are coming on to talk about building a tequila business and a consumer social play. And we will be asking him about Jensen. We've got to ask. I got to know.
>> Ulisses from Factory. We have a massive $46 million fundraise today for underwater and surface drones. Charlie Cheever from Expo is coming on. And Victor from Slash is coming on as well. And then we'll close it out with Theodor from Cognition. So big show, should be going at least two and a half, three hours as usual. We will be off tomorrow, but we'll be back on Monday. Let me start off with the clip from SemiAnalysis because it is a treat.
>> Wait and pause for a second. >> I don't... >> You know why I was asking you? >> Yeah. >> Like what app you use to edit videos? It was to make this exact video and then I saw this and I was like, oh, I don't need to make it.
>> Yeah. You're not talking to somebody who woke up a loser. And that loser attitude, that loser premise makes no sense to me. We are not a car. We are not a car.
Such a great edit. It's absolutely such a good vibe.
>> And it's so funny because... >> I love the Tokyo Drift. We're good.
>> It's funny because it's this new type of vibe where the SemiAnalysis team obviously they recontextualized the two clips and added the beat to get the video going, but that final edit with the cars sort of morphing together like it goes from there's a match cut. These are match cuts between one stick shift move and another or one car drifting and then another car drifting. That takes a really long time. Somebody clearly made this video just because they're an enthusiast of Fast and Furious and then the SemiAnalysis team was able to quickly recontextualize that to be about Jensen's answer on Nvidia's moat and the CUDA moat and what's happening with Nvidia.
So let's go through this question because it's been bubbling for a while and it's sort of bubbled up most recently because there was a whole bunch of news that Mythos might have been trained on Trainium, then maybe TPU, then maybe Blackwell, and sort of a mix. And it just feels like more and more of the AI labs are capable of making other chipsets work. In the early days, it was all about Nvidia and now it feels like the incentives are really high to figure out other options and that creates a different competitive dynamic.
So we can run through my thoughts on this and then we can go into the geopolitical considerations as well because that was another fascinating segment of the interview. So Jensen, the CEO of Nvidia, spent over 90 minutes, it was almost two hours when you include the ads too, in the ring with Dwarkesh Patel. It was electric and the key question at least for the start was whether or not Nvidia is a car. And I'm only half joking about that. It sort of was the key question.
Nvidia has been the market leader for years. During the gaming boom, Nvidia was the gold standard for rendering PC graphics. There was always decent competition from AMD. But once the AI boom kicked off, the CUDA ecosystem significantly sped up development of AI systems and training of AI models. And for those who aren't familiar, CUDA is a programming model that enables GPUs to accelerate demanding workloads by parallelizing computation.
So instead of needing to work on the very low-level instruction sets, if you are a CUDA kernel engineer, you can access all the power of the GPUs very efficiently while staying up in the more mathematical AI research, more standard Python, C++ programming paradigms. You don't need to dip down too low, but it's getting easier to dip down lower and that's what we're seeing.
So that created the CUDA moat because developers were way more productive and the biggest bottleneck to progress was allowing AI researchers to quickly test ideas and scale their experiments up to whole fleets of GPUs and eventually entire data centers. So at the time, researchers really liked CUDA and really liked Nvidia and they did not want to have to spend hours and hours figuring out other hardware systems. They just wanted to run their tests and see if the model was getting better and continue to scale.
But recently the biggest cost center for AI labs flipped from researcher time more or less to compute capacity and this creates a much larger economic incentive to figure out a way to drive down the cost of chips used to train AI models. I wrote about this back on Tuesday, October 22nd of last year. So almost six months ago. I said not every link in the supply chain of AI can be completely commoditized.
Nvidia has an insane amount of power having ramped full-year revenue over the last three years from $27 billion to $60 billion to $130 billion. Absolutely insane top-line revenue ramp at that scale. And that's why Jensen is so confident about how dominant this business is. It's the world's biggest company for a reason. It has been growing spectacularly at immense scale.
And not only did they grow the top line, but net profit margin grew insanely. So it grew from 16% to... >> you do that when you have pricing power and massive leverage because you know in this case demand massively outstripping supply plus developer love and kind of just like... >> and I believe the forecast net margin was 70-something percent. We were hearing about 80% potentially.
And so Nvidia, you know, the plan and the plan is still to make an incredible amount of profit off of these chips because they are incredibly valuable. But all the hyperscalers and the AI labs, they are sort of incentivized now to form a bit of an anti-Nvidia alliance to commoditize the accelerator market and drive down those margins at least a little bit.
And so today the AI chip market is starting to look much less monopolistic. AI coding agents can make it easier to write software that works on non-CUDA chip stacks. And the teams behind competing chips have plenty of resources and economic incentives to bring performance in line with Nvidia. Even if it's going to be a big hassle, even if you're going to need to spin up a team to get AMD or TPU working, it's going to be worth it because you're talking about billions and billions of dollars spent on chips.
>> Yeah. Another example of like, you know, an instance where an AI lab had so much urgency that they were willing to spend whatever it took was Meta rebuilding like Llama. >> Yeah. Exactly. >> Like they were willing to outspend pretty much any other lab on talent because they didn't have time to find homegrown talent or go through a normal recruiting process. Especially considering a lot of those engineers were like happy doing what they were doing.
>> Yeah. Yeah. Exactly. The incentives flip when you get to this scale or the incentives just get so big you can build a whole team for a specific thing, solve any problem. And so for the past few years, Nvidia has sort of looked like SpaceX's launch program. It's an incredible technology with very few viable alternatives. And so that creates great margins as we've seen with SpaceX's launch capacity. And they control something like 90% of the launch market.
While the products have not degraded, quite the opposite actually, Blackwell and Vera Rubin are incredibly powerful chips. They're clearly on the leading edge there. And they have an incredible amount of supply chain guarantees from TSMC and across memory and all the other different pieces of supply chain. Like Nvidia is ready to make more chips, but increased competition makes the category look a little bit more like the car market than the rocket launch market.
And so that I think is where Jensen is pushing back and saying, no, there's a lot more that we bring to the table with our customers that don't think of us like a car. This is not, you know, the difference between a Ford and a Toyota. They all sort of get you to the same place and you can swap one out. You can be driving a BMW one day, go to the dealer, turn it in for a Mercedes, and you're going to have a pretty...
>> Yeah. The other example that I was using with the team earlier was this idea of like if you're a delivery company like FedEx and you have a lot of like Ford vans and then... >> and then Hyundai comes to you and says, hey, you've been spending like $50,000 per Ford van, but like would you consider a Hyundai van? We'll sell it to you for...
>> $35,000. It's just as good. And it could be like mildly inconvenient for the company because like they're kind of used to using Ford. They maybe have like an internal team that does some maintenance. But when you start looking at that cost differential, it can start to get pretty interesting to say like, hey, why don't we try out some Hyundai? Let's move over some of our routes to Hyundai's and see how that goes. And they try it and they're like, hey, this actually works pretty well. Maybe there's like, you know, higher maintenance, but it actually like maths out. Yeah.
>> And like we're going to actually start adding more Hyundai to our overall fleet. And so Jensen's point on the podcast is that like we're not selling cars, right? This is not like something like you can swap out. And Dwarkesh was obviously pushing back.
>> And for a lot of companies swapping out Nvidia for TPU would be very difficult. Some workloads that Jensen focuses on. He says we're not a tensor processing unit. We're an accelerator. There's a whole bunch of scientific computing workloads that work particularly well with Nvidia. The problem that...
