TBPN - IBM Nukes, Demis Govt Plan, Paramount WBD Deep Dive | Dylan Byers, Noah Schochet, Saam Motamedi, Ioannis Antonoglou, Jack Dent, Evan Burns & Jamie Seltzer, Tyler Page

Starting point is 00:00:00 You're watching TVPN. Today is Tuesday, July 14th, 2026. We are live from the TBPN Ultradone. The Temple of Technology, the Fortress of Finance, the Capital of Capital. Let me tell you about ramp.com. Time is money. Save both.

Starting point is 00:00:17 Easy use corporate cards, bill pay, accounting, and a whole lot more all in one place. IBM is absolutely nuking. The stock is down 25%. Let me see if I can pull this up. I got it. Boom. IBM. Well, that is a crazy chart.

Starting point is 00:00:30 the one week chart. It looks better on the five year because the stock is actually way up in the AI era since the launch of ChatGPT. IBM has done really, really well. The stock has basically doubled since the introduction of ChatGPT during the AI era. You know, are you going to be a winner or a loser? Are you going to get steamrolled sloped, something like that? But it's been doing well up until today when the company reset the narrative around their

Starting point is 00:01:00 their server business specifically. So the high-level reason that IBM is not well-positioned in the token path to use the Brad Grosner and Gavin Baker Parlayens is that AI spending is currently flowing into GPUs, memory, networking, hyperscale cloud computing, and frontier model inference. IBM is not a major winner in those categories. So just to refresh on IBM, because it's interesting business with a great name, international business, machines. The first business machines they made were punch card systems.

Starting point is 00:01:36 They made clocks. Like, it's like you're running a business. You need a great clock. You're going to need a clock. You're going to need a clock. Not just any. Not just any clock. Like a clock that works really well.

Starting point is 00:01:45 That's right. Professional clock. Clock Pro Max. Exactly. Clock Pro Max. It's lighter, thinner. It's the lightest, thinnest, best looking fast as. You don't want a fast clock.

Starting point is 00:01:58 But tab. regulating machines, basically a bunch of different ways to process information mechanically. And that foundational insight, you know, was pretty simple. It was businesses will continually pay forever to automate record keeping. And at a high level, that's sort of been working forever. And they're continuously doing it. You know if they ever tried to sell a clock as a SaaS product, time as a service. Hmm.

Starting point is 00:02:25 If you really, really squint Red Hat Kubernetes, it's. keeping time between distributed systems, maybe there's something there. But when you're running a database across a bunch of different servers, there's some timekeeping aspect that's important. But no, I don't think they ever did. The IBM, the people know, the mainframe business, that started in 1964, System 360. It was a compatible family of devices, which is interesting. It's not just one, people think one mainframe, but it was actually a whole bunch of different systems that you can upgrade piecemeal without redesigning the entire workflow. So you need a little bit more storage. You upgrade that. You need a little bit more compute. You upgrade that. And this

Starting point is 00:03:06 turned IBM into the dominant supplier of corporate computing banks, insurers, airlines, manufacturers, governments. They all used IBM as the central system for their hardware and software. This was the mainframe era. Then, and the whole reason that IBM in particular became dominant in mainframes was they focused on high reliability, long customer relationships, expensive switching costs. It's very difficult once you're in the IBM ecosystem to weed your way out. proprietary software tied to the hardware. Certain software would only run an IBM hardware so you couldn't re-platform.

Starting point is 00:03:42 You had to rip everything out, which is very difficult for a large bank or a large airline in the 60s and 70s. Good for business. And they also had huge support and consulting contracts associated with all the software and the hardware that they were delivering, sort of a precursor to the Ford deployed engineer, if you squint a little bit. But the PC era was the real turning point. So the IBM PC launched in 1981. This legitimized the personal computing market and set up two new companies, Intel and Microsoft, to capture immense value during the next computing boom. So the IBM PC ran Windows and

Starting point is 00:04:17 used an Intel chip. At the time, IBM was doing $30 billion in revenue. Intel was doing less than 1 billion and Microsoft was only doing 17 million in sales. And so I think Microsoft had like 120 employees. And all of a sudden those two companies became ultimately way, way, way bigger, like 10 times as big. So the market eventually fractured and proposals to break IBM into separate companies started to pop up. The market fractured because once you had an Intel chip set and Windows operating system, you could run Windows on a different chip set and you have a different chipset with different operating system. And the value capture piece, there were just other PC manufacturers that came in and then obviously Apple with their anti-IBM, like, challenge the man

Starting point is 00:04:59 campaign. So the market was fracturing and there was a bunch of proposals during the 80s and 90s to break up the company into separate units. Lou Gersner, who became CEO in 1993, rejected that idea. And he said, quote, we do not necessarily need to manufacture every piece of technology. We need to be the company that makes all of it work together. So we have to work together. We're going to be the integrator, the systems integrator.

Starting point is 00:05:23 His strategy ultimately produced three things, IBM Global Services, large outsourcing contracts, and a vast consulting organization, and that's a lot of what we know about IBM today. So services businesses do have limitations, though, lower margins, higher head count, slower organic growth, price competition, et cetera. In 2019, IBM acquired Red Hat for $34 billion and spun off its traditional managed infrastructure outsourcing business in 2021. So today, you can think of IBM as sort of three key businesses. They have software, which is 44% of the business.

Starting point is 00:05:55 That's an 80% gross margins, great business. 31% of their business is consulting. That's under 30% gross margins, though. And then 23% of the business infrastructure, which is just shy of 60% gross margin. And so for the last three years, the stock's been doing really well, up 77% before dividends. And the red hack acquisition started paying off. And the Z17 mainframe cycle was surprisingly solid. But the problem is that they just called out a shift away.

Starting point is 00:06:22 from mainframe spending with customers shifting capital spending towards the physical AI buildout. Demand for AI and associated hardware is strong, but IBM is losing share of their customers' technology budget. IBM still does have a strong asset for the AI era. Red Hat OpenShift, which is their enterprise Kubernetes platform for orchestrating workloads across multiple computers. But there are so many other companies offering AI capabilities up and down the stack that

Starting point is 00:06:49 they're getting a little hammered today with the worst. the biggest share drop in its 115 year history. Rough day for IBM. But an interesting story, nonetheless. Let me tell you about Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces,

Starting point is 00:07:08 and now with AI agents. We have a great show. We have seven guests coming on, lots of fundraising news across VC firms and... I'm thinking we're back. We're totally back. Dylan Byers is also coming on from Puck. to break down the Warner Brothers Discovery.

Starting point is 00:07:24 Yesterday, it was over. We had no fundraising news. Today, we're back. I think it's just like slow weekends. People like to launch Tuesday, Wednesday, Thursday. Their news on a Monday. Yes. But Demis, Hassabas from DeepMind, the DeepMind chief,

Starting point is 00:07:41 he is called for a U.S.-led body to test frontier AI models. He says society has a precious window to prepare for technology advancing at historic speed. He's a Nobel laureate. The Financial Times has the story, and there's an article that he posted on X that will sort of click through and give you the takeaways. From the Financial Times, Google DeepMind, chief executive, Demis Hesavas, has called for the creation of a U.S. led standards body to test new frontier class AI models for national security threats, arguing that urgent action from international regulators is needed to address the risks posed by rapidly advancing technology. I'm surprised, has he never proposed this before?

Starting point is 00:08:25 This feels like something that has been proposed many, many times, but maybe I'm just misremembering the AI 27 people and the AI 2040 people and the open AI white paper and what Anthropics said. It feels like we've seen this before, like we need to have a regulatory body of some sort, all the way going back to when the All In podcast was talking about an FDA for AI back like two or three years ago. But it's now here, and it's coming from a deep-mind executive, which hits a little harder.

Starting point is 00:08:55 The warning from Hasabas, a Nobel laureate who leads Google's AI efforts, follows the White House's abrupt export ban on Anthropics' most advanced models last month, alongside a fresh wave of warnings about the potential for AI to disrupt the global economy and financial system. We talked a little bit about the economists that got together with a much more moderate proposal, I think, because it wasn't actually calling for a... any sort of change to the development of AI whatsoever or the rollout? And they were just saying it could get, AI could get better in the next 10 years. Yes.

Starting point is 00:09:28 Which is a very sort of. Could get a lot better. That's what they said. They didn't just say better. They said a lot better. But the actual pitch from the economists was we need to have economists and government officials think about responses if there is job displacement from AI. what is the impact, what will the reaction be,

Starting point is 00:09:52 to sort of like prep the legislation. So you can be more ready when things start to happen, whether that's retraining or stimulus or jobs programs or all sorts of different things. So this intervention from Demis is the most detailed proposal yet for AI regulation from Google, which is vying for AI leadership with Anthropic and Open AI. Quote, we've already seen the challenges frontier models

Starting point is 00:10:16 pose for cybersecurity, good point. and other threats, including nuclear and bio-risks, may soon emerge as capabilities continue to advance. The rapid progress we're seeing in AI requires a new approach to testing frontier AI model capabilities that is dynamic, adaptable, and rigorous. The U.S. is well positioned, given its economic and technical standing to take the first step in developing such a framework. My big question is, it seems pretty easy to go to the leading labs and say, hey, you have to go through this process. But do we have a good framework in the United States for reviewing code that China just sort of throws over here, open sourced.

Starting point is 00:10:55 Because if you, I mean, as we've seen with the Kimmy K2 and GLM, like if you tie someone up in an FDA-like review for even six months, let alone a year, let alone what the FDA timelines are for drug development, five years, 10 years sometimes, you are going to have open source models that are way, way more advanced. So like, you either have to review very quickly. Here's the name of a new frontier model. It's going through a six-month review, let's say. Maybe it's really like a one-month review, and then there needs to be.

Starting point is 00:11:29 With AI, it could be a two-minute review. Yeah, I would hope. But let's say it's like a three-month delay or six-month delay. Then when it eventually does get released, it gets distilled likely within even less time than that. and is publicly available. Yeah. Open weights. Yeah.

Starting point is 00:11:47 I would like to see, so we keep seeing these like letters and proposals. Yeah. And they always come, one, with a request for urgent action, but they rarely come with super concrete scenarios, like near-term scenarios. I want, here's what's going to happen in six months. Here's what's going to happen in 12 months. Or even just. a trigger. Like, it would be interesting if somebody said, if the unemployment rate goes above

Starting point is 00:12:17 10%, I would recommend a stimulus check of $1,000 be sent to everyone and means test it. So it only goes to the middle class and lower class. Like, that is a very reasonable thing. That's basically what happened during COVID, right? Like, the unemployment rate went to 15%. And then boom, there were checks in the mail for everyone. And that's a very concrete proposal that you can say, if this happens, then this happens. Yeah, I want, I want someone like Demis. Basically, the world of less wrong and AI 2027 and 2040, they're willing to lay out super concrete scenarios. And they can at times come across as very sci-fi. But there's always, at least so far, been some element of reality in them.

Starting point is 00:13:03 I hear what you're saying. I want somebody who's like generally more like kind of moderate to come in and just say like, here's a, a few potential scenarios and this is what I think. And because I don't believe it's, you know, Demis could suggest what he thinks that the government should do, the U.S. government, in this case, he's, you know, encouraging like a U.S. watchdog. He's in London, though. So I think it's going to be on our lawmakers and our government to understand in these different scenarios, at least start thinking through in these different scenarios, how would we approach them? Mm-hmm. Mm-hmm.

Starting point is 00:13:41 Yeah. I just, I always have a problem with the, with timelines and predictions because those can get so nitpicked and they're so hard. I'd be more interested in less of like, no, but don't you think that would be helpful if, if? I don't think it's helpful. No, no, no. I actually don't. I think it's much more helpful to say if the unemployment rate goes to 10%, create a new government body that hires people to do something. Like create the next TSA or send out similar checks or lower interest rates, right? If you tell Washington, D.C., AI models are very good at hacking computer systems and they're going to get better at hacking computer systems. There's not really much for them to do with that because hacking computer systems are already, it's already illegal. And the solution there is for companies to beef up their own cybersecurity, make sure they're using the most advanced models, right? Yeah.

Starting point is 00:14:37 And so if you play out, again, more concrete scenarios where like, here's, here's a timeline for the trucking industry and potential job displacement within trucking or any of these other categories. I just think it allows people in Washington, actual lawmakers, to start thinking about it. I just think that's always wrong. Like, they're always wrong about those predictions. Yeah. It's so much better to just say, look, if the trucking industry goes through mass job displacement, then. here's what I actually propose. Here's the solution.

Starting point is 00:15:11 As opposed to just saying, like, there might be a problem, and I think that there's a problem coming down the pipe. I don't know. It's like, what are you actually advocating for other than just being like, the sky might fall. I have a P. Doom of this number, and it's your job to go figure it out. It's like, you're smart.

Starting point is 00:15:27 What do you suggest? UBI? Higher taxes? I just don't think predictions are always wrong. There's been so many examples over the last decade where people have gotten predictions, like, dead on. Yeah, yeah. Situational awareness.

Starting point is 00:15:40 Tyler, what do you think about this? Yeah, I mean, I'm probably in the camp of, like, proactive regulation. Like, usually, like, has had bad consequences. It doesn't really work out. But also, I was just going to say, like, what he's describing is basically just Casey, the Center for AIS and Innovation, which is under the Commerce Department. Yep. And it's, like, a slightly beefed up version because right now Casey is, like, very much you opt in.

Starting point is 00:16:02 Yeah. But it seems like he should just have said, like, you should, specifically beef up Casey, add these policies, do these, like, specific things. And I think that would be much more, you know, palatable or well received or like something. Like, what do we actually do with this letter? It's kind of very, you know, like, I'm not sure what we actually do with this. Yeah. It feels like if, I mean, to go back to cybersecurity, it's like if it's a national issue, like the NSA works on this stuff, increase their budget, maybe, raised taxes to increase their budget, issue more debt to increase their budget. If it's a,

Starting point is 00:16:36 If it can be solved by the private market, it's like go support CrowdStrike or start a new company that can help with cybersecurity. I don't know. The actual concrete recommendation boiled down from what Demis wrote is something along these lines. Create a U.S. Frontier AI Standards body. That's like Casey, but probably more beefed up. He's also advocating that it's overseen federally but funded by AI companies. Define and regularly update benchmarks to determine which models and lab. qualify as Frontier.

