DOGE 砍掉第一笔法案、扎克伯格对垒 OpenAI、谷歌 AI 回归，嘉宾亚伦·列维

David Friedberg (00:00:00): J. Cal, what just happened? Did you just have a moment, an emotional moment? Jason Calacanis (00:00:02): I don't know. You know, I've been trying to get over, Sacks, and, it's hard to get over your ex. David Friedberg (00:00:08): Even when they didn't treat you well? Jason Calacanis (00:00:09): We were in a codependent relationship, and we were working on it. David Friedberg (00:00:13): You have no one to fight with anymore. Who are you gonna fight with, J. Cal? That's the emptiness you feel inside because you're a fighter. You're a street brawler, and you have no one to brawl with anymore. So you feel Jason Calacanis (00:00:22): well, you're the first guy to jump under the table in a bar fight. I mean, David Friedberg (00:00:27): there you go. There you go. As I was Jason Calacanis (00:00:28): saying, there's always more to start with. Like, if it if shit goes down, I feel like Sacks and I would have, like we would have thrown down. We're bulldogs. We would have fought like tooth and nail. Okay. Maybe under the table's Fry. Chamath Palihapitiya (00:00:40): I have this I have this I have this image. It's like we're in a bar. Okay? And all of a sudden Jason Calacanis (00:00:46): You talking to me? Chamath Palihapitiya (00:00:47): A fight is about to break out. Four thought bubbles appear. Okay? J. Cal's like J. Cal's like, let's go get him. Sacks is like, this guy this guy's a dip. Let's roll. I'm like, look at that chick. She's so good looking. And then Friedberg's like, what will happen to my invite duck? Jason Calacanis (00:01:06): Friedberg's like, oh, how do I get out of this unscathed? David Friedberg (00:01:09): Yeah. That's Jason Calacanis (00:01:12): right. Go ahead. Alright, everybody. Welcome to the number one podcast in the world. With me again today, for better or worse, your sultan of science, David Friedberg, is back. How you doing, Friedberg? I see you're a pawn, only a pawn in their game. What's going on with the pawn background? David Friedberg (00:01:47): The impostor syndrome. Jason Calacanis (00:01:49): Pawn or queen? What is that from? Is that from a movie? What movie is that from? David Friedberg (00:01:54): It's called the impostor syndrome. Chamath Palihapitiya (00:01:57): By Jason Calacanis (00:01:58): Just like some French New Wave I'm not aware of. For some time, I Chamath Palihapitiya (00:02:01): I've learned that Friedberg's background is some, like, weird secret communication language. There's a small but fervent group of people that are really into these backgrounds. They're always trying to figure something out. Absolutely. Jason Calacanis (00:02:13): Of course, with us again, Chamath Palihapitiya, your chairman, dictator. How you doing, Chamath? Nice to meet her. Chamath Palihapitiya (00:02:19): Thank you, sir. Good to see you. You ready for Excited to see you. Jason Calacanis (00:02:23): I know. Look at this. Three or four besties will be getting in the slopes. Chamath Palihapitiya (00:02:26): Three or four besties will be skiing together. David Friedberg (00:02:28): Might be there. Aaron, where are you going for the holidays? Aaron Levie (00:02:30): Oh, actually, I'm, I'm, will be in next week. Jason Calacanis (00:02:34): What? Well, there you go. New bestie in Chamath Palihapitiya (00:02:36): Aaron, are you staying in the town? In the Aaron Levie (00:02:38): Just at the hotel. Jason Calacanis (00:02:40): Okay. This is perfect. Chamath Palihapitiya (00:02:41): We're all gonna be there, bro. Jason Calacanis (00:02:43): It's $2,000 a night. How many rooms you got with the kids and the fam? You have three? Bro. You have Chamath Palihapitiya (00:02:47): Box is at all-time highs. Jason Calacanis (00:02:48): Make it easier. What did David Friedberg (00:02:50): you get? Jason Calacanis (00:02:50): Did you start buying Bitcoin with your treasury? How what do you mean box is at an all-time high? Are you doing a Michael Saylor or something? Aaron Levie (00:02:56): You know, it turns out if, if you were if you didn't get crushed during the post-COVID period, you can just keep keep cranking. So that's what we've been doing. Jason Calacanis (00:03:06): Oh, you've been building a real business. Of course, with us now, our new fifth bestie, Aaron Levie. He is the CEO of the publicly traded company Box, which means he's got the most to lose by coming here. So welcome back to the program, David Friedberg (00:03:20): Central Sacks. Aaron Levie (00:03:21): Based on what you guys were just talking about before this recording started, I have no idea what we're in for. Jason Calacanis (00:03:27): Yes. Listen. We're living in an age of meme stocks and people selling convertible notes to buy Bitcoin for their treasury and then becoming a Nasdaq 100. It's that simple. Aaron, when you see a company buy billions of dollars worth of Bitcoin and get added to the Nasdaq 100, what method of suicide do you think of taking your own life with? Aaron Levie (00:03:49): There was a brief week in 2021 where the thought kinda crossed my mind. So yes. Jason Calacanis (00:03:56): Seppuku, you're just gonna use the sword, the short blade? Aaron Levie (00:03:59): We have a very sophisticated audit committee that prevented the action. So I, Jason Calacanis (00:04:05): Will you do this for me? Yeah. Just do this for me. Take how much cash does Box have on the books? Ballpark. Aaron Levie (00:04:12): Well, we just did a convert, so we're probably 600 or 700 Jason Calacanis (00:04:17): Okay. Here's what I wanna do. A little experiment for next week. Just put 5% of the treasury, 30 million in Bitcoin. And then you we'll invite you back in two weeks. We'll see what happens. Okay? Just put 5% of the treasury in Bitcoin. Hey, everybody. Here's another announcement, a little housekeeping. As you know, we successfully got the allin.com domain. That was a big victory for us, and we now have an email list. So four years into this, Meshuggana, we now have the ability to take your email address and spam you with all kinds of great information like a notification when the pod drops. Wow. So compelling. Insights from the besties who you've had enough of and first dibs on overpriced event tickets to come hang out with us. Wow. Do you think this is the compelling pitch we have for giving us your emails? So if you'd like to give us your email and get spam, go to allin.com and let the spam begin. Alright. That's out of the way. Sacks is out again this week. I don't know what's going on. We've been trying to figure out where he is. He's MIA. If anybody knows David Friedberg (00:05:22): He's in D.C. this week. Yeah? Jason Calacanis (00:05:24): Oh, is that what's going on? David Friedberg (00:05:25): Did you see all the meetings? I know. I'm Jason Calacanis (00:05:28): being facetious. He's he's, he's in meetings. Mister Sacks went to Washington. He's creating waves, but Mister Sacks is in Washington. And have you guys seen the photos? David Friedberg (00:05:40): Aaron, what do you think of what do you think of Sacks in this role? Aaron Levie (00:05:45): I think it's, I I think it's a strong pick. So so so Jason Calacanis (00:05:51): Let the genuflecting begin. Good. Same for, Aaron. Aaron Levie (00:05:54): So crypto I'm a little bit indifferent on. You know, I haven't, you know, sort of we haven't spent much time there or leaned in much, but on AI, I think it's a very strong pick. And I think you want somebody that is, you know, has a general sort of deregulation, anti-regulation bent at this stage in the evolution of the technology. I think there's risk of sort of slowing down too much progress right now, and I think that I think he'll provide, you know, some good kind of parameters and principles around how to avoid that. So I think very strong. And then, you know, crypto, again, don't know too much about, and then we'll see the rest of the topics. David Friedberg (00:06:38): As a software CEO. Aaron Levie (00:06:39): Yeah. David Friedberg (00:06:40): Of a public company, when the Biden administration was putting forward their proposals on how to regulate AI and have definitions on the size of a model and what the models could or shouldn't do and the regulatory authority they would have over the software that's written, what was your reaction? And you were supporting Harris at the time, I believe, or Biden at the time. Right? But, like, how did you react to that when you saw those proposals? Aaron Levie (00:07:04): And just to be clear, are you talking about the EO that went out? David Friedberg (00:07:08): Yeah. There was the EO, but then they were also drafting. They published a lot of detailed drafting. And then, obviously, California had its bill, which you probably saw as well, which specified, like, the number of parameters in a model, the size of a model, and all these kind of constraints. Aaron Levie (00:07:22): In reverse order, it was against SB 1047. It felt like, you know, you had two big issues. One, you probably don't want state-by-state legislation on this topic. That's gonna be you're in a world of hurt if every state has a different approach to this. And then secondarily, if you just look at how it evolved from the very first proposal to the final proposal, and unfortunately, the kind of underlying philosophy that was in the bill, it was very clearly a sort of, like viewing, you know, basically AI progress as inherently risky right now. And so it just ratcheted up the different, you know, levels of consequence for the AI model developers. And the risk is sort of the second or third order effects of that, which is, like, does Zuck then want to release the next version of Llama if you're taking on, you know, that much risk and, you know, even the incremental updates, the liability you have in terms of any of the model advancements. And so right now, we're benefiting from just an incredibly competitive market between five or six players, and you want them running as fast as possible, not having to have sort of this, you know, a whole council before every model gets released because they're in fear of getting sued by, you know, the government for hundreds of millions of dollars if one person does something wrong with the model. So that was the problem with SB 1047. That's been the problem with some of the proposals on national legislation. I felt like the first CEO, it didn't have a lot of teeth in it. So so it kinda was more like, let's watch, you know, this space and continue to study it. The actual current head of s OSTP, Arti, Prabhakar, a lot of folks in Silicon Valley know her. She's actually very strong, very technical, you know, understands the valley well, is not a sort of does not lean into overregulation. So I actually think OSTP has had a a pretty good steward, even under Biden. Aaron Levie (00:09:10): But I think, you know, the efforts that Sacks would, you know, clearly be leading, I think, would lean even more toward AI progress and not accidentally overregulating too early in this journey. Jason Calacanis (00:09:24): So let me ask you a question then about crypto. You're not into crypto. Crypto is a little bit harder to regulate. So with Sacks being there, what do we think the one, two, or three things he could do to actually make crypto not a scam, not have consumers get left holding the bag, obviously, sandboxing projects, maybe having people know your customer, you know, some basic regulation there. The sophisticated investor test comes to mind. Chamath, what do you think Sacks should do in terms of crypto regulation in the short term and the near term? Chamath Palihapitiya (00:10:01): That's a really good question. I think that today, there are a lot of really valuable use cases that can sit on top of crypto rails. I think the most obvious one is how you can have real-time payments using stablecoins. I think the United States government is already using some of these stablecoins for a bunch of purposes. The number of companies that are beginning to adopt and use stablecoins is actually growing very Jason Calacanis (00:10:32): Take a second to quickly define stablecoins for the audience just to get your people out. Chamath Palihapitiya (00:10:36): Let me define what a stablecoin is, which is that you put a dollar into a wallet somewhere, and in return, you get a digital token of that dollar. There are two big purveyors of stablecoins. There's Tether, and then there's USDC, which is this company called Circle. I think the easiest way to disambiguate them is Tether is abroad. I think it's run out of somewhere in the Caribbean, and USDC is American. It's run by this company called Circle. The other difference is that there is some ambiguity around how these assets are secured. So what a stablecoin is supposed to do is when you give them a dollar, they're supposed to go and buy some short-term treasury security so that that dollar is always guaranteed. Right? Because if you had a billion dollars of stablecoins, but only $900 million of assets to back them up, there's an insolvency risk there. There's a run on the bank risk. Right? So theoretically, a billion dollars of stablecoins should have a billion dollars of cash in some short-term fungible security. What's incredible is at the scale in which these stablecoins operate, that has turned out to be an enormous business. Why? When you give them a billion dollars and get a billion dollars of stablecoins to return, they just go and put it into the bank. And, you know, when interest rates are 2, 3, 4, 5%, they're making billions of dollars. Jason Calacanis (00:12:08): They get the float. Chamath Palihapitiya (00:12:09): They get the float. So these businesses have turned out to be incredible, but