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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TBPN. Today is Friday, 11/21/2025. We are live from the TBPN Ultradome, the temple of technology The fortress of finance. The capital of capital. Have generated an image of the Oura Farm, the world, trying to understand A barnyard.
Speaker 1:Map, a barnyard. Sort of an AI market map, but through the lens of a a barnyard because that's really what, what is going on in AI these days. And we can take you on a tour of our our farm based market map to explain what's happening in the state of AI in November 2025. Tyler, do wanna take us through it?
Speaker 2:Sure. Yes. I mean, so so we like to use a lot of animal idioms on this show. Yeah. A lot of these you you might recognize, but we've kind of expanded out to try to cover all the major players.
Speaker 2:And, you know, so yes. So this was made with Nano Banana Pro. Very extremely good model. Yep. But you will notice as you get more and more complex, it gets a little bit sloppy.
Speaker 2:There's some sloppy in some places.
Speaker 3:Yeah. Before Nano Banana Pro was released, we would have needed to hire somebody that maybe illustrates children's books. And if they were an expert, maybe they could have whipped something together in a day. This took you far longer than that of prompting over and over and over.
Speaker 2:Yeah. Okay. So I guess let's just kind of go through each of the animals. Maybe let's just start with some of the more obvious ones, the ones we've talked about a lot on the show. Let's start over here with the piggies.
Speaker 2:So here here here we see the pigs at the at the slop trough.
Speaker 3:Who's there?
Speaker 1:Who's there?
Speaker 2:So this is broadly, this is just labeled as meta.
Speaker 1:Yeah. But you
Speaker 2:can imagine a lot of people here. Right? You could you could see Sora here. Sure. Bill Peebles.
Speaker 1:Bill Peebles could be, know, eating some slop. Yes. Meta vibes.
Speaker 2:Yep. Just like broadly AI in general, some people think basically all AI is slop.
Speaker 1:They do. They do. There's been a lot of criticism.
Speaker 2:Yeah. But I think that one's fairly clear.
Speaker 1:You don't want to be at the you you don't want to be the pig at the slop trough. Although, sometimes, you know, maybe the the profitability of being a slop farmer, is underrated. Obviously, America has a lot of pigs that live at the trough. They eat from the trough. They eventually the pigs go to slaughter.
Speaker 1:They become bacon. They are sold into the economy. You can make a good living as a farmer who That's right. Who maintains a trough.
Speaker 3:Then there's the Jeremy Gaffan take, which is we hate slop now because we know that in a few years, it will no longer be slop.
Speaker 1:Yes. Yes. Yes.
Speaker 3:Don't count out don't count out the piggies yet.
Speaker 2:This is the sloppiest slop we'll ever be.
Speaker 1:That's true. That's Okay. Who else is on this
Speaker 2:market map? Let's move up. Let's see. We have the hen house here.
Speaker 1:Yes. And
Speaker 2:so and who's in the hen house? It's the fox.
Speaker 1:The fox.
Speaker 2:Right? And so so this, you can say, is kind of Oracle in the same old one. Right? Oracle's then is the henhouse? Yes.
Speaker 3:They're letting the fox in.
Speaker 2:They're letting the fox in a little bit. Potentially. Yeah. We'll we'll see what what, you know, when what what ends up happening. But,
Speaker 1:again, now that I'm looking at this image, the fox isn't actually in the hen house yet. He's on circling it. He's circling the hen house, and there's a question of of how how how far into the hen house has the fox
Speaker 3:it's it's notable that the chickens don't seem too disturbed yet.
Speaker 1:Yes. Yes. Yeah. Yeah. They're getting along because the fox could just be browsing, could just be stopping by.
Speaker 1:It could be friendly friendly fox.
Speaker 3:Friendly fox. Yeah.
Speaker 1:But but, of course, it is if you have a if you have a lot of cash flow as a big company, if you have the ability to borrow billions or hundreds of billions in the debt market, you have to protect your henhouse because That's right. Foxes might come by and might want to might wanna use you to cosign a loan.
Speaker 2:Okay. So then we we see the cash cow.
Speaker 1:The cash cow. This is
Speaker 3:NVIDIA, The only profits in AI.
