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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
You're to TBPN. Today is Friday, 05/01/2026. We are just barely live from the TBPN UltraDome, the temple of technology, the fortress finance, the capital capital. We had to rush back from Stripe Sessions' fantastic interview with the Collison brothers, many others yesterday. Go check it out if you haven't already.
Speaker 1:Fun stuff. We didn't go nearly deep enough on the whole Cocian singularity. There's a debate on the timeline about it. We can get into it later. We we we need to have some more economists on the show to break it down for us.
Speaker 1:But this is their big pitch. Firms get smaller and the future, the the the Coase theory of the firm anyway. If you studied economics, might be familiar. But it's jargon and you're gonna be hearing a lot more of it here. Whole lotta
Speaker 2:mumbo jumbo.
Speaker 1:I'm not even gonna try. I'm not even gonna try, majority. Well, here's some here's some less mumbo jumbo. Tech earnings, Quad Kill, Recap, four in one day. Last time this happened, I think it was 2020, Four big tech companies all same day.
Speaker 1:It is random. No one really knows why. It just sort of lines up like a solar eclipse.
Speaker 2:Can astrology you to predict the next one?
Speaker 1:Potentially. Potentially.
Speaker 2:You would have to imagine it's some something around the alignment of the the planets that caused
Speaker 3:More like
Speaker 1:the holidays. More like the holidays because books close then certain things line up. Also, like, Nvidia is never in the competition because they're always like two or three weeks later. But anyway, let's go through what actually happened. Google was the big winner.
Speaker 1:They absolutely crushed. The stock's up 10% in the last couple of days, really successful. And there's a few reasons. So the core business is still growing. Google Search, this is the question of is AI, are chatbots going to be eating into the core Google Search revenue, the core business that drives all the other investments?
Speaker 1:The answer is unequivocally no. Google Search and other revenue was No, 60 so far. Point Yeah, Up 19% year over year. I mean, two years ago, there was the whole like Google search is dead thesis that has not been borne out at least this year. Very, very strong results there.
Speaker 1:Then Google Cloud is like the major story. So much so that take him when he did his earnings recap, he didn't even talk about top lines at Google, Amazon, and Microsoft. He just says Google Cloud revenue 63% year over year. Amazon Web Services 28% year over year. Azure, 40% year over year and then Meta overall revenue, which we'll get into, 33% year over year.
Speaker 1:So he's not even looking at the rest of the business. All that matters for the three major public clouds are those cloud businesses, not even anything specific within the overall business. So long story short, higher CapEx at Google, totally justified in a world of cloud acceleration. Backlog growth is huge. Cloud backlog nearly doubled to more than $460,000,000,000 And importantly, this isn't like a five year, ten year contract type thing.
Speaker 1:Half of that, more than half of that backlog is expected to be recognized in the next twenty four months. So really good news there. Google Cloud hit $20,000,000,000 up 63%. Now it is smaller than Amazon, and that's why AWS is people are hunting for high 20 growth rates, maybe it begins with three. In Google, it's smaller so it can grow 63%, but that's still fantastic.
Speaker 1:And cloud operating income was $6,600,000,000 which is very strong margin. So everything is looking good. Search Search durability, demand for AI infrastructure, it's the full stack AI play right now. Microsoft showed solid execution, but they didn't dramatically change any particular narrative. I think a lot of this goes to like the just naturally slow deployment of enterprise AI.
Speaker 1:But this is the focus for Microsoft. They are the enterprise AI play. Yeah.
Speaker 2:One thing was notable is they weren't they weren't heavily teasing anything related to the next Gemini release.
Speaker 1:Yeah. I I tease that at at
Speaker 2:Earth's No. No. They have they have historically. Yeah? So anyways, maybe they maybe they wanna let the model speak for itself.
Speaker 1:Yeah. Probably announced Gemini four, I would imagine. Announced it
Speaker 2:Or a coding
Speaker 1:Google specific model. Yeah. Something there. I mean, there's certainly demand for it. They have the capacity.
Speaker 1:There's lots of opportunity. We'll probably be following that in three weeks when Google IO happens. So Microsoft. Investors wanted to see Azure growth, copilot adoption and a solid justification for all the CapEx. The stock's down 2%, nothing crazy, but Microsoft beat on headline numbers.
Speaker 1:Revenue was $82,900,000,000 up 18% year over year. And from an analyst perspective, it was a clean beat, but there's more nuance here. So in terms of AI adoption, Microsoft added about
Speaker 2:Look at this beautiful LED wall
Speaker 1:now. Million.
Speaker 4:Yeah. Let's give it up for the
Speaker 2:Still underrated. We ordered this bad boy maybe like six months ago. Six months ago. Took while. But
Speaker 1:it is fun. We we need to Worth
Speaker 2:the wait.
Speaker 1:More things to do with it. So on Copilot adoption, this is the big question. So for Microsoft three sixty five, like total seats, you know, you think about Microsoft Teams, Outlook, like the standard Microsoft enterprise seat. I think it's about $30 per user per month, competes with Google Apps enterprise. Right?
Speaker 1:But Microsoft has been doing this for much longer. They have four fifty million paid seats. So in terms of Copilot, they added 5,000,000, which is great. They're at 20,000,000 now. So that's a solid adoption, but it's still small compared to the four fifty paid seats.
Speaker 1:Ideally, like every seat would have a copilot alongside of it. I mean, that's the idea. Right? And so the question is how quickly can they get that 20,000,000 copilot seats up to 200,000,000, 400,000,000? Ideally everyone has one of these add on subscriptions and that's lifting the overall business.
Speaker 1:Market reaction was a bit choppy as the new OpenAI relationship gets digested. And so there's two sides to the Microsoft OpenAI deal right now. Of course, OpenAI is no longer limited to selling just through Azure. Azure no longer has exclusive access to OpenAI models. OpenAI is now available on AWS as well.
Speaker 1:And it cuts both ways. So on one hand, Microsoft, they used to be the exclusive provider. If you're a sales guy at Microsoft on Azure, you're probably really excited to call somebody up and say, hey. You wanna use GPT 5.5? We're the only place in town.
Speaker 1:Like like, you should come over here. You should migrate more of your infrastructure. You should be using Azure. But it was probably frustrating because a lot of people say, no. We're locked into AWS.
Speaker 1:We are stuck in that cloud, and we'd love to, but we'll just use the API directly or we'll do we'll figure out some other workaround, but we're not moving for this.
Speaker 2:Yeah. Or people could be like, yeah. We're we're we're open to trying it, but it'll take, you know, a a couple quarters realistically to get to get ramped up.
Speaker 1:Yeah. And so from an Azure perspective, losing exclusivity is a negative. But from a business perspective, more growth for OpenAI is good for Microsoft's equity stake in the company. And so these two tensions, like the the capital balance sheet side of the business versus the Azure sales and acceleration side of the business like these
Speaker 2:two are Not to mention CoPilot versus Codex.
Speaker 1:Sure. Yeah. And so these two these two sides of the business are sort of butting up against each other and Satya Nadella ultimately has to go and renegotiate the contract. And they did. And it seems like they're in a good place because a lot of people were sort of saying like, well, is this going to get messy?
Speaker 1:Is there going to be some lawsuit here? It seems like there was a very clean negotiation, renegotiation and they OpenAI got rid of the AGI clause that allows them to to stop sharing models, but they are sharing revenue and there's like like the the overall deal
Speaker 2:Yeah. Basically the the I think 2032 end date
Speaker 1:Yeah. Just IP share Yeah.
Speaker 2:Instead of this like arbitrary Yep. AGI.
Speaker 1:So over at Amazon, Amazon still, of course, the CapEx king. They topped the CapEx forecast. But as scary as that would be, AWS is reaccelerating, and so that's very good news. So the stock moved slightly upwards. Q1 twenty twenty six sales for Amazon overall were 181,500,000,000 quarter.
Speaker 1:For the quarter, they're like on track to make $1,000,000,000,000 in revenue soon. Up 17% year over year, beating expectations. AWS is expected to see 25% growth. That was the expectation, 25%. That's sort of where they've been.
Speaker 1:They came in at 28%. Percent, so they beat on AWS growth and that's really, really important, especially for their scale. This was very good news. The ads business is still cooking, churned out $17,200,000,000 in revenue. And the Chibs business just crossed $20,000,000,000 run rate, which is very, very good.
Speaker 1:When they have big deals, AWS is in this interesting position, less of this like Google pure play, full stack and more focused on working with both OpenAI and Anthropic at this point. And so that all justifies more investments in Tranium and AI infrastructure broadly and the market seems to like it. Huge CapEx numbers but reasonable response from the market and the stock. So Meta. Meta had a rough go.
Speaker 1:Huge drop nearly 10% down following earnings. It's sort of jumping up and down now. But the core business was extremely strong. So Q1 revenue was $56,300,000,000 up 33% year over year. So high growth for the overall business.
Speaker 1:Ad impressions rose 19%. Average price per ad rose 12%. They raised the CapEx outlook from they have this range. It's within $10,000,000,000 of 125,000,000,000 They added $10,000,000,000 to both. So instead of saying, hey, we'll be between $115,000,000,000 and $135 now they're saying we're going to be between 125,000,000,000 and $145,000,000,000 Now will they actually get more compute for that?
Speaker 1:Or is that just a reflection of rising prices for all the inputs that go into compute spending? That's a big debate because there's one bull case where, oh, they're optimistic they're going to buy more compute. But it's like, no, there's a possibility they're just spending more to get the same amount of compute as they thought. But the big problem for shareholders, the big answer is it's not as clean of
Speaker 2:you imagine take one second and imagine that Meta's a private company and their pitch is that we make AI agents for selling products. Mhmm. And they're doing $200,000,000,000 They're at a $200,000,000,000 run rate Mhmm. Growing 33 a year. Yeah.
Speaker 2:How's it priced? 20,000,000,000,000? Probably. Probably. With those operating margins?
Speaker 2:Yeah. I'm joking. It truly is one of the most incredible businesses Yeah. Of all time.
Speaker 1:But They don't have
Speaker 2:the are yeah. Yeah. They don't have the cloud People are he he's he's kind of acting like the most AGI pilled CEO, like like hyper scaler CEO, right? Yeah. He he was talking about like basically talking about like RSI on the earnings call.
Speaker 2:He's like it's not just about like coding you know coding. Yeah. Like he really seemingly believes. Yeah. And he doesn't wanna be in a position where someone else has actual super intelligence Yep.
Speaker 2:And he does not.
Speaker 1:Yeah. And so
Speaker 2:And and that's just like a little bit too fuzzy because when you look in the rest of the market right now, it's like productivity tools. Yeah. Right? And so the market just like can't really read into it. Yeah.
Speaker 2:And they're just kind of like not even giving him full credit for the business that he has.
Speaker 1:Yeah. And I forget if he's ever mentioned the idea of of selling tokens, selling AI infrastructure, getting in the cloud market. But it's way easier for an AWS
Speaker 2:He kind of loosely mentioned that last year when he was like starting to ramp stuff up, like basically saying like maybe we could do this Yeah. At some point.
Speaker 1:Yeah. This is way easier to justify the the CapEx at Amazon when you say, oh, well, like, you know, if, you know, regardless of how this market plays out, maybe Anthropic takes some of the compute, maybe OpenAI takes the compute, maybe there's a whole bunch of new AI labs that take compute. Maybe we'll use it for our services, our own models. If models commoditize, it's still valuable. If they don't, it's still valuable.
Speaker 1:There's a whole bunch of different ways to shift that CapEx around and justify it. Meta, it's got to show up in the AI figures. It's got to show up in the ad business, at least right now. And so there's there are questions about how the big CapEx spend feeds back into cash flow when the company doesn't have a platform with big enterprise AI contracts, massive RPO figures, there's not an easy place to just like stuff compute necessarily and at least get a market standard like return on investment. Of course, they could spin up reselling.
Speaker 1:They could become a neo cloud or something like that, but at their scale, it's whole new host of challenges if they go that direction. And I think that that's not the plan. I think you're dialing into it, that they are in fact recursive self improvement pilled at this point. And so the other the other sort of tremor in the system was the fact that daily active people, which is something that they were it's not users anymore. It's DAP, daily active people, declined sequentially since the first time that Meta began reporting the metrics.
Speaker 1:So less people were using Meta platforms this quarter than previously, but they had some good explanations for it. They said that there were Internet disruptions in Iran and WhatsApp restrictions in Russia, and so this was not representative of a real change in Internet user behavior. And I think we all recognize that that is reality in the sense that there's not some up and coming social network that's eating Meta Platform's family of apps launch. Right? Like the TikTok threat came and sort of went.
Speaker 1:The Snapchat threat came and sort of went. Sore. Sora came and went. Right? And so there there was a different post I saw that social media use is declining, especially under young people, but it was already so high.
Speaker 1:It's not really showing up will the
Speaker 2:truly be insane Mhmm. If we get this new alien technology. We get LLMs Mhmm. Which in digital form can convince you that they're a person.
Speaker 1:Yeah.
Speaker 2:And we would and and and we end up getting no new big social platforms, like
Speaker 1:That just strengthened the current ones.
Speaker 2:Well, yeah. Yeah. No. I mean, I think that's the base case right now, but it's still wild. Yeah.
Speaker 2:I think you would expect I think, again, if you rewound to like 2020 and you said, hey, we're gonna have this technology where you can effectively have a digital twin of yourself. You would think that somebody would figure out some new
Speaker 1:Yeah.
Speaker 2:Case mechanism. I
Speaker 1:I I continue to think it just strengthens the incumbents. Roblox, Instagram, WhatsApp, Facebook, like these platforms will just get more content on them that will probably be LLM generated, LLM enhanced. Even if it's not LLM written or developed, it's it's, you know, a creator taking less time doing other boring things and spending more time on their core output. So we'll keep tracking it. So overall, what what did we learn this earnings season?
Speaker 1:One possible takeaway is that there's a little bit of a fracturing in the overall AI narrative. So the AI narrative over the last twelve months has basically been like, say the biggest number, biggest CapEx number, biggest deals, just grow, grow, grow. Now every hyperscaler reports a big CapEx number. But each company does have a different story. So Google is the full stack platform.
Speaker 1:Microsoft is focused on enterprise adoption and distribution. Amazon is most aggressive on infrastructure and partnerships with OpenAI and Anthropic. They have the cleanest less it's a less competitive relationship with Anthropic and OpenAI because they don't have the DeepMind equivalent necessarily. Meta is all about ad optimization. And Meta is also this interesting like high risk option on frontier AI.
Speaker 1:Like it's possible that if TBD Labs, MSL, if that pays off, you wind up getting an OpenAI sized or Anthropic sized business out of it in the oligopoly world where they have a breakthrough, they get to something that's five five or four seven level and then they're competing in an equal level and they're playing in that oligopoly. And so you like the meta traders are sort of or the investors are sort of weighing both of those sides. You have a very solid ads business and then you have this call option on potential frontier AI, which is still early but showing some really solid signs. So the market likes short term revenue evidence right now and there's still many strategies that will play out over the rest of the year. But this quarter was focused on can you justify your CapEx this quarter.
Speaker 1:And so we'll keep following it. Let's go over the timeline and see what people were saying. The headline numbers, of course, were huge cloud growth. AWS, 28%. GCP, 63%.
Speaker 1:Azure at 40%. Absolutely massive numbers. Remember, people were hoping for GCP to be at 40%, and it went up 63%. Absolutely massive. AWS, people are hoping for 30.
Speaker 1:They got 28. Not too bad. Take Him, we mentioned. You can go subscribe to his Substack at takehim.substack.com. He has a write up on the state of AI after Google, Meta, Amazon and Microsoft earnings.
Speaker 2:Take him's been right a lot lately.
Speaker 1:Been doing well. And and there's some people reflecting on, you know, crazy run ups, crazy numbers, crazy hype. Is this the .com bubble? Always fun to go back and comp to previous bubbles. The .com one is is still fresh for a lot of people because some people in tech were alive during it.
Speaker 1:Many people in tech were alive during it. But this poster, Wren, is comparing the price to earnings multiples today versus the .com boom. So today's MAG four PE ratio is the company's reported earnings. Meta is at 16x price to earnings. Google is at 17x.
Speaker 1:Amazon is at 24 and Microsoft is at 25 price to earnings ratio. Compare that to during the .com. Microsoft is at 73x. Cisco was at 200x plus. Yahoo was trading at 800x earnings.
Speaker 1:The Nasdaq as a whole traded at 200x earnings during the peak of the .com bubble. Today's bubble is trading at 16 to big 25x x earnings on companies generating hundreds of billions of dollars of real cash flow. Now they're drawing down on that cash flow. But even in some bizarre world where, you know, AI is a bubble and it's fake and we all go back to pencil and paper, we'll probably go back to digital advertising and spreadsheets in the cloud and, you know, SaaS and all of these companies will still benefit and be in a fantastic position.
