市场狂飙，IPO 新动向，AI 初创融资过热，Reddit 版主造反，对话布拉德·格斯特纳

Chamath Palihapitiya (00:00:00): I'm so fucking tired. I've slept 6 hours in 3 a half days. 6 hours. So wait wait. You went Jason Calacanis (00:00:06): to the world series of poker with Helmute. So you spent Chamath Palihapitiya (00:00:10): No. No. No. First of all, I flew public, took Southwest. What? Yeah. It cost me $49. flight? Costa. I got a ticket for forty nine bucks. It's so fucking incredible. Oh, did Jason Calacanis (00:00:20): you sit in seat a one also known as Jake House reserve seat? It has my name on it. Chamath Palihapitiya (00:00:24): Bose in the front row. great. You it's great. Like, Southwest has these numbers. And what they do is -- -- 1st Brad Gerstner (00:00:30): class on Southwest? Jason Calacanis (00:00:32): No. No. No. No. Premium. Plus. Brad Gerstner (00:00:34): He was in the front row. No. Chamath Palihapitiya (00:00:35): There's like these signs that that, like, have a number that attaches to your ticket. And then you stand in that line, and then you go on in this orderly way. And so I was I had, like, a 5 or something. So I was, like, the 5th person on. And then I sat in the front and I put my bags up top. Jason Calacanis (00:00:51): Yeah. You carried your bags. Yeah. Chamath Palihapitiya (00:00:52): An hour later, I was in Vegas. It was so easy Southwest is phenomenal, and then I flew back. Anyways and after after losing as much money as I did, it felt good to fly for $49. I Jason Calacanis (00:01:02): gotta be honest with you. Well, austerity measures have David Friedberg (00:01:04): their benefits. Jason Calacanis (00:01:05): You could sleep better at night with prosperity measures. And did you go to the all you can eat buffet and ticket to go as well? Chamath Palihapitiya (00:01:11): No. I may do that. Speaker 5 (00:01:12): You never know. to let your winter ride. Rainman, David Sachs. And it said, open source it to the fans and make discoveries. David Friedberg (00:01:30): Why did you fly Southwest? Chamath Palihapitiya (00:01:31): Why did I fly Southwest? Well, the planes in Europe with Matt, that's number 1. And then 2, I just wanted some flexibility to get in and out depending on when I busted these tournaments. So let me tell you about these tournaments. The 100 k is literally like the murderer's row of like every great Poker Pro. So it was like 96 of us or something. I gotta be honest with you. It was so much fun. so much fun. Why? How so? You know, we play 40 minute levels, and you have to really get the chips moving, which means that there's only so much like Game 3 optimal poker you can play. And at some point you just got to gamble it up and you got to take your shots and you have to be willing to bluff and You know, you have to bet for thin equity. It's so much fun. And then you see some of these guys that just lose their minds. Anyways, it was it was really, really a lot of fun. I finished in the middle of the pack, like, 42nd or something. So that was brutal. But then, the thing that I'm the most proud of is, and I went from that and I hopped in the 3 k six six handed right afterwards, and there was, like, 1250 people in that. And I got to 81st and -- Woah. -- the problem was, like, just couldn't get anything going. I couldn't get any real like, you need some card distribution. Like, you have to at some point -- Yes. -- make some hands. You can't just you know, I could bluff my way to 81st, but I needed hands to really to really, really have a chance to chip up and run it. Then I played in the RAS, which is 7 card stuff low, There's a 126 people now when I finished in the middle of the pack there. And then this 10 k bounty, there was about 600 people, and I finished, like, a 100 50th. Speaker 6 (00:03:08): Those are Jason Calacanis (00:03:08): all respectable. Chamath Palihapitiya (00:03:09): I mean, I know play tournaments. I have no idea how to play tournament, to be honest. I know David Friedberg (00:03:13): how to play poker. Chamath Palihapitiya (00:03:13): I know how to play catch games, but tournaments are very different. So feel like I was very ill prepared, but I had so much fun. And, you know, the crazy thing is when you're playing for 12 hours a day, you are focused for 12 hours. The thing that I forgot is that you end up I ended up losing like two and a half pounds. Brad Gerstner (00:03:31): Oh, wow. If your Chamath Palihapitiya (00:03:32): brain is going going going to 8 hours a day, biggest fucking thing. And I was I was mentally devastated at the end of each night. You're just lying in bed, eyes awake. Yep. And then you can't sleep, and so then, you know, you go and you play craps and buckwheat. Speaker 6 (00:03:47): break the Chamath Palihapitiya (00:03:47): casino for a couple hundred times a night there, and then go back to bed. It's great. Jason Calacanis (00:03:51): Great. Sounds like a great week. Brad Gerstner (00:03:52): The good news is is Phil was live blogging for you on your behalf from from the Chamath Palihapitiya (00:03:58): -- Jason Calacanis (00:03:59): Over your shoulder. Chamath Palihapitiya (00:03:59): Oh, by the way, the other thing was I brought my phone, but I don't have anything on my phone. Like, I don't have Twitter. I don't have any of that off. So I was just totally in the zone. It felt so great to not be connected to social media. It's a flow experience. Jason Calacanis (00:04:12): When you can turn just be in the moment. Congratulations on the on the you know, coming in the 10% of the field in the 3000 or 8% of the field. That's incredible, dude. Chamath Palihapitiya (00:04:21): If I really practice at these tournaments, I think I would bank a couple, but I just don't have the time. Jason Calacanis (00:04:25): The paradox there is that you did best in the largest field. If you can do this for 3 or 4 years, and you go into those RAS fields when it's a 100 or those 25 k 100 k is when it's a 100, 200 people. Chamath Palihapitiya (00:04:37): And the 100 okay. There's 90 95, 96 people. Like, you really do have about a 1% shot at winning the thing, which is pretty incredible. Jason Calacanis (00:04:44): Yeah. RAD's too. RAS is always a Chamath Palihapitiya (00:04:46): 100. David Friedberg (00:04:46): I love tournament poker. That was my that was my game back in the day. Chamath Palihapitiya (00:04:50): It's because it's because you're afraid to lose money, so it's poker for you. put up a small amount of money. You can play for many hours. In your mind, you're probably dividing the number of hours by your buy in so that you can think about what your hourly cost is. David Friedberg (00:05:02): I actually like Tournament Poker because when you lose, you lose. Like, you can't just -- Yeah. Chamath Palihapitiya (00:05:06): -- David Friedberg (00:05:06): rebuy it. And, basically and then and then there's a broader macro strategy. You start to play the chips against the other players because, you know, however, when else is playing based on how many chips they have in front of them, Chamath Palihapitiya (00:05:16): it's a great point. This theory of ICM, which is, like, independent chip model, is exactly what you just said. The craziest thing Friedberg happens right at the money bubble. These guys start I've never seen this before. They Ultra tank. David Friedberg (00:05:28): Ultra tank. Speaker 6 (00:05:29): Oh, yeah. Chamath Palihapitiya (00:05:29): They go in the tank for 2 minutes and then they fold Jason Calacanis (00:05:32): so obnoxious. David Friedberg (00:05:33): When I used to play tournament poker, I'd sit I'd I'd fold ace king suited. You'd fold pocket queens. You'd fold everything if you're on the bubble of getting into the money or you're on the bubble of getting to the final table. It just doesn't matter. because if there's 3 guys with you that that have smaller chip stacks, let them get blinded off. And now you're in the money or now you're on the final table. And then you'll play poker. It's like, go get up, go have some dinner, come back in an hour. Don't even look at your cards if you can cruise your way there. It's a totally different kind of game. Totally different. Chamath Palihapitiya (00:06:01): There's a guy that was tanking. He's a really lovely guy British guy. I offered him the mincash just just not taking. I was like, please stop taking for 4 minutes. and folding your ad. I'll just David Friedberg (00:06:13): meet it as action. Jason Calacanis (00:06:14): I kinda got through this in a tournament, and I timed it with the rest of the table. I took out my phone. I timed it. And I said whatever number of seconds you do, I'm doubling. And I just did that. It was so obnoxious that the entire table like, the guy finally stopped. Chamath Palihapitiya (00:06:29): Well, in the in the hundred k, we actually had a better setup, which is that we had these iPads on the table, and everybody gets a 32nd shot clock. So you can't really fuck around. But then in these big field events, they're not gonna have iPads on a hundred tables, obviously. Yes. And so instead, people just tank forever, and then you have to call the floor and you have to call time on these folks. The funniest thing, though, was, like, the last term that I bought in for was a 10 k secret bounty, which means that on day 2, when you knock somebody out, you actually Everybody stops the action. You go up on stage and you pull out of It's like treasure hunting. And some of these boundaries can be like a million bucks. And obviously there's a lot of people there that kind of recognized me. And when they saw me in the 10 k secret bounty, there was like a movement. It was so funny. They were like, if you win the secret bounty and you win the 1,000,000, we're gonna revolt and burn the rest David Friedberg (00:07:21): of Paris pairs to drown. I would have been Chamath Palihapitiya (00:07:24): so and I and I thought, you know, it's true. David Friedberg (00:07:26): It'd be patently unfair if Chamath Palihapitiya (00:07:28): I was the one that that $1,000,000,000 secret about it. Jason Calacanis (00:07:30): How many selfies did you take on Southwest? That's the question everybody wants to know. How many people recognized you on Southwest? And what was the shame That Brad Gerstner (00:07:37): you felt. Chamath Palihapitiya (00:07:38): It was great. Brad Gerstner (00:07:38): Where do Jason Calacanis (00:07:38): you fly from? Chamath Palihapitiya (00:07:39): I'm gonna fly I'm gonna fly Southwest to Vegas all the time now. It's fucking great. It I literally was honestly to get from my house to the gate where you stand to get into the plane. It was like, plus or maybe 15 minutes more than just driving on the tarmac. Like, it was a Nothing burger. Brad Gerstner (00:07:53): Jacob. Jason Calacanis (00:07:54): It's amazing what a down market could do to people. You know Speaker 6 (00:07:57): what I mean? Brad Gerstner (00:07:58): It is. You know what it says? Jason Calacanis (00:07:59): What is it, Brad? Brad Gerstner (00:08:00): This is the victory of the age of fitness. Shamas. Shamas. Shamas. Southwest. You were in the the first row of southwest. You were in the front row of southwest. Jason Calacanis (00:08:11): Alright. Listen. There's a big docket today. We've got a lot on the plate. David Sacks is busy in a star chamber right now selecting the next president of the United States. He's picking a VP in the cabinet for whoever's gonna win, so he couldn't make it today. So we brought the 5th bestie, Brad Gersner back, and great timing because the Fed decided to pause rate hikes in just yesterday, I guess. And this would have been the 11th executive rate hike. Is that about right? Brad Gerstner (00:08:37): Sounds right. Jason Calacanis (00:08:38): And they anticipated Chamath Palihapitiya (00:08:40): 2 Jason Calacanis (00:08:41): more 25 basis hikes before the end of the year. So here's just the Fed funds effective rate. So you can all can see it here over time. And there was also some big news this week. Couple of 2023 IPO candidates started to be floated. Obviously, we've been hearing about Reddit and tripe for a while, but arm comp financially filed for an IPO back in April, and they're seeking to raise between 8 and 10,000,000,000 later this year. That would be a pretty big deal for SoftBank, which owns the firm, and that could, I guess, save SoftBank, which has had a just a brutal run with the Chamath Palihapitiya (00:09:20): 2 Jason Calacanis (00:09:20): different opportunities that they did. Chamath Palihapitiya (00:09:23): -- David Friedberg (00:09:23): say save SoftBank. The armed deal is being done. Is what's the valuation that's being done at? Jason Calacanis (00:09:28): SoftBank acquired Arm for $32,000,000,000 in 20.16. They don't know the valuation right now. They haven't put that out there yet. David Friedberg (00:09:34): I mean, they were originally looking for anywhere from 30 to 70. But, I mean, Brad, where do you think that comes out? Brad Gerstner (00:09:38): I have no idea. I think that you know, they're shopping to get these anchor tenants into arm. If the IPO market was super hot and this was really easy to get done. This would have been done. You know? So I think, you know, they're tiptoeing now because they need to get it into the public market. But, you know, I I I think that anybody who does an IPO today, okay, is going to demand a, you know, a rate of return into that offering. That is a significant margin of safety relative to all deals that were done in Chamath Palihapitiya (00:10:16): 2020 2021. Brad Gerstner (00:10:17): And what that means is on the roadshow, investment banks go and they try to drum up demand. They wanna have anchors in the IPO book. They call firms like ours. They call strategic investors. They wanna size up what that is. And, you know, they give you their expectation of fair value or where they think the IPO will trade to. Of course, you meet with management, you ask or maintain and develop your own expectations at fair value. What I'm saying is maybe in the peak, you know, in 2020 2021, people were getting thinner and thinner In terms of the margin of safety, they demand. I my expectations, whether it's Arm, whether it's Databricks or other companies that are starting to queue up, and these are fantastic companies. Right? Make no mistake about it. NVIDIA tried to buy arm and, you know, Databricks is doing over a 1,000,000,000 in revenue growing extraordinarily fast led by an incredible team. But in order to get into the public markets, they have to, you know, step in with a bigger discount than they would of. you know, previous direction. Jason Calacanis (00:11:20): And just to put some numbers on it, Arm had agreed to be acquired by NVIDIA for 40,000,000,000 before the talks fell through. that was due to regulatory scrutiny. Bloomberg says arm is aiming for evaluation of 70,000,000,000. Obviously, there's no confirmation about that. That's just the news hopefully, intelligently speculating about it. Chamath Palihapitiya (00:11:35): What exactly would you be buying for $70,000,000,000? Yeah. Jason Calacanis (00:11:39): I thought Chamath Palihapitiya (00:11:39): they missed it. Speaker 6 (00:11:40): Yeah. Chamath Palihapitiya (00:11:41): arm had a window where they had to make some really important Speaker 6 (00:11:45): product decisions to be able to actually have reference designs that Chamath Palihapitiya (00:11:45): actually made sense beyond just simple mobile processors and CPUs, and they don't have any of that. So they have a good cash cow business. It's probably worth 25,000,000,000 They paid 30 some odd, 32. They could have gotten it out for 40 something, but it's a mid 20s $1,000,000,000 company. No more. And if you're and if if you buy it at the twenties, you're buying a cash flow yielding asset. David Friedberg (00:12:11): And be good luck to all the players. Chamath Palihapitiya (00:12:13): My guess is what I would say. David Friedberg (00:12:14): Clearly, it's a function of SoftBank seeking liquidity. Right? I mean, they it's had this position for how many years now? 4 years? Jason Calacanis (00:12:25): No more. I think this was -- 6 maybe? Chamath Palihapitiya (00:12:27): 6 years? -- something like that. Yeah. Jason Calacanis (00:12:29): When did they buy it? Was it 2016? I think it was longer. Yeah. Chamath Palihapitiya (00:12:32): 2016, Jason Calacanis (00:12:32): they bought it. So this has been And David Friedberg (00:12:34): in the fiscal year ending March, the Vision Fund alone took a $32,000,000,000 write down. Obviously, SoftBank has a big chunk of the Vision Fund. Chamath Palihapitiya (00:12:44): But this is not in the Vision Fund. And it's David Friedberg (00:12:46): not in the Vision Fund. Exactly. Jason Calacanis (00:12:47): This is not this is Chamath Palihapitiya (00:12:48): in -- -- on balance David Friedberg (00:12:48): sheet. It's on balance Brad Gerstner (00:12:49): sheet. Yeah. David Friedberg (00:12:50): Yeah. but it's clearly a liquidity driver for them. I don't think that this is you know? First of all, Jason, I don't think the point about SoftBank needs saving. It's necessarily true. It's not a company that needs saving, but they've certainly taken some hits. Chamath Palihapitiya (00:13:02): Well, they Jason Calacanis (00:13:03): could use a win. That's what my point. Yeah. David Friedberg (00:13:04): Yeah. They could use a win. But Chamath Palihapitiya (00:13:06): -- Jason Calacanis (00:13:07): The last two quarterly calls, you know, Masayoshi san was pretty repentant and humble. Right. And in fact, he used that exact language. We talked about it here. David Friedberg (00:13:18): So this big liquidity need at some point for the business. So they can get this thing out and get liquid on it. It would certainly support the balance sheet more than anything. Jason Calacanis (00:13:27): You know, the the market is on