AI 会是下一个伟大计算平台吗？ChatGPT 对阵谷歌、AGI 的围栏与 RESTRICT 法案

David Friedberg (00:00:00): Oh, Jake Cal's here. Hello, Jake Cal. Hey. Jason Calacanis (00:00:02): How are you? David Friedberg (00:00:02): Thanks for showing up. Jason Calacanis (00:00:04): I've been here the whole time. I I was just well, I was just having some of these beautiful salted roasted sachets. And my problem is when I went to the store, I kid you not. There was a shelf of these. All flavors are available except one flavor. Salt and vinegar. Chamath Palihapitiya (00:00:19): Sea salt and vinegar. David Friedberg (00:00:20): Entire, we move the market. We move the market. Jason Calacanis (00:00:23): I am not kidding. I go to the fancy, you know, bespoke David Friedberg (00:00:28): -- Chamath Palihapitiya (00:00:28): The Rally. -- they went to the Rally's in Trucking? Jason Calacanis (00:00:30): I went to the Rally's in Trucking. They are Chaseional. And they have, you know, all these overpriced Chamath Palihapitiya (00:00:35): of all, it's called artisanal. Jason Calacanis (00:00:36): That's what I said. The art stuff. The artistic food. The Artesino bro where they had this. I kid you not. Spicy, salty, no salt, every shelf packed. Then there's one shelf I can see straight through to the ice cream, but Chamath Palihapitiya (00:00:54): not see salt infection. Jason Calacanis (00:00:55): And I look at the tiny little sign, Salt and vinegar, shelled nuts, Chamath Palihapitiya (00:00:59): sea salt and Jason Calacanis (00:01:00): vinegar, chametz, shelled nuts. sold out across the country. Chamath Palihapitiya (00:01:05): You know, I cannot recommend these more highly. They're incredible. Jason Calacanis (00:01:08): You can't recommend your David Friedberg (00:01:09): salty nuts more. Chamath Palihapitiya (00:01:11): They are delicious. My salty nuts are delicious. Jason Calacanis (00:01:16): The weather winner is wide. Brainman David Sanders. Did you see Joe Manchin's Chamath Palihapitiya (00:01:33): high heater op ed in The Wall Street Journal. Jason Calacanis (00:01:35): Uh-oh. Oh my god. Yep. Joe Mancin went for it. Chamath Palihapitiya (00:01:39): Joe Mancin's running for president. Jason Calacanis (00:01:41): He is. I think okay. So let me ask Saks right there. Sacks, Joe Manchen, Nikki Halle, and who's the guy from Florida? David Sacks (00:01:48): What's your question? Chamath Palihapitiya (00:01:49): By the way, there's a big defection that was leaked this week. Ron Ladder flipped from Trump to to Santos. That's a big one because Ladder's good for a lot of money, 5 to 10,000,000 at least. Jason Calacanis (00:02:00): Joe Mancher, what impact would he have coming into the race? I'm not rolling in. Looking for your honest opinion. David Sacks (00:02:04): Well, it depends how he comes in. What did he say in the op ed? Jason Calacanis (00:02:07): was talking about the insincerity of the Biden administration to control costs and how everybody was incompetent, and it certainly, there's some ways that we can control some spending and everybody needs to grow up and get in a room and just manage the budget for the American people and stop playing politics. Chamath Palihapitiya (00:02:20): Yeah. I think the headline of the article, actually, to your point, Jake, was much worse than the up since of the article, Saks. But if you see the headline, I don't know, Nick, if you can just throw it up there, it was brutal. The headline and the byline of the article I think was more damaging than Jason Calacanis (00:02:33): the substance of the article. Biden's inflation reduction act betrayal, instead of implementing the law as intended, his administration subverts for ideological ideological ends. Chamath Palihapitiya (00:02:43): I have to think that Joe was responsible for that for the titling of that article. You know? He would get Jason Calacanis (00:02:47): permission to approve it. Right. David Friedberg (00:02:50): And by the way, I think if you guys remember, we talked about this when that act was first published. And if you guys remember, I I think I pulled up the CBO data the CBO model. And it showed for the 1st 5 years, this thing burns a couple $100,000,000,000, and then there's some expectation that there'll be some sudden boom in revenue. in the out years, and then you make the money back in the out years. So it's total, like, accounting shenanigans for him to have made the claim in the 1st place that the IRA was actually gonna be, like, a net deficit reduction or debt reduction. In fact, it's all just accounting shenanigans, and it's just a massive spend package. particularly in the near term when it matters most. Jason Calacanis (00:03:26): I Chamath Palihapitiya (00:03:26): think I told you guys this, but I think this was like when was the last time I was in Washington? Probably, what is it, March now? So maybe it was January I was there. And I saw Schumer and Mark Warner, and I spent about 2 hours with Mansion He is really