that's beyond the point. The point is that a lot of companies that you would never think, so for example, SpaceX uses these stablecoins. How do you think they collect payments from all the Starlink customers when they aggregate them in all of these long-tail countries? They don't want to necessarily take the FX risk, the foreign exchange risk. They don't want to deal with sending wires. So what they do is they'll swap into stablecoin, send it back to the United States, and then swap back to U.S. dollars. So it's a very useful utility. So number one is I think we need to make those rails the standard rails in the United States. And what that does is it allows us to chip away at all of this decrepit infrastructure that the banks use to sort of slow down and tax a process that should never have been taxed. Jason Calacanis (00:13:01): In some good competition in a way, Chamath. It's incredible. Now the banks have somebody to challenge them for money transfer and money storage, and it could be regulated and stable. But I guess so. Chamath Palihapitiya (00:13:13): But that's the first thing. But then the second thing it allows you to do is you can see a world where now you can have real competition against the traditional rails, specifically Visa, Mastercard, American Express. Because when you look at great companies like Stripe, I use Stripe, I pay them 3%. If I use stablecoins from Stripe, I don't pay 0, but I don't pay 3%. It's kind of somewhere in the middle. If I was technically adept at implementing stablecoins through the entire stack of my product, so I use it for this learn-with-me thing where we publish research, I would save a lot of money. So yes, the idea that you can take that 300 basis points you pay to these companies and crush it to 0 would be a boon to global GDP because that's 3% on many tens of trillions of dollars. Jason Calacanis (00:14:06): Aaron, you're shaking your head. This is something that you're experimenting with at Box or you're aware of or a problem that you recognize? No? No? Just the... Aaron Levie (00:14:14): mean, the credit card rails, I mean, the tax on transactions is obviously insane. So the stablecoin being the intermediary for that in the future makes total sense if you could get everybody to kind of coordinate against that. So yeah. Jason Calacanis (00:14:28): Well, regulating it would get people off of Tether, hopefully, which has a checkered, colorful, sordid past. You can go look it up, but they've had many, many legal... Chamath Palihapitiya (00:14:37): But I think, again, I think it looks like there... then I'll leave it at that. Jason Calacanis (00:14:40): Yeah. Chamath Palihapitiya (00:14:40): Yeah. But in fairness to them, I think, again, both of these two companies look as of today... Again, you have a jurisdictional issue difference, but as of today, it looks like they're both pegged one for one. But anyways, the point is if Sacks can really push the adoption of stablecoins, number one. And then number two is to incentivize much, much cheaper transactional rails. Then I think he can go to Bitcoin and these other more long-tail crypto projects off of the back of momentum. Because these first two things, I think everybody will embrace and he won't get caught in a political quagmire. These other things, you have these opponents always coming into the system and they have even Bitcoin. Like when I said this thing about encryption and quantum. And even though I, I thought I was very clear, the crypto community on the internet went absolutely crazy all last week. Yeah. Up and on. Yeah. But the thing is like some of the maxis piled on, then when they actually took time to understand the technicalities of what I was saying, other people realized that was right, that they were tweeting it. My point is that world is so religious. Animated and energized that I think it's hard to use them as the first place where you find progress. So I would tell Sacks, got it. Go to stablecoins, then disrupt the Visa rails and then go to the other stuff. Jason Calacanis (00:16:05): I would go stablecoins, and I would go even before that the accreditation test that I've been talking about because the SEC has that mandate. If people were educated, Aaron, they could buy crypto and know they're gonna lose their money or know that something's so fugazi or fugazy, whatever it is. Aaron Levie (00:16:22): Yeah. I mean, I'm sure we wanna move on, but I guess there's a parallel universe where no matter what, obviously, Gensler did not get his arms around this whole thing, so that was a big mistake. But there's sort of, like, DeFi slash financial crypto where almost everything is deflationary. It improves the rails. If you believe in Bitcoin as this store of value and digital gold, all of those things can actually kinda make sense and be a bit rational and improve things. And then, you know, unfortunately or not, depending on your views, there was this other sort of fractal event that happened, which was, oh, let's also use these things as a means of creating a virtual currency and token equities and tokens for anything where that then runs into basically the SEC remit of, like, are these things securities or not? And is there insider trading or not? And can anybody issue them at any time and promote them on Twitter or not? And so, you know, I think to some extent, if you could get back to, like, crypto 1.0, which was like, this is a financial infrastructure. I think you would have avoided a lot of the sort of noise and challenges with crypto. Now, I don't know. You can't put the, you know, you can't put it back in the bag, but, but there's, like, I don't think you could get 10 crypto people to agree on how you regulate that second category because Jason Calacanis (00:17:49): Absolutely not. Aaron Levie (00:17:49): Some people believe I should be able to issue an NFT on anything, and I should be able to trade that. And at the same time, they would obviously sort of claim, well, that's just the same as an aftermarket, you know, seat to a concert. And yet another group would be treating this as effectively, you know, a security. And so I don't know how you're ever gonna reel that in without some people being upset, you know, within the crypto community. Jason Calacanis (00:18:15): Alright. Well, more to come, and Sacks will be back. Sacks will be back, and we will be rotating the fifth seat amongst, you know, friends of the pod and newsmakers. Aaron Levie (00:18:25): Sorry. Did I already get rotated out, based on Jason Calacanis (00:18:28): Well, yeah. Basically, the energy was a little low, but, you know, I mean, it's just I think well, what's your Aaron Levie (00:18:34): You already had to warn Jason Calacanis (00:18:35): me this heart rate? What's your resting heart rate versus Verboise? And then we'll just make a decision. Okay. Aaron Levie (00:18:40): I got it. Jason Calacanis (00:18:41): I got it. Alright. Listen. Doge is fully operational. Elon and Vivek have helped kill the last-minute omnibus spending bill. Wednesday night, the bill had been killed, and we were looking at the government shutting down starting Friday, December 20, today when you were listening to this. For some quick background, in September, Congress approved a bill that would keep the government funded through December 20, the day this episode published. Keep that December date in mind for a second. This Tuesday, December 17, three days before the deadline, leaders in Congress unveiled what was presented as a bipartisan stopgap bill that would keep the government funded through March 14. That kind of bill is called a continuing resolution. Basically, it'll give you more time for the incoming GOP majority to reach an agreement on the funding for the government. But there are two major problems with the bill. It's a rush job. It had to pass the House and the Senate by Friday night after being presented on Tuesday. It's absurdly long, 1,500 pages, with $340 billion in spending, including pay raises and better health care benefits for the members of Congress. My lord, read the room, gentlemen and ladies. Funding for a global engagement center for another year. That's the disinformation watchdog group that was wrapped up in the Twitter files, $130 billion to renew the farm bill for another year, $110 billion in hurricane disaster aid, just money being thrown everywhere, $1 billion to replace the Francis Scott Key Bridge in Baltimore. Vivek had some spicy comments on it. Congress has known about the deadline since they created it, in late September, he said. The urgency is 100% manufactured and designed to avoid serious public debate. But serious public debate is exactly what's happening on Twitter. People are screenshotting and using ChatGPT and Claude and Gemini to work their way through these documents, and it looks like this is not gonna happen. Jason Calacanis (00:20:40): Friedberg, your thoughts? David Friedberg (00:20:41): So the proposed bill made no real change to the current spending level of the federal government at roughly $6,200,000,000,000 on an annualized basis, which, by the way, is roughly, call it, 23% of GDP. Just to give you some context, in 1860, nearly 100 years after the founding of the United States government, federal spending to GDP was less than 1%. And it took off during the Civil War, for a couple of years, but, you know, we're at these kind of, like, unprecedented levels year after year now, really speaking to how the federal government has grown as we talked about many times so much in our life. And, you know, at some Aaron Levie (00:21:25): Our roads were really bad back then, though. David Friedberg (00:21:27): Yeah. Yeah. Our roads were really bad back then, but lots Jason Calacanis (00:21:30): of problems. Yeah. David Friedberg (00:21:31): But remember, the objective of the republic was to have the states make local decisions about how to take care of their infrastructure. The national highway effort obviously changed that in the mid-20th century. But this was kind of the original intention of the republic. It wasn't to have the federal government come in and employ people, provide insurance to people, provide energy markets to people, own football stadiums, etcetera, etcetera, etcetera. You go through the list of things in this bill. I think the $100,000,000,000 of natural disaster relief, everyone says that seems very reasonable. That's something the federal government should do. When we have a natural disaster, we need help. We need support. That's a great thing for the federal government to do. But think about the incentive it creates. It distorts markets. So we've talked about this in the past. In areas where you have a higher probability of natural disasters and people have paid a lot of money for their homes, pay a lot of money for infrastructure, should the federal government come in and rebuild those homes and provide capital to those individuals and those businesses to help them rebuild those homes if there's a high probability of natural disaster events happening again in the future? It means that the cost of insurance doesn't matter, and the cost of real estate doesn't matter because the federal government effectively can come in and support those prices. In the same way, the federal government comes in and supports the prices in agricultural products through the work in the farm bill and through the biofuels mandates, which were also proposed to be extended in this thing. So the federal government's playing both a market role and, you know, also kind of this role that I think fills the gap where people wanna have a customer where there isn't a customer and an employer where there isn't one. So, like, how did we get to this point? So to a first principles perspective, we've kind of, I think, lost the narrative on what the federal government was meant to do. If you think about the simple rubric in a bill, like, just go back some period of time and someone says, hey. David Friedberg (00:23:21): I want something. I wanna have this in this bill. And you're the representative that's supposed to vote on that bill and say yes or no. It's very hard to just say, no. We are not gonna spend that money. What's the incentive to say no? The alternative is you say yes, but give me X as well. There is an incentive in that response. And the incentive there is to get something for your electorate, the people that voted you in as a representative of the House, which is how we ended up at this point where everyone says, I want something if you're gonna get something. And, eventually, the federal government swells to spending roughly 24% of our GDP. Now the biggest mistake I think the Founding Fathers made was that they didn't create constitutional limits on spending and enrichment. And this was because they had these deeply held philosophical beliefs that relied on the House of Representatives to provide a check by the people. If you read The Federalist Papers, and I went through a couple of these recently and I used ChatGPT to help me kind of, you know, bring out some of, I think, the key points. But in The Federalist Papers 10 and 51, James Madison emphasized that the structure of government was meant to ensure that both state and federal governments would limit each other's excesses, including their financial ones. And then in The Federalist Paper number 58, he said, the House of Representatives has control over the, quote, power of the purse, which gives the people's representatives authority over taxation and spending. But they also warned along with Alexander Hamilton of the dangers of unchecked government power through burdensome taxation and excess spending, which would ultimately erode individual freedoms. So