a tear this year, Brad. Is there now that everybody's buying back into tech stocks, I guess, two questions. Why is everybody suddenly buying into tech stocks when people think there's gonna be a recession and consumers have run out of money and Yeah. What what what's the thinking here of why so much money has gone to tech and this incredible rally? Brad Gerstner (00:13:53): It's been Jason Calacanis (00:13:53): great to watch, but People seem to be perplexed by the rally and then the Fed, even though they didn't do a rate hike, seem to put cold water on and say, hey. Listen. Don't get ahead of yourselves. We're gonna probably do rate hikes later in the year. Brad Gerstner (00:14:05): We all have short memories. You know, tech had a devastating year in 2022. So this is a bit of a reversion to the mean. Right? If you remember the chart, we, you know, we showed a lot on this pod last year at the at the end of starting at the end of Chamath Palihapitiya (00:14:19): 2021, Brad Gerstner (00:14:21): was that we were trading at, you know, multiples that were, you know, 50 to 70% above their 10 year average. And at the trough, we were trading about 30 to 40 percent below the 10 year average. Right? So the market corrected it overshoots on the upside because rates went to 0. And by the end of 2022, when you had Larry Summers and others who were going out and saying, we don't know what the upper bound of inflation and rates is, that's really scary to the markets. And so you had this overshoot to the downside. We're still trading below the 10 year average for Internet and software companies based upon our numbers. And so when you look at this, as we said at the end of last year, the framework changed early in this year. All of 22 was about 2 things. Is inflation going higher? and our rates going higher. And those things are debilitating for growth assets and growth multiples. By the beginning of this year, we started to have confidence that inflation had peaked, which meant that rates were largely in kind of, you know, spitting distance of their final destination And the framework shift to economy, are we going to have a hard landing? Now remember, at the start of the year, Mike Will from Morgan Stanley, who may give him credit, made the call in 2022. He said 22 was gonna be awful. He was right. but he stayed in that bearish position at the beginning of 2021, said the economy is gonna hit the skids in q 1, and that we're gonna revisit 3000 or 32100 on the S and P. Instead, we're sitting at 43100. So he was tragically wrong at the beginning of this year because, again, he was fighting, I think, the last battle that he that was won, as opposed to looking ahead and saying, this is no longer about rates and inflation. So the Nasdaq has moved 30% to start this year. You know, the Fed said yesterday, we're hitting pause. You know, the quote from chairman Powell that has everybody a little bit perplexed is on the one hand, he says we're data dependent. On the other hand, he said we're likely to have more rate hikes. Right? And the rates are going to stay high for a couple years. Brad Gerstner (00:16:34): Well, if we're data you can't have it both ways. If we're data dependent, we have a hard landing like Stan Druckenmiller thinks we're gonna have in q 4 this year, then rates are gonna get cut. But the market seems to like this, and let let's talk about where we are. The 10 years at about Chamath Palihapitiya (00:16:51): 3, 7, Brad Gerstner (00:16:52): The S and P is basically flat in terms of where it was and where it was before and where it was after the rate hike announcement, the economy appears to be reasonably good. 80 percent of earnings in q 1b, the guides were okay. Stan Druckenmiller said I shifted you know, he pulled forward when he thought we're gonna have a hard landing based upon the bank crisis, which now feels like it's a distant memory for many, and he's now calling for potentially a hard landing in q 4. So the Fed just came out and said, no. We're not gonna have a hard landing in q 4. We think we're gonna have 1% growth. They think that inflation to end the year gonna be at 3.2% versus the Chamath Palihapitiya (00:17:36): 3.7% Brad Gerstner (00:17:37): Goldman consensus. What I would say is, you know, we've moved but we're still below the 10 year average, but you have to start paying attention now to individual stocks that have likely gotten ahead of themselves or where they take Jason Calacanis (00:17:51): it out. What's an example of that? Who's gonna have themselves? Speaker 6 (00:17:53): A lot Brad Gerstner (00:17:53): of the return. Facebook, Apple. No. I you know, I think a lot of the AI related stocks are now at or within 10% of our end of year price target. And when you when you see that, take something like Nvidia if I'm playing at home or I'm a, you know, a professional investor, I may say, oh, I'm gonna go sell some long dated calls to buy a little protection to the downside. I don't think there's any problems with NVIDIA. I think they're gonna continue to perform. I think they beat their numbers for the balance of the year. But, you know, remember, at the start of the year, people thought they were going to miss their numbers for data center. People thought data center revenues this year were going to be negative, and they just revised their guide from $7,000,000,000 in Q2 to to $11,000,000,000 in Q2, so they've absolutely blistered their numbers. And the stocks gone from a Chamath Palihapitiya (00:18:45): $125 Brad Gerstner (00:18:47): you know, to to over $400. So when you have those parabolic moves, just like we did with rates last year, I think it's wise to say it's a fantastic company. We wanna be involved. It's gonna continue to be one of our larger positions. But if I can lock in 20 percent yield by selling calls 6 months out, I think that's a reasonable risk reward. So, you know, I think that's where we are. And now now the question really becomes, and it's unknown and unknowable. Right? Are we gonna have a soft landing, a medium landing, a hard landing, and q 4, and rolling into next year. And I would say as an investor, I'm very data dependent. You know, we're talking to companies. We're looking at Chamath Palihapitiya (00:19:26): -- Jason Calacanis (00:19:26): What data point should we all be looking at at this point? Shamoff, you think jobs, unemployment, just these stocks and their multiples? And how are you looking at it as a capital allocator per month? Still on the sidelines? David Friedberg (00:19:38): What have I said like a Chamath Palihapitiya (00:19:39): broken record? Rates are gonna be higher than you want, and they're gonna be around for longer than you like. And now Powell is basically telling you the same thing. So we're almost at the end of, I think, the bottoming, though. I don't agree with the Druckenmiller. I think he's wrong. Jason Calacanis (00:19:59): On which part? That doesn't be a hard landing in Q Four? Chamath Palihapitiya (00:20:02): Yeah. And the reason there's not gonna be a hard landing is you just thought China today basically say we're gonna start to rip in 1,000,000,000,000,000 of dollars. They're gonna stimulate the economy. You can't have a hard landing when China is printing 1,000,000,000,000 of dollars. Not possible. So I think that what Powell was forecasting is that if China starts to basically turn on the money printer and go through a huge spade of quantitative easing it's gonna just inflate everything because they're just such a critical artery to the world economy. And so you just have to get prepared for rates just being sticky. and inflation being sticky. And I think that that's probably the most reasonable base case for the rest of the decade. Jason Calacanis (00:20:43): Right. are the decade. It's 7 more years now. Yeah. Chamath Palihapitiya (00:20:45): Yeah. And so in that environment, the problem is that now you have the 7 or 8 most valuable tech stocks priced to perfection yet again. If you look at their enterprise value over their net income, these things are trading at astronomical yields. that are less than half of the 2 year note and now approaching sometimes less than half of the 10 year note. government bonds. That makes no sense. And if you subtract out those 7 or 8 biggest companies in the S and P 500, the S and P has not been a great asset. So the I think the equal weighted index you probably know the exact number. The equal weight index is just shit. So what does all this mean? I think it means that people are psychologically exhausted with having lost money. They are psychologically wanting to wheel the market up. They want to psychologically believe whatever will allow them to influence rates getting cut But I think the most reasonable bear cases rates aren't getting cut and whatever hope you had of rates getting cut just went out the window today because there is no world in which you cut rates when China is gonna print $1,000,000,000,000 a month. Jason Calacanis (00:21:58): Freeport, a lot of people seem to think that this big run up in the markets is AI related. Everybody's got an AI angle for their company. Some of them super valid like Microsoft and Google. Other ones feels kind of speculative. We talked about BuzzFeed talked about having AI journalists and their stock which looks like it's gonna be delisted. Got a quick pop. Do you think the AI AI actually coming to market Driving efficiency, driving revenue for companies is going to happen in the short to midterm, or is it more like midterm to long term? In other words, is the AI rally overheated and fake? David Friedberg (00:22:37): I don't know if I would assume that the pricing of equities is entirely driven by AI. I think there's a lot of factors in including a lot of folks maybe being on the sidelines for too long and needing to come and buy in at the same time. But I do think that there's a radical realization underway that a lot of businesses that are dependent on services that might be replaced by AI don't necessarily have the longevity today. Those are businesses that have been severely hurt by the point of view of what AI could bring to market and bring to industry. there's a lot of stuff happening on the short side. On the long side, I think it's a distribution curve on like how quickly different industries will be affected in a positive way by AI. Certainly, the most obvious is demand for chips It's all the same for the audio being built out. So that's the first. And so, you know, with a high discount rate, which is the environment we're in today, you can more quickly bet on those opportunities. And so you see a disproportionate bubbling in valuation and multiples on businesses like that. There are other businesses that are further down like services businesses. How long until lawyers are able to leverage AI? How long until banks investment banks are gonna be leveraging AI to create new products and improve their margins? There's a lot of speculation and a lot of ideas, but the discount rate is quite high right now. And that's probably a few years out to the point that the fuzziness wipes out the potential value there. Speaker 6 (00:24:15): What do Jason Calacanis (00:24:15): you mean by the discount in this context? David Friedberg (00:24:17): So let's say that I think that investment banks are gonna be severely changed in 7 to 10 years. That's the time horizon. I think that their business is gonna improve because of AI, as an example. Or, you know, factory machinery automation, right, manufacturing businesses. Probably 10 to 15 years So I can't really give them that much credit today. And so I I apply a higher discount rate there, but there are other industries that are certainly being affected much more quickly And, you know, I'm sure Brad and his his team of of finance wizard's probably have a a board, you know, where they have this list of all the industries are gonna and what time horizon. I mean, that's the way you could kinda think about this. And over different time horizons, you could kind of accrue some net improvement to earnings. and say, okay. You apply a discount rate to that. Here's how much the stock should trade up, and and, you know, that's one way to kinda think about this. I don't think it's everything everywhere all at once. Jason Calacanis (00:25:11): Great drop. Great reference, Brad. Chamath Palihapitiya (00:25:13): Great. By the way, I I gotta tell you, David Friedberg (00:25:14): I just saw that movie. I have to reference it because I saw it over the weekend. Have you seen that movie? Jason Calacanis (00:25:19): Of course. Of course. Yeah. What we should take? Chamath Palihapitiya (00:25:21): -- David Friedberg (00:25:21): an unbelievable film. I've I had not seen that film. I had Chamath Palihapitiya (00:25:24): kept on David Friedberg (00:25:25): postponing it. Incredible. Anyway, shout out. Chamath Palihapitiya (00:25:28): What movie? It's -- David Friedberg (00:25:29): Everything everywhere all at once. It won best picture at the Oscars last year. Chamath Palihapitiya (00:25:35): I don't trust the best picture of words at the Oscars. For a few years, I've just been duped by that award. Like, you get some really crap ass movies that are like -- David Friedberg (00:25:44): Watch this movie and then report back. Let's I won't even say it anymore. Chamath Palihapitiya (00:25:47): Politically correct or whatever, and then they they David Friedberg (00:25:49): get this a little Jason Calacanis (00:25:49): more -- -- virtue signaling. They were doing a little catch up because of Oscar so white, the movement to try to balance things out. In fact, people Chamath Palihapitiya (00:25:56): -- Well, that doesn't exactly reinforce trust that actually destroys complete trust and reputational credibility? Jason Calacanis (00:26:02): Yes. They're virtuous. And, actually, that was something people said that everything everywhere all at once was possibly because it's an Asian cast. I don't even know what is it. What is it? It's a sci fi adventure surrealist kind of rump Michelle Yo, is in it? She's very famous. Chamath Palihapitiya (00:26:20): From Croching Tiger Hidden Dragon? Correct. David Friedberg (00:26:22): Yeah. Exactly. She can't ask. Jason Calacanis (00:26:24): She can't ask. -- Kwan is in it. who played short round in Indiana Jones. Chamath Palihapitiya (00:26:29): Indiana Jones. Yep. David Friedberg (00:26:31): And I Jason Calacanis (00:26:31): don't do my impersonation, but I would get canceled for doing the impersonation of him in that fat Chamath Palihapitiya (00:26:36): guy must be, like, fucking seventy years old Jason Calacanis (00:26:38): now. David Friedberg (00:26:39): Yeah. No. He's, like, married. Jason Calacanis (00:26:40): He's, like, fifty or something. But it it's pretty great because he also won best actor, best supporting actor. And there are all these pictures of him with Harrison Ford and Steven Friedberg, The guys that made it -- Yeah. David Friedberg (00:26:53): The guys that made it are, like, music video directors. You gotta go see this film. It's really good. Speaker 6 (00:26:58): It's Chamath Palihapitiya (00:26:58): -- Jason Calacanis (00:26:58): And on a David Friedberg (00:26:59): really great, by the way. They have to go Chamath Palihapitiya (00:27:01): to a theater. You have to go to theaters. They just watch Speaker 6 (00:27:03): it on Brad Gerstner (00:27:03): one of your theaters. David Friedberg (00:27:04): Watch it on Apple TV in one of your theaters tonight. Jason Calacanis (00:27:06): Go to your theaters. -- theaters. David Friedberg (00:27:08): go to the theater on your plane and watch it today. Jason Calacanis (00:27:09): The theater David Friedberg (00:27:10): is in this literal theater Chamath Palihapitiya (00:27:11): on and do an interaction. Actually, we'll do that. I'll do that when I'm fighting. -- Jason Calacanis (00:27:14): moment on Shamad's point I ever had. I go to the bathroom. You know, it's a long flight back from Italy. So I'm taking my time, and I see that ASSA soap that I can't afford. It's like a 100 -- ASAP. Yeah. That one. So I see that, and I'm like, wait a second. So I look in the cabinet underneath. I'm like, if there's 2 up here, there's gotta be 6 down below. So I checked in the galley. Of course, there's 6 down there. I put 2. I boost 2 on my paper, which I'm still not doing in my in my bathroom here. That's about 300 bucks. No. No. No. Then I could do. And I check out. He's got a TV set up. So I'm like, oh, I wonder what movies are on here. And it's Netflix. He's got so much bandwidth on that freaking plane that Brad Gerstner (00:27:55): can train you on the plane. Jason Calacanis (00:27:57): You don't have to download your movies before you take off on Shamaz's plane. Alright. Let's get back to work here. Speaker 6 (00:28:02): Right. Right. David Friedberg (00:28:03): Have you seen it, by the way? Have you seen that movie? Brad Gerstner (00:28:05): Yeah. Incredible move. Incredible move. He's gotta watch it. Jason Calacanis (00:28:08): It's not the best film of thee. That was TAR, but I don't wanna get into it with Jamath. Chamath Palihapitiya (00:28:13): Oh my god. I tried to watch TAR. That movie sucks balls. It was so boring and fucking self absorbed and contrived. It is a little self absorbed all the bit. But that's what I like about it. For anybody that has sleeping issues and otherwise needs to use a sleeping aid, I would just put that movie on because, you know, once you see Kate Blanche had blathering on and walking back and forth from her kid's fucking school and then some crappy piano play. You'll fall asleep? And then next thing you know by the morning. Jason Calacanis (00:28:40): What puts you to bed faster, Tremoth? Ambien, Speaker 6 (00:28:44): tar, or science corner? Ambien tar or science corner. Which one? I Chamath Palihapitiya (00:28:48): I actually love science corner. Jason Calacanis (00:28:50): I love science corner too. Chamath Palihapitiya (00:28:50): I don't take I don't take sleep aids. I've taken Ambien three times in my life. Yeah. But that was recreationally during the day. Jason Calacanis (00:28:57): That's the thing. No. No. No. Chamath Palihapitiya (00:28:58): It was prescribed to me because I wanted to try it. I also tried Lunesta once. They were they're both, like with that Jason Calacanis (00:29:04): stuff, man. You'll start tweeting weird shit. Be careful. Chamath Palihapitiya (00:29:07): I've tried those sleeping aids four times in my life. And you wake up I wake up with a it has a really bad tail effect. So, like, you wake I woke up. Yeah. I wake up super groggy. I only get 5 or 6 hours of sleep with it. So anyways, I I do take melatonin, and that's really good. Jason Calacanis (00:29:21): That works. That's natural. And it does Chamath Palihapitiya (00:29:23): the trick Does a trick for me, and then I try to Brad Gerstner (00:29:25): just -- -- everybody on melatonin all of a sudden. Like, everybody I go takes melatonin. Are you just Jason Calacanis (00:29:30): a naturally -- -- to eat Chamath Palihapitiya (00:29:31): and to sleep? Yeah. For me, what I do is, like, I use it as part of a routine where, like, typically around 10, like all the, you know, devices, things get silenced and do not disturb mode. And I'm in a really restful place by 10 o'clock. I mean, usually, by 10:15 to 10:30, I'm out like a light. Jason Calacanis (00:29:49): I just got this infrared sauna. You guys have infrared sauna. This is, like, the new hotness. And, man, that is incredible. You get a Heart rate goes way up and then you sleep like a baby. Okay. Let's get back to AI. Brad, are people getting too much credit in their stock prices and is the -- Great. Chamath Palihapitiya (00:30:04): Do you do contrast therapy after the infrared sauna? I don't know contrast Jason Calacanis (00:30:08): ideas. What is that? Chamath Palihapitiya (00:30:09): Meaning when you do the hot, then you jump into, like, an ice bath. Jason Calacanis (00:30:12): No. I'm getting an ice bath Chamath Palihapitiya (00:30:14): -- Brad Gerstner (00:30:14): Of course. Yes. Chamath Palihapitiya (00:30:15): -- Jason Calacanis (00:30:15): next from my little outdoor sauna area, and I'm gonna start doing that. I did that with my friend Antonio Antonio friend of the pod, Antonio Gracias, He's got one of those cold plunges. We jump in the cold plunge together. He's got this thing at 45 freaking degrees. He says, don't try to do too much. You'll have a heart attack. So I go in. I get 45 seconds in. I start breathing, like, really heavily, and I'm like, I gotta get the hell out of here. He does 6 minutes. Yeah. Mine is an animal. Chamath Palihapitiya (00:30:40): I do 4 minutes three times a week. What temperature? What temperature? 42 to 40 4. The research paper that everybody references now, I think her name is Suzanne Soderbergh or something like that. She's the Swedish researcher. Huberman did it on his podcast that Rogan did it. Anyways, the the data is like an like, a little less than an hour of heat and 11 minutes of cold per week per week was shown to be physiologically optimal. So I do it three times a week, 20 minutes of heat followed by 4 minutes of of cold plunge three times a week. Jason Calacanis (00:31:15): Do you have, like, a cold plunge where you set the dial on it? Or is it -- No. Chamath Palihapitiya (00:31:18): No. I -- -- cold water in No. I do old school. I I use the master steam in my bathroom. Uh-huh. Because I after I'm done working out, the last thing I wanna slip outside, find my slippers, put on a robe. I'm not gonna do any of that. So I walk upstairs. I do the mister's team at, like, a 110 degrees. And then while I'm working out, somebody just makes an ice bath for me and -- Jason Calacanis (00:31:40): Oh, nothing. Chamath Palihapitiya (00:31:40): -- Speaker 6 (00:31:40): put a Chamath Palihapitiya (00:31:41): bunch of ice in the tub, fill it with water, and just jump in it. So they what do they do? Jason Calacanis (00:31:45): Do they carve, like, a bunch of baby seals in ice? And then they just when you get No. Chamath Palihapitiya (00:31:49): No. All the ice cubes were made to look like my face. So I have these shapes of ice. -- David Friedberg (00:31:54): of yourself? Chamath Palihapitiya (00:31:54): Sound like looking David Friedberg (00:31:55): at myself. Jason Calacanis (00:31:56): Yeah. No. infrared gets up to, like, a 130, a 140 degrees. and your heart rate will go up to a 140, 150 degrees in this. It's a whole different experience than the misterstown stuff. Brad Gerstner (00:32:06): I I was recently on a ski trip. Yeah. And it's a this extraordinary sauna, it's wood fired. Okay? Jason Calacanis (00:32:14): And told me about this. Brad Gerstner (00:32:15): So the so the lead guide on this trip we go down there, he gets the thing heated up before we show up. Right? And I show up with this great athlete down there, and we go into hot mocks because you know, this is a thing to do. Speaker 6 (00:32:28): Yeah. Brad Gerstner (00:32:28): And I look at the thermostat. I think it's broken. It shows like, shit. It's hard pegged at, 225 Degrees Fahrenheit. Jason Calacanis (00:32:37): That's a lot. Brad Gerstner (00:32:38): You walk in, you're yeah. I mean, you slow cooked meat at 225. That's that's that's that's what I'm saying. My lips are burning. You know? And this this person sitting in there is like, now this is the way you do it. Right? Tough guys. You do it at this temperature. We're like, alright. So, you know, we sit in there for, like, 10:10 minutes, and then we go and we jump in a, you know, in in a frozen lake. And about 10 minutes later, we're taking off. We had to leave this particular place, and, you know, people are way waving goodbye, and they're looking you know, they have to look over Asana -- Yeah. Chamath Palihapitiya (00:33:09): -- Brad Gerstner (00:33:09): as they're waiting to buy. And they noticed that the Asana is on fire. Chamath Palihapitiya (00:33:13): Ah, yeah. That's well, so, basically, what happens when you go to 2020? Unbelievable. But Brad Gerstner (00:33:20): it's in there. People are taking this a bit to the excess. Jason Calacanis (00:33:22): It's a little crazy. Alright. So back to back to the docket here. AI Brad Gerstner (00:33:26): Yeah. Jason Calacanis (00:33:26): Are people getting too much credit in public markets kinda running with this before it's actually ready for prime time just to add to Friedberg point here? There are a lot of people talking about doing things. In startups, I see people actually doing things. I would say 4 out of 5 startups that we've sit in and the majority of them that we're being pitched on right now are not only talking about AI, which they were all talking about it 3 years ago. They're actually implementing it now because the tool sets are available. I just had a call. Thank you, Freeburg, for putting me in touch with the Google people. I just did a call this past week with Google, and they gave me some previews of what working on. I can't say anything about it, but it's it's mind blocking. I think Google's not as far behind closed AI as David Friedberg (00:34:05): you think. What's your read on Google now? We had a little kerfuffle when I when I talked about Sundar's reaction to, you know, AI and the concerns that others might have on folks talking about the company. I mean, what's your point of view on Google today? I don't know if you've talked about this. Brad Gerstner (00:34:20): Yeah. Yeah. No. Well, I mean, I think you know, I had this I had this dinner, this incredible dinner, actually, Thursday at the pub. And, you know, it's it's how I know Silicon Valley's back because it was just like serendipitous. We threw it together in afternoon. You had this, like, 4 extraordinary, you know, CEOs there, and, you know, you had Mustafa, one of the cofounders, deep mind there, and Rich Barton from Expedia and Zoe. Just just an incredible group. And the $20,000,000,000,000 question is how does the entire open architecture of the web, get re architected in the age of AI. Another way of ask asking the question, because we're all kind of playing small ball. Right? We're all talking about, oh, you know, our GPUs and GPUs, you know, and who what cloud's gonna get accelerated. That's kind of the small ball. The big ball here, the $20,000,000,000,000 question that has defined the entire Internet for our entire careers has been web search. And I will tell you that the conversation around that table, there's increasing confidence that whatever comes next Right? The top of the funnel is up for grabs and all of those dollars. Over a period, again, a 5 years, 7 years, is going to get redistributed. And make no mistake, Google is well positioned to make its claim for that. But its claim is going to come at the expense of search. And so Google may create the best AI in the world. but it's gonna have to fight off the cannibalization of core search. And the question is in this new thing. And so Rich Barton, you know, an incredible product founder. Right? Think about Expedia. Chamath Palihapitiya (00:36:01): -- David Friedberg (00:36:01): Zillow? Brad Gerstner (00:36:01): Yes. In Zillow. So he's founder of Expedia and founder of Zillow. 2 vertical search engines that dominated right their particular verticals. And the topic of the conversation was that the new UI Right? The new you way you interact with your customers, right, is not optimizing a web page. It's not optimizing an application. he calls it the race to intimacy. The race to intimacy that you have to build a conversational UI. Chamath Palihapitiya (00:36:31): I've run that race a few times. Brad Gerstner (00:36:33): And no. And it's related race. Speaker 6 (00:36:35): I think that was Jason Calacanis (00:36:36): a sprint, not a marathon. Chamath Palihapitiya (00:36:39): Sometimes it's been a marathon. Speaker 6 (00:36:40): And Brad Gerstner (00:36:40): it's an ultimate question. who ends up on top? You know, are you always on top, Jamonne? Speaker 6 (00:36:47): Oh, god. David Friedberg (00:36:47): This is I I Chamath Palihapitiya (00:36:48): run really good middle distances. And then if I need to just make it, you know, run a Boston marathon. I can if I want it, but I don't know. Jason Calacanis (00:36:54): Oh, okay. Yeah. Sure you can. Yeah. Brad Gerstner (00:36:56): But I think, you know, I took a bowl of Chamath Palihapitiya (00:36:58): -- Brad Gerstner (00:36:58): Does he Chamath Palihapitiya (00:36:58): think sorry. Does he think Zillow is dead? That'd be he's no longer sure what they're guessing? Brad Gerstner (00:37:02): mean, don't tell me. Is the CEO? Is the chairman -- Sorry. Chamath Palihapitiya (00:37:05): Not Zillow. Sorry. Not Zillow. Expedia. Pardon me. What does he think about Expedia and travel? Brad Gerstner (00:37:09): Well, you know, you and had this conversation, Gurley chimed in. The guest chimed in on Twitter. Well, you're not on Twitter, but they chimed in. You know, about the conversation from last week's pod, Every vertical Jason Calacanis (00:37:21): search engine and Google itself, that architecture is suspect. Right? The question Brad Gerstner (00:37:21): is just over what timeline is it suspect. But the world is moving past 10 blue links. Information retrieval that looked like a card catalog is not where we're going. David Friedberg (00:37:38): You no longer need an index. You need someone to do the retrieval from the index for you. That's the the new service Brad Gerstner (00:37:44): that's gonna -- -- to the knowledge. And, again, that's I think it's David Friedberg (00:37:46): personalized to you. But I think one of the questions that's still outstanding from an architectural point of view in terms of your interaction with all the data in the world is, are you as a user gonna have a number of independent relationships with your travel search engine? your travel agent, or you're gonna have a relationship with your doctor medical office, and you're gonna have a separate relationship with your, you know, financial advisory type service? Or are you gonna end up seeing similar to the challenge we have in search versus vertical search today? an aggregator of services because there's value in cross populating the data and the knowledge about you across those services. Chamath Palihapitiya (00:38:26): So -- Yeah. David Friedberg (00:38:26): Sure. You know? Chamath Palihapitiya (00:38:27): I should -- It's gonna be the no. It's gonna be the former. Because, like, obviously, there's value to the company because every company wants to profiteer from you and monetize you in nine different ways and maximize the equity for their employees and their founders, and their board and their shareholders. But that's not what people want. Right? So like for example, when you go to a doctor, would your doctor be better off if she also had all of your data from, I don't know, pick your other service providers. Of course, maybe you could make a claim that if they had all of your personal information, and they understood your risk factors. They could do a much better job. But the reason you don't do that is you want some segregated relationship A, it gives you some level of privacy, but mostly it gives you control. In a world of AI where you can be more conversational, the idea humans will wanna get reduced to talking to one thing for everything, I think is wrong. I think instead it's actually going to be hyper fragmented. because the best in class use cases are going to be the things that people want. And then b, it gives the user control. The one thing I would tell people is Do not give up all of your data to one thing who's professing to be at all. They are going to lie to you and trick you and you're gonna have a social media problem writ large all over again. David Friedberg (00:39:44): There's another way to think about this, which is the reverse of the client server model where today you as you are the client, you are the node on the network, and you're communicating with the center of the network, which is the server. which is the service provider. And all the data sits there and you're getting data in and out of their product to suit your particular objectives. But the future may be that more data is aggregating and accruing about you, you end up becoming a server. You then have the option just this speaks to kind of the architecture on the Internet. Imagine if every individual had their own IP address. And that individual's IP address had behind it, behind your ability to control lots of information and lots of output about all all your interactions across the different network of service providers that you use. Chamath Palihapitiya (00:40:29): That's a very smart framework, I think. David Friedberg (00:40:31): And that object and and, ultimately, what what Chamath Palihapitiya (00:40:33): you would agree you wanna be able to rent that data to services. 100%. I don't David Friedberg (00:40:36): even I don't even think it's about rent as yeah. As much as it is about you should have -- And Chamath Palihapitiya (00:40:40): the reason the reason rent well, that then you have rent it. You can't give it to them because that's be stupid. David Friedberg (00:40:45): That's right. And so your your goal your your usage like, let's say the doctor says, hey. Can I can I get access to your health data? Or, sorry, your your Apple Watch activity data for the last year. You then have the option to provide that data to them through some permission type service that you then make available. So there will be interconnectivity amongst the service providers, but entirely and controlled by the user. Chamath Palihapitiya (00:41:06): Look, you're seeing this up front now with Reddit. When in this world, the people that create the content are actually in control of the data. And if you try to, like, monetize an API without paying the people that created it or giving them control, they'll revolt. You're seeing it happen. Now Reddit lost, what, 90 some odd x percent of all of their content because the mods were like, fuck you to Reddit. Well, Think of that writ large where everybody is asked, hey. I'm this great service. Hey. I'm this great service. I can solve x, y, and z problem for you. Just give me all your data. And then if you're not asking, well, what do I get? And they're like, well, you're gonna get a whizbang service and that's all they say. You're being tricked. It's already happening. Jason Calacanis (00:41:47): And there's an open source lawsuit against Microsoft's GitHub Copilot, and you have the Getty lawsuit. And You know, it it there's also a corollary for this. Google tried to kill Expedia already. They tried to kill Yelp, and it didn't work. folks use both services. And, you know, if you if you are trying to boil the ocean like chattyBT might, I think it's not gonna work because there's gonna be so much innovation, so much community, brand, and all that kind of stuff. And these LLMs seem to be trending towards good enough or some kind of parody that I think you're right from off. People are just not gonna give their data over wholesale. I've been using the the Zillow plug in to get exact. And the Zillow plug in sucks on Chat sheet. It's getting slightly better. Brad Gerstner (00:42:29): Well, it gives the wrong model. Jason Calacanis (00:42:31): Well, it's gonna live this will exist on Zillow site. Zillow will not let chat GPT take their business, you're gonna go to Zillow site and you're gonna say, hey, show me homes that have a sauna and a nice plunge and that are Four bedrooms and that are, you know, fix our uppers or are not fixer uppers and have in suite bathrooms and whatever. And and it's just gonna