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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
Would you look at that?
Speaker 2:Would you look at what, Jordy? Everything looks fine. We're back. We're back.
Speaker 1:That's that's what I'm looking at.
Speaker 2:We're we're getting ready at the last second. We may have installed Modern Warfare two on this large screen and gotten a little bit behind schedule with some of the interns playing. Ben,
Speaker 1:Ben, Tyler were
Speaker 3:was a knockout
Speaker 2:drag out fight. You won by a lot, right? Yeah.
Speaker 1:Well, was embarrassing for Ben considering that he is still in that not chief producer Ben, but other Ben, considering he's still in the main of like Demo. Game.
Speaker 2:But at the same time, I mean, you were probably two years old when Modern Warfare two came out. So you got to sort of relearn the old tricks, the old tricks on Rust.
Speaker 1:Anyway, big hope show you guys had a great weekend.
Speaker 2:Hope you had a great weekend. Big week. We'll be we are going to a conference on Wednesday and Thursday. So we might be off both those days, but we have some great shows for you planned Monday, Did you say
Speaker 1:a conference? Or
Speaker 2:It's a conference.
Speaker 1:Oh, I thought you said concert.
Speaker 2:No. Although, I think there might be a concert.
Speaker 1:That would be extremely out of character.
Speaker 2:Well, I mean, there's a bunch of news we're going to go through. But first, I was just sort of reflecting there on was a great interview with Andrey Karpathy at Sequoia AI Ascent, I think last week. It went up on YouTube. And was he was sort of reflecting on how his workflow is changing around vibe coding, and I was sort of reflecting on how my knowledge workflows are changing, particularly around image generation, now that image generation is really good at infographics and effectively designing slides or output. And so we're we're starting to see the rumblings of this idea of, like, the neural computer.
Speaker 2:There was this, people have been talking about this for years since the AI boom began, but the basic idea is like you would have a computer that basically has no software whatsoever on it. It would just have an LLM or just an AI model, just inference capability or potentially a connection to cloud inference that would generate whatever you want, whatever you need on demand on the fly. And so I think Elon talked about this with MacroHard a little bit. That was a piece of the vision. This has always been theorized, but it's becoming more and more real.
Speaker 2:And so Carpathi describes this idea of like a neural computer this way. And I think it's an interesting framing. Obviously, it'll have implications for SaaS products that might be used in a headless, under the hood scene way or might be competed with against these neural computers. But Carpathi describes this: imagine a device that takes raw video or audio into basically what's a neural net and uses diffusion to render a UI that's unique for that moment. And so this sort of like on the fly instantiation of the exact UI that you need for that particular question or whatever problem you're trying to solve, whatever you're trying to do, is an interesting paradigm shift that it feels like we're starting to see glimpses of.
Speaker 2:So I most recently felt it when I was trying to understand Ryan Cohen's proposal for GameStop to take over eBay. This is a big story. We'll go through it today. But I haven't tracked each either either company closely. We've had Ryan on the show, and, we've talked about eBay and GameStop intermittently, but I couldn't tell you off the top of my head what's the revenue for each company, what's the profit like, what are the different multiples.
Speaker 2:And so in a pre ChatGPT world, I would have gone to Google Finance or Yahoo Finance Finance and pulled some data, maybe had two tabs up, maybe used one of their comparison tools. If I wanted to be really advanced, I would have copy and pasted the stats into spreadsheet. If you're really working on Wall Street, you might have like Cap IQ or Bloomberg plugging into a sheet, an Excel sheet that then can, build you a comparison table and do, like, comps. And then once we got into the ChatGPT world, you might do a deep research report, pull all that data, put it into a table, which is effectively markdown. And sometimes the tables render is a little weird and, like, you can kind of bounce around.
Speaker 2:But now the whole process from start to finish is just a single prompt, and it outputs an image. So the you can pull up the image that I generated. So this was this was one prompt. I said, do a bunch of research on GameStop and eBay's valuation and key financial metrics, things like growth rate, top line, earnings, revenue, valuation, how the multiples fit together, build a nicely designed side by side comparison of the two companies. And you wind up getting something that is very digestible.