Speaker 1:For a long time, I don't know if anyone has really unseated them. They're certainly the most profitable by far.
Speaker 2:Now you're starting to see maybe some cracks with TPUs. Okay. But even then, I mean, they're they're still
Speaker 1:It's still a cash cow. We just saw they just yeah. They just beat earnings. I mean, we have we have an article here from the journal. NVIDIA results fail to quell AI worries.
Speaker 1:Not enough people are milking the cash cow. Gave you the perfect quarter. Maybe maybe the cash the perfect quarter. I know. And
Speaker 3:you still sold off.
Speaker 1:Maybe maybe the the cash cow has been over overly milked and is out of milk at this point.
Speaker 4:But
Speaker 2:I think it's still producing.
Speaker 1:I think it's it does seem like it's still producing. That looks like a healthy cow to me.
Speaker 2:Yes. So so here we have the bull in the China shop.
Speaker 1:The bull
Speaker 2:in the China shop. Think there's a couple ways you could read into this. Yes. So, Elon, one is just kind of on the maybe the the data center infrastructure side Mhmm. Where he's he's kind of the bull.
Speaker 2:He's Imagine that you're a contractor you're and building data centers for for these companies, and then you see Elon come in and he does it in in eight months. What took you in a year and a half? Yep. He's kinda messing up your world. Right?
Speaker 1:Totally. Totally.
Speaker 2:He's like, oh, man. This this bull, he's he's messing up my my business. I need be working way harder, way faster because
Speaker 1:He's also shipping features so fast. Like Yeah. Like, before people could even have a discussion over adult content, it was like, boom, Annie. Here here it is. Valentine's.
Speaker 1:This is the so other fast.
Speaker 2:This is the other way you could say he's the bull because there's kind of this maybe unspoken unspoken rule between the model companies Yeah. Where it's like, okay, we don't wanna go too hard into the the companion Yeah. You know, space. There were companies doing that, but they weren't It wasn't the OpenAI's, it wasn't the Anthropics, wasn't the Gemini's. Yeah.
Speaker 2:And then now you see now you see a frontier model actually moving into their
Speaker 1:Also, you know, Grok is, of course, the maximally truth seeking LLM. Just yesterday, I was asking Grok who is the strongest CEO in tech, and it told me that Elon Musk is the strongest by far. And it actually compared him to a bull. It said he was stronger than a bull and that he could beat a bull in a fight if he went head to head
Speaker 3:I believe it.
Speaker 1:With his bare hands.
Speaker 2:Absolutely right.
Speaker 1:Yes. Absolutely. You're right. That's exactly right. What else is going on here?
Speaker 3:So I bet I bet Claude would agree. If you really press Claude on it, they'd say, yeah, I I I You're absolutely right.
Speaker 1:You're absolutely right. Who else is going on?
Speaker 2:So let's move down here. We we have the the lip stick on a pig. And I think I like
Speaker 1:the pigs.
Speaker 2:You could say is Lip things are so happy. Apple intelligence.
Speaker 1:Yes.
Speaker 2:Right? I mean, although I feel like this is actually almost flipped a little bit. Right? Because the the pig is usually like the ugly thing and then you add the makeup to make it look nicer. Yeah.
Speaker 2:But Well, I think that's what they
Speaker 3:did here. Right? They took a bad model and they dressed it up and they'd said it was great and they said you should buy a new iPhone because of it and the model was bad. That's true. And there's no amount of marketing
Speaker 1:Yeah.
Speaker 3:That is gonna, like, change public perception once the product, hit the market.
Speaker 1:You could also run the the the pig is the privacy focused iPhone ecosystem that is, pretty difficult to just run-in and throw AI on top of. Like, Apple has been building a brand around, we don't access your data. We don't store your data. We would never train on your data. And and that put them in an awkward position where they couldn't just snap their fingers and deliver a great AI experience, whereas Google has been, hey.
Speaker 1:You know, we'll give you Gmail for free, but we'll also, you know, probably train on wherever you go on the web and try and understand and and route ads to you appropriately. Meta was in a similar position. And so those two companies were a little bit more equipped to just, on day one, go and go and deliver AI features. Apple had to put lipstick on their pig, which is their privacy focus.
