E99: Cheating scandals, Twitter updates, rapid AI advancements, Biden's pardon, Section 230 & more

0:00 Bestie intros! 1:34 Breaking down major cheating scandals: chess, poker, fishing 16:13 Twitter deal updates 30:05 AI making rapid advancements: Tesla AI Day, Meta's text-to-video tool, where this all leads 49:45 Biden pardons all prior federal offenses of marijuana possession 59:24 SCOTUS will hear cases regarding Section 230, common carrier, algorithmic recommendations Follow the besties: https://twitter.com/chamath https://linktr.ee/calacanis https://twitter.com/DavidSacks https://twitter.com/friedberg Follow the pod: https://twitter.com/theallinpod https://linktr.ee/allinpodcast Intro Music Credit: https://rb.gy/tppkzl https://twitter.com/yung_spielburg Intro Video Credit: https://twitter.com/TheZachEffect Referenced in the show: https://www.wsj.com/articles/chess-cheating-hans-niemann-report-magnus-carlsen-11664911524 https://twitter.com/Billyhottakes/status/1576246821139070976 https://www.bloomberg.com/news/articles/2022-10-04/musk-proposes-to-proceed-with-twitter-deal-at-54-20-a-share https://makeavideo.studio https://fred.stlouisfed.org/series/JTSJOL https://twitter.com/POTUS/status/1578097875480895489 https://www.vox.com/policy-and-politics/2018/12/22/18146338/marijuana-legalization-2018-win https://www.bloomberg.com/news/articles/2022-10-03/social-media-company-liability-draws-us-supreme-court-scrutiny

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00David Sacks?

  We're seven minutes in and we've produced absolutely nothing that will go in the show.

• 0:04David Friedberg?

  Here comes Sax waking up with his commentary.

• 0:08Jason Calacanis?

  When Friedberg is criticizing you for being too negative, you're in a dark place Sax.

• 0:12David Friedberg?

  I'm actually angry at Sax for not publishing my AMA from the other night.

• 0:15David Sacks?

  It's coming, it's coming.

• 0:16David Friedberg?

  While he publishes the vaults content.

• 0:18Jason Calacanis?

  His app crashed.

• 0:18David Sacks?

  We had such a crowded room. We had over 2,000 people in the room for like four hours.

• 0:23Jason Calacanis?

  It was crazy. It was like the original days of Clubhouse.

• 0:26David Friedberg?

  Everyone I know that was trying to get in was texting saying they couldn't get in. So it definitely capped out, right?

• 0:31David Sacks?

  I know. Well, we hit, we hit some scalability limits.

• 0:33Jason Calacanis?

  You may want to buy an extra server Sax, cheap [bleep]. Weren't you the same guy who was responsible for scaring PayPal?

• 0:38Chamath Palihapitiya?

  No, that was somebody else. That was eBay. They sold it before it scaled.

• 0:42David Sacks?

  No, that's not true. We had huge scalability challenges at PayPal too.

• 0:47Jason Calacanis?

  It seems like a theme.

• 0:48David Sacks?

  Yeah, the theme is when you have an app that's breaking out, you hit scalability challenges. It's called a high-class problem.

• 0:54Jason Calacanis?

  2,000 people is not a high-class problem. It's a trickle. It's 2022.

• 0:59David Sacks?

  2,000 people participating in the conversation is a challenge.

• 1:02Jason Calacanis?

  I haven't written code in 20 years. Here's what you do. When you get to 1,000 people coming to the room.

• 1:07Chamath Palihapitiya?

  That's a lie.

• 1:07Jason Calacanis?

  Everybody else is in passive mode.

• 1:09Chamath Palihapitiya?

  You've never written code ever.

• 1:10Jason Calacanis?

  Of course I have. Of course I have.

• 1:12Chamath Palihapitiya?

  That's a lie. Come on, be honest.

• 1:13Jason Calacanis?

  Oh yeah, it's actually been 25. The last time I wrote code was Lotus Notes. It's true.

• 1:34Jason Calacanis?

  So there have been three cheating scandals across poker, chess, and even competitive fishing. I don't know if you guys saw the fishing one, but they found weights and fillets during a fish weigh-in. And then everybody wants us to check in on the chess and the poker scandals. Chess.com just released their report that this grand master has been suspended. They have evidence he cheated, basically in a bunch of.

• 2:02Chamath Palihapitiya?

  Tournaments that were, in fact, for money, he denied that he had done that, but he had previously cheated as a kid. They now have the statistical proof that he was playing essentially perfect chess, and they have outlined this in like hundreds of pages in a report. Sax, what are your thoughts on this scandal in chess?

• 2:20David Sacks?

  Magnus Carlsen finally came out and explained why he thought Hans Niemann was cheating. Basically, he got the strong perception during the game that Hans wasn't really putting in a lot of effort, that he wasn't under a lot of stress, and it's his experience that when he's playing, you know, the top players, they're intensely concentrating, and Hans Niemann didn't seem to be exerting himself at all. So, his, you know, hackles were raised and got suspicious, and then, you know, he has had this meteoric rise, the fastest rise in classical chess rating ever, and I guess there were, he had gotten suspended from chess.com in the past for cheating. So on this basis, and maybe other things that Magnus isn't telling us, Magnus basically said that this guy is cheating. I think that maybe the interesting

• 3:04David Sacks?

  part of this is that there's been a lot of analysis now of Hans Niemann's games, and I just think the methodology is kind of interesting. So what they do is, they run all of his games through a computer, and they compare his moves to the best computer move, and they basically assign a percentage that matches, a correlation matches the computer move. And what they found is, there were a handful of games where it was literally 100%. That's basically impossible without cheating. I mean, you look at the top players, who through an entire career have never had 100% game. Chess is so subtle that the computer can now see so many moves into the future, that nailing the best move every single time for 40, 50, 100 moves is just-

• 3:45Chamath Palihapitiya?

  And, and, and in chess, which a human really can't do that well, is that there are positional sacrifices that you will make in short lines, that pay off much, much later in the future, which is impossible for a human to calculate. And so, you know, and you saw this, by the way, when, I think it was the, it was the Google AI, the DeepMind AI that also played chess. So, the idea that this guy could play absolutely perfectly according to those lines is only possible if you're cheating.

• 4:13David Sacks?

  Right, exactly. So there were a handful of games at 100%, and then there were tournaments where his percentages were in the 70-something plus. And so, just to give you some basic comparison, Bobby Fischer during his legendary 20-game winning streak was at 72%. So he only matched the computer for best move 72% of the time. Magnus Carlsen, playing at his best, is 70%. Garry Kasparov, in his career, was 69%. And then, you know, the Super GMs category are typically in the 64% to 68% range. So I think it's really interesting, actually, how you can now quantify by comparing the human move to the best computer move.

• 4:54Jason Calacanis?

  And it's multiple computers, right?

• 4:55David Sacks?

  Who's playing the best.

• 4:56Jason Calacanis?

  They actually have...

• 4:57David Sacks?

  It provides a way to assess who the greatest player ever is. I actually thought that was Magnus, but now maybe there's a basis for believing it was Bobby Fischer, because he was at 72 and Magnus was only at 70. However, look, the idea that Hans Niemann is in the 70s, 80s, or 90s during tournaments would be, you know, just an off-the-charts level of play. And if he's not cheating, then we should expect, over the next couple of years, that he should rapidly become the world's number-one player over the board, you know, now that they have all this anti-cheating stuff, right? So it'll be interesting to see what happens in his career now that they've really cracked down on, you know, with anti-cheating technology.

• 5:39Chamath Palihapitiya?

  I have a general observation, which is, these people are complete fucking losers. The people that cheat in any of these games don't understand this basic, simple idea, which is that trying is a huge part of the human experience. The whole point is to be out there in the field of play, trying. And it's basically taking the wins and the losses and getting better that is the path. That's what's fun.

• 6:04Jason Calacanis?

  Yeah.

• 6:05Chamath Palihapitiya?

  Once you actually win, it's actually not that much fun, because then you have this pressure of maintaining excellence. That's a lot less enjoyable than the path to getting there. And so the fact that these people don't understand that makes them slightly broken, in my opinion. And then, the other thing is, like, why is it that we have this strain of people now that are just so devoid of any personal responsibility? That they'll just so brazenly take advantage of this stuff. It's really ridiculous to me. They don't. It's really sad. These people are pathetic.

• 6:35Jason Calacanis?

  It's really pathetic. But it is really interesting how they caught him and running this against a computer. Here's a chart of his scores in these tournaments. Oh, here is this first chart is how quickly he advanced, which was off the charts. And then the second chart, that's really interesting, is his chess.com strength. So if you don't know chess.com, it has become like a juggernaut in the chess world, especially after that HBO series came out. A lot of people subscribe to it. I subscribe to it. I like to play chess there. And man, you look at the chess strength score there, he was just like perfect. And then the number of games he likely cheated in, you can see the last two columns. He's basically cheating in every game. Queens Gambit, yeah, great show on Netflix.

• 7:19Jason Calacanis?

  And he said he didn't cheat in any of the games where they were live streaming, but they've proven that wrong. Sax, how does he cheat in person then?

• 7:28David Sacks?

  Well, that's the thing. No one really knows. And I don't want to overly judge until they have hard proof that he was cheating. I mean, look, here's the thing. He was never caught in the act. It's just that the computer evidence, you know, seems pretty damning. And I don't know how they prove, I don't know how they prove that he was cheating over the board without actually catching him doing it. And I don't, I still don't think anyone really has a good theory in terms of how he was able to do that.

• 7:54Chamath Palihapitiya?

  Well, it's not just him though. Look, the fishing thing, Jason, which was crazy. I think Free Bird shared the video. This guy was in a fishing competition and they basically caught these fish and then they put these big weighted pellets inside the fish's body. They even put like a, you know, chicken breast and chicken fillets inside of the thing.

• 8:11Jason Calacanis?

  No, fish fillets. Yeah.

• 8:13Chamath Palihapitiya?

  Fish fillets, you know. Then there's in poker now, in poker, in poker, everybody's afraid that there are ways in which you can read the RFID in some of the cards and some of these, you know, televised situations and front run what the, what the playing situation is so that you know whether you're winning or losing. And again, I just asked the question like, is it, is it, is this, are things that bad? That this is what it gets to? Like, we all play poker. The idea that we would play against somebody that would take that edge.

• 8:43David Friedberg?

  Yeah, it's gross, yeah.

• 8:44Chamath Palihapitiya?

  It really makes me really sad. It's sad. So disappointing.

• 8:47David Friedberg?