Starting point is 00:17:08 So that's something that doesn't exist yet. Require Frontier Labs to submit models for testing up to 30 days before release. That's sort of nice because that would allow someone who's just going and building a recommender system on Netflix that's actually, it is using AI technically, but it's not a frontier model because it doesn't qualify for that. So then they can just go and ship the latest recommendation algorithm on Netflix, no big deal. test models for cyber biological nuclear deception autonomy and guardrail passing capabilities require strong cyber security personal vetting model cards watermarking and substantial safety research use national labs federal agencies and independent third party auditors to conduct evaluations develop independent confidential tests so labs cannot train specifically against the benchmarks require labs to fix serious vulnerabilities discovered after release apply the rules to all frontier models deployed in the united states including including foreign and open source models while exempting smaller models.

Starting point is 00:18:06 Okay, so he wants to apply it to foreign open source models. That feels very tricky, but I guess you could get like sort of DMCA notices to hugging face and GitHub so that it doesn't proliferate across the web. Yeah, I mean, there's probably some power lot to like where people are actually downloading and inferencing the model. And I guess if you go to all the neoclods and all the open source folks and you're like, okay, this model is actually a bad model. You got to go, you got to stick to GLM 5.2.

Starting point is 00:18:31 Yeah, it's much easier to regulate. the compute. This is going to be very controversial to the open source fans. Yeah, this is kind of like the George Hoff's nightmare take. Yeah, for sure. Tagging every single GPU. For sure, for sure. Coordinate a slowdown among Frontier Labs,

Starting point is 00:18:45 if testing reveals sufficiently serious risks and turn the US framework into an international system of shared frontier AI standards. Well, I like the general direction. I like the idea that he's just sharing his viewpoint more broadly. I think all of that is good. I'm not sure that there's enough to dig into. you hear exactly how this would, like where the rubber meets the road, how this would be implemented

Starting point is 00:19:09 or what effect this would actually have on the industry. Like this could be really good for open source because it could just slow down the frontier close source labs. It could also be really bad for open source if it's much more cumbersome because an open source project might not have a regulatory budget to actually massage a model through the approval process. Like there's a reason why small biotech companies get acquired by big pharma before they launch their drugs, it's because, like, the big pharma companies have offices in Washington, D.C., and can walk the legislators through the whole process. So in general, I'm sympathetic to the

Starting point is 00:19:45 view where people say, oh, regulation benefits the biggest companies in the world, because historically that's how it's played out. Maybe that's different this time. Who knows? It could just slow down the frontier, but, you know, he does work for a leading lab. So, um, interesting. Let me tell you about MongoDB. What's the only thing faster than the AM? market your business on MongoDB. Don't just build AI. Own the data platform that powers it. What's going on in New York?

Starting point is 00:20:10 I will tell you what's going on in New York. Today, New York Governor Kathy Hocchel signed an executive order placing a one-year pause on new AI data centers in the state. This is the want-want-for everyone except 70% of Americans. People that are probably. The order establishes a moratorium while New York develops a regulatory framework and conducts environmental impact assessments examining data centers energy demand, water use, water quality, air quality, and effects on the electric grid.

Starting point is 00:20:49 You would think there's a decent amount of oversight around those things generally already, like air quality, like whether you start a new barbecue restaurant or a coal plant, you would imagine that there's just a general rule about not polluting the atmosphere that would apply to data centers by default. But it seems like there's a little bit of a special case here. And so they're working on this in particular. The move immediately drew criticism from the tech industry, which argues that restricting data center construction will cost local community's jobs and weaken America's position in the global AI race. Earlier this year, Maine considered a similar moratorium, but Democratic Governor Janet Mills vetoed the proposal after concerns it would block a major data. data center planned for a town still struggling after the closure of a local paper mill.

Starting point is 00:21:37 Hocchel's Republican challenger, Bruce Blakeman, also opposes the moratorium, arguing that local governments, not the state, should decide whether to approve projects that promise significant economic benefits. If it stands, the order would make New York the first state to impose a broad moratorium on large-scale AI data centers. The Associated General Contractors of New York State is already. condemning the decision. So the contractors who are going to be working on this project and see it as a form of job creation are upset about this. But let's see what president and CEO Mike Elmendorf had to say. He warned that halting permits for as much as a year in this fast moving sector will not simply delay

Starting point is 00:22:21 projects. It will send them permanently to Virginia, Texas, Georgia, and other states actively competing for these investments once those projects break ground. Elsewhere, he argued the jobs, tax revenue, and economic opportunities are unlikely to return. So there hasn't been that much of a data center boom in New York State that I'm aware of. I'm trying to find the largest campus that I can find is the Lake Mariner campus in Barker or Somerset. Yeah. And it's around, it has around 205 megawatts that are active. Wow, yeah, that's pretty big.

Starting point is 00:23:01 And there's a proposal out to do another 500 megawatts. Yeah. But it hasn't been approved yet, and certainly that the new ban would stop that as it's any data centers requiring 50 megawatts or more. I know a lot of a lot of IT infrastructure data centers, if you can call them that they're usually smaller scale from financial institutions in Manhattan often are built in New Jersey. But that's basically purely for economic reasons. that the land is cheaper and the buildings are cheaper. But I do wonder if this will have any knock on effects where the Netflix content delivery network

Starting point is 00:23:39 that was just planning to build a small data center to route video streams to Manhattanites would be delayed as well. Like data center, it'll be interesting to see how they define AI data center. Will they do it on energy or what type of GPUs you're racking or what's going on there? But more to dig in.

Starting point is 00:24:00 Ken Griffin was on Goldman Sachs' podcast, the Exchange, exchanges podcast. And it was circulating this week, even though it was, I think, recorded last month. And he was talking about how, yeah, in his view, what an error this would be to his view. The data centers are going to get built. And if they're not built here, that means hundreds of billions of dollars of revenue, basically flowing through other countries, right? Other countries, I mean, it'd probably go to other states first, right? Well, he was talking about it.

Starting point is 00:24:33 Oh, if it goes national. You know, if New York does it, there's going to be a lot of other states. Yeah, the meme is like China wins in this scenario. U.S. Senator John Federman. Yeah, we did this with nuclear. We did this with manufacturing. Yeah. Both of which I can all agree were mistakes.

Starting point is 00:24:53 I was trying to find if any of the hyperscalers operator, own data centers in New York. Well, the funny thing is that when Mark Zuckerberg proposed the Hyperion data center, the visualization he used was we're building a data center the size of Manhattan, which was very cool to see. But now Dylan Patel is sharing an image of a proposed data center that takes up all of Central Park, of course, the most controversial data center you could possibly build in the entire world. Tyler's in favor of it.

Starting point is 00:25:23 But it's funny because that image probably stuck in some people's mind is like, oh, Zuckerberg's trying to build a data center in Manhattan. I don't like that idea, even though, no, he was always going to build Hyperion in a very remote location for a variety of reasons. There's also an article in the Wall Street Journal. Can a prettier data center curb the community backlash? People have been batten this idea around for a while, but let's pull up this image and you tell me, would you be okay with this going into Malibu, the Malibu Compute Company?

Starting point is 00:25:54 Would you be cool with this? If it was puking out diesel fumes 24-7? if it was clean and it didn't drive up energy, didn't use any water, it was all closed loop, and it looked like this. I wouldn't just be okay with it being in my town. I'd want it in my backyard. Yes. True Yimbi over here.

Starting point is 00:26:14 That's right. In an effort to soothe local opposition architects planned data centers that resemble tech campuses or art museums rather than bland boxes, you have to imagine that the money that they're spending on the data center for a facade like this has got to be fair. very, very cheap by comparison. It looks like a slat wall. Half a percent. And all of a sudden, just every time it screenshotsed,

Starting point is 00:26:36 like there was that odd Google presentation where they were in front of those crazy tanks and they put the logo on there and it made it look like they were taking like a brewing facility and turning it into a data center. But it was just for the press release. Like the data center was actually somewhere else, but it was just sort of like an odd image.

Starting point is 00:26:53 Americans are up in arms over data centers. Of course, we know this. They worry how much water these buildings, and fume at the amount of electricity they consume. People hate the way they look, too, says the Wall Street Journal. Now, a small number of builders are on a mission to ensure that new data centers don't have to be eyesores. Gensler, one of the world's largest architecture firms, is leading the charge. It's drawing up plans for data centers that look more like Silicon Valley Tech campuses or art museums,

Starting point is 00:27:17 rather than windowless rectangles that neighbors often grouse about resembling prisons. It's no different than any other building, and it doesn't deserve to look any worse. than any other building. So Jeffrey Diamond, a design director at Gensler. Yeah, see, this is just very rough. Yeah, not good. That is. Underground, put the plants on top, you've got to do more.

Starting point is 00:27:41 Yeah, yeah, you get, you, uh, people will push it to the limit unless there's, uh, some pushback. But, uh, in other aesthetically pleasing AI development news, Clanker media shared that, uh, researchers built a soft, floating. robot for indoor interaction. And for so many of the AI robots, of the humanoid robots that we see on the show are Lovecraftian and horrific, this is so cute. I want one. Don't you want one? Just floating around answering your questions? These have the, this has the potential to be a, like a massive hit at the consumer product. It uses helium and flapping face.

Starting point is 00:28:28 instead of propellers, extremely cute. The result is quiet, lightweight, and safe to touch. It can follow people, give reminders, and act as a study buddy. So you can be studying in this whale can come up next to you and answer your questions about your math homework. See, I don't even need it to be smart. No. I just wanted to fly around. Yeah.

Starting point is 00:28:50 Loaded up with GPT2. It's good enough. No. We don't even need any local models. Just have it fly. Just have it fly around. Oh, you don't even want to talk. Yeah, I just want it.

Starting point is 00:29:02 You just want it. I personally would demand that they install Codex on this thing. Let me tell you about Codex before we bring in our next guest. Codex is a powerful workspace for getting work done with AI agents. Whether you're writing code, analyzing data, creating content, or automating business workflows. Codex helps you move projects forward from start to finish. And our next guest is in the waiting room. We have Dylan Byers from Puck.

Starting point is 00:29:22 He's the founding partner. And he's here to get us up to speed on Paramount Warner Brothers Discovery. the acquisition. How you doing, Dylan? I'm good, gentlemen. How are you doing? We're doing fantastic. Have you been on vacation? You look incredibly tan. Yeah, what's going on? What's the secret? I'm tan. I'm unkempt. Ooh. I, I eat, no, I'm in the Pacific Northwest. I've been traipsing around the Pacific Northwest for the last month.

Starting point is 00:29:45 You've been traipsing. Business or pleasure? Yes. Like a logger. A little bit of both. Business and pleasure. I was in Sun Valley during the Allen & Company conference to meet with a bunch of folks who were there. And then I'm, I, thank you. And then I'm from here. I grew up in Seattle, so, you know, what better place to spend the summer? We had a question about Sun Valley. Who had the bulkiest security guard?

Starting point is 00:30:08 Who security guard was the strongest physically? Oh, yes, bigger? Historically, it's Bezos. I know Barry Weiss has some beefy security guards. I read about that in the New York Post. Yes, I did hear about that. I didn't see them. I didn't see any security guards there.

Starting point is 00:30:22 You know, here's what I will say about Sun Valley, about the Allen & Company conference. It is remarkable how. I mean, they create a security perimeter, but it's very subtle. And it is remarkable how comfortable all of these executives who are used to security details, how comfortable they are just moving around the property. They really feel like there's minimal attention even to the fact that they're there from the locals. Other than myself and reporters from Bloomberg and CNBC, they are largely left alone and they feel that. Sure. How, what is the interaction? We always see those photos of like the line of microphones at the fence for the, you know, ad hoc interview. Obviously, there are scheduled interviews at CNBC and Bloomberg sometimes and sit down interviews. But what is the day to day of actually reporting on Sun Valley like? Are you grabbing quotes from people or are you meeting with folks?

Starting point is 00:31:16 No, I go. Different strokes for different folks, right? I mean, there are, historically, there have been like New York Post reporters who go there. And once in a blue moon try to breach a security line. and get color and quotes. I go there to meet with people off the record. Sure, sure. For me, like that is the world I cover those executives, be they in media, tech, entertainment, whatever. Yeah. And I have off-the-record meetings with them at a cafe on the property.

Starting point is 00:31:43 There are others who go there and do get interviews like Julia Borsstein of CNBC, always gets three or four interviews. It depends. But what I do not do, thankfully, gratefully, I do not stand there at the front and shout questions at people who then just sort of like wave at you, which is really their way of giving the finger, save for David Zazlov, who's like a moth to the flame of the microphone, and we'll come over and always give a good quote. I love it. How real is the meme that like this is where the mega mergers are birth? This is the place where the ideas come together, the merger that you'll hear about in a year for $100 billion.

Starting point is 00:32:23 It's all starts in Sun Valley. Well, look, here's the deal. I have I have, I've tried to set the record straight on this. Deals do happen there. Oftentimes they happen as the culmination of conversations that happened well before Sun Valley. And occasionally, like, conversations start there. And I don't want to downplay that. Like, it is true. Like, if you just, you know, this year, there's not much that I know of at least yet. Sometimes we don't know about it until later. If you look at last year, like, yes, Apple got the rights to F1. at Sun Valley. And there were meetings between Liberty and ESPN and Apple and Apple won. Sun Valley last year was where not only Larry, or sorry, David Ellison, but also Matthias Duffner at Axel Springer and the Murdox came and tried to court Barry Weiss.

Starting point is 00:33:15 And of course, David Ellison won that one. So yes, deals do happen. I think what I reject, and I've written about this, I reject the notion that all of these people with their private jets who basically run on similar circuits throughout the year, that somehow like if Sun Valley didn't happen, they would have no way to make deals happen. And that somehow these brilliant people, these brilliant entrepreneurs and executives who have managed to like run their businesses successfully and are always thinking not just months, but years, if not decades ahead, are like, oh, I happen to be in Sun Valley with this person

Starting point is 00:33:51 and therefore I will buy the Washington Post. Sorry, that's not the way it works. But that said, everyone loves coming here because it is. The same reason I love going there, it's shooting fish in a barrel. It's just like speed dating with everyone you want to see, and it's just extraordinarily convenient. And then going back to my point about the Pacific Northwest in the summer, there are worse places to be than amid the quaking aspens in Ketchum in July. Yeah, that's great.

Starting point is 00:34:20 Well, so. So get us up to. speed on what's going on with the Warner Brothers Discovery acquisition, maybe a little bit of the prehistory just to refresh on where the deal stands and then the latest back and forth that emerged last week trickling into this week. Yeah, look, David Ellison has had to jump hurdle after hurdle to try and get this deal done, obviously, $11 billion deal, bring Warner Brothers Discovery into the fold with Paramount. And the last hurdle, he might face some challenges in the UK.

Starting point is 00:34:55 But really the last hurdle here in the States, now that he's cleared everything with the Trump administration, are these Democratic State Attorneys General, led by California, A.G. Rob Bonta. Finally, Bonta came out this week, sort of very cinematic. He was, like, on a trail in front of the Hollywood sign. And effectively said, like, yes, We are suing.