Speaker 2:More of, an afterthought. It was more of a kind of shallow integration, per se. So then we have the dark horse.
Speaker 1:The dark horse.
Speaker 2:And this is SSI.
Speaker 1:Okay.
Speaker 3:Of course.
Speaker 2:We're yet to see anything really from SSI.
Speaker 3:Ilya just charging around in the background. Yes. Yeah. Kind of the So so
Speaker 2:the big kind of departures from OpenAI, it was Miramaradi and and Ilya, you could
Speaker 1:say. Yes.
Speaker 2:Miramaradi's company, Thing Machines, I mean, they're they're
Speaker 1:She's raising up rounds.
Speaker 2:They have they have blog posts. Yeah. They do actually have a product. They do have a product.
Speaker 1:Let's hear it from my audience. Why why did you tell me earlier? Why why would why'd you bury the lead? They have blog posts?
Speaker 2:They've they are good blog posts. I like them.
Speaker 1:So in a couple years, we could be seeing Vibriel's. Is that what you're saying? We could be seeing watch videos.
Speaker 2:Do have a product. Right? It's like RL fine tuning.
Speaker 3:Watch your head. There's a hoof.
Speaker 1:The horse is really
Speaker 2:But, I mean, they're not really dark horse. Like, you can they're a bright horse.
Speaker 1:Okay. Don't know if that's
Speaker 2:a a phrase, but, like, you can see what they're doing.
Speaker 1:They're a cladstale or or a beautiful They're a unicorn 50 times over. 50 times over. Yeah. We didn't put a unicorn on here. That's an animal.
Speaker 2:It would get too sloppy.
Speaker 1:Okay. What else do we have? What else is going on on the orapharma?
Speaker 2:So here here we see another horse. Yes. And there's two ways you could look into this horse. Right? One is is this phrase, look a gift horse in the mouth.
Speaker 1:Yes.
Speaker 2:Right? Do you wanna explain this, John?
Speaker 1:Yes. So do you know this phrase?
Speaker 3:I've never
Speaker 1:You don't know this phrase, looking a gift horse in the mouth? Crazy. Okay. So looking a gift horse in the mouth is, if someone gives you like
Speaker 3:a term that was thrown around in the eighties?
Speaker 1:Yeah. Yeah. This is this is back my day. Back in my day. So, obviously, just giving someone a horse, a horse is a valuable asset today, but also hundreds of years ago.
Speaker 1:It's always been a valuable tool on the on the farm. And the way that you assess the quality of a horse, one way to assess whether it's been taken care of, whether it's healthy, is to look in its mouth All
Speaker 3:way to look a gift horse in the mouth.
Speaker 1:Never looked a never looked a gift horse in
Speaker 3:the because it would be offensive.
Speaker 1:It's offensive.
Speaker 2:It's like you're not expressing gratitude. Yes. And so I think this these are just the public market investors. Right? They should be happy.
Speaker 2:Of AI.
Speaker 1:Why are they selling their stocks right now?
Speaker 2:Why are they selling?
Speaker 1:They've been giving they they need to be buying.
Speaker 2:This beautiful gift and they just don't want it. Yeah. They're selling. Their videos down.
Speaker 1:They're digging in a little bit too much. Yeah. They should just be happy that they've been given AI
Speaker 2:Exactly.
Speaker 1:The next megatrend.
Speaker 2:Exactly. So also the horse Yes. Could be a workhorse.
Speaker 1:A workhorse.
Speaker 2:Right? And so I think you could say this is Amazon. Yeah. It's kind of it's bit hard to define Amazon's AI strategy.
Speaker 1:Has been
Speaker 2:Part of it is they're building centers for anthropic, but they're definitely not getting overly ambitious. They're not like, you know, getting over their skis. Mhmm. But they're just doing the hard work. They're building the data centers.
Speaker 2:Yep. They're serving Yeah. Serving models.
Speaker 1:Maybe not fast enough. Might not be building the data centers fast enough. They might not be super aggressive. They're not they're not they're not show jumping. They're just they're just dragging the plow.
