Gemini 3 Reactions, Cloudflare Outage, The Upsides of Bubbles | Byrne Hobart, Glenn Hutchins, Yogi Goel, Sam Jones, Ali Madani, Amit Jain

26:34this has to be Washington D.C. yeah this was last night he says the future is bright and he's pictured with David Sachs, his wife of course Elon Musk, Jensen Wong what a fantastic photo Tyler did a green line analysis on this? I think Tyler was getting a little wild with this one. It's barely barely a failure. Jensen is not beating the... I don't know. I think he's standing up pretty straight. He's a little leaned over. Pull it. We gotta pull it up. Elon is standing up extremely straight with some wild shoes. People are saying, what are those shoes for? It's Nvidia earnings day. You gotta look for any signal they can possibly get.

27:13Pull it up. It's at the bottom of the timeline squad. here we go everyone is pretty dirty you did him dirty with that line I threw the line perfectly I'm with Tyler it's all about center of gravity right center of gravity anyways I think Jensen will put on a show later right after the show ends so we will look forward to finding out more Okay, well, Elon was pictured wearing some very, very crazy shoes. These are his SpaceX shoes. I don't know who made these. Look at these, Jordan. Whoa. Would you rock these? Could you pull these off? The team likes them. I'm not, I'm not, I don't think I could do that.

28:02Are these, like, were they made in collaboration with another brand? Or are these just, I don't know. Is he vertically integrating drip? I don't know. Yeah, did he make his own shoes? I have no idea. These would go for, I have a feeling they'd go for quite a lot. Yeah, they seem pretty cool. Let me tell you about Fall. Build and deploy AI video and image models trusted by millions to power generative media at scale. Bobby says they look like Yeezys. They do look like Yeezys. That's right. Quarter. The Quarter app has dropped the, oh, I got to follow them. Why am I not following them? um quarter app has dropped a uh an announcement that the nvidia earnings call will be tonight at 5 p.m eastern time as soon as we log off this stream you can head over to quarter and start streaming the nvidia earnings call uh jensen is there pictured uh all eyes on wong and uh they've done a fantastic job developing this image style i feel like uh it's been 2025 the the meta on X has been exploding in terms of like image macros.

29:18We've had a ton of fun with the trading cards. These have done extremely well. Anything where you can bring design and just tell a little bit more of a story, give a little bit more context, texture, something breaks through. And every time they post one of these 3 ,000 likes, people love them. Scroll down if you can. Somebody ran this graphic through mid-journey and it's pretty Crazy. So bad by comparison. I mean, it still goes pretty hard. Yeah. So, I mean... The arm there is looking a little... It's also an interesting testament to, like, I know that the quarter designers use MidJourney. They use AI, but they are really, really deep in the SREFs.

30:01They obviously have a whole bunch of different stylized prompts. And then it seems like they're also doing a ton of work in post-processing, layering text on top of it. they've created like a visual style that's distinct. I'm sure people will copy it, but it's definitely created its own sort of style and broken through. And at the same time, like it doesn't feel like, yes, there's AI involved, but it doesn't feel like if you just threw, you know, this prompt at a random person, okay, hey, go make one for, you know, Coca-Cola next week, I don't know that they could necessarily pull it off, even if they had a mid-journey subscription.

30:42There's still a lot of inspiration to understand what is the texture, what is the style. Right now on Polymarket, will NVIDIA beat quarterly earnings? It's sitting at an 87 % chance. The real question is, how will it trade? Yes. After the fact. Yes. It feels like we're in this weird market where you can beat on earnings and then sell off because nothing is ever good enough for the street right now. But we will see. NVIDIA is such a big story now that just the fact that they are going to have earnings is essentially front page news, at least of the business and finance section. NVIDIA and jobs data coming.

31:24Reports will provide key signals for investors after a market pullback. The fog masking the direction of the American economy and future of the artificial intelligence boom is starting to lift. after mounting scrutiny of stratospheric tech investments, as well as a blackout of federal data during the longest government shutdown in U.S. history. Wall Street awaits two reports that stand to reshape its outlook for the months ahead. AI poster child NVIDIA is due to report earnings after the closing bell Wednesday, offering a snapshot of demand for chips that are a linchpin in the tech mania that has lifted markets and helped buoy the economy.

32:03Also, with the NVIDIA news, it's like, how much can you actually read into AI demand based on NVIDIA earnings? Because I feel like we're projecting out these deals five years in advance. We buy the chips, then we install them. Are we really seeing that whole rumored decline or deceleration in chat GPT growth? If that is real and that's happening and chat GPT usage is starting to plateau from 800 million weekly to, hey, next year, it's going to be like 900 million, a billion. Like it's not going to be 5 billion next year. If that's happening, are we expecting that to show up in the NVIDIA data this quarter?

32:47Like probably not, right? Because like OpenAI has projected out five years of demand for GPUs. So I don't know. It seems hard to actually read into NVIDIA's earnings as a real snapshot of demand. I mean, I guess demand for chips, certainly. A sell-off in NVIDIA has dragged down indexes with Peter Thiel's macro hedge fund and others dumping shares. It's sort of crazy that that's in the journal. Yeah, especially when it's the equivalent of the average person in tech selling a$10 ,000 position in the company. It's not super notable. With no statement either. It's not like, oh, yeah, he was also on Rogan Tom trash.

33:30It's like nothing. The tremors extended beyond other AI names into crypto, gold, and more. Even Warren Buffett's latest big bet on Alphabet hasn't staunched the bleeding. America's richly valued stock market has retreated in similar fashion several times during its years-long run-ups. In every instance, bargain hunters snapped up stocks, tech companies out profits. and the economy kept on motoring ahead. The fact that there's, yeah, we can move on. Yeah, I mean, the reason there's fixation at NVIDIA is currently, it's like 8 % of the S &P 500. That's crazy. So like it just, it matters more than any other.

34:16This feels like the most important earnings call of the year, given the sell-off in NeoClouds, given the pressure and debate around OpenAI, given Google's investment and progress with the TPU. I mean, there's so many different factors. In related news, it got announced this morning, Musk's XAI and NVIDIA to develop a data center in Saudi Arabia. It's a 500 megawatt data center in Saudi. Saudi, XAI is working with NVIDIA and a Saudi Arabian partner to develop a data center in the kingdom. Musk said Wednesday at an event with the crown prince, they're teaming up with Saudi Arabia's AI company, Humane.

35:02This can be 500 megawatts or enough electricity to power several hundred thousand homes for a year. The announcement came at the U.S. Saudi Investment Forum. Of course, the crown prince announced a trillion dollars of investment in the U.S. yesterday. President Trump touted Saudi's investment in the U.S. and the partnership between the two countries. My question is, there's no information here on how this data center is going to be used. Do we expect XAI to be operating and competing as an AI cloud, or is this going to be something that they want to have a local version of Grok? right and i would and and to me it seems much more likely that they're just going to be in the like they just want to be in the in like the data center business yeah oh yeah that's a very interesting and to me that's always made sense because elon is clearly better to get that pretty much best in the world i mean he was he was mogging uh microsoft for bragging about how many million work hours 15 million work hours like more than more than uh and so clearly very good at large-scale physical infrastructure build-outs, getting access to energy, doing things on a ridiculous time horizon.

36:22And so in order to support XAI's valuation, I could see them trying to get into that game. Yeah, I mean, there's also the possibility that if there is strong U.S. inference demand, but latency is not an issue, it might be valuable to actually just co-locate the data center next to the oil, because maybe the energy is cheaper. Midjourneys, I believe, have been doing that for a very long time, doing inference internationally because the data center demand during peak hours in the United States is more expensive than across the world. Let's pull up this clip. And while we do, let me tell you about graphite.dev, code review for the age of AI.

37:06Graphite helps teams on GitHub ship higher quality software faster. Let's go to Elon Musk saying AI and humanoids will actually eliminate poverty. Eliminate poverty. And Tesla won't be the only one that makes them. I think Tesla will pioneer this, but... ...humanoid robots. But AI and humanoid robots will actually eliminate poverty. And Tesla won't be the only one that makes them. I think Tesla will pioneer this, but there will be many other companies that make humanoid robots. But there is only basically one way to make everyone wealthy, and that is AI and robotics. and we can't talk about robotics without AI what do you think?

37:47all problems in the world solved by one product I love it it's not the craziest take over a long period of time you give everyone the ability to marshal anything I wonder if we'll redefine poverty at that point. Poverty will be not having a beachfront property, a beachfront mansion or something. Something that's truly scarce. This is my land thesis. Even an army of humanoids can't necessarily give everyone their own island. We joke about land a lot. We joke about it being the most undervalued asset by the current generation of investors. But land is the one thing that even with an army of humanoids, like you can't as easily like copy and paste, right?

38:40Like it's just, it truly is scarce. It's not like land on the blockchain where people were like, no, like you can buy this plot of land on the blockchain and that's yours forever. And somebody's like, what if I just make another blockchain? Exactly. That was the most ridiculous. And I can also get from this piece of land, I can get from this piece of land on this blockchain to this other piece of land on this blockchain in a second. Yeah, it's ridiculous. If you have enough humanoid robots though, then land is actually not that hard to get. Why? because you're saying like you would just put enough dirt in the ocean and like it's like oh you're good at Mars you had this ocean or you have a robot army robot army oh and then you just steal then you just take but but I think I think what Elon's saying is like if you assume universal basic humanoid army everyone gets 10 humanoids and so the humanoids can cook for you they can give you shelter they can clothe you they can give you health care so you get everything that you know would typically be bucketed in poverty, but there's still scarce resources.

39:38There's only going to be one Mona Lisa. And so you got to fight over that. Orange is in the chat. So the humanoid form factor is silly. Make it an R2-D2. I'm actually surprised. Yeah, so one Matic. I got to give a shout out to Matic. They've been crushing it. My Matic has been running in my house. The reviews have been fantastic too. Personally, I've been running it in my house daily for months now. That's fantastic. And it has worked flawlessly. Yes. Go check it out. I had like, you know, I feel like everybody's been disappointed by like a vacuum robot over the years. And so I didn't have the highest expectations, even though setting it up was like fast and it got to work quickly.

40:18But I've been shocked at how just well it's worked and haven't had to think about it. You replace the little bag every once in a while. And it's great. But R2-D2 form factors. We'd love to see more of that. What do you want out of an R2-D2 though? Because the Roomba form factor, the Matic form factor where it goes and cleans, like that's pretty useful. But if you, like, is it an R2-D2 that it can fold your laundry, do your dishes? Like you need to sort of define a few different, because clearly we're going to be in the age of like spiky intelligence and also like spiky humanoid usage. Like they're going to be good at some stuff.

40:59I think in R2-D2 form factor, you could reduce the number of motors that you need. It could potentially carry more weight. Carry? So it's going to carry you? Are you going to ride it? No. Explain what it's doing. Because in the classic Star Wars, R2-D2 is basically just a hard drive that carries a video. That's all he does, the whole movie. Yeah, but you can imagine it has a number of different... What does it have? What does R2-D2 have? Have you seen the movies? Doesn't it have like a screwdriver? It has a screwdriver. It's basically a USB cable that comes out and like plugs in. When it's like you could just use wireless to hack the network or whatever.

41:40That's true. No, the other challenge with that form factor is you have – so it's great if you have like a one-story home. If you have a second floor, RTD2 is kind of cooked. RTD2 starts asking like – Totally cooked. He's like, hey, we're going to need some more CapEx. I need some more – Can we get an elevator? Elevator, please. I think if you want to talk about like Star Wars factors, I think the optimal is General Grievous or whatever the one that has a bunch of arms. Yeah, it can walk around like a normal human, except it has more arms. No, I completely agree with that. Bunch of arms form factor.

42:14Yeah, everybody wants to make a humanoid. Nobody's trying to make the General Grievous. General Grievous is way better. Six, way better. Or lightsabers. You distilling R2-D2, it has a screwdriver. It's like the most just completely mogged. But, I mean, truly, other than just being, like, cute. R2-D2 can't even speak English. Think about that. R2-D2. It just goes beep, boop, beep, boop, boop, boop, again. I mean, the implication was, like, the general form factor of something that can roll around and has a lot of different capabilities built in. It doesn't have any capabilities. It has no capabilities.

42:53Can we pull up General Grievous on the screen? RTD2 hacked the Death Star and saved Luke from the garbage disposal. Yes, two things that could have been done with wireless networking. It didn't need to plug in for that. It is a hard drive. I'm getting into battle with the chat right now. Can we tell the story of us risking our lives yesterday? We really should. Yeah, this was truly incredible stuff. So we're looking, we're in the Ultradome here for at least another year, but we're starting to think about our second, the next Ultradome. Ultradome V2. We want to get slightly more space. There's a number of different things that we want.

43:38There's General Grievous. That is the ideal humanoid form factor. And if you're not building that, it's a zero. What are you thinking? I think Optimus would look way better with six arms. Not scary at all. It is crazy. They do the quadrupeds, but no one's really working on the six-legged, six-arm, like the really crazy, creepy stuff. There's been a couple of humanoid robots that look really scary where they're like, wow, let's put it up on the meat hooks. Remember that one? That was crazy. That was a wild one. Was that the video where it started going? No, no, no. That's a different one. But this was a company that was like, here's our presentation.

44:15Like we're ready to release our humanoid and we're like hanging it up on meat hooks and it looks so spooky because it was using muscle fibers basically. Nathaniel Smith is very bearish on R2D2. A cell phone can do most of what R2D2 can do. Completely agree. R2D2 cute for sure. Like definitely like fun to have around but more of just like a toy companion. And, you know, we looked at that lamp and that lamp we were kind of like what is that lamp? And I think there's just like it's just delightful. Like, it's just nice to have around. It's like this Turbo Puffer thing. Search every byte. You know, serverless vector and full-text search.

44:50Built from first principles on object storage. Fast 10x cheaper and extremely scalable. Like, the Turbo Puffer, I mean, obviously, we're sponsored by them. But this is something you might have in your house just because it's cute. People like having cute things around. Many people have asked to have it in their house. And having an R2-D2 in your house would be cute until it runs into a stair and goes tumbling down and smashes into a million pieces. Tell the story. So we found a space that we love. It's dome-like. We're looking for a space in L.A. that is fit for the Ultra Dome. There's not a lot of things that qualify.

45:23And so we had looked at the space a couple times. I had seen it with Ben. John and I drove by it, and then we went back to do another walkthrough. You were excited. And we're getting like, I'm like extremely excited about the space. I'm pitching John on, here's where this thing goes, here's where this goes. On the way to the show in the morning, you make me poke my head through the window. I was really selling John on it. Then we go back at the keys. We go in. Really selling John on it. It's a beautiful space. It's like a few minutes from where we are now. Made a lot of sense. Ethan says R2-D2 was the original digital guy.

46:01True. Yeah, digital guy is incredible, for sure. Sorry. Anyway. So anyways, we go for the third time to this space, and I'm just selling John on every inch of the space. I'm like, this is what we're going to do here. This is what we're going to do here. Here's where the truss is going to go. Here's where the production team is going to go. And we're just walking around kind of getting a feel for it. And we're basically wrapped up. Like, we're super excited about it. Not necessarily ready to make an offer on it, but certainly, like, we're like, okay, this is by far the best option that we've found.