>> And of course was just saying like, yeah, well, it's perfectly fine to have like a specialized chip for specialized workflows because the biggest companies in the world, the biggest buyers here have like a single type of workload that they're trying to do and that's why they're using your competitors.
>> Yeah. And so, because the AI buildout does not seem to be slowing down as long as power can continue to be brought online and data centers can continue to find towns that will approve of them, demand for chips will presumably grow. But every chip designer and AI lab has to be praying that those net margins come down. How quickly will it happen? Very early to tell.
The market did not react negatively to this back and forth in the short term. Although the price of Nvidia has been basically flat since last August and I think that's why Jensen is trying to sort of like reset on the narrative because it's possible that, you know, there's a lot of movement up and down. They've been sort of flat. There's a desire to sort of like reset and recontextualize.
>> Yeah. Inference demand is scaling. Yeah. >> In a very significant way and the Nvidia stock price is relatively flat. >> Yeah. And since August there's been so many different moments where fears of the AI bubble, fears of the products not finding product market fit, that revenue might stagnate. Like we've seen a ton of bullish signals for like AI demand broadly. Demand is there. And so if you're a supplier, you should also be going up, but there's been this overhang of what will happen to margins and market structure. And so that is what people are going back and forth on.
Tyler, did you have any other thoughts on this? Like... >> I mean, like personally, I think I probably am more on the Dwarkesh side where like... >> Yeah, I mean, at some point like these margins are so high, there's so much opportunity here. Like we've seen that like actually, you know, if you're a big lab, you actually can just like put a... maybe, you know, it's a lot of resources, but you actually can just like train a model on a different architecture. You can serve them on a different architecture. Like you actually can figure these things out. As models get better, you can, you know, you can go lower and lower on the stack. Yeah. You can, you know, you can write the kernels. Yeah. Semi-autonomously, these things get faster and faster. And it's like I'm probably much more on the Dwarkesh side.
>> Yeah. It'll be interesting to see how Grok fits into this. The new CPU integration between different pieces of the puzzle. And then also, I mean, Dwarkesh makes this point that the supply agreements that Nvidia has might be a bit of a moat for the next few years while TSMC line time is so constricted.
>> Yeah. But even then, like, you know, Jensen was saying the kind of supply constraints, this is like a two to three year problem. After that, like you can just solve these things. Yeah. So it's like almost like I don't know how to think about this because, you know, to me it seems like, yeah, so much of the value of Nvidia is just like they have such an incredible relationship with TSMC...
>> but if... and it's so valuable because of how constrained it is. But if that kind of constraint is maybe going to, you know, go away to some extent... >> at TSMC. >> Yeah, that's what he says, like that they're going to increase, you know, they can build a new fab in whatever, three years.
I mean, the big takeaway from the conversation is like you have one person who seems incredibly AGI-pilled, which is Dwarkesh, and then you have Jensen who doesn't seem AGI-pilled in that sense at all, right? He... Dwarkesh asks about, you know, he was kind of getting at early on the idea of like, can you just like prompt your way to Nvidia chips? He's like, you basically sell software...
>> and uh... >> he didn't put it quite as aggressively. But yeah. >> Yeah, that's of course like, you know, more on the nose, but Jensen was basically like, no, I don't think that'll happen. And then when you get to the whole geopolitical conversation too, again, it's like Dwarkesh is like, you're selling nukes, and Jensen is in my view like, I'm selling computers. Yeah. Right. Yeah.
And that was like the big rift. It was like these two kind of totally conflicting world views and it made for some very... >> pay-per-view. >> It was a pay-per-view. It should have been a pay-per-view.
Yeah. Shriram Krishnan summed it up pretty well. He said, every person's reaction to the Jensen plus Dwarkesh podcast can be extrapolated directly from whether they believe in the frontier labs achieving short timelines for AGI, ASI. If you believe in the labs achieving RSI and then AGI, ASI for some definition of all three in the next few years, you're probably sympathetic to the frame Dwarkesh adopts. If not, you're probably more sympathetic to the arguments from Jensen.
And so we can go into the export controls next and talk about that. Metacritic Capital sort of summed up a little bit of why just Jensen's rhetoric and how he wasn't conceding a lot of things. Dean Ball said, Dwarkesh reveals how inconsistent and unbattle-tested AI acceleration talking points are, especially when they're filtered through the prisms of corporate comms and mass politics. Strategically coherent accelerationism is possible, he says, I try, but not currently prevalent.
And Metacritic Capital says, the problem is that Jensen doesn't concede anything. Compute spending going to the moon. One trillion revenue in sight. Models keep getting better. No unemployment. Software codes are good. Other Western accelerators are bad. Chinese competitors are good. Nvidia makes token costs decline 90% per year. But Chinese compute scientists are capable of making all the necessary algorithmic improvements. He also can't be AGI-pilled enough because at the end of the day, he is an intellectual property company in the business of sending a file to TSMC. I think it's part of Taiwanese culture to want to be loyal to all clients and don't have favorite winners. He doesn't want to betray his software customers. He has antitrust concerns.
>> Yeah. He was making the bold case for software, which was that AI agents are going to use tools. So he's like, there's going to be more users of software than ever, which is something I'm like somewhat sympathetic to, but yeah, it definitely... >> it's still very easy to take the counter... >> the flip side of that. Yeah.
Well, let's play the distilled recap from Dwarkesh Patel of the back and forth with Jensen on export controls. It's about four minutes and we'll watch this and then discuss. So...
>> if Chinese companies and Chinese labs and the Chinese government had access to the AI chips to train a model like Claude Mythos with these cyber offensive capabilities and run millions of instances of it with more compute, the question is, oh, is that a threat to American companies, to American national security? First of all, Mythos was trained on fairly mundane capacity and a fairly mundane amount of it by an extraordinary company. And so the amount of capacity and the type of compute that it was trained on is abundantly available in China.
And so you just have to first realize that chips exist in China. They manufacture 60% of the world's mainstream chips, maybe more. It's a very large industry for them. They have some of the world's greatest computer scientists, as you know. Most of the AI researchers in all of these AI labs, most of them are Chinese. They have 50% of the world's AI researchers. And so the question is, if you're concerned about them, considering all the assets they already have, they have an abundance of energy. They have plenty of chips. They got most of the AI researchers.
If you're worried about them, what is the best way to create a safe world? Well, victimizing them, turning them into an enemy, likely isn't the best answer. They are an adversary. We want the United States to win. But I think having a dialogue and having research dialogue is probably the safest thing to do. This is an area that is glaringly missing because of our current attitude about China as an adversary. It is essential that our AI researchers and their AI researchers are actually talking. It is essential that we try to both agree on what not to use the AI for.
With respect to China, we want to have, of course, we want the United States to have as much computing as possible. We're limited by energy. But, you know, we got a lot of people working on that and we had to not make energy a bottleneck for our country. But what we also want is we want to make sure that all the AI developers in the world are developing on the American tech stack and making the contributions, the advancements of AI, especially when it's open source, available to the American ecosystem. And it would be extremely foolish to create two ecosystems: the open source ecosystem and it only runs on the Chinese tech stack, and a closed ecosystem that runs on the American tech stack. I think that would be a horrible outcome for the United States.