Starting point is 00:35:19 We are trying to block this deal. Here's why. We can get into it. It is very hard for me to see that he has a strong case for blocking the deal, that he and the other AGs have a strong case for blocking the deal. Because if you think about it, like, David Ellison wants Warner Brothers Discovery to have some semblance of the scale that would be required to compete in a world that is dominated by, you know, like pick your brand.

Starting point is 00:35:51 Netflix, YouTube, TikTok, Apple, Amazon, like the list goes on. And so what Bonta and Co are doing is sort of presenting this, like, very strict definition that is rather archaic, right? It has to do with, like, theatrical distribution, cable distribution, issues like that. And I get from a political perspective why he feels the need to do that. and I think there are probably political ramifications for him if he didn't do that. But the notion, I mean, like, just think about it on his face. We all live in the real world in 2026.

Starting point is 00:36:24 The notion that somehow a combined Paramount Warner Brothers Discovery, a combined CBS, CNN, combined what are the streaming services, HBO Max, Paramount Plus, is going to be this, like, a massive, dominant business that is going to somehow like, like, you know, corner every aspect of the market. That's just not real. That's not the world we're living in. So I think Bonta has an uphill climb in that regard, but he can certainly create headaches and certainly legal fees for Ellison for many months.

Starting point is 00:36:57 And so zooming out, like Hollywood is under attack loosely or facing competition from tech platforms, YouTube, Instagram. And so time, time and attention is more broad than just. Hollywood. And so with that backdrop, well, consolidation might not be good within the view of Hollywood. There's less buyers for movies. It might be a defensive move in a world where you're facing extra competition for attention across the internet. Yeah, that's right. I mean, it's just how do you define the competitive marketplace? Yeah. And if you're talking about, you know, the fact that, look, Hollywood has, Hollywood is in decline. I don't think anyone can dispute that. And frankly, like,

Starting point is 00:37:44 There are comparisons to Detroit, you know, of decades ago. And I don't know, you guys are in Hollywood. I live in Hollywood. Sometimes it certainly feels that way. So there's this notion that like, okay, we used to have six studios and then we have five studios. And if we have four studios, that's going to be a problem. And so all of this sort of, you know, there are all these negotiations over,

Starting point is 00:38:05 okay, well, we'll release 30 films a year. We'll keep both studios open. We'll have a 45-day theatrical window. And I'm sorry, but that's just, that. is not where the that is not where consumers are that is not what consumers care about that's just not what the market cares about like where you're not people aren't people people people don't think that the one form of entertainment that they have yeah uh in the world exists in a theater and they care about a 45 theatrical day window like we live i mean to even say that we live in an air of like Netflix and YouTube almost seems passe when you think about everything coming down the pipeline in terms of AI platforms and everything else so it just seems like remarkably outdated which I suppose is an ever, evergreen commentary anytime you have Washington going up against business, entertainment, media tech. And again, I just don't, I don't see how Bonta wins that case.

Starting point is 00:38:57 Jordy, can you have a question? Yeah, it was just the, how did the threat to leave California? Yeah, because it feels like there's a short-term incentive to stop consolidation in Hollywood, but if you wind up with, you know, studios leaving Hollywood, well, you've lost the war, even if you won the battle. But how, how. Yeah, it's just reminding, it's just reminding me of the, of the whole Getty images shutter stock deal, which is, uh, was announced in January of last year.

Starting point is 00:39:31 It was a $2 billion merger at the time. Now both companies are worth roughly like 300 million in the public market. So two companies that are under attack trying to consolidate. And I'm sympathetic to the idea that this does create like a stock photo monopoly. But in the world of AI image generation, like a monopoly in the real world stock photos actually taken with a camera is probably the only thing that can go up against just random image gen. And so it's a very logical move. But yes. Well, look, let me just say first about the threat to leave California.

Starting point is 00:40:05 Yeah. One, everything that you, every headline we see needs to be viewed through the lens of brinksmanship, right? Everything is basically trying to win the hearts and minds of anyone who's paying attention to this deal. And the threat to leave California all of a sudden would seem, like if you take it of face value, would seem to reverse the narrative. It's like, okay, Bonta's, you know, ostensibly coming out here to try and fight on behalf of Hollywood. and like, lo and behold, his measures are going to drive Paramount Warner Brothers discovery out of Hollywood. A lot of people, I think, looked at that and thought that that was a bluff and there's no world in which Paramount WBD can leave Hollywood. I don't know.

Starting point is 00:40:50 I mean, look, I do think it is a bit of a bluff. I do think it's brinksmanship. On the other hand, as folks I spoke to reminded me, like, David Ellison did not get into this business either to just have like an old. fashion Hollywood business that couldn't really compete with the big tech players, nor did he get into it in a David Zaslov kind of way to just like flip the business in three years. He's young. He's into, like he has, he has ambitions of grandeur, he has ambitions of empire building. He really does believe that he can position this company to compete with, with all those other companies we've already mentioned. And if you think about it through that lens, is he nostalgic about Hollywood itself and

Starting point is 00:41:34 like the actual location of Los Angeles. No, if you look at what his father did with Oracle, he moved Oracle from Redwood City to Austin. Austin, I believe now it's moving from Austin to Tennessee. And there's other precedent, right? You have Tesla, you have Chevron. You have Hewlett Packard. Disney, too, moved a lot of people to Florida during COVID.

Starting point is 00:41:58 And there was a lot of backlash and not everyone moved and they still have a huge presence in the Hollywood. And now is, like, you know, like. you know, 30 years ago, if you're said, yeah, I'm going to have one of the biggest entertainment companies in the world, it's not going to be based in Hollywood. You would have been laughed at. But now you talk to anybody here that's like actively making movies, TV shows, et cetera, and they're already traveling a bunch. So it truly doesn't need to be here. No, you're traveling a lot. Different states have different incentives for filmmaking.

Starting point is 00:42:27 And by the way, like go back to the Oracle Tesla examples, like you still have businesses. You could theoretically have a Paramount Warner Brothers Discovery based in Austin or Nashville or anywhere else that still had studio lots in California and to the folks in the writers room, the showrunners, the talent, they wouldn't know the difference. The only person who would feel the difference is Rob Banta, who suddenly would not be on the end of what David Ellison is touting as a $30 billion investment. And at a certain point, Bonta is walking a very fine line because he's trying to fight for Hollywood, but he is running the risk of alienating one of Hollywood's most valuable players right now. And so it's just, it's politics. It's pure politics. And another point I brought up this week in my writing is like, just to underscore how much this is politics,

Starting point is 00:43:22 I want you to imagine that David Ellison, who by the way, is not some like right-wing MAGA guy. Like, he's not. He's donated to Biden, whatever. He's really just a pragmatist who's trying to get a deal done. Sure. He took Trump to ringside at the UFC. He went to the state of the union address. He held a private dinner for Trump and his administration before the White House

Starting point is 00:43:44 Correspondents dinner. All of that to, like, the folks in the newsroom at CBS News looks like, you know, he's like the new Rupert Murdoch. Sure. The truth is, is if Kamala Harris or Joe Biden were in power, he would have done the same thing. It just would have been at like, you know, the U.S. Open or Wimbledon instead of a UFC match. Sure. And like, and the fact of the matter is, is that in that scenario, Rob Bonta would probably not be bringing this case.

Starting point is 00:44:12 And it would probably be Republican AGs who would be trying to bring this case. And I think we have to be honest about the politics there. Yeah. I like the idea of tennis at the White House. Maybe that'll happen soon. Right. Yeah. U.S. Open on the White House lawn.

Starting point is 00:44:25 Yeah. Maybe just all sports. just be a sports venue and they should just have the hockey and then basketball and then baseball. Was there adequate sponsorship? I didn't watch the UFC match on the White House lot. Was there adequate sponsorship? Like, did they milk that for our, for all they good? Not nearly enough. We could have gone way further. Yeah, it's unclear. There were a lot of sponsorships. Yeah. Yeah. Yeah. I remember a specific image of Justin Gaichi, you know, the American champion who won his fight, doing a backflip with a

Starting point is 00:44:57 And you can see the White House in the background. And there's a very, it was very iconic image. Yeah. Can you talk about the debate that sprung up, I think, a little bit earlier, once the merger was confirmed around the duplicative studios, Paramount Warner Brothers. They have two, when we say studios, there's the abstract concept. And there's also like that physical, historical locations that are very meaningful. There was this discussion over, is one going to be turned into apartment buildings?

Starting point is 00:45:25 And that feels like sad from I Love Hollywood perspective. Also, if you're a housing person, it feels like maybe they'd be good to bring down housing prices. But at least the reporting that I saw from Puck was there was a lot of pushback towards like, don't ruin this amazing financial, this historical institution. Is that chip still on the table? Has that been resolved? because there's been a lot of, like, okay, we're making this pledge, we won't do this, we won't, we won't cut, and I'm just wondering if any of those chips come back on the table. Well, here's what I would say to the one thing that Bonta has gotten right. Forgive me because I forget verbatim what he said, but effectively, like in spirit, it's, I can't regulate pledges, right?

Starting point is 00:46:16 And that's true. And like, there is so much that is going to be said, which you should effectively take with the same. grain of salt that you take from like a political candidate who tells you everything they will and won't do in office. Like yes, is he committed right now to 30 films a year? Is he committed to a 45-day theatrical window? Is he committed? Again, I don't have the latest on this, but to keeping both studios open, sure. Once you've got the deal and once all of this is behind you, are there ways in which you can sort of finesse one of those lots into something else for your business and then maybe finessexed that real estate out of the portfolio to save some money? Yes. Yes.

Starting point is 00:46:51 Yes, and that will 100%, 100% happen. I think about this. You know, I cover this deal a lot at the news level and the sort of tie-up of CBS and CNN. The minute this deal happens, folks at Paramount are going to start looking how to offload the real estate that is currently used by CBS News and move CBS News operations into Hudson Yards at CNN. And why you do that? Because you have $80 billion of debt and because you have promised synergies. And there's no world in which you're sitting there with two lots that are duplicative that do the exact same thing and think, like, in order to honor the history of Hollywood, we will continue, we will continue spending twice as much money as we need to. It's just not going to happen. Especially not in the news business. Like, you can sort of make the claim around specific film studios being historically important to Hollywood. Hollywood means films. But when you think about,

Starting point is 00:47:49 the the the what it actually takes to run CNN and then CBS News like there are tons of overlapping I mean just pieces of equipment that you're like oh that teleprompter there and that backdrop and that lighting is like all the same and sure and look like I am sure there are some scott pelly types who have very warm feelings about the labyrinthine halls of the CBS News headquarters up on up in a uptown Manhattan but there was a group of folks from CBS News who went to hudson yards who went to Atlanta to tour it and they're like holy shit, these facilities are a lot nicer than ours. These are great. It would actually be a lot easier to create TV here.

Starting point is 00:48:25 So that will be really easy. And look, I think there is, as someone who covers change in the media space, there's always so much panic and nostalgia anytime anything changes because you think that thing that changing is sacrosync. And the truth is, is that it usually takes a matter of weeks or months before everyone sort of comes around to the new status quo and gets very comfortable with it. And that inevitably is what is going to happen here. Speaking of change in the media industry, have you noticed, I mean, you report and operate

Starting point is 00:48:58 what I see as like a very, very high level of the executives, the mega deal makers. But have you seen any knock on effects from the summer of YouTube blockbusters that we've been talking about here from the creator economy perspective? You have iron lung from Markiplier, obsession, backrooms. There's a number of YouTubers who sort of, you know, labored away in obscurity and then just put up incredible numbers at the box office. It feels like Hollywood might be looking for more scripts, more interesting IP, less sequels, less bought in things. But is there any individual studio that's excited about that trend or anything that you're seeing that's actually rising to the level of your reporting? I here's what I say I do not have as good of an insight into this as I do into other other things we've been discussing but here's what I will say just from a distance the every studio is thinking about how do we like all the way to a 24 right which is sort of like the bell of the ball when it comes to quality content in Hollywood is thinking about like how do we incorporate AI into what we are doing and I think the signal that those creators sent with films like obsession and others is like this can be

Starting point is 00:50:13 done and this can be successful. Does it mean that, you know, like every human being is going to go away and we're going to stop? Like, no, it does not. I think that most folks will learn, will find ways to incorporate this in, in ways that does not significantly, like, degrade the value of the content that they're making. But I think the sky's the limit. Like, I really think that those examples have shown that this can be done and that there is more opportunity here. than the folks who are sort of like clutching to Hollywood's past have realized. And by the way, that doesn't need to be disruptive in a bad way. That can represent like extraordinary opportunities in the same way. Like you guys talk about this day in and day out. AI creates extraordinary opportunities in every aspect of business, industry, commerce, everything else. And like that can happen here too in ways where the human element remains. How much are you tracking these AI?

Starting point is 00:51:13 short form vertical drama apps. There's, I'm counting three in the top 25 of the US iPhone app store right now. There's vibe shorts, AI comic dramas, net short, exclusive short drama video, space

Starting point is 00:51:29 exclamation point. And then story reel, exclusive drama. I'm not following any of this. It sounds just hearing you see it, read it, it sounds like, is this just quibby AI? Yeah, it's AI, AI quibby. Katzenberg entirely vindicated on the format.

Starting point is 00:51:50 But yeah, I've just been, I don't know anyone that uses these apps. I think we need to have Tyler on our team just spend like an entire weekend, watch every single one of these and review them for us. But it's funny to me that these apps are seemingly being created not within the tech industry. their technology products and not within Hollywood. So it's like entirely just, you know, outsider groups that are ranking... The hoverboard. That are ranking like Net Short and Vibe Short are both outranking CalShe, Paramount, Polymarket, like during these massive sporting events, right?

Starting point is 00:52:34 I mean, I guess, yeah, I get... Like, like, like, vibe short is outranking Gemina, and anthropic by a very meaningful margin. Yeah. I guess here's what I say. And I'm granted, like, I'm a very poor authority on this because my entire content has been like World Cup in Wimbledon or just staring at the quaking aspens in Sun Valley. Here's what I would say.

Starting point is 00:53:00 As in every other industry, like technology has democratized the ability to do things, right? And so, like, to bring this conversation full circle, there's no, no, no, real reason anymore that this has to happen in Hollywood. Now, I'm not suggesting that, like, you know, every institution just goes away, obviously. But what I am saying is, like, there is, you cannot look at something like the success of the YouTube creators or the engagement that these short-form platforms you're saying, like the engagement that they're seeing, and just dismiss that as a fad. that is a total reorientation of the possibilities that exist for people to come along and just create something that is going to be a massive hit.