Speaker 2:Yeah. The the only thing that that's, know, or one thing that's imperfect with these comparisons is when you look at like the peak, you can say like, okay, MetaGoogle, Amazon Yeah. And and Microsoft have relatively reasonable PE ratios. Yeah. But if you look at the rest of you look at all the companies that have been started in the last five years, especially in the private markets that have been marked up from, you know, 20 to a 100 to 500 to a billion and beyond, many of them have absolutely no earnings.
Speaker 1:Yeah.
Speaker 2:And and are and are and so you have to look at like maybe something more like a Yahoo as like a decent comp, right, where Yahoo was trading at peak at 800 x.
Speaker 1:Yeah.
Speaker 2:And so And there is some there is
Speaker 1:some pushback in the in the replies here. Reasonous forces. AMD's at one thirty. Tesla's at three fifty. Palantir's at two twenty.
Speaker 1:And Intel is at 900 times earnings.
Speaker 2:I know. So it's like very, very convenient to just take the four of the greatest companies ever in the history of the world and say like, there's no bubble. Like, they're they're reasonably priced.
Speaker 1:Yeah. I think it is it is it is useful to go back to the fact that like there there's there's a lot of hype in tech, but what's driving the vast majority of the market cap right now is still fairly low PE companies. Like, Intel is so much smaller on a market cap basis than Microsoft, Amazon, Google, that even if you're overpaying on earnings for that, you like, the the overall market is anchored to a pretty decent earnings engine still. And that's like the bull case here. What else is going on?
Speaker 2:I'm George George Hotts is back with a white pill.
Speaker 1:What'd he say?
Speaker 2:May 1, he says AI will create jobs. Okay. It's nice to see Jensen talk about this and it's super obvious when you think about it. AI and immigration are fundamentally the same. There's new people showing up and hopefully everyone understands how and why immigration creates jobs.
Speaker 2:Wants are effectively unlimited. It's classic Jevan's paradox that if we make something more efficient, we end up using more of it. Or a cool aphorism I learned at Facebook, if you make the site 10% faster, people spend 5% more total
Speaker 1:time He on at Facebook for he was like an
Speaker 2:part of the machine. Yeah. Now, just like you get the Wawa crying people about how immigration lowers wages for native born Americans and we gotta keep the hardworking immigrants out because you have some right to be lazy or something, you'll get this about AI. AI will outcompete some humans at some jobs. But protectionism is for losers.
Speaker 2:The important thing is that the overall pie grows and inequality stays somewhat in check not by redistribution, but by design. There will be more to do than ever before.
Speaker 1:More to do than ever before.
Speaker 2:Can we pull up this video of Jensen?
Speaker 1:Yeah. Let's do it.
Speaker 2:In the production chat for you.
Speaker 1:Yo, you have it?
Speaker 2:Yeah. We can play it.
Speaker 1:Great. I'm excited for Eric Souffert's deep dive here. We'll get into that later. The souffinator? The souffinator.
Speaker 1:And reminder, have the Isaac inator coming on in just seven minutes. Mike Isaac has been covering the Elon Musk versus trial.
Speaker 2:Is it like a four day work week with trials? It is. Are they living in the future?
Speaker 1:It is. Wait, wait, wait. So can we pull up this screenshot? Because did you read Mike Isaac's full thread on his experience covering the trial? Did you read the whole thing?
Speaker 1:Because he's been live tweeting it and it's very funny because he will post, so we got to zoom in here. This is a
Speaker 2:Did you turn this into I
Speaker 1:turned it into an infographic. So this is a minute by minute chronological log of off topicpersonalminor inconvenience moments because Mike Isaac will talk about, oh, Elon Musk just said this on the stage. Oh, the lawyer fired back with this. The jury said this. The judge said that, right?
Speaker 1:But then in between that he has been logging very very minor inconveniences that he's that he's experienced. He talks about his his lunch, the roasted tomato and corn pizza. He says he forgot a pillow for his bird to Wait. Sit He said he Corn pizza? I don't know.
Speaker 1:He said he bought
Speaker 5:That's the very
Speaker 2:Oakland thing.
Speaker 1:At at at sixteen o 07:45. This is transcribed from X. I think the Times are UTC or something. He brought a water bottle but forgot to fill it in the rush for a seat. Now he's increasingly thirsty during an intense moment of testimony.
Speaker 1:Someone's laptop suddenly blasted a loud YouTube video in the gallery. This is a garden hose nozzle, it said. Courtroom mishap. So he's going through it all. It's very fun to to track his.
Speaker 1:And we'll and we'll dig into his experience both in the court and actually with what's going on with the case. But let's play this Jensen clip. This sounds fun. Jensen is insisting that jobs will be created in the future. Let's see it.
Speaker 1:What does he have to say?
Speaker 6:There's the things that the things that are said are very counterproductive and in fact hurtful. I on the one hand, maybe
Speaker 2:What are you
Speaker 6:talking maybe a scientist thinks that by warning people that AI is going to completely permeate and proliferate across radiology and therefore radiologists are going to get wiped out. On the one hand, that might be considered warning and therefore helpful, but in fact, the counter would have been hurtful. If we convinced everybody not to be radiologists and we now need radiologists, that actually is hurtful to society. It is hurtful that we convince all the young college graduates to not be software engineers, and it turns out United States need more software engineers than ever. That's hurtful.
Speaker 6:And so we have to be mindful of how we communicate the importance of this technology and what it's able to do to advocate for policy and advocate for guardrails on the one hand, on the other hand, scaring people with things like saying nonsensical things which are not gonna happen, that this is an existential threat to humanity. There's 20% chance that is existential. That's ridiculous. That it's gonna wipe out 50% of of of new college grad jobs. That it's gonna completely destroy democracy.
Speaker 6:I mean, these kind of comments are not helpful. They're not based.
Speaker 7:They're they're made by He's
Speaker 1:subtweeting in real life. He's not vague posting. He's subtweeting. I I do think the 50% numbers are so funny because it's like fifty fifty is like the most neutral you can be about some prediction. It feels like mean, I get that it's not.
Speaker 1:In in in that case, it's, 50% of jobs. But whenever you issue, a fifty fifty proclamation, it sort of tells you nothing. Like, we were looking at, like, the prediction markets on the trial, and we were like, oh, it's fifty fifty. Okay. So that actually doesn't give me any information about what's going to happen in the future.
Speaker 1:And it's very easy to make a prediction that's like, oh, predict this will happen fifty fifty. And then if it doesn't happen, can be like, well, 50% chance it wasn't gonna happen. Like, I had it really high that it wasn't gonna happen. And then you can also say, you know, I predicted it.
Speaker 2:Yeah. It's so is truly universal when we talk to these companies that are building AI products or selling AI products. It seems like the ambition level in every single industry is just going up. Even even Gabe from Rogo was saying, yeah, there's an opportunity to cut costs or there's an opportunity to get aggressive and like take market share. Yep.
Speaker 2:And and he said like a lot of firms Work. Are saying like, let's just do more work. Let's grow let's grow our revenue. Let's take on more clients. Yep.
Speaker 2:Right? And so it is, it's harder and harder to to doom about the job market.
Speaker 1:Yeah. Do you need to doom about the task market? If you're
Speaker 2:It's over for tasks.
Speaker 1:Tasks are getting automated. No. It's serious. Like there are tasks that like the reading of the x-ray or whatever it was, the the radiologist scan, what what do they actually read? Is that an x-ray that they're looking for tumors in?
Speaker 1:You know what I'm talking about. Right? The famous Hinton
Speaker 2:Yeah.
Speaker 4:I I
Speaker 5:don't know if it's, like, an x-ray.
Speaker 1:It's not. Right? It's a CAT scan?
Speaker 5:Get some scan where
Speaker 1:you
Speaker 5:look
Speaker 1:at it. Yeah. They do a scan. And of course, image generation and image models are very good at detecting cancers. But that is just one of several tasks, many tasks that a radiologist does throughout the day.
Speaker 1:And so radiologists are currently making more money than ever and they are in more demand than ever. And I was telling you before the show about truck drivers. They don't just drive the truck. There was a survey that said 70% of them carry weapons because they are effectively they are security guards for the truck. As well as probably a bunch of other things that you don't think about, light repairs on the truck, you know, stopping for different things, rearranging things in the back, making sure that the load is like balanced It's and driving just If
Speaker 2:with kids in the car you drive by a big truck on a road trip, can go like this.
Speaker 1:Yes. And then That's another thing that they that they self
Speaker 2:computer drive could trucks. Never look out the windows It needs see some kids in the car and
Speaker 1:Yeah.
Speaker 2:And honk.
Speaker 1:But well, yeah. I mean, we'll we'll see. Anyway, we have Mike Isaac in the waiting room. Let's bring him in to the TBPN Ultradome. He's at the New York Times.
Speaker 1:Mike, how you doing?
Speaker 3:Yo. What's up?
Speaker 1:Good to see you.
Speaker 2:Great to see you. So Wait. So what's
Speaker 1:yeah. Up So so Four day work week.
Speaker 2:Are they living in the future?
Speaker 1:Yeah. Is this universal basic vacation days?
Speaker 3:It's court is incredible in that I got to sleep in till, 9AM today, which is which is great. But I made up for it because, like, literally every day this week, I've gotten up at 05:00 in the morning to get my cold ass down to the Oakland Courthouse and stand outside for two hours. So I don't know, but it's fun.
Speaker 2:How does it how does it work? Who gets priority? Is it first come first serve? Like if some random person if some random person shows up before you
Speaker 1:They can just get it and then you're just out?
Speaker 2:Or do you get to like show some sort of like press like how does it work?
Speaker 3:Yeah. I wish I was cool enough to like cut. Well, here's the thing.
Speaker 2:You should get an artist pass.
Speaker 1:VIP pass. Yeah. Right.
Speaker 2:No. Not VIP. Artist pass is
Speaker 4:a level
Speaker 1:of Okay. Artist pass.
Speaker 3:So there are 20 reserved seats in the front row for press, but the issue is only one person per outlet gets it, and we are doing, like, live blogging for, like, the big moments, like opening statements and for Elon. Yeah. And so myself and my colleague, Cade, came on the first the whole first week, and so so we've gotten trade off. He's gotten the, like, press skip the line thing, and I've been with the other folks in the 30 unreserved seats in the back.
Speaker 2:That are watching YouTube videos.
Speaker 3:Yeah. Yeah. Oh my god. Or literally
Speaker 2:Or strike sessions.
Speaker 3:Literally, one dude fell asleep. I was actually impressed.
Speaker 1:Fell asleep.
Speaker 2:Yeah. It seemed pretty entertaining. You didn't seem like you were falling asleep. I was keeping up on the through the live blog.
Speaker 3:You reading my nightmarish Twitter too? I it's been fun, honestly. Have you guys ever done like court case things or have you ever been sued or been in court?
Speaker 2:I've never been in court.
Speaker 1:I I went to a mock court in high school where Yeah. Everyone picks a role. I think I was Yeah.
Speaker 2:We LARPed in court.
Speaker 1:Literally LARPing. In high school. But other than that, I never
Speaker 2:I the whole This whole time, it seems it seems insane. Like, with with the with the recent NASA, the moon mission, I was like, this should be a livestream plus a pay per view for the key moments Yeah. For this trial. It's like we have huge budget deficits and we have these incredible media products. Why are we not doing pay per views?
Speaker 2:Right? But That that's the the
Speaker 3:funny thing oh, I was just gonna say that's the funny thing about like federal courthouse stuff. Like, there's a lot of different rules around filming and electronics. I covered some cases in DC, and I can't even bring a laptop or a phone in those courthouses. So, like, this is actually a very permissive judge just because she believes in, like, press access and stuff, and we've had there's way more access than you would normally get in federal court cases.
Speaker 1:Okay. So you you've been to these court cases before, but if I follow your Twitter, it feels like you're making a bunch of rookie mistakes. You you you you only had egg bites at 05:30AM. Your bite energy is wearing off. You forgot your butt pillow.
Speaker 1:You forgot to fill your water bottle. Like, is this amateur hour, or are you a professional? What's going on?
Speaker 3:I'd say I think that you you guys might know me well enough that that is kind of how I operate most of my life, like kind of chaotic, but it is on the important stuff. That's right. Yeah. Yeah. Yeah.
Speaker 3:I mean, look, I can file. I may be like bleeding and hungry like limping across the finish line but we're getting I'm tweeting for you.
Speaker 2:What what is your what what is your what are some like high profile cases that that stand out that you've covered in the past?
Speaker 3:So I got to do let's see. My first one was insanely boring but important. The Apple versus Samsung thing back in the day and like them suing for Samsung copying like literally everything they do. I did Dallas. Actually, Zuckerberg's, like, I think maybe one of his first testimonies on the stand when Zenimax was suing Mehta for the Oculus acquisition.
Speaker 3:Remember that?
Speaker 1:Yeah. Palmer like And I
Speaker 3:was in Dallas. That was super fun. That I almost got kicked out of the courtroom for tweeting.
Speaker 1:Woah.
Speaker 3:And then I did the DC FTC Mehta one, and I almost got kicked out of the courtroom again. Actually, I did get kicked out of the courtroom for wearing the meta Ray Bans. These are not it. Interesting. But I wore the meta Ray and then they started putting I was I was fucking super stupid for doing it.
Speaker 3:But then they started putting signs up saying do not wear these glasses in car.
Speaker 2:But you weren't you you were just using them as glasses or you're being sneaky and you're recording?
Speaker 3:No. I was like, look, I can't record. I won't record. I was trying to play by the rules. And like, they were they are my prescription glasses.
Speaker 3:Yeah. But the bailiff the bailiff was like
Speaker 2:It's too much it's too high risk for them. Because you could just because you could have, like, turned off the the light or whatever. Yeah. Something like that.
Speaker 1:Talk about the the the fans. Are there really Elon Musk fans in the courtroom? Like, what what motivates someone to go and watch that live? Is this their UFC front row ticket? Like, why are they there?
Speaker 3:So you guys would have fun. Like, it actually is a lot of court cases are boring Yeah. To people who don't care about this stuff. Right? Like, you and I may be super into like, the FTC trial was super fun for me because it's like, oh my god.
Speaker 3:Mark Zuckerberg emailing Sheryl Sandberg and talking about Path. Like, this is incredible. Yeah. And, like, the average person has no idea what we're talking about. Yeah.
Speaker 3:Yeah. Yeah. But this is, a circus. There are people who genuinely love Elon or are genuinely worried about the end of the world happening. And I think it's a really good thing that there's public access to these courts.
Speaker 3:Like, think, like, the average person can come in and show up, and that's what I think after the the buzz of Twitter and, people seeing that this is a event, we got a much longer lines and like folks who are local, like just like I know a PM in tech from Meta that came. I know like a guy from Box made it in. Just if you get a seat if you get there early enough, then you can get a seat and you can just hang out. It's like and I think it's really great. I think it's great that people are, yeah, are there for it,
Speaker 8:you know. It
Speaker 3:shouldn't just be me.
Speaker 2:Yeah. What about the what about the jury? Does the jury seem excited and and honored to have the opportunity to be to be a part of of a case like this or are they are they nodding off? It'd be so funny to be like so out of just like off the Internet.
Speaker 1:You can't be super biased. You're probably not a p s Sam
Speaker 2:this guy Sam and Greg and this guy who makes cars and I don't even know what they're talking about. Bunch of a whole bunch of mumbo jumbo. Like there's gotta be one person on the jury that was just so not tapped in that that they're just confused. I
Speaker 3:think jury selection was super interesting for that. I can't say it's actually interesting. I can't say too much about the jury right now because, like, there's all these rules about
Speaker 1:Oh, sure.
Speaker 3:Like some random person could go up to them if you identify them or try to
Speaker 2:Something alter
Speaker 3:like that. Yeah. Totally. But I will say like during jury selection on Monday, it is an incredible slice of life, and you get like how familiar or unfamiliar people are with the tech industry despite being here, you know? Like some folks are like, have no idea you're talking about.
Speaker 3:I don't know what AI is. I don't know what AGI stands for. So it really it really played and voir dire and jury selection is so important for cases like this. Just it makes the dynamic of the facts don't necessarily always matter, but the vibe can really matter, which I think is a benefit for Elon honestly.
Speaker 2:Yeah. Were they were they trying to weed out they're trying to weed out people that are a little bit too excited about the case. Right? You want the people that are like in order to have a but but then talk I I didn't understand why why is the jury just like giving like an advisory decision? What is the history of like Why do you why do you have a jury when the judge is ultimately gonna make the final call?
Speaker 2:It it feels like just kind of putting on like a show because like theoretically the judge could just sit through a bunch of depositions and make a call. Yeah.
Speaker 3:Sure. No. I I think so I do think they want more often than not want a jury of these CEOs and companies peers to be the deciding factor in what they feel like is good for a civil claim. Like that, I think is fairly standard. But to your point, the judge can throw out their verdict, which is like is and judges, I don't think, tend to want to do that because, like, they want to have reliance on this is the public.
Speaker 3:The public should have a say in what goes or whatever. But the judge can do that. I will say also she is responsible for if they're if Elon or sorry. If OpenAI is found liable, judge decides on remedies, damages, and things like that. So she still has an active role in that regard and in steering the case.