Speaker 1:But they are consistently dragging the plow. Old reliable Amazons cooking along. They're they're they're they're staying out of the they're staying out of the slop trough. They're not doing a deal. Amazon has not done a deal yet with OpenAI for the agent to commerce thing.
Speaker 1:Maybe that changes. But for now, they're just plotting along. Who else
Speaker 2:we got here? Let's go to the black sheep.
Speaker 1:The black sheep.
Speaker 2:So black sheep, there's also a lot of people that can fit in this. Yes, of course. But I think maybe Carpathi is one of them.
Speaker 1:Yeah. On great Carpathi.
Speaker 2:Some of these contrarian to contrarian takes about just a decade of agents.
Speaker 1:To clear, we're not calling him a sheep. He's not the the the It
Speaker 2:should be more of a black wolf.
Speaker 1:Black wolf. But the idea is that he's standing out. A lot of people in his in his class of of ultra respected, you know, technologists, some of the, you know, most experienced. He's really been at Tesla. He's seen the AI wave.
Speaker 1:He's been working in it for decades. He's really worked
Speaker 2:on this.
Speaker 1:He's printed all of it. Yeah. He's done so much.
Speaker 3:Sitting with the rest of them saying, bah.
Speaker 1:He broke, but he broke rank. Even though he's worked at OpenAI, even though he's worked at Tesla, he broke rank. He went on the Dwarkash Patel show and said, you know what? I think we're more in a decade of agents. I think AGI might not be right around the corner.
Speaker 1:He took a contrarian stance at a very controversial time.
Speaker 3:And he popped the bubble with it.
Speaker 1:He basically popped the bubble with it. Mate, we'll see. Of course, the elephant in the room
Speaker 3:the elephant in the room is is was, in my view, really more of the 1,400,000,000,000.0. Right? That was the questions. That was the big question. That was what everybody wanted to talk about or or at least understand better.
Speaker 3:Brad asked the question, and it's been Yes. Downhill ever since.
Speaker 1:Yes. And it is yeah. The elephant in the room is is in every conversation. Every every financing round at this point Exactly. Is is this is this deal predicated on a continuation of exponential growth in investment, in everything?
Speaker 1:Like, how much more how how risky is this relative to the amount of froth in the market?
Speaker 3:Yeah. Never never ask a a woman her age, a man, his salary, or a a a lab founder how they're gonna spend 1,400,000,000,000.0.
Speaker 1:Yeah. Or how they're gonna pay for it. Yeah. Yep. What else we got
Speaker 2:on here? So then, in the top right, we have the bird's eye view. Yes. I yeah. Is situational awareness.
Speaker 2:This is Leopold. It's the perfect name. Right?
Speaker 1:He has the situational awareness.
Speaker 2:He's seeing everything. Yes. He's kind of the master of the board. Yes. He's taking his bets, and He's been doing pretty well off them.
Speaker 1:Yes. Yes. Yes.
Speaker 2:Yeah. That was pretty self explanatory. Yeah. Yeah. I So then we go down.
Speaker 2:We have lion's share.
Speaker 1:The lion's share.
Speaker 2:This is Satya. Satya has taken great position in OMA. Take I'll
Speaker 3:third take of the company Yeah. And you can give me 250,000,000,000 Yeah. And I'll take 20% off the top Yep.
Speaker 2:And I'll take all the IP as well. Yeah.
Speaker 1:Yeah. Everything.
Speaker 2:I'll also take your chip, and I'll make it my chip.
Speaker 3:Your chip is my
Speaker 1:The entire The the
Speaker 2:chip as me.
Speaker 1:The entire OpenAI Microsoft deal is basically could just be summarized in one line. I get the lion's share. I get the lion's share.
Speaker 2:What do we have? Monkey Business. These are the podcasters.
Speaker 1:That's us. We're having fun. Yep. We got props. We got all sorts of stuff, sound effects.
Speaker 1:We need we need some we need some monkey sound effects on there. We have a bunch of of animal themed sound effects we need to have more fun with. Anyway
Speaker 2:And then maybe let's go into the pond. We have the sitting duck.
Speaker 1:Yes. The sitting duck is is incredibly cute.
Speaker 2:So so Reddit Why
Speaker 1:are they why were why was Reddit a sitting duck?