Starting point is 00:53:49 And again, to bring this back to Ellison and to Bonta, you cannot argue that people who can put movies in cinemas on Hollywood Boulevard are somehow in a different business than the people who are making AI generated shorts. It is solely a question of where people are spending their time and then whether or not that time, that time and engagement can be monetized. And that, and it does not matter what category that falls into. It's just a matter, a question of eyes on screens. Do you have a view on how U.S. China relations might evolve with regard to Hollywood? Because it feels like some of the video models coming out of China are a little too good. And they might be training on some Hollywood intellectual property across different studios. And it feels like in order to actually take a lawsuit to the finish line or have any sort of settlement or retribution or some sort of even just truce to not allow you to put Mickey Mouse or Spider-Man or Batman in an AI generated open source.

Starting point is 00:55:06 model or something like that, it might require Hollywood sort of teaming up, going to Washington, asking for some sort of concession or, you know, deal within the construct of like the larger trade negotiations around rare earth. And it could be one of many bullet points in a new deal. Yeah, I mean, I do say like, and we're here and we've been here for a long time. Like China somehow seems to be the great unifier when it comes to businesses saying, like basically as the antithesis, right? Like the, it has been years that I have been hearing tech executives invoke China as a way to try and push back on regulation of U.S. companies. I can certainly see a world in which China becomes like the, you know, what's the term, the bug bear like that gets Hollywood to basically come together, work with regulators and say, like, we need to protect this because this is American.

Starting point is 00:56:04 And that is a very palatable argument for the folks in Washington or the folks in Sacramento. Yeah. I can totally see that. I guess the thing I would say, though, is I think what businesses really want is to be able to play in that market. And I don't, I think at a certain point, your ideal outcome is a way to protect your own IP, your own technology, while also being able to open up what is obviously an incredibly, robust and large market and work with them as well. And that, you know, that's a negotiation that obviously, like Tim, Tim Cook has been involved in for a long time. A lot of this, when it comes to the U.S.-China stuff, is above my pay grade, but that is sort of my sense of what will happen. Last question. Quaking Aspins, you've mentioned them twice. Are you a arbore? What is it? Arborist? Are you into trees, or is this just something everyone that goes

Starting point is 00:57:00 to Sun Valley recognizes about the trees? here's what here's the thank you for asking i've been wanting to talk about this for a long time um no here's what i think i wish i could convey to people i i'm very privileged in my position as covering the world that i cover to get to go like it is sort of a treat of the media tech entertainment space that these guys all sort of choose to convene in the mountain west yep so depending on where you are in the sort of hierarchy like you're either going to sun valley or jackson There are many retreats sort of in Colorado. A lot of these guys own ranches from like Montana down to Utah.

Starting point is 00:57:39 There's of course like the Aspen Ideas Festival. It is just like a real pleasure that these guys chose to convene there as opposed to say Cleveland, right? Or like just do everything in New York City. Or Vegas. Like CES is in Vegas and that would be, you know, where you'd be if you were on the electronics beat probably. Thank God I'm not. Thank God I'm no longer the politics being. have to go to like Iowa and New Hampshire every year.

Starting point is 00:58:03 And I just, if there's any way to just sort of convey the atmospherics of that world, I know of no better way than like the lull of the quaking aspens and the occasional sound of like a Gulf Stream jet taking off on the tarmac. Beautiful. Are you writing a book right now? I don't know yet. Should I? I think you should be.

Starting point is 00:58:28 You're tan. You're hanging out in the mountains. It seems like you have an incredible. Maybe an audio book. It seems like since the last time you're on here. It's through it. Okay. Maybe an audio book and it's just a recording of the quaking aspens and the sound of Gulfstreams passing by.

Starting point is 00:58:43 There you go. To fall to sleep. There you go. Thank you so much for coming on the show. Thank you, gentlemen. Have a great rest of your summer. Hope to see you soon and we'll talk to you later. Have a good one.

Starting point is 00:58:55 Cheers. Goodbye. Let me tell you about Figma agents. Meet the Canvas. Your AI agents can now create and modify your Figma files with design. system context. The quaking aspen, it's a tree. They're defined by the natural feature of Sun Valley Idaho landscape, famous for their pale white bark and shimmering autumn foliage. The quake is a flat leaf stems that cause the leaves to flutter and rustle at the slightest breeze.

Starting point is 00:59:23 Dan says Gulfstream ASMR. Gulfstream ASMR might be a market. Tyler, I need you to watch a few vibe short. a few net shorts and a few story reels by tomorrow. Deal. Deal. And we're going to, I don't know if we can watch them on the show. We can probably play a trailer on the show. Maybe.

Starting point is 00:59:46 But yeah, pick your favorite on the three apps and we'll circle back tomorrow. Well, our next guest is with us in the waiting room. We have Noah from Tara Firma. He's the co-founder and CEO. Welcome to the show. How are you doing? Doing well. How are you guys doing? In the safety vest looking great with the flag in the back too. I love it. Please introduce yourself in the company. Tell us a little bit about TerraFerma. Yeah. So TerraFerma was founded by my co-founder and I after we were working at SpaceX and we were trying to build Starship rockets down in Bocahika and the construction was just too slow. Where like why are we able to build rockets the size of skyscrapers at like one a month? But like building a road or a factory is taking years and years and years. So we quit her jobs to start a company to change all that.

Starting point is 01:00:33 We're basically becoming a new type of construction company, like a full-stack construction company. It builds their own robotics software, and we actually operate as a construction company ourselves. Okay, robotic software. So are you, how deep in the supply chain are you going to buy equipment? Are you buying from Caterpillar and retrofitting them? Are you buying from the people that make the tracks and the treads and the motors

Starting point is 01:00:54 and then building your own bulldozers and cranes? Are you using, you know, custom software and robotic automation just as a harness for the project management layer. Like, at what level of the stack are you operating now and where do you want to go? Yeah, on the hardware stack, you can probably see behind me. We take existing Caterpillar machines and we retrofit them. Caterpillar, John Deere, Kamatsu, those machines, they're pretty good. They're robust.

Starting point is 01:01:19 They've been around for hundreds of years. Sure. A hundred years, they're pretty good. Everything else we build ourselves. So we're building all of our own software from scratch, kind of the manufacturing engineering software that we built at SpaceX in order to operate. large-scale factories. We're building that for construction. And how did you actually go from zero to one? At this point, you've raised $115 million. What was the first project? Was it find the customer just sort of do it all manually?

Starting point is 01:01:46 Or did you actually build robotic tools first and then go and prototype them? What was the flow? This is a great question. So 12 months ago, we were only four people. So for the first year of the company, it was just my co-founder and I. We wanted to make sure we had a product market could fit before we started raising much money and spending it. So we actually built a bunch of robots using Tupperware containers that our lunchbox came in and like Raspberry Pi and Arduino from our college like kits. And we got robots working. And then we went around asking, like, who is willing to let us make some money with these robots?

Starting point is 01:02:19 And our landlord's like, hey, I got a building for you to demolish. You think you guys can do it? We're like, I mean, it's not rocket science. So my co-founder and I literally operated the robots ourselves. Like in the brain was a little Tupperware container. And we knocked down a couple buildings and got paid our first check. And we're like, whoa, you could just become a robotic construction company. It's Texas.

Starting point is 01:02:37 Like you can do whatever you want down here. That's awesome. What I feel like you'll quickly get to the point where permitting is like the gating factor where like you get to the point where hypothetically we could build this, you know, we could build this whole, you know, shell in like the shell they're in right now. we could build something like that in three weeks, but then you're limited by sort of local government and approvals and things like that. Is that right? And if so, how are you thinking about approaching that problem? It's a great question. People bring it up a lot. For starters, I just want to say, like, permitting is an issue, but it's not the issue. Like at SpaceX, once we had the permits, theoretically, you should go super fast. But construction still took longer than it should have.

Starting point is 01:03:22 Like we're operating at maybe 25% of a work week, nine to five, five days a week. We could operate at 168 hours a week. We could be at 100% utilization rate and we're not. So you can make construction four times faster once you get the permits before permits are the issue. Now, our approach this is very similar to like how Elon approach building rockets. Like, okay, we have to solve manufacturing. We have to solve supply chain. We have to solve testing the rockets and designing them.

Starting point is 01:03:46 And now the rockets on the launch pad fix the permits. And like I believe in the bureaucrats of this country, wanting to make the country better. If you have everything else ready to go and you make their jobs easy and you chew the food for them, they'll start approving permits faster and faster. They're not currently the main bottleneck most of the time. I imagine that we're firmly in the Centaur era at best. I imagine that every robotic piece of equipment has a human in the loop somewhere at this point.

Starting point is 01:04:15 But walk me through your vision for where this goes. I imagine that in the long term, it's sort of, you know, you create a, you know, a spec for what you want to build or destroy or the construction project that you're working on. And all of the robots go off and do everything. But before that happens, it'll probably be one human overseeing, two machines. Like, how does all of that play out? Another way to think about it is, like, you probably don't want to be, like, taking the approach to, like, same approach as, like, vibe coding with, like, building a building. Because it's like, hey, go build this ditch. and then it builds it like slightly in the wrong place.

Starting point is 01:04:51 And then you have to like, you know, fill it back in. And, you know, it feels like not as forgiving as the software domain. This is a great question. Do you want the economics answer? Do you want the sci-fi answer? Both. Let's do economics first, sort of like short term. I mean, we're familiar with Waymo.

Starting point is 01:05:09 They have, you know, overwatch drivers that might see four screens. They can sort of beam into one at a time. What are the economics of that? where do we go from there and then let's talk sci-fi so in terms of economics you have two curves that cross you have the cost of autonomy which becomes exponentially more expensive as you go from 90 to 95 to 100 percent we know spent 30 billion dollars or whatever it was over 20 years and you have the value of automation drops off a cliff when you have one person controlling one machine to one person controlling two machines wow 50 percent production of labor but when you're at one to four changing to one to five

Starting point is 01:05:43 it's if it's between 25 percent of your labor or 20 percent of your labor so I think those two curves cross in construction at about one person controlling three or four machines, about 75% autonomy. That's the goal for us, 75% autonomy, and then you add a new machine, and then you add a new workflow, and then you go from dirtworks to subsurface utilities, to concrete, to steel. We're building up the tech tree. Yeah, and that sort of makes sense because I imagine that when you're actually just one, like, old school piloting a construction machine, there's probably about 60% of your time is like downtime.

Starting point is 01:06:15 I know I need to get the crane from here to here, and I've now put my finger on the button, and I just have to hold it there while I get there. So while that's happening, you can sort of beam into a different machine, do something else, and sort of cue them all back and forth. Yeah, it's a little bit more video game than that. You ever play like StarCraft or Age of Empires in the Actorium?

Starting point is 01:06:35 Yeah, yeah, yeah. So we're able to say, Excavator, dig here. And you design a task for a minute and it will run for 20 minutes. Then you say bulldozer run here, roll or run here. Yeah. And this is actually our teleopsyvator operation center.

Starting point is 01:06:46 Sure. We have like 20 desks behind me. And these 20 desks allow us to operate like 80 machines at a time. That's very cool. So what are your what are yeah on the sci-fi front timelines to you know, you have a piece of dirt and robots arrive to the piece of dirt autonomously. And you have zero humans in the loop and you just get a structure in a very short period of time.

Starting point is 01:07:10 You don't want zero humans in a loop. It's not cost effective. There's so many edge cases in construction. Yeah, but I'm saying like, but if you continue to execute in the way that you're doing right now, wouldn't we be able to get to that point in 10 years, 15 years? I'm not sure if construction will ever fully be without a human in the loop. I think you'll have like a very small team of people that's very efficient building larger and larger projects. And it doesn't ever make sense to get rid of a human. That's my personal belief.

Starting point is 01:07:39 Even on Mars, I think we're going to have a small team of astronauts conducting like a large fleet of robots. There's just a lot of things that edge cases and things that the robots have never seen before. You can't collect enough training data to simulate every possible thing in the world. But if you're asking you the SimCity moment, when I can say, I want a road here, I want a restaurant here, I think we're like five to ten years away from that. I think it coincides with our Mars ambitions. Coensides as five years to Mars? What are you thinking? We are technologically capable of going to Mars today if we had the political and economic desire.

Starting point is 01:08:10 I mean, we've actually sent robots to Mars. Like America has sent robots to Mars. So it's possible. He's like, send me. Send me. Yeah. Yeah. It's not a technology problem.

Starting point is 01:08:19 It's more so like an economics problem. Yeah. But I think we will solve both within the next 10 years. How, but I imagine that the machines that you build for the moon and Mars will be much more highly specialized. When I think about the helicopter we had deployed to Mars or the rover, like those are science experiments meant to take samples and test specific factors of what it means to move around on Mars. But I imagine even in terms of building, you wouldn't just plop down a caterpillar, would you? No, diesel engines won't work in vacuum, so you've got to redesign the hardware. But at the end of the day, it's like a smart shovel, like you're moving dirt. It's not the

Starting point is 01:09:00 most complicated thing in the world. Sure, sure, sure. Very cool. Well, let's hit the gong. Yeah, last question, just because the crowd is loving it. And I wish we had more time. But how do you, do you expect any changes to like the materials side, like building materials side as robotics become, you know, much more part of building various types of structures? Or is it like, let's just change one thing at a time? Because I feel like. This is an awesome question. Are you familiar with the term DFM, like design for manufacturing? Yeah.

Starting point is 01:09:33 Like at SpaceX, we literally had to, the materials were pretty simple as like stainless steel, like the most common type. But you had to change the inputs to your system to be assembled by a robot. Like Starlink couldn't take V1 Starlink and make it at the speed that they're building V4 Starlink. They had to change the piece parts. I think we're going to change the way we connect pipes. I think we're going to change the chemical formulations of concrete. We're going to change how we weld steel structures. We're going to redesign the building codes to match something that can be built quickly by a robot.

Starting point is 01:10:00 That's amazing. I figure. Tell us about the round. How much did you raise? So we've raised $115 million. Who'd you raise it from? So our series A was $100 million led by Kleiner Perkins. Kleiner Perkins.

Starting point is 01:10:16 Oh! We got Maine Capital, Banner, VC, Saga Ventures, Trust Ventures, Magnus Hart. Wow. Murgers Pro. Saga? You got a bunch of great folks around the table. Congratulations. The American Industrialists.

Starting point is 01:10:29 You have the capital to build. We need it more than ever right now. So thank you for everything you're doing. And have a great week. Do us a favor. Raise another massive round. Yes. Come back soon.