give you that list. Why would they give that business to closed eye. Brad Gerstner (00:42:53): Can I take a crack just summarizing what we all just said? Because your your initial question was, Friedberg was like, what does this mean for Google? What we all just said that what we're certain of is there's not gonna be 10 blue links and a model of search that they have monetized in a way that has been the most prolific business model in the history of capitalism. Right? So that's a problem for them, you know, from a business model So they're gonna have to reinvent their business. That's gonna be hard to do. It's like rebuilding the plane on the fly. But that then if you just go to the 2 models that we outlined here. On the one hand, Shamas said, you know, you're gonna work with all of these agents. That's exactly what Mark Zuckerberg said on Lex. He's like, you're not gonna have one super agent. You're gonna have know, hundreds of agents, and he he he thinks of what's happened. All of his platforms is the new open web where all of these agents will live and you'll interact with them. You'll interact with your Zillow agent there. You'll interact with your booking agent, your Expedia agent there, etcetera. On the other hand, chatgPT high at inflection, Reed Hoffman and and and Mustafa and many others think that the benefits of general intelligence, this will be the first time that we solve vertical problems horizontally. Right? And their metaphor, the compare there is we all don't have a hundred personal assistance in our in our office. You have one that gets to know you really well. They get to know what you like to wear, how you like to travel. the things you like to eat, the things you like in your house, how many kids you have. So there's a real leverage in that in that horizontal knowledge that can then be a applied to these different verticals. I think the answer lies in between. Your personal assistant will do a lot of the general stuff. Okay? Brad Gerstner (00:44:36): Whether it's pie, chat, GPT, whatever goods comes up with, etcetera. But I think they will subcontract the work, whether they chain it out via, you know, behind the the scene, you know, mechanism to other agents. So for example, if you're interested in traveling to this undisclosed location that I'm at in in in Europe right now. You know, my a my my assistant doesn't know anything about this place. So she may interact with a specialist for this particular place to get you that magical experience. So, you know, I I don't think you have to pick 1 or the other, but architecturally. Chamath Palihapitiya (00:45:13): $20,000,000,000,000 Brad Gerstner (00:45:14): of value on the web is built around web pages, advertising, and ecommerce, right, and sending traffic to those other places. And what we're all saying unequivocally is it's moving to knowledge extraction and intelligent agents. And I think that's tectonic. Jason Calacanis (00:45:34): But I still think there'll be clicks. I, you know, I have been using Bard a whole bunch and they have made massive rapid progress just to give you, but one example here I'll share my screen. It is pretty extraordinary how quickly they're figuring this out And I did this just in the search while we're talking about the 5 Best Greek restaurants in the Bay Area. Obviously, came out with Kokari and, you know, other ones. And then I asked that, like, hey, what are the top items on each of these menus? They started putting images in and linking to Yelp. And then I said, hey, tell me the most expensive wines and It actually got that from Kokari. They have a Chateau Margaux 2009 for 1500 Shamath. I don't think it's good enough for you. David Friedberg (00:46:14): But What year is it? Jason Calacanis (00:46:15): It looks like 2009. Yeah. They have screaming Eagle 2013. I'm I don't know if that's a no go. Harlan 2014. Yeah. So it's a no go. David Friedberg (00:46:23): New go reach. Yep. Chamath Palihapitiya (00:46:25): Yeah. But anyway -- Oh, Harlan's good. Harlan's good. 1 year's okay. Jason Calacanis (00:46:28): Okay. Good. So we gotta say. Anyway, this I did the same exact search, like, 4 weeks ago. It didn't have images. and it couldn't get me the items on the menus. And these could all be links. And these could all be paid links. So in these results, there's nothing to stop Google from saying, hey. Yo. If you want we'll put your information here or not up to you. You choose do robots dot TXT except where to call it. ai.txt. You'd tell us what you wanna be included. And if you wanna be included, we want you know, it's it's a marketplace for clicks. We'll include 3 of your images with clicks, and we'll call it sponsored. they are gonna be able to insert ads into here that are better than the current ads, and that will perform at a higher level, and they're gonna know us. This could actually be the reverse of what everybody's thinking. This could lead to higher CPMs and higher cost per click because of intent. Chamath Palihapitiya (00:47:13): By the way, I mean, the the 2014 is actually, I think, underrated, and it's very highly rated, but I think it is an excellent one. Alright. That's an excellent year. Brad Gerstner (00:47:23): Okay. Jason, as to your point, I think all of that I mean, that's impressive. It's true. You can also do it on chat GPT. I'll just say, the number of people I interact with on a global basis who talk about Chamath GPT versus Bard is, like, 10 to 1 today. Now Google's got massive -- -- change real fast. Google's got massive distribution power. me tell you what I what I also think the -- But Jason Calacanis (00:47:45): but to your point, Brad, about this, Brett, I just Brad Gerstner (00:47:47): wanna I wanna respond to your -- Sure. Sure. Chamath Palihapitiya (00:47:48): -- Jason Calacanis (00:47:48): Bard versus GPT 4. That's people are not paying attention. And when Google puts this on the home page Chamath Palihapitiya (00:47:56): -- Speaker 6 (00:47:56): Yeah. Chamath Palihapitiya (00:47:56): -- Jason Calacanis (00:47:56): and starts sending 5% of users to it, I mean, obviously, it's expensive to do powerful. People are gonna have their eyes jump out of their head. I think Google's going to be Chamath PD Four, I'm saying it right here right now. I think they're going to beat them. because I think that they're better at indexing all this information and understanding it than anybody on the planet, and they have the the largest ad network. If they get this done in the next 6 months, I think it's gonna increase the cost per click because they're gonna know so much about each user, continue your bread. I know I'm in the minority here. Brad Gerstner (00:48:25): Well, No. No. I I mean, listen. I think a lot of Google's revenue comes from de facto navigation of the web. They turned they turned the URL into a navigation box. There are a bunch of ads there that, you know, people click on. They don't even know they're clicking on ads. And, you know, they they generate a lot of revenue off of that. But let let's be clear. Google is firing at this. I just don't think it's gonna be as monopolistic as they are in search. I think there are going to be other competitors who are gonna be well financed, who are gonna have access to the data. And today, you have well north of a hundred million people who are paying to, you know, a huge percentage of those to use Chat TPT. And I think this you know, it's the 1st competition. But, you know, Friedberg knows he and I had the back and forth. They reported earnings. Stock was flat. I said on CNBC that we had sold our shares We bought back some of the shares around Google IO because we do think they're gonna be a player. We think they're gonna be a beneficiary. But I I would say as I sit here today, The distribution of potential for them is less than it was before chat GPT. you know, the the distribution of of upside. They have some competitors now who are going to be vying for this next new thing. And I wonder whether or not, you know, as they try to navigate, you know, you're saying they're gonna take some of this traffic from search and feed it into this other thing. This other thing better monetize as well as search. Or by definition, that means revenue goes down. Jason Calacanis (00:49:58): It feels like Google is so close to figuring this out. I mean, I I've been doing some barred searches. Brad Gerstner (00:50:03): Jake, how much Google do you own? How much Google do you? Jason Calacanis (00:50:05): Not enough. Not enough. See, I've just been playing with the j on myjtrading.com. Chamath Palihapitiya (00:50:09): He's thinking of adding this I think of adding, but I think Brad Gerstner (00:50:11): of it, like, $10,000. I'm Jason Calacanis (00:50:13): like a buy in or 2. But let's pivot over to this Reddit thing because it's super important that people understand this. I'm gonna buy 17 more shares. I'm gonna buy, like, a Harlan 2014 equivalent insurance. No. My j trading is up right now. jtrading.comshadows. to my trades. I did it as for fun. I'm at, like, a 20% return for 6%. Well, David Friedberg (00:50:35): Jake, you're kinda quiet for a while. So when you're down. You don't talk about it. And that's the thing comes up when you talk about it. Jason Calacanis (00:50:40): Like -- -- and I didn't wanna change them. David Friedberg (00:50:43): Do -- Track them and exit, or what do you do with track Jason Calacanis (00:50:46): the exits, but I haven't exited any. If you go to jtrading.com, you can play along. But -- Jacob, Brad Gerstner (00:50:52): how can you only be up 20% when Facebook has doubled. Jason Calacanis (00:50:56): Oh, sorry. Chamath Palihapitiya (00:50:57): 22.43. Brad Gerstner (00:50:58): Yeah. But Facebook doubled off the bottom. The whole goal of trading, Jakeow, is to maximize your highest conviction. To maximize your highest conviction, what do you do? Put a nickel to put 5% into Facebook? Jason Calacanis (00:51:10): I don't know. I just I just bought companies Brad Gerstner (00:51:12): as they went by in the group chat. Jason Calacanis (00:51:14): Would you talked about it on group chat? I made the companies. Brad Gerstner (00:51:16): You gotta put a lot of chips on the table. I mean, Jason Calacanis (00:51:19): you have that's, I think Chamath Palihapitiya (00:51:20): what's the optimal number? Jason Calacanis (00:51:22): As a day trader, Brad, what's the optimal number of names I Speaker 5 (00:51:24): should have. David Friedberg (00:51:24): You're not a day trader. You don't trade. Jason Calacanis (00:51:28): As a long trader, what's the optimal number of names I should be Brad Gerstner (00:51:32): in? You have too many. Okay. I think with your level of insight you know, on the things that you really believe in. There was such asymmetry in that position at the time that you bought it. It was your best idea You should have put at least 30% of of whatever you are going to allocate to this into that position. Jason Calacanis (00:51:50): That's what I'll do. Yeah. I mean, it's done okay. I mean, listen. I'm up. What did I buy? I bought 500 shares, and my basis is 47 and I'm at a Chamath Palihapitiya (00:51:59): 140. Jason Calacanis (00:51:59): So it's a good trade. Yeah. Brad Gerstner (00:52:00): Now imagine if you could, you know, 10 or 20 x that? Yeah. Jason Calacanis (00:52:03): That's what I should have done. Yeah. Alright. David Friedberg (00:52:05): Jason, how how wait. Hold on. How much have you put into all those stocks? Chamath Palihapitiya (00:52:07): 1,500,000. Jason Calacanis (00:52:09): I I basically I had some money in an index fund laying around, and I was like, let me do this. Chamath Palihapitiya (00:52:13): 1,500,000. Jason Calacanis (00:52:14): I did J Trading as a blatant attempt to get a sponsor for this weekend start ups. So I was like, oh, maybe Robinhood or E*TRADE will sponsor this and make it like a segment. Oh my god. Chamath Palihapitiya (00:52:24): So -- So I Jason Calacanis (00:52:24): was like, can we do like a segment where I trade and see if I can secure the bag? And it you know, the markets are so crushed that nobody is spending advertising from Robinhood or e trade or interactive brokers or Bloomberg. But I I also did because I wanted to become better at public market trading to your point to last week's conversations a month is under understanding when to sell and when to go long when you get distributions as a VC. That was really the reason I tried to do it was just to try to have skin in the game. You know, just like learning to play PLL or you playing the RAS tournament. I just wanted Chamath Palihapitiya (00:52:55): it's very it's very easy. Once you get shares distributed to you, immediately sell them. And then -- Yeah. -- and then hold on. Yeah. And then re underwrite from scratch from there. Okay. Once the money is sitting in your account, Even if it takes a day, a week, a month, it's not like the stock's gonna rip and triple on you over the next 30 days. Reunderwrite it from scratch. And then see if you have that much conviction when you see the money in your bank account. Jason Calacanis (00:53:22): I like it. Brad Gerstner (00:53:22): I would just tell you guys, the distributions, you know, there were a a lot of firms that wrote, you know, a lot of these big names, right, all the way down, You know, they they they got public, but they didn't distribute much, if any. And it's really Chamath Palihapitiya (00:53:41): Don't say the names, but what do they rhyme with? I'll I'll I'll start. I'll start. Brad Gerstner (00:53:46): But what's my -- Go ahead. Chamath Palihapitiya (00:53:48): You go you go next. You pick 1. Brad Gerstner (00:53:51): Not doing it. Chamath Palihapitiya (00:53:52): Bliger. Bliger. Okay. Andresen, Jason Calacanis (00:53:56): Horowitz. Mounders Lund. Chamath Palihapitiya (00:53:58): Look at free breakfast drop. boss. Jason Calacanis (00:54:00): Sorry. I was Speaker 6 (00:54:01): like, I Chamath Palihapitiya (00:54:01): don't wanna be associated with this conversation. Alright. Listen. We all got our asses kicked Jason Calacanis (00:54:06): except for me. Uber's up. Chamath Palihapitiya (00:54:08): 67% Jason Calacanis (00:54:08): this year. Brad Gerstner (00:54:09): Oh, come on. Come on. Let me what what I was gonna do what David Friedberg (00:54:12): I -- -- Blorowitz. Chamath Palihapitiya (00:54:13): -- Brad Gerstner (00:54:15): All of what tends to happen is they hit the bottom, they bounce a little bit, and people are so relieved that they bounced a little bit, that they immediately start distributing because LPs are hammering them. LPs are like, why did you not send us this? You know, Snowflake when it was at $400 a share. Why didn't you not send us this DoorDash? Why didn't you, you know, go through any name, you know, that you can think of. But then people compound the mistake, I think, that as soon as they get a little relief, boom, it's out the door. And then the thing doubles on them. And I just think, you know, part of the benefit of me having to get up every day 5 AM deal with public markets and think about longer short. It's what we're talking about in the fall of 2021 around the table before the poker games, which is The public market is tilty. It doesn't feel good. And that, you know, we stopped making venture investments in October of 21. principally because of how we felt about public markets at that point in time. And so I think a discipline in fact, I was meeting with a managing partner of a very big venture firm in Silicon Valley this week. They just started about a year ago or 6 months ago doing public market investing, and they said it was readily valuable to how they think about distributions and what they're doing in the venture business. Jason Calacanis (00:55:37): That's what it's been for me. I have now started to learn how these things are and I just think it's great as a learning thing for me, I have to make 2 decisions. 