Speaker 2:Yeah. So I think they brought
Speaker 3:It's because whether or not you have a permit, you're getting the hunters are gonna get you.
Speaker 1:I think I I think Alexis Ohanian sort of laid this out saying that that when when Reddit did the deal to give the data to OpenAI, they didn't realize how valuable that data was gonna be, and that relationship has grown, grown, grown. And so they were kind of a sitting duck just sitting there. They didn't really they kinda got caught off guard. Maybe could have trained their own model on their data internally.
Speaker 2:Yeah. I mean, I feel like Reddit has mostly been they've kind of already gone out to the slaughter in in a sense, like, every model company has trained
Speaker 1:on that. So. But look at the market cap. It just keeps going up. Reddit was sold for $5,000,000 or something when it launched.
Speaker 1:Like, it's been
Speaker 3:It was 10. Was 10. To Conde Nast.
Speaker 1:10 to Conde Nast. That's a crazy, crazy low valuation. And then eventually spun out. And then for a long time, it was in the hundreds of millions. And no one was thinking this is a tens of billions.
Speaker 1:Like, for a long time, like, people the narrative was not, oh, yeah. This will be orders of magnitude more than snap.
Speaker 3:Yeah.
Speaker 1:No way. No way. Then Yeah. And then it just sort of finally came together.
Speaker 2:And we have the headless chicken. This is Perplexity.
Speaker 1:Perplexity.
Speaker 2:So I think Perplexity, you know, they have a lot of different strategies. Mhmm. Some of them kind of seem opposed to each other. Right? Maybe they're doing a browser.
Speaker 2:Maybe they're doing a Bloomberg terminal.
Speaker 3:Mhmm. Maybe they're rebuilding Yahoo Finance. I do see more positive reviews of their browser than any of the other AI browsers.
Speaker 1:There's just a lot of stuff going on. It's the Snapchat deal, the trying to buy TikTok, trying to buy Chrome, launching a venture fund, Bloomberg terminal. It's like, are competing with all of these? Really? You're gonna beat TikTok and Chrome and Bloomberg and the next thing.
Speaker 3:Do you guys ever witnessed a a headless chicken?
Speaker 1:No. No. I haven't.
Speaker 3:Growing up in the country, I have. You grew up in the country? What are talking about?
Speaker 1:I thought you I thought you grew up with the East Bay Rationalists.
Speaker 3:I was born in Berkeley, but I grew up in wine country.
Speaker 1:Oh, okay.
Speaker 3:And I have fortunately, unfortunately watched my father take one of the chickens, you know, every now and again. A chicken needs to to move on to the next chapter and and as a child.
Speaker 1:You sound like you're firing the chicken.
Speaker 3:It is a real thing. They run for, you know, at least twenty seconds or so. Yeah. And I'll never forget it.
Speaker 2:So next, we have the snake in the grass.
Speaker 1:Snake in the grass.
Speaker 2:This is the Chinese open source models. Right? These are kind of lurking. I still don't really see that much coverage of Chinese open source models
Speaker 3:outside of the Nobody wants to talk about it.
Speaker 1:Well, no one has bags, so they can't pump them. Snake in the grass feels like it's good to attack. Elephant in the room means we got to address it. It's like, it's totally possible that the entire open source LLM ecosystem is just like, yeah. There's like a $10,000,000,000 business there.
Speaker 1:It's sort of like, you know, a a a stalking horse, another another animal based analogy. But it's sort of a stalking horse for, like, hey, Gemini and and Anthropic. Like, if you guys don't lower your prices, we will go to the open source option. And that's sort of what Linux how Linux works. It's like that that you can kind of bid the closed source models against the open source models.
Speaker 3:It's a very real threat
Speaker 4:Mhmm.
Speaker 3:To the the business models of some of the closed closed source models.
Speaker 1:Maybe. I don't know.
Speaker 3:It's certainly a pressure. Yeah. It's it's Kimi is hot on everyone's tails. The other thing is a soft power thing. Yep.
Speaker 3:Right? Ask it ask a Chinese open source model about Tiananmen Square.
Speaker 1:So we agree it's a snake in the grass, but unclear how poisonous the snake is, unclear the size of that snake.