  Yeah, it's horrible. One, one observation might be that across all three, because I'm trying to find some common thread across these, but it could be that there was a lot of cheating going on for a long time. And maybe the fact that we do have so much digital imagery that's live on these things now, and so much coverage, and everyone's got a cellphone, that suddenly our perception of the cheating in competitive events is becoming more tuned. Whereas maybe there's been a lot of cheating for a long time, and it's just kind of coming to light. I mean, we didn't have a lot of live streaming in poker. Who knows? I mean, we could probably ask Phil this, for cheating, but like, for how many years? Oh, there was tons, yeah.

• 9:32David Sacks?

  Well, there were tons of cheating in online poker.

• 9:35David Friedberg?

  Yeah, and high limit poker.

• 9:36David Sacks?

  Remember, like, people were using these, like, software programs that would track the hand history of your opponent.

• 9:44David Friedberg?

  Heads up displays.

• 9:45David Sacks?

  Yeah, exactly. So, so it'd help you assess whether the person might be bluffing in that particular situation. Like, it has superhuman memory.

• 9:52David Friedberg?

  So I don't know if you guys, I don't know if you guys watch Twitch, like, video games, like Fortnite or whatever, but there are, like, players that have been accused of using these screen overlay systems that basically more accurately show you and drive the mouse to where an individual is on the screen, so you can more accurately shoot them. And so there's software overlays that make you a better, you know, competitive video game player. Can I tell you what the through line is? And then the, the stuff basically became like, so now, what's interesting is now there's eye tracking software that people are using on Twitch streams to see if the individual is actually spotting the target when they shoot, or if the software is spotting the target to then reverse cheat them. They're aim bots. They're aim bots, yeah. Yeah, and like, reverse cheat the whole thing.

• 10:36David Friedberg?

  And I think what's interesting is just that there's so much, you know, insight now, so much more video streams, so much more, I mean, think about it, all those guys at that fishing competition, that all had cellphones, and they all videoed this thing happening. Yeah, yeah. Think, 10 years ago, that wouldn't have been the case, and there wouldn't have been a big story about it. And so... Schumacher said there was a theme you wanted to, uh, there was a thread.

• 10:54Chamath Palihapitiya?

  I, I think the theme is, is pretty obvious, which is that there's been an absolute decay of personal responsibility. People don't feel like there's any...

• 11:05Chamath Palihapitiya?

  downside to cheating anymore. And they're not willing to take it upon themselves to take a journey of wins and losses to get better at something. They want the easy solution, the easy solve, the quick answer, you know, uh, that gets them to some sort of finish line that they've imagined for themselves will solve all their problems. The problem is it doesn't solve any problems and it just makes them a wholly corrupt individual.

• 11:29Jason Calacanis?

  Yeah. Okay. So let's talk about this Hustler Casino Live Cash Game Play. There's this woman Robbie, who is a new player. Apparently she's being staked in a very high stakes game. She's playing against a guy Garrett, who is a very, very, um, known winning cash game player.

• 11:48Jason Calacanis?

  And it was a very strange hand on the turn. All the money gets in, she says she has a bluff catcher. Then she claims that she had a thought she misread her hand. Now people are saying that the poker world seems to be 70 30 that she cheated. But people keep vacillating back and forth. There was a lot of weird word salad that she said that she had a bluff catcher, which would normally be an ace. Then she said she thought she had a pair of threes and then she immediately said afterwards that he was giving her too much credit. They confronted her in the hallway. She gave the money back because she supposedly loves production. So all of this stuff sounds very weird. One side says, okay, all this is happening because she's a new player.

• 12:28Jason Calacanis?

  The other side is saying, somebody was signaling her that she was good and giving her just a binary. You're good, because if you were going to cheat, cheating with Jack high in a situation where you just put all in for a two hundred, a quarter million dollar pot seems very suspect. Uh, I don't know if you guys watched the hand breakdown. Where does everybody stand on a percentage basis, I guess, of if they think she was cheating or not? Cause we, this is not definitive, obviously. It's not like they cut it open and found the ball bearings.

• 12:55Chamath Palihapitiya?

  It's not, it's not so obvious in that situation, but I think the way that that line played made no sense.

• 13:02Jason Calacanis?

  Did not make any sense.

• 13:02David Sacks?

  She was holding a Jack four and I guess in her previous hand, she had a Jack three and there was a three on the board. So if she misread her hand for it.

• 13:12Chamath Palihapitiya?

  The board was 10 10 9 3. No, but you would have, but you would have, you would have had to call the flop. I'm thinking what?

• 13:17David Sacks?

  Yeah, no, I get it. The hand makes no sense, but I'm just trying to find a logical explanation.

• 13:22Jason Calacanis?

  And that Jack 3 explanation, somebody kind of fed that to her and then she changed her story to that. So this changing of the story is the thing I was sort of keyed on Friedberg is, why does she keep changing her story? Is it because she's embarrassed? Maybe she's had a couple of beverages or whatever? Or she's just a new player and she's embarrassed by her play and can't explain it? She can't explain the hand history?

• 13:43David Friedberg?

  All of the things you're saying are probable. I don't think that, yeah, I don't think there's any data for us to have a strongly held point of view on this. I'm just looking forward to us all playing live at HCL Poker Live, October 21st, minus David Sacks, unfortunately. Chamath, J Cal, Gersner, Stanley Tang, Phil Hellmuth, Alan Keating.

• 14:03Jason Calacanis?

  So we're going to be playing on the same stream.

• 14:05David Friedberg?

  We're going to be playing on the same screen, same table. I figured out how to hack into the video stream for the cards.

• 14:10Jason Calacanis?

  Yeah, no, I just got my RF to ID sunglasses as well.

• 14:13David Friedberg?

  I'm going to read all your shitty hands, J Cal. I'm going to take your money and I'm going to buy my kids some nice clothes.

• 14:18Chamath Palihapitiya?

  My, for my 40th birthday, Sky organized poker in Tahoe, okay? And, and we, we brought in the team from CBS. That was the present where, and they, they taped it as if it was being broadcast with hole cards and commentators and we edited it into a two day show. It was an incredible birthday present. I, I, it was, it's one of the greatest things that, that anybody's ever given me. I appreciate it. There was a one hour block where somebody at the table said, okay, guys, how about we do a cheating free for all?

• 14:48Jason Calacanis?

  Yes.

• 14:48Chamath Palihapitiya?

  Where you could look at each other's cards and you know, you could sort of help somebody else.

• 14:53Jason Calacanis?

  Switch cards, whatever.

• 14:55Chamath Palihapitiya?

  In that one hour, our beautiful home game of friendship became Lord of the Flies. I have never seen so much hatred, angling, mean behavior. Oh my God, it was incredible.

• 15:10David Friedberg?

  All that humans are capable of.

• 15:11Chamath Palihapitiya?

  So I, I hope that we never, uh, we never, we never see cheating in our game.

• 15:16David Friedberg?

  Yeah. Well, we'll see how it goes on October 21st at HCL Poker Live. I'm excited. I can't wait.

• 15:21Jason Calacanis?

  It should be a lot of fun. It should be a lot of fun. And we're not having any official 100 stuff, but the fans, some of the fans who were at the All In Summit 2022 are doing their own 100, episode 100 meetups on October 15, I think, all in meetups.io. So there are fan meetups happening in Zurich and a bunch of other places. I'm going to FaceTime into some of them and just say hi to the fans. You know, it might be like 10 people in a bar somewhere. I think the largest one is like Miami or San Francisco are going to be like 50 people or something.

• 15:54David Friedberg?

  We should all FaceTime in. That'd actually be kind of fun.

• 15:57Jason Calacanis?

  I'm basically, I told them, just send me an invite and I'll FaceTime in any, anytime.

• 16:01David Friedberg?

  This is next week? When is this?

• 16:03Jason Calacanis?

  The 15th, I think, is this occurring. Yeah, October 15th. It's a Saturday. The Saturday after the 100th episode, people are doing these all in meetups.io.

• 16:12David Friedberg?

  What's next? Earlier this week, it was reported that Elon contacted Twitter's board and suggested that they move forward with closing the transaction at the original terms and the original purchase price of $54.20 a share. In the couple of days since then, and even as of right now, with some news reports coming out here on Thursday morning, it appears that there are still some question marks around whether or not the deal is actually going to move forward at 5420 a share because Elon, as of right now, the report said, is still asking for a financing contingency in order to close. And there's a lot of back and forth on what the terms are. Meanwhile, the court case in Delaware is continuing forward on whether or not Elon breached his terms of the original agreement to close

• 16:56David Friedberg?

  and buy Twitter at 5420. As we know, leading up to the signed deal or post signing the deal, Elon put together a financing syndicate, a combination of debt investors as well as equity co-investors with him to do the purchase of Twitter at $54.20 a share. So the 40 some odd billion dollars of capital that's needed was committed by a set of investors that were going to invest debt and equity. And there's a big question mark now on whether or not those investors want to or would still consummate the transaction with Elon, given how the markets have turned and given how debt markets are trading and equity markets are trading. So Chamath, I'd love to hear your point of view on what hurdles does Elon still have

• 17:39David Friedberg?

  in front of him? Does he still want to get this done? And is there still a financing syndicate that's standing behind him at the original purchase price to get it done?

• 17:47Chamath Palihapitiya?