Speaker 3:But I really do think that full courts often prefer or often appreciate a peer a jury of your peers making some of these decisions. So I don't think it's gonna be like completely disregarded is what I would say.
Speaker 2:Yeah. How has judge Rogers done so far in your view? Just reading reading the live blog, she seemingly has like zingers and like pretty pretty like good like one liners the time. I'm just like kind of imagining what it's like in there because obviously I'm just reading text but she's had like seemingly like some pretty good comedic timing.
Speaker 3:Yeah. Oh my god. She's so funny. She's like real, like as you might imagine, there's like a number of different types of judges and how they handle their court or whatever, and she just takes no BS from anyone, including the lawyers. And like when they try to, like, tap dance or break the rules or whatever, she's like, no.
Speaker 3:Shut up. Or, like, get back on track. Or no. No. No.
Speaker 3:Actually, the best part or the most insane part so one woman in the overflow room who is just as not just, it was a civilian going to attend and watch it, started recording, which is, again, against the rules, if not the law in a federal courthouse. So the judge brings her in, and in front of a room of like a 100 people, just like dresses her down, yells at her saying, did you not see any of these signs? What are you doing? I will kick you out. I will it was like, I I would have, like, peed my pants and
Speaker 1:started
Speaker 3:crying if she had done that to me. It was deeply, deeply intense.
Speaker 1:It's it's teacher, you know, berating a student. Yeah. Glasses in session. Glasses in session here.
Speaker 3:It was brutal.
Speaker 1:How how how do you how have you been processing Elon's positioning? It feels like the two the two stories that I've heard him sort of telling are, one, about his commitment to technology, humanity Yeah. Saving the world through, you know, Tesla and the electrification of the internal combustion engine and SpaceX making, you know, humanity multiplanetary. And then and that's like a very high level, you know, high concept pitch. And then he also sort of brings it down and starts beating this drum on, like, you can't steal a charity.
Speaker 1:You can't steal a charity. Is that the correct framing that he's trying to go, like, high and low there? How much have he's been beating each of these drums, and how useful is that?
Speaker 3:So I I totally agree that's the framing, and I think this really goes to the point of a lot of these trials are pageantry is the wrong word, but let's say theater in that you are this is a jury trial, and it's a different thing than just convincing a judge who I would say is much more attuned to the facts and merit of the case
Speaker 1:Yep.
Speaker 3:And, like, hammering in on the evidence and, like, something that may be boring to you or me or whatever or the jury is gonna be more important to a judge. Elon, I think from day one has leaned into into the persona of Elon, and just from him being on the stand and saying, I care about humanity. I mean, he he says he does whatever he does or doesn't, but like just leaning into this, I'm a world changing entrepreneur, and this stuff is existential, and I'm the one who has cared about it. And, like, that may work on a jury. You know?
Speaker 3:Like, there are people who still love him, and, you know, OpenAI is really hammering the facts of what they feel are are their side of the case and saying Elon has known about Elon has never been in the dark. He quit in a huff. He he's made it very clear he hasn't been there. He's trying to sue now, or he's trying to file this claim now because he's catching up, because he's behind as an x AI competitor. But like, again, this is all stuff that maybe it doesn't play.
Speaker 3:Like, this is why jury trials are so risky for companies a lot of the time, you know. It's really it's fun for me. It's probably not fun for for everyone in there, but it's fun to see it play out, if that makes How
Speaker 2:did the distillation comments come up?
Speaker 3:That was like was the news of the day yesterday. You guys obviously were a Which
Speaker 2:you broke you it. Right?
Speaker 3:I think I did. Yeah. I think it was one of those things where I was like, holy shit. This is news. And I think like folks like started figuring it out, but I was like, gotta put it on Twitter.
Speaker 3:And so point so Bill Sabbat is lead counsel for OpenAI. He was sort of talking about the the point was made in the context of they want to hammer home. Elon is creating a competitive product, and also he keeps stressing that this is doom world ending technology, but at the same time, he's he's he's ripping off the toss and using the technology to improve his own technology in an explicitly for profit company. Yeah. And so the the point is like hammering him as a hypocrite.
Speaker 3:And I think look. Like, I think Elon has history in his businesses. It would not be controversial to say to to, like, say one thing and do the other. And I think he sees it as, like, rules of engagement. That's the game in the, you know, no holds capitalism land.
Speaker 3:But, like, that is how it came up and that they didn't go super deep into it, but they wanted to make the point. He's using OpenAI's tech. He's breaking the toss, and he's partly distilling it. And I wanna say also that Elon went out of his way to say everyone kinda does this. Mhmm.
Speaker 3:It's like an open secret in the industry, which I think is, like, also kinda true, but that doesn't make it there's like it's it's fraught, I guess, is what I would say.
Speaker 1:Yeah. Yeah. It's a there's obviously a continuum there, which is why he tried to hammer that it was, like, partly. I imagine most car companies have taken a rival car for a spin. Have they taken the car apart?
Speaker 1:You know, there's a line there and there are laws, but that's a separate issue, of course.
Speaker 2:Has anything come up with a jury around prediction markets? Because I was thinking we've now seen insider trading across every possible prediction market, right?
Speaker 3:Know, I'm sure
Speaker 1:from like That's very interesting.
Speaker 2:You know, even even the Maduro thing was was was
Speaker 1:Insider trading. Interesting
Speaker 2:because a lot of people were like, oh, he's just betting on himself. But then I saw that I was like, hey, that's sending a signal to the entire world that an attack could be happening which puts your entire team at risk. Right? Like very very clearly like US military personnel should not be able to trade against our own military's actions ever. Right?
Speaker 2:And that that they need to come down really hard on that.
Speaker 1:Are you just trading this? Are you just trading on this crazy? Are you are you gonna retire off
Speaker 2:of this? The reason the reason that the jury thing is is is bad is it creates a potentially an incentive for the jury to basically work together and say like, hey, like we all have to be here for like a month. Like we could at least make some money on it and then you only need to get like four or five of
Speaker 1:these The people that chat is saying monetize jury duty.
Speaker 3:Oh my god.
Speaker 2:No. But but but like it seems like very important that this does not happen. Right? Because Totally. Because there's very like they they tried to select a jury that just doesn't care about the AI race.
Speaker 2:They don't care about this or that. And if they are self interested in some capacity, they could be like, well, my my decision is not is not even really legally binding. It's just advisory. Like I may as well, you know, I don't know. Right?
Speaker 3:No. I I think that's a great point and like something that I imagine like court systems aren't even prepared for fully yet because like
Speaker 2:Well, there hasn't been a big trial like there's been I'm sure some like epic Apple stuff that was slightly big but but nothing where nothing nothing anything at this scale with this much even just this much volume already from people that are generally interested in in Mhmm. In the story.
Speaker 3:Yeah. The outcome and like I think the other thing you should know is like they're not sequestered. Like they show up kind of like before
Speaker 1:Like anyone else.
Speaker 3:Right before they yeah. Like they literally like we see them walking in and that the marshals there's, like, a ton of, like, US marshals there. They're like, is anyone a juror in this line? The juror gets to go in. So let and at the end of every day, the judge is, like goes back over the rules saying, do not discuss this case with anyone.
Speaker 3:Do not watch it on TV. Do not look at it on your phone, which is like a verbal command. Yeah.
Speaker 2:Don't go on your
Speaker 3:phone. Don't. Exactly.
Speaker 2:Hey. Don't use the most addictive thing that has ever been created in human history. Don't use the thing that you use for six hours a day.
Speaker 1:That you probably turn your lights on and adjust your thermostat.
Speaker 3:I mean, it's that's a it's something I had not thought of, Jordy, but it's a really good like, when does that come up at some point, you know? Like, that's very worried.
Speaker 9:Not not just seriously,
Speaker 3:but just ever.
Speaker 2:Yeah. It seem it seems like something that that that the court should be paying attention to heading into a decision from from the jury.
Speaker 1:Yeah.
Speaker 2:How much is the history between Opening Eyes counsel, Bill, who represented he represented Twitter when Elon was trying to get out of the the the the Twitter buyout? And ultimately, it feels like the X slash Twitter acquisition has worked out pretty well for Elon. He's made a number a number of plays. So hard to hard to imagine him like, you know, deeply regretting buying it even though at the time he was happy to get out until Bill said, no. We're we're doing this.
Speaker 3:I you know what's funny? He is I I can't underscore enough how different the tenor chain I mean, look. It's like it's opposing counsel, so it's always gonna be different. But Elon went from, like, I'm a entrepreneur sort of like Rosalie explaining to you what I think the future should look like and, like, very concerned for the future of the human race to, like, openly antagonistic to Sabbat's questioning. And, like and the the thing that I'm very curious how this plays with the jury is, like, Elon was very he's like, I'm a literal guy.
Speaker 3:Like, the questions they're asking me are, like, too complicated or, like, they're not yes or no questions, which is, like, fair, like, as a grievance, but also the thing he either doesn't understand or doesn't care about understanding is that that's just lawyers. Like that's the whole point of a cross examination is to ask these questions as reductively as possible to get as type of answer they're looking for, and his job or his, you know, pretrial sort of discussions with his own lawyers is to know how to navigate those essentially while also telling the truth. So I don't know. They're they just don't like each other, or at least Elon doesn't like Sabbat, and you can very it's very clear that he's just, like, mad at that. And whenever Elon gets sassy, I would hear, like, clearly people who are fans of of Musk, like, laughing behind me or being like, yeah.
Speaker 3:You got him. Like, blah. It's just it's very it's very funny. It's like kind of a it's different than the usual vibe is what I'd say.
Speaker 1:That's very interesting.
Speaker 2:Outlook, what's going on Monday? What's the outlook
Speaker 1:for This this week was the Elon side for the most part. Are we gonna flip to Sam and Greg and and some other OpenAI folks, or is there an intermediate step? Like, do you do you have a clear view of what the next couple weeks look like?
Speaker 3:Yeah. So it's a little rough because we we have witness lists in full that they presented and are in evidence, but they you don't really learn who's coming until, like, very soon that week. It's actually a giant pain in the ass for me and for reporters who are trying to schedule. But, like so we Jared Birchall
Speaker 2:Yeah.
Speaker 3:Who's, like, Musk's family office guy, just finished testifying. We're gonna get this guy Stuart
Speaker 2:Russell That's today.
Speaker 1:As No. No.
Speaker 3:That that was yesterday. That was yesterday.
Speaker 1:Right. And and you said Burchall was very dry. Like, was that intentional? That feels like that does not work in favor of, like, swinging a jury. Was that more for the judge?
Speaker 1:Like, what was the goal of that of that testimony?
Speaker 3:I think it was to really just sort of show how Musk was trying to set up this, like like structure things as a non nonprofit and like hammer home. Like he's always wanted it to be a nonprofit, and he's not sort of like so it was it was I believe it was Musk's witness who OpenAI then cross examined, and OpenAI used the occasion to show an email that had like a proposed equity structure
Speaker 1:Yeah.
Speaker 3:For Musk. And so like they both kind of used him differently, but I think like Bertrand's like a essentially an accountant, books guy, like, behind the scenes. So I think it was like, here's the beat behind the curtain. Here's how they were dealing with the finances. Here's how Mhmm.
Speaker 3:Musk was like, this is only a charity. And then OpenAI's lawyers were like, actually, check this shit out. So I but I think, like, I don't I honestly don't know. They also struck some of his testimony because is a little complicated, but if you remember last year, OpenAI or Musk made a bid with Ari Emanuel and some other buy companies
Speaker 1:the whole company.
Speaker 3:And that opened the door or that sort of complicates things from Musk's side because there might be some of those discussions around that bid admitted into evidence, and that may not be good from Musk because if there's, like, weird compromising emails in there. So, like, it's gotten complicated. But next week, we're getting Stuart Russell, safety researcher. We got Greg Brockman. Maybe Sam Altman.
Speaker 3:Maybe not. It's four days a week in court only, so we may not have time, but I gotta be ready. I'll be there most of the time, but I'll be there for Sam for sure, and then I don't know.
Speaker 2:Sorry. Rewinding a second. Did did they bid did they bid on the PVC, like, the the for profit arm? Yeah. That was the
Speaker 3:It was the yeah. And they they wanted to just sort of I I don't actually know what their plans were afterwards, but, like, it was like trying to take over the asset those assets basically, and then, you know, morph it into what they I mean, they knew that it wasn't gonna get accepted as a bid basically, but it was like and then Burchall sorry. Burchall in court was saying this was us trying to sort of establish a pricing mechanism to, like, value the actual entity itself, and that was gonna help them somehow. I actually am not quite sure how that would help them somehow, but someone in the chat is probably smarter than me on that. But, like, it was them trying to sort of take that over.
Speaker 3:And I think OpenAI said publicly at the time this is, a stalling tactic. They're trying to, like, slow us down while also using this in court in this concurrent lawsuit later, basically. So it's all, like, really messy, and I think even Musk's side took a risk there if those emails get into discovery, but it's unclear to me if that's gonna happen. If we if they are, then we may see them next week.
Speaker 1:Do you think
Speaker 2:Why would that that kind of discovery process around that bid be coming up now when everyone involved was well aware that it had happened quite a long time ago?
Speaker 3:So I think because of a line of questioning with Birchall yesterday about the bid that like, if that happens on the stand and again, like, a lawyer gut check me here because I'm a stupid tech reporter. But if that happens on the stand, then it gives an entry point for open eyes lawyers to be like, okay. Well, we need to, you know, now admit basically, the judge said to Musk's side, you open this line of questioning. Now it's fair game to go into this, and then you can start calling new evidence in around that, like, to open up discovery. It's like really like strategy, and, like, you have to be careful in your strategy when you're asking certain questions in court.
Speaker 3:I've been learning a lot about it. So maybe it's a strategic misstep by Tobaroff, Elon's lawyer, but it's not quite clear yet.
Speaker 1:Do you have a idea of the purpose of the AI safety researchers testifying what the goal is there? Like, does that align with one particular side? Like, if there's more nonprofits, like, you still probably wind up with Anthropic, DeepMind, x AI. Like, it it, like, having one, like, you know, more focused nonprofit going on for a long time doesn't necessarily lead me to, like, oh, then we wouldn't be in an AI race. Like, it's it's not a clear solve for me, but I imagine that there's that some one side is trying to position this as important.
Speaker 1:But do you have any predictions for what that goal is?
Speaker 3:Totally. So this is Musk's witness, and your point is well made, which is like, okay. If even if you kneecap one, like, good luck on literally everyone else.
Speaker 1:Yeah.
Speaker 3:And, like, there's been a lot of time spent Elon talking smack about Larry Page and how he, like, doesn't trust him anymore. That's actually been really fun to hear. But the the point I believe is this is actually a point of contention. So the judge does not the judge prohibited like going too far into like doomerism into the world stuff,
Speaker 1:and
Speaker 3:she's like, look, that's kind of a sideshow distraction, like extinction humanity stuff is not the point of this case.
Speaker 1:Yeah.
Speaker 3:But must side call this guy because they want someone, and this is my understanding is that Stuart is like very aligned with the idea that AI is super dangerous and gonna harm us all. And so if you get this How does guy
Speaker 1:in there
Speaker 3:make that point.
Speaker 2:How does that not like, if this guy's gonna come on and say that AI, like, the the most insane, like, doomer point of view, which I think is everyone's gonna have their own Sure. Opinion around this debate. Sure. It's worth completely worthy of of having and and talking about. But but how does Elon square that with like, I'm trying to build the biggest cluster possible and, you know, distill on the rest of the industry's model and, you know, create tens of of gigawatts of space compute and like how how does that how does that like can't this kind of witness potentially backfire in some capacity?
Speaker 3:No. Mean you're you're you're exactly right in that squaring that circle is pretty hard and like exactly what I should be I
Speaker 2:should be I I should be trusted with the, you know, all powerful
Speaker 1:We're gonna be in the Terminator situation no matter what. So you want me in charge of the Terminators, not some other guy, not some nonprofit, not some Well, well positioned. Shareholders.
Speaker 2:Is making he's he's he's pivoting Tesla production to Terminators. To Terminators basically. Yeah.
Speaker 3:No. I I and can I just make one last point is that I think he he misunderstood the Terminator because like we still survive and we fight back in that world?
Speaker 7:Do you
Speaker 3:do you remember this?
Speaker 1:I've been saying this. People haven't seen the movie. Jordy actually hasn't seen the Terminator. But in all of Are these movies
Speaker 3:kidding me, dude?
Speaker 1:Yeah. Yeah. In in in all of these movies, like, it completely leaves out that there is a problem and then humanity overcomes it. And so it's Yes. If there is a Terminator scenario, like, I just wanna know that you're on my side as the resistance fighting back.
Speaker 1:And like No. It's John Connor here.
Speaker 3:Yeah. You're John Connor.
Speaker 1:Hopefully. I mean, I I would yeah. It's don't know. I don't wanna get into the the the full Udkowski thing, but like like it is reasonable to be to to to to sort of steel man that like if it is bad, right now it's not.