1, to distribute to my LPs, which I just give them the shares the second I have them and let them make the decision. But then it's also personally for me. Speaker 6 (00:55:51): Do I Jason Calacanis (00:55:51): wanna hold it or do I not? I like your suggestions. Nice punch up Chamath of looking at the cash and then deciding if you wanna reality or not. Chamath Palihapitiya (00:55:57): -- this crazy thing from Calpers where they were like Speaker 6 (00:56:00): Yeah. Speaker 5 (00:56:00): You know, Chamath Palihapitiya (00:56:00): they were they were down, like, 4 I mean, horrible returns on the venture side, and so their decision was to double down. Jason Calacanis (00:56:07): Well, they didn't have. They took, like, a decade off from venture. Chamath Palihapitiya (00:56:11): The returns of what they did invest in venture were atrocious. Brad Gerstner (00:56:13): To be fair, I don't know how the board is changed at Calpers. But Calpers brought in a a new CIO, an entire new team, and so they can't be held liable for you know, that track record. I did kinda see something on Twitter about I was shocked. It would be very difficult to manufacture that data track record if what I saw was accurate. However, I would say the team that is there now, the portfolio that they're putting together, and doubling down where I think Venture is kind of a the bottom or bottom third. And Chamath Palihapitiya (00:56:44): -- Jason Calacanis (00:56:44): Oh, this is the bottom, man. Brad Gerstner (00:56:45): I take and on bottom third, I don't know. Bottom half. You know? Listen, in Venture, you gotta find 3 things. You gotta find you know, you don't wanna invest all your money at the top. So you gotta get the bot you know, bottom third. None of us can call the bottom, but, you know, lack year, at the end of 22, we were certainly in the bottom third evaluations. Then you wanna be early in a major platform disruption. I think we all agree we're early in a major platform disruptions, probably the 3rd of our careers. And then you wanna back one of the best firms, best brands, the Silicon Valley. Like, if you do like, can people know who those are? If you do those 3 things, you know, simultaneously, like, you got a good of producing really incredible vintage. Jason Calacanis (00:57:25): Just to put some numbers on the Calipers thing so you can respond to it. It's not America's public, largest public pension, Calipers. That's California's manages some 444,000,000,000 in capital on behalf of California's 1,500,000 state school and public agency employees. is leaning into Venture. After years of bringing down its VC exposure to 1% to a 1% target, institutional investor is now looking to increase its allocation more than 6 fold, obviously, 6% from 800,000,000 to 5,000,000,000. The Financial Times reported. So that's not not your month? Chamath Palihapitiya (00:57:57): Well, I mean, this is the moment. There's a lot of venture firms that are hard up for money. And so They may have a shot. Jason Calacanis (00:58:04): They can get allocations now. Chamath Palihapitiya (00:58:05): In order to get into these funds, the problem that they have to realize is They may be buying a bunch of toxic assets or a bunch of toxic partners in the sense that a lot of these people have been getting run over for the last for your 4 years. We don't know. Again, we've said before, most venture investors are probably unprepared for the shock because they've never lived through 1. There's been a lot lot of junior marketing mux that were hired because they were x, y, z, middle level exec at random company. means nothing. So I don't know. I think it's smart that they I I mean -- They have to be thoughtful. -- picking managers. How is it that the like, literally, it's like Brad Gerstner (00:58:47): I know. It's incredible. Chamath Palihapitiya (00:58:49): of dollars being made in your backyard and some genius was like, well, the thing that's creating all the wealth in the world, which is in our backyard, where we probably have the best pitch in order to get into this one. We're gonna have a jack. -- 1 Brad Gerstner (00:59:00): And you just called Del Leonie and say, hey. Chamath Palihapitiya (00:59:02): Oh my god. Brad Gerstner (00:59:03): Give me the list of 10 and put money on those 10 and call it a day. Chamath Palihapitiya (00:59:06): Oh my god. That's unbelievable. Unbelievably, Darrelick. that's unbelievably -- Yeah. -- sloppy and emotional. I don't think you sorry. That's it. Sorry. Let me just finish. Brad Gerstner (00:59:16): That's Yeah. Chamath Palihapitiya (00:59:16): Actually, that's the best word to use. When you look back on a decision like that, there's no numerical justification that one could have made in the 2000 teens to have made that decision except that that was an emotional decision. And when you're running a half a $1,000,000,000,000 fund, there is no room for emotion. You should not be allowed. There should be some So I think that that shows a very hollowed out and at a minimum, embasilic risk management infrastructure at Calpers that needs to get fixed. So whether the allocation goes up or down, if I was a teacher and my money was being managed by them, I'd say, man, these people, I would wanna understand how they're making decisions because I don't I would wanna see the investment memo that got them to decide as an investment committee that 1% in the most important asset class that's in your backyard that's making all the money in the world made any sense. I just wanna read that memo and see, could I agree with that? Because then Jason Calacanis (01:00:14): I would do one of those is so important. Chamath Palihapitiya (01:00:16): Hold on. Then I would wanna read the investment memo that says we're gonna change course and get back to 5 or 6%. Because if that process isn't fixed, these decisions are just going to be equally bad. You're just gonna compound bad on top of bad. Because, again, they clearly did a terrible job. And then on top of that, they had horrible partner selection because the people that they did invest in, because the data is public, have performed horribly So what changes now all of a sudden? Right? Because if the best firms still don't want you in, increasing it from 800,000,000 to 5,000,000,000 just means you're gonna 4,200,000,000 more than you would have otherwise at 800,000,000. Jason Calacanis (01:00:54): Says here, they made 2 bets. They had bet on looks like light speed in the last couple of years, light speed and TPG. So we'll see how those go. That'll see 2020. Those Chamath Palihapitiya (01:01:06): I do have I do I do have I Brad Gerstner (01:01:07): do have some data on this because we've spent a lot of time talking with them. And as you know, Jason, we were just talk you know, like, talking to folks like Mubadala who I I Yep. Yeah. California is one of the largest sovereign wealth funds in the world. Right? This is not just the state. This is bigger than most countries. Right? This is one of the biggest economies in the world. I would say that what my interactions with the new team have been very impressive, and I will tell you they're not just looking funds and building a new portfolio, I think they are thinking about doubling down at the right time, and they're thinking about thematic bets against super cycles like AI to say, let's allocate this much money. Who are the 3 or 4 deep strategic partnerships that we can have? to drive, you know, return on that. So I I I think it's I I think they're on their way, but I I agree with you. They're the sovereign wealth fund of the most prolific state in the world. they should have outsized returns, not trailing reports. Jason Calacanis (01:02:04): I just wanna point out one thing here is the power of writing. Chamath, you decided to write your annual letter a couple years ago. Brad, you also will write a letter. Famously, the Facebook getting fit 1 or the meta getting fit 1. The power of writings and and I just did this for the launch on Chamath Palihapitiya (01:02:19): 4. Jason Calacanis (01:02:20): And when you write a deal memo, compare it to doing a deck, the questions you get are so qualitatively different and the people you tracked are so different. It is extraordinary. I am advising startups across the board to write really tight deal memos because I write these we write these deal memos internally when we make an investment. But, man, is it great for clarity of thought? And for the person on the other side to just stop and read a 1000 words or 2000 words as opposed to go through some stupid performative deck. It it's just so such a better process. Maybe you could you both could speak to that or a free break. I don't know if you're you've been writing deal memos. But maybe for people who are listening were capital allocators and founders. Chamath Palihapitiya (01:02:59): I've been writing for years. Jason Calacanis (01:03:00): why and what is the what what does it what does it do for you? Chamath Palihapitiya (01:03:04): Yeah. Well, it allows you to actually find people who will critique things in a thoughtful, intelligent way. It's hard to critique decks because you use broken English. You use fancy graphics. all of a sudden somebody that's very good at like graphical layout can dupe somebody else. And so you don't get to good outcomes because This weird group think effect sets in when you look at decks. So I'm not a fan of decks. I I use them, but they need to be a companion to some sort of long form narrative document. And I just think it's more useful. You get people who can really think about what they agree about, what they don't agree about. It shows the intellect of the person writing it quite honestly. I just think it's a it's like a basic skill that people should have. It's a useful skill to teach people as well. Dex are very dangerous, I think. If you're gonna make decisions, I would encourage you the bigger the decision. A deck is insufficient. It can be a companion piece, but it needs to be attached to long form documents. But the long form documents don't need to be long either. 2, 3, 4, 5 pages. But without it, I think you're gonna allow some really bad decisions to creep into some good ones. Jason Calacanis (01:04:12): Friedberg, any writing from you? For deals? Okay. Speaker 6 (01:04:19): Do you Brad Gerstner (01:04:19): have he Jason Calacanis (01:04:21): ran. talk about writing. Alright. As everybody knows, Reddit is on Strike right now. I should say the mods who run Reddit are on strike. 90 5 percent of Reddit went dark. They basically turned off new posts, or they just went private, basically. Nobody could join. Nobody could see the content. I believe is what that me means between Monday Wednesday. And the reason they're doing this is because Reddit decided it would start charging for its API. So who gets impacted by using the API? It turns out apps. We saw this at Twitter as well when Twitter started changing its pricing for its API. And this means that some of the really high end Reddit apps would have to pay $20,000,000 a year for access to Reddit's data. Now they originally had said they were changing this pricing because they were gonna train AI models. And they wanted anybody using that data, i e, Google Bard or Chat CPT 4 and closed AI. They wanted them to pay for it. And Steve Hoffman was explained to all this in the New York Times profile in April. You can go search for that. Reddit wants to get paid for helping to teach big AI systems. The largest app is called Apollo. Just so you know, if you're if you're not into those, really came out with their app really late. This was a function of the 2005 to Chamath Palihapitiya (01:05:36): 2015 Jason Calacanis (01:05:37): time frame back then. web 2.0 startups didn't have a lot of capital, so they let other people build on their APIs and build apps. Some of those apps caught steam and are actually better then the apps developed at least for a while. It was better than the Twitter app and the Reddit app. So thoughts on this, Friedberg, There's a history here David Friedberg (01:05:58): is mimicked at both Facebook and Twitter, both of whom had open APIs that provided access to 3rd party app developers to build tools on top of the platform by accessing either user data or content off of the network and then making that available via some different product functions, some different UI than the native tools allowed. if you'll remember Facebook started to kill off its API and in the process killed a number of these third party app developers, the the most prominent of which was Zynga, I think this is around the 2012 time frame. You guys know if I'm right on that? I think it's right. Brad Gerstner (01:06:34): Sounds right. David Friedberg (01:06:35): And, you know, we saw the same thing happen in in Twitter where if you guys remember in the early days, a lot of users accessed tweets from people that they followed through 3rd party apps and 3rd party apps all competed for the user. And, ultimately, Twitter's management team realized that having direct access to the user being able to control the UI, the UX, and not just become a a data network, but to actually become a a service for users made a similar sort of change So, you know, Reddit's motivation around AI training is is an interesting one, but it does speak to this idea that these social network companies social in the sense that the users themselves are creating the value. They're creating the content at both Facebook, at Twitter, and at Reddit. Ultimately, the company loses the value if that data, that content gets extracted and they can't monetize it or capture the value somehow. And it's a lot different. You know, every company ultimately wants to become a platform company, meaning that they can offer multiple products or services to users that sit on top of some, you know, network that they've created and in the process create a network effect because more products, more apps, creates more users, more users, begets more apps and so on. That works well in some contexts like an Apple App Store context. But in the context where there is a network unto itself like Facebook, Twitter, and Reddit, meaning that there is already a user network that is generating value in the form of the content that's being produced and consumed. You don't necessarily gain anything by then building an app network. on top of it. And I think that's been one of the kind of key learnings that's repeated itself over and over with Twitter and Facebook. The thing about Reddit, it's always been a community service. if you guys remember, like, in Chamath Palihapitiya (01:08:24): 2014, 2015, David Friedberg (01:08:26): Ellen Powell stepped down after there was a Reddit revolt. She was the CEO at the time. And she fired an employee at Reddit that ran the q and a site for Reddit's mods and their users. And the network, the community was super pissed off when this happened, and they all revolted. They were gonna shut down the service. and ultimately, Ellen, you know, got removed from her role as CEO when this happened. So, you know, because so much of the value of Reddick isn't in the management team. It's not in the the work that the software engineers do that run the company. It's not the the VCs or the shareholders. The value of Reddit is inherent in the community. It's inherent in the individuals that build the content on that platform. And that community has convened many times in the past at Reddit to change the rules to say, this is what we want this community to become, and this is how we want this management team to operate. And so it's a really uniquely positioned business says a lot about how social networks in this kind of modern era are operating. It really speaks to how much of the value ultimately accrues to the shareholders in a business like this. when the users themselves can step in and unionize and say, hey. You know what? We're not gonna allow this much value to be pulled out of the network in this way. We want this to change. So I think it'll it'll have a lasting effect in terms of investing in social network or social media type businesses where the users are generating so much of a value and have the ability to kind of communicate with 1 another and control where value ultimately falls. Jason Calacanis (01:09:48): Tremath, you were at Facebook, I think, when Zuckerberg realized enabling a bunch of folks to use the API wasn't as good as controlling the user experience, having a uniform user experience, and it got deprecated. And I remember Zynga and a bunch of other people had games and were sucking users the platform. There was a LinkedIn competitor at one point that was growing at an incredibly violent pace. And I guess y'all made a decision We don't want you sucking our user base off the platform. Maybe you could expand on what the decisions were at Facebook at the time. Chamath Palihapitiya (01:10:20): That was one of the things I ran, I think. One of my teams was responsible for Facebook platform. Yeah. It was just a very clinical decision around enterprise value. Look. The the thing with Reddit is that it's a hot mess. And in order to try to create enterprise value, they decided it to really leverage the mods so that there was some level of control And that control was necessary so that they could basically sell ads. That's how this thing moved in lockstep because the minute that there was corporate venture investors and other investors and a need to generate enterprise value? And is it worth 2,000,000,000 5,000,000,000 or 10,000,000,000, whatever the number was that they thought they were worth, they had to make money. Right? And Huffman was very straightforward about that and wanting to go public and the whole nine yards. But because it was such a hot mess, the mods became this integral part of the ecosystem so that they could actually drive reasonable revenue. But then what happened was it also allowed them to basically take over. And I think that it was a pretty significant miscalculation because I think that what they needed to do was really redefine the economics of how revenue generation splits would work before they could do all of this stuff to try to monetize the APIs. So I think like they got the order of operations wrong. But I also think it's very fixable, and I think that they have some very smart people around that table. So as long as they're again willing to be clinical and unemotional like we were, They'll get to the right answer, which is give them a healthy rev share. That's the future. Friedberg, you know, what version of what Friedberg said is true. The content creators need to get paid. You know, you see content creators now on YouTube making tens of 1000000, 1000000 and a few unique cases, billions. And then we are all content creators yet most of us on these old legacy platforms make nothing. So that ex that exchange has Jason Calacanis (01:12:25): to change. Brad, any thoughts with us to derail the IPO? Brad Gerstner (01:12:27): Not on that, but, I mean, I think, you know, you bring up this thing about Meta. you know, did anybody pay attention to, you know, Zuck's launching Project 92. Right? And Project 92 is gonna take on Twitter It's a text based social network that's gonna pay creators, and they're courting apparently, Oprah Winfrey, the Dalai Lama, and all of their creators that are already on their current sites are saying we will use this thing to interact, and we will compensate you. And then on Lex Friedman's podcast, He mentioned something about, you know, having been inspired a little bit by what was going on with Blue Sky. So I'm super intrigued. You know, you talked about it at this all hands meeting. I think Chris Cox talked about it. So it looks like Meta may be revisiting some of these things that she shelved a while back. You know, it doesn't have any direct implications on the Reddit front, but I think there's a suggestion here that it may be more about putting the control back in the hands of the user from a data perspective and a monetization perspective. That would be a pretty gangster move, you know, an an interesting way to leverage the platform, and I don't really hear anybody talking about it. Jason Calacanis (01:13:45): there's a really easy solution here for Reddit. Those mods, most of them do it for fame, glory, and affiliation community. But if some number of them wanted to monetize their activity there, why not allow people to subscribe to subreddits and pay a membership fee? and split it with the mods. That that seems like it would be a high scale move, adding Patreon, you know, subscription services to let them make a little bit of money. And then with these it's only 3 apps that are being affected. They should just either buy those apps and then bring those teams internal or David Friedberg (01:14:19): I think it's not a webcast. Chamath Palihapitiya (01:14:20): -- Jason Calacanis (01:14:20): split revenue with those apps. They could tell those apps that Chamath Palihapitiya (01:14:22): -- That's the key issue. It's like it's like if you're gonna try to monetize APIs on user generated content, I think What's happening here is the Internet is saying, okay, that's enough because we're gonna leak our activity someplace else where we can directly monetize it. So that's the whole point, I think. In this current version of the Internet, the value is gonna go and, again, further further further erode away from these centralized apps and more towards the individual people or in this case these hubbard spokes, these mods, and not to the centralized organization that that has the housing, the Reddit, the Facebook of the world. So that's just the trend that's happening, the Instagrams of the world. And there's nothing wrong with that. YouTube as well. It's just where the pendulum is swinging. So I think that Reddit just has to cut them a deal. Jason Calacanis (01:15:10): Pretty easy to do. Speaking of AI funding, there was a breaking news story just in the last 48 hours. A startup mean, MISro AI has raised a 105,000,000 seed round. They're calling it. should be at about a 240,000,000 valuation according to reports. 