Speaker 2:Like, just looking at this, I mean, it's obviously a little zoomed out, but you can zoom in and see, okay, eBay has about three times the revenue, 50,000,000,000 versus 15 for GameStop, and revenue growth. EBay is growing while GameStop shrunk by 5%. EBay grew 8%. Operating income eBay has 10 times the operating income at $2.2280000000 versus 202 232,000,000 for GameStop. And so you just get this, like, very easy, Okay, what's the operating margin?
Speaker 2:EBay is up at 20%. GameStop's down at 6.4%. And so you can start to see on a price to sales ratio, GameStop's at 4x. EBay's at 4.5x. But on a market cap to net income, GameStop's higher has a higher value, 34 x, versus net income versus eBay's 25 x.
Speaker 2:So you can just sort of see this table, and this is something that usually would have been like three or four steps to get here. And instead, it's just this single prompt. And so I think that there's like, this is not a perfect result. Like, in in that image, can see that, like, it chose red as the color for all of GameStop's financials, which is not what you'd normally do because red is usually for negative numbers, but those revenue figures are positive. Like, it could be better.
Speaker 2:I could probably go further and prompt it a couple more times to get exactly what I wanted, but it solved my problem of having like, here's the summary of the question that you were actually asking, which is like, how do these companies stack up to each other? What's the relative size of the business? What are the strengths and weaknesses of each of them? And then boom, you have a square image that you can easily text to someone, and and it's ultimately shareable. More importantly, I don't care what it used under the hood.
Speaker 2:It could have puppeteered a spreadsheet and put it all in comma separated values and make a CSV, and it could have transformed it with Excel or Google Sheets. Under the hood, it could have written Python. It could have used used Pandas or scikit learn. It could have done anything it wanted to, but it's all abstracted to me, and I don't even think about it. And this is different from the previous era of, like, okay.
Speaker 2:Well, if I wanted to do some sort of stock comparison tool, I could vibe code a stock comparison tool with API integrations, make sure you have the the the data connections. But it's just kind of less necessary as the models get fatter and they sort of eat more and more of the process. And so Karpathy describes this concept as Software three point zero. And we should pull up his example because it's very similar. Of course, it happened like months ago because he's ahead of me on everything, obviously.
Speaker 2:But he gave a good example of shifting from like, you have a problem that there's no solution for, so you're going to vibe code an app to just a few weeks or months later, like, the AI tools can just do it. And you don't need any code. You don't need any system to build. Even though it's fun to build a system and it's interesting and it allows for more maybe more speed, more reliability, like, more and more things are, like, one shot able by the model. So let's pull up Andre Karpathy talking at Sequoia AI Ascent about his experience with Software three point o.
Speaker 4:I think one more maybe example that comes to mind that is even more extreme than that is when I was building MenuGen. So MenuGen is this idea where you come to a restaurant, they give you a menu, there's no pictures usually. So I don't know what any of these things are. Usually, I like 30% of the things. I'd have no idea what they are.
Speaker 4:50%. So I wanted to take a photo of the restaurant menu and to get pictures of what those things might look like in a generic sense. And so I built I've encoded this app that basically lets you upload a photo and it does all this stuff and it runs on Vercel and it basically re renders the menu and it gives you, like, all the items and it gives you a picture that it uses an image, you know, generator for to basically OCR all the the different titles, use the image generator to get pictures of them, and then shows it to you. And then I saw the software three point o version of this, which is which blew my mind, which is literally just take your photo, give it to Gemini, and say, use Nano Banana to overlay the the things onto the menu. And Nano Banana basically returned an image that is exactly the picture of the menu that I took, but it actually put into the pixels.
Speaker 4:It rendered the different things in the menu. And this blew my mind because, actually, all of my menu gen is spurious. It's working in the old paradigm. That app shouldn't exist. And, yeah, the software three point zero paradigm is a lot more kind of raw.