I mean, I think the concern going back to the flop difference and the hacking is, yes, they have compute, but there's some estimates that because they're at 7 nanometer, they don't have EUV because of chip-making export controls, the amount of flops they're about to actually produce, they have like one-tenth the amount of flops that the US has. And so with that, could they train eventually a model like Mythos? Yes. But the question is, because we have more flops, American labs are able to get to these level capabilities first because Anthropic got to it first.
They say, okay, we're going to hold on to it for a month while all these American companies, we give them access to it, they're going to patch up all their vulnerabilities and now we release it. Furthermore, even if they trained a model like this, the ability to deploy it at scale, you know, if you had a cyber hacker, it's much more dangerous if they have a million of them versus a thousand of them. So that inference compute really matters a lot. In fact, the fact that they have so many researchers who are so good is the thing that makes it so scary because what is it that makes those engineer researchers more productive is compute.
>> We should always be first and we should always have more. But in order for that outcome, for what you described to be true, you have to take it to the extremes. They have to have no compute. And if they have some compute, the question is how much is needed. The amount of compute they have in China is enormous. I mean, you're talking about the country is the second largest computing market in the world. If they want to deploy, aggregate their compute, they got plenty of compute to aggregate.
Very, very tense back and forth. Dean Ball says it's a shame Jensen mostly fails here because the monoculture on export controls is bad. If you're a young AI policy researcher trying to make a name for yourself, it's almost impossible to be taken seriously unless you are pro-export controls. Monocultures are usually bad. And I am sympathetic to Dwarkesh's points there for sure, especially on the inference side.
Even if models exist in both worlds, like having a whole bunch of, you know, good guy compute that can go and patch bugs while the amount of attackers is much smaller. It's just a matter of, you know, how many resources you have on each side. That's a great point. The only thing that they are like talking around is just Taiwan as a particular turning point and how their various positions flow through to Taiwan policy and where the... how the China stance on Taiwan is something that I've always puzzled and I wish that both of them had articulated their sort of philosophy on actually wargaming out what export controls do to likelihood of Taiwan intervention or blockade or anything like that.
I don't exactly know. I've been trying to like work through it, but I don't have a complete thesis, but we've been debating it back and forth all day. I don't know if you have a strong take on any of this, Jordi.
>> I appreciate Matt Zitelland's point. I kind of appreciate that Jensen Huang seems relatively normal about non-business stuff compared to other tech founder CEO types, but then when it comes to Nvidia's actual operations, he's a complete sicko.
>> Yeah. Yeah. I saw a couple takes around this that he had like some very, very strong points if you're deeper in the supply chain. I couldn't really assess how he did on that, but some people were. There were definitely people that were in Jensen's camp. It was divided, which I think is why this went so viral.
Elliot Arledge summed it up here. Jensen Huang on Dwarkesh today. Most combative interview he's done in a while. The biggest regret not funding... >> Has there been a more combative interview ever with Jensen? It seems unlikely. >> I think so. No.
And I'm trying to think of just like in terms of combative, like people were sort of comping this to like the Elon Dwarkesh interview, which wasn't combative, but it was more just like digging into all the different projects and trying to elucidate the strategy and how they all fit together. There's actually some interesting updates on where XAI might be going with a partnership with Cursor that we can go into.
There is some funny details in here. Apparently the Larry and Elon begged Jensen for GPUs at dinner story. That never happened. We absolutely had dinner. At no time did they beg for GPUs. Which is funny. I wonder what would happen. Quietly folded Grok into the CUDA ecosystem. Reason premium ASP tokens where latency beats throughput. Higher throughput used to always win. That trade-off has bent though, bent enough that Nvidia is expanding the Pareto frontier towards fast, expensive, low throughput. And it will be interesting to see how all of that comes together.
On ASIC cost savings, Nvidia margin is 70%. ASIC margin is 65%. What are you really saving? Someone still pays Broadcom. Open challenge to Google and AWS. Publish TPU and Trainium on MLPerf and Inference Max. I would welcome Trainium to demonstrate their 40% claim. And so Jensen threw down the gauntlet and said to Amazon and Google, head over to SemiAnalysis and put your chips on Inference Max so that they can be properly benchmarked so we can see.
>> Yeah, that was a very good call out. >> Yeah. Yeah. It was smart. I've just... I just don't know why they don't go over and... >> I've been excited for Inference Maxing... >> to see the Inference Max results.
Dwarkesh posted a photo and it's him and Jensen standing next to each other and Alex Vulkov said, hey, Dwarkesh, was this picture taken before or after the pod? Because it does feel like it was a tense situation. Although, you know, to both of their credit, like Jensen, it felt like he loved being in the arena, getting asked hard questions, like working through this.
There's this back and forth where Jensen's pushing back and Dwarkesh says, ah, I can drop it. And he says, you don't need to drop it. I'm enjoying this. Like, let's hash this out. And I thought that was very diplomatic and just good overall.
Well, Intel is up on the news, up 4% today, 10% over the past five days. Almost at all-time highs. I think we're very close to the 2000 peak for Intel, which it was also around where they were trading in 2021. $67 a share, $330 billion company. Clearly with all of this backdrop and just the idea of more chips and maybe the CUDA ecosystem being something that you can work around, can an American fab run by Intel produce a chip that's viable for an AI lab? It feels like increasingly yes.
That's certainly the argument that's being put forth by Dwarkesh and it would be very exciting. I think it's something that everyone would support, an Intel resurgence. And there's some news around TerraFab potentially getting involved. But first, let's start with the scoop from Grace K over at Business Insider. She says, scoop, Cursor plans to use XAI's infrastructure to train its Composer 2.5 code.
>> Where's the golden scoop, Tyler? >> According to people familiar with the matter, Cursor will use tens of thousands of XAI's GPUs. They said, and we got a scoop for Grace K. >> This one's going to Grace. Grace, congratulations. >> You win the golden scoop. The golden scoop. >> Congratulations.
Now, interesting to see something we talked about probably midway through last year. XAI's shown a tremendous ability to, on the infrastructure, data center side, spinning up a huge amount of compute very, very quickly ahead of any timeline that any reasonable party would have probably expected. And demand hasn't exactly followed in the way that they would have liked. And so opening that up to a company like Cursor who has all the demand and what they really need is their own...
>> is their own model. >> Yeah. It was also interesting because I don't know if it was thrown out as a potential project for other companies. I feel like MSL mentioned it at some point, maybe OpenAI, but there was some talk of like, okay, if you're marshalling all this compute and you wind up with too much, like what do you do then? And the idea of becoming a cloud provider if you have a data center and everything...
>> and that's been the big question of like, with everything that SpaceX is doing and now TerraFab, they're going to be creating all of this capacity. Yep. But where's the demand for that capacity going to come from, right? And so you could imagine a world in the future where if SpaceX has a bunch of space data centers, they open up that capacity to a bunch of companies other than Yep...
>> just Elon Inc. So, Grace says, the setup effectively turns XAI into a kind of cloud provider by renting some of its GPUs to other companies. XAI could start generating revenue from its massive infrastructure while still developing its own AI models. The arrangement could help the company offset the costs of building and operating data centers while also deepening ties with a startup that has access to valuable coding data. And so there could be some sort of trade deal going on.
Ed Lello at Bloomberg has a report from the TerraFab. Musk's team is actively requesting price quotes and delivery timelines for a wide range of chipmaking equipment, photo masks, substrates, etchers, deposition, cleaning, testing tools according to sources. Elon Musk's lieutenants have reached out to chip industry suppliers for his envisioned TerraFab project. Remember he was pictured with Lip-Bu Tan from Intel I think last week. Early steps in an audacious and likely arduous attempt to break into the production of cutting-edge chips.