  It's a great question. Maybe the best way to start is, Nick, do you want to queue up what I said in August 25? The lawsuit really boils down to one very specific clause, which is the pinnacle question at hand, which is there is a specific performance clause that Elon signed up to, right? Which, you know, his lawyers could have struck out and either chose not to or, you know, couldn't get the deal done without. And that specific performance clause says that Twitter can force him to close at 54.20 a share. And I think the issue at hand at the Delaware Business Court is going to be that, because Twitter is going to point to

• 18:30Chamath Palihapitiya?

  all of these, you know, gotchas and disclaimers that they have around this bot issue as their cover story. And I think that really, you know, this kind of, again, builds more and more momentum in my mind that the most likely outcome here is a settlement where you have to pay the economic difference between where the stock is now and 54.20, which is more than a billion dollars, or you close at some number below $54.20 a share. And I think that that is like, you know, if you had to be a betting person, that's probably, and if you look at the way the stock is traded, and if you also look at the way the options

• 19:15Chamath Palihapitiya?

  market trades, that's what people are assuming, that there's a 7 to 10 billion dollar swing. And if you impute that into the stock price, you kind of get into the $51 a share kind of an acquisition price. Again, I'm not saying that that is right or should be right. That's just sort of what the market says. Yeah, so it turns out that, you know, sort of like that kind of guesstimate turned out to be pretty accurate, because the stock today is at $51 a share. So I think that the specific performance thing is exactly what this thing has always hinged on. And I think that there is a realization that there were very few outs around how that contractual term was written and agreed to. So there is an out in the contract, and that

• 19:57Chamath Palihapitiya?

  out says that, I think it's by April, if the deal doesn't get done by April, then the banks can walk away from their commitment to fund the debt. And if the banks walk away, then Elon does have a financing contingency that allows him to walk away. So the actual set of events that have to happen is those two things specifically. Get to April so the banks can pass and say, we've changed our mind, market conditions are different. And then Elon is able to say, oh, you know, the banks just walked away. Right now, the banks, if you look at all of the debt that they've committed to,

• 20:32Chamath Palihapitiya?

  well, they committed at a point in time when the debt markets were much better than they are today. In the last, you know, six or seven months since they agreed to do this, the debt markets have been clobbered and specifically junk bonds and a bunch of junk bond debt. The yields that you have to pay, so the price to get that kind of debt has skyrocketed. So roughly, back of the envelope math would tell me that right now the banks are offside between one and two billion dollars. Because they're not going to be able to sell this debt to anybody else. So I think the banks obviously want to way out. The problem is their only way out is to run the shot clock off until April. So I think that's the dance that they're in right now. Elon's trying to find a way to solve, you know, for the merger.

• 21:16Chamath Palihapitiya?

  I think Twitter is going to say, we're not going to give you a financing contingency. You have to bring the banks in and close right now. And then we will not go to court, otherwise we're going to court. And so I think it's a very delicate predicament that they're all in. But my estimate is that the equity is probably 20% offside. So it's not a huge thing. He can make that up because he can create equity value like nobody's business. The debt is way offside by a couple billion dollars, which is hard to make back, but I think in the end, you know, given enough time, they can probably make that back. The best off in all of this are the Twitter shareholders. They're getting an enormous premium to what that company is worth today in the open market. And so I think this deal is going to close, it's probably going to close in the next few weeks.

• 22:01Chamath Palihapitiya?

  And had you bought Twitter when we were talking about it in August, you would have made 25% in six weeks and, you know, if the deal closes at 54, you would have made, you know, a third of your money in eight weeks, which is, you know, very hard to do in a market.

• 22:14David Friedberg?

  If you're a GP at one of the funds like Andreessen or Sequoia, and you had made this commitment to Elon or even Larry Ellison a couple of months ago. Do you fight against closing at 5420? Do you stick with the deal and support him? I mean, what do you do, given that the premium is so much higher than where the market would trade it at today? Some people are saying the stock should be at like 20 bucks a share or something.

• 22:38Chamath Palihapitiya?

  The average premium in an M and A transaction in the public markets is about 30%. So, and I think the fair value of Twitter is around 32 to 35 bucks a share. So, you know, it's not like he is massively, massively overpaying. And so, you know, I would just sort of keep that in the realm of the possible. So like if you take $35 as the midpoint, fair value is really 45, 50. So, yeah, he paid 20% more than he should have, but he didn't pay 100% more. So it's not as if you can't make that equity back as a private company, particularly because there's probably $10 of fat in the stock. If you think about just OpEx in terms of all the buildings they have,

• 23:21Chamath Palihapitiya?

  maybe they don't need as many employees, maybe they revisit salaries. You know, one thing is when I looked at doing an activist play at Twitter, I think I mentioned this five or six years ago. One of the things that I found was at that time Twitter was running their own data centers. And, you know, the most obvious thing for me at that time was like, we're going to move everything to AWS. Now, I don't know if that happened, but I'm sure that if it hasn't, just bidding that out to Azure, GCP and AWS can raise, you know, three or four billion dollars, because I'm sure those companies would want this kind of an app on their cloud. So there's all kinds of things that I think Elon can do as a private company to make back, maybe the small bit that he overpaid. And then he can get to the core job of rebuilding this company to be usable, or this product to be usable.

• 24:05Chamath Palihapitiya?

  Because I, look, I'll just speak as a user right now. It has been decaying at a very, very rapid clip. And I think that his trepidation in closing the merger In part also, even though he hasn't said it, has to do with the quality of the experience. It's just degraded. It's not as fun to use as it was during the pandemic or even before the pandemic. So something is happening inside that app that needs to get fixed. And if he does it, he'll make a ton of money.

• 24:33David Friedberg?

  Sort of like what happened with Friendster and MySpace and any social networking app over time, the quality degrades. If it's not growing, it's shrinking and it gets.

• 24:41Chamath Palihapitiya?

  If it's not growing and also if the product hygiene isn't enforced in code and product hygiene in this case are this, you know, spam bots, you know, the trolling, it can really take away from the experience.

• 24:56David Friedberg?

  Yeah. I mean, interestingly, like if you think back to the starting days, the original days of Twitter, I don't know if you guys remember, you would send in an SMS to do your tweet and then it would post up and other people would get the SMS notification and it would crash all the time and the app was notoriously crashing. It was poorly architected at the beginning and some people have argued that Twitter has had a cultural, technical incompetence from the earliest days.

• 25:25Chamath Palihapitiya?

  I think that's a little harsh. So I do think, look, Twitter was known for what's called a fail whale. You know, they used to have these fail whales constantly and they did hire people that attempted to try to fix it. I remember the funniest part of when I went in there and said, hey, here's my plan and here's what I want to do is literally a day or two later, the head of engineering quit. I can't remember who his name was, but he was just out the door. But it is a, I think it is a team that has tried its best, that probably at the edges definitely made some technical miscalculations. Like I said, at that time, the idea that any app of that scale would use their own data centers made no technical sense whatsoever.

• 26:09Chamath Palihapitiya?

  It made the app laggy. It made it hard to use. It made it more prone to downtime, to your point. But that being said, I would be shocked if they haven't made meaningful improvements because the stack of the internet has gotten so much better over the last seven years. And so, to your point, David, if they didn't take advantage of all these new abstractions and mechanisms to rebuild the app, or to rebuild search, or to rebuild, you know, how, you know, all these infrastructure elements of the app work, I would be really surprised because then what are they doing over there?

• 26:39David Friedberg?

  Yeah. Well, look, I mean, to the point earlier, besides the product points, there was a really good tweet I liked that said, "For what it's worth, I think Elon will show us just how lean these Silicon Valley advertising companies can be run. At the very least, it'll be an interesting thought experiment for spectators." Because if he does go in and actually does significantly reduce OpEx and headcount, and the company does turn profitable, and he can grow it, it'll really, by the way, it'll really be a beacon for some of these other big companies.

• 27:12Chamath Palihapitiya?

  From a financial perspective, there is $10 a share in OpEx cuts that he should make right away, just so that he is economically break even, and he looks like every other M&A transaction. You know, you paid a 30% premium and you bought a company. There's a lot of margin of safety there if Elon does that. So to your point, there probably is, and there probably needs to be a meaningful riff at Twitter. I'm not saying it's right, I'm not saying it's, you know, and I feel for the people that may go through it, but from a financial perspective, the math makes sense for him to do that, because then he is a break even proposition on a go in M&A transaction. And I think that there's, there's a lot of intelligent financial sense, so that all the debt holders feel like he's doing the right thing, and all the equity holders particularly, see a chance for them to make a decent return here.

• 27:57David Friedberg?

  All right, well, let's move on. This has been a great conversation between Chamath Pollyapatia and David Friedberg about the Twitter transaction, and now we're being rejoined by our besties who are...

• 28:11Chamath Palihapitiya?

  Yeah, by other besties.

• 28:13David Friedberg?

  Yeah. How was your cappuccino, J. Cal?

• 28:16Chamath Palihapitiya?

  It was great. I have a nice cold brew here, a nice iced cold brew and a nice drip coffee. I'm working both.

• 28:22David Sacks?

  I'd love to talk about topics I'm not being subpoenaed or depositioned about.

• 28:26Chamath Palihapitiya?

  We will have a lot to say in the coming weeks.

• 28:28David Sacks?

  I love to talk about topics that my lawyers have advised me not to talk about.

• 28:31Chamath Palihapitiya?

  How eerie was our prediction? $51 a share, and it is exactly where the stock is right now. That's eerie.

• 28:38Jason Calacanis?

  Yeah. All right. Lots of advances.

• 28:40Chamath Palihapitiya?

  Let's keep going.

• 28:41Jason Calacanis?

  Yeah. Speaking of Elon, Tesla AI Day was last week. I actually went. It was great. This is a recruiting event where

• 28:50Chamath Palihapitiya?

  What did you do after?

• 28:51Jason Calacanis?

  Phil Hellmuth and I went and I drove Phil Hellmuth home.

• 28:56Jason Calacanis?

  The end. No, it was a great event and it is essentially a giant recruiting event. Hundreds of AI

• 29:03Chamath Palihapitiya?

  Sorry, I'm sorry. Can we just talk about Phil Hellmuth's non sequitur in the group chat about Ken Griffin?

• 29:11Jason Calacanis?

  I mean, oh, yeah, where he's just like, I made a joke about his net worth and he responded.

• 29:16Chamath Palihapitiya?

  What is going on? We were talking about the most serious of topics and he just comes over.

• 29:21Jason Calacanis?

  Seven seconds to Phil. What's going on? Seven seconds to Phil.

• 29:25Chamath Palihapitiya?

  By the way, I was texting with Daniel Negranu. He did an incredible podcast show. If you guys with Lex Friedman, if you haven't listened to it, the Daniel Negranu pod with Lex is incredible. But I was joking with Daniel that there's a section where he's talking about the greatest poker players of all time. And if you look in the bar of YouTube, it shows where the most viewership was. And it was exactly the 30 seconds he talks about Hellmuth. And I said to Daniel, this must have been Phil rewatching it over.

• 29:55Jason Calacanis?

  I put it on loop. He went to bed with it like it was ASMR to put him to bed. Negranu talking about him.

• 30:03Chamath Palihapitiya?

  Sorry, Jacob. Sorry.

• 30:04Jason Calacanis?

  No, no, it's all good. So anyway, the event was super impressive.

• 30:10Jason Calacanis?

  Elon only spoke when he showed the Optimus, the new robot. He's building a general purpose robot that will work in the factories. It's very early days, but they showed two versions of it. And he said he thinks they could get it down to $20,000. It's going to work in the factory. So it's actually got a purpose. And obviously the factories already have a ton of robots, but this is more of a robot that will benefit from the general or the computer vision.

• 30:38Jason Calacanis?