Speaker 2:Early bird that cut the worm, this is Josh Kushner?
Speaker 1:I think so.
Speaker 2:Right? I like that. He got the worm. The worm's OpenAI.
Speaker 1:Yes.
Speaker 3:He was very He's early Early with size.
Speaker 1:Early with Double down many times.
Speaker 2:Yeah.
Speaker 1:He got the worm. He's the
Speaker 2:early bird. Incredible.
Speaker 1:Yeah. Why is Anthropic donkey work?
Speaker 2:Donkey work? I mean 100% sure that this is like a real phrase. Apparently, I asked GBT 4.5 and I asked Gemini three Pro.
Speaker 1:Okay.
Speaker 2:And they both said it was a real thing.
Speaker 1:Okay. It's boring or laborious part of a job. It's drudgery. Donkey work.
Speaker 2:In this case, I I think it's kind of that Anthropic has gone very hard on coding Mhmm. And API and enterprise.
Speaker 1:Oh, okay. Okay. Yeah. The laborious work.
Speaker 2:It's kind of laborious.
Speaker 1:Yeah. Yeah. They're not doing, like, the the really hot, sexy, like
Speaker 3:They're not doing a browser.
Speaker 2:They're not
Speaker 1:doing science. Yeah. They're not doing consumer Yeah. Science stuff. Yeah.
Speaker 1:They're doing the donkey work.
Speaker 3:Daria is sitting there being like, who's gonna take all the jobs?
Speaker 1:Who's gonna take all the I like donkey work. That that feels the most accurate for what they're doing. They're going after the entry level white collar workers. They're they're they're doing the donkey work. Yeah.
Speaker 1:Google. I just love this image. I this
Speaker 2:is the last one. Google is the fat cat. Before we had Google snail's pace, I think this would have been true maybe a year ago.
Speaker 1:That cat's so much funnier. Look at that cat. It's so fat. I love it.
Speaker 3:All the cash flow. All the TPUs.
Speaker 1:All the TPUs. They're GPU rich.
Speaker 2:The best image model. Yep. The best text model depending on Yeah. What what benchmark you look at.
Speaker 1:They're on top of the world.
Speaker 3:Slightly concerned we have a sign for golden goose, but there's no golden
Speaker 1:was removed, but the Who sign was
Speaker 3:stole the golden goose?
Speaker 1:Yeah. Who killed the
Speaker 3:golden goose? Is there just no gold if there's no golden goose on the a in the AI barnyard, is that is that bearish?
Speaker 1:The golden goose is a goose that lays a golden egg one every day. And in the parable, in the story, the farmer kills the golden goose to get all of the gold inside, but it is revealed that by killing the goose, you no longer get the the the passive income.
Speaker 2:Maybe one take is the golden goose, they were the neo clouds, and then the market is hurting hurting is taking the goose away.
Speaker 1:Yeah.
Speaker 2:Right? Core Weave not in the past past what month? Yeah. They've selling off a little bit.
Speaker 1:Core Weave continues to lay golden eggs, but the market got overheated and so that that that sort of killed the the gains or something. And the gold
Speaker 2:is the GPUs, subsidized GPUs.
Speaker 1:The chip CEO staring down NVIDIA and talk of an AI bubble. At a board meeting in late twenty twenty two, Lisa Hsu, chief executive of chip designer AMD, announced that she was radically changing course. I'm going to pivot the entire company, she told the directors gathered around a boardroom table at the company's Austin campus. The rise of AI was a once in a lifetime opportunity, she said, and the company had to put AI at the center of its entire product line. Three years later, the Santa Clara, California based company has nearly quadrupled in size, its market value rising from 90,000,000,000 to more than $335,000,000,000 despite a recent pullback.
Speaker 1:AMD's strategy of positioning itself at the center of the global AI race has paid off handsomely, making Sue into a billionaire and her company into one of the only viable designers of powerful chips needed to power advanced AI models. In a market that has recently been complete completely dominated by NVIDIA, Sue is showing that there may be a place for a strong number two that can compete on
Speaker 3:flow, by the way. Check this out.