Starting point is 01:10:39 Maybe take it up from nine figures to the next zero. I like it. Come back on this year. You deserve it. Great to me. We'll talk soon. We'll host our next one from the Mars base. Fantastic.

Starting point is 01:10:49 We'll talk to you soon. Have a good one. See ya. Let me tell you about CrowdStrike. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops. Our next guest is returning to the show.

Starting point is 01:11:00 We have Somm from Greylock Partners. He is a partner there. So I'm welcome back to the show. How are you doing? I'm doing great. Great to see you guys. Thanks for having me back. Thanks for hopping on.

Starting point is 01:11:11 Let's kick it off with another gong hit since it's warmed up. Tell us what happened. Give us the news. What's new in Greylock World? We've got some big news today. We're announcing Greylock 18, our 18th venture fund. It's a billion and a half billion. Go.

Starting point is 01:11:26 Early stage founders. Early stage founders specifically. Amazing. I want to know opportunities created in AI. I'm interested in the next generation of AI companies. Obviously, there's so much. many huge private, now SpaceX is public. So like there's a number, a deep mind. There's a number of like first gen AI companies that are huge. But there still is a lot of opportunity. Where are you

Starting point is 01:11:49 seeing the opportunity? There's there's early stage companies that are going deeper in the stack selling to the big labs. There's also niche players. Like how are you viewing the market? How are you mapping things out? Yeah. I'd say overall is we're very early in this wave and we think there's going to be winners up and down the stack. And I think the only mistake you can make an AI is underestimate the size of the wave and think it's binary and outcome. So, you know, we've invested up and down the stack and the foundation model layer, you know, we're investors in Anthropic and up and AI.

Starting point is 01:12:20 And infrastructure, you know, we invested in base time back in 2019 before generative AI was a thing. Today, they're the leaders in inflates, right? Brain trust. I remember in 2023, no one was using the word evals, right? Notion was using their product. And today, fast forward, evals are the core IP of AI. and most of the values using brain trust for it. So we've done a lot in infra and then, of course, a lot in applications.

Starting point is 01:12:42 We're going to see new opportunities up and down the stack. So on the infra side, I think, you know, you guys are talking about agents every single day. There's going to be a new set of abstractions around infrastructure to actually power agents. Of course, inference and observability is going to play a big part of that, but there's more to do there. There's new things in data structures, databases, runtimes, etc. On the application side, I think we're just getting started. It wasn't until, you know, the model set of model releases in December of 25 that you actually had robust agents. And now, like, and I see in our portfolio, like we led the initial round in Resolve, which is an agentic software reliability engineering.

Starting point is 01:13:17 Today, companies like Coinbase, it completely automates on call. So engineers are no longer getting woken up because there's an incident because the Resolve agent fully handles it autonomously. Or, you know, we're in 7 AI, which does the same thing for security teams. Those products are like coming to life because the underlying models are finally there to really support these. these long-running agent workflows. And so you're going to go into different application categories and be able to build new agent off-rank. So I think that's going to be really big.

Starting point is 01:13:43 And then, of course, things outside of software. Like we, you know, we were some of the early investors in autonomy, like Aurora, which is, I think, the largest standalone public company and self-driving. You know, we've led the initial round in, neuro others. We're now going to see a whole new wave of things happening in robotics. And I think the underlying model capabilities and the data sets that we're building are finally going to get us there where we're going to see. where we're going to see like proliferation in the real world economy as well.

Starting point is 01:14:07 And we've made some new investments our still and stealth. We're excited to talk about soon. Yeah, we talked about Aurora yesterday because they bought ATG from Uber, the autonomy group. I'm interested in hearing, are you noticing any categories of company that have shifted from venture backable to more likely to be successful as a lifestyle business? because they are so capital light in the AI era that you, if you have a friend that comes to you and says, like, I want to start a video game company or I want to start a niche SaaS company, you're like, yeah, 20 years ago, you'd need to raise $10 million to rack a bunch of servers. A couple of years ago, you'd have to go through YC or raise a million bucks to hire some software engineers. But this, you can just build it this weekend and go get customers and be profitable tomorrow. And so are you noticing that trend?

Starting point is 01:15:01 How is that changing your investing philosophy or is that just a ruse? I think the lens on whether or not something should raise venture capital is more about the ceiling, not the floor. So I think it's absolutely correct that you can get a lot more done with less capital now. But what's also correct is that the size of the prices that are available on our whole brand around the new fund is the map is blank again because we think AI just resets the entire map. Yeah. The size of what's possible now, the size of these categories is so enormous. that venture capital, dramatic, even if you can be capital efficient and get a lot done on a given dollar, if you can increase the size of your capital base, the aggression and speed

Starting point is 01:15:38 with which you can move is just much faster. And I think it's an interesting kind of observation. You take the last three years, there's a lot of discussion around what you can get done with AI, et cetera. At the same time, the capital velocity in companies is faster and at a larger order of magnitude than it's ever been. But we look at this in our portfolio. you know, we're primarily doing the first rounds.

Starting point is 01:15:59 And the speed at which companies we raise their series A, series B, series C, and the size of these rounds, which often are in the hundreds of millions, you know, very, very quickly. Like, that's an interesting observation. You ask why is that? And I think it's because we're operating in such big, like in such big and new categories and opportunities that the price to be the number one player is so significant that you need to do everything you can as a company. And so if you can be more efficient, the real. lenses like what else can you go do and how quickly. That's why we're seeing companies have much

Starting point is 01:16:31 faster product velocity, have much faster revenue growth. They're spending. They're getting more out of that spend, but they're spending. And in fact, I would say they're spending more in this last three years than in the prior decade. The map is blank. I love that as a rallying cry. At the same time, I see a new market map in every category and it's stuffed full with AI startups and it feels like it's more competitive than ever. I'm interested to know, are there categories that are now more oligopolistic, more, like less monopolistic? It feels like the software 2.0 era was very much, oh, there's a runaway leader in this particular niche and it's winner take all and they're just compounding. But now I've been so surprised when I check in with the third biggest or third most well-funded

Starting point is 01:17:19 company in a particular area and they're accelerating revenue. And they like tripled revenue last year. And it's a great company by historical standards, even though it's like a laggard in the modern era. Yeah, it's a great question. And yeah, it's interesting, by the way, like we, there's all these market maps. People calm these companies as winners. And I think we forget that like the game's just beginning.

Starting point is 01:17:39 I mean, you rewind the clock just 18 months. And you look at what the foundation model landscape looked at at that time. And then you fast forward to today. And, you know, we fast forward another 18 months. and there's going to be more evolution. So I think we all live on Twitter where we're trying to clear everything over like every single minute. Like we should zoom out and remember these things are very nebulous.

Starting point is 01:17:59 But yeah, I think, you know, the difference with AI is the size of the prize, especially when you're automating labor and you're shifting these labor dollars to software and technology dollars is so dwarfed, like, or so dwarfs relative prior software categories, they think you can have more winners that can get larger, much faster. And I'll give you just two examples. In the customer support category, we, you know, led the initial round in Cresta. Cresta's north of $100 million in ARR, you know, growing very quickly doing customer support AI.

Starting point is 01:18:29 There are likely, there's at least two other significant companies in that category, maybe more, you know, at similar revenue scale. And I think multiple companies in that category will get to a billion of AOR in the coming years. And the reason for that is just AT&T alone spends a billion dollars a year in contact center spent. And you extrapolate that across all enterprises. you think about what's addressable. Yeah, it's way different than IT spend, right? Absolutely. Because there was a war for Zendesk and Salesforce had a solution,

Starting point is 01:18:57 and there's a number of previous era, you know, software products, but it's a very different pool of spending to pull from. That's right. That's right. What are your first checks? What have your first checks been looking like? It's a $1.5 billion fund. You're investing.

Starting point is 01:19:15 You want to be doing the first, you know. Two early stage deals. Yeah, just $750. No, but yeah, so how are you thinking about it? What percentage of the new fund is going to be reserves, follow on capital, versus like, you know, net new investments? So, you know, for us, the North Stars, we want to back the most important companies of this era. And we think some of those companies require much more significant checks when they get started because of the people who are starting them, the ambitions, the opportunity. So as one example, you know, we, uh, at, at, uh, at, uh, at, uh, at.

Starting point is 01:19:48 21 years ago, we backed Palo Alto networks when it got started, got started on our offices. I think that company today is almost a $200 billion in market cap. When we wrote the initial check, I think it was a $250,000 initial check. Wow. Fast forward, the founder of that company near Zook left Palo Alto last year. He started a new company with Greylock. Right? That company is called Sylake, right?

Starting point is 01:20:10 It's building a really new important cybersecurity platform. Our initial check, there's $36 million. That's what I figured. That's, yeah, that's what I figured. We want to build the largest company in cybersecurity in history, a $300 billion in our company. We want to back him to go build something, you know, of consequence, and that has a different capital requirement.

Starting point is 01:20:27 And so we have a larger fund, not because we're going to... We just got a goal. Sorry. World comes on. Who scored? Who scored? Spain? Spain just scored.

Starting point is 01:20:38 There we go. There we go. Sorry, we had to cut to the fan cam. I respect it. Anyway, who you got? Are you got in the game? Who's playing? So Spain's up one zero.

Starting point is 01:20:53 I thought France was going to win this easily. Oh, well, Spain's on its area, yes. But you are too, and thank you so much for coming on the show, breaking it down for us. And congratulations for the new fund. Yeah, stoked for you guys. Stoke for you. And looking forward to talking to all the new founders out of the new fund. Yeah.

Starting point is 01:21:09 We'll talk to you. Have a good one. Goodbye. Let me tell you about Cisco, critical infrastructure. the AI era unlock seamless real-time experiences a new value with Cisco. So yeah, what, what actually happened there? I have not been watching the game, but. Yeah, there was a Spain goal, 22 minutes left. Oce Bajel. Okay. One-0 Spain. Was, uh, you thought the P.K. was fair? Yeah, yeah. Very nice shot. I don't know. Yeah, yeah. Kicked Laminia Mall on the, on his, like, side.

Starting point is 01:21:38 It's kind of like a bang, bang play. Okay. Well, our next guest is in the waiting room we'll bring in Janice from Reflection. He's a co-founder, president and CTO. That's his first time on the show. Welcome to the show, Janice. How are you doing? I'm doing all right. Thank you so much for the invitation. Thank you so much. Hopefully we didn't pull you away from the World Cup. I'm not sure if you've been following, but it's one zero in case you're rolling. He hasn't even seen a minute. He's locked locked in. But since it is your first time on the show, I would love a brief introduction on yourself. And then I'd love to hear about the news and the deal with Nebius. Absolutely. So first of all, again, thank you so much for having me. I'm Giannis. I'm the co-founder of reflection.

Starting point is 01:22:21 Before that, I was one of the founding engineers of DeepMind, joined really early, and I spent most of my career that are working on deep-inforced learning research. So anything from DQN, which is the first deep-reinforced learning agent to ever exist to AlphaGo, Alpha-Zero, and I was doing RLHF. I was leading RLHF for Gemini before I left. and left with Misha to start reflection where we're building Frontier Open Models and we want to ensure that intelligence remains open and accessible to everyone. So I imagine demand for the businesses through the roof because you just signed this big new deal.

Starting point is 01:22:57 What's actually driving it? What are the enterprise use cases that you're seeing? Who are the key customers? What's the shape of the customer base? And then why now with this particular deal and why Nebius is a partner? Yeah. Yeah, so I mean, let me just start by saying that, you know, building Frontier Open Models

Starting point is 01:23:16 requires two things, right, requires, like, a lot of incredible talent, and we've been extremely privileged with the fact that, like, many of the best people in the industry have actually joined us to work on Frontier Open Models and work closely with me. So just, like, really like for that. At the same time, the other thing that you need is compute, right? Like, this is what fuels AI research. Like, that's kind of like the thing. that keeps the researchers busy.

Starting point is 01:23:44 So to this end, we actually, like, you know, signed this a billion-dollar deal with Nibius to just, like, get the computer that we need. Congratulations. Thank you. That's amazing. I'm interested in, if we can shift to history for a second, just your reflections on, no pun intended, sorry.

Starting point is 01:24:12 just the progress in computer use recently I saw a demo of Codex and 5.6 soul playing Slay the Spire, this card game that I played a lot of, and I know how hard it is, and it sat there for five hours and played the Daily Challenge. And I'm wondering if are we ahead of your timelines in terms of generalization? What is your overall thesis on progress? Where have you been surprised based on what you obviously had a front seat to a preview of years ago. Yeah, that's a really good question. I think that it's actually like, you know, I've been in the industry for like 15 years. And I've actually like seen the progress that we've actually made in the past 15 years.

Starting point is 01:24:57 And, you know, every time that we felt that we, there was a wall or there was like something stopping us, we just kind of like overcame it almost immediately. So it's kind of like really, you know, this is like the best time for anyone just be doing like AI research and you know, I think that I'm not surprised anymore. I think I've seen so many things in the past like this year so it's really hard to be surprised.

Starting point is 01:25:22 Sometimes this exponential growth, the exponential curve is like really hard for the human mind to just like fully understand it. But, you know, just things just change extremely fast and we should just be really adaptable and really understand

Starting point is 01:25:37 that you know, AI is still on this exponential curve and incredible things are ahead of us. But once you're on, once you're living on the exponential, you sort of internally, like, emotionally operate on the second derivative. And so you're sort of like, yes, this is as expected once you've internalized it fully. But yes, I agree that it's shocking. Can you talk about the advantages and disadvantages between Chinese labs that are making

Starting point is 01:26:05 open models versus American labs, like reflection that are making open models? because I imagine it's like, you know, you might have better access to compute, maybe more capital, but potentially more restrictions around, you know, things like distillation that could provide advantages in some way. But how do you how do you think about that competition? Yeah. So, you know, one thing is that like it's a, it's really opaque exactly like what the Chinese labs are doing like on the ground. some things we know is that maybe there hasn't been aspects of respect to IP and, you know, kind of restrictions in terms of like use of data that we know, as an American company, of course, we are like fully compliant.

Starting point is 01:26:52 At the same time, there are like, there have been accusations. I don't know if they're true or not. But, you know, from like US labs that the Chinese labs are actually doing distillation at like an industrial scale from their models. and that's not, of course, something that, like, any Western lab would ever do. And, you know, there are, like, definitely gains in terms of access to compute or, like, you know, things that we can get access to, like, the latest compute. At the same time, I've also heard that, like, the Chinese labs, you know, have found ways to bypass maybe the restrictions in terms of compute, like, via getting compute from, like, other places. I think that, like, we have definitely the advance of, like, heavy.