Speaker 4:It just Neural network is doing more and more of the work, and your prompt or context is just the image and the output is an image, and there's no need to have any of the app in between. So I think that people
Speaker 2:have to kind of like refrain apps. Yeah. It it it it it I mean, it's it's real. And I I had some takeaways from this. Like, what are the implications for this?
Speaker 2:And I think there's a few things. The the the first thing that was on my mind was that although we have gone through this crazy vibe coding boom where everyone is vibe coding apps, it feels like a very temporary aberration. And also, I know that even though there are millions and millions of people that have used Codecs and ClawdCode and OpenClaw, like, the numbers are big, but it's not at 20% of The US population. Like, it's just not at that level of adoption as opposed to chat apps, which are at like 70%, 80% penetration. Right?
Speaker 1:Yeah. The other the other thing that's been interesting is non like people outside of tech that have gotten into vibe coding Yeah. That have been pitching me their ideas here and there. Every time they're pitching me the idea, it is something that Claude Code and Codex can do themselves pretty well today like just in one chat thread.
Speaker 2:Or the app. Like the apps can do them. And that's what I'm like what's blowing my mind now is that is that Yeah. In many ways
Speaker 1:that's what I'm saying. Yeah. So I'm they're like they're using vibe coding tools to vibe code something that doesn't necessarily need to exist because you could just use the app itself to do the thing. And they're already widely available. So it's been interesting.
Speaker 2:Yeah. So I think there's two things. Like, one is that if you've been, like, hesitant to jump into vibe coding because, like, it's just it's a little bit too much of a hassle. Like, Andre Carpathi is, like, obviously very, very comfortable being, oh, yeah. Let me deploy to Versal and do all this.
Speaker 2:Like, you can figure all that out, but that leads to this world where it's like, oh, I was staying up all night. I was I was really, really, like, burning the midnight oil to get this app deployed and, like, do all this stuff. A lot of that's gonna go away, and, you're not going to need to do that. But then there's also the the the this question what you had, which is, like, there needs to be this higher order loop of thinking around, okay, you have a problem. Should you actually vibe code as an app?
Speaker 2:Or should you just try and one shot it with the current model capabilities? Because for a lot of things You mean like
Speaker 1:And within
Speaker 2:Yeah, within ChatGPN, within Gemini, within Claude, the actual apps. You can take a picture of your food and say, hey, start tracking my calories. There's a lot of things that the apps can just do in one chat thread that people are doing. But I think that there's this tension between when you actually need to, for sure, go and vibe code something versus when you can just do it in a one shotted LLM context. Frontier models are already to, in basically 90% of situations, I feel, instantiate exactly whatever is required to solve the actual problem under the hood, entirely abstracting away like code and tools.
Speaker 2:Like, you will just not be aware of what's happening, and it doesn't matter. And then
Speaker 1:the Yeah, second I would add to my previous statement by saying that doesn't mean that there's not necessarily a business there. Because sometimes taking a raw capability and presenting it to people in a way that's very easy for them to digest, you can still deliver value. And you can get customers, and people will pay you money. But it has been fascinating to see, like, does this actually need to be an app?
Speaker 2:Yeah. Yeah. I mean, there's a ton of apps and software that will still be valuable, whether it has a liquidity pool or some sort of unique source of strength or some differentiation point that that the existing chat apps can't hack at all. And then there's also just like like marketing arms effectively, where it's like, okay. Yes.
Speaker 2:The any frontier model in a chat app could do this, but you weren't aware of it. And this company was really good at running ads to actually get awareness going and then drive downloads of this specific thing. And so we see those in the App Store all the time. The other thing that I was reminded of was did you ever read Union Square Ventures 2016 blog post Fat Protocols? Are you familiar with this?
Speaker 2:So Fat Protocols was this concept around how in the web, like web, I guess, one point zero, two point zero, there were protocol layers, which are like TCPIP, HTTP, SMTP, like file transfer protocols, HTTP. And there and a lot for, like, a couple of years, the crypto community was like the group that developed and maintained HTTP. They basically created the standard that the web ran on, and yet very little value accrued to the creators and the maintainers of that protocol. And crypto would be different because the Bitcoin protocol had the value capture component baked into it. And so there was this idea of the application layer in blockchain would accrue very little value, and the protocol layer would capture the vast majority of value.