  And the AI, the narrow AI being pursued by the self-driving team. This is like two and a half hours of really intense presentations. The most interesting part for me was they're building their own supercomputer and their chips. And the Dojo supercomputer was really impressive at how much they can get through scenarios. So they're building every scenario, every self-driving. I actually have the full self-driving beta on my car. I've been using it. It's pretty impressive, I have to say. If you haven't used it yet, I feel like AI is moving at a pretty advanced clip. The past year, if you haven't also seen Meta announced a text-to-video generator. So this is even more impressive than Dolly.

• 31:23Jason Calacanis?

  Dolly, you put in a couple of words, Friedberg, and you get a painting or whatever. This is put in a couple of words and you get a short video. So they had one of a teddy bear painting a teddy bear. So it looks like you're going to be able to essentially create a whole movie by just talking to a computer. Really impressive. Where do you think we are, Friedberg, in terms of the compounding nature of these narrow AI efforts? You know, obviously we saw poker, chess, Go, Dolly, GPT-3, self-driving. It feels like this is all compounding at a faster rate. Or am I just imagining that?

• 32:02David Friedberg?

  Yeah, look, I mean, it's interesting. When, when people saw the first computer playing chess, they said the same thing. I think any time that you see progress with a computer that starts to mimic the predictive capabilities of a human, it's, it's impressive. But I will argue, and I just, I'll say a few words on this. It's, I think this is part of a 60-year cycle that we've been going through. Fundamentally, what humans and human brains do is we can sense our external environment. Then we generate knowledge from that sensing. And then our brains build a model that predicts an outcome. And then that, that predicted outcome is what drives our actions and our behavior. We observe the sunrise every morning, then we observe that it sets.

• 32:46David Friedberg?

  And you see that enough times and you build a predictive model from that data that's been generated in your brain. That I predict that the sun has risen, it will therefore set. It has set, it will therefore rise. And I think that the computing approach is very similar. It's all about sensing or generating data and then creating a predictive model. And then you can drive action. And initially, the first approach was just basic algorithms. And these are deterministic models that are built. It's a piece of code that says, here's an input, here's an output. And that that model is really built by a human. And a human designed that algorithmic model and said, this is what the predictive potential of this software is. Then there was this term called data science. So as data generation began to proliferate, meaning there was far more sensors in the

• 33:31David Friedberg?

  world, it was really cheap to create digital data from the physical world, really cheap to transmit it, really cheap to store it, really cheap to compute with it. Data science became the hot term in Silicon Valley for a while. And these models were not just a basic algorithm written by a human, but it became an algorithm that was a similar deterministic model that had parameters. And the parameters were ultimately resolved by the data that was being generated. And so these models became much more complex and much more predictive, finer granularity, finer range. Then we use this term machine learning. And in the data science era, it was still like, hey, there's a model and you would solve it statically. You would get a bunch of data, you would statically solve for the parameters, and that would be your model, and it would run.

• 34:16David Friedberg?

  Machine learning then allowed those parameters to become dynamic. So the model was static, but generally speaking, the parameters that drove the model became dynamic as more data came into the system and they were dynamically updated. And then this era of AI became, and that's the new catchword. And what AI is realizing is that there's so much data that rather than just resolve the parameters of the model, you can actually resolve a model itself. The algorithm can be written by the data, the algorithm can be written by the software. And so with AI. Example, so poker playing, an adaptive model. So people, so you're playing poker and the software begins to recognize behavior and it builds a predictive model that says, here's how you're playing.

• 35:00David Friedberg?

  And then over time, it actually changes not just the parameters of the model, but the model itself, the algorithm itself. And so AI, and then it eventually gets to a point where the algorithm is so much more complex that a human would have never written it. And suddenly, the AI has built its own intelligence, its own ability to be predictive in a way that a human algorithmic programmer would have never done. And this is all driven by statistics. So none of this is new science per se. There's new techniques that all on their underlying use statistics as their basis. And then there's these techniques that allow us to build these new systems of model development like neural nets and so on. And those statistics build those neural nets, they solve those parameters and so on.

• 35:39David Friedberg?

  But fundamentally, there is a geometric increase in data and a geometric decline in the cost to generate data from sensors, because the cost of sensors is coming down with Moore's Law. Transmit that data, because the cost of moving data has come down with broadband communications. The cost of storing data, because the cost of DRAM and solid-state hard drives has come down with Moore's Law. And now the ability to actually have enough data to do this AI-driven, what people are calling AI, but it really is the same, it's part of a spectrum of things that have been going on for 60 years, to actually drive predictions in the world, is really being realized in a bunch of areas that we would have historically been really challenged and surprised to see. And so my argument is... At this point, big data played a big role, yeah.

• 36:23David Friedberg?

  Yeah, we've, over the last decade, we've reached this tipping point in terms of data generation, storage, and computation, that's allowed these statistical models to resolve dynamically. And as a result, they are far more predictive, and as a result, we see far more human-like behavior in the predictive systems, both physical, both those that are, you know, like a robot is the same as one that existed 20 years ago. But the way that it's run is using the software that is driven by this dynamic model. The data allows for a better answer. Chuma.

• 36:54Chamath Palihapitiya?

  Okay, I have two things to say, but one, the first one is a total non-sequitur. So use the term "data scientist." Do you know where the term "data scientist" came from?

• 37:04Chamath Palihapitiya?

  As classically used in Silicon Valley. It came from Facebook and it came from my team in a critical moment. This was in 2007, I was trying to, 2008, I was trying to build the growth team. This is the team that became very famous for getting to a billion users and, you know, building a lot of these algorithmic insights. And I was trying to recruit a person from Google. And he was like a PhD in some crazy thing like astrophysics or particle physics or something. And we gave him an offer as a data analyst, because this is what I needed at the time. This is what I thought I needed, an analyst to analyze data. And he said, absolutely not, I'm offended by the job title. And I remember talking to my, my HR, you know, business process partner.

• 37:49Chamath Palihapitiya?

  And I asked her like, I don't understand, what is this, where is this coming from? And she said, he fashions himself a scientist. And I said, well, then call him a data scientist. So we wrote in the offer for the first time, data scientist. And at the time, people internally were like, this is a dumb title. What does this mean? Anyways, we hired the guy, he was a star. And, uh, and that title just took off internally.

• 38:11David Friedberg?

  It's funny because parallel, we started Climate Corp in 2006. And the original, the first guy I hired was a buddy of mine who was a 4.0 for, in applied math from Cal. And then everyone we hired on with him, we called them the math team. And they were all applied math and statistics PhDs. And we called them the math team and it was really cool to be part of the math team. But then we switched the team name to data scientist. And then it obviously created this much more kind of impressive role, impressive title, central function to the organization that was more than just a math person or data analyst, uh, as I think it may have been classically treated, because they really were building the algorithms that drove the models that made the product work, right?

• 38:50Chamath Palihapitiya?

  Peter Thiel has a very funny observation, not funny, but you know, uh, observation, which is you should always be wary of any science that actually has science in the name, political science, social science, I guess maybe data scientist, you know, because the real sciences don't need to qualify themselves, physics, chemistry, biology. Anyways, that's, so here, here's what I wanted to talk about with respect to AI. Um, two very important. Observations that I think is useful for people to know. The first one, Nick, if you throw it up here is just a baselining of, you know, when we have thought about intelligence and compute capability, we've always talked about Moore's law. And Moore's law, essentially, this idea that there is a fixed amount of time where the density of transistors inside of a chip would double.

• 39:33Chamath Palihapitiya?

  And roughly that period for many, many years was around two years. And it was largely led by Intel. And we used to equate this to intelligence, meaning the more density there was in a chip, the more things could be learned and understood. And we used to think about that as the progression of how computing intelligence would grow and eventually AI and artificial intelligence would get to mass market. Well, what we are now at is a place where many people have said Moore's law has broken. Why? It's because we cannot cram any more transistors into a fixed amount of area. We are at the boundaries of physics. And so people think, well, does that mean that our ability to compute

• 40:18Chamath Palihapitiya?

  will essentially come to an end and stop? And the answer is no. And that's what's demonstrated on this next chart, just to make it simple. Which is that what you really see is that if you think about, you know, supercomputing power, so the ability to get to an answer, that has actually continued unabated. And if you look at this chart, the reason why this is possible is entirely because we've shifted from CPUs to these things called GPUs. So you may have heard companies like Nvidia. Why has companies like Nvidia done so well? It's because they said, they raised their hand and said, we can take on the work. And by taking on the work away from a traditional CPU, you're able to do a lot of what Friedberg said is get into these very complicated models.

• 41:04Chamath Palihapitiya?

  So this is just an observation that I think that we are continuing to compound knowledge and intelligence effectively at the same rate as Moore's law. And we will continue to be able to do that because this makes it a problem of power and a problem of money. So as long as you can buy enough GPUs from Nvidia or build your own. And as long as you can get access to enough power to run those computers, there really isn't many problems you can't solve. And that's what's so fascinating and interesting. And this is what companies like OpenAI are really proving. You know, when they raised a billion dollars, what they did was they attacked this problem

• 41:47Chamath Palihapitiya?

  because they realized that by shifting the problem to GPUs, it left all these amazing opportunities for them to uncover. And that's effectively what they have. The second thing that I'll say very quickly is that it's been really hard for us as a society to build intelligence in a multimodal way like our brain works. So think about how our brain works. Our brain works in a multimodal way. We can process imagery. We can process words and sounds. We can process all of these different modes, text into one system, and then intuit some intelligence from it and make a decision. Right? So, you know, we could be watching this YouTube video. There's going to be transcription.

• 42:32Chamath Palihapitiya?

  There's video, voice, audio, everything all at once. And we are moving to a place very quickly where computers will have that same ability as well. Today, we go to very specific models and kind of Balkanized silos to solve different kinds of problems. But those are now quickly merging, again, because of what I just said about GPUs. So I think what's really important about AI for everybody to understand is the marginal cost of intelligence is going to go to zero. And this is where I'm just going to put out another prediction of my own. When that happens, it's going to be incredibly important for humans to differentiate themselves from computers. And I think the best way for humans to differentiate ourselves

• 43:16Chamath Palihapitiya?

  is to be more human. It's to be less compute-intensive. It's to be more empathetic. It's to be more emotional, a lot less emotional. Because those differentiators are very difficult for brute force compute to solve. Be careful, the replicants on this call are getting a little nervous here. They're not processing that. That was an emotional statement. Do not want to process that one.

• 43:38Jason Calacanis?