Starting point is 01:27:35 the talent here in the sense that the frontier labs, close frontier labs, are based in the United States and like many of these people have actually been to the frontier, they've seen the frontier, and many of them have actually chosen to join us now and just like work on our models. So that's definitely a benefit. Yeah, I think it's like this is kind of like

Starting point is 01:27:58 the world as it is, but you know, I don't think that like the fact that we are a Western lab and we might not we cannot cheat means that like we won't just build the most powerful open models. I think it's actually the opposite. The fact that the closed labs also like never cheated and there are the frontier means that like we have

Starting point is 01:28:16 the talent, we have the know-how and we now have the compute of like all these deals to ensure that we catch up to the Chinese open frontier and after that our ambition is to just like close a gap between close and open and ensure that like frontier intelligence is accessible

Starting point is 01:28:32 to everyone. Awesome. In keeping with bringing access to frontier intelligence to everyone, your former colleague, Demis Hasabas from Deep Mind just today is advocating for a U.S. Frontier AI Standards body, and he specifically says that he wants to apply rules and tests, submit models for testing. that would even include open source models. Have you grappled with that? I mean, you're a large company, very successful, $8 billion as of the last round.

Starting point is 01:29:10 And yet, as someone who can be a little wary of overregulation, I don't want to slow an exciting company down that might not have the resources to staff a huge lobbying group in Washington, D.C. to get open source models approved. So how are you grappling with the idea of as models get more powerful? deepening your relationship with the United States government? Yeah, so I think it's important. As a reflection, we always want to engage and ensure that the models are safe. They are well-received, and they actually meet standards. So we'll just like do whatever is required from us.

Starting point is 01:29:51 I don't want, I want to ensure, and I think that many people in the community feel the same, that there is a frontier open model in the U.S. market. This is kind of the bedrock upon which resets in the research institutions around the country are building their solutions. This is the tools that like developers and like early stage startups used to just like build new products and kind of like drive innovations. So we need to just like be, we need to just ensure that there is like room for frontier open intelligence in the United States and in the Western world. And I think like this would be just a net positive for the society as a whole. So, you know, always here to engage in any way we can, just like from and also like express the voice of people who believe in the open ecosystem.

Starting point is 01:30:39 Yeah. I think my nightmare scenario would be some situation where you're slowed down, but international firms are not slowed down by some weird quirk. And so I hope that whatever happens, we at least get a level playing field for everyone, both close source, open source, but also international. you don't want to advantage a geopolitical rival by accident. But that makes a ton of sense, and I'm sure you'll navigate it all flawlessly. Thank you so much for coming on the show. Congratulations on all the progress. And it's really great to meet you.

Starting point is 01:31:12 Have a great rest of your day. Thank you, too. Thanks so much. We'll talk to you soon. Let me tell you about Railway. Railway is the all-in-one intelligent cloud provider. Use your favorite agent to deploy web app, servers, databases, and more, while Railway automatically takes care of scaling, monitoring, and security. Our next guest is Jack Dent from Chai Discovery, and he's here with us now in the TBP&Lter.

Starting point is 01:31:33 Welcome. Welcome. Welcome. Thank you. Great to be here. Thank you so much. Could you quickly introduce yourself in the company, and then I want to go through the news, but I'll let you start with an introduction. Sure. So I'm Jack. I'm one of our co-founders here at Chai. A Chai word building what we like to call the computer aid design suite for molecules. So think like Photoshop or Blender or SolidWorks, except instead of designing a car, you're designing molecules. These are small collections of atoms, which are often used for things like medicines and that actually go inside our bodies and do things like cure us. And so we operate at all levels of the stack.

Starting point is 01:32:15 We're both a frontier research lab, also a product company, also a bit of a science company, and tie all of those things together to put that piece of software in the hands of some of the largest pharmaceutical companies in the world. So specifically narrow to pharma, but I imagine that you will have applications in material sciences all over the place. But is, is pharma just the best landing zone? Or is that such a deep market that you'll stay there in perpetuity? Yeah, I think pharma is right now where we're really focused. Our models, they work at the level of atoms and molecules, and you also require different categories of models when you're trying to do different tasks.

Starting point is 01:33:00 So it's not like a specialized model that will design an antibody will necessarily, like, out-of-the-box work for material science as well. That's still some additional work. But Farmers also, you know, this is a multi-trillion dollar industry. It's actually larger than the chip industries in revenue in and of itself. And so it's this massive market that obviously does huge amounts for human health, and there's just so much runway to build into that. So what actually is different about the models that you're developing? Do you have the same sort of massive CAPEX around pre-training runs and scale is all you need and you need to marshal all this compute?

Starting point is 01:33:41 It doesn't have a different shape. Is there a different data puzzle that you're solving? how important is your feedback loop with your customers? How does your lab look different than sort of a lab that's focused on coding, for example? Yeah, it's a great question. It's really all of the above. So when I say we're a research company, that means that we actually train our own models from scratch.

Starting point is 01:34:06 These aren't like LLMs that we take off the shelf and fine-tuned some open-source architecture. We're starting at, you know, Pytorch and then below that down, even at the kernel level sometimes, and creating models, which actually look quite unlike, the sorts of models that you build elsewhere. It's sort of like how, if you're training a video diffusion model, that's a pretty different architecture to what you train for language. These just different model categories require fundamentally different avenues of research.

Starting point is 01:34:36 And one piece of intuition here is in the same way that video models sort of think in 2D and they put pixels on a grid. And so, you know, auto-aggressive token prediction with a language model maybe isn't the best fit. You know, our models think in 3D, really. They put individual atoms in 3D space to construct these molecules. And so that means we really need to have a command of the entire stack. And then the data as well, this is not natural language data. It's very domain-specific data.

Starting point is 01:35:05 It's these vast troves of protein sequencing data sets and structure data sets where people look at We've used essentially really powerful microscopes to go and look atom by atom at the structures that exist in nature. And then we also do a lot of data generation in house as well. We throw that off as well. And that's just at the research layer. Then there's a whole products layer on top of that as well. It's almost like we're training clawed as we're also building cursor or cognition.

Starting point is 01:35:37 And so we need to do those things hand in hand. So there's also this feedback loop with the scientists. and are both at the farmer companies, but our users many of whom sit inside the company and dog food and try and push the frontier of these models. So it requires, yes, to be just a plus across both science, AI research and product engineering as well. Please. Have you seen any scientists get a quote unquote one shot in the way that certain vibe coders have? Like staying up all night? Yeah.

Starting point is 01:36:10 Where they're just like staying up all night. Stop, I open with China. We're running at all times. Yeah, because, I mean, it's such an interesting challenge that the labs have faced where you're trying to balance, like, making products that are enjoyable to use, effective. In a weird way, you know, you are optimizing for engagement. If you're optimizing for revenue, just because someone's more engaged, they're using more tokens. But I'm curious if you've seen any signs of that because so far, the labs that have experienced the most. extreme product market fit have gotten to the point where there's this idea of one-shotting,

Starting point is 01:36:45 and then you have to like, you know, align the model better and improve that. Yeah, totally. And actually, you know, maybe it's worth just providing some historical context here on just how quickly the research has moved in this field. You know, a year, a year and a half ago, basically none of this stuff worked. You know, it was, or the success rates were extremely low, you know, 0.1%. And over the course of 2025, these models went from being these research curiosities in that they were maybe interesting things to study in some academic labs, but they weren't really being used in real drug discovery workflows. In July, June July of last year, we put out a paper called Chaitu where the title of that paper was Zero Shot antibody design in a 24-World plane, literally getting at this exact point where you could start to design these molecules without.

Starting point is 01:37:40 needing to fine tune them on a lot of data, you could really just prompt them in the way that you'd prompt an LLM with an input, you know, a target, maybe some disease you're going after, a target that's implicated in that disease. And it would, you know, design a number of candidates that would help do that, essentially. And so, you know, I created some really, you know, interesting situations where, you know, we would go into, you know, a farmer company and we'd be presenting some data. And there's one that comes to my mind. in particular where somebody pointed to one of our slides and says, oh my God, you solved that one?

Starting point is 01:38:14 Did you choose that on purpose? And we're like, no, we didn't choose that one on purpose. Why? And they said, you know, I spent five years of my life working on that target, trying to find a binder to it. So, you know, this technology has really moved beyond, I think AI Android discovery has been in the realm of promise for a really long time where there's been a lot of hype and attention around it.

Starting point is 01:38:38 but in 2025, we really, like, crossed the, you know, crossed the Rubicon in a way. And now these technologies are, you know, actively being deployed in companies like Eli Lilly, Novartis, Pfizer. You know, these are some of the most scientific, highest tech companies in the world, and they're putting them into real drug programs and, you know, making them part of their core discovery engine. And I think that's what might get missed here about, you know, so much has changed in the last year on the technology side,

Starting point is 01:39:11 and it's created this wave of new applications. And what's amazing is the scientists themselves are the most happy about it. They don't love the fact that they fail 90% of the time or that their work. Yeah, or they could dedicate half of their career to one disease and make modest progress or maybe their entire career. Do you think there will be something the music industry is funny right now because every artist is using AI, not every artist, but many of them, both casual artists, non-professionals, you know, amateurs, but also professional musicians are using it, but no one

Starting point is 01:39:50 wants to talk about it. I expect that pharma will be much happier to talk about it, but is that the right intuition? Yeah, I think that's exactly right. I think 2026 is the year where these technologies are going from, being fringe technologies which people are adopting on the side to actually technologies which you know entire discovery programs are are built around and so the you know pharma companies are not necessarily the loudest you know they care a lot about their IP and they you know there's obviously some some alfarin figuring out some

Starting point is 01:40:28 you know an advantage in getting a drug to market faster than someone else so I think that will be lagging and then I think there will also be some time for some of these de novo drugs to get into clinical trials and humans and there'll be validation there still but what's important is you know that adoption curve is is well underway now it's kicking off you know it is the most sophisticated companies and you know some of the stories we're hearing already are just it's just remarkable on the on the business model side you're you're very full stack already you're building the you know the harness the model and then the recent that goes into the model.

Starting point is 01:41:06 At some point, I imagine you'll have a customer that develops a new drug using Chai, and that drug goes on to generate tens of billions or hundreds of billions of dollars of revenue. To me, that's like what success... Blockbuster. A blockbuster drug created with Chai. Depending on how you charge for that, it's possible that you end up capturing... 200 bucks a month. Yeah.

Starting point is 01:41:31 Just some like very minimal amount of... amount of value, which is good. Every company, you know, you want to capture less value than they create. But at some point, would you consider or have you considered a model where you're a true partner to these companies and you're doing sort of joint ventures where you're basically giving them access to the product in exchange for long-term upside. Yeah. That traditionally has been the model. If you look at how biotech deals tend to work. A lot of them includes things like royalties and upside sharing in the drugs. You know, this is really just all partner-driven for us. You know, what does,

Starting point is 01:42:12 you know, we live to serve our partners, really, and what do they want to do? And what they want to do right now is a lot of them want to take our technology and deploy it, you know, fairly broadly across the portfolio. And that, that means that, you know, we get rewarded financially for that. we also can reinvest some of the money they're paying us into building even better models for them. And so that way of doing business is working well for us right now. There may come a point where some pharma companies turn around and say, hey, we'd love to do a joint venture or go 50 on this thing with you. And I think suddenly open to that, but really it's partner driven for us.

Starting point is 01:42:52 And we're trying to, you know, what we see ourselves as, as this core platform layer, which enables their discovery engines. And if you look at the top farmer companies, they might spend $5, $10, $15 billion a year in R&D. And so that's not even on what they're spending on royalties or anything. That's just their R&D costs. So it's a massive market to be building into. In fact, it's even larger than some of the money that's spent on semis R&D every year.

Starting point is 01:43:27 Farmer is one of the most enduring and durable categories of applied R&D spend in the world. That's a good point. We have some new partners on the financial side. Tell us about the round. I want to hit the gong. How much did you raise? Yeah. So we raised 400.

Starting point is 01:43:46 Who came in? Everybody. Everybody came in. Yeah, we raised $400 million at a $3.8 billion valuation. We're super lucky to be partnered with index, Kleiner Parkin, Sequoia and Dimension were the largest checks in the rounds. And, you know, it's an all-star cast. Some people we've known for very long time.

Starting point is 01:44:11 Nina from Index, Ilya from Kleiner, Pat Grady from Sequoia and then Zab, mainly. But really the whole Dimension team, you know, they're all, you know, it's rare to get this caliber of investors on a cap table and especially rare in one round. So we feel incredibly fortunate. Well, congratulations and thank you so much for coming on the show and chat with us. This was fantastic. We'll talk to you soon. Have a good rest of you day. Goodbye.

Starting point is 01:44:38 Let me tell you about the New York Stock Exchange. Want to change the world? Raise capital at the New York Stock Exchange. I think Chai Discovery might be there any day now when you're putting up multi-billion dollar rounds. Anything's possible. Our next guests are Evan Burns, the CEO and co-founder of state affairs and Jamie Seltzer, the co-founder of state affairs. Very excited to be joined by both of them.

Starting point is 01:44:59 How are you guys doing? We haven't seen each other in, what, a year and a half, Hereticon. I think there was the last time we hung out. How you doing? Welcome to the show. Quick introduction to yourself and- So great to see you guys. Good to see you guys.

Starting point is 01:45:13 I'm happy to be here, guys. Jimmy, you want to go first? You got it. Yeah, I'm one of the founders of state affairs and also at GP at Lightshed Ventures. I fashioned myself as a poor mandelians or a poorer man, Josh Kushner, doing kind of both. But, yeah, founded at State Affairs with Evan four years ago. Very cool.

Starting point is 01:45:34 And you're an absolute dog, a very humble one at that. And a dear friend. So it's great to see you here at long last. Evan, over to you. Hard to follow that. Entrepreneur, most recently built and sold, finished long drink. I should have come on here when we had that exit a couple months ago. boys were so ready to crack them open in the in the studio today they were they were they wanted

Starting point is 01:45:57 us to be they wanted you guys to join and we go yeah they were like this is huge anyway sorry state affairs yeah yeah and so also the co-founder in ced state affairs yeah and uh just set the table on like the shape of state affairs business why it's unique how like the footprint the strategy because it's fascinating i think uh under discussed yeah jamie why don't you tell me about how you didn't even mention or tell me to invest until about a couple years had passed and you guys were at tens of millions of revenue. No, I'm just kidding. Evan, go for it.

Starting point is 01:46:33 I think Jimmy was worried about that when we were coming on here. I don't know. We might be asking for this. We had to do something different than everybody else doing finance. Of course, we picked this. But the problem that we saw and that what we're focused on every day is, and it's probably true for most of your guests. These policy and regulatory markets affect so much of what companies do, but everybody just acts like they're a thing that have to happen to us. We're all reactive to them.