Speaker 2:So this is on the web, the applications on top of HTTP. You can think of Facebook as a beneficiary of the protocol of HTTP because that's what how the actual information, the photos, and the text gets transferred to you. But the HTTP standard does not accrue the value. The value accrues to the application on top. And if you scroll down, you'll see the blockchain example, which was sort of borne out, that the application layer was pretty thin on top, and most of the value went to, like, the tokens and the protocol Yeah.
Speaker 2:Exactly. Ethereum is a good example. Solana is a good example. Of course, there's there's value in the application layer, and there's some companies that are being built. But this was basically this thesis that the he says, we see that very early we see this very clearly in two dominant blockchain networks, Bitcoin and Ethereum.
Speaker 2:The Bitcoin network has a 10,000,000,000 market cap. Wow. I think it's like a trillion dollars now, right? Isn't it $700,000,000,000 Yet the largest companies built on top are worth a few $100,000,000 at best. Now we have Coinbase, which is in the tens of billions.
Speaker 2:So both sides of the protocol application layer did very well, but the point is still true. Similarly, Ethereum has a $1,000,000,000 market cap even before the emergence of real breakout applications on top and only a year after its public release. And so that was sort of the core thesis on this fat protocols thing. And I think there's something similar happening in the AI value chain. Of course, there's like a bunch of other dynamics going on in the AI value chain, and there's a lot of capture and complicated market dynamics.
Speaker 2:But the models feel like they're getting fatter every month, they're sort of eating away at the edges of what you can do with them. And so increasingly, you can just get more and more out of the core model, which is an interesting dynamic. Third, there's still, like, this huge question of, like, walled garden jumping. We've talked about this before, but it's almost we need, a different term for, the dead Internet theory. It's like the it's like the walled garden Internet theory.
Speaker 2:Like, the Internet's not dead. There's great information in Substack on certain legacy media websites and on Facebook and on X and on YouTube. But all of those companies don't want to interact with each other. And so that's where you get something like, oh, well, if you write code, you do get access to it loosely. Or if you're puppeteering a browser on a Mac Mini, you get access to that.
Speaker 2:Or if you're digging through iMessage locally, that can require a different workflow. But that's more of, like, a legal and business discussion than a technical one. Like, there's no reason technically that a single LLM wouldn't be able to just query every single web resource, except for the fact that the big the the various tech companies don't want each other to talk to each other. And so the models, I think, will continue to find a way under the walled garden, over the walled garden, through the walls. Like, they'll seep everywhere, and it's more of a question of just inference cost, how how long it takes to actually grind through the wall.
Speaker 2:But they they are already figuring out a way around. And OpenClaw is a good example of that. A lot of the walled gardens were sort of brought down by running a
Speaker 1:little Yeah. Except I think SAP came out and said, no, unauthorized agents here. They're trying to they're trying to put up the walls. They're trying to build a moat. They're trying to get some alligators to scare off the the agents.
Speaker 2:Yes. But I would be very surprised if they're able to stop me from if I have SAP and I'm running it locally, told me to take a screenshot of my computer and then tell the mouse to go where it wants. Yep. It's like, it it it's very hard to fight back
Speaker 3:against these. Rune had a good tweet where
Speaker 2:he was
Speaker 3:like, you know, people are now just like vessels for the AI where they just like the AI tells them what to do and then they just act exactly like
Speaker 2:Yeah.
Speaker 3:What the the model said.
Speaker 2:Wasn't John Collison talking about this? Or John Collison was saying, like, the humans get the thing off the high shelf. Every time I have to, like, go and, like, export a PDF and upload it to JatGPT because I can't get it in there by default even though I could just give them a web URL. I have to export it or print or whatever.
Speaker 1:Let's talk about I think we should talk about GameStop.
