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Thank you. Hang out. We're going to close out. Let me on. Before we jump, I got to talk about my dear friend Brandon Jacoby, who I saw in the chat earlier, launched his new studio, a multidisciplinary design practice for those who challenge the boundaries of technology. He combined a Star wars intro style video with a barrel. A wave. A barrel. Oh, cool. Okay. I'm visualizing that kind of. I think he made this for us. Okay, do you want to pull it up? There we go. There we go. Look at this. Wait. Motion design. Oh, interesting. Yeah. This is both of us, our interest. Yeah, this is perfect. 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 a few years and he was doing this. He was one of the first personnel news we did on the show. We tracked his move to X the everything but anyways, he's been doing this kind of work forever. He was a design lead at X as well as Cash app as well as my last company and he's incredibly talented. So he's opened open open for business. Fantastic. Well, that's our show folks. Let me tell you about public investing for those who take it seriously. They got stocks, options, bond, crypto, treasuries and more with great customer service. And that is our show. We'll see you tomorrow at 11am sharp. Leave us five stars on Apple podcasts and Spotify. Sign up for our newsletter tvpn.com and we will see you tomorrow. Goodbye.

David Ellison has had to jump hurdle after hurdle to try and get this deal done. Obviously, $111 billion deal, bring Warner Brothers Discovery into the fold with Paramount. And the last hurdle, he might face some challenges in the uk, 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 AG Rob Bonta, former. 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. 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 pick your brand. Netflix, YouTube, TikTok, Apple, Amazon, the list goes on. And so what Bonta and co are doing is sort of presenting this 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. The notion that somehow a combined Paramount, Warner Brothers, discovery, it combined CBS, CNN combined, GoT. 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. And 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. And so the zoo.

IBM is absolutely nuking. The stock is down 25%. Let me see if I can pull this up. Boom. IBM. Well that is a crazy chart. What is that? That's 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. Are you going to be a winner or a loser? Are you going to get steamrolled, slopped? Something like that. But it's been doing well up until today when the company re reset the narrative around their server business specifically. So the high level reason that IBM is not well positioned in the token path, to use the Brad Gerstner and Gavin Baker parlance, is that a 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 interesting business with a great name. International Business Machines. The first business machines they made were punch card systems. They made clocks like it's like you're running a business, you need a machine, you're need a great clock, you're going to need a clock. No, that really was part of the business. Not just any clock. Like a clock that works really well. That's right. Professional clock Clock Pro Max that keeps you on time. Exactly. Clock Pro Max lighter, thinner, it's the lightest, thinnest, best looking, not fastest. You don't want a fast clock. But tabulating machines basically a bunch of different ways to process information mechanically. And that foundational insight 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, you know, if they ever tried to sell a clock as a SaaS product. Time as a service. Hmm. 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 did the IBM that 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 turned IBM into the dominant supplier of corporate computing. Banks, insurers, airlines, manufacturers, governments, they, they all used IBM as the central system for their hardware and software. This was the mainframe era. 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 on IBM hardware, so you couldn't re platform. 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, 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 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 fr and proposals to break IBM into separate companies started to pop up. The market fractured because once you had, you know, an intel chipset and Windows operating system, you could run Windows on a different chipset and you could 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, you know, anti IBM like, challenge the man campaign. So the market was fracturing, and there was a bunch of proposals during the 80s and 90s to break up the country, break up the company into separate units. Lou Gerstner, 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. 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 headcount, 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, that's at 80% gross margins. Great business. 31% of their business is consulting. That's under 30% gross margins though. And then 23% of the business is infrastructure which is just sh 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 Hat acquisition started paying off. And the Z17 mainframe cycle was surprisingly solid. But the problem is that they just called out a shift away 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 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.

It and what's going on in New York? I will tell you what's going on in New York. Today, New York Governor Kathy Hochel signed an executive order placing a one year pause on new AI data centers in the state. This is the. For everyone except several Americans, people that are. But 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. 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 communities jobs and weaken America's position in the global AI race. Earlier this year, Maine considered a similar moratorium, but Democratic Gov. Janet Mills vetoed the proposal after concerns it would block a major data center planned for a town still struggling after the closure of a local paper mill. Hochul'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 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. 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 active. Wow. Yeah, that's pretty big. 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 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 put, have any like knock on effects where the, you know, like Netflix content delivery network that was just, you know, planning to build a small data center to route, you know, video streams to Manhattanites. Yeah. Would be delayed as well. Like, like data center. It'll be interesting to see how they, 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, Ken Griffin was on Goldman Sachs's 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, 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, flowing through other countries. Other countries. I mean, it'd probably go to other states first. Right. Well, he was talking about, 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 yeah, we did this with nuclear, we did this with manufacturing, both of both of which we can all agree were mistakes. I was trying to find if any of the hyperscalers operate our 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. But it's funny because that image probably stuck in some people's mind is like, oh, Mark 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.