  Well, to your point, during this AI day, they were showing in self-driving, as you're talking about this balkanization and trying to make decisions across many different decision trees, you know, they're looking at lane changes, they're looking at other cars and pedestrians, they're looking at road conditions like fog and rain, and then they're using all this big data, to your point, Friedberg, to run tons of different simulations. So they're building like this virtual world on Market Street, and then they will throw people, dogs, cars, people who have weird behaviors into the simulation.

• 44:15Chamath Palihapitiya?

  It's such a wonderful example. Imagine that system hears a horn.

• 44:20Jason Calacanis?

  Yeah.

• 44:21Chamath Palihapitiya?

  Well, you hear a horn, so clearly there's some auditory expression of risk, right? There's something risky, and now you have to scan your visual field, you have to probabilistically decide what it could be, what the evasive maneuver, if anything, should be. So that's a multimodal set of intelligence that today isn't really available.

• 44:42Jason Calacanis?

  Yeah.

• 44:43Chamath Palihapitiya?

  But we have to get there if we're going to have real, full self-driving. So that's a perfect example, Jason, a real-world example of how hard the problem is, but it'll get solved because we can brute force it now with chips and with compute.

• 44:54Jason Calacanis?

  I think that's going to be the very interesting thing with the robots as well, is all of these decisions they're making, moving cars through roads, all of a sudden we're going to see that with VTOLs, vertical takeoff and landing, you know, aircraft, and we're going to see it with this general robot. And everybody wanted to ask Elon about general AI, you know, the Terminator kind of stuff. And his position is, I think, if we solve enough of these problems, Friedberg, it'll be an emergent behavior, or an emergent phenomenon, I guess would be a better word, based on each of these cities crumbling, you know, each of these tasks getting solved by groups of people. You have any thoughts as we wrap up here on the AI discussion about general AI and the timeline for that? Because obviously

• 45:37Jason Calacanis?

  we're going to solve every vertical AI problem in short order.

• 45:41David Friedberg?

  I spoke about this a little bit on the Ask AMA on Call-In on Tuesday night, once Saks gets it out, you can listen to it. But I really have this strong belief that...

• 45:53Jason Calacanis?

  The servers crashed, there's no AI, no AI team at Call-In.

• 45:56David Sacks?

  This episode drops.

• 45:57Jason Calacanis?

  Oh my god. Yeah, you guys can try to download the app, but it might crash, so just be careful.

• 46:01David Friedberg?

  So here's my...

• 46:04David Sacks?

  The problem is Friedberg that you are 10 times more popular than J Cal, so it's unexpected levels of traffic.

• 46:10Jason Calacanis?

  Well, you had, you did have an account with 11,000 followers. I mean,

• 46:14David Sacks?

  You're right, J Cal. We'll put you on that account next time.

• 46:17Jason Calacanis?

  Yeah, please. I'm starting from zero.

• 46:20David Sacks?

  Yeah, that's fair. That's fair.

• 46:21David Friedberg?

  Yeah, look, my, my core thesis is I think humans transitioned from being, um, let's call it, you know, passive in the system on earth to being laborers. And then we transitioned from being laborers to being creators. And I think our next transition with AI is to transition from being creators to being narrators. And what I mean by that is as, as we started to do work on earth and engineer the world around us, we did labor to do that. We literally plowed the fields, we walked distances, we built things. And over time, we built machines that automated a lot of that labor. You know, everything from a plow to a tractor, to a caterpillar, equipment, to a microwave that cooks for us, labor became less, we became

• 47:06David Friedberg?

  less dependent on our labor abilities. And then we got to switch our time and spend our time as creators, as knowledge workers. And a vast majority of the developed world now primarily spends their time as knowledge workers, creating. And we create stuff on computers, we do stuff on computers, but we're not doing physical labor anymore. As a lot of the knowledge work gets supplanted by AI, or as it's being termed now, but really gets supplanted by software, the role of the human, I think, transitions to being one of a narrator, where instead of having to create the, the blueprint for a house, you narrate the house you want and the software creates the blueprint for you.

• 47:43Jason Calacanis?

  You dictate.

• 47:43David Friedberg?

  And instead of, yeah, and instead of creating the movie and not spending a hundred million dollars producing a movie, you dictate or you narrate the movie you want to see and you iterate with the computer and the computer renders the entire film for you. Because those films are shown digitally anyway, so you can have a computer render it. Instead of creating a new piece of content, you narrate the content you want to experience. You create your own video game. You create your own movie experience. And I think that there's a whole evolution that happens. And if you look, Steve Pinker's book Enlightenment Now has a great statistic, a set of statistics on this. But the amount of time that humans are spending on leisure activities per week has climbed extraordinarily over the past couple of decades. We spend more time enjoying ourselves and exploring our creative interests than we ever did in the, in the past in human history,

• 48:28David Friedberg?

  because we were burdened by all the labor and all the creative and knowledge work we had to do. And now things are much more accessible to us. And I think that AI allows us to transition into an era that we never really thought possible to realize, where the limits are really our imagination of what we can do with the world around us. And the software resolves to the, and automation resolves to make those things possible. And that's a really exciting kind of vision for the future that I think AI enables.

• 48:53Jason Calacanis?

  Star Trek had this, right? People didn't have to work and they could pursue things in the holodeck or whatever that they felt was rewarding to them. But speaking of jobs, the job reports for August came in. We, we talked about this. We were, we were trimming 300,000 jobs a month. We're wondering if the other shoe would drop. Oh, boy, did it drop. A hun, over a million jobs burned off in August. So without getting into the macro talk, it does feel like what the Fed is doing and companies doing hiring freezes and cuts is finally, finally having an impact. If we start losing a million, as we predicted could happen here on the show,

• 49:32Jason Calacanis?

  people might actually go back to work and Lyft and Uber are reporting that the driver shortages are over. They no longer have to pay people spiffs and stuff like that to get people to come back to work. So at least here in America, feels like we're turning a corner. Do we want to go?

• 49:45David Friedberg?

  Cal, can we, let's talk about the marijuana.

• 49:48Jason Calacanis?

  Yeah, breaking news.

• 49:49David Friedberg?

  That Biden just did, yeah.

• 49:50Jason Calacanis?

  Yeah, I was about to say, we got a couple of things we really want to get to here. Uh, Ukraine, section 230, and then this breaking news. Uh, we'll pull it up here on the screen. While we're recording the show, President Biden says, and I'm just going to quote here.

• 50:04Jason Calacanis?

  First.

• 50:06Jason Calacanis?

  I'm pardoning all prior federal offenses of simple marijuana possession. There are thousands of people who were previously convicted of simple possession, who may be denied employment, housing, or educational opportunities. As a result, my pardon will remove this burden. That's big news. Second, I'm calling on governors to pardon simple state marijuana possession offenses, just as no one should be in a federal prison solely for possessing marijuana. Nobody should be in a local jail or state prison for that reason either. Finally, this is happening. Third, and this is an important one, we classify marijuana at the same level as heroin and even more serious than fentanyl. Makes no sense. I'm asking Secretary Bakara and the Attorney General to initiate the process of reviewing how marijuana is scheduled under federal law.

• 50:51Jason Calacanis?

  I'd also like to note that as federal and state regulators change, we still need important limitations on trafficking, marketing, and underage sales of marijuana. Thoughts on this breaking news?

• 51:02David Friedberg?

  Zach, do you think the timing on this is kind of midterm related? I guess this is a politically popular decision to do?

• 51:13David Sacks?

  I think so. I mean, look, I support it. So Biden finally did something I like.

• 51:18David Friedberg?

  Great.

• 51:19David Sacks?

  I mean, I thought that we should decriminalize marijuana for a long time. Or specifically, you know, I agree with this idea of descheduling it. It does not make sense to treat marijuana the same as heroin, as a Schedule I narcotic. It just doesn't make any sense. It should be regulated separately and differently. Obviously, you want to keep it out of the hands of minors, but no one should be going to jail, I think, for simple possession. So I do agree with this. And I think the thing they need to do, I don't see it mentioned here, is they should pass a federal law that would allow for the normalization of, let's call it legal cannabis companies.

• 52:00David Sacks?

  So companies that are allowed to operate under state laws, like in California, should have access to the banking system, should have access to payment rails. Because right now, the reason why the legal cannabis industry isn't working at all in California is because they can't bank, they can't take payments. So it's this weird all cash business that makes no sense. So, so listen, if we're not going to criminalize it as a drug like heroin, if we're going to allow states to make it legal, then allow it to be a more normal business where the state can tax it. And it can operate in a more above board way. So.

• 52:37Jason Calacanis?

  Federal mandate is what you're saying, the federal mandate.

• 52:40David Sacks?

  I think it could still be regulated on a state by state basis, but I think you need the feds to bless the idea that banks and payment companies can take on those clients, which states have already said are legally operating companies. And right now they can't. And it's a huge gap in the law. So maybe that's the one thing I would add to this, but I don't have any complaints about this right now. Based on what we know from this tweet storm and I would say this, this by the way was about face. This was an about face by Biden.

• 53:09David Friedberg?

  Yeah. Do you know what the polling data says? I mean, is there, I'm assuming there's big support in kind of the independents and the middle.

• 53:16Jason Calacanis?

  Uh, for this. It was 70% at one point.

• 53:18David Sacks?

  Yeah.

• 53:19David Friedberg?

  Yeah.

• 53:20David Sacks?

  So, so look, this, to me, this is the kind of thing that Biden should be doing with the 50 50 Senate, finding these sorts of bipartisan compromises.

• 53:27David Friedberg?

  Right.

• 53:29David Sacks?

  So, yeah, I look, this is good news as far as I'm concerned.

• 53:31David Friedberg?

  Why hasn't this happened in the past? Like, what's been the political reason that other presidents, Obama even?

• 53:40David Friedberg?

  Didn't that have.

• 53:41Jason Calacanis?

  There was rumors.

• 53:42David Friedberg?

  ideology like why, why, but why, does anyone know why this hasn't been done in the past?

• 53:46Jason Calacanis?

  There was rumors he was going to do in the second term. They just didn't have the political capital to do it.

• 53:51David Friedberg?

  Why? I don't, I don't.

• 53:53Chamath Palihapitiya?

  Well, a pardon doesn't require. Yeah, the pardon doesn't require political capital. I think it's probably the perception that this is soft on crime in some way, or there wasn't enough broad based support, as David said, I mean, I think the the United States population has moved pretty meaningfully in the last 20 years.

• 54:10Jason Calacanis?