Speaker 2:It's says I have to
Speaker 1:watch Terminator.
Speaker 2:I gotta watch Terminator tonight.
Speaker 1:You gotta watch Terminator.
Speaker 3:Okay. So just saw this on Twitter. Terminator two is coming back into IMAX pretty soon. You can go see it in the theater, so you have to go see it, Jordy. Like it's it's required viewing.
Speaker 2:Let's go together. Yeah.
Speaker 3:Yeah. I'm down. I'm down.
Speaker 2:Do you do you have any I would say that so far the trial is less. I mean it's hard for the trial to go very viral because there's no audio video and it's just like live blogging. You can imagine you can imagine some of these scenes like just the stuff that you're typing. I'm like if that was on video that gets like 50,000,000 views in like Oh, man. You know, in a few hours on on on x, you know Yeah.
Speaker 2:Across a bunch of these different aggregator accounts. But part is is maybe part of the like, my my feeling is like it's just so it's just so like, I feel like the entire tech industry is like, it's just kind of depressing to see to see these groups like fighting in this way when we have so much bigger problem. Like we have so many bigger problems as an industry. Right? The big problem being like public perception of AI is like already so bad.
Speaker 2:Like people, you know, don't don't like, you know No
Speaker 1:matter who wins, we all lose or something like that. There's some very negative stuff and
Speaker 3:I mean that so I totally agree and I do think actually everyone not everyone, but like many in the AI industry have started realizing, oh, we have like, not everyone loves us. Like, this is a perception problem in a lot of ways, which like to me is funny because like I I not that I'm smart, but I feel like I've known that for a little while. And but it's the the the issue is the the industry is coming around to that, or at least certain folks are, and know that they want to change that perception. Yeah. But this case has been in the system for like years now, and sort of like actually happening at a time where they wouldn't want it to necessarily happen if they're trying to change it.
Speaker 3:So the timing just sucks, honestly, for for folks who don't like that, if that makes sense.
Speaker 1:Yeah. There's so many different, like, little tidbits, and I don't know if they're gonna be exact quotes, but you can just imagine plenty of things that are gonna happen on the stand winding up on a Bernie Sanders postcard and being like, stop it. Paul's AIR. Oh my god. I guess, like, you know, it's always, like, give the tech people enough rope to hang themselves and like, there's a lot of rope going out the next couple of weeks.
Speaker 9:Oh my
Speaker 1:gosh. It's
Speaker 3:totally you gotta one of y'all both of y'all should just show up to the courtroom at some point Yeah. And like experience it because, I mean, you have an actual day job, but it's, like, literally
Speaker 2:Figure
Speaker 3:it out. It's really interesting and, like, an experience. So you
Speaker 1:you can't record video. You can't record audio. Is there a world where you have, like, five of your own stenographers there taking a perfect transcript? Would that be possible with enough resources?
Speaker 2:And then we could do a table reading on the
Speaker 3:show.
Speaker 1:That's what I'm thinking is that is that you could use voice cloning. I don't know if you noticed this. Tyler, what was it? Grok launched voice cloning today or something? Yep.
Speaker 1:Which is why is that controversial again?
Speaker 5:Well, for like I mean, we we've had this technology for like five years and then no one released it because like you don't want people to make deepfakes of other people's voices.
Speaker 1:Okay. Yeah. Because it's like textbook like I can
Speaker 5:It's like, oh, I I
Speaker 2:call you John. I need I need I need like Yeah. $500. Okay. Can you just give me your credit card
Speaker 1:for So a obviously, there's a bunch of risky uses of that. The good use is the comedic table read in the voice of Sam Baldwin, in the voice of Greg Brockman, in the voice of Eli Fox that we can all enjoy.
Speaker 2:Was thinking more of like doing like a Judge, judge,
Speaker 1:and TMJ's.
Speaker 2:End of the day. Yeah. There's like we do a play here.
Speaker 1:Yeah. That's probably best. Best. Full costume.
Speaker 3:You know, there are transcription services Okay. And even like
Speaker 2:You could do you could be Mike Isaac by like Oh, He's
Speaker 1:the one playing you for sure.
Speaker 3:No. No. They're pod tweeting.
Speaker 2:No. It's like it's a it's a cameo.
Speaker 1:He's playing himself. Good night. And then you gotta go full Nathan Field.
Speaker 2:And the whole the whole time just crashing out like I forgot my lunch. I forgot to fill up my water.
Speaker 1:I had a banana. I had a banana. Oh my god. Okay.
Speaker 3:Can I just say there is an attorney there that looks exactly like Nathan Fielder? Really? And I'm like, almost like
Speaker 2:Are you sure
Speaker 1:it's Nathan Fielder? Looks like Nathan Fielder. Okay.
Speaker 3:I I every time I see him, I'm like, is this, a bit? Like, I'm am I gonna be on TV in some way? It's very intense. I'm gonna ask him next year.
Speaker 1:I mean, Elon Musk says the funniest outcome is the most likely, and that might be Seriously. What what is the what is the funniest outcome? The funniest outcome is like Elon wins and the penalty is like is like $50 or something. Yes. Like that like that it's like Elon like you win.
Speaker 1:Here's here's a $150. Enjoy.
Speaker 3:It would be very hard. Oh my god.
Speaker 1:Just the most like inconsequential fine for the AI industry which is flush with cash at all times.
Speaker 2:Well, find that like Yeah. You're good. Fine like there's so many any anytime a company in tech gets that gets fined or not every time, but often it's like
Speaker 1:Sometimes it's a fine for ants.
Speaker 10:Yeah.
Speaker 2:Like, they they they did something that was bad. They generated a 100,000,000 of revenue and the fine is like $1,500,000. Yeah. It's like,
Speaker 1:did that I think the current meta YouTube lawsuit was like maybe a $10,000,000 settlement. Of course, there was like Oh, wow. Knock on of potential for
Speaker 2:that was for one individual.
Speaker 1:That was one individual. But still, it was you have this like landmark case, this big build and then you're like, oh, how how how damaging is it gonna be? It's gonna be like five minutes of revenue.
Speaker 3:But The stock actually in Meta earnings is as far I mean, there was a lot of shit that took the stock down. But like, I think one of them was them saying, like, this might have a material impact on like, these cases, like, may have a material impact in the future if it opens the door. So, like, yeah, I agree. Like, it's always remedies are always, like, it can be existential from a financial point of view, but also just from a guess what? This is about to become your whole fucking life for the next ten years or whatever, if that makes sense.
Speaker 1:Yeah. Yeah. We talked to a a a law professor who said, like, the question is, social media exist in the future? Like this is an existential moment. I'm not sure that we're quite there, but is it is there's definitely a risk and you need to consider that if you're an investor.
Speaker 1:Totally. Anyway Totally. What's the game plan for next week? What's going in? Are you doing trail mix?
Speaker 1:Are you doing protein bars? I want you fueled up, ready to go.
Speaker 3:Camelback? Blogging to be a Camelback.
Speaker 2:You you should be able to do like a sponsored Camelback. You know? Did
Speaker 3:you ever watch jury duty the show jury duty?
Speaker 1:Oh, yeah. Of course.
Speaker 3:I I wanna be the guy with, like, the chair pants Yep. And the, like, the water thing attached to my back. And, like, I need I'm gotta this is blogging. This is back in my blogging all things digital blog days, man. This is this is it.
Speaker 3:So
Speaker 1:I This will train weekend.
Speaker 3:More prepared. This weekend. That's right.
Speaker 1:You should go sit in a chair for eight hours straight. Are you are you
Speaker 2:gonna do all four days? Are you doing all four days?
Speaker 3:I think we're gonna switch off a little more. I I apologize. I will not be my, like, disastrous falling apart self every day of the week, just maybe two days of the week. So Kate you should follow Kate Metz, my other colleague who's Although he he is much more put together and does not tweet like a person off their meds like I do. So it'll be a different vibe each day, but I I will be there next week.
Speaker 1:Last question. Is this book material? Is it there's a rise to that quality, this drama?
Speaker 3:I do like the someone's gotta
Speaker 2:read it. I would I would write a book on your coverage of this trial.
Speaker 3:Yes. That's what I wanna
Speaker 1:read. This the my And that's I would
Speaker 3:do a podcast about it.
Speaker 2:I would do a podcast about it, and then someone would make a book about the book. Coverings.
Speaker 1:This is the covering. We'll create a content Ouroboros here.
Speaker 3:I'm not sure. We'll just keep it going someday. I don't know. We'll see.
Speaker 1:Anyway, thank you so much for taking time talk to Good
Speaker 2:to see you, Mike.
Speaker 3:Thanks for
Speaker 2:the update.
Speaker 1:We'll talk to you soon.
Speaker 3:Have a
Speaker 2:good one.
Speaker 3:I'll see you soon.
Speaker 1:Bye. We're running late, but we got Kyle Harrison in the waiting room. Let's bring him into the TBPN Ultra Dome. He wrote a book about the Andoril thesis, 300 pages of defense tech lore history knowledge. You know what's more valuable than any of these cars up here in the Hollywood Hills knowledge?
Speaker 1:And you wrote a book. Tell us about it. What was the process? What was the thesis of the book, the Andoril thesis?
Speaker 9:It was an incredible experience. I would say I think the thing that I came to appreciate the most was everybody talks about Andoril like it's just any other company. All these high growth companies that are are defined by an awesome team chasing a big idea, Market turns out to be bigger than you possibly expect. You know, Ben Horowitz has to tell Databricks that they're undersigning themselves at 10,000,000,000. It's a 100,000,000,000.
Speaker 9:It's 200,000,000,000.
Speaker 1:Yep.
Speaker 9:Like, those stories are very common. Yep. The Andoril story is so underappreciated because it is counter positioned to there's like over almost a hundred years of military, geopolitical, industrial history
Speaker 1:Yep.
Speaker 9:That really define the company that people just they just they don't know. Like, they think about, oh, this is an interesting strategic choice, it's like, no. This is actually because of things, decisions that people made in the fifties and sixties that we literally have to do things this way. That was the biggest takeaway.
Speaker 1:Yeah. I feel like Shamsankar at Palantir with the first breakfast has done a good job shining a light on the Last Supper. So Mhmm. Many people in tech are familiar with that sort of key moment of industry consolidation that led us to this moment. Were there any anecdotes or historical stories that you discovered that were more under the radar, more, like, less discussed as, like, you know, the the the the founding moments of this whole journey?
Speaker 9:The biggest appreciation that I got was for this sort of, like, dual pairing of people pushing forward a specific project. In The Kill Chain, which is Chris Brose, who now is the kind of co president and chief strategy officer at Antero, but at the time was coming off the Armed Services Committee. He wrote this book, The Kill Chain. He talks about this idea of, like, military mavericks.
Speaker 1:Yeah.
Speaker 9:And I kind of combined this with this kind of founder founder mode energy that people bring. And so you have this, like, founder plus military maverick pairing, where you have folks like the the team so Bernard Treiber, I think is the name of the guy, who basically led the team inventing ICBMs.
Speaker 3:Mhmm.
Speaker 9:He absolutely needed Eisenhower as his kind of military maverick Sure. To, like, pair that effort. Yeah. There's countless stories of this, the modernization of the Navy. There's all these different things that were like, that one two punch was kind of required.
Speaker 9:Once you get away from, like you know, at one point, the DOD was 36% of global R and D Yeah. They had a pretty good handle on the cutting edge. Once you've the further away you get from that, the more you need founder mode people digging in to figure out the solution. Sure. And and it's heartbreaking because you see these, like, countless examples of, like, profits of urgency throughout time, where, like, once we lost that that sort of, like, desire for founders to come in and solve problems, you have all these people who are, like, throughout the eighties and nineties and early two thousands, they're releasing reports and and writing white papers and talking about how, hey.
Speaker 9:This is gonna be a problem. Warfare is changing. China's going to school on how we do conflict, and that's problematic. And none of them had sort of founders to be able to come solve problems because no one was willing to pay attention to the actual problems, and so we lost that pairing.
Speaker 1:There's reports of Vanderbilt raising a new round, $60,000,000,000 potentially. Is this book a financial thesis? Is this financial advice? Is this something that investors, potential investors, maybe future investors Yeah.
Speaker 2:There's four chapters dedicated to price targets.
Speaker 1:Price targets,
Speaker 9:multiples, cash For entertainment purposes only right across the right across the no this is this this does not constitute financial advice
Speaker 1:Okay.
Speaker 9:Entertainment purposes only. You know what's crazy is, I think, if I remember correctly, in secondary markets, if if there is any secondary volume that that Androil's founders haven't already gone to war on
Speaker 1:Yeah.
Speaker 9:I heard somebody say that it was like a 100,000,000,000 indication. Like, even just tracking, like, what people are willing to pay because of Matt Grimm's war, there may be no no supply for the demand, but the demand is priced at a 100,000,000,000. So it's not, you know, where where the new round ends up, whatever, the appetite continues.
Speaker 1:Sequel. Sequel. The annual financial thesis. Let's go.
Speaker 9:That's right.
Speaker 2:This is investment advice. Anderil's been very very acquisitive. And it feels like the some of the most, like, meaningful innovation and, like, founder mode behavior in the last twenty years has come out of, like, Ukraine and what what they've been doing to basically figure out how to, like, innovate and create these, like, r and d loops around drone warfare. Like, do you any any I don't I don't know if you can make predictions, but, like, does Andoril end up buying any of these companies? Is that is that have you have you uncovered anything on that front?
Speaker 2:Is that even is that even a possibility? It just feels like they've done some very impressive work to, protect their their country and, a lot of it seems relatively aligned to Andriel's own efforts.
Speaker 9:Yeah. So there's a couple of pieces of the puzzle. So first, like, in terms of how acquisitive Andriel has already been, our, you know, our good friend, Paki McCormick, has described it well. Think that calling it an an API into the DOD Mhmm. Where Andoril is effectively enables this, like, plug in mechanism of somebody can go very deep into a very specific capability in a way that, like, like, companies like the the company that may dive like, it'd be very difficult for them to sort of become a standalone large company.
Speaker 9:Mhmm. But by being acquired by Andoril, immediately, they're able to plug in and get a $100,000,000 contract with the Australian Navy and and stuff like that. So I think like the acquisition muscle plugs in a lot of other stuff pretty capably. The second piece of that puzzle is I think that a lot of times we do a disservice like the venture capital industrial complex does a disservice by focusing everybody on this sort of like neo prime North Star of everybody needs to be the $10,000,000,000 20,000,000,000 50,000,000,000 $100,000,000,000 outcome. I think that there are a lot of opportunities for companies to be very, very good at a very specific thing capability and then to plug into some of these systems, whether it's through partnership or through acquisition.
Speaker 9:And what's funny, probably the most frustrating part about the book is we wrote it over the course of two years in part because we you know, it's it's difficult to sit down. We all have day jobs and stuff. But in part too because the world is constantly changing. Right? When we started when we originally sat down thinking about what would this would look like, you know, none of the things that happened in in Israel, like Ukraine was sort of just continuing to evolve, Venezuela happens, all these different conflicts happen over time.
Speaker 9:But then on top of that, Andoril as a company continues to ship. And so even six months ago, I would have said, what is the kind of like signal? And what's interesting is you look at some of their product launches. Some of these requisitioning some through partnership. But I don't if you guys have seen their like anime style No.
Speaker 9:Product launch videos. Right?
Speaker 1:Oh, great.
Speaker 9:So I don't know if everybody has noticed this, but the last two videos had teasers of their future products. So I think it was the video that where they talked about Furi. And then it was maybe Furi or the Barracuda. And then at the end of the video, it kind of went under the water and you started to see these assets moving, but then it cuts away and you don't know what it is. Couple months later, they they announced Copperhead, which is their, like, torpedo product.
Speaker 9:And that paired with Dive and stuff, then they have a video about that. And at the end, it pans above the water and you start to see this thing kind of come out of the corner of the shot and it cuts away. And then just, whatever it was, last week or so, Andrew will announce a partnership with Hyundai about building autonomous surface vessels, right? So it's like kind of going into all these different surface areas. I think that that is indicative of like where the signal is, is that whether it's through partnership, whether it's through acquisition, a lot of the stuff that's happening in Ukraine, what kind of exposing is that there is significant opportunity for like networked assets.
Speaker 9:And Anderil is absolutely has this mindset on becoming the the sort of networked everything. The military yeah. Military Internet of Things is what Chris Bros calls it.
Speaker 1:Where can people find the book?
Speaker 9:Amazon.com. Our own Jeff Bezos is hosting it for us. We're not in the book printing business so
Speaker 1:You're do an audiobook version of
Speaker 2:Oh, they print they have a print on demand.
Speaker 9:Yeah. It's sick. It's great. It's you put in the thing. It takes a lot
Speaker 2:of what
Speaker 1:I'm thinking, John? What you're thinking.
Speaker 9:It's pretty good. I'm
Speaker 2:telling you time what. To it's time to ship books.
Speaker 1:You gotta write a book about
Speaker 9:TBPN the novelization.