1 of the cofounders is a deep mind researcher. I guess people were saying this is insane because they haven't written any code yet, and they've been working on the company for Speaker 6 (01:15:39): a couple Jason Calacanis (01:15:39): of weeks. Chamath Palihapitiya (01:15:40): -- why these rounds are so big is, I guess, that You have to buy all these h 100 and they're expensive, and these rigs are very expensive. I mean, you guys saw this that Matt Friedberg basically published that He spent $75,000,000 on a bunch of hardware. And if you were one of his portfolio companies, you could use it. So getting these h 100 and a100s to train on seems to be a nontrivial task. And so and they're very expensive even if you can't get a hold of them. So I think what we're talking about is basically that these rounds have to go up. My and because if you notice, like, the the post You had to raise the post so that it wasn't so utterly dilutive as to completely disincentivize the employees, but let's speak honest here. Nobody's writing a $105,000,000 seat check. That a $105,000,000 is chopped up probably ten ways to Sunday. So there's a bunch of people putting in fives and fifties. I asked what people Jason Calacanis (01:16:34): in the round, and they said it was massively oversubscribed. Chamath Palihapitiya (01:16:37): Yeah. So I so it's everybody taking a little teaser bet. The problem with these teaser bets is they never hit in the way that you think. Maybe you'll get your money back with all the dilution that's gonna happen, etcetera, etcetera. This is not the way to make money, guys. I'm just gonna be honest with you. So whoever's putting money and thinking they know what the fuck they're doing, you might as well just light it on fire, go to Vegas and have some fun with it because you will make you'll get more enjoyment from that than you will for making these kinds of investments, Brad? -- Jason Calacanis (01:17:02): dumb. Stupid. Stupid bat? Brilliant bat? Brilliant bat? Brad Gerstner (01:17:06): nothing to do with the company. Chamath Palihapitiya (01:17:07): Nothing to do with the company. Nothing to do with the idea. I'm gonna Jason Calacanis (01:17:10): say, just talk about -- When when Chamath Palihapitiya (01:17:11): you're betting 4,000,000 in a $105,000,000 round at 240 posts, you do not know the fuck you're doing? That is not the job. Brad Gerstner (01:17:19): So, again, mister there gonna be a couple monster rounds, I think, announced next week. like, that are gonna make this one look like kids play. So a lot more of this is coming. You're exactly right. This is about buying h 100 and compute. Everything we're talking about, right, an essential ingredient is compute, and it's a scarce resource. Chamath Palihapitiya (01:17:40): My god. These people that put the money in the seat round should have just bought NVIDIA. That's a call option, so I can make more money. Jason Calacanis (01:17:46): Well and there's downside protection because NVIDIA has a a floor. Chamath Palihapitiya (01:17:50): And, by the way, because just in case Mistral doesn't work, NVIDIA will sell those h 100 to somebody else? The reason about it. Jason Calacanis (01:17:56): Yeah. They probably have the option to resell. Crazy. Brad Gerstner (01:17:58): I don't think you're right on these teaser bets. This is a power law business. There's a massive pressure on young junior partners, principles within these firms to do something. Chamath Palihapitiya (01:18:11): Fire them. Brad Gerstner (01:18:12): It it's not just keys or patch. What happens in these fires? Speaker 6 (01:18:16): Fire Brad Gerstner (01:18:16): them fire that -- -- get the logos because they need to explain to their LP. Chamath Palihapitiya (01:18:21): No. Actually, no. That's even worse. the GP that can't manage their fucking principle should be fired. Brad Gerstner (01:18:27): Right. And so Chamath Palihapitiya (01:18:28): I think I should those the the young people should shut the fuck up Okay. Be lucky you have a job. Learn the craft. It'll take you a decade. And if you are proposing stupid bets like this, Again, sizing matters. Again, I'm not talking about the company here. I'm just saying when you make a $5,000,000, $3,000,000 deal memo for a $105,000,000 round. That is stupid. Okay? And so if you're the partnership that allows those kinds of things to leak through, You don't know what you're doing. So at some point, somebody should be held accountable for this. And I guess what's gonna happen is the returns of calpers are gonna gate through everybody else thinking, well, at least I own some, you know, h 100 for a minute. Brad Gerstner (01:19:10): So let let me stipulate. I think this You wanna Jason Calacanis (01:19:12): take the other sidebar out of that? Brad Gerstner (01:19:13): No. This is just an incredible team that's gonna to do you know, this may turn out to be a fantastic bet for, I don't know, light speed or whoever led this round. Let me let me say something different. In in 1997, 98, we had a similar phenomenon. Everybody thought Internet search was going to be huge. There was massive, themo, and chasing. and everybody scrambled to get a search logo. Alta Vista, InfoC, Lycos, go plan it all, you know, geo cities. Just go through the lists, you know, that people were scrambling after. And the truth of the matter is almost all those companies went to 0, even though you got a couple of bets right. You got the Internet right. You got search right, but you didn't have to invest a dollar in search until 2003, and you would have captured 98.99 percent. Chamath Palihapitiya (01:20:02): Do it again. Do it again. Now social networking. Same thing. Do it again for social networking, Brad. Say all the names. Say all the names. Brad Gerstner (01:20:09): It's the same thing. Chamath Palihapitiya (01:20:11): Same thing. Speaker 6 (01:20:11): And Brad Gerstner (01:20:12): So, you know, when you when I look at it today, we have a huge anti portfolio for AI. it's painful. We've said no to over 60 companies. Right? We you know, but when we look around, I see a lot of our competitors doing a lot of these deals. Maybe their teaser bets. I don't really know the size they're putting into those companies. But I suspect that if we believe this is as big as as is going to be and gonna play out over decades, then putting a bunch of really small bets in order to buy a network or buy relationships or buy logos, etcetera. I don't think it's gonna work any better this time than it worked then around social networking. But to be clear, there are gonna be some people who lead these deals who help these companies build incredible businesses, and those will you know, there are gonna be some winners here. I think there's time to participate in the winners. Right now, a lot of this is unknown and unknowable. It will become more clear in the 1, 2, 3 years ahead. Chamath Palihapitiya (01:21:14): The problem is for the LPs. Like, if you are the LP, I am an LP and a bunch of venture funds. This stuff really turns my stomach because I'm like, wow. I am losing money every day. When I see these things, that's why I get so emotional about this. I think to myself, if the GPs that I've given money to are doing these kinds of deals. I'm screwed. At best, maybe I'll get back 50 or 60¢ on the dollar. And I immediately start thinking to myself I really need to write this down and I'm reunderwriting that person and that organization because I'm wondering how can you let these things happen? Because if you just look back in history, You have to be really, really negligent to not learn that these things never work out the way that you think they are, and especially these kinds of pounds in this nominal ownership, the inability to defend ownership. It's just not a a path to success. Jason Calacanis (01:22:03): I mean, also, if you think about this, Shamal, you know, what company in recent history that got overfunded actually used that money logically? The magic of Silicon Valley is the milestone based funding system. And whenever you short circuit that, this money becomes a huge distraction to founders. If they were to receive Chamath Palihapitiya (01:22:21): 10,000,000, 25,000,000, Jason Calacanis (01:22:22): work for a year or Chamath Palihapitiya (01:22:23): 2, Jason Calacanis (01:22:23): then raise another 25 or 50,000,000. They don't need to raise all this money at once. This is like taking your ABC round, putting it all Chamath Palihapitiya (01:22:30): in 1. And Jason Calacanis (01:22:31): all it does is distract founders, and then everybody coming for a salary says, well, you got a 105,000,000 in the bank. I want $3,000,000. I want Chamath Palihapitiya (01:22:38): $5,000,000. What's the best example, guys, of a huge financial winner that raised these ginormous amounts of money. David Friedberg (01:22:44): What's the best example? Jason Calacanis (01:22:45): Free launch of a product, Chamath. There's no product here. Chamath Palihapitiya (01:22:48): What's the best example? Magic Leap, What is it? Jason Calacanis (01:22:52): Oh oh, of disasters that actually Chamath Palihapitiya (01:22:54): No. No. No. What is the best example of a great company quote? I'm putting great quotes. that raise these kinds of amounts so early in this like. Quibi. No, Brad. Do you have an example? Like, what's mean? What's mainline? Brad Gerstner (01:23:08): people who raise a lot of money over the life cycle like an Uber. Jason Calacanis (01:23:11): Oh, no. I'm not talking about that. They're talking Chamath Palihapitiya (01:23:14): three rashes Jason Calacanis (01:23:15): at once. Chamath Palihapitiya (01:23:15): What was your first seed check-in Uber? What was the total seed round? I can tell you what Facebook's was. It was $500,000. Jason Calacanis (01:23:22): It was 1.25, I think. Chamath Palihapitiya (01:23:25): k. Facebook's was $500,000. Jason Calacanis (01:23:27): Yeah. We need Speaker 6 (01:23:28): a lot Chamath Palihapitiya (01:23:28): of money later. We needed a lot of money later, but no. It's 5,000,000 sorry. 500,000 safe at 5 5 posts. Jason Calacanis (01:23:35): Here's another thing. -- a $5,000,000 valuation for Uber and 1.25, I think, wouldn't it? Brad Gerstner (01:23:39): Here's another thing. Everybody walks in and they say, well, I have to raise this much money. And as a no. This it's good. There's there's a circular logic. I have to raise this money because I have to have all this compute. And I say, well, okay. You gotta train it. You you know, we wanna have a vertically integrated model. We wanna train a model. I say, okay. So there's a huge upfront cost they're like, but I don't wanna take a lot of dilution. So I have to raise it at a really high price. And and so you say, okay. Well, that's a that's a challenge for you, not necessarily a good thing for us. And then they say, oh, and I if you ask the question, is this an ongoing they're like, oh, yeah. We're gonna have to retrain. Like, we're gonna have to continue to spend this money. And I'm like, well so if if if you're a software company, for example, and you say, well, what's my COGS? If all of a sudden you have an embedded COGS that's massive and recurring. Right? for your compute cost that we haven't had in the past. Then the revenue on the other side of that's gotta be a multiple of what a traditional software company might have. in order to get back to that set of economics. So I think there's this there's a scramble and understandably so. If you think the big win AGI or, you know, this autonomous agent that's going to, you know, be the top of the next funnel, that thing is gonna be worth a lot. But to me those are those are lottery tickets at this at this stage. Chamath Palihapitiya (01:25:05): Can I tell you a little secret? Here's a little secret. When you put in a $100,000,000 into a startup to buy compute, you are not buying whizbang next generation IP. You are subsidizing CapEx. And that is a job that many, many other people will do had a very low hurdle rate. And so it is a law of capitalism. that it could be the most incredibly innovative company in the world. But if you are offering money to them, to fulfill a low yield thing, you are just not gonna make a lot of money. When you put money into a start up that is there writing code to build groundbreaking IP, you own something that's really real. But that's because 80¢ on the dollar is going to core critical r and d in that point in time. And then they raise a lot of money at a lot less dilution when 80¢ on the dollar goes to sales and marketing. Then they raise a lot of even more money at an even smaller, smaller amount of dilution. You start to get to to scale. Internationally. So you start to see. Right? More dollars, less return. Right? You're you're owning less of the critical differentiation. So if if everybody is like, oh, it's so expensive for a compute. I need to raise a 100,000,000,000. Well, buddy, you know, that's like a leasing function. You know, you're you're you're like all of a sudden, like, the best VCs in the world have become like Comerica Bank. Jason Calacanis (01:26:42): Yeah. I mean, they could have done it with the same structure. Right? Comerica could have given them Chamath Palihapitiya (01:26:46): 50,000,000 Jason Calacanis (01:26:47): to buy these machines. And maybe they should. Chamath Palihapitiya (01:26:48): And Comerica and JPMorgan and somebody else should basically say, hey, you know what? Here's a lease line for your h 100 because I know they're worth so much, and I'll just -- Yes. -- write it at 10%. And and my point is that the fact that people don't understand this is why the money will get torched. I would love a critique that says, actually, Chamath, you're an idiot. I'm right. I know that that's happening, but here's why I still see it happening. David Friedberg (01:27:10): I don't hear any of that. Brad Gerstner (01:27:11): Here's the problem with that critique. Okay. So you asked, like, what are the biggest projects in history you know, around startups. Think about AWS. I don't know. They spent 400,000,000 probably in order to get AWS off the ground, but it it wasn't done by a startup. Right? You think about what Zuck's spending on the metaverse. It's not being done right by a startup. The truth of the matter is the hyper Chamath Palihapitiya (01:27:32): -- Can you go back to a p a AWS AWS was dogfooded on Amazon Retail -- Brad Gerstner (01:27:37): Of course. Of course. Chamath Palihapitiya (01:27:38): -- Jason Calacanis (01:27:38): and Oculus was done on Chamath Palihapitiya (01:27:39): Kickstarter and the Cash of Amazon Retail. fed the development of AWS. Brad Gerstner (01:27:44): Correct. My point is that when you think about what these hyperscaler are going to do. They're not gonna spend a 1,000,000,000. They're not gonna spend 10,000,000,000. They'll spend a $100,000,000,000, right, in order to be in this race. And so if you're backing a startup that says I'm going to build a better chat GPT. Right? Just like OpenAI discovered themselves, they sold Chamath Palihapitiya (01:28:03): 51 Brad Gerstner (01:28:07): per 50% of the company to Microsoft for a reason. They had to. They had to have the data and they had to have the compute. This is a nuclear arms race around compute, and so but I think it's Chamath Palihapitiya (01:28:18): -- This is insane. It's financially illiterate for someone to think that they are actually doing anything other than subsidizing CapEx when you're giving a $100,000,000 to a start up to literally buy chips and servers and rack and Jason Calacanis (01:28:32): stack up. about 40% of their equity. the other thing. This equity is so valuable. Why would you wanna give 40% of it when you could get an equipment lease and keep another Chamath Palihapitiya (01:28:40): 20% Brad Gerstner (01:28:40): of your account? David Friedberg (01:28:41): You you Chamath Palihapitiya (01:28:42): you can't. You probably can't get those Brad Gerstner (01:28:43): You can't give it to them. Jason Calacanis (01:28:44): If the VC's putting 50,000,000 instead of a 105, you don't think America would come on the back end with 25,000,000? Of Speaker 6 (01:28:50): course, Chamath Palihapitiya (01:28:50): they would. Brad is right. This happened in 98,992,000, where all of this money was getting flushed down the drain, going into buying data center capacity where remember even at Facebook, like, we were racking and stacking our own servers. And and then we then we ultimately got big enough where we actually built out our East Coast and data centers and data centers all around the world. But it was very expensive. And in that moment, again, all of those companies just lit all that money on fire. it they torched it. There was no remnant equity value for that capital. And I I guess I guess I'm just I'm just questioning, like, what does a GP think they're actually buying? Jason Calacanis (01:29:29): Well, 80 per if 80% of it's going to hardware, I mean, they're they're buying Chamath Palihapitiya (01:29:32): the other 20% things. buying chips? Jason Calacanis (01:29:35): I mean, it doesn't make sense. Chamath Palihapitiya (01:29:36): A chip that's gonna get obsolete. Jason Calacanis (01:29:38): I wanna make one point here. And, Freeport, I want I wanna get your input on this as well. It constraint is important for founders. And what the thing that I find really troubling about this is and putting this startup aside because crypto people also went through this for the last 3 or Chamath Palihapitiya (01:29:52): 4 Jason Calacanis (01:29:52): years where they were overfunded. How did that David Friedberg (01:29:53): turn out? Jason Calacanis (01:29:54): It was tens of 1,000,000,000 of dollars burnt of LP monies, people's retirements, and college endowments, and it's gonna be quite a postmortem. But look at you you invoked Meta. It's important for people who don't know this. to know that that was a kickstarter. Shout out to Palmer Lucky. He raised a couple of $1,000,000 in 2011, I think it was. On a kick starter, pre selling the devices. Right? Contrain makes for great art. Contrain makes for great startups. You need to have pressure on a startup. for them to deliver. You cannot give startups 5 years of runway and expect it's going to work. It just doesn't work. nevertheless. We've seen this movie so many times. Chamath Palihapitiya (01:30:35): But now we've gone through 18 months of nobody doing anything, I guess, in VC land. So folks on San Francisco are itchy. They wanna justify why they should still be drawing 2% on the full fund. They wanna try to show activity so that they can raise the next fund and continue to stack fees. Mhmm. And all of these sort of leads to these suspension of financial logic, but it gets replaced with financial illiteracy. which is why there's an optimal fund size. Right, Shamal? And this is why the people that pay the price are ultimately the LPs, and it may be the case that Calpers maybe actually avoids a lot of these pitfalls because by missing, yeah, they missed all the returns, but then they missed writing the mega follow on checks for all of these folks that they And then they would have torched Okay. Brad Gerstner (01:31:17): I'm gonna take the other side of that. Jason Calacanis (01:31:19): Go ahead, Brett. Brad Gerstner (01:31:19): I think it's nearly impossible to conceive that all of these bets that are currently being made are bad bets. I think it's a major platform disruption. But I you know, instead, I think the right way to think about it is it's about pacing. And if you're trying to if everybody thinks they're going to build the next Google, they're going to build the next autonomous agent that's going to sit on top of the funnel, that's gonna be worth a trillion, and therefore, they can burn a $1,000,000,000 training models. That's not like, we're not gonna have 10 of those winners. Okay? But at the same time, there's a lot of stuff getting funded that is in the application layer that is in the tool layer And these are not the big headlines that you're reading about, but these are really interesting businesses that are solving real problems in the software and tooling layer here, you know, in the smaller model layer, vertically oriented things around life sciences or you know, targeting, you know, financial services or things in the application layer, you know, like character.aietcetera. So I do think there are a lot of good things getting funded that will deliver real value, but I agree with you. The problem that There's a there's a second problem to this, Chamath, if you drop a 1,000,000,000 or 2,000,000,000 or 3,000,000,000 into something. you have not only a a product challenge, you have a distribution challenge. Right? We know all the hyper scalars are going to play. Google is going to play. Meta is going to play. And so you gotta compete and then beat them, and It used to be that you would say, well, if I get a lot of traction, they'll buy me. If I'm Instagram or WhatsApp, like, they'll buy me. Well, we have such a regulatory nightmare in Washington DC today. No hyperscaler can spend over a $1,000,000,000 to buy any AI company. Chamath Palihapitiya (01:33:11): Not even that 400,000,000 gift what is it Giffey? I know it was even led by that. Brad Gerstner (01:33:16): Unfortunately, in the United States today, we replaced mergers and acquisition, right, with copy and compete. Because we've said to hyperscalers, you're not allowed to acquire any of these companies. So the unintended consequence of the regulation in Washington is that entrepreneurs and founders and venture capitalists who might otherwise have had a good idea, built something with some traction. They can't find a home for it in the way, you know, that WhatsApp found a home or an Isn't that a good thing? Instagram. Jason Calacanis (01:33:48): Isn't that a Chamath Palihapitiya (01:33:49): good thing to come down with it? I just can say go public Jason Calacanis (01:33:51): and be independent? Is it better for the market? Brad Gerstner (01:33:54): presupposes that everything can become a big and profitable business. There are Speaker 6 (01:33:58): a lot Chamath Palihapitiya (01:33:58): -- -- Jason Calacanis (01:33:58): net net can Chamath Palihapitiya (01:33:59): -- Jason Calacanis (01:33:59): What is it better for names? Chamath Palihapitiya (01:34:00): -- Brad Gerstner (01:34:00): become a big and profitable business? No. on its own, no chance? Jason Calacanis (01:34:05): Well, it's still not a big umbrella. This is Okay. Brad Gerstner (01:34:07): So that's what I'm saying. Chamath Palihapitiya (01:34:09): So maybe it Jason Calacanis (01:34:09): should have died. I mean, maybe it's been kept alive. But, I mean, it it's bad Brad Gerstner (01:34:12): for them. Jason Calacanis (01:34:13): I think it's great that it Brad Gerstner (01:34:15): got it. It was it was innovative technology. Chamath Palihapitiya (01:34:18): It was yeah. Brad Gerstner (01:34:18): It you know, you you were able to to back it with some good funding, and I think what's coming is gonna be really exciting. But it took a really long runway, a lot of capital, a lot of intelligence in order to build. Unfortunately, we've killed that. So you have a 2 sided problem. We're spending more than ever to fund and start these companies and we, you know, have undermined a lot of the downside protection. Jason Calacanis (01:34:41): Friedberg. Your thoughts. So if David Friedberg (01:34:43): you look at how the capital is being deployed, if it's mostly being deployed to train models, then the question has to be, is there really a sustainable advantage that arises by being the first to train the models and then being able to persist an advantage by training new models from that Speaker 6 (01:34:59): foundational model David Friedberg (01:34:59): going forward. And the reason that that matters so much is because you have to really have a deep understanding if you're gonna invest a lot of capital here. you have to have a deep understanding for how quickly model development and training is accelerating and how quickly the costs are reducing. So something that cost like we we said, OpenAI spent $400,000,000 training models for for GPT Chamath Palihapitiya (01:35:23): 4. David Friedberg (01:35:24): If they spend $400,000,000 in the last couple of years, You could probably assume that doing the same trading exercise could be done for Chamath Palihapitiya (01:35:32): 5 David Friedberg (01:35:32): to $10,000,000 18 months from now to generate the same model. That's a, you know, 100 x cost reduction, and I'm just ballparking it here. But if that's really where things are headed, then does the $100,000,000 to train models today really make sense if training those same models can be done for $5,000,000 in 18 to Chamath Palihapitiya (01:35:51): 24 Jason Calacanis (01:35:52): Great point. David Friedberg (01:35:52): And that's where it becomes a really difficult investment exercise. And one that you have to really critically understand how cost curves are moving in AI. The same thing was true in DNA sequencing in the early days. And it's following, by the way, a similar cost curve is DNA sequencing, which is actually greater than Moore's Law, greater than a 2 x cost reduction every 18 months. We're seeing something much greater than that in machine learning right now in terms of cost reduction and model training. So, ultimately, the business model has to have some advantage that by being the first to market, you can then generate new data that gives you a persisting and no one can catch up with you. And my guess is if you get under the hood of the business models, it's unlikely gonna be the case. And it's very likely gonna be the case that you don't know when the market advantage will lie, when you will be able to kind of create a persisting moat, a moat that expands as you get more data and can train more And this is why it's so hard to invest generally in technology is because you don't know the point at which the market tips relative to the point at which the technology tips. So there's a moment where the technology gets so cheap. And then the market maybe adopts after the technology gets cheap. And at that point, it's a totally different game. Chamath Palihapitiya (01:37:02): Remember in the mid 2000 where we had memory shortages and we used to have to buy RAM, Yeah. I mean, it's just like it's all this stuff, and it's like if VCs are funding this stuff, just you just like like the equity on fire, guys. Not gonna be worth anything. David Friedberg (01:37:15): Brad's point is right, which is the question is what's possible now? Where can you build a sustaining advantage now? rather than go after big model development cycles where the cost curve is gonna come down by a hundredfold in some period of time in the near future, Is there a business model advantage you can build by being in the market first, building a customer base, accelerating your features, getting user feedback. And that certainly exists in the application and the tools layer as Brad is talking about. That seems like such a no brainer for disruption across many different segments, many different verticals, many different markets right now versus trying to compete further down the stack, where it takes 100 of 1,000,000 of dollars of capital. And in a couple of months, that 100 1,000,000 of dollars of capital can be replaced with 5,000,000 bucks of training exercise and and computer Chamath Palihapitiya (01:38:01): I take the other side of that? Yeah. All that coordination makes no money today. So to your point, when you cut the actual input cost by a hundredfold, the coordination cost goes from being 0 to being worth less than 0. Right? I don't see any money being made there either. And all the people that say, I'm sure there's gonna be some genius in the comments, but what about open source? it's like, what about it? Jason Calacanis (01:38:21): OpenAI also just gave an update on their cost structure for their API and They just dropped it 25 to 75%. Again, this is after the tenfold drop they did last year. David Friedberg (01:38:32): Play this out. A $100,000,000 of capital spent training today is a $1,000,000 spent doing training in 8 years. 3 years. Yeah. 3 years. 18 18 to 36 months, somewhere in that time frame is likely the the time frame. So why would you spend all this money today when an 18 to 24 month things are gonna get Jason Calacanis (01:38:48): so much David Friedberg (01:38:48): cheaper? Yeah. I think the further up the value stack you go, the more of an opportunity to truly kind of innovate, disrupt, and make more capital as possible. What happens in 24 months? So when you've made a bunch of Chamath Palihapitiya (01:38:59): $100,000,000 investments and they're all zeros, Jason Calacanis (01:39:03): You get fired maybe? Brad Gerstner (01:39:08): Unfortunately -- As David Friedberg (01:39:08): an investor came up, is that what you're asking? Jason Calacanis (01:39:11): At some point, you don't get invited to join the next fund. David Friedberg (01:39:15): Think about the alternative investment strategy with lots of capital where the cost curve is not coming down as quickly in terms of where that capital is being deployed. For example, building rockets to go to space or building infrastructure to transport power or building roads. You could raise a $1,000,000,000 to build a tollbooth system or or a port. Let's use a port a shipping port is a good example. You could spend a $1,000,000,000 to build a shipping port. It's not that the cost of building a shipping port is gonna come down by 10 x in 18 months. Chamath Palihapitiya (01:39:45): So it David Friedberg (01:39:46): makes sense to raise a $1,000,000,000 and build a frigging shipping port and charge people right to coming out VCs thought Chamath Palihapitiya (01:39:53): they were underwriting IP instead they're just actually subsidizing CapEx. It's Jason Calacanis (01:39:57): the craziest thing. It's the craziest thing. Brad, is this a problem of the optimal venture fund size that Fred Wilson talks about, that Bill Girly talks about, a lot of the OGs say, hey. Chamath Palihapitiya (01:40:08): 250, 400, 600,000,000. Jason Calacanis (01:40:10): There's an optimal size here for 4 or 5 partners in a venture fund to put money to work. Is this part of the problem right now, which also happened in crypto, is you had $1,000,000,000, $2,000,000,000 fund sitting around and and and different venture brand names. having 4 or 5 of these multibillion dollar funds burning a hole in their pocket and getting frisky over this, you know, Chamath Palihapitiya (01:40:30): 18 Jason Calacanis (01:40:30): month pause. And is this about optimal fund size, making bad debts? Brad Gerstner (01:40:36): You know, we have over a $1,000,000,000 fund. So if I if if if I take the other side of that, the people are gonna say you're talking to your book. But I don't think this is about large funds. I think this is about good and bad decisions. at the end of the day, some of these decisions will pay off. Like, for example Chamath Palihapitiya (01:40:52): -- Jason Calacanis (01:40:52): What's the largest bet size from a $1,000,000,000 fund that you've made or will make? Brad Gerstner (01:40:57): I think out of that fund would be a $100,000,000, most likely, but we may cross it over other funds and have, you know, bigger bets. certainly -- Would Jason Calacanis (01:41:08): that happen two or three times, though? Would you do it all at once like this, or or might it happen over, you know, a series a, b, c kind of situation where you build a position? Brad Gerstner (01:41:15): I I would say, you know, we're not writing I you know, we haven't written a $100,000,000 check into series a, and I don't think most of people to Chamas point that you're talking about are writing a $100,000,000 checks into those series a's, the mestraw round that you referenced, I imagine the lead check into that was maybe 50. maybe 50? So listen. Larger fund sizes enable you to participate in companies that require more capital, and and these companies do require more capital. So you may take the position that all these companies are going to 0. That's not my position. My position simply is that I do believe there is a bit of over exuberance that too many things are getting funded. Right? And it's, you know, like, the margin of safety, the margin of return being required, is probably lower than it should be, but there's no doubt out of this vintage in my mind that you're going to have some epic companies. Now I don't know if what Mustafa and Reed Hoffman are doing at inflection is, you know, building pie to take on Chat GPT and to take on Bart and to be the intelligent assistant. The ambition is extraordinary. The cost of compute is high, but the first mover advantage is also high. Right? because whoever secures this position, you know, Bill Gates said he's been playing around with it. It's one of his favorite agents or whatever. That's an interesting comment, I think it's pretty good. But I think Chad GPT is out in front in this regard. I think a lot of people are gonna try to compete for that space, but you know, I can't imagine that all these researchers leaving deep mind, right, are going to be able to compete for the most sophisticated model to answer general purpose questions. So I don't think it's the large fund size. I think it's just a lot of exuberance. to participate in what everybody perceives to be a massive platform disruption. I think that can be true just like the Internet was in 1997, and a lot of these bets can, you know, can and will likely go to Chamath Palihapitiya (01:43:19): 0. How great is America? You just rent other people's money. They pay you 2%, And then you're allowed to get exuberant yet keep your job when you lose it. God bless America. Jason Calacanis (01:43:30): Well, I mean, the the issue trim off is it takes 10 years to prove you're bad at this job. Poor David Friedberg (01:43:36): good. No. Chamath Palihapitiya (01:43:37): No. No. No. No. It takes 10 years to prove you're good. and it takes 20 to prove to prove that you can be consistently good and didn't get lucky. But in a few years, you can tell that somebody sucks. Jason Calacanis (01:43:49): Can LPs though? Chamath Palihapitiya (01:43:51): Well, I'm not sure that they get the visibility because when LPs interact with GPs, they're grind fucked for the most part. So I don't know probably not. But when I interact with them just as a peer to peer level and I see the deals that get done is pretty easy to understand that some people just suck. They don't know how to make money. I guess is the point, which in the job, that's the job is to make money. To consistently make money. Jason Calacanis (01:44:16): Okay, Brad. Take care. And let's go to science corner. Bill Gates wants to genetically modify mosquitoes. Is this fake news or real? David Friedberg (01:44:23): Incorrect fake news. Jason Calacanis (01:44:25): It's fake news. Okay. Explain. David Friedberg (01:44:29): The reference is from RfK Junior's tweet that he set out where he retweeted someone talking about this mosquito factory in Colombia. And this guy basically put out a tweet saying, oh, look. Bill Gates has a mosquito factory in Colombia. It's the largest in the world. 