46:34We've looked at a bunch of stuff. Checks a bunch of the boxes. Checks a lot of boxes. And right as we're about to leave, John looks over and there's a closet door with a key in it. And you just walk over. I just watch you walk over and open it up. And you start looking around. And first, I make the joke. I'm like, oh, this is the intern closet. Because it's this really long, narrow hallway thing. It's the worst room you can imagine. And so the idea of putting Tyler in it was at least entertaining. and then we're like, wait, what's that humming sound? And there's like this box that's like covered up and it's just like this like, not super loud, but just like constant humming sound.

47:12And we asked the broker, we say - It was super weird because it was drywall. Like you walk into this big room, it's a big room and then within that big room is a massive drywalled box. With no entrance. No entrance to the box, but it's drywalled. Like you don't usually see drywall inside of a room that doesn't go all the way to the ceiling. And so it was very clear. And so we walk into this room that has. Behind this drywall, they were hiding something, basically. And there's no purpose to the room. Yeah. Other than it just stores the box. It stores the box. That has no entrance. That has no entrance.

47:41And it's humming. Yes. And we look around, and John's like, what's in the box? And the broker says, oh, that's just the machine that cleans the soil. No, no, no. She said, that's just the machine. That's just the machine. And we're like, oh, like. What kind of machine? What kind of machine is in there? And she's like, don't worry about it. She's like, don't worry about it. It's not a big deal. Yeah, just like, you know, buildings have machines sometimes. There's a machine in there. It's a machine. And it's always on, but you don't, it's, we took that out of the square footage. So don't worry. Oh, yeah, that was a wild one.

48:16We took it out of the square footage. We're not billing, we wouldn't bill you for it. And so we were like, okay. Yeah, it was like, what type of machine is it? And then she goes, it's a machine that cleans the soil. And we're like, is this on like some sort of haunted burial ground or something?

48:30And she goes, again, really not a big deal. I would worry about it if you were going to buy the place. But since you're just planning to lease, don't worry about it. And then we were like, okay, like the more you tell me not to worry about it, like I kind of want to know more. So what's it cleaning up? And she's like, oh, I mean, it's 85 % of the way clean. We're like, what's getting clean? When did this process start? How long will that go? Has it been going for 100 years? It's going to be 15 years. Will the machine start an hour ago and it's just going to be 15 more minutes? You gave us no context to actually project out what 85 % of the way means.

49:11And finally, she's like, there was a laundromat here ago. And we start piecing it together. And we kind of don't want to press her on it too much. So we leave and start doing some Googling. We figure out that it's not a Superfund site. But apparently there was a laundromat there that was using toxic chemicals that - No, it was a machine shop. Oh, a machine shop. Oh, that's what we figured out. Yeah. So they said laundromat, and apparently laundromats can give off toxic chemicals that if they get in the ground can be very cancerous for a very long time. This was apparently a machine shop like almost 100 years ago or something.

49:45Yeah. And they're working on cleaning the soil. but I still don't even understand how you clean all of the soil under a massive building without causing a collapse is it like a whole bunch of tunnels that are digging around a bunch of r2d2 robots maybe it's a bunch of r2d2s honestly anyway so so she's still saying yeah I really wouldn't worry about it it's just like not that big of a deal it's just a machine it just runs well you won't even know that it's running we'll keep the door closed and granted the machine would be like 10 feet from the set so we'd be sitting here doing the show and and you just have the the death machine running right there always so and it was very very bizarre it was one of the funniest like just like jump scares ever uh very it was just it was such a good bit too because i'm i'm far more health conscious i think than you and even you were we're thinking there's no way we're going to lease an Ultradome that has a death machine that always needs to run.

50:44I found it so fascinating that it could sit there and clean the soil for years with a massive machine the size of a giant room. I want to learn more. I want to know what that machine is. I want to know what company makes it. I want to invest in that company. Exactly. That's what I want to know. We've got to figure out how to make money on the machine. We've got to have the CEO of whoever makes that machine on the show, I want to get to the bottom of it. We need to do a deep research report. Tyler, can you fire off Gemini 3 Pro deep thinking max 24-7 mode where it works for ages, works for eons?

51:18So I found two groups, CDE group, soil washing equipment. Our wet processing equipment extracts maximum value from hazardous soil. So is it just that corner that has the hazardous soil. What I want to know is, is it going under the building and then over so that underneath us over here, the machines here, is it digging a tunnel that goes underneath the building and then washes over here too? Is there a network of tunnels under that building? I have to know. We have to go back. We have to lease this thing. We have to buy the building just to get to the bottom. Just to get to the bottom of it. I have to know.

52:00I'm ravenous for information. Yeah, the cool thing is they use physical and chemical methods to separate heavy metal from the soil. That's super cool. That's super cool. That's exactly what we want. That's exactly what we love. Well, in other news related to water. I think I found the machine. We've got to pull it up. I can't leave people hanging. Yeah, I dropped one of the bakers of these machines. It sounds like fracking. Yes. Because if we could frack directly some natural gas out of the soil and then use it to power a natural gas turbine that we use to run the show and power us, I'm down for that.

52:40While you're looking that up, let me tell you about Fin.ai, the number one AI agent for customer service. If you want your AI to handle customer support, go to Fin.ai. So in the water news, okay, you want to pull up that and then we can go into the water news. I got to talk about Andy Masley at some point this show. I just want to see your reaction when you start to see the scale of this contraption and how it pretty much perfectly fits into the box. Yes, yes, yes. Fracking with extra steps. Language, please. Was someone swearing? I don't know. Anyway, let's pull that up. Let me also tell you about Profound.

53:20Get your brand mentioned in chat. reach millions of consumers who are using AI to discover new products and brands. Let's see about this water story. Andy Masley is going back and forth with, what's her name, Karen? The AI and the environment, somewhat related to our own environmental story that we could kind of go through. How we doing, boys? There we go. Look at this, John. This is from GN Separation, Core Equipment for Contaminated Soil Washing. And you just look at this machine. This is pretty much exactly what would have been in the room. Soil washing. You have to wash all the soil. And there's a graphic if you scroll down a little bit more.

54:12I want to know so much more. Look at this. It's a simple process. It's 85 % done. It's 85 % done. We just need to get the hazardous waste into the decanter centrifuge and then get it into the non-acceptable solid second wash. Then take the acceptable solid up to the coarse screen into the washing fine screen. And then take the washing chemical and bring it up into the washing reaction tank. Put it back in the centrifuge. Push it down into the soil. Filter press. De-watering screw press. And then move it back up through the hazardous waste, John. And you're good. So Doug is asking, if it's behind drywall, is that because it generates fumes?

54:55We have no idea. Maybe it does generate fumes. We still don't know how they access it without knocking down all the drywall. Yeah, we don't know how they access it. Is the drywall just up? And also, I really want to know, was there another entrance that someone could go into? What if the machine breaks while we're there? Does someone come by and change out something? Does this machine need to be turned off at night? Does it require, is it fully automated? Does it just run for years? Would we have never seen a technician come by? What if it gets jammed? Like, is it just the most flawlessly built machine in the world that never breaks?

55:27That seems unfathomable. All machines break. All machines need some level of attention from time to time. But maybe it's the most perfect machine possible. And the machine is, of course, made by Hebei GN Solids Control Co., which is a China-based company. Wow. Well, we don't know that this is the actual machine, but who knows? Anyway, let's go over into the environmental impact of artificial intelligence. There was a very funny post from Henry Thunberg who says, Whoa, I had no idea that AI uses 5 ,329 ,584 water per year. That's insane. Like it uses just one water. Yeah, people are all over the place at the water thing.

56:14It's so interesting because no one is debating that it uses a lot of energy. Like you could just have all the same discussions about energy. Like we're actively burning natural gas for a lot of this AI stuff. Like all of the old school don't cause global warming by burning fossil fuels. Like all of those claims apply to AI today. Like you could just make those claims. But instead, everyone seems to have been like caught up in this water. Oh, the water usage is so bad. And it's like you had a layer right here, which was like we're burning fossil fuels and that's bad. Is it because water feels more scarce to people than electricity?

56:55Maybe. Energy in general. It's like if I can't drink water, I die. But if I can't access natural gas, like I can still live maybe. Yeah. Or the sun beams energy on the earth daily. Yeah. And maybe it's easier to spin move out of that being like, well, we're doing nuclear and solar. tomorrow next year we're doing we're doing nuclear and solar so so like you don't it's not a gotcha that i'm using natural gas today because tomorrow i'm going to be using nuclear and solar um maybe maybe whereas the water issue might be like more like it's not as concise to to wrap up in a bow but anyway um we covered this story yesterday a little bit uh and i and i wasn't able to pull up the original post andy masley called me out he put me in the truth zone he said john you follow me how do you not know where the story broke?

57:40I broke the story. And yes, Andy Masley, you did break the story. And so we wanted to run through a little bit of this post to actually understand the claim about what he's saying went wrong here. And basically, the high level is that he says, this is the single most massive factual error in a major book I've ever personally noticed on my own. And I think I'm the first person to notice it. Empire of AI asserts that a data center is using 1 ,000 times as much water as a city. In reality, it's 22 % of the city's water. And so the chapter turns to Chile. We talked about this a little bit. It's a unique combination.

58:21Look at this line again. So the line says, in other words, the data center could use more than 1 ,000 times the amount of water consumed by the entire population of Surillos, that Chilean city, roughly 80 ,000 residents over the course of a year. How justifies this number in the notes saying, in other words, the data. The Google Environmental Impact Report to SEA stated that the data center could use 169 liters of potable water a second or 5 million. Oh, it's right there. That's the same number. 5 billion liters a year. According to the Water Service Authority in Cirillos, the municipality consumed 5 million liters in all of 2019, the year Google sought to come in, 5 billion liters a year divided by 5 million liters equals 1 ,000.

59:09Something isn't adding up here. It doesn't make sense that you could use 1 ,000 times the amount of water used by that city. And so Andy Masley has successfully put this book, Empire of AI, in the truth zone. And we thank him for his service. Let's go back to the timeline. But first, let me tell you about Numeral.com. Let Numeral worry about sales tax and VAT. Numeral.com. New product from Travis Kalanick. That's exciting. Big. Try picnic.com slash request picnic. Travis says, I'll come out of Twitter retirement for this one. Picnic at work. LFG. Great job. Picnic is delivering lunch directly to your office floor with no fees and no tips.

59:55Every day from 50 plus restaurants. sign up your office for free. Okay. There's only one benchmark for this stuff. We got to look at the benchmarks. What's the max amount of protein? Is it over 200? Are they protein maxing? Or is it over 200? Because we saw a major, major jump in the amount of protein in a bowl yesterday with sweet green. Sweet green's at 108 now. This is the most important benchmark in the bowl economy, which I'm a huge fan of. But are we seeing acceleration? Are we seeing a fast takeoff in the amount of protein? I want to be seeing 200 grams of protein, then 1 ,000, then 10 ,000, then 100 ,000.

1:00:36It should be 10xing every year, just 10x that. Yes, exactly. So everyone's always talking about fast takeout, but we need to be talking about a fast takeoff. Fast casual takeoff. No, just a fast takeoff in protein per serving. Yes. Anyways, I think this is smart. This has to be built on top of Cloud Kitchens. Cloud Kitchens. I wonder if it's a separate company or it's just a subsidiary, kind of a front end for Cloud Kitchens. and uh but either way i think people just don't like paying delivery fees and uh and tipping too is still uh you know debated yeah so you get and part of it part of it is like i feel like a lot of a lot of these things if you just build it into the cost of the food people feel better about it but when you're when people are forced to make the decision around tipping for something they want to do every single day.

1:01:32And it's like, well, uh, you know, maybe, maybe it's great sometimes, maybe it's not, but you're setting these things oftentimes before. Yeah. Uh, so yeah, a lot of the tipping stuff, it just, it needs to be, uh, like injected in the UI at the right time. And a lot of the apps don't necessarily, uh, like, like prompt for the tip at the right time. Like if you ask, if you ask for the tip before the service is rendered, it's hard to use the tip as a, as a quantitative feedback mechanism. Exactly. Exactly. So, so I will, when I order, I ordered delivery from a grocery store and I tip like upfront.

1:02:11Do they see the tip? That's the other thing. I don't know. I don't know. In theory, I'm like, I'm going to tip because I want you to not throw the drinks a bunch. Exactly. I do that. But, but then, yeah. Getting the, the fact that we've just normalized getting an exploded bag of drinks in a bag is just funny. Back to the press release economy. Today's press release is out. Brookfield today announced the launch of a$100 billion global AI infrastructure program in partnership with NVIDIA and the Kuwait Investment Authority. There are tons of press releases going out every single day. Daniel Tenriro says, running a business is all about partnerships.

1:02:54It's all about announcing partners. It's not even about, you don't even necessarily need to do the partnership. You just got to announce the partnership. I mean, the partnership economy is going crazy right now. The prediction markets are obviously the most heinous offenders with a new partnership every single day. It's hard to keep up with. We obviously are partnered with Polymarket, and we want to celebrate them when they do great things. But there's a lot of these things going on. And so we tend to give you a little bit of a higher level review. On the prediction market front, somebody just leaked a bunch of screenshots from Coinbase's upcoming prediction market.

1:03:31Everybody's getting into this game. There's different approaches. Some are partnering with existing prediction markets. Others are building it entirely themselves. I'm more interested to see if when Coinbase does their prediction markets product, how are they actually running it under the hood? Are they taking on the responsibility of actually managing the markets, being a market maker? What is that actually going to look like? They should just hire a guy on the other side of every trade where you just go to Coinbase and you say, look, I want$50 on the Eagle. And the other guy says, yeah, I'll take that.

1:04:05I think they're going to lose. And that's how it goes. It should be a guy that you call. Almost like a bookie. They should acquire mybookie.ag. Maybe mybookie.ag should pivot to not having any digital experience and just lean into being. No, no, no. Lean into just the guy method. Oh, the guy, yes. Actually being. Become a guy company. Well, Cloudflare unfortunately had an outage yesterday. We were not affected. Although, Tyler, do you want to take us through how we seem to be dodging exposure to Internet outages lately? What's going on? Well, so, I mean, to be clear, all my systems were fine. But I recently moved some of the kind of back-end processes we use onto, like, a local machine.

1:04:49Yeah. You went on-prem. Yeah, on-prem. And then I used Cloudflare tunnels to, like, help do, like, API stuff. Okay. So I was worried for a second that the stuff that I moved off AWS onto on-prem was actually going to go down because of a cloud. Yeah. Because AWS was down, what, two weeks ago, three weeks ago or something? I think it was longer than that. Maybe longer. That one was rough. I feel like that day we actually did cancel a bunch of guests. There was a lot of stuff going on. We've had a few rough outages, but let's read a little bit of the postmortem from the journal because it did make front page news.

1:05:24Obviously, sending our best to Matthew Prince over at Cloudflare and the team, hoping for a swift recovery because we love the internet and we love them. An outage that knocked swaths of the internet offline was resolved Tuesday after drowning social media sites. disrupting retail sales, and stalling transportation networks. Users visiting sites including X, ChatGPT, DoorDash, Ikea, Metropolitan Transport Authority in New York City were met with error messages related to Cloudflare, a cloud provider used by major companies for security tools that protect from cyber attacks and traffic surges. A spokesperson, a spokeswoman from Cloudflare said an unusual rise in traffic to one of its services at around 6.20 a.m.