That is a very, very tall order. But maybe there's never been a better time to break into the cutting-edge chip market given that you don't need to... I mean, you sort of need to reinvent CUDA, but it's becoming easier potentially. That is the story.
Well, there are two big releases from Anthropic and OpenAI today. Claude announced Claude Opus 4.7, our most capable Opus model yet. It handles long-running tasks with more rigor, follows instructions more precisely and verifies its own outputs before reporting back. You can hand off your hardest work with less supervision, they say. Very good score on SWE-bench Pro, 64.3%. Excited to test it.
They say Opus 4.7 has substantially better vision. It can see images at three times the resolution and produce higher quality interfaces, slides, and docs. As a result on the API, the new X high effort level between high and max gives you finer control over reasoning and latency on hard problems. I'm excited to see how these do on ARC-AGI v3.
>> I think the most notable thing here is you have a model card that shows a model that's not publicly accessible. >> Yeah. Yeah. They share the Mythos benchmark. So... >> Mythos mogging Opus 4.7 just sitting there, but of course unless you're one of select companies, you won't be getting access to it at least yet.
Well, Addi gave Opus 4.7 the tiny man bench, which is a very funny one where you ask the model, I am a tiny man. When my son was born, they handed me to him. And Opus 4.7, that's a nice little riddle. The answer is a bar of soap. No, wait. Let me think about it. Tiny man handed to him when his son was born. This sounds like it's pointing to a cigar. The tradition of handing out cigars when a baby is born and a cigar can be thought as a little man-shaped object. That is very, very odd.
This is like the new how many Rs in strawberry where all the models seem to have weird results for this. We of course have shrimp fried rice bench which no one has really solved. Even just humor bench and tell us a novel joke has been increasingly difficult for these companies.
>> Yeah, I think we're going to have to wait and see on Opus 4.7 what the reactions are. I will be keeping an eye on Dan Shipper who always does great analysis immediately after launch. >> Yeah.
>> Yeah. I mean, I feel like generally benchmarks are like almost completely meaningless at this point. Like there's so many like open source models where they can like really... I don't even know if they're like actually benchmaxing. >> Yeah. >> But like you just talk to the model for a while and you say like, okay, this is a good model. Okay. Or this is not a good model. Like it's very hard to get like a quantifiable signal at this point.
>> Yeah. I mean, increasingly, it feels like all of these models will be sort of like tested through like enterprise rollouts and you'll just do a demo project, swap in something, test this model, test that model, just see, okay, well, our goal was to deliver value and we had some KPI like reduce cost, increase sales. Like were we successful when we implemented this model, rolled it out to our team, used it for a couple weeks, did we see a tangible result or not. That's at the end of the day all that matters for businesses. So I could imagine that that's where all of this goes.
Well, OpenAI announced Codex for almost everything. It can use apps on your Mac, connect to more of your tools, create images, learn from previous actions, remember how you like to work and take on ongoing and repeatable tasks. With computer use on macOS, Codex can now use any app by seeing, clicking, and typing with its own cursor. It runs in the background without taking over your computer. Working on tasks like front-end iteration, app testing, or any workflow that doesn't expose an API.
You can now generate and iterate on images with GPT Image 1.5 and Codex to create front-end designs, mockups, game assets, and more without leaving your workflow. Usage is included in your ChatGPT account. No API needed. Automations can now run in the same thread. Lots of updates here. And Thibault says Codex just got a lot more powerful. Computer use, in-app browser, image generation, editing, 90 plus new plugins to connect everything, multi-terminal, SSH, lots and lots of stuff. So go give it a test. Go take it for a spin. openai.com, of course. And you can download it for macOS.
Well, speaking of websites, DJB went to the Oreo website and hit accept all cookies. Now, we wait. I love this. Very funny. What else is going on in the timeline? The West creates the internet. Try nailing that jello to the wall. CCP nails it. The West creates LLM. All right, try nailing this. And the CCP picks up a hammer.
There's a piece in the Wall Street Journal opinion section. AI is bound to subvert communism. This is a very contrarian take because people, at least with the internet, there was the perception of like decentralization, permissionlessness, anonymity, a lot of things that felt very democratic. AI is very centralizing by default. This is the Teal take of like AI is communist and crypto is libertarian. And so this is a pretty wild thing to argue, but read the opinion piece and see what they say.
The nailing jello to a wall, I believe that's from the Clinton administration. The idea that the internet would spread so widely that the Chinese Communist Party would not be able to control the population, everyone would be coordinating, it'd be sort of like an Arab Spring type moment. But of course the firewalls went up, the surveillance happened and nothing really changed and the Communist Party seems stronger than ever.
But this does sort of undergird a lot of what Dwarkesh has been saying about the risk of China and having strong AI and stronger control over the population. It's always hard to get a read on exactly how things are rolling out in China. There's some people that seem to like it over there. Of course, Dwarkesh took a whole trip to China and made it back. Okay, so it's not all doom and gloom, but it is a tricky thing to argue, but we'll see.
>> YouTube, according to The Verge, now lets you turn off Shorts. >> It is getting community noted. >> What does the community note say? >> This feature is a new setting for YouTube time management. Does not hide the Shorts tab in the app, nor does it hide Shorts from appearing in recommendations when set to off. The only change is that a dismissible warning screen will appear when the Shorts tab is selected. So...
>> Oh, interesting. >> Yeah, I've tried. I land on YouTube on my phone, it immediately recommends a bunch of Shorts. You can hit the three dots. >> Yeah. >> And say like, show me less Shorts. And that feature does not work at all. And I don't watch Shorts on YouTube. >> And I don't watch Shorts on YouTube. >> The Shorts in the feed have been a lot. I wonder if they're seeing... Yeah. I mean, they must just be seeing data that shows that the Shorts are more retentive or keep people on the...
>> Well, when you're using YouTube as a video search engine, there are so many types of searches where it can be vastly preferable to watch a 60-second video on something. So an example is like if you're doing research on cars. >> Yep. >> And you want to like quickly understand how the seating... I need to get a new family car, right? So I've been looking up different cars, trying to get a sense of like how spacious the cabin is, what the seating arrangement is like.
And so I'd rather just click into a Short and just get a quick 60-second overview and then bounce. I don't need to see like a 15-minute review of the entire car. But yeah, it's... >> that YouTube Shorts creator Forest Auto Reviews sort of pioneered the perfect 60-second car review where he talks really, really fast and says like, inside you get Apple CarPlay and Android Auto and the heated leather and massaging seats and vinyl on the dash and carbon fiber here and he sort of runs through the whole car in 60 seconds. Shows you how fast it takes off if it's a fast car. Opens the door, shows you all the features and it's sort of like a 20-minute Doug DeMuro video cut down to 60 seconds, which of course is doing very well.
Doug's response has been to create one-minute cutdowns of his content and so you can enjoy that as a Short as well if you want. But if you do want to turn off Shorts on the YouTube feed, the way to do it is to uninstall the app, use the mobile version, and then get a plugin that... there's an extension for Safari, I think, that will just go and remove the actual Shorts that...
As they pop up. But, uh, it's a hassle and it's slower than using the app. So, hopefully, uh, this feature becomes more real in the future since it does seem like some things that people are demanding. But, uh, always tricky to ask a platform to give you an option that would, in theory, increase churn. Uh, very, very tricky.