they recognized that there were gonna be limits, but their expectation was that the House and the individuals that were electing people to the House that were members of this republic would come in and say, we're gonna keep that from happening. And, clearly, something went wrong along the way that we got to this point where, again, spending is 24% of GDP. And I think that the biggest thing they got wrong was that they didn't create these constitutional limits on federal spending or taxation through either a balanced budget, structure, spending as a percent of GDP, no federal debt or term limits, or all of these other mechanisms that could have been introduced at the beginning that could have created some structural limits. Instead, they assume that there was this natural limit that would emerge as a function of the democratic process because of how they formed the government. David Friedberg (00:25:43): But, unfortunately, I think they failed to realize that the electorate would eventually not want the freedoms of the people of the time. Back then in 1776, this was a pioneering country where everyone wanted to come here to have freedom to do anything they wanted, everywhere they wanted to build a business, to homestead, to be rugged individuals. It Jason Calacanis (00:26:06): was entrepreneurial. Yeah. It was. And over David Friedberg (00:26:09): the last 250 years, we've gotten used to an increment in lifestyle every year and discovered that we have a mechanism to force the increment in lifestyle through the actions of government. And so the electorate has stood up and said, I want more each year and I want the government to provide it for me if the free markets are not doing it. And that's really where we kinda got to this point where I think we elected people to the House who ultimately had this incentive that said, if I give you this, I need to get this. And we ended up swallowing this. So I don't know if it cracks with Doge. I really don't know if people step up and recognize the limits of government and what the limit should be of the federal government on an electorate basis. It's an amazing moment to see that Elon went on Twitter and said, hey, guys. This is nuts. And everyone said this is nuts. We're not gonna elect you if you do this. If that momentum and that transparency can keep up, I hope that people start to connect the dots that this isn't a free lunch, that the federal government spending is not limitless and it's not unaccountable. Jason Calacanis (00:27:05): Aaron, I think we have enough people who are notable now speaking up about this excess spending and the out-of-control debt, that it's now in vogue to talk about austerity, to talk about inefficiency. And that really all comes back to Doge and, dare I say, you know, the conversations we've been having on this podcast for two years that this is becoming acute. What are your thoughts on this vibe shift, this complete pivot? Yeah. Where we've gone from, my lord, everybody's saying, I gotta get mine. You got yours. I'm getting mine, to name and shame. They're naming and shaming now very specific pieces of pork in these bills, you know, including stadiums for the NFL. And people are like, why is the NFL getting this if they're worth $20, $30, Aaron Levie (00:27:55): Two just quick thoughts. One, Patrick Collison had a tweet yesterday that basically said this sort of this big misinformation kinda created by people that wanna be slow is that you have to sort of choose two of fast, good, and cheap. And I think basically, you know, Elon's companies have sort of always effectively kind of proven the opposite, which is actually, if you just, like, start to ask the question, like, why does that thing have to cost as much? You know, if you're building a rocket or designing a car or developing batteries, like, why, you know, if you just do ground up, why does that have to cost as much? And so what's interesting is that probably if most people looked at what the government was spending on, they wouldn't even feel like, you know, it's not even helping them in, like, the disaster relief sense of, you know, I think, like, that either probably actually people that actually do experience the benefits of disaster relief. It's actually just all of the overhead that we've created to getting anything done in the government that could actually make the government better serve all of the constituents. I was talking to, you know, sort of a nameless individual in the government the other week where by Congress, they have to hire contractors to do work, and the contracting firms charge them two and a half times the sort of cost of an individual employee that they could otherwise hire. And so now they have to outsource the work, and they don't have any accountability mechanism for that contractor. And so I think there's not a single American that could look at that and say, and say, this is actually working well. Like, yeah, we are spending more money to do less. And the ultimate outcome is actually lower quality. And so you have to, at some point, just kind of do a little bit of a reset moment. And that's obviously the upside of DOGE is like, it's like it breaks every rule of us thinking about how you would actually go and attack this problem. We thought you'd attack it through meetings, and we would do it through congressional processes and research. Aaron Levie (00:29:54): And it's actually just, it is, you know, obviously a much more sort of founder startup oriented way to approach this. There's gonna be lots of things that are broken glass around the edges. There's no question. But I think what's interesting about this week's event is I think that there's been this underlying kind of notion of, like, you know, Elon and whatnot at all, you know, don't understand the government enough to be able to change it. And it might actually be the case that the government doesn't understand Elon in the sense of, like, he will just see this thing through, and the tools at his disposal and Doge's disposal are sort of, you know, completely unprecedented in terms of the ability to put anybody in Congress on notice if, you know, if basically they are promoting things that are not making the country better. So the, you know, the thing that we saw this week was actually that playing out. Everybody's been wondering, well, what are the actual, you know, what are the formal mechanisms Doge has to accomplish and enact change? And it's like, you just saw it. Like, they can just create enough visibility and spotlight on the problem that it causes a level of discomfort in supporting moving forward with whatever that thing is. And so I think it's interesting. I have no opinion on the actual elements of the bill other than from a process standpoint and a new kind of case study of how this is gonna play out is I think we're seeing some early indication of what Doge will be able to do. David Friedberg (00:31:17): Aaron, how do you feel about this Doge effort as someone who is a public Harris supporter? So you've come out. I think you've been public about this. But I wanna understand, like, why people wouldn't be supportive of this effort. Right? Like, what is, like, what is the motivation for people saying this isn't a good thing. We shouldn't be doing this. Like, because there's a lot of folks that have gone on these shows. It's like they blast Elon. They blast Vivek. But, like, aren't these principles, like, shouldn't they just be universal that we should not be wasting money and stuff? Jason Calacanis (00:31:51): Sure. Of course. Aaron Levie (00:31:52): I mean, so to give some credit, you know, you have Ro Khanna supporting it. You have Fetterman supporting it, Bernie Sanders. You know? Everybody has Bernie David Friedberg (00:32:00): Yeah. Bernie Sanders had a good call out for Elon. Aaron Levie (00:32:03): Everybody has their thing in the government budget that they don't like. So assuming that they see that as something Doge can contribute to, you could probably get actually broad support. You know, there's a classic reflex within probably the Democratic Party at this point, just because of Elon's support of Trump, that if something is an Elon project, they're certainly gonna instantly respond no matter what the thing is as a negative without actually saying, does this actually support something I do agree with? And so that's just It's Jason Calacanis (00:32:34): all partisan. None of it's first principles. Right? And which is for these people, but this group of people, which isn't everybody. That's gonna be Aaron Levie (00:32:41): true of both sides. Like Michelle Obama, Michelle Obama was like, let's get kids healthy. And all of a sudden now it's in vogue to do that. So, I think we're just in an environment where anything will become partisan. What's interesting is that because of some of the cross-party elements of Trump and now his cabinet, it might pull in more of the Democratic Party than would usually happen. And I think because of Elon and the people that are surrounding Trump, you probably have a bit more air cover for the Ronas of the world to also step up. Because if it was like Steve Bannon and Trump doing Doge, it would be like, ah, okay. You know, maybe this is not the thing to lend credibility to for pure political reasons. If you have some of the best entrepreneurs that are out there actually, like, literally in the cabinet driving this, at some point, it is an IQ test if you're on board or not. Jason Calacanis (00:33:34): Chamath, this is a sea change that we're seeing. And to Aaron's point, this administration gets to pick their priorities, but everything can't be a priority or it's not a priority. Therefore, they've picked the priority of smaller government, more controlled spending over, say, mass deportation or removing more rights from women to choose when they have an abortion, etc. So this seems like a distinctly different focus for Trump 2.0, the second term. What are your thoughts on what we saw this past 72 hours? Chamath Palihapitiya (00:34:05): In relation to this bill? It was the most incredible change in how politics will be done going forward. I think that people are probably underestimating what happened here. This was a multi-$100 billion grift that was stopped on a dime over 12 hours of tweets. You would have never thought that that was possible. The point is to put a dagger in something that big that had so much broad support just a few hours earlier. I think it's so consequential in how the United States can run going forward. Jason Calacanis (00:34:48): So building on what you said, Chamath, also very interesting here is the fact that Trump hasn't taken office yet, and they're having this huge impact. This is occurring a month before he's even in office. If they can stop this, what will they do when they actually are in power? Chamath Palihapitiya (00:35:04): I think right now, you're seeing the first-order reaction, which is about the bill itself, and I think that misses the point. The bigger issue is going forward, you will have the ability to, and part of it is because we have a set of tools now that allows us to do this, to read 1,500 pages in a matter of minutes, to summarize it into the key essential elements, to really understand what's being asked and what's being offered, and then to put it in a digestible format that normal people can consume. Yes. Then all you'll have to do is just connect the dots and tell your congressman or congresswoman that you'd like or dislike this thing, and what you're gonna see is a much more active form of government. And I think that's the really big deal. The fact that it's it really becomes the voice of the people. Now the alternative can also happen. Imagine there is a piece of legislation that is very controversial, but it turns out that people actually want it. Then the opposite will also happen and can also happen now. So I think that it's a very nuanced and interesting way that governance can happen. The other thing that I'll say though, which is funny, is we should have a segment called today in hypocrisy. And if I was running the segment, what I would say is today in hypocrisy, you have a group of people, i.e. the Democrats, who are very upset and who now point to Elon as sort of like some shadow cabinet minister or some shadow president-elect or some shadow first buddy. Right? Jason Calacanis (00:36:39): First buddy. Yeah. I love that. Chamath Palihapitiya (00:36:41): Except then I thought to myself, well, hold on a second. Like, there was, like, something untoward happening in the shadows, and I thought, well, actually, actually, this is the exact opposite. The guy is tweeting in real time his stream of consciousness. You absolutely know everything that he wants because he just lays it all bare. And at the same time, I thought it was really interesting. The same people who were saying that were the ones that finally admitted that they were hiding Biden for the last two years. Mhmm. And I thought, did we just miss this? Like, the same people that are like, hold on, Elon. I don't like the fact you're telling us what you actually want on Twitter transparently while we hide our president of the United States in a box. Jason Calacanis (00:37:21): Well, yeah. So you're referring to a Wall Street Journal story that broke, Chamath Palihapitiya (00:37:26): think this week in hypocrisy, Jason. Take it away. Jason Calacanis (00:37:28): Yeah. I mean, it was just, as we said on this pod, we knew that they were hiding him. Now the cover-up is worse than the crime and the cover-up is a cover-up. They were not letting him take meetings. They were limiting access to him. Dean B. Phillips came on this program. Shout out