  That's it, Shomoff. Look at the chart here. Um, you know, we were talking about 2000, it was only 31%. Uh, and then you look at 2018, it's up at 60 plus percent. So when people saw the states doing it and they saw. Absolutely no problem, you know, in every state. And I think what people will see next is

• 54:27David Friedberg?

  That's a gallup poll.

• 54:28Jason Calacanis?

  That's a gallup poll you're seeing there. Yeah. So I mean, it's increased dramatically. MDMA, psilocybin, and some of these other plant-based medicines, ayahuasca are next. And they're doing studies on them now.

• 54:38Chamath Palihapitiya?

  I don't want to take away from how important this is for all the people for whom this will positively impact. I just want to talk about the schedule change for marijuana. As a parent, one of the things that I'm really, really concerned about is that through this process of legalization, getting access to marijuana has frankly become too easy, particularly for kids. At the same time, I saw a lot of really alarming evidence that the the intensity of these marijuana-based products have gone, you know, I think it's like five or six times more intense than they were 20 years ago.

• 55:13Jason Calacanis?

  Fifty or a hundred times, much higher.

• 55:15Chamath Palihapitiya?

  Right. So, so it's no longer, you know, this kind of like, you know, do no harm drug that it was 20 years ago. This is, this could be actually, David, the way that it's productized today as bad as some of these other, you know, narcotics. So in June of this year, the Biden administration basically made this press release that said, the FDA is going to come out with regulations that would cap the amount of nicotine in cigarettes. And I think that was a really smart move because it basically set the stage to taper nicotine out of, out of cigarettes, which would essentially, you know, decapitate it as a, an addictive product.

• 55:59Chamath Palihapitiya?

  And I think by thinking about how it's, how it's dealt with, what I really hope the administration does is it empowers the FDA. If you're going to legalize it, you need to have expectations around what the intensity of these drugs are. Because if you're delivering drugs, OTC, and now any kid can go in at 18 years old and buy them, which means that 18-year-olds are going to buy them for 16-year-olds. 16-year-olds are going to get fake IDs to buy them for themselves. You need to do a better job so that parents, you're helping parents do our job.

• 56:32Jason Calacanis?

  Here's what you need to do.

• 56:33David Sacks?

  Shouldn't it be 21, like alcohol? If alcohol is 21, then...

• 56:38Jason Calacanis?

  Of course, yeah.

• 56:39Chamath Palihapitiya?

  Fine, but even alcohol, David, you know that there are, we know what the intensity of these are. There are labels and there's warnings and you know the difference between beer versus wine versus hard alcohol.

• 56:48Jason Calacanis?

  But let me just give you some statistics here, Chamath. If you think about the cannabis in the 90s and prior to that, there have been a ton of studies on this in Colorado. It was, the THC content was less than 2%. And then in 2017, we were talking about, you know, things going up to 17 to 28% for a specific strain. So they have been building strains like Girl Scout Cookies, et cetera, that have just increased and increased. And then there are things like shards and obviously edibles. You can create whatever intensity you want. So you have this incredible, you know, variation. You could have an edible that's, you know, got one milligram of THC, one that has 100.

• 57:30Jason Calacanis?

  Or you could have a pack of edibles and you see this happen in the news all the time. Some kid gets their parents' pack or somebody gives one and the kids don't know. And this dabbing phenomenon combined with, dabbing is like the shards, like this really intense stuff, combined with the edibles is really the issue and the labeling of them. So you gotta be incredibly careful with this. It's not good for kids. It screws up their brains and so, yeah, be very careful.

• 57:55Chamath Palihapitiya?

  I have a zero tolerance policy on this stuff. I don't care if it's legal or illegal. Like I don't want my kids touching any of this stuff until...

• 58:00Jason Calacanis?

  It's not for kids, obviously, yeah. But we also should not be putting...

• 58:03Chamath Palihapitiya?

  Until they're 35 or 40 and even then I hope they never do it. But, but I need some help and I'm not sure I'm the only parent that's asking. You can't have this stuff be available, effectively sold like in a convenience store.

• 58:15Jason Calacanis?

  No, no, that's not gonna happen.

• 58:17Chamath Palihapitiya?

  Where there isn't even labeling, at least like cigarettes are labeled. It's very clear how bad this stuff is for you.

• 58:23Jason Calacanis?

  Do you guys have any feedback on the job report or anything? They're all going away when, when the, when the AI wins. Well, that's why I brought it up is like, we're now going to see a potential, you know, a situation where jobs go away and a lot of the stuff like even developers, right? Don't you think Friedberg developers are going to start development tasks?

• 58:40David Friedberg?

  No.

• 58:41Jason Calacanis?

  And design tasks are going to be AI-based.

• 58:43David Friedberg?

  Everyone assumes a static lump of work. I think what happens particularly in things like developer tools is the developer can do so much more and then we generate so much more output. And so the overall productivity goes up, not down. So it's pretty exciting as these and remember, like, like, we were talking on the AMA the other night, Adobe Photoshop was a tool for photographers. So you didn't have to take the perfect photograph and then print it. You could, you know, you could use the software to improve the quality of your photograph. And I think that that's what we see happening with all software in the creative process is it helps people do more than they realize they could do before. And that's pretty powerful. And it opens up all these new avenues of interest and things we're not even imagining today.

• 59:24Jason Calacanis?

  All right. So SCOTUS is going to hear two cases for section 230. The family of Nojima Gonzalez, a 23 year old American college student who was killed in an ISIS terrorist attack in Paris back in 2015. You remember those horrible attacks is claiming that YouTube helped and aided and abetted ISIS. The family's argument is YouTube's algorithm was recommending videos that make it that makes it a publisher of content. As you know, it's section 230, common carrier. Now, if you make editorial decisions, if you promote certain content, you lose your 230 protections. In court papers filed in 2016, they said the company, quote, knowingly permitted ISIS to post on YouTube hundreds of radicalizing videos inciting violence, which helped the group recruit, including

• 1:00:07Jason Calacanis?

  some who were actually involved in the terrorist attack. So they have made that connection.

• 1:00:11Chamath Palihapitiya?

  Well, look, let's, let's be honest. We can, we can, we can put a pin in this thing because I think it would be shocking to me if this current SCOTUS all of a sudden found it in the cockles of their heart to protect big tech. I mean, they've dismantled a lot of other stuff that I think is.

• 1:00:31Chamath Palihapitiya?

  A lot more controversial than this. And so, you know, we've, we've basically looked at gun laws, we've looked at affirmative action, we've looked at abortion rights. Sorry, well, I mean, I think, as, as we've said, I think we all know where that die is unfortunately going to get cast. So to me, it just seems like this could be an interesting case where it's actually nine zero in favor for completely, for completely different sets of reasons. I mean, if you think of the liberal left part of the court, they have their own reasons for saying that there are two thirty protections for big tech. And if you look at the, the far right or the, the right leaning parts, members of this, of SCOTUS, they have, they have another set of different reasons.

• 1:01:12Jason Calacanis?

  You think they're gonna make a political decision, not a legal?

• 1:01:14Chamath Palihapitiya?

  No, but even, even in their politics, they actually end up in the same place. They both don't want the protections, but for different reasons. So there, there is a reasonable outcome here where, you know, Roberts is gonna have a really interesting time trying to pick who writes the majority opinion.

• 1:01:28David Sacks?

  There was a related case in the Fifth Circuit in Texas where, do you guys see this Fifth Circuit decision where Texas passed a law imposing common carrier restrictions on social media companies? The idea being that social media companies need to operate like phone companies and they can't just arbitrarily deny you service or deny you access to the platform. And the argument why previously that had been viewed actually as unconstitutional was this idea of compelled speech, that you can't compel a corporation to support speech that they don't want to because that was a violation of their own First Amendment rights. And what the first, the Fifth Circuit said is, no, that doesn't make any sense.

• 1:02:10David Sacks?

  Facebook or Twitter can still advocate for whatever speech they want as a corporation, but as a platform, they, if Texas requires them to not discriminate against people on the basis of their viewpoint, then Texas has the right to, to impose that because that doesn't, their quote was, that does not chill speech. If anything, it chills censorship.

• 1:02:31Jason Calacanis?

  What's the right legal decision here in your mind? Putting aside politics, if you can, for a moment, putting on your legal hat, what is the right thing for society? What is the right legal issue around section two thirty? Specifically in the YouTube case and just generally, should we look at YouTube? Should we look at a blogging platform like Medium or Blogger? Twitter? Should we look at those as common carrier? And they're not responsible for what you publish on them. Obviously, they have to take stuff down if it breaks their terms of service, etc., or if it's illegal.

• 1:03:01David Sacks?

  I've made the case before that I do think that common carrier requirements should apply on some level of the stack to protect the rights of ordinary Americans to have their speech in the face of these giant monopolies, which could otherwise deplatform them for arbitrary reasons. Just to, you know, just to explain this a little bit. So historically, there was always a debate between so-called positive rights and negative rights. So where the United States started off as a country was with this idea of negative rights, that what a right meant is that you be protected from the government taking some action against you. And if you look at the Bill of Rights, you know, the original rights are all about protecting the citizen against intrusion on their liberty by a state or by the federal

• 1:03:46David Sacks?

  government. In other words, Congress shall make no law. It was always a restriction. So the right was negative, but it wasn't sort of positively enforced. And then with the progressive era, you started seeing, you know, more progressive rights, like, for example, American citizens should have the right to healthcare, right? That's not protecting you from the government. That's saying that the government can be used to give you a right that you didn't otherwise have. And so that was sort of the big progressive revolution. My take on it is, I actually think that the problem we have in our society right now is that free speech is only a negative right. It's not a positive right. I think it actually needs to be a positive right. I'm embracing a more progressive version of rights, but

• 1:04:27David Sacks?

  on behalf of sort of this original negative right. So, and the reason is because the town square got privatized, right? I mean, you used to be able to go anywhere in this country, there'd be a multiplicity of town squares, anyone could pull out their soapbox, draw a crowd, they could listen. That's not how speech occurs anymore. It's not on public land or public spaces. The way that speech, political speech especially, occurs today is in these giant social networks that have giant network effects and are basically monopolies. So if you don't protect the right to free speech in a positive way, it no longer exists.

• 1:05:00Jason Calacanis?

  So you not only believe

• 1:05:02David Sacks?

  Wow.

• 1:05:02Jason Calacanis?

  that YouTube should keep its Section 230, you believe YouTube shouldn't be able to deplatform as a private company, you know, Alex Jones as but one example, they should have their free speech rights, and we should lean on that side of forcing YouTube to put Alex Jones or Twitter to put Trump back on the platform. So that's your position?