1:06:09Eastern time caused traffic passing through the company's network to experience errors. The bug was fully resolved by 9.30, she said, in an update. For several hours Tuesday, users were unable to access sites and services from retail and social media to financial services. The outage echoes problems with AWS. Cloudflare and AWS services were effectively invisible to users, but their tools underpin many people. So I don't know if there's a full breakdown here. Last year, a bug in a tool used by cybersecurity company CrowdStrike upended computer systems across the world. There's just a lot of these going on.

1:06:45But I don't think we have a full postmortem. I would love to know exactly what happened. It's always interesting. We failed our customers. I'm interested to know what happens to the business when they have these outages. Because on one hand, it's a great way to tell the world that the entire world runs on Cloudflare, or at least like a large amount of Super Bowl ad. Yeah, it's like super very very much so. Yeah, and then and then you talk about the stress from the Cloudflare team where anybody that's built a software product has experienced the product going down and the stress around that. But it's it's like when your product goes down and then and then you know many of the services that people use and love across the country and the world also go down it's even more stressful.

1:07:26but it also probably brings like a ton of, you know, ton of traffic to the site. And people might start evaluating some features and say, hey, maybe this is a good solution. I'm going to watch, I'm going to sign up and see how they kind of react to this. Well, I mean, the Cloudflare team like reacted very well. They got a lot of praise for their response. Dane Connect here says, or Nekt, he's the CTO of Cloudflare. He says, I won't minch words. Earlier today, we failed our customers and the broader internet when a problem in Cloudflare's network impacted large amounts of traffic that rely on us.

1:07:59The sites, businesses, and organizations that rely on Cloudflare depend on us being available. And I apologize for the impact we caused to transparency about what happened. And we plan to share a breakdown with more details in a few hours. In short, a latent bug in a service underpinning our bot mitigation capability started to crash after a routine configuration change we made. that cascade into a broad degradation to our network and other services. This was not an attack. That issue impacted, caused, and time to resolution is unacceptable. Work is already underway to make sure it doesn't happen again.

1:08:33But I know I caused real pain today. Ooh, I know I caused, I know it caused real pain today. The trust our customers place in us is what we value most just taking full responsibility here lulu says um well done response and the comments reflect that people in the comments are very happy um mert of course always having fun okay thanks dane but have you considered that blockchain's handling 0.0000001 of your load did not go down very funny um there was another company there was another company has a picture here from uh from shogun i think uh says cloud flares comms playbook i ask permission to commit seppuku because they're just like fully throwing themselves down just being like yeah we're 100 responsible we won't mince words pretty sweet uh we should uh get into mr hobart's piece we should he's joining the show in just a few minutes tyler before i they're breaking news OpenAI, new model.

1:09:35New model. Yeah, GPT 5.1 Codex Max. Okay. They're firing back. They're firing back. We were debating, did they have the juice? Well, what's interesting is that Gemini 3, the one benchmark that it didn't outdo Anthropic on, it was better in a lot of benchmarks, but it wasn't better at Sweebench, correct? Correct. And so that was, of course, a testament to Anthropic being really, really great at doing just something special in code. Obviously, that's aligned with their mission of reaching super intelligence through self-replicating code, essentially. But a fascinating durability of their business that even with this Gemini 3 thing that's so good at all these different things, Anthropik's still on top in Sweebench.

1:10:18But do we know how OpenAI is faring in this bench? Is there any reaction? What can you tell us about the latest model from OpenAI? Because we've got to get to the bottom of it. And while you look it up, I'm going to tell everyone about Vanta, automate compliance and security with the leading AI trust management platform. Also, Suno raised$250 million to build the future of music. I'm going to hit the gong while Tyler pulls up the reaction.

1:10:47Great hit to open up the day. While Tyler gets into that, there is some breaking news. Glue has hit the public markets. Christian Tech Group tests investors' faith in AI deals on Wall Street debut. Shares in a company backed by former Intel chief Pat Gelsinger. Waiver after scale-back IPO. I didn't realize that Glue was IPO-ing. No, I didn't know. Pat's company. Shares in a company developing AI software to connect Christian organizations across the U.S. wavered in its Wall Street debut following a scale-back initial public offering. That's very cool. Glue counts Pat Gelsinger as exec chair and video rental store Blockbuster's former chief operating officer, Scott Beck, as chief executive rose as much as 5 % after it began trading on NASDAQ on Wednesday morning, having raised$73 million from investors.

1:11:45The average share price pop for a U.S. IPO that has raised$25 million or more this year is nearly 25%, according to Renaissance Capital Management. Founded in 2013, Glue hopes to pull the Christian faith into the digital age by using values-aligned generative AI to distribute content and sell marketing services to ministries and community outreach groups. There's an imperative to shape technology for good. On its own, it isn't good or bad. The question is what it's used for, Beck told the Financial Times. And anyways, so wasn't tracking this one, but really enjoyed having Pat on the show. a while back.

1:12:23Yeah. No, he was amazing. I'm very excited for him. He's just like, I don't know, just fun to talk to. Let's run through Bern Hobart's economist piece. But first, Tyler, did you give us any updates? Yes. So previously, the codex, as we bench verified, was 73.7. And now, with the highest reasoning, it's at 77.9. And then Sonnet 4.5 is, it's always kind of hard to tell what exactly it is because people measure it differently. Yeah, don't they take some of the questions out sometimes? Yeah, sometimes they do that. So Sonnet 4.5 is officially 77.2, so that's lower. But then with parallel test time compute, it's at 82%.

1:13:07So it's kind of unclear what that really means. But it's definitely better. So this is a big improvement. Isn't Parallel Test Time Compute just a real guy who's just kind of sitting there being like, oh, actually, don't do it like that. Do it like this. I think the main headline is that they said... Yeah, tool use. You find a dude who's a bit of a tool, and you tell him, hey, I can't solve this. You've got to do it, human. I've got to kick this one out to you. Do this arc puzzle for me. AJ, our incredible broker, is in the chat. He's talking about the office debacle. He said, LMAO, I still can't believe that happened.

1:13:44Maybe something the landlord broker should disclose before tours. I can't believe he's in the chat watching us. AJ's been incredible finding us every possible space in the greater Los Angeles area for the next Ultradome. Highly recommend if you're in the LA office market. I also recommend Figma. Think bigger, build faster. Figma helps design and development teams build great products together. So we have our update. We will keep monitoring the GPT 5.1 Codex Pro Max story. One more thing. There's an interesting headline. They said there were some tasks they found that the model worked for more than 24 hours, which is like if you're following that one meter chart where it's the time horizon.

1:14:33That's super interesting. Definitely a good sign. Have you ever worked for 24 hours straight? Buckle up, buddy. It depends on how you define it. Time to take it for a spin. Yeah. Tyler Bench. I would love to know what it actually is doing for 24 hours. I want to know the prompt, and I want to know the output. Yeah, that's what people are asking. Yeah, of course. They didn't say that in the press release. Because, I mean, it's like just sit there. It was working on the easiest problem just trying to debug it because it's so bad. Yeah, or, I mean, there is a world where it's like, hey, the prompt is like, just go take a crack at every single open GitHub issue on every repo for as long as you can and work on it.

1:15:14And then you're basically just wrapping another for loop around it. And it's like, is that one continue? Like there's obviously a lot of, but even if it is that like having a task that you can continuously work on, just having a like kind of plan that you can maintain, you don't get lost. Totally. It's still like a big improvement. Yeah, no. I mean, in general, I would imagine that there's maybe some SaaS productization, but there's also just a ton of value to having agents that sort of roam through your organization continuously and clean up data or look for different errors or just do opportunistic tasks.

1:15:48That seems very bad. Trey says count for 24 hours. Yeah, Tyler, do you think you could count for 24 hours? Mr. Beast has literally done that. There's a YouTube video up. I think it's 24 hours. What about doing one rap of 135 every five minutes for 24 hours? That would probably get absolutely brutal. I don't know if that would. I think most people. It sounds like it doesn't sound bad. Yeah, it sounds very easy, but I imagine it would be very difficult. Anyways, we have to talk about Bern Hobart, Bern Hobart, the legend of Bubtalk. The king of Bubtalk. Yeah. He wrote the book on bubbles. He wrote the book on bubbles.

1:16:31He's in The Economist. He says, how I learned to love financial bubbles by the author of a book on bubbles. So he says, tech stocks have sold off this week over fears of frothiness and artificial intelligence, AI. I love that. Economist adding that in. Some investors were no doubt surprised by this. But for the others, the question. Some reader out there is just like, I never put that together, that artificial intelligence was the thing that people were talking about. They have a very broad audience of The Economist, but I absolutely love The Economist. I've been a subscriber for probably over a decade.

1:17:07The signs of an AI bubble have been there for some time. Clearly, whose original product was a tool for using AI to cheat during Zoom job interviews, raised$15 million and then dropped its cheat on everything tagline and pivoted to being a more benign AI meeting assistant. More serious AI labs have been able to raise 10-figure sums and 11-figure valuations, not just pre-revenue, but pre-product. Individual researchers have reportedly been offered nine-figure signing bonuses, and in the past year, the spending commitments made by a single company, OpenAI, total about$1.4 trillion, a sum equal to 1.2 % of global economic output.

1:17:48A frenzy like that is enough to make you long for the relatively sane and responsible days of the pets.com sock puppet or the synthetic CDO squared. You want to continue reading? Yeah. But bubbles are tricky things. The default school of thought is that they're driven by irresponsible speculators who aren't trying to invest in great companies, but to buy something they can flip to someone more gullible. A more benign theory is that there are wealth transfer from rich investors to everyday consumers. People who bought telecom firms, junk bonds in the late 1990s lost their shirts, but the rest of us were blessed with bandwidth cheap enough to support the likes of YouTube and Netflix.

1:18:26This is one of my favorite takes of his is that in the bubbles, like when bubbles pop, rich people actually get hurt more than Main Street, which I think is not how it's framed most of the time. It's because, yes, there are some retail traders that go crazy and put, you know, they have a five-figure net worth and they put it all in the most risky NFT and they do lose it. Like there are some anecdotes like that. But in general, most people have a pretty diversified asset base, whether it's their house or their stocks in a retirement fund. And those fluctuate a lot less than someone who's in the most risk-on positions.

1:19:11We're Dogler, the first AI native dating and vibe coding platform for dogs. We've raised$150 million as part of our seed. as part of our team. Dogler is a good name. It's hilarious. There's some truth to this. To this day, America and Britain benefit greatly from rail networks whose construction turned out very badly for the original investors, but there's another way to look at bubbles. The participants in the AI race are all building products that are economic complements to one another. You need the turbines that power the grids, that power the chips, that run the models, that power the products, and you need firms to build their growth and hiring plans around the expectation that ever more of their work will be done by ai but that every company and every employee will be automating different sets of tasks if tsmc builds hugely expensive chip factories but the big ai labs all decide they've spent as much as they need to those factories are a stranded asset but when asset prices are loudly signaling that the technology is real and the economics will be compelling it encourages those complementary investments that actually make it happen.

1:20:16There are countless historical examples of this. The car industry's growth implicitly subsidized oil production and vice versa. Electrification followed a similar path. Appliance manufacturers had to operate on the assumption that utilities would wire up more households, and those utilities had to bet that once power was available, GE, RCA, and the like would give people something to plug in. During the heyday of Moore's law, chip companies raced to build ever more powerful chips and software companies rushed to ship products that would use them. It's hard for any of this to happen without entrepreneurs getting excited about a business based on its hypothetical future rather than its present profits.

1:20:54And it's impossible for this process to keep going unless investors too get excited. Naturally, one side or the other will overshoot. This hasn't been a technological revolution in history. There hasn't been a technological revolution in history that didn't at some point get overhyped. there's always there that's always obvious in retrospect but less so when we are in the cycle an investment researcher once circulated an essay called a home without equity is just a rental with debt warning that house price appreciation was driven by loosening underwriting standards and would inevitably lead to collapse but it was dated june 2001 wow that's crazy even at the post so early because it's true yeah it's seven years too early or six years too early even at the post-crisis low a decade later the case shiller index of american house prices was still 18 above its level when that piece was public wow wow i mean this is like the bitcoin bubble stuff yeah i was like yeah it's gonna crash and it's like yeah crash from 100 down to 90 or whatever yeah it's like similarly media coverage of dot com's described trading as nutty and quoted an investors saying, I don't really know anything about the company.

1:22:02But that article, the Wall Street Journal on the Netscape IPO was published in the summer of 1995. At its post.com low in 2002, the NASDAQ 100 was still 40 % higher than it had been then. Signs of a bubble aren't necessarily signs that it's time to sell because they precede the peak of the mania by an unpredictable amount. Anyone who read the quite cogent arguments against buying a house in 2001 under buying tech stocks in 1995 would have benefited financially from completely ignoring them. The famous dictum, uh, uh, pop, apocryphally attributed to John Keynes is that markets can remain irrational, uh, longer than you can remain solved.

1:22:45Didn't Keynes didn't say that. That's funny. I always thought that really. Yeah. I mean, that's, that's, that's like his, well, no, it's not. No, I know. But apocryphally attributed to him. We'll have to get to the bottom of that. but this presupposes that everyone has the same information and that irrational traders are simply ignoring it it's more in the spirit of canes to argue that the economic growth is partly a matter of believing that it will happen recessions and when people and companies start to spend as if they're over animal spirits and booms persist when some participants are building the infrastructure that others need to make that boom happen when open ai announces a splashy new scale up or meta declares that it has found yet another opportunity to raise its planned capital expenditures they're signaling to AI users, coders, lawyers, writers, whoever, that they'd better be prepared for smarter models.

1:23:30The more people and organizations gear their behavior towards a world in which AI is even more powerful and ubiquitous, the more they're locking in the demand that justifies all of those eye-popping expenditures. In the end, a bubble functions like an industry cluster that exists in time rather than space. If you want to be a movie star, you move to Los Angeles. If you you want to start a hedge fund, you move to New York. And if you want a part of being first to something in AI, first to build, first to use, first to profit from, asset prices are insisting that now is the time to act. I love it.

1:24:05Fantastic. Someone in the chat was saying earlier they were expecting NVIDIA to beat and then trade down 5 % to 10%, which I feel like is the consensus view now, which means that I think we might see something else. Something else happen. Who knows? It's all been very unpredictable. Well, I'm very excited for Byrne to join the show. I'm also excited to tell you about Julius.ai, the AI data analyst that works for you. Join millions who use Julius to connect their data, ask questions, and get insights in seconds. It really is like a UAV for your business. It is. Although that's night vision. That's not a UAV sound.

1:24:47Play the UAV online. That's the UAV for your business, baby. Crazy, crazy times in the telehealth world. While I was reading, Ben got me this. What do we got here, Ben? That's bub talk, baby. Wow, that's actually a lot of bubbles. I like that. Oh, all right. We will be ready to go when Bern joins the show. Hopefully those don't get on the camera. There is some pretty crazy news. The founder of an ADHD startup is found guilty of conspiracy in an Adderall case. What a crazy story. Ruthia He. Got to give credit to Will for predicting this years ago at this point. He was just saying all this stuff seems deeply wrong.

1:25:33So back in 2021, Will Manitis said on October 3rd, 2021, so four years ago, he said, telemedicine psychiatry startups have driven an unprecedented wave of amphetamine abuse. So he was worried. He was sounding the alarm bells four years ago about ADHD medications being overly prescribed, too easy to prescribe. He said, after tweeting this, an executive at helloahead.com DM'd me from an anonymous account, details of my care history with them, asking that I delete the tweet or caveat that they are not bad. This is an unimaginable violation of patient privacy and an odd threat. Just the worst person to do that.