Uh, well, we have the beginning of our guest lineup starting now. We have Ben Smith from Semaphore. He is the editor-in-chief. He's in the waiting room and let's bring him in to the TV ultra. Ben, how are you doing?
What's going on? Doing great. Can you guys hear me? All right.
We can hear you. We can see you but we don't know where you are. You're looking very sharp.
Dapper, I might say.
Thank you. That's, you know, we're convening the biggest gathering of business leaders in the US this year here at Semaphore World Economy.
How many business leaders is that? Yeah. How many people are attending?
500 global CEOs and then lots of political figures from the US and Europe.
Had Scott Bessent earlier. We got Lutnik later. I assume they all just kind of came over from Hillen Valley.
That's great. Uh, what's the structure of the conference? It's a few days. Are there specific breakout sessions, talk tracks, uh, certain themes, or is it sort of more driven by the individual who's on stage at the moment?
You know, it's five days, three simultaneous stages, a bunch of really interesting kind of Chatham House rules breakfasts and dinners and things like that. Um, and I mean, the core topic is really kind of where we live is the intersection of politics and sort of political power and finance and technology. And so, I mean, that is what people here are obsessed with.
Yeah. And within that intersection, what are the top topics that people are discussing in particular? Obviously the conflict in the Middle East is big but then AI is big. What's actually driving the conversation today?
You know, every conversation winds up coming back to AI.
Um, and yeah, and I think whether that's, you know, Bessent, actually I had an interesting conversation with Bessent on stage where he really downplayed the conflict with Anthropic. Okay. He said they have kind of like some minor technical issue with the Department of War. The Treasury is working with them to make sure, you know, the banks don't go down. Sure. Um, but just, you know, I think there's just a sense in particular that like really big enterprises and the kind of big brand name American companies are the ones most at risk. Yeah. Uh, in the transition and I think people who work for those companies, who advise them, who compete with them are thinking a lot about that.
Yeah. What about on the labor side of big business? We've seen some reasonable strength in the job market recently. At the same time there's a lot of layoffs going on. And how are people grappling with the unemployment situation in the economy?
Yeah. I mean, you know, the numbers are good. Yeah. And yet there is this sense, you know, among the American public that AI basically exists to put everybody out of work and they hate it. Yeah. And so that's lingering over things. And I do think there's also a sense that like the class of 2026 is not a great time to get out of college.
Yeah. And I think there is, I would say, like both kind of authentic nervousness about, you know, what is everybody's labor force going to look like because of course class of 2026 are also the ones who aren't native to these tools. Yeah. And are the ones you ought to be hiring. Yeah. Um, and then also of like, are they going to come and chop everybody's heads off when they realize they aren't getting jobs. So I would say those two competing questions about the youth.
Has there been any discussion around resolutions to that or economic policy that can strengthen the safety net or, you know, deal with taxes or more weekends or anything that can sort of offset the anxiety about weakening labor markets?
You know, every member of Congress is like thinking about this all the time, taking questions about it all the time, and yet also aware that this is an institution that spent like 20 years talking about regulating social media and only now is sort of getting to it, but most of it's happening in the states. Yeah. And so I think there's a lot of pessimism that Washington will act. Um, but I think there's also a sense that I think a lot of companies are seeing unexpected jobs coming out of AI. I talked to somebody who operates like basically the sort of call center dealing with financial fraud that you would think would really get wiped out by AI. But the good news is there is so much more financial fraud being driven by AI that they're keeping people very, very busy.
That's, you can see something like that emerging in the legal space is like you just get way more contracts because contracts are easier to create or you get more lawsuits. So a lawyer is spending less time per lawsuit, but there's a lot more of them to work on. And so you still have full employment. The good news.
Yeah. How are you using AI in the newsroom at Semaphore? Are there, I imagine you're not just writing AI articles, but is there internal tooling that's been built? Are you understanding?
Well, I feel like you guys are well set up for this because you're there's like, hey, here are the facts and then here's like takes and like separating those two things out. Yeah.
I don't care what you use here. I want the takes to be generally pretty organic and coming from the author. But how do you think about it?
Yeah, you know, we use it and it's interesting. I think like a lot of media, there's these two sort of huge trends. One is AI and automation and the other is creators and individual connection. And people do not want AI in the way of that. I mean, when they realize that you're just avatars, you're going to be in trouble. And um, and so we use it all over the place behind the scenes to try to like help amplify our journalists. Um, I vibe coded something that predicts mean tweets about stories that I'm personally very proud of. Though I cannot say that I've driven wide adoption with my team.
Um, that feels like that would just create like anxiety. If you want to get pre-dunked on, use this tool.
That is what the tool I called it. Pre-dunk.
Um, they spent a whole day. It's in Google Apps Script. I love it. I would say more usefully, one of my colleagues, because actually one of the challenges with an event like this is you've got three simultaneous stages and the reporter who's most qualified to write the story or even to know what's news is often the same one doing the interview and sitting on stage. Sure. Sure. And so we did build a great tool that, you know, just takes the transcript of every interview instantly and pops out what's new. So that a reporter who's maybe more of a generalist totally will know, oh yeah, this is news, this isn't, which is incredibly useful. And we, you know, obviously we check it, but that's a great starting point.
Yeah. Yeah, that makes a lot of sense because there's so many times when people fall back to a talking point, but you're looking for something that's actually novel or a new data point or a new prediction or something announcement that just might sneak in. Got this like how do you deal that you do an interview and you think there's one part that's interesting but you're on the air and something else goes viral, right?
Totally. Totally. Yeah. And we've, and we, I, that's a very interesting tool. We should probably think about integrating something like that because we, yeah. We've found that it's very, very hard to predict even with the best AI tools um what content, what clips will actually perform, what is news. And we see a lot of coverage downstream of our show where something that's said on our show will then turn into coverage on other news sites and uh we've never really figured out how to grapple with all of that. But that's that's... Yeah. And it's not just performance, right? Like it's also you might like think this is the new part, this is the interesting part, but if you're doing it live, it just sort of floats by. Yeah. So that's been, that's probably the thing that I mean just this week that I'm most kind of jazzed about.
What about overall market sentiment? JD Capaludo who made it. Sorry. Um, what about overall market sentiment? I don't think, uh, if you told me last year we would be, you know, over a month into a war with Iran and the S&P 500 would be at a record high, I would not have believed you.
Yeah. I mean, it's amazing. And the, you know, people who, CEOs, people who show up at events like this tend to be optimistic people. It's sort of a job quality and so there is like a pretty positive vibe here and the driven sort of parallels and is driven by the markets. One thing about Washington now though is there's also a lot of self-censorship and there's a real difference between what people say in public and what they say in private. And I think, you know, in our kind of Chatham House rule gatherings, you're hearing a lot more concern about a kind of, but just about the long-term direction of US power, the US economy, the US markets, people hedging away and no one's saying that stuff in public.
Yeah. Well, yeah. Biggest, biggest ever disconnect in my life between like group chat conversations and like timeline conversations among people who have something to lose is how I would put it. Um, well yeah, interesting times. Uh, hopefully it, uh, what's the plan to turn the synthesis of what you're hearing in the Chatham House context into reporting or content? Will you be writing op-eds that are informed by what you learned? How do you think about actually distributing that information?