to him. Congratulations on a great run. You know, he he just told the truth here. He's not up for it. He's sundowning, you know, terrible situation. People get old, and people have cognitive decline. The end. Chamath Palihapitiya (00:37:59): Question. Hold on a second. So just to get contrast and compare. Trump is not even in office. You know? Elon is not a member of the Cabinet per se. These are effectively today still private citizens. When there's all of this noise about what happened over the last two days to stop an absolutely ridiculous pork barrel bill. But when are we gonna double-click into what decisions have been made in the last two years that were actually Biden's versus surrogates that just decided? And who gave them the authority to make those decisions? Jason Calacanis (00:38:30): If they're gonna do, Aaron, and you and I are left-leaning moderates, I think that would be the most accurate way to describe us. I mean, if they wanna do an investigation, there should be an investigation to did they know that he was in massive cognitive decline and let him stay in charge of the nuclear codes? Do you agree or disagree? Aaron Levie (00:38:50): This is, this is sort of not the part of politics I think about as much, so I'll leave that up to you as the other less-leaning moderate. So yeah. Jason Calacanis (00:38:58): No. I just wonder if, like, this is a crime that they like, what if it turns out he actually has Parkinson's or Alzheimer's? Like, a diagnosis. It's not out of the realm of possibility that they covered up an Alzheimer's diagnosis, Chamath. And if they did, is that criminal? I mean, it's unethical. Chamath Palihapitiya (00:39:18): It's deeply unethical. Yeah. It's very dangerous. Yes. Again, it just goes back to the people elected Joe Biden. He won fair and square. He ran on a specific mandate that the people endorsed. I just think it's devious though that certain figures in that White House Jason Calacanis (00:39:38): took Chamath Palihapitiya (00:39:38): a level of power and decision-making authority that they were never entitled to. If they wanted that, they should have run, and they should have been elected. That's what we all sign up for. And so I think that that idea that we let that happen or that that happened to the American voting public is, I think, very unfair. That's why I think you have to realize that, and you've said this before, we need these checks and balances going forward. And I think the way that you have these checks and balances again is to veer towards transparency. The more transparency there is. And, again, this is where I'll say, you may or may not like Donald Trump, but the one thing you will never have to be worried about is whether you will not be able to hear from him in first person. David Friedberg (00:40:26): You're gonna hear from him. Chamath Palihapitiya (00:40:28): That is absolutely true. I mean, simple suggestion here, Chamath. If you're ever in doubt, you will be able to know very quickly where he stands on whatever topic is important to you. And I think that that idea is very important because then if it's filtered through somebody else because of some health issue that's then covered up, we're making decisions that impact the entire world. We're making decisions that impact the economy. We're making decisions that touch hundreds of millions of American lives. Who are making those decisions? Jason Calacanis (00:40:58): Yeah. It's kinda crazy. I I Chamath Palihapitiya (00:41:00): have a simple suggestion here Jason Calacanis (00:41:01): with these bills, by the way, when they're 1,500 pages. How about for every 100 pages you release, you have one day of review? So if you wanna release 1,500 pages, 15 business days of review, does that sound reasonable? Maybe three weeks and then just stop doing 1,500 at a time. Break these things up into 200 or 300 pages at a time. I just love the fact that people are motivated and they have the will and the desire to focus on these focus and desire because you people have to have the will and people did not have the will to get in the weeds and examine the spending. And now it's becoming, like, in vogue. It's becoming a pastime to question the spending. This is a really great moment in time for America. Chamath Palihapitiya (00:41:42): The other thing, Jason, that we haven't done is I think that killing the bill was step one. Mhmm. The thing that America has not yet seen, and I think Aaron brought this up with the Patrick Collison tweet, which is just excellent, Nick, if you just want to put it up there. It really is true. America still believes that the more you spend, the more you get. We do at the core. That's why there are 1,500 pages of spending in here because people want things because they want things to be better. What we need to train people to understand is actually that it's the lies that are told that make you think that with more money comes a better outcome. Jason Calacanis (00:42:22): And we... Chamath Palihapitiya (00:42:23): see every day in Silicon Valley, we all start with next to nothing as a startup, and we outmaneuver and we out-execute companies all day long with way more resources. So it has nothing to do with the resources. Jason Calacanis (00:42:35): Constraint leads to great art. Aaron, your thoughts? Aaron Levie (00:42:37): No. I mean, I can't add that much more to this. I think there's probably a little bit of a disconnect at times from the, let's say, the voting public and, you know, broad constituents from those that have sort of seen this in real life being inside of a company, having to, you know, do a startup and scaling up and just this, the perverse incentives to build bigger teams, spend more, your project then is more important the more dollars it gets. We have all of these systems in place, which is the stuff that gets attention are the things that you spend more on. So you have all these weird incentives to actually have your thing literally cost more, to have, you know, more overhead because you've brought in more contractors into the project that then, you know, you're gonna get some, you know, kind of future benefit from in some way. So you have a lot that is sort of fully broken in this, and there's no, you know, it's hard to imagine any other way to veer off from that path other than something that does shake things up, you know, as much as Doge is doing. Jason Calacanis (00:43:39): Alright. Listen. We can't do any worse than being massively in debt, so just let's have a culture Chamath Palihapitiya (00:43:44): of yes. We can. No. Yes. We can. You could have you could have runaway debt. David Friedberg (00:43:48): Yeah. I think we have Jason Calacanis (00:43:49): I think we already have that. I mean, this is for people who maybe are rooting against Trump in the audience or rooting against this because they're super partisan. All I'll say is I know these individuals around Trump. Root for them and root for this process, please, because this is a path to fixing the most acute existential problem we have, which is our debt. You don't have to like Trump to like Elon, to like Vivek, and to like these other individuals, Sacks included. There are great people who are being called to serve. Let's judge them based on their performance. That's all I ask for the people who hate Trump, who hate these individuals. Judge them on their performance. They've come out with a bold plan. Let them cook. Once they've cooked, then judge their results. That is what I'm telling everybody who hates Trump and who hates this administration and who's partisan on the other side. Let them cook, judge the results. Aaron Levie (00:44:42): I'll just throw out one more thing on this because I think Doge has the branding of Doge is often the efficiency side, which people always go to the spend side. But the corollary to that is the regulations that obviously are expensive to maintain, and that's what creates layers and layers of overhead on reviewing everything that's coming in to the government. And, you know, unfortunately, we have great examples in California where literally we spend more to do less. And it's because we've ratcheted up these layers and layers of regulation. And I have friends literally doing climate tech, in like climate tech, you couldn't imagine something more probably left-leaning Democrat that they can't actually get things done in California, the state that you would imagine to be the most kind of climate-first friendly state because of the amount of regulation that prevents them from getting things done. So, you know, there's actually this total combination of actually fewer regulations. You'll spend less money in government. You'll actually grow the economy faster, which will create more jobs. Like, all of the things get solved the more efficient you get, you know, kind of, you know, writ large on all of the topics. Jason Calacanis (00:45:54): So this is spending. Great point, Aaron. Regulation's next. Let's see what they do there. I was in the room when Antonio Gracias was doing zero-based budgeting at Twitter, now X, and Sacks and I were looking at roles for people. What this team can do in terms of making things more efficient, it's amazing what can happen when you do zero-based budgeting and when you just think from first principles, well, do we even need to do this? Does this need to exist? Take all these regulations. Put a 20-year clock on half of them, a 10-year clock on the other half. Aaron Levie (00:46:29): Can I just get one more random example? Feel free to edit it out. Chamath, you like this because it came out of Meta. Have you followed the Zstandard compression library from Meta? So this open-source library kind of a need to get a next-gen compression on data. And we finally, it took us, you know, probably too long, but the team worked insanely hard, implemented this compression algorithm. We literally, our uploads and downloads got faster. We spend less money on networking and compute. And, you know, it took some re-engineering of the system, but like it, like, that's just not a concept that people go into problem-solving with, which is like, what if the thing actually was cheaper to run and it was better? And so think about all the systems of government that could be, that could just be upgraded and then you would spend less money actually maintaining them. I mean, we spend, you know, hundreds of billions of dollars, way, way too much on legacy infrastructure, technology. We could automate more. You could spend way less money and then get better outcomes. So this is just happening everywhere, and I don't think people realize the scale of the opportunity. So Jason Calacanis (00:47:27): And I'll just give an example. When we went into Twitter, nobody was coming to the office. There were people who hadn't committed, who hadn't come to the office, who hadn't committed code in six months. So what were they doing, right? So you start looking at the data. Then they were spending an enormous amount of money on SaaS software that nobody had logged into. And then they had desk software to route people around. That was costing $10 per day, per desk, per, you know, location, whatever. Nobody was coming to the office, but they were paying for software to route people to the right desk in office suiteing. The waste, when I tell you the waste and the grift, and I'll just call it what my interpretation is stealing, they were stealing from those shareholders. The government is stealing from taxpayers. It has to be fixed. Let our boys cook. Friedberg, you get the final word before we go on to conspiracy corner. You got nothing? Alright. Let's go straight to conspiracy corner. Everybody put your tinfoil hats on. There are drones over New Jersey. Thursday morning, the FAA banned drones. This is breaking news in parts of New Jersey until January 17 due to, quote, unquote, breaking news, special security reasons. They also warn that the government may respond with deadly force against drones posing a threat. This thing is getting crazier by the day. There have been thousands of reported drone sightings in New Jersey and bordering states over the last week. Here's some examples. Play the clip, yada yada. Until Thursday morning, White House officials have been dismissive, saying repeatedly that nothing significant is going on. One of the theories was that the drones were looking for nuclear material, aka a dirty bomb or lost radioactive material or, the ultimate, a lost nuclear bomb from, like, an actual nuclear warhead from Ukraine. On Tuesday morning, the mayor of Belleville, New Jersey, suggested the drones could be looking for that radioactive material that went missing on December 2. Jason Calacanis (00:49:26): That was radioactive material, germanium-68. We'll get details on that from Friedberg in a moment. And then, of course, conspiracy theories are going wild. It's Iran. It's UFOs. And my favorite, Project Blue Beam, which is that NASA is using holograms and other technology to create a new world order and religion and projecting Jesus into the clouds. You can look that stuff up, or we'll have Alex Jones on, in Sacks' seat one week. Okay, Friedberg. You're the genius here. Tell us what's going on. David Friedberg (00:49:56): I think there are three likely explanations. The first is that the government's got some activities that can't be disclosed, so we don't know and they can't talk about it. No one can either, you know, say yes or say no to it. So, you know, that's kind of one that's pretty possible. The second is these are just individuals with a bunch of drones messing around, having fun, trying to wreak havoc. Could be fun. Bunch of kids. I think we've all been there. The third