Starting point is 01:47:00 So, Jimmy and I had this idea, like, what if we could build a platform? Kind of like Bloomberg. Instead of focusing on financial markets, we're just focused on building a knowledge graph around the day-to-day movement federally in all states and eventually cities around these policies that change, around regulations. And in the day, we think they affect most businesses more than what the financial markets do, but if you're a leader of a business, how do you pay attention to them? How do you hear what the discussions are about SNAP benefits access or about AI data center building or about public safety tracking? Are we going to have tracking or not? Like, these things are massive. And I think most people in America have just decided, oh, they are, these things are what they are.

Starting point is 01:47:35 So we said, let's try to build something around that. And so how much does this look like a media business? How much does this look like newsrooms across the country? Roll-ups? Are you hiring people, are you acquiring whole businesses, walk through how you actually get a broad footprint out there to track all those topics you mentioned? Yeah, I think what we didn't realize getting into this was if you look at the legislative process of making policy, there's so many pieces to it and so much data to it. So you have all the hearings that happen in every state. You have all the bills that are introduced.

Starting point is 01:48:07 And every bill, if it even makes it, is going to have hundreds, if not thousands of data points that change along the way, whether it's the wording or the wording or the, the votes or the committees or the sponsors. And of course, we did actually build out journalists, a team of journalism. And it's very important that they're nonpartisan going and doing coverage, what's happening in the state houses also asking questions around this policy and regulation. So it's that whole mix together that becomes this knowledge graph that enables the users to plug in and say, okay, what's happening today with Snap access benefits?

Starting point is 01:48:36 What's going to happen next year around GLP1 access with Medicaid? Like these things are changing kind of by the day, but you might not see it in a law for another six months a year or two years either. And so for the, for the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the experience of the customer was a subscription and then, what are you building? Well, the, the first thing that we're able to do is map the relationship. of all of these different data sets using AI. And so sometimes something will happen in one state and it can affect, you know, states that are tendentially down.

Starting point is 01:49:24 And so without basically having built out, you know, through journalism, we have on the ground people that input data that sometimes doesn't make it to the government websites, budgets, bills, hearings, fiscal notes, executive orders. We're mapping the relationships of all these things through our models and we're finding net new insights for our customers. Yeah, talk about how legislation and ideas flow between different, different, you know, state and local governments. We were covering, you know, New York's data center ban or moratorium earlier today. We were talking also about how Paramount and the Ellisons are up against a number of different AGs. And so it just feels like you guys could get to a point where you can almost forecast the way that policy is kind of shifting. and moving around the country? We do do that to a certain extent right now.

Starting point is 01:50:19 I don't say we do predictive, but we do model the momentum of how bills are likely to get picked up or the likelihood of a certain policy picking up more and more steam in a particular state. So we basically have, our models have 150 unique data points that we source from on a daily basis that are kind of constantly resetting the momentum on these. Historically, big companies, let's say Fortune 500s, like how many, how many, how many individual, what would the teams look like, you know, the government affairs teams look like to try to get the level of coverage that you guys are now offering?

Starting point is 01:50:59 I imagine they're buying data, working with maybe more local companies, but, but the pitch now is like, you know, one platform, access to intelligence across tons of different, you know, counties and states and. and things like that. But how are you pitching it? I think the main thing you have to, when we talked to all these folks, when we've sat down with a ton of Fortune 100 brands and have brands like MasterCard and McDonald's and Walmart that are already subscribers,

Starting point is 01:51:27 but the problem of what everybody is facing before is they've got like lobbyists or like old school data platforms that are often like much slower than real-time information. So you're waiting for a firm to send you a PDF deck from like something that happened two weeks ago and you've got 50 different states,

Starting point is 01:51:44 So it's different formats. And so the ability to plug in and understand real-time movement on what's happening with discussion around, you know, data center licensing or power build-outs. It's very tough and it's late. So we want to switch people from being kind of late to the game to understand what's even happening to proactively involving themselves in the democratic process. And ideally trying to get their voice heard involved before the bills are even introduced, let alone waiting for them to get all the way to the governor's desk, which happens a lot. We were talking to the CEO of a publicly traded company that, I think the, I guess you've been on here. I won't say his name,

Starting point is 01:52:16 but their company business model was basically banned in a top 15 state. Got to the governor's desk. And this, you didn't even know about it. So got to the governor's desk until their business model would have been banned. And then they had to pull all this very painful,

Starting point is 01:52:29 very painful strings and favors to kind of get it fixed at the very last second. But if they had just been involved a year before, they'd have seen it coming. What does your guys' team look like? I imagine it's extremely distributed. Well, we have about

Starting point is 01:52:46 187 employees. It's about half editorial, half tech and sales. The editorial newsrooms are on the ground in each state. So yes, they are distributed. We do believe that being in the room is the difference maker on a lot of this intelligence from an editorial side. And then engineering, we're in DC, San Francisco, and Miami. Are you seeing acceleration or value in sort of like vibe coding integrations to government websites to scrape and organize data? I think it's very difficult to do that. It's the final. That'll be AGI.

Starting point is 01:53:29 We need super intelligence to get filings into a database. However, unsophisticated federal government websites are, state government websites are that much harder to navigate. I think like only two of them have APIs. Okay. Just a level set on where they're dealing with. And a lot of this the syntax on how they label their data is very different. And so there's like a huge cleaning process in Ohio, for example, if a bill has an amendment to it, sometimes it never goes onto the government website.

Starting point is 01:54:01 You have to go into an office in the state, go and get it. There's this example we love to give in North Carolina that if you don't watch a Senate floor committee hearing, you have the only way to go and get a recording of that is to go into the congressional library, pay a dollar and 25 cents, get it burned onto a CD-ROM, and then you get custody of it. So, like, yeah, it's, it's, it's, uh, pretty antiquated. Yeah. And you have to, and you have to information every day, right? So we made the joke before, like, we all think about the Roman Empire a lot, of course, but you only have to label the Roman Empire once. Like, it's done. It's over. And like, you've got to get the information and data around what's happening in government

Starting point is 01:54:40 legislation every day. Because what the process was last week has changed and whatever today happening today is the most important. What do your customers want you to do next in terms of coverage? Is there a demand for international coverage or even more local, like, you know, like HOA or something? I don't know how deep you could go. Like how low, how low level can you go and then how high? If the mayor in this town of 5,000 people sneezes, I want to know. I want to know.

Starting point is 01:55:09 For the right price, we can definitely figure that out, you know. I don't know about HOA, though. The sanity equation. match. If you look at these major, we have international customers, Fortune 50 brands, you name it. The thing that they're trying to figure out, again, is this real-time movement on things that have billion dollar or tens of millions of dollars affecting their business. So for sure, like we do federal now, we do state, we'll get into city.

Starting point is 01:55:32 There's a huge ask for international because if you've already got your executive team and government affairs leadership on us and you've got U.S., why not Canada, why not Australia, why not UK? So the goal to do this daily, build this kind of daily knowledge graph. and platform for sort of all Western democracies, but we're definitely starting here at the U.S. That's very exciting. Well, you raise some more money.

Starting point is 01:55:50 Tell us about the round. How much did you raise? 70 million. A bunch of nobody's, right? Who participated? How many times a day do you get to do that, by the way? Today is like five or six. It's great.

Starting point is 01:56:07 Yeah. You got to warm it up, too. Sometimes we'll hit it twice. I'll all hit it for you guys, too. Who participated in the round? Who participated? It's been primarily CoSlai and Founders Fund. Those guys, they needed a word.

Starting point is 01:56:22 Never heard of them. Never heard of them. Glad you guys are putting them on the map. Yeah, yeah, it's good. Thank you for what you're doing for them. So great to have you guys on and incredible progress. I'm glad you're talking more about what you're doing because I've been getting the updates for years now. And yeah, I know you guys would only start talking about what you're doing once you were confident you were going to eat the entire.

Starting point is 01:56:45 entire market. So, great. Congrats. We'll talk to you soon. Have a good rest of your day. Goodbye. Cheers. Let me tell you about console.com. Console builds AI agents that automates 70% of ITHR and finance support, giving employees instant resolution for access requests and password recess. Our next guest is Tyler Page here with us in the TBPNLT realm live. Thank you so much for taking the time to come on down and chat with us. Of course. Welcome to the show. Please, why don't you kick it off with a little introduction on yourself for everyone who's watching? Sure. I mean, look, long-time listener, first-time guest. So thanks for having me, excited to be in studio for that.

Starting point is 01:57:21 Yeah, look, I'm the founder and CEO of Cipher Digital. We're a developer of AI data centers, a popular trend these days. Over the last year, we've really completely transformed our business. Once upon a time, we were a Bitcoin miner. Also a data center building business, actually a lot closer to building AI data centers than I think is in the popular imagination. but we've really had just a complete transformation over the last 12 months. We've signed a series of leases with hyperscalers or with companies affiliated and backed by hyperscalers. We're currently building 700 megawatts of AI data centers at three sites in West Texas. There we go. That was Bonham-esque. That was awesome.

Starting point is 01:58:10 Yeah, so look, we're really busy with that. and then we have a massive development portfolio beyond that. So we've at this point sort of proven that we can sign these leases, we can construct these data centers, we can finance them, also a really big part of it. And then we have a really big development portfolio. So the total portfolio at Cipher is 4.2 gigawatts. Wow.

Starting point is 01:58:34 He's going back. It's even louder. It's even louder in person. Yeah. That's just really awesome. Yeah, so, I mean, look, we're on the path to sort of rinse and repeat on that business. Demand remains really high. Of course, everyone in non-podcast media will point out everything's a bubble or there's challenges or whatever.

Starting point is 01:58:58 And, you know, we can run through those things. But, you know, right now, listen, the demand remains really high. I don't see any signs of that pulling back if you've got power available in the next couple years. Yeah. And it's a really exciting business. I mean, honestly, with all the things going on in the space, Cipher lives in a little bit of, you know, it's got a unique structure that we're really doing co-locations. So building like a full turnkey AI data center for a multi-decade lease and handing over the keys. And on a spreadsheet, truthfully, it's a pretty simple business if you can execute in the real world.

Starting point is 01:59:34 It's real estate development. It really is. And there are so many interesting things going on in the space. and there's lots of people trying to be more vertical up the stack and build a software layer, and that's all super cool. And there are big prizes to win there, probably. But I love our simple rinse and revenue business. You're in the warm shell business.

Starting point is 01:59:52 How are you thinking about site selection across the development portfolio and new opportunities? We had the New York State Data Center moratorium get announced this morning. I would expect other states to follow suit. you guys don't want to invest, you know, tons of time and resources into a state that could eventually say, like, hey, you just got to stop what you're doing. Yeah, I mean, listen, so I'm actually based, our corporate headquarters is in Midtown Manhattan. No way. None of our data centers are anywhere in the state of New York.

Starting point is 02:00:27 I think that's a little bit of a hangover from our days, starting as a Bitcoin miner, when not only did people not want to give you the power in New York, but they also decided they didn't like Bitcoin. Oh, interesting. And I think the biggest data center in New York right now is still a Bitcoin miner or they were and they've been pivoting. I think it's pivoting over. I think it's one of our good friends and rivals. But, you know, look, I think there are going to be layers of challenges from the federal level to the state level to the local level anywhere in the country.

Starting point is 02:01:02 Of our 10 sites, nine are in Texas and one is in Ohio. Texas is generally known as a very kind of low regulation business-friendly state, very entrepreneur-friendly. That said, the exact same concerns about data centers exist there, and we spend a lot of our time trying to be good neighbors and good partners and deliver the message of how it's going to be a wonderful addition to the community when we come join. But quite understandably, people show up, I mean, it is outside of the universe of the savvy listeners. to your podcast. Yeah. There's a lot of, like, naked dislike of data centers. Yeah, you see it in the polling data, too.

Starting point is 02:01:42 But, you know, it's interesting. Even as recently as yesterday, we had folks down at a local hearing. And I completely understand why people show up and they're not happy. Because I've heard this stuff's terrible. Totally. And it's going to end the world. And, you know, it's going to end things that are creative and everything is going to be an automated chatbot. And, like, I don't like anything about that.

Starting point is 02:02:04 And then you get all the way to the spectrum of frankly, just people don't know what happens in the building. So you get questions like, is this going to harm my cows that are next door? Or like, I mean, someone asked, like, is my pacemaker going to have a problem because of the building? And it's not for the record. Yeah. But, you know, so. Well, yeah, there's no, there's no immediate upside to them often. And then there's potential downside like noise and energy prices and things like that.

Starting point is 02:02:31 What have you thought about certain proposals or ideas around doing direct payments to people, you know, in towns or counties that are going to have a data center developed and they're thinking, well, I don't, what's a benefit to me other than some construction jobs and a handful of jobs and local tax revenue, but it's not as like direct as like, you know, cash coming into your account? So that may be where it goes, Jordy. I mean, I think there's this needs to be answered on a couple. levels. There's like a really, really high up public policy question about do we have the right tax regimes and ownership regimes and large language models and government ownership and things like that. And that's what I mean. Like it goes through all the layers down to the state. I think what I'd start with is just number one, back to the big point about this scary new neighbor you might have. I mean, I try to focus very much on starting with what happens in these buildings.

Starting point is 02:03:27 And, you know, I'd say, look, we're a pretty entrepreneurial-driven culture. It's Cipher. But some people, especially a lot of younger people, a little bit more mission-driven. And I point out, like, you guys are racing on this construction project. And that literally might be the building that has the breakthrough and research to cure cancer or dementia or something like that. Or we've got, you know, one in every five employees at our firm is a veteran. And I point out, like, we may have work that goes on in there that saves our soldiers' lives. So part of it is just starting there.

Starting point is 02:03:58 To get to your actual question, though, about like money sharing, I'd point out there's already a fair amount of framework in place that envisions this. It's not exactly the giant AIAI buildout that's happening. But, like, for example, in Texas, we will pay tens of millions of dollars a year to the Texas public school system. Yeah. We are the largest taxpayer in the counties, typically, of our data centers. And then we try to go above and beyond that to do a fair amount of community outreach. So in one of our locations, we're refurbishing the small hospital there.

Starting point is 02:04:30 We're buying them a new fire truck. We're rebuilding the playgrounds and the pools, little things like that. And having job there. Virginia has an example of a state that benefited from tax revenue as the AWS campus built out there. And a lot of local people that live there have lived through the data center boom and seen lower taxes on their balance sheets because of that. Yeah, I mean, listen, affordability is a really big political topic right now. And so people say, well, wow, my electricity bill's a lot higher. Must be the data centers.