I mean, the basic Chatham House rule is that you can steal the ideas and pass them off as your own, but you're not allowed to attribute them. So, that's the plan.
Okay. Well, we'll look forward to it. Uh, I'm sure everyone can follow along at some of... Thank you so much for coming on the show, uh, next year. I'd love to. Yeah, that'll be fantastic. Uh, have a great rest of your day. Have a great rest of the conference and congratulations.
You guys too. Thanks for having me.
We'll talk to you soon. Up next we have Jonathan Criss from Vital Life working on desalination with a fantastic new fundraising round. Jonathan, welcome to the show. How are you?
I'm doing fantastic. How are you guys doing?
Uh, we're great. I'm so excited to talk to you. Insanely fired up. We were talking with Peter Diamandis about desalination. And it's always been such a fascinating, uh, just not even a sci-fi technology, but just an underutilized technology that has incredible, uh, promise, but, uh, hasn't felt like it's hit the takeoff that it needed to. And, uh, so excited to hear your plan. But why don't you kick us off with an introduction on yourself and the company and how you're thinking about things?
Yeah, so, uh, I'm John, CEO and founder. I was at SpaceX for, uh, 13 years before this. Started off in Dragon. Uh, started off in Dragon. Uh, Elon was like, stop using Dragons or building Dragons, idiots. And I was like, oh man, I'll figure that out, boss. Started off with a small team to go figure out Dragon reuse. Yeah. Uh, the whole program became reuse vehicle. So just took over as product manager and then kind of got bored of spaceships, wanted to take on a new challenge. Uh, jumped over to the Starlink team to figure out rate manufacturing where we got really plugged in on how you design for really high volume manufacturing. Uh, and then, you know, my co-founder and I started really talking about how do we make a meaningful impact in the world? What's the next big challenge? And then got our heads wrapped around answering that question that every 8-year-old kid has. How could there possibly be water scarcity when there's oceans everywhere? Yeah. Um, and then just like you said at the top of the segment is like, man, this technology feels like it's really cool but it's just right on the cusp of becoming awesome. Uh, and we think if we apply the lessons that we learned on Starlink with high rate manufacturing driving down the cost and really delivering this technology to everyone, uh, we can really make that meaningful impact.
So, uh, walk us through the first product. I was always thinking that the next big desalination company would be a huge desalination plant, but you're going much smaller. So, walk me through the thesis there.
Yeah, I love that because that's pretty much where everyone in the industry has focused, right? We got to clean a ton of water. These systems are super freaking expensive for upfront capital costs. So, the only way to make your unit economics in that use case work is by going really large and cleaning a ton of water. Yeah. We just looked at it from the other end is like, man, if the upfront cost is negligible and you can keep your energy and maintenance costs low, you can probably do about the same and just scale it in terms of number of units, not a large centralized system. And then it's just kind of blown up the thought process entirely inside of that because now you're looking at infrastructure resilience and people being less reliant on centralized systems and then you can open up to people that are more on the move, people that are island-struck and really, man, the customer base has kind of exploded from there like, oh man, like if you could just deliver a low-cost product, people want to use it.
Yeah. So walk me through like a textbook customer. Where are they? Can you explain first? Can you just explain the product like M5? Yeah. Like how big are we talking? Like is this diesel generator size like...
Yeah. So we launched Access this week which is our first consumer product. Uh, we're a little bit more in the middle market going into customer bases that already exist. So Maritime Industry has these types of products. It's a reverse osmosis is at the core of our technology. Mhm. Uh, what we do is we're able to do that manufacturing process at a much lower cost and then a much higher volume. Um, so the product that you're seeing on your screen, Access, the facility that we got here in Torrance, we're able to produce more of these devices in a single month than currently exist. So we're kind of really taking that whole process.
Okay. Explain. But sorry, sorry. This is, uh, you put a hose into salt water and then it goes into the machine and out comes portable drinking water.
Exactly. So we always say we design for Terry.
I just for the audience I wanted to be clear. So water, push button, hydrate. Yeah. How many people off-grid actually have access to salt water or dirty water?
Well, this should work for springs and lakes and, yeah. Yeah. Yeah. So you can clean what we say is any naturally occurring water source. Salt water being the hardest one to clean and why desal has been kind of out of reach for most people until now. Um, but yeah, well water is super common in the United States. I think it's like 11% of homes live on well water in the US. Um, and then brackish water is super common. I mean in marshlands. I mean lots of south, all pretty much all Florida.
Yeah. How do you deal? One of the common things we hear about desalination is that, yeah, you get clean water out, but you also get all of the dirt and all of the salt and whatever else you don't want in your clean water. Uh, what do you do with that in your case? What happens normally?
Yeah. So, uh, the stigma is in your what you call brine or your concentrate. So, when you run a very large plant, you want your recovery as high as possible. So your concentrate is much higher, like two times the salinity in your salts. We actually run our system efficiently at a much lower recovery rate, like 15 to 20%. So as long as you're putting your brine or your concentrate back into a source water greater than five gallons or so, it almost immediately dissipates into that volume. So we get the wins inside of there in terms of, hey, you can use this product, it's not making that environmental impact because it's smaller form factor, lower flow rate and lower brine concentrate as well.
Mhm. Uh, what about battery? Is it battery powered? Do you plug it in? What's battery life like? Could you eventually create some type of solar array so that it's entirely self-sustaining?
100%. Yeah. Uh, so it runs on AC/DC. It's got an integrated battery. If you're cleaning ocean water, you're running for about an hour. If you're using fresh water, anywhere from about probably closer to 3 hours. Uh, so it all depends on the source water that you're cleaning. So ocean water has a ton of salts inside of it. So it's really difficult to remove those at higher pressure. Fresh water is much easier. Uh, you're essentially just killing bacteria and viruses. Um, so yeah, you can run it on AC/DC. We do integrate with solar as well. So, uh, you know, if you have a decent sized solar panel, you can run this thing as long as you have sunlight.
Amazing. Talk about what you've learned about the traditional large-scale desalination operations. There's actually an article in the Wall Street Journal today about San Diego producing surprisingly a ton of water from desalination. San Diego now has so much water that it's selling it. Once a drought poster child, the California city now generates enough water to rescue parched states like Arizona and brew beer from recycled sewage. Uh, are you optimistic? What about that last part? Recycled sewage. So, they take sewage water and they clean it so effectively that they can brew beer in San Diego. They might have to disclose that on the label, but I think, you know, we can get past the stigma at some point.
The wastewater once Bill Gates solved this problem a long time ago and it's like no one wants to drink poop or pee water, right? Uh, locally, uh, the ocean is arguably the most abundant resource on Earth. Yeah. Uh, and that's kind of the resource that we want to tap to bring this technology forward. But, uh, large plants are, you know, they serve a purpose. We want to be a partner with them, not a disruptor in the near term, right? Similar to Starlink, you had your, uh, what was it, $10 billion infrastructure bill to give internet to rural areas that serviced zero people. Uh, yet Starlink could do that over at a fraction of the cost. So we look for those people that are kind of high and dry right now and need access. Um, and that's kind of our initial customer base that we're going after.
Yeah. Uh, how much does the product cost? Where's the business? Give us an update on the round.
Yeah. Yeah. So $749 is our cost right now, but you can pre-order for $800 total refundable. Wow. Um, we're getting into production here over the next, actually our first PCBs show up next week which I'm very excited about. Um, the round was towards the end of last year. We have a great table, really awesome partners with GC and Interlogos. Yeah. Um, and that capital has gone a really long way to help us accelerate. Like the business has only been around for a little over a year. Uh, and we're about to step into production here over the next few weeks.