is what I would call kind of a bit of a more nefarious, like, this is my conspiracy theory. I think it could be considered a psyop. Okay. So right now, the U.S. has a significant regulatory burden on drone utilization in a commercial setting. And it's very hard to use drones. You have to have line of sight to the operator. These things aren't supposed to go on their own. There's all these rules and restrictions and so on and so forth. Meanwhile, you've got countries like China rocketing ahead. So I don't know if you guys know the company Meituan in China. You know, the food delivery company? Mhmm. Have you guys did you know that they do a large amount of drone delivery of their food now? Jason Calacanis (00:50:59): I was not aware of that. Yeah. We're testing that here in the U.S. David Friedberg (00:51:02): Yeah. The drone delivery business in China is already $30 billion a year. And they're also launching a pretty significant fleet of what we would call kind of the eVTOLs or flying cars. The expectation is that by 2030, there'll be 100,000 flying cars moving people around in China. And these are huge efficiency gains. In fact, with Meituan, you can now order food while you're on the Great Wall at one of the ramparts, and the drone will bring the food to you while you're walking the Great Wall as a tourist. And in the U.S., the reason that these things haven't taken off and the reason we don't have a large kind of drone industry, which is clearly emerging, is gonna be a huge economic driver for China and others around the world, is simply the regulatory restrictions. And so if you were gonna try and mess with the U.S.'s ability to move forward with the drone economy, you would probably try and wreak some havoc, stoke some fear, and get people to say, hey. This doesn't seem cool. What's going on? I don't like that there's all these drones in the sky. I'm freaking out. And try and get the regulators to come in and say, hey. We're banning drones. And set up everyone, including the people in the government to say, we should take a beat. We should think a little bit before we deregulate. We should Jason Calacanis (00:52:14): Who would do this? Who's the motivation? Uber Eats and Postmates? David Friedberg (00:52:17): No. No. No. No. No. It could be the other government. That's my psyop point. This could be your psyop. Jason Calacanis (00:52:24): This could be China doing this to start to David Friedberg (00:52:25): slow down our economy? Think about it. If you're gonna pass a bill in Congress to make drones more freely roamable in the skies, you're gonna reference back this crazy story in New Jersey. Everyone's freaking out about it. And you're gonna say, hey. Wait. What about all that stuff that happened in New Jersey? Maybe this doesn't make as much sense. People are kinda scared about it. We shouldn't rush. We shouldn't rush. We shouldn't rush. That would be my psyop theory. That's my, you know, kind of conspiracy theory tinfoil hat. I don't often do them, but that's what I would kinda think about. I think the first two are probably more like Jason Calacanis (00:52:53): Alex Jones would be proud. Aaron, why don't you jump the fence and tell us your best conspiracy theory in this? Aaron Levie (00:52:59): No. No. I'm not. I this is that that was all crazy pills, but I just heard, Jason Calacanis (00:53:03): there there Yeah. Take some. Aaron Levie (00:53:05): I think there's, like, there's, like, 10 higher psyops you would do if you wanted to to get us to, you know, have a collapsing economy than going after drone deliveries. But, no. I What David Friedberg (00:53:14): would they be? What would they be? Jason Calacanis (00:53:16): I mean, well, first of all, Aaron Levie (00:53:18): I think you'd have AI, like like, do a robot like, David Friedberg (00:53:20): conspiracy corner. Aaron Levie (00:53:21): I think you'd have a robot AI thing that goes, you know, runs amok, waste in the airways. Rogue robot, Robocop. Jason Calacanis (00:53:27): Yeah. Aaron Levie (00:53:27): Yeah. I I think that'll be way sooner than you Jason Calacanis (00:53:31): worry about food delivery. No. You have 10 self-driving cars hop the, you know, hop the curb and and crash into a storefront. Self-driving is on ice for two years. That would be, you know, an example. Chamath, your thoughts? You you got some conspiracies here. What do you think is going on here? Chamath Palihapitiya (00:53:45): No. But I thought that the most credible thing was that they were looking for radioactive material that somehow got lost and Jason Calacanis (00:53:56): Why would they only look at night? Actually, it's interesting you say that. There was somebody on Twitter, X, who claims to be an expert in this field, and there's a startup actually that I just talked about on Chamath Palihapitiya (00:54:07): Which one? Kanekoa the Great? Jason Calacanis (00:54:08): I think it might have been Kanekoa the Great. Shout Chamath Palihapitiya (00:54:13): out to Kanekoa the Great in his mom's basement eating pizza bites. Hate Kanekoa. He's a nice man. Kanekoa. Aaron Levie (00:54:15): I told Chamath Palihapitiya (00:54:16): you. Kanekoa. You always Jason Calacanis (00:54:16): Kanekoa was trying to get me back because he said I was trying to dox him. Chamath Palihapitiya (00:54:20): You always Kanekoa. He's great. Jason Calacanis (00:54:22): No. I just think it's hilarious that people are retrading Kanekoa the Great as if he's, like, this great journalist, and he's in his mom's basement eating hot pockets or he's working for Putin. Chamath Palihapitiya (00:54:33): He's a really good David Friedberg (00:54:33): I don't know. Do I want my Chamath Palihapitiya (00:54:34): real good Jake. David Friedberg (00:54:35): It's J. Cal or Kanekoa? I don't know. I don't know. Jason Calacanis (00:54:38): Who do you take? I mean, your consideration Chamath Palihapitiya (00:54:40): is pretty good. I subscribe to Kanekoa. I subscribe to Kanekoa. Jason Calacanis (00:54:44): Yeah. Aaron Levie, you have a favorite? Or who are you? You Autism Capital or Kanekoa? What do you mean Chamath Palihapitiya (00:54:48): by the team? Capital too. I think he's really Absolutely. Aaron Levie (00:54:51): I'm I'm liking Geiger these days. David Friedberg (00:54:53): Oh, you're to Geiger. Geiger Capital is good. Geiger Capital is good. Jason Calacanis (00:54:56): I I share them all. BC Brex. BC Brex. Aaron Levie (00:54:59): I think the nighttime thing would be, it would be at least typical of this government to do a Streisand effect of just, like, maybe if we cover it up, nobody will see, and then, obviously, it's the biggest thing. So yeah. And they've got all these lights on them. Jason Calacanis (00:55:11): Yeah. Like, they're putting new lights on it. This big. But if they there is a startup that makes, we really looked it up, and there is a startup that makes drones to do this specific task to look for dirty bombs in ports, and ports obviously look for these things. It's a known threat. This is not rocket science. David Friedberg (00:55:30): I'm sorry. Chamath Palihapitiya (00:55:30): And why and why only at night to free the charge? Jason Calacanis (00:55:33): That they can read the signatures better was the theory. That at night, you can read the signature, which doesn't make sense to me. Science guy, you wanna come in here? David Friedberg (00:55:42): I don't see how Jason Calacanis (00:55:43): at night. David Friedberg (00:55:43): I don't see how at nighttime you'd get a better read on radioactive material. It doesn't make any sense. So yeah. Jason Calacanis (00:55:49): No sense. That sounds like a crazy thing. But, anyway, we're living in crazy times. Speaking of crazy By David Friedberg (00:55:55): the way, that was my first conspiracy theory in 208 episodes of the All-In Pod. So Jason Calacanis (00:55:59): Very nice. Yeah. I actually can participate in conspiracy corner now. I'm coming back next week with a better one. Chamath Palihapitiya (00:56:07): Okay, Jake. I'll David Friedberg (00:56:07): read us some more news. Go to Google News and read us some more news Jason Calacanis (00:56:10): so we can do another docket. Christ, man. David Friedberg (00:56:12): Read a whole article for us. Us. Jason Calacanis (00:56:14): No. You do it. God. No. No. You get the talking in front of me. Just okay. So today, the Dow Jones Industrial Average is up 23,000 to 44,000 viewers. A high level of David Friedberg (00:56:23): guys make you look good. Jason Calacanis (00:56:25): Said he's super happy. Skiing. That's enough. I'm going skiing. Yeah. I thought Aaron Levie (00:56:29): it was cool how he read the entire congressional bill earlier. Jason Calacanis (00:56:32): Yeah. Call 1,500. David Friedberg (00:56:34): loves to filibuster. Jason Calacanis (00:56:36): But I'm not filibustering. Alright. Listen. Here. Let's do another story. Let's see if you can contribute something. OpenAI update, Madison. Your contribution was amazing. Oh, I was actually using ChatGPT to go into the founding fathers' papers, and, yeah, I was reading The Federalist Papers with Gemini. Chamath Palihapitiya (00:56:55): 13 and number 44. Jason Calacanis (00:56:57): I would like to quote Jacob Evans. Hamilton the musical. Oh. Hamilton the musical. I was comparing the lyrics from Hamilton the musical. Oh my god. Hey, Nick. David Friedberg (00:57:11): Can you send JCal another Yahoo News article? Let's get going. Come on. Jason Calacanis (00:57:14): Let's go. Yahoo. Let's go. Let's go. Can't can't wait to David Friedberg (00:57:22): can't wait can't wait to see you tomorrow. Let's go, dude. Come Jason Calacanis (00:57:25): on. Oh my god. Wait. Wait. Just can we just end it here? Yeah. No. Chamath Palihapitiya (00:57:30): Do it. Do it. Because I wanna talk about OpenAI. Jason Calacanis (00:57:32): You wanna talk about OpenAI? You do? Yeah. David Friedberg (00:57:34): Yeah. Give him his red meat. Give him his red meat. Jason Calacanis (00:57:36): Alright. Here's an update on closed AI flipping and, Sam Altman supervillain Sam Altman securing the bank. Meta wrote a letter to California's attorney general open yet. It's on OpenAI's for-profit conversion 2 months ago. OpenAI announced a $6,600,000,000 funding round, $157,000,000,000 valuation. They're projecting $3.7 billion in revenue this year. Pretty great revenue growth. But there's a poison pill in the deal. OpenAI must convert to a for-profit within the next two years or investors can ask for their money back. And right before they announced this round, you remember CTO Mira Murati and two other top researchers resigned. Many people saw this as a protest. Elon, who put the first $50 million in and co-founded OpenAI, is currently suing the company and seeking a court order that would stop the for-profit conversion. Now Zuck is joining team Elon. Elon and Zuck are in some weird pairing up. They're not in the ring, not in the octagon. No. Last week, Meta sent a letter asking California's attorney general to stop OpenAI's for-profit conversion. What do you think of this? We've got them now not in the octagon, but they're in the political arena. Chamath, your thoughts? Chamath Palihapitiya (00:58:57): I think that this is so interesting. So I was looking at all of these things. If you put them all together, it paints a really interesting story. So you have Elon filing an injunction, which basically says you should not allow this conversion to happen until we sort out all of these details because if you allowed it to convert and then I win, it'll be very messy to go backwards. I think that that's a pretty credible legal argument. Then you have Zuck basically say, hey. Elon's right. This company should not convert. But the more interesting thing that really got me thinking about this was a chart that Menlo Ventures put out. Nick, can you just show this? What this shows is just what's happened in the last year. And what do you notice? What you notice is the market share of OpenAI has changed pretty meaningfully from half to about a third. And what you see is Anthropic doubled, Meta roughly staying the same, Google picking up steam. And it started to make me think this is very similar to a chart that I would have looked at when, you know, in 2006-7 when we were building Facebook because we had this huge competitor in MySpace that was the de facto winner. And we were this upstart, and it made me think, is there a replay of the same thing all over again where you have this incumbent that pioneers an idea and they start with a 100% share? And then all of these upstarts come around from nowhere. And then I thought, well, what is better today if you are a company that's just starting versus if you were the incumbent? And I think that there's a handful that are worth talking about. So the first is when you look at what XAI has done with respect to NVIDIA GPUs, the fact that they were able to get 100,000 to work as, you know, in one contiguous system and are now rapidly scaling up to basically a million over the next year. Chamath Palihapitiya (01:01:03): I think what it does, Jason, it puts you to the front of the line for all hardware. So now all of a sudden, if you were third or fourth in line, XAI is now first, and it pushes everybody else down. And in doing that, you either have to buy it yourself or work with your partner. And I think for the folks like Meta, that translates and explains why they're spending so much more sort of like this arms race. If you can't spend with my competitors, I'm just gonna prefer my competitor to you. So I think that creates a capital war. In a capital war, I think the big companies like Google, Amazon, Microsoft, Meta, and brands like Elon will always be able to attract effectively