Thank you. I'm interested in if we can shift to history for a second. Just your reflections on. No pun intended. Sorry. 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 actually, like, you know, I've been in the industry for, like, 15 years, and I've actually, like, seen the progress we've actually made in the past 15 years. 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 to 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 15 years, it's really hard to be surprised. Sometimes this exponential growth, exponential curve is really hard for the human mind to just fully understand it. But things just change extremely fast, and we should just be really adaptable and really understand that AI is still on this exponential curve and incredible things 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. Can you talk about the advantages and disadvantages between Chinese labs that are making open models versus.

AI research and product engineering as well, Please. Have you seen any scientists get, quote unquote, one shot in the way that certain vibe coders have, like staying up all night where they're just like staying at laptop open with Chai discovery 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 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 and then you have to align the model better and improve that totally. And actually, maybe it's worth just providing some historical context here on just how quickly the research has moved in this field. A year, a year and a half ago, basically none of this stuff worked. The success rates were extremely low, 0.1% over the course of 2025. These models went from being these research curiosities and that they were maybe interesting things to study in some academic labs, but they weren't really being in real drug discovery workflows. In July, June, July of last year, we put out a paper called Chai 2 where the title of that paper was Zero Shots Antibody Design in a 24 well Plate. Literally getting at this exact point where you could start to design these molecules without 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, a target, maybe some disease, you're going after a target that's implicated in that disease. And it would design a number of candidates that would help do that essentially. And so that created some really interesting situations where we would go into a pharma company and we'd be presenting some data and there's one that comes to mind in particular where somebody pointed to one of our slides and says, oh my God, you solved that one. 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, that target, trying to find a binder to it. So, you know, this technology has really moved beyond, I think AI and drug discovery has been in the realm of promise for a really long time, where it's been there's been a lot of hype and attention around it but in 2025 we really like crossed the you know crossed the Rubicon in a way and now these technologies are are you know be 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 that's what might get. Mr. You know so much has changed in the last year on the technology side and it's created this wave of, 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 do you.

Within even less time than that publicly available. Yeah. Open. Wait. Yeah, 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 like a trigger. Like it would be interesting if somebody said if the unemployment rate goes above 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 four 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 super scenarios and they can at times come across as very sci fi. Yeah. But there's always, at least so far been some element of, of reality in them. I hear what you're saying. I want somebody who's like, yeah, generally more like kind of moderate to come in and just say like here's, here's 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 U.S. watchdog. Yeah. 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. Yeah, I just, I always have a problem with the, with timelines and predictions because those can be get so nitpicked and they're so hard. I'd be more interested in less of the like. No, but don't you think that'd be helpful? 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 stimulus checks or lower interest. Right. 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. Yeah. And the solution there is for companies to beef up their own cybersecurity, make sure they're using the most advanced models. Right. Yeah. 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. I just think that's always wrong. They're always wrong about those predictions. 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, as opposed to just saying there might be a problem. And I think that there's a problem coming down the pipe. I don't know. Like, 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. What do you suggest, ubi? Higher taxes? I just don't think predictions are always wrong. There's been so much. So many examples over the last decade where people have gotten predictions, like, dead on. Yeah. Situational awareness. Tyler, what do you think about this? Yeah, I mean, I'm probably in the camp of proactive regulation, like,

What? I built the largest company in cybersecurity in History, a $300 billion company. We want to back him, to go build something of consequence, and that has a different capital requirement. And so we. We have a larger fund. Not because we can. We just got a goal. Sorry. World Cups on. Who scored? Who scored? Spain. Spain just scored. There we go. There we go. Sorry we had to cut to the fan cam. I respect it. Anyway, who you got? Who you got in the game? Who's playing? So Spain's up 1 0. I thought France was going to win this easily. Well, Spain's on Terror, I guess, but you are, too. And thank you so much for coming on the show. Great.

Clanker Media shared that researchers built a soft floating robot for indoor interaction and for so many of the 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. This has the potential to be a massive hit consumer product. It uses helium and flapping fins 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 and 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 want it to fly around. Yeah, load it up with GPT2. It's good enough. No, we don't need any. We don't even need any local models. Just have it fly. Just have it fly around. Oh, you don't even want to. I just want it. Yeah, I just want it. You just want it for the. I. 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.

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 batting 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, 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 tolerable. I wouldn't just be okay with it being in my town, in my backyard. Yes, true. Yimby over here. That's right. In an effort to soothe local opposition, architects plan 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 very, very cheap. By comparison, it looks like a small percentage less. And all of a sudden, just every time it's screenshotted, like there was that hot 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 a brewing facility and turning it into a data center. But it was just for the press release. The data center was actually somewhere else, but it was just sort of like an odd image. Americans are up in arms over data centers. Of course we know this. They worry how much water these buildings use 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, 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 way worse than any other building, said Jeffrey diamond, design director at Gensler. Yeah, see, this is just very rough. Yeah, not good. That is underground. You got to do more. People will push it to the limit unless there's.

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 up. Coming on from Puck to break down the Warner Brothers discovery. Yesterday news. It was over. We had no fundraising news. Yeah. Today we're back. I think it's just like, slow weekends. People like, no one wants to announce Tuesday, Wednesday, Thursday news on a Monday.