Yeah, it looks like you're in a production facility. How big is the warehouse? How many people do you have on staff?
Yeah. Yeah. Uh, we're a 37,000 foot facility here in Torrance. Uh, we're actually right next to the K2 guys. Oh, cool. Um, I keep seeing all my friends on your guys' show. Man, it's kind of a rite of passage at this point. Uh, we have 37 full-time employees right now, plus a ton of contractors that help out. Um, and we'll probably be closer to, man, 70ish when we're at rate. Um, with a bunch of associate and production staff just waiting to hire once we get into production this summer.
Yeah. Do you think that the business will remain almost entirely direct to consumer or do you think there will be applications for business-to-business, construction crews, military, government, all sorts of different things?
Yeah, I use this a lot. Uh, Gwen gave us a talk in 2013 and she was like, 'Yo guys, we got to get NRO certification because NASA's pretty much supporting this entire business.' So, when we started the business, we wanted to have multiple revenue streams that in the event of a macro event, we could be reliant on. So, the US military has a water logistics problem. Half of all casualties coming out of Iraq and Afghanistan were related to convoys moving water and fuel. So, they're excited to be able to open up where they can get water from. Uh, and then, you know, NGOs, humanitarian groups are almost solely reliant on bottled water which is another logistical nightmare. Uh, so these are both groups that we've engaged with and we have a lot of exciting conversations with but then also some partnerships that we're going to be announcing pretty soon. Uh, and then direct to consumers, uh, the hardest problem. Elon used to tell us all the time when we were starting Starlink like go after direct to consumer because they're going to give you the biggest feedback. You're going to get roasted on Reddit and you're going to know quick whether or not you made a mistake. Uh, so after being personally roasted on Reddit a number of times, uh, you learn really fast. So that's who we want to go after first. We want to solve the hardest problem first and then open up to those other larger customers afterwards.
Yeah, that makes sense. Awesome. Well, uh, very, very, very cool product and uh, I'm going to pre-order one just to play around with it. Bring it to the beach just to have some fun.
Come by the factory. I always say bring a bucket of your favorite ocean water. We'll clean it and drink it. It's a lot of fun.
That's amazing. How long does it take to clean a bucket of ocean water?
Uh, well, we do six gallons of ocean water an hour. Okay. Uh, so about an hour. Well, a little under an hour because most buckets are five gallons.
Five gallons. Cool. You're going to need two. John's like horse-sized, so he could easily go through like 10 gallons an hour. Okay. The chat wants to know what happens if you put a Diet Coke through it.
It'll separate all... We do this all the time. We did a reverse Jesus the other day. Uh, we removed all the alcohol and water from wine. That's amazing. Yeah. You'll pull out all the gross stuff and just have a pure glass of water. Some water. We did Monsters the other day where we removed all the water from five Monsters and then drank the concentrate which was just a super caffeinated syrup.
That's insane. Sounds like a fun time. That's crazy. Well, congrats on the progress and thank you. Great to meet you, John. The company and we'll talk.
Great stuff. Goodbye. Uh, up next we have Paul Scherer from Egan raising $15 million from Benchmark to build a mutual friend platform. Paul, how are you doing? What's going on?
Hey, so good to meet you guys.
Great to meet you, too. Great to meet you and uh, excited that you're not building another agent for the enterprise. You got something new for us. Yeah, break it down. Introduce yourself and the company.
Yeah, I mean, so great to meet you. Thanks for having me. Um, you know, uh, we're building, you know, we call it the world's mutual friend. Sort of, you know, instead of all of these things that are, you know, out there trying to, you know, optimize our own bubbles, we're sort of, you know, they're diverging more and more and, you know, the world that's super hyper-personalized for all of us. Yeah. Is also really isolating because it's different for all of us and we want to bring these bubbles a bit closer together again.
Yeah. So, walk us through the experience. Well, first maybe like where are you in this journey? Uh, you've raised some money, but do you have a team? Is the product live? How are you thinking about actually building the company?
Yeah, I mean it's super early. Um, we're really, really grateful for all the support and all the partners that we've, you know, been able to meet. Um, I'm from Germany. I literally grew up in this like tiny village, less than a thousand people. Um, I moved here like less than a year ago to San Francisco and I've been, I literally landed, I had a one-way flight here, uh, stayed in a hostel and a few months later I've been, you know, meeting some of the greats and they've been, you know, so incredibly helpful and we've built a small team. It's very early, we don't, you know, we haven't launched anything. We're working with, um, you know, early users to build something really special and something really meaningful.
So, uh, what can you share? Living the SF dream. Yeah, well, take us back first and uh, what were you doing before this? How did you get into startups? Walk me through that.
I've been building things, you know, forever. Um, I grew up, you know, in this really middle-class town and I never knew anything about entrepreneurship. So, I've always been building things. And then during the pandemic, I actually just went on Twitter and I started to spend a lot of time, like 12 hours a day on Twitter. I think I have like 25,000 tweets and replies from like a three-month period. Yeah. And um, and that's when I first, you know, I didn't know what a VC was until I was like 18. Yeah. Um, and yeah, it's just like during the pandemic, like about to turn 17, I left high school to do that. And so I've been doing startups for five years now. Um, you know, spent some time in Paris where I worked with the incredible people of a company called Augment and then, you know, I could finally get a visa and go to the US which I always kind of felt like was my real place to be.
Yeah. All right. All right. And then take us through the idea maze and how you landed on this like general kind of space.
You know, I think I've always been like really interested in sort of this intersection of arts and culture and, you know, technology and like, you know, growing up in this like, you know, place where I grew up and I really love German children's literature. And there's this book that my dad read me when I was 10 about this little girl called Momo who kind of connects everyone in her little town and helps sort of save the world from the time thieves. And uh, I've always sort of been inspired by this. And so it's been something I've been thinking about for a really long time. And I think now more than ever we really need this.
Uh, feels very early but you got Benchmark to come in and invest $15 million. They are the consumer social fund. They're willing to bet, you know, big and early, but typically I see them investing after there's like a spark or like some real sign of life. Do you feel like you're there yet and that you have something that early users love? Like at what point do you, and then I guess at what point do you think you'll launch?
Um, so I think with Benchmark, you know, and just more broadly, we already see, I think, moments of magic, and it's very, very early, but it's been just really incredible to see how people create these moments of connections, uh, you know, early users. And I think just partnering up with Benchmark has been, you know, an incredible experience. And I think I don't feel like I've ever pitched Benchmark. I think we just met and we sort of very quickly, um, I think the deal got done like three days, um, and we very quickly just realized that we had very similar ideas of what the future should look like and that we wanted to go on this journey together. Um, and everything else kind of became secondary to just like trying to make that happen together.
Uh, do you think there's a risk of becoming a dating app or is that the wrong way to think about it? That's funny. Um, is I just like historically the like, you know, meet people in your area apps, even if they're intended to create, you know, friendships, you know, you may get power users that have other intentions.
I mean totally. I think for us we care more about, you know, strengthening, you know, already existing relationships, right? We live in a time where we have all made way more relationships than, you know, ever before. Um, you 100 years ago you might have 100 friends, today you have probably like about 600 relationships and we really care about you making these relationships meaningful much more than like adding just random people on top of that. And so I think it's less of a thing for us.