infinite capital, and their cost of capital goes to zero, which means they'll be able to win this hardware war. Okay. So put a pin in that. Then the second thing is what happens on the actual data and experience side on the training side. If you listen to Ilya Sutskever, if you listen to Andrej Karpathy, what they effectively are saying is there's this terminal asymptote that we're seeing right now in model quality. So what happens? A lot of these folks are now experimenting on the things around the model. Right? The user experience, how you use it. Can I keep things in memory? Can I cut and paste these things from here and there? Because what it says is, like, the data's kinda static and brittle, but it's actually not as what we said before because you have this corpus of data on X that's pretty unique. I suppose if Elon fed in all this kinetic data that he controls through Tesla, that's very unique. Does that all of a sudden create this additive pool of information? Possibly. And then the third thing is when you look at that chart, what that chart says is, hold on a second. Why are corporates moving around? And what I can tell you just through the 80, 90 lens is we are completely promiscuous in how we use models. And the reason is because these models offer different cost-quality trade-offs at different points in time for different tasks. Chamath Palihapitiya (01:03:07): And so what we are seeing is a world where instead of having two or three models you rely on, you're gonna rely on 30 or 40 or 50, and you're gonna trade them off and you're gonna use effectively like an LLM router to disin, you know, to Jason Calacanis (01:03:20): Load balance them. Yeah. Chamath Palihapitiya (01:03:21): And to route them. Or just to manage and route them. And then there's an intelligence above that that's constantly tasking and figuring out prompt optimization across these models. So it's this thing where we were very reliant on OpenAI. Now we're reliant across three or four. Ideally we'll be reliant on 30 or 40. And so I just see this world where it's all getting commoditized quite quickly. And so I'm just, like, sort of scratching my head, like, where is the market value here? Jason Calacanis (01:03:49): Aaron, your thoughts. I know you're very promiscuous when it comes to LLMs such a way. Aaron Levie (01:03:53): I mean, we have a very similar model as what Chamath said, which is we're agnostic, so we work with multiple AI vendors. But I think a friend deep in AI land a couple of years ago, right before ChatGPT, said there's no secrets in AI. And I didn't totally understand at the time; it hadn't registered what that meant. But very quickly, it kind of became obvious, which is the research breakthroughs sort of propagate insanely quickly across the AI community. And so back to this Chamath framework, if you just think about it as if the research effectively becomes open at some point in time quickly enough because either the researchers move or people publish it or whatnot, then it really is a compute game and then maybe a data access game. And that means that there's four or five at-scale players that can fund this. And I think as we've seen in other areas where it's an infrastructure play, you eventually have the underlying service with enough competition. You have the underlying service eventually trend toward the cost of the infrastructure. So, what we should expect is that the price of a token in AI land, you know, basically will be whatever the price of running the computers are, and maybe with like a, you know, plus 10, 20% margin. Jason Calacanis (01:05:07): See the same thing happen with storage? I remember in David Friedberg (01:05:09): the early days 100%. Jason Calacanis (01:05:10): Box and Dropbox and YouTube, you all had this major innovation with storage. And how did that play out? Let me Aaron Levie (01:05:16): give you a fun stat. We give our customers unlimited storage. We have 82% gross margin. So, what happened was the price of the underlying storage has gone down by hundreds of times since we started the company. And then all our value is in the software layer on top of the storage. So we've benefited from this incredible, just, you know, ruthless competition between Western Digital, Seagate, and other players that are just trying to pack more, more, more, you know, basically more storage density into these drives. And every couple of years, they have a new breakthrough. We're now, you know, upcoming, we're heading toward maybe a 50-terabyte hard drive. When we started the company, they were kind of 80 gigabytes. Jason Calacanis (01:05:56): Much of your time in the early days was spent on dealing with this infrastructure issue, and then how much of your time and your leadership team's time is spent on this issue now? Aaron Levie (01:06:06): Yeah. So back in the day, like, if we had, you know, 10 people in engineering, you know, 80% of them were doing, you know, pure infrastructure work. Now if we have 1,000 people, it, you know, be inverted in terms of the ratio. So you just get more leverage, both as you get the advancements in the technology, but then also as you get scale. But all of this is to say, you should basically anticipate a world where—and I think Zuck is this interesting counterbalance on all of this because of open source. If at any moment, you know, that Zuck will basically provide an open-source model that is at kind of best-in-class benchmarks and at the frontier, then there is a limit on how much you can charge for the tokens of your hosted model, because anybody will then be able to go host the open model and be able to provide infrastructure around it. So if you always have that counterbalance and the tokens eventually kind of look the same, the output tokens kind of look the same. Jason Calacanis (01:07:00): Isn't it, yeah. Always isn't it also the truth that major enterprises, Fortune 500, 200, you know, 20 years ago weren't interested in open source, and now that's kind of their default? They want to buy into open source because they don't want to be locked into a vendor? Aaron Levie (01:07:15): It's actually not even necessarily the case that the customer has to pick the open-source vendor. They might buy it through an abstraction layer that is letting them get the benefit of open source. Jason Calacanis (01:07:24): Got it. Aaron Levie (01:07:24): But still buy through a proprietary. So Jason Calacanis (01:07:26): you believe open source wins? Aaron Levie (01:07:28): I believe in the not? No. No. No. So I believe open source causes pricing to always be extremely low. Jason Calacanis (01:07:34): Right. But so okay. But in this case, do you think open source is gonna ultimately win the day in models? Aaron Levie (01:07:40): No. Not necessarily. Jason Calacanis (01:07:41): You don't. Aaron Levie (01:07:42): No. Because only Meta has the scale to be able to provide Chamath Palihapitiya (01:07:47): some Aaron is saying here. Let me let me maybe try to Jason Calacanis (01:07:49): frame it. Chamath Palihapitiya (01:07:49): I think what he's saying is there'll be open source models, there'll be closed source models, but the price that Aaron or me or anybody else pays these model makers will effectively go to zero. Got it. Aaron Levie (01:08:02): And it'll go to the cost of the compute to be clear with a little bit of margin for, for the work of Jason Calacanis (01:08:07): hub, the physicality of that compute. Got it. Aaron Levie (01:08:10): Now it's important to step back and say, I still think you could probably have the entirety of the model providers make 10 times more revenue than they do today because we're just literally in like the first percent of the total TAM. So, so it'd be a mistake to think that that has some kind of downward pressure in terms of the long-term economics of these businesses, especially because I think OpenAI's revenue stream is increasingly looking like a SaaS revenue business, as opposed to just, you know, just the API kind of token pricing. So, so none of this is to provide any sort of color on, like, what would you bet on today? I, I agree with Chamath that you're gonna have maybe not 30 providers, but let's say you at least have, you know, 5 to 10 good choices, all competing heavily for the next breakthrough. Like literally this morning, Google had a breakthrough in sort of this reasoning-oriented model from their Gemini family. Jason Calacanis (01:08:56): Yep. Aaron Levie (01:08:57): Yep. And so what's incredibly, you know, kind of great is it's sort of the best time ever to be building software, assuming that you have a play in the market that lets you remain differentiated. And the key there is just do enough on top of the AI model that there's enough value there. Chamath Palihapitiya (01:09:14): How much the world spends on software and software-related things every year? It's about $5 trillion. So there's, like call it, a trillion and a half of software licenses, a trillion and a half of consulting, and a trillion and a half of IT folks inside of companies, plus or minus a little bit more, you get about $5 trillion, and that's compounding 13% a year. I'm pretty sure that the market here shrinks by an order of magnitude. And instead of fighting over $5 trillion, I think we'll be fighting over Jason Calacanis (01:09:50): What do you think, Aaron? You buy that? Aaron Levie (01:09:53): No. Not at all. I mean, I don't know if you want to make the case more, but well, David Friedberg (01:09:58): I the Chamath Palihapitiya (01:09:58): the only reason is that I think that as we delever the software development process from humans, I think the unit cost of creating code effectively becomes so cheap that it's gonna be very hard to differentially price these products the way that they are. So an example would be that, let's say you use, I don't know, pick your favorite piece of software. I don't want to pick on anyone. That's why I'm not saying anything. Jason Calacanis (01:10:25): Office suite. Let's pick an office suite. Everybody's got one. Chamath Palihapitiya (01:10:28): Sure. Let's pick on Excel because maybe that's like sure. Jason Calacanis (01:10:32): Excel, Google Sheets. Chamath Palihapitiya (01:10:33): Yeah. It's not it's not that Excel isn't valuable. It's incredibly valuable. It's what's the marginal cost of creating the Excel equivalent that is good enough that people switch. The marginal cost today is very expensive, and you can see that because it's what it costs Google to make Sheets, but that's humans. So the real question is if you have a legion of bots that works 24/7 incrementally and increasingly more accurately every day, the question is what is the marginal cost? And I think the marginal cost of that is going to be very cheap. And when you do that, it's very difficult to price it anywhere near the same. And the reason is that other companies will then replicate it and say, hold on. If Excel wants to charge $100, I'll charge 50, and I'll take a lower margin. That's just supply and demand economics. Aaron Levie (01:11:24): Yeah. Yeah. So so so so I I think I I I think there's I I just don't agree with the TAM compression because I think there's another kind of counter event that's happening that that AI is is really going after, like, services. And and so that then then conversely expands the the TAM software where IT budgets weren't usually applied to those types of things, but we can get in that in a second. But I think we've already seen I I think we've already seen this though, and it hasn't exactly played out as, as you're saying. So you already have like a Zoho, like, so, Zoho is this really interesting business. It's probably a couple of billion in revenue at this point. And it's basically a suite of, of extremely low-cost affordable Right. Software products by category. Chamath Palihapitiya (01:12:02): Cycle time of Zoho is poor. But it's not that's not been Aaron Levie (01:12:05): that's not been the reason people don't switch, though. They they don't It's Chamath Palihapitiya (01:12:08): all it's all levered to humans. I just think it's not a good product. It's it's decent enough. Jason Calacanis (01:12:13): Why do you think people don't switch, Aaron? By the way, sorry. Just a sec. Chamath Palihapitiya (01:12:15): Yeah. I do agree with you, Aaron, by the way, that when you bring that whole offline services category online and you automate them with AI, I agree with you that that TAM could be ginormous. All I'm saying is Jason Calacanis (01:12:27): Right. Chamath Palihapitiya (01:12:27): The traditional software TAM today, what people spend $5 trillion on, I think people will spend $500 billion on, and barely if that. David Friedberg (01:12:37): There are Chamath Palihapitiya (01:12:37): there may be other things that people spend money on that that are that are wrapped in AI. Aaron Levie (01:12:41): Yeah. I I guess the the the counter and maybe you'd look at an ERP system or a CRM system or something else like like it that that is sort Jason Calacanis (01:12:50): of like, those Chamath Palihapitiya (01:12:51): things are totally screwed. Aaron Levie (01:12:52): No. But, like, but but this is my point. The opposite. Like, the last thing you wanna touch is the system that is, like like, powering your supply chain. Chamath Palihapitiya (01:13:00): The companies I talk to, they're consistently like, rip it out. Get us to a point where we can rip it up. And the reason is because what they've realized is they'll spend $50 to $100 million a year for 5 features. And they're like, just give me these 5 features as workflows. David Friedberg (01:13:14): Yes. Chamath Palihapitiya (01:13:14): Give me a simple CRUD database and just get me get