• 1:05:23David Sacks?

  I'm not saying that the Constitution requires YouTube to do anything. What I'm saying is that if a state like Texas, or if the federal government wants to pass a law saying that YouTube, if you are, say, of a certain size, you're a social network of a certain size, you have monopoly network effects, I wouldn't necessarily apply this to all the little guys, but for those big monopolies, we know who they are. If the federal government or a state wanted to say that they are required to be a common carrier, and they cannot discriminate against certain viewpoints, I think the government should be allowed to do that, because it furthers a positive right. Historically, they've not been able to do that because of this idea, because this idea of compelled speech, meaning that it would infringe on YouTube's speech rights.

• 1:06:08David Sacks?

  I don't think it would. I mean, Google and YouTube can advocate for whatever positions they want. They can produce whatever content they want.

• 1:06:15Jason Calacanis?

  Yeah.

• 1:06:15David Sacks?

  But the point that, and I think Section 230 kind of makes this point as well, is that they are platforms, they're distribution platforms, they're not publishers. So if they want, so especially if they want Section 230 protection, they should not be engaging in viewpoint discrimination.

• 1:06:28Jason Calacanis?

  Okay, so now there is a rub here.

• 1:06:29Chamath Palihapitiya?

  Can I just say, can I just say?

• 1:06:31Jason Calacanis?

  Go ahead.

• 1:06:31Chamath Palihapitiya?

  Your explanation, David, your explanation that you just gave before was so excellent. Thank you. That, it allows me to understand it even more clearly. That was really good.

• 1:06:40Jason Calacanis?

  So, Chomov, do you think the algorithm is an act of editorialization?

• 1:06:45Chamath Palihapitiya?

  Yes, yes, yes, yes.

• 1:06:46Jason Calacanis?

  And so then, should YouTube TikTok?

• 1:06:49Chamath Palihapitiya?

  Look, guys, at the end of the day, let me break down an algorithm for you. Okay, effectively, it is a mathematical equation of variables and weights. An editor 50 years ago was somebody who had that equation of variables and weights in his or her mind. Okay? And so all we did was we translated, again, this multimodal model that was in somebody's brain into a model that's mathematical, that sits in code.

• 1:07:20Jason Calacanis?

  You're talking about the front page editor of the New York Times?

• 1:07:23Chamath Palihapitiya?

  Yeah, and I think it's a fig leaf to say that because there is not an individual person who writes .2 in front of this one variable, and .8 in front of the other, that all of a sudden that this isn't editorial decision-making is wrong. We need to understand the current moment in which we live, which is that these computers are thinking actively for us. They're providing this, you know, computationally intensive...

• 1:07:50Chamath Palihapitiya?

  Decision making and reasoning. And I think it's it's pretty ridiculous to assume that that isn't true. That's why when you go to Google and you search for, you know, Michael Jordan, we know what the right Michael Jordan is because it's reasoned. There is an algorithm that is doing that. It's making an editorial decision around what the right answer is. They have deemed it to be right. And that is just true. And so I think we need to acknowledge that because I think it allows us at least to be in a position to rewrite these laws through the lens of the 21st century. And we need to we need to update our understanding for how the world works today.

• 1:08:30Jason Calacanis?

  And you know, Chamath, there's such an easy way to do this. If you're TikTok, if you're YouTube, if you want section 230, if you want to have common carrier and not be responsible for what's there, when a user signs up, it should give them the option. Would you like to turn on an algorithm? Here are a series of algorithms which you could turn on. You could bring your own algorithm. You could write your own algorithm with a bunch of sliders. Or here are ones that other users and services provide like an app store. So you, Chamath, could pick one for your family, your kids. That would be, I want one that's leaning towards education and takes out conspiracy theories, takes out cannabis use, takes out this one.

• 1:09:05Chamath Palihapitiya?

  It's a wonderful, what you're saying is so wonderful. Because, for example, like, you know this organization, Common Sense Media?

• 1:09:10Jason Calacanis?

  Yes, I love that website. Every time I put in a movie, I put Common Sense Media to decide if we should watch it.

• 1:09:15Chamath Palihapitiya?

  Or like, I use it a lot for apps because they're pretty good at just telling you which which apps are reasonable and unreasonable. But, you know, if Common Sense Media could raise a little bit more money and and create an algorithm that would help filter stories in TikTok for my kids, I'd be more likely to give my kids TikTok when they turn 14. Right now, I know that they're going to sneak it by going to YouTube and looking at YouTube Shorts and all these other things because I cannot control that algorithm. And it does worry me what kind of content that they're getting access to.

• 1:09:47Jason Calacanis?

  And you could do this, by the way, Chamath, on the operating system level or on the router level in your house. You could say, I want the Common Sense algorithm. I will pay $25 a month, $100 a year for it.

• 1:09:58Chamath Palihapitiya?

  I think that we are as a society.

• 1:09:59Jason Calacanis?

  Put it on your router and then any IP that goes through it would be programmed properly. I want less violence. I want less sex. You know, whatever.

• 1:10:05Chamath Palihapitiya?

  I think we are, as a society, sophisticated enough now to have these controls. And so I think we need them. And so I think we do need to have the right.

• 1:10:16Jason Calacanis?

  Observation of the current state of play. Friedberg, where do you sit on this? Do you think the algorithm should be carved out of 230?

• 1:10:26David Friedberg?

  Yeah, I don't fully agree with Sacks on the monopolistic assumption. I think that there are.

• 1:10:34Jason Calacanis?

  Unpack it.

• 1:10:34David Friedberg?

  I think that there are other places to access content and I think that there is still a free market to compete. And it is possible to compete. I think that we saw this happen with TikTok. We saw it happen with Instagram. We saw it happen with YouTube competing against Google Video and Microsoft Video prior to that. There has been a very significant battle for the attention of kind of being the next gen of media businesses. And we have seen Spotify compete and we're seeing Spotify continue to be challenged by emerging competitors. So I don't buy the assumption that these are built in monopolies and therefore it allows some regulatory process to come in and say, hey, free speech needs to be actively enforced because they're monopolies.

• 1:11:18David Friedberg?

  This isn't like when utilities laid power lines and sewer lines and trains across the country. And they had a physical monopoly on being able to access and move goods and services. The internet is still, thank God, knock on wood, open. And the ability for anyone to build a competing service is still possible. And there is a lot of money that would love to disrupt these businesses that is actively doing it. And I think every day, look at how big TikTok has gotten. It is bigger than YouTube almost or will be soon. And there is a competition that happens. And because of that competition, I think that the market will ultimately choose where they want to get their content from and how they want to consume it. And I don't think that the government should play a role.

• 1:12:00Jason Calacanis?

  Sacks rebuttal to that, do you buy that?

• 1:12:01David Sacks?

  Well, so not all these companies are monopolies, but I think they act in a monopolistic way with respect to restricting free speech, which is they act as a cartel. They all share like best practices with each other on how to restrict speech. And we saw the watershed here was remember when Trump was thrown off? First Twitter made the decision, you know, Jack, I don't even know if it was Jack, but basically the company.

• 1:12:25Jason Calacanis?

  Jack said it wasn't him.

• 1:12:26David Sacks?

  Actually, he said it was the woman who was running it specifically. Yeah, Jack actually said it was a mistake. But any event, Twitter did it first and then all the other companies followed suit. I mean, even like Pinterest and Okta and Snapchat like officially. Facebook, YouTube, everybody. Yeah, but Trump was actually on Facebook. He wasn't on all these other companies. They still threw him off, so they all copy each other. And Jack actually said that in his comments where he said it was a mistake. He said he didn't realize the way in which Twitter's action would actually cascade. He said that he thought originally that the action was okay because it was just Twitter deciding to take away Trump's right to free speech. But he could still go to all these other companies and then all these other companies.

• 1:13:09David Sacks?

  Basically, you know, they they are all subject to the same political forces. The the leadership of these companies are all sort of they all drink from the same monocultural found. They all have the same political biases. The polls show this, so the problem of Friedberg is, yeah, I agree. A bunch of these companies aren't quite monopolies, but they all act the same way. I hate to say it, but I agree with you, Sacks. Yeah, the collective effect is of a speech cartel. So the question is, how do you protect the rights of Americans to free speech in the face of a speech cartel that wants to basically block them? Go ahead, Friedberg, respond.

• 1:13:41David Friedberg?

  Here's my argument. My argument is that these are not public service providers. They're private service providers and the market is telling them what to do. The market is saying, and I think that the pressure. I think that the pressure that was felt by these folks was that so many consumers were pissed off that they were letting Trump rail on. Or they were pissed off about Jan six, or they were pissed off about whatever. Whatever the current fad is, the trend is, they respond to the market and they say, you know what? This has crossed the line. And this was the case on public television when nudity came out and they're like, okay, you know what? We need to take that off the TV. We need to because the the market is telling us they're going to boycott us. And I think that there's a market pressure here that we're ignoring that is actually pretty, pretty relevant.

• 1:14:22David Friedberg?

  That as a private service provider, if they're going to lose half their audience because people are pissed about one or two pieces of content showing up, that they're acting in the best interest of their shareholders and in the best interest of their platform. They're not acting as a public service.

• 1:14:36David Sacks?

  Look, I love market forces as much as the next libertarian. But I just think fundamentally, that's just not what's going on here. This has nothing to do with market forces. It has everything to do with political forces. That's what's driving this. Look, do you think the average consumer, the average user of PayPal, is demanding that they engage in all of these restrictive policies, throwing off all these accounts who have the wrong viewpoints? No, that has nothing to do with it.

• 1:14:59Jason Calacanis?

  It has to do with the vocal minority.

• 1:15:01David Sacks?

  Yeah, it's a small, it's a small number of people who are political activists who work at these companies and create pressure from below. It's also the, you know, the, the, the people from outside, the activists who create these boycott campaigns and pressure from outside. And then it's basically people on Capitol Hill who have the same ideology, who basically create threats from above. So these companies are under enormous pressure from above, below, and sideways, and it's 100% political. Hold on, it's not, it's not about maximizing profits. I think it's about maximizing, you know, political outcomes.

• 1:15:33Jason Calacanis?

  Yeah, I don't.

• 1:15:33David Sacks?

  And that is, that is what the American people need to be protected from. Now, I, I will, I will add one nuance to, to my theory, though, which is, I'm not sure what level of the stack we should declare to be common carrier. So in other words, you may be right, actually, that at the level of YouTube or Twitter or Facebook, maybe we shouldn't make them common carrier. And I'll tell you why, because just to take the other side of the argument for a second, which is, you know, if you don't, because those companies do have legitimate reasons to take down some content. I don't like the way they do it, but I do not want to see bots on there. I do not want to see fake accounts. And I actually don't want to see, like, truly hateful speech or harassment.