Speaker 2:Let's do it. What's up with GameStop? What's going
Speaker 1:on with GameStop? Yesterday, it came out through Wall Street Journal. GameStop was preparing to make an offer for eBay as part of Ryan CEO Ryan Cohen's plan to turn the retailer into a $100,000,000,000 plus juggernaut. Mhmm. GameStop has been quietly building a stake in eBay shares ahead of a potential offer and could submit an offer as soon as later this month, which they did this morning.
Speaker 1:If eBay isn't receptive, Cohen could decide to take the offer directly to eBay's shareholders. And they released a letter yesterday
Speaker 5:Mhmm.
Speaker 1:To Paul Pressler, who's the chairman of the board over at eBay. Happens to be a friend of mine. Really? Yeah.
Speaker 2:Wait. Really?
Speaker 1:Yeah. I I I his daughter and my wife are good friends.
Speaker 2:Oh,
Speaker 1:cool. So I end up we end up hanging out a decent amount. Does does And we're neighbors. Does he
Speaker 2:do a lot of does he do a lot of, like, podcasts or press appearances?
Speaker 1:It can it can we can it can be discussed.
Speaker 2:I I'm just saying like determinism of Pressler would be like somebody who dominates the press.
Speaker 1:The press circuit.
Speaker 2:Think you would be doing press circuit all the time.
Speaker 1:Anyways, Paul Paul is fantastic. Yeah. And Ryan wrote this letter to him yesterday
Speaker 2:saying
Speaker 1:GameStop is proposing to acquire all common stock of eBay at $125 per share. We have accumulated a 5% economic stake in eBay through derivatives and beneficial ownership of common stock and are filing a Schedule 13D and HSR notification tomorrow. Our offer is $125 per share, comprising 50% cash and 50% GameStop common stock, which we will get to in just a little bit because Ryan Cohen discussed this on CNBC this morning. That represents a 46% premium to eBay's uneffective closing price on 02/04/2026, the day GameStop started accumulating its position in eBay. And blah, blah, blah, blah, blah, blah, blah.
Speaker 1:But let's go straight to the CNBC.
Speaker 2:So quickly, there was a question. So said, can someone please tell me how GameStop has 56,000,000,000? It's not a $56,000,000,000 company. There were questions. And Ryan Cohen went, in the ring with Aaron Sorkin over at CNBC or Andrew Ross Sorkin.
Speaker 2:Sorry. Andrew Ross Sorkin on CNBC Squawk Box to interview about the GameStop eBay acquisition. Could play this.
Speaker 6:Through how you could get to that price and how it would work?
Speaker 5:It's on our website. It's half cash, half stock, but
Speaker 3:but the details are are on our website.
Speaker 6:Can you help? I I I've read them, but can you help our audience understand them?
Speaker 5:Yeah. What what which part exactly?
Speaker 6:Well, I think we can start with the idea that the market cap of of GameStop is, call it, $11,000,000,000. You have $9,000,000,000 on your balance sheet arguably if you're providing effectively all of your stock and then the cash that gets you to 20, You have this letter from TD, that's another 20. We're now at 40, but we're still off by, call it, 16. And and the 20, as far as I understand, while it's considered a highly confident letter, meaning TD's saying they're highly confident that they would provide the financing, it's not locked financing.
Speaker 5:Yeah. We'll see what happens.
Speaker 2:Founder knows. Never doubt.
Speaker 6:I I hear you.
Speaker 2:Dead end.
Speaker 6:I understand that. I'm I'm just trying to understand where the the rest of the money would come from.
Speaker 5:It's half cash, half stock.
Speaker 6:I I I hear you. I'm just saying that that math doesn't get you to the to the price that you're offering.
Speaker 3:Question. I don't get it.
Speaker 2:Thank you chiming in.
Speaker 3:Where's the rest of the money coming from? Andrew laid it clearly.
Speaker 5:I I don't understand your question. We're offering half cash,
Speaker 3:half stock and we have the ability issue stock in order to get the deal done. But the full details offer on
Speaker 5:our are on our website.
Speaker 3:But you're air. We we thought we'd get
Speaker 5:So but I don't understand your question.