30,000,000 genetically modified mosquitoes are released every week into 11 countries. Because Bill knows better than nature, what could possibly go wrong. RFK Junior then took it upon himself to retweet and say, should Bill Gates be releasing 30,000,000 modified mosquitoes into the wild, part of the mentality of Earth as engineering object, what could possibly go wrong. So I really wanted to take issue with this. Because I do think that this is the sort of misinformation that both create scientific illiteracy and damages and impacts negatively some of the significant progress that can be made in medicine and in science. So I wanna speak clearly as to what is going on, what the science is behind it, why this is super important. And then we can speak philosophically if you guys are interested on kind of should we be doing this sort of stuff and why? So Chamath Palihapitiya (01:45:36): -- Jason Calacanis (01:45:36): What's real here? Like, what what are actual facts versus fake news? Maybe that's a good place to start. David Friedberg (01:45:41): The most common disease carrying mosquitoes are called Edas EJIPTIA. It's a species of mosquito that carry yellow fever, dengue, Zika, a number of viruses that obviously are pretty adverse to human health. Each year about 400,000,000 people are infected with dengue virus via this mosquito vector. 100,000,000 become ill, and 21,000 deaths are attributed to dengue. Globally, 200,000 cases of yellow fever each year, causing 30,000 deaths. These are pretty significant health concerns. And it turns out that in mosquito populations, not in this particular species that carry these viruses, But in other species of mosquito, there's a bacteria, a natural bacteria called Wabakia. And this bacteria exists in nature and sometimes these mosquitoes get infected with this bacteria, so they carry this this this bacterial bond. And this bacteria is really interesting because it causes what's called cytoplasmic instability in the mosquito cells, which actually makes the mosquito largely resistant to a lot of viruses. And there's a bunch of theories for this mechanism and why this is the case, but it causes the mosquito to not be able to carry and spread these viruses that are super adverse to human health. So number 1, there's a natural bacteria that's found in nature, and up to 40% of mosquitoes are already infected with it. Number 2 is it's not common in the the mosquito species that is common in these areas that are spreading these awful viruses to humans. And so there's been a project that's been going on now for 12 plus years where they're taking large amounts of mosquitoes and breeding them specifically to have this bacteria in the mosquitoes, and then they release those mosquitoes into the wild. And over time, The bacterial infected mosquito start to become a larger percentage of the population. And as a result, the vector of carrying these awful viruses into humans goes way down. David Friedberg (01:47:37): there was a study done in Indonesia where they took these Wolbachia infected mosquitoes, and they released them into the wild. And they looked at a population that was in a region where they released them in calculation that they didn't. In the releasing region where they didn't release them 9.4% of people ended up getting infected. with dengue fever. And where they did release them, only 2.3% were infected. So it was an amazing 75% reduction in the infection of people fight these mosquitoes. And so the whole point is just to kind of, you know, move the mosquito populations in a way without doing any sort of genetic modification, but by exposing them to this bacteria so that they don't carry these viruses into people. But, you know, because people Chamath Palihapitiya (01:48:19): -- -- Jason Calacanis (01:48:19): the nuance point there, Friedberg, the it's not genetic modification or it is? David Friedberg (01:48:24): It's not. I I just explained it's a bacteria And they just expose the mosquitoes. They're exposing the so that they end up getting infected with this bacteria. And then as they breed, the mosquitoes breed in this facility -- Got You you have to have 2 an infected male and an infected female for the offspring to have the bacteria. If you have an infected male, they're actually infertile. they can only fertilize an infected female. So unless you do this breeding work, you don't end up seeing this happen naturally in the environment where the Wolbachia starts to spread widely. Speaker 6 (01:48:53): Where is Jason Calacanis (01:48:53): the genetic modification misinformation coming from them. Or is that David Friedberg (01:48:57): also occurring? From from from the the presidential candidate, RFK Junior, who just propagated it. And so this is why I wanna make this point. Because this whole idea that, oh, should we be engineering the Earth? Let me just say something about engineering the Earth. Humans used to wander around the earth or proto humans did without access to food. And until we realized that we could plant a seed in the ground and grow crops, and started to engineer the earth in the form of farming, we did not have access to a reliable source of calories. Human ingenuity, human engineering, gave us the ability to do this, gave us the ability to feed ourselves. Similarly, humans got infected by viruses, by bacteria, by fungus, and died at a young age over and over again. And when humans began to engineer medicine and engineer unnatural substances, Because he makes this point, oh, should we be interfering in the natural world? What is natural is for people to get infected with viruses or bacteria and die. And if not for the advent of our engineering and our ingenuity and our ability as a species to create solutions through science, which allows us to do discovery, And then through engineering, which allows us to make solutions that solve problems that humans face, we would all be dead at a young age, and we would not have realized the progress that we've had as a species. So I really get ticked off when I see guys like Rfk Junior and others not just propagate this this BS misinformation spiel about, oh, genetically modified this and that science is bad. But to then say, should we be messing with the natural world? because I would say to him, what about when your kid got infected? and you gave your kid antibiotics. Maybe you shouldn't have done that. And this notion Jason Calacanis (01:50:31): that -- -- group of people who are saying that you shouldn't do that. Right? There is a movement to stop taking antibiotics because it's making Yeah. Because it's it's having a a sudden negative impact. David Friedberg (01:50:40): I'll tell you a couple things. There are bad pesticides that impact human health and cause damage to our DNA. There is bad sunscreen that is endocrine disruptors and can damage human health. There are plenty of chemical products that are made that we use in everyday products that cause cancer. there is an endless string of things that are wrong with the system of engine the systems of engineering that we do use. That doesn't mean that they're all bad. that doesn't mean that we then say, hey. You know what? Let's not do anything. Let's not do any engineering. Let's not use any antibiotics. Let's not use Chamath Palihapitiya (01:51:12): any technology. David Friedberg (01:51:14): in food. And that's the challenge is, you know, getting into the details on like, I'll tell you, I don't use any sunscreen products with myself or my care. I only use Zinc. And I have a similar sort of nuanced approach to understanding what things we should or shouldn't use in our lives because of Chamath Palihapitiya (01:51:28): the data on the side David Friedberg (01:51:29): of that Chamath Palihapitiya (01:51:30): Can you please explain that? Because I didn't know this. What am I doing am I gonna what? Explain. David Friedberg (01:51:35): Yeah. So there there's a number of substances which are known endocrine disruptors that are found in sunscreen. I think it's like one of the craziest things that we haven't made these products illegal at this point. But the only sunscreen that you should use is natural mineral sunscreen. This sorry. I shouldn't say that you should. I should say this is what I chose. choose to do. Based on the data that I've seen, what's a good brand? What brand? Any brand that Zinks just Zinc sunscreen. Just look at the back If there's anything but zinc in it, don't use it. Jason Calacanis (01:52:03): Zinc oxide. Is that David Friedberg (01:52:05): what it's referring to? -- totally. Exactly. Zinc oxide Jason Calacanis (01:52:09): sunscreen? Yeah. Oh, that's David Friedberg (01:52:12): the ingredient in it. Speaker 6 (01:52:13): So I don't know what you guys Wow. But David Friedberg (01:52:19): here. Let me just send you this. Speaker 6 (01:52:20): But are Chamath Palihapitiya (01:52:20): are you saying that you're not allowed to have any other ingredient? Like, there's no stabilizers. There's nothing else? David Friedberg (01:52:25): No. No. That like, it's it's it's the stuff -- -- principle Chamath Palihapitiya (01:52:28): ingredient has to be zinc oxide versus some other chemical you're saying. David Friedberg (01:52:32): Yeah. So oxybenzone, I don't use any product with oxybenzone. That's, like, the most common sunscreen ingredient octinoxate is the other one, homo cellulite and the parabens. All of those product categories, which are the most common products used in sunscreen, They're absorbed by your skin. They go into your bloodstream and they're endocrine disruptors. Now the problem with the zinc sunscreen and the mineral sunscreen is it actually stays on your skin. you look like you're wearing it. It's really hard to rub it in. You gotta really, really rub it in. So they're actually not popular from a cosmetic point of view. People don't like wearing them because they look like idiots, and it's really hard to Chamath Palihapitiya (01:53:05): Yeah. That's the stuff I I use in the summer, the isdin. It drives me crazy because I look like this weird ghost -- Yeah. -- shiny ghost thing. I know. But I do use that. That's, like, really hardcore about that stuff. David Friedberg (01:53:17): That's an example of understanding nuance. Right? It doesn't mean all sunscreens are bad. And it doesn't mean that we shouldn't use sunscreen, but understanding what the risk factors are that are associated with different ingredients or different engineering that's been done to make sunscreens available is important, but that's so many levels deep. It's a really difficult thing. So then people end up being scientifically illiterate. and being wrong because someone like RFK Junior comes along and says, hey. Should we really be engineering the Earth with genetically modified mosquitoes? And then people have this called action, shut those things down, shut those things down. And they're incredibly beneficial and effective. They're not taking any sort of genetic editing to market. They're not doing anything that people might consider risky. And we could have a separate conversation about the risks and benefits of of genome editing. That's another topic. But Jason Calacanis (01:54:01): How much of this Friedberg Archima, as we get ready to wrap here, is a reaction to what happened with COVID 19 and people's fear now of and getting sort of educated on gain of function research and, you know, this sort of recency effect of my lord doing some of this science feels like it's too dangerous, certainly too dangerous to do inside the city. And what's the point of taking bats out of caves and and doing gain of function research. How much of it has to do with that right now? And it's a sort of the downside to questioning that. David Friedberg (01:54:32): Technology can can be asymmetric. You can have, like, nuclear weapons can wipe out the world. They can wipe out the whole population. Yeah. You know, Tala makes this point on his argument against GMOs, which I I would argue against him on this point, but we could do that another time. If he's willing to come from a list, Jason Calacanis (01:54:50): I'd be 2023. I'd David Friedberg (01:54:51): be super happy to debate him on this But the idea being that there's super asymmetric downside. And so, you know, what happens is people see incremental improvements from technology, and they don't really praise those incremental improvements. They assume that to be the case. It's a linear step function. But when something goes wrong, it's a big step down. And then people are like, oh, wow. And then people get scared of technology. then people wanna step away from it. And this is true in anything that relates to your health, to food systems, to the environment now. Now it doesn't mean that all technology is bad or all engineering is bad. But, you know, as mistakes are made in the system, as new things are discovered, we have to retrench and change what we're doing. But it doesn't mean that we should stop progress. And it doesn't mean that the whole system of humans figuring out how to engineer ourselves of the world around us, to benefit the health, to benefit the planet, to benefit other species on the planet, isn't a critical mission and effort that we should be undertaking. Chamath Palihapitiya (01:55:48): Well, the sunscreen thing is really tilting. I mean, I just I need to make sure I'm pretty sure we have a good one, but I don't Jason Calacanis (01:55:54): Yeah. I'm on this right now. I'm this has got me a little nervous with my kids. I I like these like, I I have all my kids have long sleeve sun shirts. And I try to -- That's what David Friedberg (01:56:05): I yeah. Yeah. Chamath Palihapitiya (01:56:06): -- Jason Calacanis (01:56:06): that I think is, like, the key thing and because I my family has skin cancer. Chamath Palihapitiya (01:56:10): Will I have to do that since I'm dark skinned, Friedberg? Jason Calacanis (01:56:13): I mean, do you want a white skin cancer? I mean, I I I I don't know why that's such a rash guard thing. You know? Chamath Palihapitiya (01:56:20): Yeah. You know, it's a summertime. You're in the bed. You know, you wanna show up there. Jason Calacanis (01:56:23): You wanna show up your -- Typical. Chamath Palihapitiya (01:56:24): -- Jason Calacanis (01:56:24): revenge body. I get it. I get it, Chima. Alright, everybody. On behalf of Saxx, let me just say Ukraine, Ukraine, Ukraine, Biden, Biden, Biden, Biden, Biden, and Francis. Mayor Francis is now in the race, so I guess we'll have him on the pond. David Friedberg (01:56:42): We've already talked to him. Jason Calacanis (01:56:44): Oh, okay. So David Friedberg (01:56:45): yeah. At the summit last year? Jason Calacanis (01:56:47): And, also, we're doing a survey for the podcast all in podcast.c0/survey. all in podcast.co/survey. If you got to this point in the podcast, please fill out our survey, our listener survey. and we will see you all next time on the all in pop. David Friedberg (01:57:05): Put your voice. Jason Calacanis (01:57:05): Bye bye. Bye bye. I love you. Best of luck. Speaker 6 (01:57:08): We'll let Speaker 5 (01:57:09): your winners ride. Speaker 6 (01:57:11): Rainman, David Sachs. Brad Gerstner (01:57:11): I'm doing all. Speaker 5 (01:57:12): And it said, open sources to the fans and they've just gone crazy with it. what airliners ride. Speaker 6 (01:57:28): Besty's our car. I don't think so. That is my dog, so you know, David Friedberg (01:57:33): driveway steps. Speaker 5 (01:57:36): Oh, man. Might have a casual media analyst. We should all just get a room and just have it be cute, George, because they're all just useless. It's like this, like, sexual tension, and they just need to release her now. What? Brad Gerstner (01:57:47): You're the VP. flirt Speaker 5 (01:57:49): your feet. What? Jason Calacanis (01:57:52): Where did you get Murphy's artifact? going all.