1:26:19It's also insane because he didn't specify. He didn't call anyone in particular out, but then he got a threatening message from one person in particular. So that was very rough. Just say you're responsible. Yeah. And so Will has followed it up and said, Worth remembering that in 2021-2022, many major healthcare venture investors funded a cabal of internet pill mills that operated with mafia tactics to silence regulators and drive an unprecedented wave of amphetamine dependence in the United States. Well, today there has been some justice, Dunn, I suppose, for these ADHD startups. And so a jury found Ruthia He guilty of conspiring to distribute controlled substances after her startup, Dunn Global, became a ready source of Adderall prescriptions for more than 100 ,000 patients.

1:27:07The jury found he and Dunn's former top doctor, David Brody, guilty on two conspiracy counts and four counts of distributing controlled substances. The former CEO was found guilty of conspiring to obstruct justice. So the company was the subject of a series of articles in the Wall Street Journal from 2022 to 2024. Maybe they were reading Will Benatis tweets first. It's interesting that Tech and Venture basically decided doctors were a bug, not a feature. It's like, yeah, why waste time talking to a doctor just to get the medication that you want and that you know you need? It's like, oh, actually, like having somebody that is like, you know, even if it's slower, like having somebody that's there and actually understanding the patient and having like some personal connection with the patient feels very much more and more like a feature.

1:27:55And also having the economic incentive of the doctor being like they get paid a lot of money and live a great life just to give great advice and follow the Hippocratic Oath and be like a pinnacle. To give great care. member of their society, not to increase conversion rate. Exactly. As opposed to like piecemeal, how many scripts did you write? That's the pill mill model. And so defense lawyers argued that he, so during a seven week trial, prosecutors argued that he sought to enrich herself by making it easy to get Adderall and other stimulants. Well, the government classifies this as a controlled substance with high potential for abuse.

1:28:34The startup collected more than a hundred million in revenue. And the defense lawyers argued that they just wanted to make it easier to get the drugs when there was a shortage of providers. Quote, I think the goal we want to optimize is to help patients manage their ADHD in a convenient way. And there's some good reasons for that. Not everything. Sometimes you actually can't get to a doctor. There were good arguments on both sides. But in this case, it does seem like they pushed it way too far. There's some crazy, crazy quotes in here. Whoever is the first person to get arrested, I'll buy you a Tesla, Ruthie told concerned staffers, saying like, don't worry, you know, bend laws.

1:29:17Wait, wait. If you get arrested, I'll buy you a car. Testified that the CEO encouraged staff to quote unquote bend laws. Okay. I'm encouraging everyone here who works for TVPN, never bend the law at all. Operate within the law. Operate within the law. Tyler? 100%. Tyler. Looking at you. Tyler. Operate within the laws of physics. Yeah, don't bend the laws of physics. You're studying physics, make sure to operate within the laws of physics always. Yeah, whoever is the first person to get arrested, I'll buy you a Tesla. That's a crazy thing to say. Was that in writing or was that just like a quote from one of the employees?

1:29:53No, that was the former executive testified on the stand that this was said by the CEO, which is pretty crazy. Anyway, fortunately, the bubble in ADHD medication is winding down as the justice is being served. We have Berne Hobart in the Restream waiting room. Let's bring him in to talk about other bubbles, more positive bubbles, more beneficial bubbles. It is great to have you here. We brought the bubbles. Awesome. We brought bubbles. Great to be here. We brought bubbles. The bubble king. It really goes everywhere. For those who don't know you, please, can you kick us off with a little bit of an introduction on yourself?

1:30:34And thank you so much for taking the time to be here. Yeah, absolutely. So, hey, everyone. I'm Byrne. I am probably best known for writing the newsletter, The Diff, which you can check out at thediff.co, covering topics in tech, finance, everything adjacent to them, everything in between. um also a partner at anomaly an early stage frontier tech venture capital firm um also co-authored with uh anomaly partner co-authored the book boom bubbles in the end of stagnation published late last year by stripe press so uh yeah i'm the bubble boy the bubble boy on a roll how can we talk how should we set the table do you want to talk about uh just it feels like Like you've been sort of defined as like pro bubble.

1:31:18So I feel like asking you the question, are we in a bubble is a little bit irrelevant. But would you agree that we're in the bubble, in a bubble, maybe at the start of a bubble, maybe at the end of the bubble, but we are, it feels like we're in a bubble and it's safe to say it now. Yeah, totally. It's great. Yeah, that is the curse of co-authoring a book that is trying to rehabilitate the image of bubbles is that every time the NASDAQ hits a new high, people start calling you and asking you if that's good. And yeah, my obligation here and the model advanced in the book is to say that, yeah, it is pretty good.

1:31:51Like not to say that stocks will always go up forever, not to say that everybody's options or their weird quasi-equity participation units will all be valued at their present prices. But yeah, so the general argument we advance in the book, I guess you can rewind a little bit and say you can go through these different ways of talking about bubbles. One is to just say they're stupid. It's when people just get overexcited about some new technology or in the case of housing, they get excited about some very old technology that is newly easy to finance. And they just lose their heads. And by the end, everybody knows they're overpaying.

1:32:28Everybody assumes someone else will overpay more in the future. And just when you run out of stupid people, prices collapse. So that's like the bubbles are really stupid vein of thought. And then there's one which is a little bit more nuanced, which is, hey, yeah, they're stupid, but they're actually a wealth transfer from hedge fund people, venture capitalists, et cetera, to everyday consumers. So I lived in San Francisco in 2015. I remember I long for the incredibly cheap universal basic Uber where you could get anywhere for like$8. It was amazing. And that was – yeah, it was great. It was like wonderful wealth transfer from the Saudi Arabian Sovereign Wealth Fund to me.

1:33:04And I really appreciate it. Thanks, guys. um but but that well it's also notable that they they they've you know done fairly well even though there was like it was it was a it was a bubble it wasn't necessarily sustainable but it created a enduring business or at least one out of the out of the out of the two yeah and that's that's often what we get um now uber is a little bit of an abstract case what we often get from bubbles is we build too much infrastructure but that means we have the infrastructure and we have enough infrastructure to build the next thing. And that was the case in the 19th century with railroads.

1:33:37That was the case in the late 90s with telco infrastructure. And, you know, that could end being the case today with GPUs. But there is the pro-bubble argument, which is that what bubbles really do is they coordinate different market participants, both founders, employees, investors, regulators, customers, suppliers. They convince everyone that this is happening, it's happening right now, and that if you build something, if you overbuild for today's demand, you will still have underbuilt for future demand. And if everybody's doing that at every layer in the supply chain, then you actually do build enough to satisfy future demand.

1:34:12And so making it more concrete, if TSMC does not buy into the idea that AI is a really big deal, they're not going to build enough fabs, NVIDIA will not be able to ship enough chips, the next model will not be quite as good, or we'll have to do more of a trade-off between training and inference, and the whole thing slows down. But if everyone is wildly optimistic, then they do build all of that infrastructure, all the way from the power generation to the end use cases. They're building all of that, and it's kind of like just-in-time manufacturing of the future. And the prices, like the crazy prices, they are the signal that this is the time.

1:34:45It's happening now. If you build something on the assumption that OpenAI is going to keep shipping better models and that they will need a lot more compute and that we'll need a lot more power to make those models work, if you operate on that assumption, you're making the right call. How have you been processing some of Ben Thompson's maybe jitters around the idea that the infrastructure that gets left behind in this particular bubble might not be something that's with us for 100 years? he's been advocating for, hey, let's do energy. Let's do nuclear, solar. Let's build out a lot of energy. But if we're just like, yes, we way overbuilt like a bunch of H100s.

1:35:23And then, you know, years later, we're like, those actually aren't that valuable. They don't, they may be depreciated over a few years. That's sort of how he's articulated some of the fear of the overbuild not being as durable. Does that resonate with you? Or how have you been processing that? Yeah, I think you can look at these different lags, and you also look at how generalizable the use cases are for these products. And so it is true that GPUs depreciate. But depreciation, it is this economic concept that's tied or it's an accounting concept that's tied to an economic concept. And it actually ties in a couple different things, one of which is just if you use a machine, there is friction, it can break, it can overheat, whatever, and so eventually it's trash.

1:36:02And then the other piece, more on the economic side and much more relevant to GPUs is if the GPU is producing fewer tokens per watt and that just relative to newer ones, it can be economically worthless, even though it can still actually do something useful. And so if the GPU buildout slows down, that actually decelerates the depreciation for all of the world's existing GPU fleet. And power is harder to slow down. Just the lags are a lot longer. It takes a long, long time to build a new power plant and to build all the equipment that goes into it. So you could have this case where bubble pops, open AI has to do some weird recap at a much lower valuation, NASDAQ's down by half, or probably not down by half, but down by a lot.

1:36:44And, you know, a lot of people who felt very smart as of like a month ago look pretty stupid, myself included. And, you know, we could have that, but there will still be this increase in power generation capacity because that stuff is locked in. And the gas turbine companies, they can really lock their customers in because there are just not that many places you can go to buy one. And so if you're going to buy one and they say, OK, you have to actually guarantee that you'll pay for it, even if you really regret this, that's pretty much what you'll have to do. So you could have this case where what actually happens in the aftermath is power costs decline.

1:37:17And so these GPUs actually become higher margin when they're doing inference. And so you get really, really cheap, abundant intelligence at today's model capabilities. And that is still... Yeah, the GPU is fully depreciated and power costs have come down, which would make them... The concern around depreciation is you just get a chip that is so much better that is just non-economical to run one of these old GPUs. But the scenario that you're pointing out, they could potentially be valuable for much, much longer. Yeah, so if you look at a company like CoreWeave, where their business model is, we stack a bunch of GPUs in a data center, we lease them out to various people in varying terms.

1:38:01That is actually kind of a bet on this narrow slice where AI is not a complete flop. We don't find out that it was actually just Sam Altman typing those answers really fast all along. But it also doesn't completely revolutionize things because if there's another generation or two of GPUs or if TPUs take more share of inference, then maybe those GPUs end up being economically stranded. But if there's a world where we're not building many more GPUs, but we do find all the use cases for the ones we have, that might be a world where actually CoreWeave is reporting pretty nice gap profits and their investors are happy.

1:38:35And when you look at CoreWeave, one of the interesting things about them is on their cap table. So one of their big backers is this hedge fund, Magnetar, which has done incredible things with structuring various bets. If you control their prospectus, Magnetar is actually mentioned more often than NVIDIA. And Magnetar likes to make interesting bets on the relative volatility of different things or the relative timing of things. And so you could see this as them making this kind of esoteric bet that AI is actually both a really big deal and somewhat overhyped. Now, it's always hard to read into.

1:39:09Like what you're reading into is Magantar is involved in this. They have done a bunch of really interesting deals throughout the core reef cap structure. But it is still striking that they are very sophisticated about this exact kind of trade. That's interesting. What is the right way to view a bubble? Is it this monolithic structure in which they're – or are you viewing it as like – because in my view, it's like we just read your article or essay on The Economist. right before you. Congratulations, by the way. It's great. Thank you. Great kind of summary of everything. But high honor to be in.

1:39:42But you're saying like there's pieces of a bubble that are feeding into each other and making the possibility for durable value creation to be higher and higher because you have all these parts combining. I feel like another view maybe is similar, but slightly different is like you have these rolling bubbles that are all kind of like building up. And right now there's like you have a private credit bubble. Maybe there's a NeoCloud bubble? Maybe there's an LLM bubble, right? It's unclear if we need the 50th closed source LLM, right? I don't know. Maybe we do, right? It's hard to predict. But what is the right kind of way to even just visualize the bubble, the AI bubble broadly?

1:40:26So like a lot of other bubbles, it starts out as this really differentiated, unique thing, where most people do not know, you know, like five years ago, most people did not know or care that much about AI. It was kind of this thing where you would listen to the quarterly call from Google or from the company then known as Facebook. And they would talk about how they're an AI company. And you'd think, okay, like, I'm glad you have your science project nerds, but I really care about more ad clicks and more dollars per ad click. So good luck with whatever, whatever robot experiments you're doing. And then when it starts growing, what it starts doing is actually connecting with the rest of the economy.

1:41:01So now, like the marginal dollar of AI CapEx is increasingly going into general purpose power generation infrastructure. So and meanwhile, AI is getting much more broadly distributed, like initial initial use cases were one, it was a really good autocomplete for coding. And two, if you needed to create original content in order to spam people, or if you were replacing like the lowest value bloggers, you could do it, and it was cheaper. But then it became this thing where it's like a lot of, there are just a lot of things where you wish you could apply a little intelligence to it. It's really not worth your time, but if you can get the right answer easily, then you should do it.

1:41:38And just like a lot of, a lot of cases where you'd want it. Like I use it a lot when I'm writing as a research tool where it's like, I want examples of this phenomenon or it's a research tool, not a writing tool. Yeah. Right. Are you even using it as a first draft or is it more like you have a bunch of facts here and then you are actually typing out the sentences that you were like bloodhounds for ai content and we did not and no no alarm bells went off when we were reading oh yeah the economist article was like i've just been i've been surprised the most clearly human written it's so it's it's extremely notable that like using ai for writing has become the most low status thing that you can do on the internet it's like it just feels like disrespectful like it is lower status than making just like sloppy memes.

1:42:24Like there are lower status things you could do. Yeah. Okay. Adult content. Or use my coupon code to sign up for a prize picks. Here's my parlay. Who's right. But still, it just communicates it. You know, people feel disrespected by it because it's like, hey, you put this out. You wanted me to read this. And if it's completely obvious that a computer generated it. It's like, well, was this even worth my time? You couldn't have said it in your own words. So there is this dynamic where sometimes when there's increasing efficiency with something, we find out that some of the effort was load-bearing.

1:43:04And that doesn't mean the technology is bad. It means we do have to adapt. And so in the case of writing, one of the things that used to be the social norm was if you can produce a grammatically correct, lengthy document about some topic, that is an indication that you probably know what you're talking about. And to get into a position where you can do that, you have to read a lot. So you acquire knowledge. And if you want to write something persuasive, you probably have to talk to a lot of people and find out what's persuasive to them, what's persuasive to you, et cetera. And if you can just ask a model to admit that, then you can basically write at a level that is much higher quality than your ability to think.

1:43:37You can write well beyond your wisdom. It's kind of like when people use some peptides and steroids, they end up getting weird injuries because they're just like mechanically their body is not actually suited to lift the weights. that their muscles can move. So they do get serious injuries unless they train pretty rigorously. So I have a nine-year-old who has in the past used ChatDBT to write emails to me explaining her side of a fight that she had with one of her siblings. And the email is very clear, very articulate, lots of M dashes, lots of it's not X, it's Y. And it's, you know, that I think if someone that age sat down and write this coherent letter explaining their side of an argument, that would actually be impressive.

1:44:17You'd say, okay, this person's actually thinking seriously about what happened. But in this case, it's like she can write two sentences in chat GPT and answer some follow-up questions from it and then produce this nice coherent-looking document. How much do you worry about a new... We have kids younger than that, but how much do you worry about potentially a generation of young people never... Maybe in a classroom setting, teachers can be like, put your phones in this box and you guys are all going to write a paper on this. And it's possible that writing will become like highly supervised because the only way to prevent somebody from just generating the written word.