Speaker 2:We wanna make we wanna make ad supported business books. They're free. Yeah. But they come with ramp ads.
Speaker 1:Yep. That's great.
Speaker 10:You could you could yourself
Speaker 1:a good sign.
Speaker 3:It's as easy as it
Speaker 1:can be.
Speaker 2:Last question from my side. Do you have have we reached peak early stage defense tech investing boom? Has it already passed? Is it are we still on the app? Like, what what is your feeling at this point?
Speaker 9:I think that it is going to take to to take the air out of the balloon is gonna require some type of black swan. Hopefully hopefully micro swan micro black swan event. We
Speaker 3:don't want it to be too bad and Wait.
Speaker 2:Said to take the air out of the defense tech investing sales, you would need a black swan event. You're saying like World peace. We declare global peace.
Speaker 9:World peace. I think I think it's more about the capability. I think it's gonna take like either there is a company that has been highly valued, highly sought after, kind of held up as one of the golden children of the the neo defense industrial wave that just something
Speaker 1:things are just It's terrible.
Speaker 2:It's really bad.
Speaker 9:Oh, okay. Like something very bad happened. And so then investors start to say, oh crap. Wait. You're telling me not every company I invest in that does defense is gonna be the next and roll?
Speaker 9:I can't underwrite to every company. Maybe they're not 60,000,000,000, but at least they'll be 20,000,000,000. Like, if that underwriting muscle goes away
Speaker 3:Sure.
Speaker 9:You have a whole swath of carpetbagger VCs that suddenly get very panicked. Like, something like that happens.
Speaker 1:Social, there were a whole bunch of, like like, fifth wave social companies that didn't get the Instagram acquisition. They didn't get the WhatsApp acquisition. They raised a couple $100,000,000, and they just sort of burned it down and just went away and nothing really happened. And the VCs sort of woke up, and they're like, okay. We gotta be much more careful if we if we're investing in that category.
Speaker 1:So
Speaker 9:Yeah. Because I think it's like I think the problem is, like, there are sort of, like, three varieties of VCs are in and around, like, defense tech more broadly. And it's, the people who invest and get it and they're actively building understand the, like, moral implications of the types of technology they're investing in. Then there are still people who have said, we will not invest in weapons. We don't want to invest in defense, whatever.
Speaker 9:It's this middle ground tier that is problematic. It's these people who they have no real philosophical weight behind why they do what they do. They just see big number and pursue shiny object regardless of consequences.
Speaker 1:Line go up. Well, we hope that the line goes up on your book sales. Head over to amazon.com and buy The Andoril Thesis by Kyle Harrison of Contrary. Thank you so much for coming on the show. Can't wait to see soon.
Speaker 2:Great to see you. Okay? Congrats, dude. Goodbye.
Speaker 1:Thanks. Up next, we have David Marcus from Lightspark. He's the cofounder and CEO, and he's launching Grid Global Accounts, a Bitcoin powered system enabling global USD accounts, cards, and cross border payouts. We talked a lot about crypto payments yesterday. We'll let you introduce the business yourself.
Speaker 1:Again, welcome back to the show. Give us the update on what's
Speaker 2:going on
Speaker 1:your world. Great to see you.
Speaker 11:Thanks for having me back, guys. Well, look. So the the big announcement we had this week, so Lights Park has been around for about four years. And, you know, in the last four years, we've been building connectivity into payment systems all around the world, like 65 countries now. And the announcements that we added this week is great global accounts, which is basically a global dollar account that any platform can issue and give to their stakeholders.
Speaker 11:And that dollar account is what I think is the most powerful money account ever created because you can move money in real time to 65 countries, payment systems, like, really at any time of the day or night. You can move money on any chain with any stable coin you want. You will have a Visa debit card that can allow you to spend that balance at a 175,000,000 merchants around the world that Visa supports and Lightspark is becoming a a principal member of the Visa network as part of that process. And it's got, like, this nice feature that enables those platform to actually be ready for the the complete change of interfaces as we move from websites and apps to conversational interfaces driven by agents. And so this idea that you can delegate safely money to agents so they can buy things or send money around the world for you is really part of that whole GRYT global account platform that that we've announced and launched this week.
Speaker 2:Very, very cool. So how how like, when when did you guys start thinking about this opportunity? Obviously, you know, everyone's thinking about stablecoins. We have more regulatory clarity than ever. Was this always on the roadmap?
Speaker 2:Or did you guys start to get customers saying like, hey, we want support for stables and not just BTC related products?
Speaker 11:Yeah. I mean, look, I think, you know, we so we've been working on stable coins for a long time, but the the concept of a global dollar accounts that can actually live everywhere is really novel and like the the the there was no chance of us like actually doing that like even twelve months ago because like the the prerequisites, the stars were were really not aligned. Right? And right now with the Genius Act here in The US with MICA in Europe and similar legislation all over the world, plus really really great embedded wallets like, you know, the the self custodial wallets of like two years ago where you had a seed phrase that you could lose and you would never give that to a family member because like they would lose money almost invariably. All of that is gone.
Speaker 11:Right? So now you have really great wallets that you can log in with Google, with Apple, with a passkey, with any login that's familiar and never lose your your keys or or your money. And the last part of it is actually really stable coin backed debit cards where the networks have really leaned in hard on and like now gives us an opportunity to really basically connect those dollar accounts to a 175,000,000 merchants around the world making that balance really useful for anyone receiving money on them.
Speaker 2:Yeah. Very cool.
Speaker 1:Is the pivot from CryptoMiner to AI Neo Cloud that's happening across the industry having any sort of effect on crypto markets? Or is that a because we we talk to companies all the time that are compute constrained. There's this CPU crunch. There's GPU crunch. There's backlogs for power, and data centers are delayed, and that's what's going on in the AI world.
Speaker 1:But Bitcoin as a network needs compute as well. Many other chains need compute. And is compute scarcity bleeding over in any way to the upside or downside? I I I just I don't know the effect at all. Does it matter, or is there enough compute for crypto to do everything that they wanna do as a community?
Speaker 11:Yeah. I mean, look, I mean, proof of work is definitely and so, you know, more more specifically for the Bitcoin network, proof of work is definitely using the the level of energy that at times will compete with like AI data centers. Sure. But but, you know, the hardware is like, you know, started GPU based, but it's very a six driven now. But on the energy side, definitely definitely competes for the the same source of energy.
Speaker 11:But, look, I am personally an acceleration maximalist, then I actually think that we're actually going to unlock unbounded energy in the next, like, you know, ten, fifteen years. So I I I actually don't think that we're going to have these types of issues of, like, actually competing resources with, like, massively, like, you know, forward deployed amounts of capital on Bitcoin miners being replaced with, you know, GPUs. And and also, like, those data centers for for Bitcoin mining are are so specific, like, you know, a lot of those miners are, you know, liquid cooled in a certain way and like operate on certain grids that, you know, they're able to actually like turn on and turn off the the mining capabilities really easily whereas Yeah. Like you know, it's harder for
Speaker 1:necessarily you wanna do that if you're like actively serving inference or even just like training. You might not wanna bring the bring the train down. Interesting.
Speaker 2:Where where are you expecting to see the first real hockey stick growth when it comes to agents leveraging stablecoins.
Speaker 1:Oh.
Speaker 2:Because like right now, it feels like there's a like it's a lot of like potential early experiments going on. But at least to me, it's unclear where we'll see that, you know, really break out use case.
Speaker 11:Well, I mean, I can share a little bit more about, like, you know, my my thoughts and my experience. Like, you know, the the first thing is I think that everyone competing to build, an agent to agent protocol standard is kind of, like, you know, really future forward.
Speaker 1:Mhmm.
Speaker 11:And there's not much happening there. Right? It's like there's a lot of like big news and big announcements and very little volume. And that's normal because like, you know, agents are not moving money at scale by by any stretch of imagination. We took a little bit of a different stance, right, which is that we want to build a mass market money account that suits the needs of people and businesses all over the world.
Speaker 11:And then we've a safe scope delegation framework that enables those agents to actually use the debit card, use the 65 countries reach of moving money around, use like the multi chain support for stable coins and then you can delegate that. And so what I've done with mine and I've lived with it for the last like, you know, five weeks or so. So I have my great global account and then I have an open claw running on Mac mini at the office and I connected both and and and so it it just takes a scoped debit card, goes buy things online, which is actually more difficult than I thought, you know, starting this but like it now works. It it can message people on WhatsApp that I need to send money to and offer them like, you know, seven or eight different ways to pay them and I don't have to worry about it. And it really works real time really really well and it's been it's been so much fun to actually build on OpenClaw and have like a money account that that that that Lobster could use.
Speaker 11:It's been it's been a
Speaker 4:lot of fun.
Speaker 1:Yeah. Yeah. It's awesome.
Speaker 2:Lobster accounts.
Speaker 1:Well, thank you so much for taking the time to come chat with us. Congrats on the progress. Thanks for having me.
Speaker 3:Great great
Speaker 2:to get the update. We'll see you back. Yeah.
Speaker 1:We'll have to go
Speaker 2:way deeper. In the next hopefully in the next one or two quarters.
Speaker 1:Yeah. Fantastic. Sounds good. We'll talk to
Speaker 3:you soon.
Speaker 2:See you.
Speaker 1:See Have a great weekend. Up next, we have Turner Caldwell from Marina Mariana Materials. Mariana Materials, like the Mariana Trench. We'll get into it with Turner Caldwell, the co founder and CEO. Help me understand how to pronounce this company's name.
Speaker 1:I don't wanna get it wrong.
Speaker 12:Mariana Minerals. Mariana.
Speaker 1:Where does the name come from?
Speaker 12:It comes from the Marias Trench. Mariana Trench. But that's because we were looking at
Speaker 2:guess. They've got some crazy minerals down there. Or do we even There
Speaker 12:are some minerals at the bottom of the ocean. That's right. That we So are
Speaker 2:you're saying you yearn for the trenches.
Speaker 12:That's right. There you go.
Speaker 1:Okay. The business is an autonomous copper mine. Can you take me a layer deeper, explain the history of the business, the current current shape of the business, where you where you where you're taking it all?
Speaker 12:Yeah. Sure thing. So we just restarted a copper mine that we acquired at the end of last year with a major focus on autonomy across the entire stack. So that includes the kind of orchestration layers around mining operations as well as autonomous execution, which we'll do with partners. And and then also autonomy around the refining processes.
Speaker 12:So the the site is a mine and a refinery.
Speaker 1:Yeah. But but we're In practice, what does that look like? Like, you go into the mine and there's and there's some, like, ERP system or maybe just some, like, manual paper based workflow, and you're saying, like, let's go vibe code a software solution for it? Like Yeah. Or is it like more
Speaker 12:than vibe coding. Yeah. Yeah. Basically basically, the way to think about mining is that you have a whole bunch of different disciplines that have to collaborate. It's a big coordination problem.
Speaker 12:You have geologists. You have a geologic block model.
Speaker 3:Yep. You have a
Speaker 12:mine plan. You'll usually have multiple mine plans, like a long range, medium range, and short range mine plan. Okay. That has to be transferred to the mine operations teams that are running a ton of, like, large scale or not autonomous, large scale manual Yeah. Mining equipment.
Speaker 12:Then the like, what is actually in the ore usually shows up on a piece of paper to the refinery saying, like, get ready to process this.
Speaker 1:Okay.
Speaker 12:And then the refinery the folks who are running the refinery have to figure out, like, kind of the optimal process conditions to maximize recovery of copper, lithium, nickel, cobalt, manganese, iron, graphite, kind of the whole thing. Yeah. All of the different metals through the processing circuit. And so what we're doing is we're kind of integrating everything into one, like, integrated data frame first. And so there's a lot of work that goes into kind of bringing all of the data feeds back into one, like, kind of aggregated architecture.
Speaker 12:And then we'll build world models of the mines of the refineries that we then use to kind of do a reinforcement learning training that we feed up into a reinforcement learning training pipeline. And then you wanna close the loop between what reinforcement learning agents are recommending on the policies that are developed to the actual thing that's happening in the mine. And so we'll bring autonomous haul trucks in. We'll bring autonomous drill rigs in. We'll bring in autonomous loaders and dozers and graders and water trucks, kind of like all the assets that are being used to run a mine that today are, you know, 99% of mines are are manned.
Speaker 12:And we wanna go full closed loop between kind of the world models and the reinforcement learning agents and and determining what the autonomous assets actually do. And then I to the refinery.
Speaker 2:What do you think the potential efficiency gains are from going from legacy copper mine to the kind of end state, you know, fully autonomous system?
Speaker 12:Yeah. I think it'll happen in two phases. I think the first phase is gonna double productivity, through just, like, better orchestration and better logistics management and better utilization of all the equipment. The that's productivity and and and unit costs. You know, diesel is a good example for for heavy haul machinery.
Speaker 12:Like, half of the diesel consumption up to half is from, like, idle time in the in the pit on the equipment. And so there's a lot of kind of, like, short term potential gains, but I also think that autonomy is gonna fundamentally change. It's gonna unlock a lot of, like, operating modes that can't really be done with humans. And so the way that the mining industry has kind of driven down cost over an extended period of time has been through scale. So the haul trucks are getting bigger, the shovels are getting bigger, and it's all focused on kind of reducing your labor intensity.
Speaker 12:So, you know, maximizing tons of ore tons of ore moved or tons of material moved per unit of, like, labor hour. But as you move into, like, autonomous systems and eventually kind of, like, design the mines themselves to be autonomous, I think we're gonna see things get smaller. And, like, swarm mining is gonna get unlocked, and that's fundamentally gonna enable you to actually kind of, like, be more selective in how you mine. Your roads get smaller, which means you can maximize kind of recovery of the ore from the pit. Yeah.
Speaker 12:So I think it'll all happen in two phases. It's like, take the existing architecture, make it autonomous, and maximize utilization and and availability of equipment. And then there's gonna be this, like, once autonomy is kind of, like, fully demonstrated across the stack, there's gonna be this opportunity to actually attack, like, fundamentally how is how are minds mind?
Speaker 1:You started the company in 2024?
Speaker 12:Yep. 2024. Raised a seed round in August. We're at 220 people now across the company. We have we have two projects.
Speaker 12:One is a lithium refinery in one's a one's a lithium refinery in in East Texas that's extracting lithium from oil and gas wastewater and the and the others are kind of first large scale commercial mine.
Speaker 3:Another one.
Speaker 1:He's got two.
Speaker 3:Yeah. Exactly.
Speaker 1:Pitch I have a question.
Speaker 2:Pitch for you. Robotic canaries.
Speaker 5:Do they Well,
Speaker 12:we have we have Sensors
Speaker 5:for sure.
Speaker 12:We have a Boston Dynamics spot that is basically like mobile sensing system Mhmm. You know, instead of the canary in the coal mine. And we use them mostly for like undercarriage inspection. So like you want to keep humans away from like heavy haul machinery, the closer they get to it, obviously the more hazards that are present. But also like the chemical refineries, ideally humans aren't walking through chemical plants all the time, kind of doing thermal inspections.
Speaker 12:There's a lot of stuff that's, like, auditory, so you're, like, listening for sounds of the motors sounding weird. Words. The exactly. And then that all that all needs to feed back Yeah. Into into, like, again, the integrated kinda, like, sensing integrated, like, data frame that tells you, like, how what's the healthier systems.
Speaker 1:Okay. Did you start with copper 2024?
Speaker 12:We started with lithium in 2020. Okay.
Speaker 1:Because it because it feels like it feels like, you know, there's this whole autonomy story, more efficiency, all of that makes sense, but the price of copper has doubled since you started the company. And I feel like that just makes bringing a copper mine back online just wildly different from an economic perspective. And and it's very interesting that you're sitting at the tailwind of like two AI trends, which are just demand for copper for data center development, wires, circuitry, all this other stuff. And then you can actually be more efficient. But you can be as you can be as efficient as they were a couple years ago and just reap twice the price.
Speaker 1:It feels like the oil dynamic. Right?
Speaker 12:Yeah. That that's right. But I I I don't think so the reason you wanna be diversified is because, like, all these metals are cyclical, and you can't really, like, live and die by a single commodity price. And so the plan was always to diversify, and the plan is to continue to diversify into nickel and cobalt and uranium and graphite
Speaker 3:and rare earths.
Speaker 12:Yeah. And, you know, as we as we kind of work to build 10 projects in the next ten years. But, you know, we started working on this project kind of like well before copper had its like little explosion and and run that it's on because you don't really want to jump into projects in the middle of the hype. Like, that's when you're gonna pay the most for an asset. That's when you're going to like, the labor pool is most constrict is, like, most in demand.
Speaker 12:Yeah. The equipment suppliers that make the equipment that is specific for a specific metal are gonna have longer lead times and and and have higher pricing. And so you really do want like, we jumped into lithium when lithium was, like, at the bottom of its recent trough and jumped into copper, you know, before it started to go on this run. So the generally, we wanna work on metals that we think have a long term, like, supply demand imbalance. Yeah.