out of the way. And it's like, the trade off for that makes a lot of sense because look. Let's face it. Like, when you have to build one piece of software that has to sell to 50,000 companies, the reality is that that piece of software is trying to do everything and then some, and it's trying to solve 2 or 3 use cases plus around, you know, 5 or 6 common use cases that are generalized. Aaron Levie (01:13:39): Yep. Chamath Palihapitiya (01:13:40): For 50,000 customers, so you end up with 50,000 features. Jason Calacanis (01:13:43): You know, it's really interesting because, Aaron, you kind of alluded to there's a TAM expansion moment there, and I'm seeing this on the front lines. We run a program called Founders University. I've talked about it here before where we see people pitching us. They're year zero startups, two or three person teams. And what they're doing is they're not going after existing legacy software. They're kind of going after jobs. They're looking at a position or a job somewhere. This is an accountant. We're gonna take an accountant. We're gonna make the number one accountant in the world. That's an AI agent. We're gonna make a podcast producer with Podcast AI. We're gonna make a virtual assistant with Athena. We're just seeing it over and over again. That's a whole other category where you study a person's behavior as they work, a social media manager and what they do, and then you replicate it with AI. And that's something that just hasn't previously been done. So there could be two things occurring here, Chamath and Aaron, at the same time, which is a deflation in legacy systems and they'll be replaced. And then additionally, human capital and jobs that are easy enough for AI to do as an agent will also expand the TAM. You are at the same time. You are Chamath Palihapitiya (01:14:56): completely right about the usage. All I'm debating is when you have to price something. Jason Calacanis (01:15:01): Mhmm. Chamath Palihapitiya (01:15:02): You have to look at the total cost of what it took to make it. And then you want to try to build in a reasonable amount of margin and some reasonable expansion, and you discount it back, and this is what you think it's worth. Even though you may not think you're doing that when you implicitly price something that way, that is what's happening underneath the hood to the unemotional buyer of that good. And all I'm saying is if what Aaron says before, which I agree with is true, which is the cost of using a model to get to an output effectively goes to zero. But it's sort of somewhat what I've been saying before, the marginal cost of compute goes to zero. The marginal cost of energy goes to zero. The real question is, what does it take to make a good in the digital world? Jason Calacanis (01:15:46): Let me ask Friedberg a question here. You're back in the CEO slot at a hollow. You're doing it every day, Dave. You're making these choices as to what SaaS products and how you're gonna solve problems. Are you looking at it saying, I'm gonna hire developers who can work 10x because of all these new tools, and I'm gonna build my own internal systems, or are you looking and saying, I'm gonna buy off-the-shelf SaaS products? What are you doing when you make your own decisions every day, David Friedberg? David Friedberg (01:16:13): Well, I try and encourage the teams to build stuff that better meets our needs, and then it can actually be a better solution, and it can be built in-house. And I think we did a—I think I mentioned this in the last episode, but we did a hackathon where we brought in people to learn how to use Cursor and ChatGPT to build software that had never been done before to try and create this as a capability for people broadly in the organization, and there were great tools that came out of it. So I think that that's really the future. And this is kind of like, you know, I'd say early generation, but as we get to further later generation capabilities, you could see the instruction to attach GPT or, like, interface. Hey. I'd love to do the following things with a piece of software. It shows you a couple options. You pick one. It shows you a couple UX. You pick one. It does user testing automatically for you. It does QA for you. And, ultimately, it puts it into production for you, which is the biggest challenging step right now. You still need engineers that can load stuff into production and do QA. But if all of that gets automated as well, now any user in a company can actually stand up software to do something for them. Jason Calacanis (01:17:19): A non-developer, you're saying for your developer. Yeah. Stand up software. Aaron Levie (01:17:22): Maybe, maybe, so, Chamath, just to clarify, are you there? There's two different ways to approach lowering the cost of developing software. One is that it just creates more competitors in each of these categories, which then lowers my price because now there's some downward pressure. Dave's bringing up a different example, which is I'm going to build my own software at effectively the price of zero. The challenge on this, especially the second one, is like, most organizations don't want to be in the business of having to think about building their own software. They just like want it done for them. Like, it's like not a core part of, of their, like, so, you know, your, your business would be very unique relative to the broad economy, which is like, I just want, like, just like, I want a place to put my CRM records. I want a place to like, just like have my HR get managed. And I think the downward pricing pressure. Due to software costs lowering makes total sense. I don't think it's a 10x factor. But, you know, I think that we've always had a long tail of applications that enterprises build. You did it at Microsoft Access. Now you do it in Retool. So the next era of that will be obviously AI-built, and there'll be 10 times the amount of that software. But it's not obvious to me why that would go after the kind of core systems of running a business because just most companies are not looking to reinvent the wheel of that. Chamath Palihapitiya (01:18:34): We're working with an aerospace partner. Won't say who it is. And we sat there, and they walked us through what they deal with to make the things that they're making. It's convoluted. And this is not a software problem. It's that there is no piece of software that understands how they wanna run their company. And so instead, they have to morph their org chart Jason Calacanis (01:18:56): Yep. Chamath Palihapitiya (01:18:56): to the tools that are available. So I think what Friedberg is saying is some version of that as well. There were probably people there using the tools that were available. And as a result, at some point, some HR person said we need to hire this other person and this other person. And instead, what it allows companies to do is just completely reimagine. How do you want your company to work? And what is the business process you actually need to implement? And then let's just get that built. And, you know, I don't know if you guys saw this, but Satya Nadella had this clip that's gone pretty viral in the last couple of days where he effectively said the same thing. And what he's effectively saying is all these big software systems are business rules wrapping a database plus an incredible go-to-market Jason Calacanis (01:19:44): team. Mhmm. Chamath Palihapitiya (01:19:45): You know, and this is what Alex Karp points to as sharp knives, steak dinners, and basketball game tickets. I don't know if you guys saw that clip. Jason Calacanis (01:19:55): I did see the clip. Yeah. He likes to win based on product, not on sales effort. Chamath Palihapitiya (01:19:59): Nick, you should find this clip. Speaker 5 (01:20:01): We don't play golf. What we do do is we play software. We will put if you wanna actually compete, compete on your product. And what's very special and, yes, do I enjoy humiliating people who have better steak dinners and sharper knives and better golf swings? Yes. I do. You know what? I really, I really like that we win in that way. It makes me very happy, and it makes our clients happy. Chamath Palihapitiya (01:20:22): But it really points to the heart of how the software industrial complex, that's what I call it. This $5,100,000,000,000 software industrial complex, how has it evolved? I think it's people that build good-point products, but when the market, meaning the shareholders and the public investors demand growth, you have this natural expansion. And what do they do? They inflate the feature set. They inflate the cost. And then in order to sell that, they inflate the set of incentives that they give to the buyer. So the CIO inside of these large organizations, they control budgets. They're equivalent to, like, state-level budgets in some cases, you know, what do you think the CIO of a top five bank is spending? It's probably $15 billion to $20 billion a year. They are getting wined and dined to a way that you could not even imagine. I don't even think the CEO probably understands. And that filters down through the org and so they make these Aaron Levie (01:21:22): don't, like, totally ruin our whole game here. Jason Calacanis (01:21:24): Well, I'm I'm it's not Chamath Palihapitiya (01:21:25): it's not I'm just pointing it out like Jason Calacanis (01:21:27): It's, I mean, I'll say the counterbalance that we, yeah. But here's another part of the game in the field. If these tools make your team, yeah, 10, 20, 6%, whatever you can quantify, more effective at their jobs, then it's a de minimis amount for most organizations who have created very profitable businesses. I see this where I was mentioning some companies earlier, and their SaaS pricing is broken because the number of employees at a company has been going down because people are getting more efficient. So now they're looking at saying, well, what value do we provide with this podcast, you know, producer in a box and whatever it does? They say they were starting with, like, $99 a month or $49 a seat. I said, listen. Just charge a minimum of $500 to get the software. Nobody complained. And they got rid of the bottom tiers. So there's a value being created here that is so great that, yeah, I don't think everybody's gonna roll their own like Friedberg because they'd be like, you know what? This is so great. It's 6,000 a year. It, Yolo. I'll just buy it. David Friedberg (01:22:29): It is today. And in five years, just like we're all gonna and we're all using, chat-like interfaces more frequently. Yeah. You go to your chat-like interface and, eventually, you realize you can ask it to build some tool for you that does something. And it renders the tool, and it makes it possible, and it stands it up in production, and suddenly you're using it at your company. And then you ask it to do another tool, and it does it exactly to spec, and you define the UX you want. You define what you want it to do, and it works. And it interoperates by you and really clearly and really cleanly with the other tool. And there's a big aspect of this where you can start to build all of the software infrastructure that you as an organization want. Right. Chamath Palihapitiya (01:23:12): But I thought you and Aaron, you and Aaron mentioned this, though. The extreme difficulty is not that front-end part. That's easy. It's like, I think it's less than 3 or 4% of the work. The 96% of the work is how you actually integrate it in the back end and how do you provision it, how do you have controls, and how do you do security? Because if those things fail and those are implemented in a bot in a highly regulated market, as an example, you may not actually be allowed to operate. David Friedberg (01:23:41): Let's go through that example. And let's say that you're in a bank and you tell the AI, figure out all the security and permissions and authority rules that are necessary for me to operate as a bank, and it can actually render it. It sounds far-fetched today, but there's no reason that in seven years, that is not the standard. Azure, that I don't have the ability to say, go look at all the software that's out there in the world today. Chamath Palihapitiya (01:24:01): So that will be built. David Friedberg (01:24:02): A tool that meets compliance standards, that meets all of my security standards. And you can actually instruct the AI to operate like a large number of software engineers. No, I think so. Operate today. Chamath Palihapitiya (01:24:12): The practical issue where the rubber meets the road there is when there is a penetration and a regulator who's a human, because it will not have been a bot, comes and knocks on your door. And you're like, well, here's this immutable log of the things that I did. And they're like, I don't want an immutable log. Who the hell tested this? Show me the unit test that you created and signed off on. So there is a critical human-in-the-loop problem on that other 95 percent, which is where I agree with Aaron that David Friedberg (01:24:40): In in in reach in in, like, stage 1, like, we're in stage 0. No. No. No. You need that'll be the case. Chamath Palihapitiya (01:24:45): No. But you'll, I think it's in stage 5 and 6. I think you'll need governments to take an entirely different risk posture for highly regulated markets. I don't see that happening in any in any time in the near future. Aaron Levie (01:24:55): In life sciences, if you want anything in a clinical system, I don't need to tell you guys this, but you have to do a QA test on every single change that ever happens and be able to prove that you tested every single thing. So the idea of a probabilistic AI system generating the