1:44:55It literally already is at many schools, but yeah, yeah, yeah. But, but, but even, even then it's like, when I think about, uh, growing up and being forced to think deeply about topics, oftentimes it was because I was assigned to write an essay on something and I didn't have the world's best autocomplete tool. And I just had to sit there and kind of wrestle with an idea and actually learn about it. And I had to read a book or read a bunch of essays and really put it together. And I think it's possible that just a lot of time spent like deeply thinking is just fully lost forever. Yeah, I think it comes back to that load bearing effort question.

1:45:32So I do tell my kids that there is just a qualitative difference. And also that when they get an assignment at school, it's not because the teacher has this burning desire to read an essay about, you know, whatever, about Charlotte's Web or something. Like, it's not like the teacher is absolutely, you know, they have been pining for this. It's like, the point is the effort. And the point is the way that you think about things. And that writing is actually just a very useful way to think something through. I don't really understand why that is. Like, I don't know why it is that if you just try to talk to yourself for 20 minutes straight about a topic, you won't get to the same level of clarity that you do if you type it out, even though the typing it out process is just really similar.

1:46:13It is one word after another, and then a little bit of editing sometimes. So I think some of what the education system has to do, which different schools do to different degrees, is actually explain to kids what the purpose of what they're doing is, so they understand what that purpose is. And then we also do have to make this adjustment of sometimes there are things that it used to be necessary for basically every adult to be able to do, no longer as necessary and fewer people will be able to do it. And maybe the ones who do it will still take a lot of pride in their craft, but they won't strictly have to.

1:46:48So think of it as like, I don't know, things like manual labor and I don't know, wilderness survival skills, things like that. there was a time when being physically strong and knowing how to, like being able to navigate in space and figure out which way is north if you're lost was actually a pretty important skill that a lot of people had to have. And there's actually - You'd probably be mocked. You'd be mocked if you could. Right, right. And so then you go through this generation where there is a lot of mocking, there is a lot of bullying, but the nerds are actually probably right that this thing is not so important.

1:47:17And then the next generation is only the hobbyists who do this. Thomas Sowell had this argument about, I think it's in his book on knowledge and decisions, where he's talking about how if you live in a really, if you live in a subsistence level tribe somewhere, you actually have to have this incredible breadth of knowledge. Like you've got to know all the landmarks, how to get from one place to another, all the signs of danger, everything you can eat, everything you shouldn't eat, and you know, which local tribes are friendly, which ones aren't. And you just don't need nearly that level of knowledge to survive in a modern city today.

1:47:50There are all kinds of things about where your food comes from and what is safe to do and not to do that you simply don't have to know because you're not exposed to any of the risk. And so we actually have just a much lower knowledge requirement in more advanced societies. On the other hand, we have much higher returns from having unique kinds of knowledge because now that whatever value you can create can be amortized over a much larger number of people and there's just more stuff to go around. So So the rewards from being really, really smart are a lot higher. And I hope that when I talk to my kids about this stuff and I basically say like there's going to be a cognitive overclass and a cognitive underclass, you can opt into one of them and it's super easy.

1:48:30You tell your kids that? That's amazing. You must escape the cognitive underclass. I don't agree with it quite that way. It is true. It is so easy to go through life without thinking and it will only get easier. And so you have to decide, knowing that the thinking part is increasingly optional in a larger and larger number of domains, do you want to be the kind of person who thinks because you like thinking and you like creating and discovering new things? Or do you want to be the kind of person who has just a much easier, more relaxing time because they don't? uh very there's that we could continue uh on this conversation for a long time but i wanted to ask you about what scares you about this current bubble like things that are not necessarily like uh bad today but could get bad to me like tech you know indulging in in uh in leverage for the first time, maybe as an industry or as like a lot of the leadership has not, they weren't participating in the telecom bubble, they didn't get blown up, maybe they've never gotten blown up by leverage, and maybe that's a concern, but I'm curious how you think about it.

1:49:39Yeah, I mean, I'm less concerned about that. I think the current generation of tech leaders, there's a lot more tech history that they can know about, and they just seem more interested in tech history. You can actually go back and see that the people who were more obsessed with tech history tended to do better. Like Steve Jobs was obsessed with the story of Polaroid. It's this beautiful consumer device, changes everybody's behavior, really simple tool. You look at it, you know exactly how to use it, you know what it does, and it does what it looks like it's supposed to do. Jeff Bezos gave a TED talk when that was a much cooler thing to do, I think, right after the dot-com bubble had rolled over, where he's talking about the early days of electrification and how the internet is like that, partly in the sense that we did not know how to use it.

1:50:22We didn't know all the applications. And he, I think he, he said, I think that's where I heard that the original appliances, like if you bought an iron, originally it would actually plug into a light socket. Like you'd unscrew a light bulb, screw in the iron and then iron your clothes in the dark and then screw in the light bulb again. Or I guess you'd iron your clothes during the day. But anyway, like we, it was very janky. And so you could have looked at it at that time and said like, this is just a clown show. Like, okay, sure. Electric lighting. I get it. But what are you doing with all these other weird gadgets and who needs that?

1:50:54Like we already had irons. They were fine. So I think that a lot of tech people are actually pretty keenly aware of history. And a lot of them are just, they're way more obsessed than you would think with the prospect of their company becoming irrelevant in six months and a total failure in two years. So I think we're, you know, it is riskier to borrow than not to borrow, but we're probably safe on that front. I think one thing that could go wrong is some combination of corporate behavioral norms and regulatory norms and investor assumptions where we decide that this stuff is really dangerous.

1:51:25We should not touch it. It will blow a giant hole in somebody's balance sheet because we know it happened and it'll happen again. And it just becomes untouchable for a while, which did kind of happen in the dot-com space. And I think people underestimate that when they look at things like Mark Zuckerberg starting a social network in 2004, is that that was, you could have looked at that as really like, now it looks really forward thinking. at the time it kind of looked dated it kind of like the example is like if you if in 1999 you moved to seattle to start a grunge band like you missed it you were you were way out of date and that's what it looks like so it was still a kind of contrarian thing to do and it was still a company that was started in the aftermath of this dot-com bus when people were cautious so um but with ai the capital requirements are so high that it is actually a really big deal if investors decide that the space is uninvestable, progress actually stops.

1:52:20Whereas you just don't need a lot of capital if you're in your dorm room on your laptop, just slinging PHP. Yeah. Or you can at least monetize much, much earlier. And you see that with like the Google earnings, like pre-IPO is like a massively profitable business, undeniable, didn't need any permission. What do you think about sovereign AI international, how bubbles spread internationally? I was listening to Tyler Cowen talk about one of the weird side effects of tariffs is that other countries might copy America's tariffs just for sort of mimetic reasons. And America might be in such a powerful position that tariffs might not actually wind up hurting America because of its position in the global economy.

1:53:01But if another country says, oh, let's copy that, they might be hurt more. I'm wondering about how bubbles propagate. At the same time, a lot of the telecom magnates in foreign countries that just kind of copied our telecom build out. Well, they're the richest people in those countries now. So how are you thinking about the bubble spreading internationally? I think it is a really cool toy for petro states. I've actually done some really impressive work. So I don't really begrudge that. I'm not sure how many general purpose models the world needs. I suspect what the world needs is lots and lots of special purpose models.

1:53:39And that could be the level of, okay, this model just knows rust, but it is insanely good at rust. And it has not polluted its mind with any bad habits from C or C++ or anything else. It's just pure rust. And then you could also have even more narrowly scoped models where it's like this model is this one person. And it will give you the best approximation it can of what this one person does. And if you have a lot of different models and people who interact with models interact through a router where the first thing the router does is figure out which submodel to send things to, and it can do many iterations of that.

1:54:11And eventually might be sending some things to – maybe delegating some things to an agent that ends up talking to an agent at some third-party service. So I'm thinking of things like if you are planning – I mean everyone says if you're planning a trip. Let's say you're planning a really complicated, tax-sensitive, global M &A transaction. So maybe you need the French tax law bot to interact with the US tax law bot, and they both need to make sure that the economics of your weird tax thing also makes sense. In that world, you could actually have this great diversity of models with a great diversity of model use cases.

1:54:44But for the general purpose stuff, I think that there is enough room for customization at the user level that we probably don't need 50 different models that are close to the frontier. What are your labor displacement timelines? Because every CEO over the last year has used AI as the reason behind layoffs. And I think everyone has been calling BS on a lot of that. It's just like they need a good reason to do a round of layoffs for other more real reasons. And everyone, I think, has seen the chart by now of job openings versus when ChatGPT was released. And at the same time, if you've used these tools, you're not a lot of people.

1:55:35It doesn't feel like a drop-in replacement. Yeah. Meanwhile, you have engineers. There's like, you know, LMs are incredible at coding and you have engineer, if you're a talented engineer or even a high agency engineer, you probably have more opportunity than ever. And but I'm so I'm curious about how you're thinking about timelines. Yeah, like this stuff takes a surprisingly long time to deploy because one of the load bearing inefficiencies is that if something required intelligence, there's a single there's at least one human being whose judgment is implicitly tied to the output of that product.

1:56:06and it's really hard to go from there is some specific person to blame like if a mistake was made some someone made it to if you scale up your work by you know 100x and now 95 % of the time you do just fine and 5 % of the time you mess up is that your fault is that Claude's fault we don't want to blame Claude Claude's so nice to us we don't know so like we actually have to rethink how people get judged there's this sense in which everyone becomes a kind of engineering manager who, like everyone in software, becomes this engineering manager who is describing what needs to get done and vetting what has been done, but is writing less code themselves.

1:56:41On the other hand, LLMs are actually pretty good at doing the opposite, where you are the junior coder, you are doing the grunt work, and what it's doing is looking at your overall architecture and telling you what things you missed and what design mistakes you have made that are just a lot easier to fix up front. But a lot of organizations, they don't want the risk of their workers are massively more productive, but they're also producing some mistaken things. And that's actually going to be a big hit to the company's reputation. So you'll probably see, what I think you'll see is that a lot of AI deployment is that there will be a legacy version of something.

1:57:19There'll be an AI native version of that thing. The AI native version will sell to smaller customers. Those customers will grow faster than legacy companies. And then the AI native product gets sold to all the legacy companies. So this is kind of the Stripe model where they started out doing payments for early stage companies that had pretty simple requirements and had some tolerance for error. And then as long as they stay good enough to maintain whatever their biggest customer is, they are necessarily building out the feature set for other companies the size of that biggest customer. So you get some deployment that way, but it actually takes a while because the big companies, they want to be somewhat cautious on this.

1:57:56And you sometimes have this case where there's a top-down mandate at a big company saying everybody's got to use AI. And there's also this bottom-up insurgency of I can use AI and it makes my job more effective. Well, also there's going to be a dynamic. There's a dynamic, too, where we will see scenarios where employees say, well, I don't want to adopt this AI. This one's a little too good. I'd be worried about losing my job, right? And so I think we're going to see more friction between even with tools that actually can replace labor, like truly not just being like a co-pilot, and the friction to adoption because the people that would be adopting them.

1:58:31And that's probably, you know, years out. Certain investors have been underwriting early stage private market bets to they're saying like labor is the TAM. Like, how do you view that framework? Is that like it feels overly simplistic to just say like any dollar that is spent, you know, that goes out through any type of payroll system today is up for grabs. But there seems to be some some element of truth to it. Yeah, there's a little truth to that, but I think it's in the same way that Netflix says that time is the TAM and their biggest competitor is sleep. It is broadly true. It's marketing. Yeah, it is marketing, but it's also a way to frame the scope of the opportunity.

1:59:13So what I would say is that when the labor in question is mostly delivering value by producing a sequence of tokens, whether that is writing a document or building an Excel model or writing some code, that that is the addressable market for an AI tool. but the real world just has enough complexity that models have to develop a really good world model and what we can think of it is in software they have a really good world model because that is their world like their world is this abstract world that is defined by whoever wrote the compiler and to a lesser extent that world has some complexities if you're actually working with real world physical systems where someone can trip over a cord and unplug one of the servers in your distributed system.

1:59:53And that is just not contemplated in the purely software world model. But as soon as you move out of pure software that is running on one machine for one user, you start to get some real-world complexity. And then when you're trying to automate something like building a financial model, you need pretty tight feedback between what assumption works in the real world, what actually maps economic realities, and then what assumption is the the most probable token in this cell that needs a token. And I think that as AI gets deployed in messier parts of the world, what you'll actually see is that more of the world will get structured in an AI-friendly way and that more of GDP will be in that world that is already pre-structured for AI.

2:00:36But then you still have the rest of the real world where it's just really hard to get Eagle onboarded. And you can actually see that with things like when the company then noticed Facebook was growing internationally, one of the obstacles they ran into was in many places almost nobody has a computer so that's one of the reasons that they went into mobile early but they also realized they could market themselves through internet cafes and that apparently for a while in the developing world if you went to any internet cafe half of the unused computers would have the facebook logout screen and that was actually a huge source of user acquisition for them in develop mark in developing markets and then once smartphones came out those people migrated onto smartphones and then meta was able to keep them and continue to sell them.

2:01:18So somebody would be on Facebook, they would use a computer in an internet cafe, they would get up and leave and then somebody would sit down and they'd be like, what is, what is Facebook? And then they would just create exactly. Yeah. Yes. There's, there's a great story in chaos monkeys about this and about how they wanted to have an ad on the logout page. Cause they're like, this is otherwise just wasted real estate. And it turned out the logout page is this mission critical thing in all the, in many of the non U S markets. So there was a big internal fight on that. And they did end up doing ads on the logout page, only in developed markets where growth had slowed down enough and they were already a dominant market share.

2:01:50But they needed the outside infrastructure to catch up with the product. And once it did, the product was already there waiting for that infrastructure and saturated it really quickly. But this is another thing that happens with bubbles in general, technology bubbles in general. It's like you don't consider the podcast an electricity company. You don't think of yourselves as that business. But the business doesn't really function if you can't plug something into an outlet or use a battery and actually get power from it. Nothing can stop us from podcasting, let's be clear. You can yell. We'll do it without microphones, without cameras.

2:02:21We'll just find a crowd of people and scream at them. Megaphone on the rooftops. In one sense, the 1920s bulls who were like, I'm all in on electricity, this is the future, they were absolutely right. But if you transport a trader, a stock trader, from 1925 to 2025 and you're like, okay, go buy all the electricity stocks, it's like, well, that's everything. Like every company uses this. So there is no real way to make a direct bet on it. And to the extent that there is, the direct bet is now a totally different bet. Now, actually, that particular time traveler, if he arrives in 2023 instead of 2025, actually his 1925 thesis of just buy levered power generating companies that put all your money to that, it's actually brilliant.

2:03:02So these things, you know, the cycle does repeat itself a little bit. But as it disperses, you've got a little bit of AI and everything. And, you know, Internet is the same way. Like, you don't consider Target an Internet retailer. They do a lot of e-com. Basically, all the physical retailers do a lot of online sales. The fast food restaurants do a lot of their sales through apps and through kiosks. So there is just this convergence where by the time the bet is such a big, scary bet that you're like, the whole economy is dependent on this. you're also like, well, it's just mixed in with the whole economy.

2:03:33You can't actually take the AI part out of the US economy and the US growth story without completely breaking things. And at that point, it kind of converges. It settles. Yeah, makes a lot of sense. I have one more question that is probably worthy of a 10-minute answer. We only have a few minutes. Is it the CEO's job to disconnect the stock price from reality? Thank you. Well, it's partly the market's job to tell employees where their equity, where they should go if they want to max out the value of their equity comp. And this is something that I used to not really believe. And what happened with Meta in 2022 kind of converted me to this view where Mark Zuckerberg did not actually have to care that his stock was under$100 a share.