Speaker 12:And for copper, it very it's, like, very much felt. Like, grades are dropping or or deposits are getting deeper. Mineralogies are getting more complex. And it just makes this gonna be a lot harder to make copper in the future, and that's that's what we wanna work on.
Speaker 2:What were you doing before this?
Speaker 12:I was at Tesla for about a decade. Most recently, I was running our minerals and metals team. So I was building our lithium refinery in Corpus Christi in Texas and running a lot of our battery recycling work.
Speaker 1:Very cool.
Speaker 2:Kind of like the absolutely most perfect background for a company like this that any any A VC couldn't a VC couldn't dream of a more perfect resume for this business.
Speaker 1:What what's all the text in the gulf behind you for that map?
Speaker 2:Yeah. What does that say?
Speaker 1:I understand that it's a map of America, but what's in the what what's all the text for?
Speaker 12:So these are all it's basically calling out, like, things that they don't have space for the words on map. Okay. So it's just it's a it's a legend you got.
Speaker 1:A crazy detailed legend. Yep.
Speaker 12:Well, our project is right on the border with Louisiana, so that's the that's why we got in the background on the lithium side.
Speaker 1:Well, you're a legend, and thank you for coming on the show. Legendary appearance.
Speaker 2:Yeah. Great great to
Speaker 1:meet you. Have a fantastic weekend. Thank you so much for coming on the show. We'll talk to you soon. Cheers.
Speaker 1:Goodbye. Another one. We got another guest, Everette Taylor. He's the CEO of Kickstarter coming in the Ultradome. He's in the waiting room right now.
Speaker 1:Everette, how are you doing? Welcome to the show.
Speaker 8:I'm really I mean, it's sunny Florida right now, so I'm escaping the cold in New York right now.
Speaker 1:So I'm
Speaker 8:feeling good. You got it going?
Speaker 1:Amazing. I I I'm very excited to talk about the Next Wave Fund. But first, I'd love to know a little bit about your journey to Kickstarter, where the business is today, what your day to day is like, how big is this company, sort of set the set the ground for us.
Speaker 8:Yeah. So, I mean, Kickstarter, you know, started in in in 2009. I've been here Yeah. About four years And you know, we're the largest creative crowdfunding company in the world. We still are today.
Speaker 8:When I came into the company though, the company was in a bit of decline. We were down 20% year over year. Really? And since then, you know, we've grown dramatically year over year. Last year, we had another record breaking year.
Speaker 8:This year, we're already up 52% year over year over last year. The company has been scaling and growing we are transitioning just from a crowdfunding company to more of a creator economy company.
Speaker 1:How has the AI boom, the gen AI boom benefited or changed Kickstarter projects? When I think about the, you know, the catnip of Kickstarter project, it's like a board game that probably took a lot of time to to to build. And if the if the idea is great, I might not care if somebody used an image gen model to speed up the, you know, the graphics for a tree on the back of some playing card. I could see this being a bit Yeah.
Speaker 2:Not at all. I mean, I'm sure a lot of Kickstarter creators historically were spending a ton of money on renders.
Speaker 1:Totally. Totally. But at the same time, there's does this exist at all or is this just AI slop and there's a community dynamic and there's an artist displacement dynamic? And so have you grappled with the pros and cons of the last two years crazy boom in AI?
Speaker 8:Yeah. It's a it's a it's a great question. On the AI side, funny enough, gaming is where it's probably the most controversial. Right? Because gaming tends to be very artist forward.
Speaker 1:Yep.
Speaker 8:Right? And so, we've gotten probably the most pushback and some of the most negative pushback on the AI side from gaming because they really want to see artists be able to have jobs and do their thing. And so, you know, we were one of the first major tech companies to have our own AI policy. Every Kickstarter creator, if they're using AI, they actually have to say upfront how they're using AI Yep. Crediting the artist if they're using another artist, etcetera, etcetera.
Speaker 2:Mhmm.
Speaker 8:But on the design and technology side, these new AI powered, you know, tech products, especially in the hardware side, it's booming. Right? So both categories are growing, but you you see the differences in how people are accepting of AI.
Speaker 1:Yeah. That makes sense. Talk about the partnership with Google. What's the news?
Speaker 8:Yeah. So this week, we announced the next wave fund with Google to power the next generation of tech innovation. I'm a, you know, founder myself. I saw the struggles, you being an early stage tech founder struggling to get funding. And so, what we really wanted to do was give early stage tech startups and small business owners the funding they need, the tools to be successful Mhmm.
Speaker 8:The guidance that they need, and also be able to leverage Kickstarter's audience of millions of people to really get their first customers and scale their product. So this fund is focused on innovative products in hardware, software, gaming, and connected technology. And people will get $10,000 upfront non dilutive capital from Kickstarter and Google to launch their products and their companies on Kickstarter. And we wanted to focus on these areas because Kickstarter has just a natural product market fit for technology and gaming. They are our two largest categories, and we also have a large audience for both.
Speaker 2:So you're going to have a huge portfolio.
Speaker 8:Well, Kickstarter doesn't take Kickstarter doesn't take any equity. I mean, I have a aura ring right now. I wish we did take some equity on that. But but but, yeah, we don't take any we don't take any equity. And so this is really as a way to support people, give them the tools that they need to be successful.
Speaker 8:And also build a relationship with Google. Right? These people will have an opportunity to to apply to Google accelerators for their business as it grow and scales. They'll get access to our team that, you know, has decade plus of experience in scaling new products. So it's a great opportunity for a lot of people.
Speaker 1:Where can people get started? Take us through the is there an application process? Where does the where does the journey start for someone who wants to participate?
Speaker 8:Yes. So you can go to our to our website and and check out the Next Wave Fund.
Speaker 1:Mhmm.
Speaker 8:You can apply. This is for entrepreneurs or small businesses with fewer than 20 full time employees. Mhmm. Like I say, your project has to be focused on technology or digital gaming. Sure.
Speaker 8:And unfortunately, we we've been hearing this, and we gotta we gotta shout out to our international creators. But this this is for The US only.
Speaker 2:So Okay.
Speaker 8:At least one member of your team has to be a citizen of The US and be 18 years old. So
Speaker 1:Well, lots of opportunities. And thank you for taking us through it. Thank you for taking the
Speaker 2:time to
Speaker 1:chat with us.
Speaker 2:Great great to meet you.
Speaker 1:And great to meet you. We'll talk to you soon.
Speaker 2:Peace, guys. Cheers, Everette.
Speaker 1:Goodbye. There are many more conversations going on in the timeline today. One was kicked off I think by Josh Kushner. Think he sort of started this. There were some other people talking about data center beautification, and he summed it up perfectly.
Speaker 1:He says make data centers aesthetically beautiful. And so people have been quote tweeting, posting, riffing on this, sharing different ideas. More people would be pro data center if every data center had a beautiful open to the public heated pool. That's an interesting twist. Full water slide.
Speaker 1:I think half pipe is a big idea. Monster truck rally constantly going on. These are ways to, you know, win people over sort of a nitro circus going on data center.
Speaker 2:Truck rally on the roof of a data center?
Speaker 1:Yeah. Sort of a universal basic Nitro Circus. So you get are you familiar with Nitro Circus? Are you are is this a three fingers moment for you? Are you like, I'm familiar?
Speaker 2:No. I'm just imagining
Speaker 1:never actually to Nitro Circus.
Speaker 2:I'm imagining they're building the like dirt bike ramps over the data center Exactly. Back flipping over. Exactly.
Speaker 1:Julie Young shares a trick. This one neat trick that Los Angeles uses to hide oil deckers. We have a few oil derricks in LA that are disguised as synagogues. They are literally just sitting in the middle of the city, Lowell. Surprisingly, people are aware.
Speaker 1:There's a number of data centers that are disguised in Los Angeles as well. Usually, you can tell because there's no windows in the building, but these exist in downtown. Usually for edge computing, for, like, the content delivery network. You put a store in your Netflix videos there, that type of stuff. Not doing training runs, not gigawatt clusters.
Speaker 1:I did look up how how energy intensive Bitcoin is relative to what we think of AI. I think the numbers are OpenAI and Anthropic are around two gigawatts in terms of capacity, something like that. We've heard about the Colossus Data Center. The average Metacamp is around half a gigawatt. Zuck's building something in the one gigawatt range.
Speaker 1:There's gigawatt a week plans. But if you were to put the Bitcoin network current sort of estimates using between a 120 and a 170 terawatt hours per year, what is that in average power in gigawatts? It's between 14 gigawatts and 19 gigawatts. And so that's where you should sort of comp Bitcoin to if you're putting it in AI terms in in in the numbers that we throw around, which are usually like a one
Speaker 2:Before our next guess, Palmer Lucky has been getting into it with someone on the timeline. He says responds to someone named Clifford by saying, dumb tweet, Toto has been fabricating advanced ceramics for semiconductor manufacturing for many years. They make more money from that than toilets. Strong technical moat in a rapidly growing industry. Clifford says, perhaps.
Speaker 2:Fair point. But call me dumb under your real name or s t f u coward. Just like not realizing that he's talking talking about me.
Speaker 1:But isn't Cliff Asness like a big deal? I think he's an author. He's a his papers. I've I've heard of Cliff Asness before.
Speaker 2:That's funny because
Speaker 1:And so it is funny that they just like didn't over oh, he's a co founder of AQR Capital Management, hedge fund manager. Is this the right person? Forbes estimated net worth of $3,000,000,000?
Speaker 2:I believe
Speaker 1:I think this is accurate. I think he he yeah. Global Alpha. He started career in nineteen ninety, twenty Yes. Worked at Goldman Sachs.
Speaker 1:AQR Capital
Speaker 2:the the, like, Anderol
Speaker 1:You just have seen the SVP SPVs or something. Stable asset management and other institutions in the aggregate made commitments of several $100,000,000 to a new multi manager hedge fund. He's published in academics. He's done a bunch of stuff. I've heard of him I've heard of him before, so this is very funny.
Speaker 1:He he runs
Speaker 2:he runs he has he has a he has a AQR.
Speaker 1:Oh, AQR. Yeah. Interesting. Anyway
Speaker 2:Very, very funny.
Speaker 1:I believe we have our next guests in the waiting room. Let's bring them in to the TBPN Ultra Dome. Natomi Wonderco, welcome to the show. Would you mind both kicking us off with some introductions on each of you?
Speaker 13:Yeah. Of course. Hey, Jordy, John. Great to see you both.
Speaker 1:Good to
Speaker 3:see you.
Speaker 13:So Justin Wexler, one of the general partners at Wonderco, working closely with Jeffrey Katzenberg. Yeah. And and you've met all of us. Yeah. Yeah.
Speaker 13:Sujay, Chen Lee, Jeff, Anthony. So it's been an amazing run. I've been with the firm since early twenty seventeen. Cool. And also on the board of Natomi.
Speaker 1:Okay. So yes, please introduce Natomi. Yeah.
Speaker 10:Adam, great to see both of you. My name is Puneet. I'm the founder CEO of Natomi. We are an agentic application tier company focused on the customer experience use case.
Speaker 1:Okay. What what specifically in customer experience? Is that different than customer service or are we doing surveys to understand how companies are and products are being received all of the above? What's the shape of the business today?
Speaker 10:Yeah. We look at customer experience a little bit differently than how most, companies in AI have have looked at this. So if you if you think about it historically, businesses were designed as a sales, as marketing, as customer service Yeah. Because that's how the customer journeys were created and they had to keep those silos to keep cost efficient. But, you know, with, with the GenTeck, now, you know, there's a resource that has become abundant.
Speaker 10:You could apply it through the journey. That's what we are doing. And also, one of the key factors is if you think about traditional customer service, it looks at customer journey, then it says we'll wait for something to break and then fix it after the fact. Mhmm. And then hopefully, we regain that trust.
Speaker 10:We are saying, hey, you got you you can address this upstream. You can address this in digital experiences. You don't even have to wait for the problem to occur. So that's what we are doing and that's why we are excited to partner with, Extension and Adobe in this financing that we just announced and, we're gonna do this for all the Fortune 500.
Speaker 1:Talk about the decision to go with enterprise versus small business. Was it ever on the table to go broader self serve, or is this is there something unique about the technology where you're it's actually more suitable for enterprise use cases right now, or is that just your personal DNA where you flourish?
Speaker 10:Actually, all of the above. So Mhmm. My personal DNA, I I grew up in automated trading, building event engines for for different firms on Wall Street. You're born in the enterprise.
Speaker 1:I like it.
Speaker 10:Born in the enterprise. Exactly. Born in the enterprise, born in low low latency systems, born in event correlation, all of those things that just came together for this. But also we looked at where is money getting spent for this problem. So if you look at this broadly, human capital spend is about $500,000,000,000 a year.
Speaker 10:Mhmm. About 75% of that comes from the world's largest enterprises, literally under a thousand companies. Right? Mhmm. So that's how fragmented the market is.
Speaker 10:And now with, Natomi's technology, you know, you could run the autonomous front office. So when you do that, not only is that a cost efficiency which more than pays for itself, it really transforms the entire company because you can connect all the systems processes right in those agentic flows and then that sanctioned architecture presented safely to your customers. So yes, love that medium to high complexity, love the enterprise complexity comes in the DNA. That's what we are the words best at.
Speaker 13:Yeah. And just to add Yeah. To So at Wunderco, as you all know, we invest in consumer, we invest in different areas of technology, but a big focus for us is enterprise and how enterprise is going to evolve with technology, particularly AI technology. I'm fortunate that I work with Jeffrey who has a lot of great relationships across enterprise and thinking through how to apply agentic capabilities in these organizations is very top of minds. We invested in Puneet actually before this AI paradigm of ChatGPT and everything that we know today.
Speaker 13:And so we've been a little early to this, but knew Puneet's DNA as these advances became more prominent was really the right leader to build for large enterprises. And so with Puneet, we sat down with leaders at Delta, United, MetLife, who have all had huge success deploying Natomi. A big proud moment for us is when the yeah. No. It's it's pretty incredible.
Speaker 13:Anyone could go on the United mobile app and see powered by Natomi interacts with with Natomi. And then earlier this year, OpenAI recognized Natomi on one of the case studies, calling it the blueprint for deploying large scale GenTick AI. So it just had a lot of great moments over the last couple of years. And that's what inspired Puneet and me to really sit down and think about, okay, this has been proven at scale, but what's the coalition around this technology that would really allow it to be in the hands of many, many more millions of consumers? And so that's why this rounds brings together Accenture.
Speaker 13:No one knows enterprise complexity better than them and their seal of approval on this company is is is a huge sign to enterprises that this is what they should be deploying. Yeah. Absolutely. And then with Adobe, the idea with Adobe is, you know, many times chat interfaces sit on top of websites. Mhmm.
Speaker 13:And while it's a step above prior technology, the next generation is going to bring those capabilities into the digital layer itself. So not having the website and then the chat disconnected on top, but fusing these two layers. And the work that Natomi and Adobe are doing together, and we can talk a bit more about it, is going to bring about a gentic digital experience.
Speaker 1:Sure. Tell us about the round. I wanna hit the gong. How much came together for this deal? What's the total?
Speaker 4:Go ahead.
Speaker 10:We raised a $110,000,000.
Speaker 2:There we go. Awesome. Damn. Well, that shook the whole room, John.
Speaker 1:Want to It's a good one. Look
Speaker 3:at this light.
Speaker 10:Yeah. Yeah. We we are we are here to shake the
Speaker 9:room. Fantastic.
Speaker 10:So so yeah. All all focused towards enterprise deployment, all focused towards the last mile of AI. You know, we think AI really needs a big enterprise win that's ROI positive where large companies can go on their earnings call and say, this is what AI did for me. That's what we want to deliver
Speaker 1:for the I entire love it. Well, thank you so much for taking the time to come break it down for us. Congrats on coming together and the progress. It's At
Speaker 2:this rate, I'm sure you'll be back on this year.
Speaker 1:Yeah. We're excited. We'll talk
Speaker 3:to you
Speaker 1:all soon. Have a great weekend. Have a great rest of your day.
Speaker 2:Talk soon.
Speaker 1:Talk to you Thank you, Jared. Goodbye. We have an update from the chat. Cliff Asness has been on Patrick O'Shaughnessy's Invest Like the Best. You know who else has been on Invest Like the Best?
Speaker 1:Palmer Luckey. They both been on the same podcast
Speaker 2:I'm back on.
Speaker 1:Didn't know about each other. They got to do a crossover episode. Back to back. If you're looking to get up to speed on both Palmer and Cliff Asness, head over to Invest Like The Best with Patrick O'Shaughnessy. Can listen to both episodes.
Speaker 1:Although Cliff was on in 2018, almost a decade ago. He's got to go back on. Set the record straight on who he knows, who he doesn't know. Anyway, there's there's more debate over the data center thing. Some very cool renders, some very cool ideas.
Speaker 1:I think the the the problem is is that the the the the plans are delayed, plans are set years in advance. Any any move to actually make data centers beautiful is gonna take a long time. Hopefully
Speaker 2:Yeah. This this feels like one of those things where
Speaker 1:make them better. I don't
Speaker 2:Data center operators would would say, I would love for my competitors to focus on making their data centers beautiful
Speaker 1:Yeah.