Starting point is 02:04:59 Sure, sure, sure. And it's sort of like, well, we printed an awful lot of dollars starting five years ago. And we've had a couple wars. And there's a lot of inflation. And so it's not really the data center. But, I mean, I think, look, we try to be very front-footed on that. We do not want to raise local ratepayers bills. By the way, all the regulators in Texas feel the same way.

Starting point is 02:05:18 So, like, that problem will get addressed. Yeah. I really think it's the big picture thing of, like, this is something you should want in your community. Sure. You know, it's a big warehouse that's air-conditioned and full of computers. Yeah. It's not, you know what I mean?

Starting point is 02:05:32 And where we're building them, and it's really, it's interesting, it's we've gotten to be a bit of a disruptor to the traditional data centers, like in northern Virginia. Sure. When we started our pivot, we almost had an unfair advantage from being a Bitcoin miner. Because when you're a Bitcoin miner, the business doesn't work on the spreadsheet unless your power costs are really low. Yeah.

Starting point is 02:05:53 And where are they really low? In really remote places with a lot of generation and typically not a lot of demand, like not a lot of houses. So if you look at just the map of Texas, most of the people live in the east, there is a ton of generation in the West. You can't ship the electricity that far. And so it's really cheap historically in West Texas. When we started having this idea of like, wow, look how fast, you know, chat GBT is taking off. And look at all the implications for how many megawatts you're going to need at a data center. we said, well, surely they're going to have to draw the conclusion that everyone's going to have to move to places like West Texas.

Starting point is 02:06:28 And the entire incumbent data center industry was like no hyperscaler will ever sign a lease at those locations. This is as recent as like a year and a half a year ago. And the floodgates really broke up. Just because it was a hassle and they'd want to just locate around their existing? I think they were just using pattern recognition where they're like, I've been in this business 20 years and no one's ever signed a lease out there. And I think, and then there was a second question about, like, well, is latency really bad out to West Texas because it's a long way away from the city.

Starting point is 02:06:59 But the truth is, there's a big fiber line running out there, and it's fast enough. Yeah. You might not do traditional cloud work out there. But even Northern Virginia exists because everyone went there 20 years ago and then built out all that infrastructure. Yeah. I can tell you because we're the tip of the spear, like all these guys are coming to West Texas. our portfolio alone is almost as big as all of Northern Virginia.

Starting point is 02:07:25 So, I mean, I just, I think this is kind of the next thing that's going to happen when people, the sort of next skeptical thing about locations like ours is, well, we're at this really funny time where there's no power available. And so there's a ton of demand. And so people will go to these places, but that's going to be like a dinosaur relic at the end of this lease in 15 years. and we are 180 degrees opposite of that. I actually think the cap rates will be lower. That will be a more valuable, like, terminal value for a data center at the end of a lease in West Texas

Starting point is 02:07:58 because of what West Texas will become, I think, over the next decade or two. It feels like when new data centers come to town, there's like a suite of questions that local residents have. everything from aesthetics to power rates to water usage to sound to air quality. What of those five have, you know, solid regulatory frameworks in place where you can go and say, okay, we did the EPA test and we passed and so we're good? And which ones are more subjective? So it really depends, which is an unsatisfactory answer. But yeah.

Starting point is 02:08:40 I think we always start on the power. side. Okay. And so if you look at Urquhart and the way they interconnect large sites, that's generally a low regulation zip code state. And so what I'd say is you need to address all those issues. There are some local permitting requirements around them, but I'd say it's more about the like what issues could be raised. There's no real framework of we'll just hold up the noise permit. Sure. Because there's a lot of oil and gas

Starting point is 02:09:13 and like industrial things and places we're building. But I would say probably in our experience, of course people care a lot about affordability, so we need to discuss that. I think water at our locations

Starting point is 02:09:25 tends to be the biggest issue. Sure. You know, they say I think whiskey is for drinking and water's for fighting in some of the places out there. Just it's dry.

Starting point is 02:09:37 But what's interesting is, and I know you guys, I've talked data centers a lot on here before, but, you know, with modern closed-loop systems, it's much less, really don't use that much water. And I think the other thing is you can innovate. So there's actually a lot of like brackish non-potable water underneath the dirt in Texas. And so you can build facilities to filter it and use it and actually help the aquifer. So, you know, I generally think all these kind of growth issues are challenging. but they're all solvable.

Starting point is 02:10:12 Yeah, it feels like a meat in the middle here is instead of jumping straight to like data center ban, you're focused more on what is the decibel level that is acceptable in this city for any building. Right. What is the power consumption for any building? What is the impact on the water supply for any building? Right. And then that framework.

Starting point is 02:10:30 So then if somebody shows up and they're just like, yeah, I have a house where I'm going to be blaring music. It's like, yeah, that can't happen in this neighborhood either because we've determined this. And then that's applied broadly as opposed to just narrowly targeting that. Well, what I'd also point out is, like, all of those same objections could be raised about almost any industrial build. Yeah, for sure. So, of course, I mean, if you go to the places where we build our data centers, we own hundreds of acres. And in some places, you can see to the horizon in all directions.

Starting point is 02:10:57 Sure, sure. So I'm really not too worried about, you know, we'll be cognizant of measuring the decibel level at the edge of our property. But, like, I'm not worried about anyone hearing it. Sure. I think it's going to vary by jurisdiction. If you try to plop one down in a neighborhood or something, that's not what we're trying to do. It seems a lot of them have sort of like grown over time where there was, it made a lot of sense to co-locate some data center for delivering Netflix to a local neighborhood. And then the place just got upgraded and upgraded and upgraded until it's like running diesel generators 24-7 and then people are annoyed.

Starting point is 02:11:32 Yeah. So having to creep up on you is more of a problem than like the new project coming in with the data. dedicated. I think this is like any industrial build, though, where you've just got to strike the right balance. It gets back to what you said. Like, maybe the end policy solution is a different way of taxing, regulating, sharing the income, whatever.

Starting point is 02:11:54 And we will certainly be good citizens. It's not necessarily, it's not even necessarily like more dollars that are being shared, but it's like how you share the dollars. Because, again, like money going to someone's, you know, city feels a lot different than money going directly into someone's pocket, right, that they can use to pay their bills. Walk me through your capital market strategy when you're working on a new site, new project. What does your road show look like?

Starting point is 02:12:24 We're familiar with like a series A pitch, series B pitch, even an IPO occasionally, but you're talking to private credit? Are you talking to real estate investors, banks, debts? Walk me through the whole picture of like who you're calling, who you're pitching. Who's around the table? Just in broad strokes. Sure. So, I mean, high level, the sites we're developing, and again, this is some of the most lucrative real estate development in the history of real estate development. We have purchased these sites typically really cheap. Yeah.

Starting point is 02:12:52 Like a couple million bucks. For a hundred acres? For the land is almost secondary. It's getting the interconnect for power. So the price has gone up like per megawatt. But for example, we're building a 300 megawatt site right now for a, um, for AWS, and we paid like $7 million for the site three or four years ago. Wow. I mean, it's been a while.

Starting point is 02:13:16 Today, that would be hundreds of millions of dollars to sell it. And we own lots of acreage around that. So back to your question about the model. So typically we will try to find a good deal, harder to find these days, but we have a pretty big portfolio. Like I mentioned, it's closing in on the size of Northern Virginia. So it's pretty big to still be developed. Next phase is we want to shorten the development timeline as much as we can, and that typically will be an early equity investment.

Starting point is 02:13:42 So the longest lead time item to build one of these things typically is the high voltage to mid-voltage conversion infrastructure, the substation. Okay. And that might be like 18 months to get one and call it $100,000 a megawatt. So 300 megawatts, 30 million bucks. We'll get that done, and we'll do some early civil work to get the same. site, like the timeline to build shortened. That's currently at least, you know, who knows if we evolve over time, but currently at least that's where we stop generally our equity investment until we find a tenant

Starting point is 02:14:18 that's interested. That's very hard. It takes forever. Negotiate for months and months, hundreds of pages of documents. But if you get, let's say, a hyperscaler long-term lease, at that point, they will be very opinionated about the particulars that they want for that site. that's a very iterative process with our engineering team. You figure out exactly this is the style they want, takes all these boxes.

Starting point is 02:14:42 At that point, if we have a signed lease, we will try to debt finance as much as possible. Are you buying the actual GPUs or is the hyperscaler? No. To this point, that business has been less interesting to us. It's not very interesting. But the business returns, the ROIs, the piece we see the best, certainly risk-adjusted return and for the last year or two, frankly, just the best absolute return, is building everything down to the GPU, basically.

Starting point is 02:15:13 So, wait, wait. So, yeah, walk me through exactly how far you're taking it. So the building goes up. Yep. The polished floors are in? Yep. Air conditioning. Yeah, we're bringing cooling everything down to the rack.

Starting point is 02:15:25 Okay. They're going to pretty much wheel in the rack. Got it. Okay. Connect the various connections. And then. But water lines, power lines. Yep.

Starting point is 02:15:33 All of that. Chillers. Down to the rack. Yeah. It's a very, like, everything ready to go. And the reason why, by the way, on a long-term lease, right, figure they're going to recycle those racks probably twice. Sure.

Starting point is 02:15:45 Yeah. So, like, a lot of the modern design and iteration is, how do we build this site to make it as easy as possible to not be outdated when we want to change the racks? And the racks are going to be, like, it's going to be way more rack density. I don't know. They might replace them in five, six years with one megawatt racks. You might be 120 kilowatts or something now, and it's going to be way more dense.

Starting point is 02:16:08 And so, you know, high level, you have to bring basically, you know, electricity and water and air into the building. You have a very big open building, kind of like a lot of these types of studios. Like an ultradown. Yeah. Fantastic. And then the ability to dial down those various valves and so forth as you get towards the rack. Yeah. And probably the floor space shrinks over time.

Starting point is 02:16:32 And you have cool ping pong. You open the podcast studio in the other end of the other end of the data center in a few years. So just because I didn't finish it. So then we'll go debt finance it. We have gone to the high yield markets. We've raised a couple billion dollars at about 6% in change. So amazing. It's a really high LTC.

Starting point is 02:16:54 So the market's wide open. That's great. Does your team look like a private equity fund with a bunch of people, sitting at desks in front of spreadsheets, and then you call people to actually go and build the building and they're off your staff and you're hiring construction firms, or do you have sort of, you know, guys who can work a shovel on staff? I think it's a really weird company. Like I tell people, so I started the company in my attic during COVID. So we've had to hire like every person knew how to do something better than me at some point and then that's cascaded down. We only have about 100 employees at this

Starting point is 02:17:31 point. It's a very unique firm in that it's a little bit like a Venn diagram of, yes, a finance sort of structuring spreadsheet person. Project management. Yeah. That type of stuff. Let's call it a technology firm to figure out a lot of what needs to be done. Like networking and stuff like that. It's not exactly the industrial side of construction. And then the last part really, and like the most populated part is the more industrial piece. We do in-house, project management and most of the procurement activities. We externalize the like trade work. Sure.

Starting point is 02:18:08 So if there's... So you might pick the transformer to buy, schedule it for shipment, but you're calling a truck and company to bring it out. You're calling other people to unpack it off the truck, planted, bolt it to the ground, do whatever else they need to do. We have an external EPC that really brings all those trades to the sites. Got it. We have 1800 people...

Starting point is 02:18:25 What does APC stand for? EPC. Oh, EPC? Yeah, sorry, engineering procurement construction. Got it. Right. So, sorry, that jargoning on you. Yeah, so if there's 1,800 people on the site, maybe five of them are Cipher employees. Yeah.

Starting point is 02:18:40 The others are like the staffed up folks from the outsourced provider of a lot of that trade work. Do you like railroad analogies to this business? Actually, it's the best analogy. More than oil? Yes, and I'll tell you why. because it's this, the buildout of this industry is so tied to capital markets. It's one of the reasons why we have such a New York nexus. Sure.

Starting point is 02:19:03 Like, honestly, even in Bitcoin mining, that was a big part. We went public as a way to raise a bunch of money in a business that's hard to, like, get the CAPEX for. All the hyperscalers are now doing the, like, varsity version of that with big debt offerings and so forth. But I like the railroad analogy because the modern capital markets were kind of created because of the railroads. Like there wasn't enough bank lending in the world to get them built. So the idea of like buying equity shares in a project is kind of the railroad. So that's why I like that one.

Starting point is 02:19:36 None of them are exactly perfect, but that's closer than any of the other ones I can think of. Yeah. Jordy, do you have something else? Sorry. We like the railroad analogy minus the, you know, massive bus. So true. I actually haven't studied the railroad boom and bus. as much as we should study i mean it was a very long long period of history yeah uh fascinating well

Starting point is 02:20:00 thank you so much for coming yeah great to have you here in person great to see great to see i love going a level deeper like this this is fascinating uh yeah please send anyone to us send anyone on your team our way when you have news uh and congratulations on everything that's going on we will thank you so much yeah great to have you have a great day congrats on the podcast thank you much hang out for you're going to close um let me uh On, before we jump, I got to talk about my dear friend Brandon. Jacobi, who I saw in the chat earlier, launched his new studio, a multi-disciplinary design practice for those who challenge the boundaries of technology.

Starting point is 02:20:41 He combined a Star Wars intro style video with a barrel, a wave. A barrel? Oh, cool. Okay, I'm visualizing that. I think he made this for us. Okay. Do you want to pull it up? There we go.

Starting point is 02:20:59 There we go. Look at this. Wait. Motion design. Oh, interesting. Yeah, this is both of us. Our interest. Yeah, this is perfect.

Starting point is 02:21:08 He made the launch video for an audience of two. For some reason I was imagining the text curling up like a wave and it being sort of hard to read, but this is much better. I love it. It's a good statement. This is a mission statement. This is an essay. worked together for for a few years and he was doing this he was one of the first personnel news we did on

Starting point is 02:21:29 the show we we tracked his move to X the everything out but anyways he's been doing this kind of work forever he was a design lead at at X as well as cash app as well as my last company and he's incredibly talented so he's open open for business fantastic that's our show folks let me tell you about public investing for those to take it seriously they got stock options, bond, crypto, treasuries, and more with great customer service. And that is our show. We'll see you tomorrow at 11 a.m. Sharp. Leave us five stars on Apple Podcasts and Spotify. Sign up for our newsletter at TBPN.com. And we will see you tomorrow. Goodbye.

TBPN - IBM Nukes, Demis Govt Plan, Paramount WBD Deep Dive | Dylan Byers, Noah Schochet, Saam Motamedi, Ioannis Antonoglou, Jack Dent, Evan Burns & Jamie Seltzer, Tyler Page

There aren't comments yet for this episode. Click on any sentence in the transcript to leave a comment.