2:04:21It's not like the board is going to vote him out. Even if he didn't have voting control, they're just not going to kick him out. But it did mean that it was harder to recruit people. And so if your dream is we're all going to live in the metaverse, we're going to have this legless utopia, you can only hire the people who make that possible if they think your stock is going to go up. Otherwise, you have to pay them entirely in cash. And then your stock goes down even more. And suddenly you're in this position of making really hard decisions that you don't want to make. So sometimes you take a foot off the gas pedal in terms of massive capex for something investors are skeptical of.

2:04:53And as long as you're still in the lead. And this is what investors would send hedge fund people. There was a great hedge fund letter that was completely plaintiff. It was like, Mark, even if you cut your metaverse spending in half, you'd still be spending the majority of the world's metaverse money. Like, you're still a winner. You still get the trophy, but please just give us some free cash flow. Buy back some stock. It's cheap. Yeah, it feels like disconnecting your stock price from reality, at least to the positive, can be a massive advantage. And you can see different like Palantir is a good example of this, or Tesla is a good example of this.

2:05:31And if you can keep it going, it's tremendously effective because investors want to be in companies where the stock price is not necessarily always going to be tied to fundamentals and even employees can benefit. And maybe like the opposite side of that is like Dylan Field with Figma. Like I feel like he just wants to be valued like fairly and like accurately and just wants to make the business better and better and better every day. But of course, it's a double-edged sword and it's great when it's disconnected to the higher end. But anyways, this was super fun. Thank you. Thank you so much for joining.

2:06:04I would love to have you back on again soon. Let's do this again soon. This is fun. This is a great time. Have a great rest of your day. We'll talk to you soon. Will do. You too. Before we hop on with our next guest, let me tell you about Privy. Privy makes it easy to build on crypto rails, securely spin up white label wallets, sign transactions, and integrate on training infrastructure all through one simple API. Our next guest is Glenn Hutchins. He is the co-founder of Silverlight Partners. A legend. And the chairman of North Island, North Island Ventures. I believe he's in the restream waiting room.

2:06:32We will bring him in with TDPN Ultra Dome. We were keeping him waiting just a few minutes. We'll keep the bub talk going. How are we doing? If he is on the line. Glenn, good to see you. Sorry for keeping you waiting. Welcome to the show. How are you doing? We don't have audio. Can we check on the mute button? Check on that and see if we are getting audio through the call. I will give some more context. Next, he is the chairman of North Island, North Island Ventures, the co-founder of Silver Lake, the vice chairman, lead independent director of Santander. There we go. He's also the lead independent director of Corweave, and he's here on the show.

2:07:15Welcome to the show. Thank you so much for taking the time. I just want to say I'm a big fan of your show. That's amazing. So it's so much fun to be here. It's really a real pleasure to meet you guys almost in person. Yeah. Well, next time you're in Los Angeles, please feel free to stop by the TVP and Ultradome here in Los Angeles. We are so excited to have you on. So much to talk about. Yeah. Why don't we start with just a little bit of your career arc? I know we're going to want to talk about the dot-com bubble, the dot-com boom, your experience there. But walk me through your career up to co-founding Silver Lake in, I believe it was 1999, right?

2:07:53That's right. Just really briefly. Please. Basically, when I got by, Silver Lake was my third, and now I'm on my fourth, essentially startup in and around investing, largely called Private Equity. The first one, I was a junior partner to a guy by the name of Tom Lee, founding what people look back on now and say it's one of the first Private Equity firms. Then I took some time off, worked in the White House for Bill Clinton, and then was recruited to come to a young little firm called Blackstone. There you go. That was getting into the private equity business and wanted to build a private equity platform.

2:08:30about five years later the Blackstone guys helped me start Silverlake which was the they invested in it which was the first large-scale organization to combine private equity type of investing with technology and now I'm on my fourth which is my platform called North Island which has one very difficult limited partner, which is me. He's the best guy. And I'm doing, so it's my fourth startup in investing. And, you know, maybe we can get into this a little bit later, but, you know, the origins of private equity might be something worth talking about at some point if you'd like. But we'll come back to that.

2:09:11What's your next question? No, let's start there. I love your view on it. And it really is quite funny to think that you couldn't have maybe picked better stepping stones across the whole journey. It must have had some good intuition. Yeah. You know, it's better to be lucky than smart. But so, you know, the one thing I would say is, can I get a little geeky with you guys for a moment? We can come back to the more personal dimension. But there are four or five real advances in largely quantitative approach to finance that enabled the creation of kind of what I've done over the years, especially in the early 80s when we started thinking about private equity.

2:09:56And the first was the capital asset pricing model, which allowed us to really do very good in-depth valuation of equities, which had not been done before. The second was the Black-Scholes option pricing model, which allowed us to value options and really understand how to value embedded options inside of equity securities. Oftentimes, when you bought a private equity company, you paid for the company, and then you identified something inside the company that had a real upside. And how to value that and how to pay for that was the question. Second, or maybe third, was understanding fixed income.

2:10:30A fellow named Marty Leibowitz came up with something called Inside the Yield Curve, which let us really value fixed income. And then Mike Milken really understood really good work on understanding the risk-reward associated with high-yield securities, which became a tool that we were able to use to build these companies. Michael Porter at Harvard Business School did a bunch of research using standard economic analysis about the five forces that you could use to extract value from companies, which wasn't being done in a very systematic way in those days. And then finally, modern portfolio theory with sharp ratios and efficient frontiers were adopted by places like Harvard and Yale.

2:11:10And a key part of that was having an allocation of private equity. And as that model was rolled out across first pension funds and then sovereign wealth funds, a huge amount of money flowed behind us. That makes a ton of sense. We figured out how to value companies. We figured out how to use debt. We figured out how to extract value from the companies. and then we had a big flow of money coming into Bacchus doing it. Fascinating. So that's kind of one way to think about what happened over the last 40 years. How quickly did those ideas and methods actually disperse? And tying that to the present, it feels like with AI labs today, there'll be some sort of innovation that gets discovered and then one of those people gets immediately poached to another lab and suddenly another lab is developing the same type of system or approach?

2:11:59That's a really good question. Now, someone, quote, you could look it up. Someone quoted, I read a quote recently, said the future is already here, it's just not evenly distributed. And so, you know, innovators try to, I've always tried to find the next way to be successful in investing and stay ahead of what people do who copy me. One of the things I say is that my best ideas are ones that people dislike. And my very best ideas are ones they hate intensely. Because I know if someone really hates something, I'm thinking about it. And I know it could be really good. And then by the time it turns out to be generally accepted, that's when I sell what I bought before to them.

2:12:43If you know what I mean. Yeah, so you're basically, like, if they think an idea is dumb or silly, that gives you a window of opportunity to— That's a signal. It could be good. Yeah, well, and it gives you a window to, like, you know, get as much value out of that idea before it becomes common knowledge or an accepted approach. Occupy that territory before they get there. When they come there, then you sell to them the beachfront property that you've already purchased. That's right. Right. And then, but to go back to it, the half-life of innovation on Wall Street, AI is a little bit different, but the half-life of innovation on Wall Street is a time it takes someone to read a prospectus and then copy what you did.

2:13:21And so, like, you know, someone does a SPAC and everybody does SPACs. Someone does a digital asset treasury thing and everybody wants to do a DAT. You know what I mean? Yep. It's like on Park Avenue, New York City, as soon as it starts raining, the guys with the umbrellas come out. It's almost like they knew it was raining and then blocks on either side of Park Avenue. Everybody's with umbrellas. You've got to figure out something else to sell because the umbrellas are already there. So when we first started doing – and private equity was a way of exploiting value that was latent inside companies because you didn't have the financing to be able to purchase these companies.

2:13:55And you didn't have the toolkit to extract value from them. Those are the issues that we resolved with what I talked about earlier. Especially when Mike Milken untapped this high-yield market that we could borrow from to finance these companies. Then people rushed in. And in part, the Blackstone idea you'd have to talk to Steve Schwarzman was to build a platform that you could take to scale where you could raise an amount of money that people who would come into the space couldn't match you. So you could mine a different vertical layer of companies that were immune yet to private equity disciplines by getting to scale in the enterprise.

2:14:37You see what I mean? Very comfortable in Silicon Valley to call that out nowadays. There's a big discussion over platform funds and funds that might be doing exactly that. Yeah. Okay. We'll come back to that. And then I decided that another path, that the technology industry had reached a point where there were scale companies where you could use debt and more private equity style skill sets to buy the companies. First big one we did was something called Seagate. Yes. Where we borrowed a bunch of money to buy a big tech company. Yes. But if you look at companies like, so when I was coming up, people looked at companies like Microsoft and they said, oh, these are very risky companies.

2:15:16Steve Ballmer and Bill Gates were college classmates of mine, by the way. You're a lucky guy. Class of 77 at Harvard. Steve and I graduated. Bill did not, but he did better. On the financial innovation, it feels like a lot of what you identified, Black-Scholes, modern portfolio theory, sharp ratios, all of that, that's all pre-1999. I'm interested in understanding what was the key unlock to bringing private equity to technology specifically? Were you thinking about Metcalfe's law, network effects, zero marginal costs? Were you looking at businesses that fundamentally differed from the traditional widgets business or industrials business and had different structures?

2:16:02Or what else was going on there? Really good question. So at that point, technology was in a point of transition. This is like the future is here. It's just not evenly distributed. Yeah. It was thought to be an area of two things. One, it was thought to be an area of expertise where you – and it was true. You really had to have specialized expertise to understand the companies to invest in them successfully. You couldn't just wander off of – out of Wall Street with your pinstripe suit and sort of think you could figure – go to a couple conferences and think you could figure out how to buy a technology company because the process of evolution was so rapid.

2:16:38And then secondly, to that point, people did not understand how technology companies had evolved. At that point, technology companies were big. They consumed huge amounts of cash in investing in R &D to build the products. And they had very volatile earnings streams as a consequence of being pioneers in a space that came and went very quickly. And so people looked at that from, it was a venture capital gig, but looked at it from a private equity perspective and say you can't do it. But at that point, Microsoft, for instance, that's what I was talking about, Microsoft got to a level of scale where it was one of the greatest economic enterprises in world history.

2:17:20Where you make this piece of software that comes out of someone's brain, has almost no capital expenditures associated with it, no kind of fixed cost, and sell it a billion times. right i mean that's it and it just this massive flywheel of cash comes into that company and we i you know when was that when was that like light bulb moment for you no but for you personally i i observed it in the 90s um i had the benefit then of living in boston and the venture capital business was pretty pretty um uh vibrant there then it moved later primarily to silicon valley but there was a big footprint in boston in those days uh because you remember data general and digital equipment.

2:18:03We're kind of there, the micro companies, some of the mini computer companies. And so you can watch it happen and you say, you know, that's a better way to make money than just trying to extract value from rationalizing legacy industrial companies that have been poorly managed. Yeah, widgets business. Right. And then the other thing is, remember, is that people will, in thinking about exiting businesses. The market will pay you more for companies that have good... This was an insight in those days. It's not now. By the way, in those days, to borrow money, you had to have assets to back it with.

2:18:37You know, like inventory, working capital, building, building... You couldn't use the company that... Cash flows. And then, yeah, you couldn't use the cash flows in a software business. They maybe had a lease for an office, but not a lot of servers. But so what we had to do was teach the markets to lend against cash flow. Actually lend against assets. So cash flow lending became this kind of new thing that we had to teach people how to do. And then once you got that, then you realize that if you had a rapidly growing company like a Microsoft that had an extraordinary cash flow engine, huge barriers to entry.

2:19:14At that point, when I came in the investment business, people said tobacco is the best business to invest in because – I'm serious – because it was very stable. It had stable cash flow, stable pricing, and it didn't vary with recessions. I said, let me get this straight. A business that addicts and sickens its customers is better than Microsoft? No. I'm sorry. I don't agree with that. Right? You've got to look at the modern world and understand that these cash flows are sustainable and these businesses are extraordinary because the product comes from someone's head. You don't have to build a factory to build the thing.

2:19:51Fascinating. And so we just built this business that got that set of insights. And as a consequence, we were able to build a – so the other idea there was to build a strategic competitive advantage, a commanding heights that you could occupy that made it very hard for anybody to compete with you. So help us bridge to some of the debt financing that's going on today. I think that there are a lot of folks in the tech community that are very used to a bunch of 20 % dilution equity rounds, maybe a growth equity round. And the idea of bringing on a partner like Blue Owl for some massive deal, it just doesn't map to the traditional tech startup path.

2:20:33and yet folks who are trying to understand where AI is going and where the big hyperscalers are working start have to grappling with debt and how debt is coming into this generation of this technology. And Sam Altman has said, like, we maybe need new... He said we need new ways to finance this. Like financial innovation. We need financial innovation, not just technological innovation. A lot of people have, you know, kind of shunned him for suggesting that. But I think based on what you've been describing of what enabled this wave of value creation and unlocking the value of these private companies and the value of their cash flows.

2:21:11It can be done responsibly. It can be done responsibly, yeah. Wow, that's a really, really good question. And maybe we'll have to do a second show just on that. Please. Because this is a complicated topic, right? But technology is very – I like technology. you know gotten into it full-time for now you know 25 years ago um i still feel like i'm new to like i'm still new to golf even though i've been playing it about the same period of time um the uh but one of the things great about is it's constantly changing and you have to constantly adapt your thinking and develop new modes of sort of how to of investing and so this ai thing is brings us back to the future, which is it's software-driven LLMs, technology enterprise that requires a scale of capital investment that we've never seen before.

2:22:09And that's a really unique kind of challenge. It's one of the things that's drawn me into the kind of investments that I've made there. It reminds me a bit, historically, it reminds me a bit of when the semiconductor companies went fabulous about 25 years ago. And the industry split into companies that designed semis and basically TSMC, right? And TSMC succeeded largely because the country of Taiwan was willing to, essentially, to lend them the credit rating. The scale of capital necessary to build a fab that could design these, that could manufacture these wafers with a nanometer scale that they had at prices that were cost competitive that could continue to drive adoption of technologies based upon semiconductors was only approachable by a national credit rating.

2:23:02TSMC had a backstop. Basically had the backing of the government of Taiwan to go get this done. There's a reason why it's in Taiwan. You couldn't do that in those days. The capital wasn't available to do something like that in those days at that scale for that kind of enterprise. It's very similar today, which is the scale of financing that's required to build all these fabs, not fabs, I'm sorry, factories, data centers. I call them factories because I think they're factories manufacturing data now. And what I say to my people, what I say to my friends is America is now the leader in the world in advanced manufacturing because we're building these data centers to manufacture data.

2:23:43Yep. Right. And that's kind of what it is. It's a massive factory manufacturing LLMs and applications for both trading and inference. Yeah. But that's kind of one. But the second point would be that people compare this to – so the question is, are we in a bubble? Sure. That's kind of underlying the thing you raised, right? What kind of bubble is it? And the question, you have to make a decision whether or not this is more like subprimes in 08 or more like the internet in 1999, 2000. You know, whether the subprime is just kind of something that's not real, it's going to collapse. And when you're left, you're just left with a bunch of debt and no value there because the home values all went down.