Speaker 1:Yeah. This is not the time to stay on the sidelines and worry, hey. Am I overinvesting? She said. It's much more dangerous if you underinvest than if you overinvest in my opinion.
Speaker 1:Let's go. I love that. As AI models like and Gemini become increasingly integrated into daily life and as companies design thousands of enterprise software tools that rely on AI models, demand for inference functions is about to go up by a billion times wonk said last month. AMD has a strong line of inferencing inference computing chips, but has struggled to design chips powerful enough to compete with NVIDIA in training. Is 200,000,000 the new 100,000,000 in luxury real estate?
Speaker 1:What do you think?
Speaker 3:Many people have been asking that. So there's
Speaker 1:a $200,000,000 house in Indian Creek, a $250,000,000 house in Bel Air, a $300,000,000 house in Aspen, and a $205,000,000 house in Palm Beach. A surge of ultra rich buyers has pushed asking prices to new extremes, yet many headline grabbing mega mansions languish on the market or trade for a fraction of their debut numbers just a decade ago. The 100,000,000 price tag was still considered a new frontier for luxury real estate. The first 9 figure home sale occurred in 2011. By 2019, there had been about 20 sales recorded at that price point.
Speaker 1:Now real estate insiders say a new pricing benchmark is setting the tone for the high end market, 200,000,000. There's going to be a massive wave of wealth created from the AI boom. And I would not wanna be in the
Speaker 3:market for a single family home within 20 square miles of OpenAI.
Speaker 1:There's, like, 40 people that are looking for houses in the five to seven million dollar range in North San Francisco, and there's none for sale because
Speaker 3:All cash offers.
Speaker 1:I'm sure. Yeah. From the from the liquidity.
Speaker 3:Yesterday, I resigned from TB Labs slash Meta AI. I wasn't there for very long, but I think I got a few useful things done.
Speaker 1:Nice.
Speaker 3:An impressive group of people. Here. And it's especially impressive that it got assembled as quickly as it did with such a high talent bar at a large company. Quote unquote founder mode is real and good. I will certainly miss my coworkers there.
Speaker 3:I think now is an unusually high leverage time to pursue ambitious new projects at the intersection of AI and other technologies. Please reach out to me if you're interested in that sort of thing. And I expect I will have something more detailed to share in not too long.
Speaker 1:Is that the sound of a thousand venture capitalists writing term sheets?
Speaker 3:Bernie Sanders.
Speaker 1:Okay. What's happening
Speaker 3:with Bernie? Firing shots.
Speaker 1:Here are some of the most powerful o AI oligarchs in the world enjoying a private dinner with a dictator who murders his own citizens with a bone saw. Woah. Does anyone really believe they wanna wipe out poverty or improve life for ordinary male Americans? I don't. And he's sort of mogging Greg Brockman here because he leaves Greg Brockman's net worth.
Speaker 1:He doesn't even try and estimate it. He just says question mark, question mark,
Speaker 3:question mark.
Speaker 1:Bernie Sanders' age. 75.
Speaker 4:Guess again. 78. Guess again. 77. Guess again.
Speaker 4:80. Guess again. 82. Guess again.
Speaker 1:I have no idea.
Speaker 3:84.
Speaker 1:84. Oh, he's up there.
Speaker 3:He's up there. So grandpa is
Speaker 1:is pissed. He's pissed.
Speaker 3:Yeah. I don't I don't blame Bernie for being a little bit salty at this point because he's never on those charts of of the best political traders. That's true. Right? He's It's true.
Speaker 3:He's been having to sit there and watch Nancy Pelosi
Speaker 1:He's run it up.
Speaker 3:One of the most insane runs.
Speaker 1:And he's just missed out. The FOMO must be crazy. Every day is opening up, and Nancy's up another mill. And he's just sitting there like, oh, I missed it. I missed it.
Speaker 3:Luxury watch guy is concerned about the Bitcoin sell off because he says there are gonna be so many effing APs on the market. Facepalm.
Speaker 1:Oh, no.
Speaker 3:The cryptocurrency industry certainly has been known to enjoy an AP. Yeah.