Uh, have you been surprised that, you know, we're this far into the consumer AI boom and yet the only AI apps topping the app store charts are basically language models?
I think it's natural maybe. I don't think we're in the consumer AI boom yet because, you know, the great product people usually take, you know, a bit of time to sort of come out of the woodworks and start, you know, imagining what the new paradigms might look like. We've seen, you know, an incredible thing which is that the sort of single-player experiences are more powerful than ever before. Um, you know, multiple orders of magnitude. And I think now the interesting thing is how are the enduring experiences built? Like what does it, you know, how do you build a product that, you know, is so different that it couldn't have been done, you know, five years ago because it's just a new paradigm and sort of new primitives. Um, and I think it takes time to find and invent that.
How do you think about Dunbar's number? I remember Dave Morin had this app Path that you were supposed to add no more than 150 friends, I believe. And I'm wondering if you think that number is changing or you think that there's some sort of like optimal ground truth to that idea of Dunbar's number. Have you reflected on that at all?
We think a lot about it and I think there's a lot of interesting things in Dunbar's research. To me, the two things that stand out are that the headline number is growing, right? We have way more relationships than ever before. That doesn't mean that our brains are getting better at computing the social dynamics, but the real big problem is that we have way less close people, right? So, um, and I think that really is the most interesting thing to me is how do we get that back?
Yeah. Um, what do you think, do you think there's anything to be done on the social networking side to make filter bubbles less prevalent? There was some work done it felt like on YouTube where you would watch one video and immediately get served another video that was similar and so you'd wind up sort of down a rabbit hole and then YouTube seemed to have changed the algorithm to sort of show you the opposite side of the argument if it was a video in favor of something you'd see a video that took the other side pretty quickly. Uh, but I agree with you on the general trend that like there are these like, you know, niches and niches and niches and that's been good in some ways but it's also created some isolation. Have you just reflected on like if you had full control over all the social platforms what you might do differently?
It's an interesting question. I think what's missing is sort of opinion, right? We went from, you know, five newsletter outlets, you know, maybe 12 radio stations, a bunch of TV stations to like sort of infinite nuance, right? And everything, you know, every take that you could possibly have, you can find it on Twitter. Um, and what we want is not the average of the world, right? Like you don't actually care about the recommendation or the take of the average of the world, but you care about, you know, the take that your people care about. Yeah. And so there's sort of like we think there's something in the middle, right? An in-between space that's really interesting that brings you closer with actual people. Um, you know, just makes you the average of the world or, you know, leaves you alone in this like hyper-isolated bubble where you end up seeing things on TikTok that maybe are generated on the fly and like no one else will ever see that video and you can't go to your office anymore and be like, 'Guys, did you see this like insane thing?' and talk about it.
How do you think about just app growth? There's obviously viral loops that can happen with anything that's somewhat social, even if it's a little bit tighter. Uh, there's launch videos and paid marketing. Have you explored sort of like the current landscape of what it takes to actually make it in the app store, which feels like more competitive than ever?
I think maybe the answer is to not make it in the app store. Um, what does it look like to build something, you know, I don't know how the, I mean, we have obviously, you know, strong opinions on how the world might look like and where I'm not convinced that it's going to be another app. Yeah. I have this wonderful story that one of our investors, Ben Silbermann, told me when I first met him, uh, about sort of, uh, you know, his son describing his job, like Ben's job, and he was just like, 'Oh, you know,' he was asking, you know, 'all these squares on your phone. Um, and my dad makes one of them.' And I don't want to make another square. And I think we have enough squares competing for our attention. And um, maybe the next thing isn't another square, but something completely different. And I think that's what's exciting about this time. You can build something that just truly has never been there before. And um, that sort of escapes any previous incumbent.
Yeah. Yeah. It's funny because like even within Pinterest, the app that Ben Silbermann founded, uh, there like it has more squares within the square. It's like squares all the way down. The layout, a bunch of squares. Yeah. We're extremely curious to try what you're building when you're ready. I know the chat is, I think the mystery is good. Everyone's coming out. They're launching with, you know, the three-minute launch video explaining and you're just coming out with pure mystery. Where can people go to, do you have a wait list at least?
Uh, we're on team.com. You can sort of visit our office. Okay. And if you want to learn more in person. Yeah, we love in person. That's why we built our office as the website. No, no email, no email capture on the website. No, we're, I think you guys are post-email, post-app, post-software. This is amazing. I love it. Uh, yeah, come visit us on our office website or in person in our office. We're hiring exceptional people and we're excited to build something really special.
I like this typewriter that you can play on. This is really fun. Uh, beautiful website. I absolutely love it. The bowling balls and everything. Yeah, great website concept. Unfortunately, it will be copied relentlessly. Yes. But you did it first and that's what matters. Uh, anyway, great to meet you, Paul. Very excited to see what you guys ship and come back on when you launch. We'll talk to you soon. Have a good day.
Um, did you hear that Alphabet is poised for a $100 billion windfall on the SpaceX investment they made? Google owns around 5% of SpaceX and could get a hundred billion from SpaceX's IPO if they manage to pull it off at the two trillion valuation. Uh, not bad. Uh, that is a crazy stat. And, uh, they needed a windfall. Ah, Sanvi from Haystack says, 'What are the odds that this was a result of this?' and he's showing the debate between Eric Schmidt and Peter Thiel where Peter made the argument that Google is printing too much cash and needs to innovate, needs to invest in more things. It's funny, uh, Doresh actually asked a very similar question to Nvidia. He was like, 'Oh, you guys have all this extra cash. Are you going to train a new model?' Um, like do something internally, right? Because they've said they're going to do open source models. Yeah. Aren't they? Wasn't the answer just yes? Uh, I mean he didn't say like, 'Yeah, we're going after the labs.' It's like very different. They're doing open source, but it feels like a very similar question still. Yeah. Yeah. Uh, they're also doing self-driving cars at Nvidia and obviously Google's been very successful with that. Uh, it feels like the Google investments that burn money for a very long time although they obviously stayed very profitable. Uh, a lot of those penciled out very, very well and it does seem like the end result of this discussion was Google should invest more and they did and they invested in SpaceX and Waymo and a bunch of other projects and some of them didn't pan out but certainly many of them did. Um, what else is in the timeline? Uh, Mark is noping out. Uh, Zach says, 'Okay, actually in same paper published yesterday, a research group in Korea built a gene switch you can control wirelessly using EMFs.' EMFs, would look at that, fields. Uh, they expose mice to 60 Hz EMF, same frequency as your wall outlet, using a pair of large coils that generate a uniform magnetic field around the animal for cyclic three-day or four-day off pulses. This showed that you could activate OSK to do epigenetic reprogramming in the progeroid in aged mice, uh, extending lifespan and reversing aging markers across multiple tissues. Conditionally switch on mutant amyloid genes only in aged mouse brains letting them separate aging effects from amyloid to study AD biology in a way previous models couldn't. No drugs, no implants, just a magnetic field from outside the body. Uh, I'm close to taking a victory lap, John. I'm very paranoid about EMFs, but this could be positive. There could be a positive outcome responsibly.
We don't have... anyway. What? Oh, we have our next guests. We have James Morrissey and Kevin Hart. Welcome to the show, folks. How are you guys doing?
Gentlemen, what's going on?
What's going on, guys? How are you?
Welcome to the show. Thank you for taking the time.