2:24:26I am more in the internet camp. Yeah. which means that, of course, there will be companies that will be formed that won't be successful. Of course, there will be investors who put capital in bad places and lose money. Of course, there will be some number of scoundrels and shysters who come in because money gets moved around and they get attracted to this, right? But there are one major, you mentioned Blue Owl, the one major difference today between the build-up. So what was happening simultaneous with the internet was being, when the dot-com companies were being built, let's say the LLM equivalent today, the fiber optic networks were getting constructed all around the country, the CELEX.

2:25:13And those all went to zero and people lost their money on it. The major difference between that, and people use that as analogy today, and maybe the railroads is another analogy, but the major difference between that and today is every one of these data centers, almost all of them, has a counterparty, a solvent counterparty that is contracted to take all the output. They're built to suit. Not if you build it, they will come. Yeah. Okay. Microsoft has, I think, the world's best credit rating. If you sign a deal with Microsoft to take the off-put for your data center… Satya is good for it. He's good for it.

2:25:50Yeah. And by the way, Microsoft's going to survive if that has a collapse at some point before it comes back again. That's a good point. It's a very different kind of financing structure. And the last point I would make, and just finish this in a little bit, is that each of these deals, so far as I understand it, is done in a way that essentially generates, in the four to five-year period of the deal, generates about a two times multiple of money on the cost of buying the GPUs and standing at the data centers. Oh, interesting. Right? So, the contract, and they're about four to five-year contracts.

2:26:22Yeah, yeah, yeah. And the output has a – and then talking about, okay, embedded options and how you value those, right? And then the owner of the GPUs in the data center has an embedded option on the value of the used GPUs, which will be worth something. I mean, your five-year-old iPhone is still worth something. Of course. Even though people are buying the new ones, right? Yep. And so each of the contracts and builds right now has a commercial proposition in it. and when done well these companies that are doing this like core weave are putting one of building a wall with one of those bricks on top of the other yeah do you see what i mean yeah so it's not it's not analogous at all to the sea likes where they put a bunch of money in the ground and then went to get the customers and the customer weren't there sure that's a very different thing that's a really good point i haven't considered that that makes a ton of sense that's great uh yeah i feel like a lot of people in tech are just struggling to, you know, there's been this narrative for a while that ChatGPT is the new Google.

2:27:26And then you look at how capital consumptive OpenAI will be before profit comes or cash flow comes versus what happened with Google, where they were throwing off millions of dollars in cash, like well before IPO. And the prospectus just looked so clean, this super high-margin business very fresh out of the gate. And it's just a very different world that we're in, where we're delivering something similar. It feels just like a website. Partly because OpenAI has to compete with Google. Maybe, but it's just a different... It's a capital consumption. So the model's changing a little bit. Each wave of technological innovation, companies are created that don't obsolete the company that went before them.

2:28:11They do something completely different. And they're sometimes very different. So you've got the Microsoft software that was the operating system and the applications was unlike anything we had before because we didn't have the PC. And then Amazon was not anywhere near like Microsoft. It was a whole different kind of innovation that was based upon the internet that was built. And then Google was something new and Facebook was something entirely new. So these aren't companies that say, I'm taking your thing away from you. Each one is a very different kind of unique unicorn type of business that occupies a niche itself and eventually obsoletes the other businesses because they stop growing.

2:28:59Like Facebook might stop growing if consumers go to OpenAI, but it's not because they're going to OpenAI because it's a new social network. Yeah. It's because as a different use case is valuable to them today. What's been the biggest learning surprise sort of update to your mental model from working with CoreWeave?

2:29:26That's a really good question. um the the the pace of change the scale that we talked about i mean the thing that just amazes me is the scale at which this thing is growing uh and the um uh this the rapidity uh that you have to have in order to act at to be successful at this kind of scale with this kind of growth. It's unlike anything I've seen before. You saw the adoption curves of, you've seen the adoption curves of OpenAI versus Google versus other things, right? And it's just like this asymptotic thing going to 700 million customers right overnight. All the infrastructure to support that is like unlike anything we've ever seen before.

2:30:17Yeah, it's still under-discussed how much bigger and faster the outcomes can be when you have the internet as a distribution engine. So like during when you founded Silver Lake in 1999, I'm sure you've looked at a bunch of companies that had a lot of potential, that if there was already billions of people using the internet, they would have done very well. And the challenge at that point is there maybe wasn't enough internet users to support even ideas that were maybe like structurally good ideas, just missing enough of a user base. How much time do you spend finding and meeting and backing new managers?

2:30:59I feel like every new technology cycle, the hottest hedge fund of the year is situational awareness or at least on X. and that feels like, I imagine there will be more of those. And so I'm curious how much new fund formation you're seeing and what you're most excited about on the GP side. Yeah, so I have investments. I don't do venture capital investing per se. So I've got investments in some of the major venture capital funds in my investment platform, and I know all the people and watch what they do. But my business model outside of that is to find a small number of companies where I can put a fair amount of capital and be engaged, helping to create the outcome.

2:31:49See, that's kind of where I spend my time. So I'm not doing the whole build the massive portfolio thing. I'm picking my spots. And you mentioned the European bank that I'm the lead independent director of. Yeah. You know, we've got that stock up 3.5x in the last three years since I invested. Hit the gong. We have a gong here. We'd love to hit. Right. So, you know, there you go. Oh, that's great. Thank you. Thank you. I got to tell you, I didn't get founder mode, guys. I don't know. I don't know what's going on here. Founder. Here we go. There you go. I didn't get founder mode. Come on. I've been waiting for that.

2:32:24You got to do founder mode for you. I love that. Boy, they love better than show. The goat is also very important. I got the goat for you. I love it. You know, I've got children about your guy's age. I just love your generation. I love hanging out with them. It's a lot of fun. So, by the way, you see this logo here on my shirt? Yes. What is that? That's binary code. See that? You know what that's binary code for? 1-0-0-0-1-1-0. What's that? 1-0-0-1-1-0. It's binary code for 70. 70? 70. It's my 70th birthday logo. Oh, very cool. There we go. Happy birthday. Thank you. So as I say, I've got kids your age, and I really love hanging out with your generation.

2:33:15It's been a great pleasure for me. Yeah. Thank you. So we love hanging out with you, too. You asked me another question that we got distracted from. So what I'm trying to do is find a small number of enterprises in which I can engage, get involved with them at a senior level. In both cases, Cor Weave and Santander, I'm lead independent director. It's another term for non-executive chairman. There's usually an executive chairman and I'm non-executive. And then really work with the enterprises to build value. That's kind of how I think about it. And then I let venture capitalists, who I invest with, and I still invest with Silver Lake, be on the rock face every day building these portfolios.

2:33:55The rock face? That's a funny analogy. I like that. Well, you're the mountain climber, right? Yeah. Yeah. Right. So you're the height of a basketball player. I think you probably had the wrong sport. I think you're referring to one of our early episodes where I was joking, remember, about you climbing. Oh, yeah, yeah, yeah. Yeah, that's what I heard. I heard that. Yeah, I thought that was – you were just kidding him, right? Yeah, we were. We were just messing around. Just because the idea of John, a 6 '8 guy, skating. Okay, yeah, I agree. Okay, rock climbing. You could do – I believe in you, but I think that would probably violate some key man insurance.

2:34:34Yeah, I know. I definitely want to be above him on the wall. I don't want to be above him. Anyway, so I'm trying to pick my spots and really add some value. Yeah. well thank you so much for coming on the show we have to have you back soon this is fantastic we could talk all day long yeah there's so many more questions I want to ask congratulations on the success of the show guys thank you so much you're welcome on any day you're on the east coast come see me fantastic yeah we will thank you so much great hanging Glenn thank you so much Glenn for taking the time we'll talk to you soon let me tell you about getbezel.com shop over 26 ,500 luxury watches, fully authenticated in-house by Bezel's team of experts.

2:35:16We're going to our lightning round. We got Yogi Goel from Maxima announcing a massive round. Let's bring him in to the TBP and Ultra Dump. Welcome to the show. What is your t-shirt? Introduce yourself. What do you do? Give us the news. What's the latest? Absolutely. So nice to meet you both, Jordi and John. Great to meet you. Yogi here from Maxima. We are an enterprise accounting platform focusing on waging the war on the month-end close process. Let's go. We are, in a short focus, our AI agents are co-writing the monthly financial package and preparing the data for the accounting team. We've been around for now five, six quarters and helping incredible companies like Scale AI, Rippling, Spot On, Press Juice.

2:36:06So a lot of companies in both tech and non-tech world to make accounting sexy again. Very, very on brand to count the time you've been in business by quarters. Exactly. And what's the news today? Break it down for us. Yeah. So we just raised$40 million in C plus Series A. All right. There we go. Congratulations. Very exciting. Love it. Explain to me how this plugs in. Obviously, there's a lot of folks that have an accounting layer of record, a single pane of glass, an ERP, an accounting suite. Do you want to just plug into that? Do you want to rip and replace that? There's so many different folks eating around the edges, creating different solutions.

2:36:53I don't think anyone knows exactly how the market will play out, but what have you built? Yep. So we've built a system of action and system of intelligence which works with any system of record. So when you go to an enterprise company, asking them to replace the ERP is like asking them to do a brain surgery. I would agree, and I would not agree to that. And we say that, hey, your system of record is where your data should eventually sit. We help with automating the human work of grabbing the data from upstream systems, doing the manual, doing our agents do the automated work, and then eventually finding anomalies and errors.

2:37:33I don't know if you're following, but last year was the maximum number of companies in the U.S. which had material misstatements and up to 40 % stock price drops. It was the most mistakes from accounting specifically last year. That's not good. Hopefully, we can fix that. I have one last question, and then we will let you go. I want to know, give me some examples of where the current crop of AI models really excels in finding these types of problems. And then where do you want to still leave the human in the loop? Where do you want the human? What's the really intractable problem that maybe we'll solve in a few years with AI?

2:38:11But for now, you'd leave it with the human. Yeah. You've got to have somebody to fire.

2:38:20Who's the last guy in the accounting office, I guess, is the question. But, you know, I'd love some examples of problems that really excel for AI and problems that are maybe more intractable. Yeah, look, I'll just add a thing. Our problem, we are not going after the human labor salary. We are going after errors, inefficiency, and pain that I personally face both as an auditor and as an accountant for 20 years. There are not enough accountants in the world that you can truly hire for the amount of work that's there. So in terms of where AIs are very good at today, they are very good at taking a defined set of instructions and following things over and over again for a variety of transactions, provided you give them deterministic operators, which we have built, that they will only use those tools and then come up with the right answer.

2:39:12So we are using this hybrid approach where agents follow Maxima tools to come up with the exact same answer. And so when Deloitte and EY comes knocking, looking at the work that Maxima produced, they will do two plus five and the answer will always be seven. It will not just be 15. So that's one thing we determined really well. second is it's uh really good at finding anomalous behaviors and errors uh that might happen because it is uh looking at millions of transactions over time within the company it can just see that hey this your legal bill used to be fifty thousand dollars suddenly it's five hundred thousand dollars turns out uh jim jim had a late night and he had one extra zero and that's why it went up yeah and i mean artificial intelligence has been used in like fraud detection for years and years and years.

2:39:58And so applying that sort of heuristic-based to stochastic-based, more less deterministic computing, more probabilistic computing makes a ton of sense there. I love the positioning around pain and errors. You've got to talk to the venture capitalists who are yelling loudly to anyone that will hear, we're going to replace all labor. Give me more money to replace labor. It's like, no, you can show the sort of optimistic, like positive. you know yeah well thank you so much for taking the time congratulations on the massive round we will talk great to meet you i'm sure you'll be back on soon and have a great rest of your day great shirt too let me tell you about eightsleep.com exceptional sleep without exception fall asleep faster sleep deeper wake up energized our next guest is sam jones from method we will bring him in from the restream waiting room into the tvpm ultra dome sam jones how are you doing Welcome.

2:40:53Good to meet you guys. Great to see you guys. That sound effect kind of just, I don't know, it doesn't have enough of a crescendo for me. We need to work on that one. Anyway, we're working on our drum roll. Thank you so much for taking the time to hop on the show. Please introduce yourself, introduce the company. Tell us what the news is today. All right. I'm Sam Jones, the CEO and co-founder of Method Security. Our mission is to deliver cyber resilience to the U.S. government and critical enterprises. Think of what we do as building the command and control layer for autonomous cyber operations across defense and offense.

2:41:22And the news today is that we are announcing our$26 million combined seed and Series A investment from Andreessen Horowitz and General Catalyst. Incredible. Very good. Obviously, I want to jump in. We did a gong preemptively last time. We did a preemptive gong. It happened. But we got you in the ultra-gong. We'll have to raise more money to pay you back for that gong. That's great. I'm sure you will. I would love for you to get me up to speed on how you're thinking about that story in the Wall Street Journal about Anthropic. I'm sure you know the one. Yeah, AI on AI violence. Exactly. Is this relevant to your business?

2:42:00Are you building a solution to that? Or do you even have a comment on it or anything? Can you just get me up to speed? Highly relevant. And that's kind of the moment that we've been building for for a couple of years now. We've known this is going to happen. And AI is effectively, you know, taking at the limit, taking cyber offense to infinity and taking the cost to zero. And this is bad news for good guys, bad news for the defenders as our adversaries are essentially eliminating their requirement or limitation on human headcount. So what we do is essentially allow organizations to safely become the threat to test their own defenses before some adversary does.

2:42:41and the best offense is the best defense has always been a notion in security but ai is really the unlock to do it at scale the hard part is you need to do so safely ethically legally and that is the infrastructure that is like needed to do and that's what we build specifically so like in that report it's almost like no news to anyone in the security trenches like obviously this has been happening obviously that wasn't the first yeah what are some other without without naming names or any details on the individual companies that were attacked? I'm assuming anytime I see a report like that, I'm like, okay, this must be happening a ton, and just a lot of it just never hits headlines.

2:43:24But what are some of the most common strategies that bad actors are using today in the context of AI to carry out whatever their goals are? If you think about pre-AI malware, it was already autonomous, but it was basically reliant on if-then decision-making. What AI basically allows it to do is a broader, non-deterministic path planning that allows it to harness a multitude of tools, thus do a lot more damage. That's what's different now. And I guarantee you the most sophisticated actors are not using vanilla clod code to run their operations. That's ludicrous. They have our adversaries have better models at home that they make themselves that they're using that we have no, you know, telemetry on.

2:44:11And so they're essentially using it to scale and speed up their operations, which for us and why we have like a national cyber resilience urgency moment on our hands is that all of these exposures that we've left out on the Internet and in our, you know, in our enterprises are now, you know, easy, easy takings for these types of attacks. And that's essentially why it's so urgent that we focus on resilience. Can you talk to us a little bit about traction? What unlocked this$26 million fundraise across these two rounds? Are you doing like, yeah, just walk me through how you actually show progress in, you know, you're building a product, but you're also trying to do deals with the government.

2:44:56That can be very difficult. What does progress look like? So we are deployed in production with a number of organizations to include the Department of War, U.S. federal government, and Fortune 500 organizations. That's probably the biggest hallmark of traction. And we're doing so across defensive and offensive use cases that get to the heart of resiliency. So that's, I think, the unlock that we were able to do that. And we've had this hypothesis and mission from the beginning that in order to secure what matters, you need to be dual use. And we set out to basically pick what is the most intense, hardest government customer we could go after from the beginning and what's the commercial equivalent.