Speaker 1:Google's genius By not selling TPUs, Google allows NVIDIA to maintain high GPU pricing, which in turn props up price of inference. Google then captures that inference price premium by running TPUs for inference on GCP. This is a conspiracy theory by Dave three and thirty Tepper.
Speaker 3:Just just because you have two players in the market, like, doesn't mean you can sort of have a you know, what happens in the soda industry. Right? But effectively, like, the
Speaker 1:g l p one market. There's just a lot of demand. You don't need to cut prices. The
Speaker 3:price Yeah. And you also understand that there can be reason not to get in a race to the bottom dynamic and effectively have a gentleman's agreement to keep prices in a certain range.
Speaker 1:Of course,
Speaker 3:that can go too far.
Speaker 2:Yeah. But shower thought,
Speaker 3:why is no one doing outbound for pizza? Hey, this is Gigi from Gigi's Pizza calling. You ordered last week. We have a pepperoni pizza ready and could deliver it in ten minutes. Are you hungry?
Speaker 3:Tech sales guys has trillion dollar idea, and, of course, it goes viral again. Some, ideas, and bangers are evergreen.
Speaker 1:What is this story of the FBI raising a bounty for a former Olympic snowboarder who turned alleged drug kingpin?
Speaker 3:We love these stories. We covered this guy on the show before.
Speaker 1:Ryan James Wedding.
Speaker 3:He's married to the game.
Speaker 1:Is he? What is that?
Speaker 3:No. What? Ryan Wedding.
Speaker 1:Oh, Ryan Wedding. Okay. Yes. He's married to the drug game, I suppose. A former
Speaker 3:Olympic snowboarder from Canada. He represented Canada at the two thousand and two Winter Olympics in men's parallel giant slalom. Woah. After the Olympics, it is alleged that he became a transnational drug trafficker and orchestrated the murders of various witnesses. Woah.
Speaker 3:And he's only 44. So Wow. He's kind of just kinda hitting his stride. He was added earlier this year, March 6, to the FBI 10 most wanted. So he's in the top 10.
Speaker 1:10. They have any idea where he is? I wonder how he'd hunt this guy.
Speaker 3:And and they they're saying he's running one of the largest drug trafficking operation and is believed to be the dominant cocaine distributor in Canada. So from the Canadian Olympic team to the narcotics trafficking MVP status. Hard thing the hard thing is when they talk about
Speaker 1:Yeah. Because
Speaker 3:drug kingpins have just been the stars of of of so many different great television show Mhmm. TV shows and movies. Pam Bondi said he's the modern day iteration of Pablo Escobar.
Speaker 1:It's like somebody was about to turn him in, but they hear that, and they're like, oh, he's he's too cool to turn in. Can't do it. It's not worth it. I just gotta be friends with this guy. I'm living through history.
Speaker 3:Oh, wow. So after the two thousand and two Winter Olympics, he moved back to Vancouver and attended university. He got into bodybuilding and started working as a bouncer. After two years in university, he dropped out and began to speculate in real estate, which he financed by growing marijuana Mhmm. In a massive warehouse.
Speaker 3:He eventually expanded his operation and joined up with Iranian and Russian smugglers.
Speaker 1:Yeah.
Speaker 3:And, in 2010, he was convicted of attempting to buy drugs from a US Government Agent. Yeah. And he went to prison for
Speaker 1:There are so many startups these days that are going after Palantir's market, competing in enterprise software, enterprise AI, four deployed engineers. It's all a bunch of memes. Everyone's everyone's keying off of the, the Palantir strategy. I think if you're trying to play in that market, you gotta take down a most wanted fugitive. Yeah.
Speaker 1:You get the 15,000,000. That's your seed round. And you use this as marketing. The company that finds this guy, I'm gonna believe that your model's pretty good. Whatever you whatever you're doing, if you if you can find this guy, I'm gonna be like, yeah.
Speaker 1:Yeah. That's enough of an eval for me. You pass the benchmarks. I don't care your MMLU. Tell me how many fugitives have you checked off the FBI top 10 most wanted list.
Speaker 1:Thank you for tuning in. Thank you for listening. Thanks for hanging out. We love you, and we'll see you on Monday.
Speaker 3:Have a fantastic weekend.
Speaker 1:Have a great weekend. Goodbye.