Speaker 2:And really make that a part of their strategy. While while the the Zucks of the world, you know, throw up like REI tents throwing GPUs.
Speaker 1:Exactly. People will do the minimum viable beautification potentially. But Dan Lincoln Harris has some comments here. Love that we are having this conversation. The questions that flow from Josh comment are why and what we should aim towards.
Speaker 1:These should be places of wonder that we can marvel at, modern cathedrals for the silicon age, not to worship them but to stoke our aspirations. Square gray boxes do not inspire. Speak for yourself. I like a square gray box every once in a while. Given the epicenter of this technological revolution was California, the light and space movement seems a fitting direction.
Speaker 1:James Terrell is the is the most well known for this movement. And he shares some James Terrell images which are absolutely beautiful. Good inspiration if you're a data center builder. You can also just throw some trees, do some AI imagery here perhaps. People wouldn't be so against data centers if they were building the style of the elf city Rivendell.
Speaker 1:That's kind of cool. Greco futurism. They do look cooler this way, but it looks a lot more expensive than just some walls. Who knows if This you will see any
Speaker 2:video.
Speaker 1:Progress. What?
Speaker 2:Justin, skin exams are getting automated. Oh, yes. Sis is a very cool product.
Speaker 1:Okay. Break it down for us. Let's pull it up.
Speaker 2:We have video here. Yes. You have a pen I or think anybody that's been to a dermatologist Mhmm. It's like looking for potential, you know, skin cancers, things like that that abnormalities has had the experience of like the, you know, like when you're you know that video or the meme where the the guy's like walking through security and the and the security guys just like, you know, does this like really Yeah. Yeah.
Speaker 2:Yeah. Yeah. Yeah.
Speaker 1:I know what I mean.
Speaker 2:It's like that's basically what like a lot of dermatologists are doing where they just like take a quick glance and they're like, oh yeah. Look look looks good.
Speaker 1:Yeah. They might be busy. They might be sleeping.
Speaker 2:Back in like a couple years. But this robot It's a robot that just does it like really really precisely
Speaker 10:They're
Speaker 2:consistently, ideally, hopefully hopefully a lot more accessibly. I can see this making a lot of sense. And then you actually it doesn't even replace the job of the doctor. It helps them speed up the process.
Speaker 1:Where is this company? What stage are they? Do they have to go through FDA medical device approval process? That could be a couple of years maybe. But this seems like once you get it through, it's gonna be massively successful.
Speaker 1:I wonder I wonder where they are in the FDA process. Hopefully, they can move along quickly. Ark Prize put out an update on Ark AGIV three which Tyler, are you still on the human leaderboard for that? Or
Speaker 5:I don't think I'm on the leaderboard That was still early on. Like, I think there's actually more games
Speaker 1:now. Roasted. Well, Arc AGI v three has been very tough for even the most frontier AI models, but the good folks over at ArcPrize have benchmarked the two latest and greatest AI models from OpenAI and Anthropic. GPT 5.5 scored 0.43%. Opus 4.7 scored 0.18.
Speaker 1:It is it is state of the art. This is the weird thing about these these ArcGI tests is that they they start with such a low baseline, 0%, 1%, and then they start they start shooting up as the models get more capable. But it is very interesting and reassuring to see these powerful models that you sometimes hear these narratives. It can do everything. And then there's something that, you know, to continue working for, to look forward to in the future.
Speaker 1:There's more applications here. And so they found three total failure modes, true local effect false world model, wrong level of abstraction from training data, solved the level but didn't reinforce the reward, and so the ARC Prize account goes through a little bit of what's going on when an AI model tries to play ARC AGI v three, which is basically a two d video game, Simple enough for any human to progress through, but increasingly difficult for AI models.
Speaker 2:Okay. Yes. We gotta talk about one of the most exciting new products created
Speaker 1:What's that?
Speaker 2:In the last hundred years. Tell me. According to Katie at Business Insider, Amazon will now create an AI podcast Yes. About their products where two AI hosts discuss the products and take your questions as if it's a call in show. Yes.
Speaker 2:Let's play
Speaker 1:We don't need to play this one. This one is so rude but you can imagine the type of products that people are generating AI podcasts for. Only the silliest things will be generated. I don't know if people want to listen to a full podcast about every product they buy on Amazon but you have had some very opinions about paper towels. You wanted paper towels from like the nineteen fifties or something.
Speaker 1:Remember this whole thing? You didn't
Speaker 2:I just wanted a filter to be able to buy only shop for things on Amazon.
Speaker 1:Well now instead of a filter, you can listen to an hour long podcast about every possible SKU, and then you can make the most determined decision available. Well, we have Alex from OpenAI. He's a member of product staff here to talk about Codex and GPT 5.5. I believe he's in the waiting room, so let's bring him to the TBPN Ultra. Alex, how are you doing?
Speaker 4:Hey. Doing great. How are you guys?
Speaker 1:We're doing fantastic.
Speaker 2:Close to the camera. You make me wanna you make me wanna scoot up. Some people come
Speaker 1:on and it's standoffish.
Speaker 2:Yeah. It's just like a little bit of a There
Speaker 4:we go.
Speaker 2:No. You're locked in. You're locked in.
Speaker 1:Okay. So give us some updates on Codex. I mean, we've seen some crazy numbers. Things seem like they're going well. But what I'm most interested in is applications, usages, just as I'm talking to friends and folks that are outside of the most intimate tech community, what are the magical experiences?
Speaker 1:What are the prompts, the usages that are seeing adoption? How should people even be thinking about Codex and ChatGPT these days?
Speaker 4:Totally. I mean, it is such an exciting time. I feel like last year was the explosion of agents for coding.
Speaker 1:Yeah.
Speaker 4:You know, now we bring it to to everyone else. Codex now is becoming this, like, amazing tool for just, general work or, honestly, anything you can do on your computer.
Speaker 1:Yeah.
Speaker 4:So the model launch, was it was that only last week? I think it
Speaker 1:was last week. Think it's
Speaker 2:really fast. Really feels like a month ago.
Speaker 4:Yeah. Yeah. Honestly, I lose track of time but like, you know, API revenue for that model is growing two x faster than any prior release. Like Codex revenue actually doubled in the last week.
Speaker 1:I see.
Speaker 4:So it's just like the the growth is insane.
Speaker 1:Yeah.
Speaker 4:And what's cool is that, obviously, the growth in usage and the way people are using Codex for coding is is just like getting way better. But I think if this is kind of what you're asking for, there have been we're we're making Codex great for everyone. That's all the way from like what the agent can do and also just like how simple it is to use. Yeah. And so now we have, you know, Codex being used by like salespeople, marketing people, finance people, data science people, whatever you have whatever you're thinking.
Speaker 4:Yeah. It's like 85 of the company uses codecs and we're seeing this happen outside as well. So, yeah. I'm happy to jump into some fun use cases if you want.
Speaker 2:I wanted to ask about like how you feel the the perception around computer use has been. Mhmm. Like, it felt like there were so many things that that got released at one time that that kind of was quite magical and you see some posts popping up here and there, but do you feel like that's getting the attention that it that it deserves now?
Speaker 4:Yeah. I mean, like, so broadly what we have is we have this amazing amazing agent that can write code and if wanted we to do more work than just coding work, it needs to be able to do anything you can do on your computer. And so computer use is this big step because it's like, hey, well, now it basically can do anything you can do on your computer. But the magical part of computer use and that the team really cooked here is that it can use applications in the background. Mhmm.
Speaker 4:So, you could be doing something in one app and the agent can be doing something in another app and that's important because
Speaker 1:it means
Speaker 4:you can actually delegate Yeah. Which means you can give the agent hard tasks that take us some time to do. Yeah, So, mean, reception around that was actually awesome. I I thought we got people noticed sort of just how hard and magical that is more so than I even expected. So, yeah, we've been really happy with that.
Speaker 1:Yeah. I I I've noticed that codex puppeteering a mouse cursor has gotten good. It feels like it crossed some sort of like touring test where when I see a video of codex moving a mouse around, it doesn't read to me like, oh, that's a jittery that like the AI is using It just looks like, oh, somebody just recorded themselves moving the mouse. Is there a benchmark? Is that is that something that just comes from the new model or work that's being done on Codex?
Speaker 1:Like, what is going on with the the progress
Speaker 2:to the Sky team Yeah. Of acquisition. Yeah.
Speaker 4:So there's kind like three things going on there. Like, first of all, GPT 5.5 is our best model ever for like general work or knowledge work. Yeah. And so it's really good at using computers. The next thing is, well, what harness do you give the model or, like, what information is the model seeing and, like, what tools does it have to use the computer?
Speaker 4:A lot of early versions of giving a model access to a computer were just giving it screenshots of the computer. But there's a lot of secret sauce in our implementation where the model actually gets text representations of what's on screen from like frameworks like accessibility. Sure. And so the model is like much more efficient when it has access to all this information. Oh, that's interesting.
Speaker 4:And then the last bit that I I honestly think I well, don't know if I would say it's underappreciated because I feel like people really appreciate it, but it's the level of craft that was put in to how it feels when the agent is using the computer. So, for instance, you could totally just have the agent, like, click around on your screen and just have that be invisible and and, you know, you wouldn't even it's just like the computer is updating as clicks happen. But the team put a ton of care into, like, exactly the animation that this, like, mouse cursor takes as it goes between the different click positions. And, yeah, it was it was really fun to talk about that and jam on that with them. Like, we actually made some interesting trade offs.
Speaker 4:Like, having this animation actually slows down how quickly the agent can work by just a tiny bit.
Speaker 3:Mhmm.
Speaker 4:But it means that it's so much easier as a human for me to understand the system and therefore to trust the system.
Speaker 1:Yeah. That's interesting. That that sort of goes back to I remember the the initial ChatGPT app launch on iOS had haptic feedback as the token streamed in. And so it felt like it was typing. And that could have easily just been generate the full response, give you a little waiting wheel and then boom, it loads like a web page.
Speaker 1:Like when I go to, you know, The New York Times, like the whole page loads. It doesn't stream in. But that streaming made it feel more like a conversation. Those little like UX queues help like create this more like interactive motion back and forth. That's very interesting.
Speaker 2:Gordy? Someone's trying Codex Yes. For the first time. What are you've got one minute to explain the three things that they should do to get the most out of it. What do you tell them?
Speaker 4:Okay. Cool. Is this person an engineer or are they like a knowledge worker?
Speaker 1:Let's say you're not an engineer because I feel like
Speaker 2:Well, no. Let's do let's do both.
Speaker 1:Sure. Yeah. Let's start with engineer.
Speaker 4:Okay. Start with engineer. If someone's using Codex for the first time, I just say download Codex, attach connect it to your project, whatever you've been working on Yeah. And then ask it a question about your code base, like a hard architecture question, and it's just gonna give you an amazing answer. Yeah.
Speaker 4:Then the next thing you do is you say, cool. Like, give it a bug that you've been trying to track down and ask it to solve the bug. And, like, I hear this all the time, like, on Twitter, etcetera, like, people will be like, hey, I was trying to solve this bug myself, couldn't do it. I gave it to, like, all the other coding agents, they couldn't do it, but Codex could do it. Yeah.
Speaker 4:And then maybe as a final thing to, like, experience a little bit of the magic that has shipped in the last week or two, if you're working on, like, something that's, like, has a web view, like, maybe a website or something like that, ask Codex to make a change and then, like, watch it just, like, iterate on that change by opening the in app browser and sort of observing its outputs, clicking around, and then, like, naturally just, fix and improve the change that it made. It's, like, it's super magical because you just realize when you see it, like, work in that loop, you just realize how powerful it is now.
Speaker 1:Okay. Speaking of loops, explain Ralph loop, explain slash goal.
Speaker 4:Okay. So basically, we've had this interesting thing for a long time where people this is like months ago. People would tell us that they knew that Codex was super powerful, but it felt annoying to work with because they had to like constantly tell the agent, you can do this. Keep going. Right?
Speaker 4:So you have this like brilliant model, but you have to like encourage it constantly. We then shipped a feature called queuing, which you can use to give the agent a message that it will, like, receive whenever it thinks it's done. And people use that to say, do this, then do that, then do that. But actually, a lot of people started using that to just say, keep going. So, like, they would just queue, like, 10 messages, like, keep Keep going, keep going.
Speaker 2:Yeah. Exactly.
Speaker 4:And now at this point, we have these amazing models that if you know how to use in the right way, you can have them do hours of work or even days of work, just like independently, autonomously. However, the average person doesn't necessarily know how to do that. You have to do like all this contrived harness setup, and so with Goal, which is a feature that we shipped into the command line interface and will come to the app soon, we wanted to make that super easy. So now you could basically describe to like, hey, like, I want you to keep going until you achieve this goal, and then Codex will just take care of working for however long you need until you can do that. And so internally, this is something that people have been really excited for for a long time when we do a lot of like long running work.
Speaker 4:So for example, when you're like babysitting like a training run for a model, you don't want to just like tell Codex to do something and then have it return in five minutes. You actually want it to pay attention like all night. Mhmm. So that's what that's what goal is. Do you want yeah.
Speaker 4:Go ahead.
Speaker 1:I was wondering about the like, what is for for the non engineer use case, the thing that gets you to move from ChatGPT to Codex, like the first the first the first, like, more complicated query, more complicated project that you would recommend someone say, oh, yeah. Like ChatGPT can do a decent amount of research, but for this, you should spin up Codex and and and start working with that as your primary workflow. Like, what is the entry point? What is the the appetizer into the Codex workflow for someone who's nontechnical, not writing code, wouldn't mind if code was written behind the scenes, but really just is interacting with typical knowledge work suites. So email, spreadsheets, Word docs, generating graphics, research.
Speaker 1:There's a lot of stuff and ChatGPT satisfies a ton of that. And so when are they jumping over to Codex?
Speaker 4:Yeah. So I kind of think about the way that you can do general work with Codex. There's maybe three categories of work that's like, just very easy tasks. Mhmm. And that's not to dismiss those.
Speaker 4:Actually, most of my usage of Codex is like easy tasks. Mhmm. And those are the first things you should try. Then there's like hard tasks that are like really cool demos, but actually, if you start to do a hard demo, you might you might just, like, waste a lot of time. Yeah.
Speaker 4:And then there's automating. So you everyone should kinda go through this progression. It's, like, easy, hard, automated. Yeah. And if you think about it, it's kinda like a human teammate.
Speaker 4:Right? Like, you hire someone onto your team, you know, you don't usually well, maybe at OpenAI we do it. You don't just say, like, hey, just, like, figure out what you wanna do. Maybe what you do is you say, hey, like, why don't you do this, like, small starter task or something, and then from there, give them a harder and harder task, and then eventually you say, okay, just like go figure it out and work automatically. Mhmm.
Speaker 4:So, okay. Easy tasks. The thing I always recommend people do is, like, wherever your company works at OpenAI, that's Slack, maybe for you it's Teams or it's email, connect Codex to that tool and then just ask it like, hey, like, am I missing any urgent like, do I need to reply to anything urgently? Just, like, draft some answers for me. Or maybe, like, I get tagged on these really long threads all the time.
Speaker 4:It's like, hey, just summarize this thread. What am I supposed what am I being asked, and what should I what what should I answer? You know, just ask these, like, these questions. Or maybe someone mentions something you don't know what it is, and you're just like, hey, search all my company information and tell me what is x y z, you know, the thing. So those are really basic, easy queries that Codex is amazing at, and I have found that even though those may not sound that hard, people just get hooked on doing that all the time, and then from there, once you're hooked, then you kind of become fluent in using this tool to answer any even small question.
Speaker 4:Use it for harder things. So, for example, one of the use cases that I do a lot that tends to, like, really get other people excited when they see it is I you know, we we don't like meetings. I try to keep meeting attendees to a minimum here. So, often, instead of adding people to a meeting, I'll post in a channel and say, if anyone wants to talk live about this, just reply. And This is something I used to do, you know, before, but now what I do is I I tell Codex, post in this channel, see who wants to join, and add anyone who wants to join to the meeting.
Speaker 4:Sure. Super basic thing. Right? Yeah. But the fact that you can ask an agent to do a thing and then monitor that post.
Speaker 4:Mhmm. And then, like, just keep it up to date Sure. Is actually really powerful. And then when people reply to the the post and then the the agent replies back saying, like, cool, you're in the meeting. It's at this time.
Speaker 4:Here's the link. Yeah. That always mind blows people. Yeah. And then you start people start trolling, you know, people like add spam to the meeting.
Speaker 4:Oh, yeah. The agent knows not to.
Speaker 2:Yeah. That's just like functionally what what if you're lucky enough to have an EA, you get something like that where it's like, hey, I need to get this thing done. I'm gonna kinda set it. I'm gonna I I wanna set off the process, but then someone else monitoring it, kinda backfilling it.