2:45:36Those were our first two customers. And then basically just continuing to build on that. From the adversary's perspective, they do not discriminate between public and private, and neither do we. And that's why I think the ultimate game changer solutions will come from dual-use companies like ourselves. Now I'm thinking about the hardest to hack, Fortune 100 and government. It's not necessarily always the hardest to hack. A lot of times it's the hardest to sell to, hardest to deliver for. If you think about the government done accreditation, deployability, interoperability, huge technical challenges.

2:46:10That's why startups would never dare touch there. But when you think about what matters, they are what matters. And that's what we built this company to serve. What were you doing before this again? So I started my career actually seeing this problem firsthand at the U.S. Air Force. So I was a cyber operator. in many ways were building the tools that I wish I always had. I joined Palantir about 11 and a half years ago, pre-product and building up both their cyber, commercial, and DOD business. And then I was also at Shield AI pretty early. And so you can kind of think of this company as we were the users.

2:46:41My CTO and co-founder also started his career at NSA. His last name is Hacker, by the way, if you want to know. Oh, there we go. About destiny. And then also, I want an overnight success for being in this industry. 15 years. He had no choice other than work at NSA, but we met at Palantir and did great work together. But we're combining our knowledge of like, we were the users. We know how to build hardcore software and dual use businesses. And then we built AI before, you know, it's become a meme and certainly in no fail scenarios, which I would group security in for sure. Yeah. This is very cool.

2:47:18I'm very bullish. Yeah. Extremely bullish. Thank you so much for taking the time to come chat with us great to get the update my uh my background wasn't as good as glenn's mahogany i i showed the startup you brought you brought a wood which is which is good yeah thank you for bringing what what's the biggest fish you've ever caught yeah yeah probably a nice nice uh walleye i'd say okay there we go good answer good answer midwest shout out thank you so much i cannot wait for the bees congrats on all the progress yeah have a great day Cheers. Talk to you soon. See you. Bye. Let me tell you about Wander.com, Book of Wander with inspiring views, hotel-grade amenities, dreamy beds, top-tier cleaning, and 24-7 concierge service.

2:47:56Our next guest is already in the restroom waiting room. We have Ali Madani. Welcome to the show. How are you doing? Awesome. Thank you so much for taking the time to come chat with us. Please introduce yourself. Introduce the company. Tell us what the news is today. Sure, absolutely. My name is Ali. I have a PhD in machine learning from UC Berkeley. I've been working in the space of biology and AI for almost a decade now. Previous to this, I led a moonshot at Salesforce, pioneering language models for biology. And what started out as a purely scientific endeavor to develop transformer models for sequence generation has led into ProFluent specifically, where our mission is to make biology programmable.

2:48:38And I'm happy to kind of break that down. Yeah, yeah. I've seen, obviously, there's a ton of just like momentum in the space, AI curing cancer is like a buzzword that a lot of people are throwing around. How are you thinking about concretizing what you're actually, how you're trying to fit in? Are you a tool? Are you a drug maker? Is it uncertain? Like, who are your customers? How much are you in like a science project world? Like, you know, you could be a nonprofit in another era versus like you're ready to commercialize, you're going to market and not that there's one path that's wrong or the other, but I'd love to know how you're thinking about the business right now.

2:49:20Totally. Yeah, I think there's a lot to unpack there. I think the meme that came to mind specifically, I don't know if it's a self-marketing or otherwise, where it starts with like build something and then there's a dot, dot, dot, question mark and then it's make profit. Step one, step one, you know, make biology programmable. Step two, bro down with your boys. Step three, profit. And I think a lot of folks, you know, right now there's an incredible amount of excitement around AI. It's kind of like step one is make a chat bot, for example, and then it's question mark, dot, dot, dot, and then solve disease or cure cancer specifically.

2:49:53Whereas what we're actually trying to build here is actually tackle on the disease head on specifically. So what we do is we build language models. So the same language models that have enabled GPT-2, 3, and 4, and chat GPT specifically, these incredible models and algorithms that can learn on sequences, what we can feed instead of words in a sentence is actually amino acids that are strung together to form a protein. And why that's actually important, why making biology programmable, maybe take a step back. People usually shut off their brains when it comes to biology. And when it comes to rockets landing on a platform in the ocean, we're amazed, right?

2:50:29And that makes sense, right? These are man-made machines. We can see it. They're incredible. But honestly, biology is not that much different. There are these molecular machines called proteins that enable us to breathe and see they're responsible for everything in human health and disease. And also they sustain the environment involved in daily products, like even our detergents to begin with. And how let's actually stick to drug discovery in particular, how we've gone about finding these solutions, these molecular machines that we utilize day in day out has actually been through random discovery.

2:51:00So, you know, that middle school example of Alexander Fleming coming across penicillin, right? He had a petri dish, they molded, for example, and then they found the advent of antibiotics. And now after you get a cut on your skin, for example, where the bacterial infection happens, it's no longer a death sentence, right? That actually is not the exception. It's the rule in which we've gone about finding life-saving medicines. Even fast forwarding to today, CRISPR-Cas9 was actually found in a Denisco yogurt facility where people found these interesting bacteria doing these interesting characteristics, having these interesting characteristics.

2:51:33It was taken a molecule, plucked it from nature and then crammed it within human therapeutic applications to actually save lives. And honestly, like, let's put this really in rudimentary terms, that's kind of absurd. It's almost caveman-like in terms of our technique, our techniques that we have and methods that we have available for us for drug discovery. And what we're trying to do is actually move away from random discovery and finding a needle in the haystack and relying on nature altogether and using AI to design bespoke medicines from scratch. And that's, you know, like, that's our mission to really gain control and mastery over biology and perform bespoke design.

2:52:11So in terms of your question of like, where are we with respect to, you know, is this just a science project or how's the commercialization looking specifically, I would still say we're in early days, like the equivalent of GPT eras of like maybe GPT-1 and GPT-2, but we've already seen an incredible amount attraction. So we have this project called OpenCRISPR specifically. What we took is we took these language models trained on gene editing proteins specifically and generated a novel protein from scratch called OpenCRISPR1 that thousands of people use now in pharma, large pharma, small biotechs, academics, industry users and scientists as well.

2:52:48And over thousands of people use this over worldwide today. And I think that's like, it's amazing to actually see us solving problems today that have lead to commercial traction and that we have partners both from therapeutics to diagnostics to biomanufacturing even agriculture that are utilizing today can you talk about like how you create feedback loops as a company because you know there's no shortage of people in ai that talk about the uh opportunity of like curing various diseases many of them aren't saying that from the standing in an actual lab you are standing in a lab, that makes me more excited about what you're doing because you're not just kind of, you know, like there's, you're not just saying like, oh, like the next version of the model will just do this.

2:53:33Like, don't worry about it. It's like, no, like we're going to run a lot of experiments. But yeah, talking about, yeah, like, you know, using AI to, to, to learn and generate, you know, potential approaches, but then actually bring it into a lab setting. Absolutely, yeah. We operate within a pre-training and post-training paradigm within proteins, similar to NLP and natural language processing as well. So the pre-training step really involves, similar to how we have all the internet that we can scrape from and can learn these underlying principles and grammar and semantics as to what makes human-generated texts, we've actually collected a tremendous amount of data of proteins that have naturally evolved through nature for selective reasons, selective pressures and evolutionary kind of pressures that have shaped those proteins specifically to make a functional protein.

2:54:20And just to put that into context, AlphaFold 3 was trained around, it was exposed to around 2 to 3 billion proteins. What we've actually trained to date so far at ProPoint is over 100 billion proteins. And to put that into tokens, that's over 20 trillion tokens. Exactly. So there's an incredible amount of data for pre-training purposes that we utilize. And then what you see behind me as well is the data that we're doing, the assay labels, labeled examples, meaning actually taking protein sequences and then measuring their function, not just in vitro and test tubes and petri dishes, but in human cells and relevant cellular contacts and seeing how well they actually perform and we can feed that back into our models.

2:55:01So I think that's, you know, the future is really an integrated future where you're building frontier AI models and having the closed loop specifically with respect to the wet lab, which is what's behind me today, to actually test these and feed them back into our models to get better and better over time. Well, congratulations. I want to ring the gong for you. And by the way, Gerstner and Bezos, I mean, potentially the coolest.

2:55:29How much was the deal? Yeah, absolutely. Yeah, it's$106 million. And I think what's more important, what's more important than number are these legendary investors that we have. I mean, Jeff Bezos is a legend. He's transformed industries. And I think what's exciting for him and for us as well is that biology is the next frontier for AI specifically that will have tremendous impact. And it really, honestly, is the most important question in our lifetime. So we're really excited. So much for stopping by. Sure, you will be back on very soon. And congratulations on all the progress. Great to meet you.

2:56:04We'll talk to you soon. Talk soon. Have a good one. Our next guest is already in the Restream waiting room. We have a hard stop at two. We got to run. We got to hop on with New York. So let's bring in Amit from Luma AI with some massive news. How are you doing? It's been too long. Great to see you again. Welcome to the show. What's happening? Give us the news. What happened today? What happened? Break it down for us. Yeah. So we did two massive things. One, Luma raised a$900 million Series C. Okay, what was the second thing? Come on, I'm sorry. Was there not another$100 million lying around? You couldn't?

2:56:45You're going to make us wait for the Luma$1 billion round? Come on, dude. I'm very happy to accept friends and family checks. Oh, yeah. If you got$100 million from your friends and family to round out, that would be fantastic. And then what is the second thing? And, yeah, the second thing is basically along with Humane, which is this AI company being built in Saudi Arabia, we are building a 2-gigawatt compute cluster that we are going to use to train multimodal AGI. This is the big news. This is actually the big news. This is much bigger. This is much more important. This is what we actually need to compute.

2:57:24So, you know, the TLDR of what happened here is basically, you know, so far, LLMs and LLM labs have had the right resources. And multimodality, world simulation, these problems actually, you know, were side projects for most companies. Now, there is a lab and there is a company in the world that has this level of resources and is going right after AGI that can help us in the physical world, AGI that can help us simulate and, you know, generate the universe. So I think that's actually what happened, basically. Amazing. How do you think about, how do you explain the scale of 2 gigawatts? Because it sounds like 2 is not a big number.

2:58:04And is that, is it 2 gigawatts because you're expecting 2 gigawatts worth of inference? Or do you need a particularly big cluster for some sort of pre-training run that you're planning on doing? So it's both inference and training. but inference is actually so you know majority of the workloads as we go forward right like you know as air deployment uh goes forward as we mature from just text only models to models that are able to like you know generate videos models that are able to explain things to us in video what's going to happen is most of the workload and tokens will move to video understanding and video generation and video tends to be you know computationally much more intense than than language.

2:58:47So we need this level of compute to be able to deploy this technology and to be able to train. But this is mostly inference, honestly. Even today, Luma's inference to training compute ratio is two to one already. And we are seeing that ramp actually growing further and further and further while we do deep research and train some of the largest models in our space. Inference is the one that is actually taking off. Okay. React to this take I got from someone who's also building a world model, a generative world model. He told me that he believes that it's more likely that AGI, something fully paradigm shifting emerges from world simulation than merely scaling up next token prediction, GPT 5, 6, 7, 8, 9.

2:59:38Getting away from text is actually somehow foundationally important to the next major breakthrough in AI as we know it as a whole. I think getting away from text is a mistake. We need to build models that combine audio, video, language, and image. So, like, you know, we need to build things that, like, operate like human brain. If you remove text, you remove the entire interpretation of the human logic and, like, you know, reasoning and those kind of things. So we need the physics that comes from video. We need the causality that comes from video. And we need the text, which actually makes all of this interpretable and logically connected.

3:00:15you know, across the world. So, no, I think what we need to do is build these joint unified models. But on the simulation side, I agree. And I think that's really, really important because think about robots or think about systems, you know, how they would operate, right? Like, they need to be able to understand the world. So, this is world understanding, which is where world models are going to be very, very powerful and multi-model models are going to be very powerful. And second is simulation, being able to run the process or idea in your head and drawing out conclusions. What if I go 20 meters this way?

3:00:50Would I fall? This is a simple question. But as robots become more general purpose and day-to-day in our lives, we need this level of simulation capability in their heads. So generative models give you simulation capability. Simulation is extremely important. Second thing is, LLMs are really good at things that can be represented more or less fully in text code analysis, these kind of things. But when we think of the physical world, especially acts like designing, you know, manufacturing, these kind of topics. Like one of the things we think a lot about at Luma is manufacturing of a jet engine, right?

3:01:24Or manufacturing of a rocket engine. These are one of the most complex things humans do, and it takes a decade to build one. imagine having models that are able to run these physical simulations and get to an answer it's not about the visuals it's about getting to the right answer people do that in cad people do that in in like you know software today but it's like very uh um inaccurate but if you're able to build models that can accelerate building of these complex systems humanity has a chance at like you know uh building better and better things for ourselves for for our planet so that is why simulation is really important and that's why multimodality is really important that text is just the first step to text is like you know 1990s internet then we got images on the internet then we got videos on the internet and today like you know videos is the internet for humans at least yes um ai will not be any different yeah um last question from my side uh what is the actual timeline for building a two gigawatt cluster yeah and where where where where will the majority of the infrastructure be when can i see it when can i go inside i can be trusted so some of it already exists so by the way, we are building this in partnership with Humane in Saudi Arabia.

3:02:30And today it was announced here. So we are in D.C. right now for the U.S.-Saudi Investment Forum. Oh, no way. It was announced by President Trump and Crown Prince Mohammed bin Salman. So the data center is going to be built in Saudi Arabia. Quite a lot of capacity is actually already available, and Luma is actually an active customer and using that today. But the deployment of two gigawatt is going to take time. That's an absolutely colossal amount of power and infrastructure that needs to be built, starting with 2026. And currently, we believe that by end of 27 or early 28, we will have majority of the capacity at hand.

3:03:08And we'll go from there. Fantastic. Well, thank you so much for taking time while you're traveling to come chat with us and break down what's going on. Congratulations on the amazing news and good luck with the next phase. I'm sure there's a lot going on. Next time you call in, call in from Saudi. That'd be amazing. From the desert. That'd be amazing. The first time actually I was on TPPN, I was in Saudi. Oh, no way. There we go. We already did it. We'll check that box. Next time I want one of those 4x4s that, you know, call in from the desert, from Humane. I want to be live on the ground with you.

3:03:48Amazing. Great to see you again. Congrats on the progress. Thank you so much for jumping on. We have to hop on with New York. No, but first, we have one post we got to pull up. One post. And it's a post that I made. You made. Right when I saw that NVIDIA beat. NVIDIA beat earnings. They have traded up. The stock is up 3.91%. Massive. It is at the very bottom. There were signs. This is your prediction. One of your many predictions. This is the only data. This is the only day that you need to know. You know, you said this. I think he's going to beat earnings because he's drinking beers. And Ev was like, yeah, you belong in a pod shop.

3:04:28And he was saying it like sarcastically. Like, you know, to be in a real hedge fund pod shop, like you have to be much more quantitative than that. Turns out you don't. Turns out the vibe-based analysis works. You got to take it all in. Absolutely. You got to take it all in. Thank you to everyone for tuning in and watching our show. Leave us five stars on Apple Podcasts and Spotify. And we will see you tomorrow. And the global economy continues. Continues. The party continues, folks. White suits tomorrow. Gabe in the chat. Gabe's getting drunk. Goodbye. Get drunk responsibly. See ya.