Speaker 2:Where's the money coming from? That's the question. You're wondering record scratch, freeze friend. You're wondering how I try to buy a $55,000,000,000 company with $40,000,000,000 earmarked. Do you think
Speaker 1:he was expecting Why can't this to go out on Sunday, Monday? GameStop stock to pop like crazy. Yeah. And it's actually down today.
Speaker 2:I guess that's possible. I I I don't know. I I also don't understand why he can't just say, like, hey. We're in the process. Like, we got a highly likely letter from a bank for 20.
Speaker 2:Yeah. We need 16 more, but we're gonna go get more letters from other banks. We're gonna go get other equity investors. Like, this is a whole process. We're excited to announce this and this is like our first close.
Speaker 2:Like, we're not, like, we're fully ready. Yeah. But maybe
Speaker 1:So the tough thing is think he took this offer to Paul
Speaker 2:Yeah.
Speaker 1:Chairman of the board. Yeah. Now, Paul has to look at this and be like, okay, is this a real offer? Yeah. And I imagine Paul will watch CNBC and It's not.
Speaker 1:That's not gonna give anyone a lot of confidence.
Speaker 2:Yeah. It's yeah. I mean, you can imagine it in the in the context of like buying a house, you know, you show up and someone says like, I have 80% of the money and like, my bank will underwrite me for 50% and I have 30% in cash and you're just like, look, I need the full amount.
Speaker 1:Yeah. The tough thing is like I'm I'm I'm wondering I'm wondering what Ryan you know, eBay is an incredible business. Yeah. It's been remarkably durable.
Speaker 2:Mhmm.
Speaker 1:They've faced an on slot of competition for every single category from sneakers to
Speaker 2:Mhmm.
Speaker 1:Watches to art to name any cars. Right? Any category there is like a vertical competitor to eBay. Yeah. And yet the business has done has been remarkably remarkably strong.
Speaker 1:Yeah. Up pretty meaningfully this year. Yeah. Right? Yeah.
Speaker 1:Management is executing. Yeah. And it's unfortunate for Ryan and his bid that the most viral sort of video clip out of all of this is just him failing to answer like, you know, a pretty straightforward question and not having an opportunity to talk about, okay, why do you, you know, if presumably if you're buying this company, think it can and should be worth a lot more. What's your what's your plan? What's your plan for the business?
Speaker 1:Why are you better suited to run it than than Jamie who's been in in the seat since 2020? Worked at eBay from 2001 to 2009. Woah. So he's a veteran, knows the business very well.
Speaker 2:Yeah.
Speaker 1:And you're coming in $16,000,000,000 short. At least, that's what it looks like. Yeah. Anyways, this bid could be could be over before it really started.
Speaker 2:Yeah. Or, I mean, it could attract a bunch of investors who wanna line up and fall in line and wind up producing the the 55 or so required, but it does feel like it's a ways away. Breaking news for gamers out there. What's that? I know a lot of gamers out there.
Speaker 2:They have laptops. They're worried about the price of these laptops, the batteries. Electricity is getting expensive. What are you gonna do? How are you gonna charge?
Speaker 2:We got the solution for you. It's a gas it's a gasoline powered laptop. So it's pretty simple. It's a one of a kind gasoline powered laptop. It's offered for just $850.
Speaker 2:Looks like it's right on Windows XP. You might not be able to play the latest and greatest games. Will it run Crisis? Maybe, maybe not.
Speaker 1:With a full tank, you can get an hour and a half of run time out
Speaker 2:of this. It runs a two stroke engine, and it's perfect for off grid computing. That's hot right now. And so, the laptop specs, let's take you through it. It's got Intel Core two Duo.
Speaker 2:Two gigs of RAM. RAM's going up in price. This is valuable. This is an appreciating asset. 120 gigs of hard drive space.
Speaker 2:That's gonna hold a lot of games when you're off grid. You only have a little bit of gasoline. If you want a game, this is the laptop for you. It's a good It's work
Speaker 1:running Windows XP.
Speaker 2:And it says that it starts easy. The the two stroke engine on the gasoline powered laptop, yes, it does start
Speaker 1:in the x chat says it gets 300 tweets to the gallon. 300 tweets.