• 1:16:15David Sacks?

  And the problem is, I do worry that if you subject them to common carrier, they won't actually be able to engage in, let's say, legitimate curation of their social networks.

• 1:16:25Jason Calacanis?

  Yeah, right.

• 1:16:26David Sacks?

  However, so, so there's a real debate to be had there, and it's going to be messy. But I think there's one level of the stack below that, which is at the level of pipes, like an AWS, like a Cloudflare, like a PayPal, like the, the ISPs, like the banks. They are not doing any content moderation, or they have no legitimate reason to be doing content moderation. None of those companies should be allowed to engage in viewpoint discrimination. We have a problem right now where American citizens are being denied access to payment rails.

• 1:16:53Jason Calacanis?

  So wait, hold on.

• 1:16:54David Sacks?

  And to their banking system.

• 1:16:54Jason Calacanis?

  You're saying AWS shouldn't be able to deny service to the Ku Klux Klan or some hate speech group?

• 1:17:00David Sacks?

  I think that they should be under the same requirements the phone companies under. Okay. So when you frame it that way, it's, you know, the question is like, look, I could frame the same question to you. Should, you know, such and such horrible group, should such and such horrible group be able to get a phone, a phone account? Yeah, no, no. And you'd say, no, they shouldn't get anything, but they have that right.

• 1:17:21Chamath Palihapitiya?

  That has been litigated and that's been pretty much protected by the Supreme Court. You know, even if it's a government conferred monopoly, the Supreme Court has said, okay, listen, like, it's not violating one's constitutional right. For example, if your water bill gets terminated without you getting due process. And the inverse is also true. So for what, whether we like it or not, that, Jason, that issue has been litigated, I think. I think, I think for me, again, just like practically speaking for the functioning of civil society, I think it's very important for us to now introduce this idea of algorithmic choice. And I don't think that that will happen in the absence of us rewriting section 230 in a more intelligent way.

• 1:18:06Chamath Palihapitiya?

  I don't know, I don't know whether this specific case creates enough standing for us to do all of that.

• 1:18:14Chamath Palihapitiya?

  But I think it's an important thing that we have to revisit as a society because, Jason, what you described as having a breadth of algorithmic choices over time, where there are purveyors and sellers. Could you imagine that's not a job or a company that the four of us would ever have imagined could be possible five years ago? But maybe there should be an economy of algorithms and there are these really great algorithms that one would want to pay a subscription for because one believes in the quality of what it gives you. We should have that choice, and I think it's an important set of choices that will allow actually YouTube, as an example, to operate more safely as a platform. Because it can say, listen, I've created this set of abstractions. You can plug in all sorts of algorithms.

• 1:18:58Chamath Palihapitiya?

  There's a default algorithm that works, but then there's a marketplace of algorithms, just like there's a marketplace of ideas. I don't discriminate and let people choose.

• 1:19:07David Friedberg?

  This is the decentralized model, like if, if, if it was on a blockchain, if all the videos, all the video content was uploaded to a public blockchain and then distributed on distributed computing system, then your ability to search and use that media would be a function of a service provider you're willing to pay for that provides the best service experience. And by the way, this is also why I think over time to Sax, to, to kind of, Sax and I are both arguing both sides a little bit, but I, I think that what will happen. I don't think that the government should come in and regulate these guys and tell them that they can't take stuff down and whatnot. I really don't like the precedent it sets, period. I also think that it's a terrible idea for YouTube and Twitter to take stuff down. And I think that there's an incredibly difficult balance that they're gonna have

• 1:19:52David Friedberg?

  to find, because if they do this, as we're seeing right now, the quality of the experience for a set of users declines, and they will find somewhere else, any market will develop for something else to compete effectively against them. And so that's why I don't like the government intervening, because I wanna see a better product emerge when the big company makes some stupid mistake and does a bad job, and then the market will find a better outcome. And it's messy in the middle. And as soon as you do government intervention on these things and tell them what they can and can't take down, I really do think that over time, you will limit the user experience to what is possible if you allow the free market.

• 1:20:26Jason Calacanis?

  And this is where the industry needs to police itself. If you look at the movie industry with the MPAA and Indiana Jones and the Temple of Doom, they came out with the PG 13 rating specifically for things that were a little too edgy for PG. This is where our industry could get ahead of this. They could give algorithmic choice, an algorithmic app store. And if you look at the original sin, it was these lifetime bans. Like, Trump should not have been given a lifetime ban. They should have given him a one-year ban. They should have had a process. And because they overreached, we wouldn't be in this position where it is so vitriolic.

• 1:20:59David Sacks?

  But Jason, when you talk about, like, having an industry consortium like the MPAA, what you're doing is formalizing the communication that's already taking place, is already happening between these companies. And what is the result of that communication? They all standardize on overly restrictive policies because they all share the same political bias.

• 1:21:15Jason Calacanis?

  No, but if they did it correctly, it's all in the execution sacks. It has to be executed properly, like the movie industry. It doesn't matter.

• 1:21:22David Friedberg?

  You'll end up with the same problem as having the government intervene. If you have the government intervene or a private body intervene, any sort of set standard intervention that prevents the market from competing.

• 1:21:31Chamath Palihapitiya?

  No, I disagree with you. I think you can create more competition if the government says, "Okay, folks, you can have the standard algorithm, but you need to make a simple..."

• 1:21:41Chamath Palihapitiya?

  Abstracted way for somebody else to write some other filtering mechanism and to basically you so that users can pick those.

• 1:21:47Jason Calacanis?

  Power users, yes.

• 1:21:48David Friedberg?

  I don't like it.

• 1:21:49Chamath Palihapitiya?

  What the MPAA did was.

• 1:21:50Jason Calacanis?

  I don't understand why you don't like.

• 1:21:52Chamath Palihapitiya?

  Why isn't that more choice?

• 1:21:53David Friedberg?

  Because as a product person, as a product company, I don't want to be told how to make my product, right?

• 1:21:58Chamath Palihapitiya?

  You're not.

• 1:21:58David Friedberg?

  If I'm on YouTube.

• 1:21:59Chamath Palihapitiya?

  You have, you have an algo.

• 1:22:00David Friedberg?

  You're now saying that there is this distinction of the algo from the UX, from the data, and my choice might be to create different content libraries. For example, YouTube has YouTube Kids, and it's a different content library, and it's a different user interface, and it's a different algorithm, and you're trying to create an abstraction that may not necessarily be natural for the evolution of the product set of that company. I would much rather see them figure it out.

• 1:22:20Chamath Palihapitiya?

  That's not a good argument. That, again, if, if you were not a monopoly, I, I would be more sympathetic, but because like somebody, somebody's feelings would get hurt, a product manager's feelings would get hurt inside of Google.

• 1:22:30David Friedberg?

  Feelings been getting hurt.

• 1:22:31Chamath Palihapitiya?

  It's not the reason to not protect free speech.

• 1:22:33David Friedberg?

  I'm saying you're unnaturally disrupting the product evolution.

• 1:22:36Chamath Palihapitiya?

  Tough luck. That's what, that's what happens when you're worth $2 trillion.

• 1:22:39Jason Calacanis?

  And when you impact a billion people on the planet. When you start having massive impact in society, you have to take some responsibility.

• 1:22:47David Friedberg?

  Guess what's gonna happen?

• 1:22:47Jason Calacanis?

  And those companies are not taking responsibility if you're not super, super, super successful. If this is not going to affect you, so you don't have nothing to worry about.

• 1:22:54David Friedberg?

  You'll see, you'll see apps offshore, and you'll see TikTok and other things compete because they'll have a better product experience.

• 1:22:59David Sacks?

  No, no, nobody's gonna create a new Google because they're down ranking, you know, 1 to 10% of the search results for political reasons.

• 1:23:09David Friedberg?

  Agreed.

• 1:23:10Jason Calacanis?

  Some accountability.

• 1:23:11David Sacks?

  Hold on, in an ideal world, companies like Google and so forth would not take sides in political debates to be politically neutral, but they're not. You look at all the data around the political leanings of the people running these companies, and then you look at the actual actions of these companies, and they have become fully political, and they've waded into all these political debates with the result that the American people's rights to speech and to earn have been reduced. You have companies like PayPal, which are just engaging in retaliation, basically financial retaliation, purely on, based on what political viewpoints they have. Why? It's not like, it's not like PayPal needs to be in the business of content curation.

• 1:23:47David Friedberg?

  Let's continue this conversation on our next.

• 1:23:49Jason Calacanis?

  We're not gonna solve it.

• 1:23:49David Friedberg?

  Call in AMA.

• 1:23:52Jason Calacanis?

  Well, if they can get some servers over there, I don't know, maybe so you gotta raise some money, Sacks, for this app and get some more servers. All right, listen, for the dictator who needs to hit the loo to do a number two.

• 1:24:03David Friedberg?

  Yes.

• 1:24:03Jason Calacanis?

  I am the world's greatest moderator, Friedberg is the Sultan of Science, and David Sacks.

• 1:24:10Jason Calacanis?

  Is the prince of... Peace. See you all next week on episode... Wait, wait, is this 98 or 99? No, it's 99, it's 99.

• 1:24:20David Sacks?

  Only one episode left.

• 1:24:21Jason Calacanis?

  Wayne Gretzky.

• 1:24:22David Sacks?

  Get it while less.

• 1:24:23Jason Calacanis?

  Enjoy it while less, then we're wrapping it up here. Alright, we'll see you all next time. Have a great movement, Trumah. Bye, bye.

• 1:24:31Speaker 04

  We'll let your winners ride.

• 1:24:34Speaker 04

  Rain Man David Sacks.

• 1:24:38Speaker 04

  And it said, "We open source it to the fans and they've just gone crazy with it."

• 1:24:42Jason Calacanis?

  Love you, S.

• 1:24:43Speaker 04

  The queen of Kinoah.

• 1:24:51Speaker 04

  Besties are back.

• 1:24:54Speaker 04

  That is my dog taking a notice in your driveway.

• 1:24:59Speaker 04

  Oh, man.

• 1:25:01Chamath Palihapitiya?

  We should all just get a room and just have one big huge orgy because they're all just... It's like this like sexual tension that they just need to release somehow.

• 1:25:09Speaker 04

  What? You're the bee. What? You're a bee.

• 1:25:15Speaker 04

  We need to get merge. Besties are back.