Speaker 4:Yeah. I think any any work that requires, like, a lot of work, like, a lot of time from you but is not hard, those are good starter tasks. Same for, like, managing tasks, you know, tracking issues coming out of a bug bash. For, like, pre launch, we do this thing where I'll have Codex monitor a bunch of channels I'm in with internal and external users, and I'll just say, hey, if anything comes up, put this in in linear, which is where we track our bugs Mhmm. And, like, make sure it's deduplicated, and then let people know that we're tracking the bug.
Speaker 4:So, you know, very very simple task, but actually incredibly useful time wise. Last thing I'll say on this Automation.
Speaker 11:We have executive
Speaker 4:assistant kind of like plug in internally that I would love to ship externally. Mhmm. We should get on that. And it's really taken off internally. Like, people basically have this thing that is, like, keeping track of all their information and just, like, helping them organize their day and, like, stay on top of things.
Speaker 4:It's it's pretty cool.
Speaker 1:So then, yeah, talk to me about automation because I I I understand from integrations and computer use how a single prompt could go into Slack or go into your email or pull some documents together, write code, do whatever it needs to on the Internet, APIs. I understand all that. But then what is the workflow to get Codex to do something every morning at 7AM to prepare me a digest or take the same actions to really get rid of that rote work that I've demoed and I've seen the results. It's working. And now I just don't want to think about it ever again forever.
Speaker 4:Yeah. I mean, it's it's honestly super simple. You just tell Codex, hey, do this every morning. There
Speaker 1:we go.
Speaker 4:Right. Well, like, in my case Yeah.
Speaker 2:Mean, that's kind of an interesting thing with these kind of products that have effectively unlimited potential. It's like, where's the line between like a feature and just a prompt? Yeah. And when when should as a company, when should you just launch something and make a big moment out of it? Or when should you just let people just understand the full potential of it?
Speaker 2:And then when they want something, they can just ask it. Right? They don't need to, like, request a feature. Yeah. It's just, like, literally just request it Totally.
Speaker 2:With the agent.
Speaker 4:It's really interesting as we design the product. Like, I like to think that we need to keep sort of all the rules and, like, sort of the heavy UI and stuff around the agent to a minimum because it kind of constraints Mhmm. How much better the product can get when we have a smarter model. So the more things we can kind like, let the model decide, you know, it's like it's AI soon, AGI, the better. And then sometimes you just need UI so that people can learn that this thing exists.
Speaker 4:But even that, the model can suggest things. So I'll I'll give you the the most powerful, I think, example of a use case I heard recently was this person on the growth team needs to figure out, like, what experiments to run, and then they need to write code to run the experiment, and then they need to analyze the experiment. And it turns out they were use they started using Codecs individually for each separate thing. So they would have it, like, run a bunch of analyses, they would sort of interrogate the data. They would just talk to Codex about the data.
Speaker 4:And then they would pick an experiment and then they would, like, write ask Codex to write the code. Then they would run the experiment and then they would ask Codex what the results of the experiment were and then they would, like, produce a deck. Right? So all steps they were doing individually, and they they didn't start by saying, I'm gonna automate this entire thing because that's like hard and scary. Right?
Speaker 4:They just started with using codecs, like, accelerate themselves, individual productivity for each task. Then they started basically connecting all these things together into a giant skill and then one day, they just said, hey, why don't you do this every morning? And they gave it a name, it's called Lord Bottleneck because it's like solving the Mhmm. Bottlenecks of, like, friction for new users. And basically, this is the thing the team does now, every morning, Lord Bottleneck evaluates past experiments, looks at data, looks at new things, proposes some experiments, and offers to the team like, hey, like, let's run these experiments.
Speaker 4:The team, like, picks, like, let's do this one or that one. Then Lord bottleneck is like, okay, cool. Here's some code or whatever config that needs to be done, runs the experiment, and at the end, they, like, they go and do the same loop the next day and analyze the results. And so that's actually, like, really serious value in automation that's, like I forgot the numbers, but it's produced, like, you know, significant company value just automatically through codecs.
Speaker 1:How are you thinking about game development? It feels like all of these tools are super useful and could really accelerate game development.
Speaker 2:Especially with images too.
Speaker 1:Totally. I think there was a time when like everyone had an idea for a meme but not everyone knew Photoshop. Now everyone can go and use images in ChatGPT to sort of make the exact meme that they want very quickly, very easily And there's this takeoff in like everyone can create the thing. Now everyone can vibe code a Python script pretty easily. And it feels like the next thing is like going and shipping something.
Speaker 1:And we're starting seeing these like simulators and these little one off like web games. It's still a little bit like prosumer, I would say. But is this something that you think just is like a natural outgrowth or something where you might actually spend some cycles thinking about that as a particular, like, workflow?
Speaker 4:Yeah. I mean, I think I'm really just excited about how easy it's becoming for everyone to bring their ideas to life. ImageGen you you bring up ImageGen. That was actually a really big deal Yeah. In a way that I still think people don't really realize.
Speaker 4:Like, having an agent able to just generate images as it's working is massive. Yeah. I mean, ImageGen two in itself is actually really popular and is great even outside of Codex. Like, I think let me see here. Yeah.
Speaker 4:Like, I think we are like, people are making, like, 50% more images with ImageGen two just, like, a few weeks after launch than they were before. So it's, like, really taking off and it was already popular. But then, with ImageGen, we see all these cool use cases where people will have the agent let's say, we'll take a development and a non development use case. For development, they'll have it, like, build a bunch of sprites. Sprites is like a term for, like, the image that you use in your game.
Speaker 1:Yep.
Speaker 4:So for so, like, one cool example of this is, like, in the GPT 5.4 blog, we have some example prompts to try, and one of them is, like I forget. It's it's, like, build, like, an art roller coaster simulator or arcade simulator or something, and you can just copy paste that prompt into Codex now and it it's it's just like even better because Codex will like create all the assets for the game using ImageGen and then like build a game using it and then play the game for you to test it in the in app browser. So, yes, this is happening very naturally and I suspect it would be quite interesting to lean into it to make it even better. Yeah. A cool, like, non non coding use cases, we're seeing people use ImageGen to create slides or, like, slide templates
Speaker 3:Yeah.
Speaker 4:Or assets go on slides and then produce the slide deck, which again, you can iterate on just inside the Codex app. Interesting. Yeah. Image images are massive for us.
Speaker 1:Yeah. Yeah. That makes tons sense. Jordan, anything else?
Speaker 2:No. This is great. Yeah. Appreciate the update. I'm sure you'll there will be more news this time next week.
Speaker 3:Yeah. We're we're
Speaker 4:thinking about like how many Thursdays can we ship in a row, you know, like
Speaker 3:Yeah. Well,
Speaker 2:the more the more you ship, the easier it is to ship. So it's a it's a good feedback loop.
Speaker 1:That's fantastic. Thank you
Speaker 2:so much for taking Great to see
Speaker 4:Thank you.
Speaker 1:We'll talk to soon. A great weekend. Goodbye. Should we show show everyone the game that we made? Should we show everyone TBPN simulator?
Speaker 1:Do we have that pulled up? Can we play that? Would would now be a good time? It's a late might
Speaker 2:not have enough time.
Speaker 1:We we can have them pull it up while we while we read through
Speaker 2:the Let's pull up this packaging of the neo robot over at one x.
Speaker 1:The Neo robot over at one x.
Speaker 2:Have you seen this?
Speaker 1:Oh, yes. They got
Speaker 2:a suitcase
Speaker 1:got a for suitcase is remarkable. Let's pull this up.
Speaker 2:This packaging is so cool.
Speaker 1:Aesthetic. This warm tone. It's it's welcome.
Speaker 2:I gotta say it's really cool until it's 2AM and you hear a shaking in your house and you go and you turn on the lights and this little like, you know, suitcase thing shaking and then Neo pops out and I and goes Terminator mode. I wouldn't know what that what that actually is like, but I'm
Speaker 1:gonna watch Terminator this weekend and report back. Ridiculous. Wow. Amazon, Google, Microsoft, Meta collectively are spending more money than the Manhattan Project every single month. That's insane.
Speaker 1:Wow. Wild. Anyway, in the mansion section, there is a record breaking home in Los Angeles with a question. Will a Los Angeles area mega mansion become America's most expensive residential property? $400,000,000, they're asking.
Speaker 1:70,000 square feet. The the guesthouse is 30,000 square feet. It's absolutely insane. 39 bedrooms, eight acres, three pools. It has an x-ray machine.
Speaker 1:This is in the mansion section of the Wall Street Journal. Fascinating because Tyler was unimpressed. And I was wondering like what could possibly be better than a $400,000,000 mega mansion in Los Angeles but you found something. What what absolutely
Speaker 5:Well, I was comparing it to, you know, some kind of palatial manner. Right? So clearly it's like Versailles. Yes. Versailles, you know, 10 x bigger.
Speaker 5:It's like it's like 700,000 square
Speaker 1:feet. 700,000
Speaker 5:indoor space. Obviously with the gardens, it's like millions of square footage.
Speaker 1:Millions of square footage.
Speaker 5:Getting brutally mogged.
Speaker 1:What about on bedrooms? This one has 39. You certainly can't go higher than 39 bedrooms.
Speaker 5:I think it would yeah. 2,300.
Speaker 1:2,300?
Speaker 2:Oh, no. No.
Speaker 5:That that was just rooms actually.
Speaker 1:That was rooms. Okay. So not all bedrooms. But I mean, if you need a buddy who crashes, like they can crash in any room. Right?
Speaker 1:Like, you know, have you ever slept in a kitchen? You've never had we don't have any room.
Speaker 2:I don't know I've ever
Speaker 1:slept You gotta sleep in the living room. You gotta sleep in the dining room. Lucky.
Speaker 2:Alright. Let's pull up the trailer for TBPN Simulator.
Speaker 1:Oh, have a trailer.
Speaker 2:Yeah. We got the trailer.
Speaker 1:Oh, let's go. Let's watch this.
Speaker 2:I think TBPN needs a game.
Speaker 1:Yeah. We definitely need to build some sort of game. This this project has evolved so so much to the point where you can move the goal posts. I don't know that you can interact with a horse. You can definitely hit the gong, and then any team member is now playable.
Speaker 1:Okay. Oh, wait. So there is a mechanic. You have to gain the most subscribers. Interesting.
Speaker 1:Yes. You have to puzzle piece everything. You can watch the stream in the game. You can explore the UltraDome. It's a full Backup.
Speaker 1:Replication. Tbpnsimulator.com. That's sloppy. That was image gen
Speaker 2:one. Image
Speaker 1:Image gen two would never do that. But but can we pull the actual game up? Oops. Hopefully.
Speaker 2:Yeah. Here it comes.
Speaker 1:Let's see. Pop up. If we can pull up the actual the actual game. Let's let's see. There's a whole bunch of stuff on here.
Speaker 1:Okay. So this is TBPN simulator, the latest and greatest version. A remarkable how Ben, how did you actually get this? Like the geometry in here? Was this all described via prop?
Speaker 2:We got intern Ben here to
Speaker 1:Yeah.
Speaker 2:Talk.
Speaker 7:Yeah. So basically the whole process is kinda like I'm like, okay, look at that wall right there. Yeah. I need that to be taller. Place a desk right at that wall.
Speaker 7:So the whole idea was that I How interesting. Single object so I was able
Speaker 4:to like talk
Speaker 1:Is there someone else in the game? Wait. It's multiplayer? It's multiplayer. Wait.
Speaker 1:So we're getting other people in the game right now. Oh, no. People are coming in. There's Mark. Tbpnsimulator.com.
Speaker 1:I can't believe it's a multiplayer. I can't believe you created a multiplayer game. Okay. So we got the bathroom. Okay.
Speaker 1:This is incredibly What's that? No. No. No. No.
Speaker 1:Get out of there. Get out of there. Okay. So there's a chess board which was gifted to us.
Speaker 7:Ring the gong. You can ring the gong. To the actual studio.
Speaker 1:Okay. Oh, gong And cool then those are the Yeah. Photos that we take. And there's the UltraDome.
Speaker 7:It's a one to one lidar scanned measurement. Did
Speaker 1:you wait? Did you actually lidar scanned it?
Speaker 7:I lidar scanned it.
Speaker 1:We know. Yeah. Okay. Yeah.
Speaker 7:The measurements and you can play as any character. So yeah.
Speaker 1:Yeah. Okay. So what yeah. What does it take to to make it in TBPN simulator?
Speaker 2:Camera cut. Yeah.
Speaker 1:Okay. So you're watching the show and you need to cut between oh, so you get a current queue and you have to cut between different queues on at the right time to produce the show live. Okay. We have Tyler. We have Mark in TBPN simulator.
Speaker 1:Okay. What else can you do here?
Speaker 12:How much activity? Like 35% of Is this from yesterday? Yesterday.
Speaker 1:Oh, this is yesterday's show. Building playing currently. Okay.
Speaker 4:So they're using the wallet
Speaker 1:And and if you're Jordan
Speaker 12:example like
Speaker 1:You play as you have to do a mini game which is Guitar Hero but with soundboard basically. Is that the game? Let's hear. Overnight success. Friendly IPL inbound.
Speaker 1:So you have to you have to hit the soundboard at the right time as the blocks come down. Okay?
Speaker 12:Things like
Speaker 1:I think I was doing some ad reads for a while. There's a gong, of course. We're really packing that ultra dumb. We'll see if this thing has high throughput networking. You can play as the guest.
Speaker 1:What do you play as the guest? You just see what it's like to be a guest on TBPN? Okay. You get someone's moving the goalposts. Okay.
Speaker 1:We got a new definition for our goalposts. These are general intelligence.
Speaker 4:I didn't realize that.
Speaker 1:Yeah. The chat has joined the the game. Oh yeah. Someone says make it a Roblox game. This does have some Roblox aesthetics but this is not.
Speaker 1:This is vibe coded. And so this is creating the daily newsletter. You have to stack the different blocks, the strips. It says, perfect alignment published clean. That's Brandon Garell's job.
Speaker 1:Nick has to, of course, fix the schedule. Get everyone to come together. We're watching some Tetris.
Speaker 2:Calendar Tetris.
Speaker 1:You're trying to calendar Tetris fit. How are you gonna get Patrick Collison and Brian Chesky on the show with Alex Karp and Mark Benioff all at the same time. How will you do that?
Speaker 2:Paul Kugen.
Speaker 1:There we go. And then this is is Tyler organizing the show, figuring out how to get different posts into the show. Okay. Oh, here you go. You're moving the different oh, you're jammed up there.
Speaker 1:You're jammed up there. You got to keep working on that. What else is this? What is Jackson up to? Making cards?
Speaker 1:What are we doing here? What? Oh, whack a clip. Okay. The timeline sniper.
Speaker 1:There's breaking news. You got to ramble. You don't want to cut that. Okay. You to hit the good hot takes at the right time.
Speaker 1:That is fantastic. I cannot believe the number of mini games here. This is insane. What a remarkable oh, this is me. Okay.
Speaker 1:So I have to read different phrases. It's a typing game. Because I have to read without a teleprompter. Live from the TBPN Ultradome. Uh-oh.
Speaker 1:Someone's typing Phrase deck. Okay. Well, we got a whole bunch of people. You can go enjoy it. Hopefully, are playing TBPN simulator all weekend long.
Speaker 1:Yeah.
Speaker 2:Yeah. Expect people to put up.
Speaker 1:I mean, if you're launching a TBPN type show, this is a great way to get your reps Get
Speaker 2:some practice.
Speaker 1:Get some practice in before you Until go we get
Speaker 2:our mastermind.
Speaker 1:Yeah. It is it is the path of financial freedom for a lot of folks. So we recommend it. We endorse it. Get your reps in on tbpnsimulator.com, and we will see you on Monday.
Speaker 1:Anything else, Jordy?
Speaker 2:Is it actually live?
Speaker 1:I think it's live. Yeah. Wow. Oh yeah. People are in there.
Speaker 1:They're playing some TV
Speaker 2:We gotta the the slop images. One more time, guys.
Speaker 1:A lot of this
Speaker 2:Incredibly well done, man. Like Our
Speaker 1:first video game Truly
Speaker 2:shipped. Anywhere and
Speaker 1:People are asking for a wave pool.
Speaker 2:That's true. We do need a wave pool.
Speaker 1:We don't have a wave pool in here. Well That's not a simulation. But
Speaker 2:we if if we make it in the simulator Yeah. It's probably increases the likelihood. I
Speaker 1:think I think the key is you have to be able to sit down on one of those and play an even rougher version of TBPN simulator two layers deep.
Speaker 5:That's how you simulate Ben.
Speaker 1:That you know, no. Yeah. Yeah. Yeah. When you simulate Ben, it should go into a two d version top down low even lower graphics pixel art.
Speaker 1:Yeah yeah. A pixel art version of TBPN simulator two layers deep and we can see how how how deep we how deep the whole the rabbit hole goes. But will you break out of the matrix? We certainly hope you do this weekend. Go enjoy your weekend.
Speaker 1:Enjoy your Friday. We will see you on Monday. Goodbye. Love you. Flashbang.