kind of code for you, you know, in a clinical trial workflow, like, I just think, yeah, it's gonna take a lot of change from regulators. Jason Calacanis (01:25:17): Another decade of evolution here to make these things sustainable and have a high quality. David Friedberg (01:25:23): I think it'll happen faster than everyone thinks. Aaron Levie (01:25:25): Yeah. And I think actually that's that like, there's actually no reason why that wouldn't be a good thing if that did happen, to be clear. I think though back to, you know, Jason's earlier point though, like, then the counterbalance on the TAM compression is just now the sort of thing that we think of as software that market now is much larger. So yeah. If you're selling if you're selling security, yeah. So but like, but like, that means that if you're selling, let's say, $50,000 of security software, you know, maybe that goes down a little bit to, you know, $25,000, but but you might, yeah, but Jason Calacanis (01:25:55): you might sell. Exactly. And the agent of Chamath Palihapitiya (01:25:57): of the new agent. Yeah. That I so I agree 100% with that. My only comment is the software industrial complex today has to shrink because the stranglehold that it has on how companies run Jason Calacanis (01:26:08): Mhmm. Chamath Palihapitiya (01:26:09): is incredibly high for an experience that's incredibly poor. Nobody nobody raises their hand and says, gosh, this piece of enterprise software that I use in my day-to-day life is as good as Instagram or TikTok. Nobody says that. Jason Calacanis (01:26:23): Well, I mean, except about Box. I was reading the reviews earlier today. Good. Good. Good. And I was on G2 or one of those sites, and it's just Box was just a rating for a tremendous Chamath Palihapitiya (01:26:32): so I love Box. Jason Calacanis (01:26:33): I love Box. It's incredible. Aaron Levie (01:26:34): Well, I mean, just the what's Jason Calacanis (01:26:36): the ticker symbol? Dollar's not. We trash it. Aaron Levie (01:26:39): very simple for people. So Jason Calacanis (01:26:41): Is it dollar BOX? Is that what it is? It is. I have to put a I'm putting a J trade in here because I may have to J trade this. It sounds like a really great opportunity for me. Alright. Listen. Aaron, you just got craven. David Friedberg (01:26:52): What was your last j yeah. Yeah. You got Kramer-ed. Jason Calacanis (01:26:53): My last day trade is I'm just I'm I'm loading up on MSTR and Bitcoin. I'm doing a I'm shorting Bitcoin and I'm buying M-S I don't know what that I'm not I'm not trading stocks right now. I'm focused on investing in 100 startups per year. 100 new startups per year and putting the first check into them. That's what I do. Alright. Listen. Enough. This has been a great episode. Aaron, you're amazing. Thank you for coming on constantly. Everybody follow. What is your fourth rep David Friedberg (01:27:20): on AI? Can I just tell you guys, Jason Calacanis (01:27:21): are you at Levie or at Aaron? Aaron Levie (01:27:23): L yeah. Yeah. At Levie. Jason Calacanis (01:27:25): Levie, is that the French pronunciation? L E V I E. L E V A. David Friedberg (01:27:29): Have you guys seen the VO model from Google? Aaron Levie (01:27:31): Yeah. Have you guys talked about how Google has, like, gotten some Chamath Palihapitiya (01:27:34): Google's incredible. They are Yeah. Aaron Levie (01:27:36): They are. Chamath Palihapitiya (01:27:36): They're back Jason Calacanis (01:27:37): in the office. Cylinder. I literally paid Chamath Palihapitiya (01:27:39): Shout out to Sundar. Jason Calacanis (01:27:40): Yeah. Yeah. And Sergey is going to Chamath Palihapitiya (01:27:42): work every day, by the way. He's at work. What can Brown do for you, J. Kelsey? Sundar back in the group chat. Okay. Jason Calacanis (01:27:47): Did we David Friedberg (01:27:47): help? Guys see Genesys yesterday? Jason Calacanis (01:27:49): Well okay. Let's let me just put this up here, and then I'll tee it up to Jeffrey Berg. Google has been putting out new models. They have this new Google Gemini, and they have one with deep reasoning and their 2.0 model. I did a side-by-side test, same prompts with our friends in DeepMind on This Week in Startups just this week. We did multiple tests. He has the 0.1 pro, the $200 per month. Gemini was beating that, hands down, for me. And I think he conceded that with their free model and their $20 model, if we just gave it decent prompts, I think Google now has reached parity and they have an app out. Friedberg, what are your thoughts? Because people were counting them out and here we are. I think not only have they caught up, I think they have exceeded. What are your thoughts? David Friedberg (01:28:34): They were late. The compounding effects are playing out, and it's only gonna continue to compound. And I will say the data repository at Google, the engine that they have, the infrastructure, the team, everything down to components is advantaged. And so everyone's been kinda counting them out, but it's clear they're in it to win it. They're here to play. Chamath Palihapitiya (01:28:50): percent of the usage of OpenAI is consumer. Jason Calacanis (01:28:53): percent is consumer. Chamath Palihapitiya (01:28:55): What does that mean for them as Gemini and Google gain momentum? David Friedberg (01:28:59): I think you'll end up having a Gemini that has ads eventually. And you could pay and have no ads or you could not pay and have ads. Chamath Palihapitiya (01:29:08): No meaning. Do you provide enough value and have enough quality where folks don't need to, then folks stay on Google? Jason Calacanis (01:29:16): On Google.com? Chamath Palihapitiya (01:29:17): I'm asking you whether it impacts OpenAI, the quality of Gemini as it increases, or do you think that these usage cohorts are roughly set? David Friedberg (01:29:25): I jump back and forth personally. My experience is I don't feel like I've got embedded data on OpenAI or on Gemini that makes me stick with one. I'm just like with Google, I'm gonna go to the best interface, the best engine. So I do think that there's fungibility here, and people will move over as they realize better results, better performance. But I will say that what we're seeing now with the data advantage at Google. So, you know, the Internet, all these LLMs are language models trained on text from the Internet. Right? There's, call it, 50 billion words on the Internet. And I think if you estimate the data repository in these training sets, it's, like, probably a couple terabytes, 1 to 5 terabytes or something like that. But if you look at the video data that's out there, there's 100 of billions of hours or 100 billion plus hours of video data. A large amount of that is sitting on YouTube. And by some estimates, there's a thousand exabytes of video data on the Internet. So about a billion times more video data than there is word or text data. And I think we just saw that play out with the Veo model that launched yesterday, but here's some examples of Veo. Google has all of this YouTube data. You know, whether or not they're using it to train, I don't know the answer. Jason Calacanis (01:30:30): I don't think they're allowed to is what I heard from the insiders. They have to do with the terms of service. Yeah. To get explicit permission to use it. But you're right. These models are tremendous. David Friedberg (01:30:40): They're using. And it's basically rendering physics or it looks like it's rendering physics. Now Genesis came out yesterday, and it's open source. So you can actually go play with this Genesis model, which similarly renders the actual 3D objects into a 3D environment. So rather than rendering a 2-dimensional set of pixels to look at a video visual, with Genesis, as you can see here, you can type in a prompt, and it renders this extraordinary video that also has underlying it the three-dimensional objects that make up the video. Jason Calacanis (01:31:12): Banana. So you could change the angle. Right? Which means you could work with it. David Friedberg (01:31:16): And also with Google and this, you can start to implement three-dimensional models based on some prompt that says something like, I wanna have the camera angle at this point in the room. Jason Calacanis (01:31:27): Yes. David Friedberg (01:31:27): I wanna have the room look like this. I wanna have this color, this wallpaper. And suddenly, everything starts to prompt in a way that you can actually render in real time a video game, a movie, a visual experience. And it goes to this point that we're unleashing the capacity for human imagination and creativity with these systems because it's no longer just a lookalike two-dimensional image. It's now an actual three-dimensional object that then renders the visuals to make this happen. So we're starting to see, I think, the next era of these models that goes beyond just text prediction. Jason Calacanis (01:31:57): What do you think, Aaron? Aaron Levie (01:31:58): Yeah. There was another release last week of an experimental project for browser use by Gemini, which is another advantage because YouTube has obviously an incredible amount of screen-sharing data and videos. So you have, you know, like we used to think about visual as just like, okay, it's gonna be, you know, for developing, you know, CG characters or something, but it's actually just all of the use cases of a computer are also on YouTube. Jason Calacanis (01:32:24): Project Mariner is the name of it. Right? Where your Chrome extension AI can control your browser to do things. Aaron Levie (01:32:31): And if you go to the AI studio from Gemini, they have a mode where you can turn on your webcam, and then you basically it has full visual, kind of access to anything. And so they're cranking, and it's super exciting because, like, just you can tell that Google's woken up, and they are just on full assault. So the I mean, just in 10 days, the quantum, the AI, open source, Gemini updates, it's like every morning you're waking up to a Sundar tweet that is some new breakthrough. So Well, Jason Calacanis (01:33:03): yeah, it's amazing when you fire 20,000 people who weren't doing any work and were involved in DEI nonsense, and then you yeah. That's not the point. That's David Friedberg (01:33:13): not the point. The point is they've had this compounding, you know, infrastructure advantage, data advantage, personnel advantage, and now they were just a little late to the game. But when you Jason Calacanis (01:33:23): But they were all distracted is my point. They were distracted with nonsense. You know that's true. Come on. The first version of this came out, it was making Abraham Lincoln remember remember an African American and Okay. That's right. That's true. Asian. You know? Like, they were distracted. David Friedberg (01:33:36): Okay. A big part of Google's orientation historically has been don't mess up the machine. A classic kind of big company dilemma where if I do something that's either disruptive to my core business or if I do something wrong where I will invite regulatory and consumer scrutiny, I'm gonna get wrecked. And so they avoided launching stuff early. And what they've done is they've changed the posture in the last two years. Yes. And now the posture is launch early, launch aggressively, push hard. We have to win this battle or we're gonna get eaten alive. And it's amazing to see the founders and Sundar lead this organization. Yep. I think there were a lot of question marks a year ago, but I think that the questions have been answered. Jason Calacanis (01:34:13): I agree. I'm saying it right now. I think we've hit peak OpenAI in the market. I think they're gonna be the number three or four player. I think Gemini, Meta, and XAI are going to lead them. If we're sitting here in three years, I think OpenAI is number three, four, or five, not one or two. I don't think they get the one or two slot. What do you think, Aaron? OpenAI, who's in the one and two slot? Aaron Levie (01:34:38): Yeah. I don't think you wanna bet against Sam and Greg. You don't wanna bet against Elon. You don't wanna bet against Sergey now, you know, in office with Sundar. You don't wanna bet against Sacks. So I think the rankings are kinda less interesting as much as just the fact that it's like game is on. You do not have incumbents that are sleeping at this point. That's just gonna push everybody forward. So, yeah, just an incredible time for everybody. Jason Calacanis (01:35:02): What a time to be alive. Alright. For the sultan of science, David Friedberg, the chairman dictator, Chamath Palihapitiya, and I don't have a nickname for you, Aaron Levie, but we will have one soon. This is the All-In Podcast. We miss you, Saxxy poo. We miss you, say, come back soon, Saxxy poo. Chamath Palihapitiya (01:35:19): Come back soon, Sax. Jason Calacanis (01:35:20): We miss you. Alright, everybody. Have a great Christmas break, and we'll see you shortly. Go sign up for our spam, at allin.com. Sign up for the spam newsletter. We'll send you some updates on fun. No. It's what you think to sign up for. I'm joking. I'm talking. Chamath Palihapitiya (01:35:33): Sign up, boys. Dotcom. Love you, boys. Jason Calacanis (01:35:35): Bye, guys. We'll let your winners ride. Rain Man David. And it said, we open sourced it to the fans, and they've just gone crazy with it. Robbie West, nice queen of quinoa. Besties are called. That is my dog taking it. David Friedberg (01:36:02): I wish in your driveway Jason Calacanis (01:36:09): We should all just get a room and just have one big huge orgy because they're all just useless. It's like this, like, sexual tension that they just need to release somehow. David Friedberg (01:36:17): Wet your the