Speaker 2:Oh. Oh, no. I accidentally set GTA five to max settings. Well, at least it'll serve as a benchmark test. How many Chrome tabs can it open before it crashes?
Speaker 2:People are having fun with this. But the gasoline powered laptop, this is true hacker mindset. Whoever built this is an incredible engineer and did something. They did the impossible. They built a gasoline powered laptop.
Speaker 2:I've seen a couple other of these like gasoline powered projects, people making all sorts of different things. It's always a funny gag. Obviously, if you have
Speaker 1:The actual breaking news is the White House is considering vetting AI models before they are released. Oh. Bad, FDA for took a non interventionist approach to AI is now discussing imposing oversight on AI models before they are made publicly available.
Speaker 2:Well, FDA for AI. We'll see.
Speaker 1:It would be potentially an executive order Yeah. Create an AI working group that would bring together tech executives and government officials to examine potential oversight procedures. Okay. So this would be an executive order to create a working group that could potentially create an oversight
Speaker 2:Okay. So we're a couple steps away. But it seems reasonable. I don't know. Depends on what the the what the what the benchmarks are, but you certainly don't want
Speaker 1:And Trump says we're gonna make this industry absolutely the top because right now it's a beautiful baby that's born.
Speaker 2:Interesting way to put it.
Speaker 1:We have to grow that baby and let that baby thrive.
Speaker 2:Is this real?
Speaker 1:It's a real quote.
Speaker 2:Are you messing with me?
Speaker 1:It's a real quote that Trump said about AI. He said, we have to grow that baby and let that baby thrive. We can't stop it. We can't stop it with politics. We can't stop it with foolish rules and even stupid rules.
Speaker 2:It's not a baby. It's a $10,000,000,000,000 industry. It's like the the engine of the global economy. Anyway
Speaker 1:Dean Ball's got a quote in here.
Speaker 2:What does he say?
Speaker 1:He said, the technology is moving extremely fast and there are few formal procedures, but they don't want to overregulate. He said, It's a tricky balance.
Speaker 2:I say, Don't release it unless it's acing tax bench. It's got to be able to do the taxes before it gets out into the wild. No. Obviously, you want these models to be safe. You want them to be reliable.
Speaker 2:You want them to avoid negative externalities. And anything that gets us in that direction is probably good. But everything comes with trade offs.
Speaker 1:Final post of the day. Yeah. From Tommy. Do say? Hi.
Speaker 1:PhD in haemorrhology here. All right. So what we're looking at is a nail.
Speaker 2:That is the correct mindset. When all you have is a hammer, everything looks like a nail. Also, go check out Riley Walls' new project. He's shipping stuff every week. This one got a million views.
Speaker 2:You probably already saw it. 27,000 likes. 10% of AMC movie showings sell no tickets at all. So if you wanna go see a movie in a private theater with no one else, he made a site that finds empty theaters and tells you exactly when you should go and book. You can go see project hail Mary at 12:30PM today in New York.
Speaker 2:If you don't have work, you can go see project hail Mary in your private theater. It's available at walzer.com/emptyscreenings, walzr.com. Empty screenings. You can search by zip code. Let's see what's around us.
Speaker 2:Is there anything good?
Speaker 3:There's 10:45PM, Devil Wears Prada two.
Speaker 2:Okay. Around us.
Speaker 3:Woah. Zero seats.
Speaker 2:Enjoy it. Woah. Enjoy being a last.
Speaker 1:You got it.
Speaker 2:This is very funny. Yeah. There's he he does he does surface some that have one seat or two seats. Interesting way to make a new friend. Me and you.
Speaker 2:Because you think so you think, oh, I I got the zero seat theater. You're you're in the one seat theater and somebody's like, wanna meet the psycho that went to the empty theater and then they're talking your ear off. Who knows? Leave us five stars on Apple Podcast and Spotify. Sign up for our newsletter at dot and we will see you tomorrow.
Speaker 2:Love you. Goodbye. Little bit missed time there.