impressive. He's cool. He's interesting. He's thoughtful. He's moderate. Mancin's like a formidable guy. So this will be really interesting if he steps in there and tries to determine David Friedberg (00:03:56): if that. -- and Mancin, where do you write your check? Chamath Palihapitiya (00:03:59): I'd probably write a check to both, to be honest. Jason Calacanis (00:04:01): Feels like a good ticket to me. I've always wanted to see the the cross David Friedberg (00:04:04): -- Chamath Palihapitiya (00:04:04): Could you imagine a a Democrat Republican merging somehow and, like, running together. Would be Jason Calacanis (00:04:08): the greatest? Chamath Palihapitiya (00:04:09): My god. Jason Calacanis (00:04:10): I've been pitching that for years. I think that's like a -- Oh my god. Clear path. Chamath Palihapitiya (00:04:14): David Friedberg may have just come up with one of the most disruptive ideas in American politics that's ever been floated. Jason Calacanis (00:04:20): Oh my god. -- Kelly. Match and Helly? Haly, Matthew. David Sacks (00:04:23): Keep a dreamer. Jason Calacanis (00:04:23): Imagine Helly. Yeah. David Sacks (00:04:24): This to my comment on this. So so first of all, I remember when, you know, Mansion did a good job stopping Biden's 3 and a half $1,000,000,000,000 buildback better. Remember, it was him in Cinema that were the hold Yep. But then, Manchin compromised and gave Biden a $750,000,000,000 version of it. And I guess now he's complaining. that Biden didn't live up to his end of the bargain and doing the deficit reduction. But quite frankly, many commentators said at the time that the bill's claim a reduction were preposterous and that would never happen. So quite frankly, you know, Mansion shouldn't have been euckered or hoodwinked by Biden. Everyone was basically saying, there'll never be any deficit reduction out of this bill. It's just more spending. So I don't really feel bad for mansion here saying that somehow he was betrayed by Biden, he should have known better. Now in terms of him running, Yeah. I think as a democrat who's figured out how to get himself elected in West Virginia, which is a plus 20 red state, He obviously knows how to appeal to the center. The problem for him is just how do you get the Democratic Party nomination? Because he's far to the right of your average Democratic Party voter. if he wants to run as an independent, that's a different story. And that that would really throw a curveball into the race. But I don't see him doing that. I think it's kind of a stretch. And this is the problem with a lot of these fancy candidates is that, you know, centrist or moderate voters might like them, but they can't get the nomination of their party. I'll see David Friedberg (00:05:46): -- -- Jason Calacanis (00:05:47): Trump and Obama, those were Fantasy candidates. David Sacks (00:05:49): I don't think so. Jason Calacanis (00:05:50): I mean -- Trump was not a Fantasy candidate. He's the ultimate. David Sacks (00:05:52): Well, he was an out cider, but he appealed to the base of the party. He appealed to the base of the party. What I'm saying is in order to get the nomination of a major party who have to appeal to its base, And I don't think mansion appeals to the base of the democratic party. He's out of step with it. He's out of step with it in ways that I like. Don't get me wrong. But I just I don't see how he's gonna get a nomination. Jason Calacanis (00:06:11): Chris Christie, what do you think of him? He seems like he's about to come in the race too, David. David Sacks (00:06:16): Pointless. Jason Calacanis (00:06:16): Eviable? Pointless. Pointless. David Sacks (00:06:18): He's just he's just clutter. Jason Calacanis (00:06:20): Okay. Pointless. Alright. Listen, everybody. Welcome to the all in podcast It's, like, episode 100 something. With me again today, The Rainman himself. Yeah. David Sacks is here. Friedberg is in his garden at his home in Paris. Spring has sprung, the queen of quinoa, And of course, the dictator himself, Chamath, Palihapitiya, the silver fox. Look at that little tough of silver hair. So distinguished. Chamath Palihapitiya (00:06:47): I got a haircut from somebody recently who said that people go to her and ask her to put the silver thing in their hair. Really? David Sacks (00:06:57): I don't have to worry about that. Jason Calacanis (00:06:59): Yeah. He's also David Friedberg (00:07:00): -- David Sacks (00:07:00): Looks like he's in Smurf Village there. What is what is that backdrop background? David Friedberg (00:07:04): That is a a scene from -- David Sacks (00:07:07): Oh, okay. David Friedberg (00:07:08): I like most of my backgrounds. I think my god is, like, smooth in the moment of the week. Chamath Palihapitiya (00:07:13): You guys just totally totally denied half the beta males in the YouTube comments from being able to guess what the background. Thanks a lot. I've been really good for them. Well, he'll Actually, I Jason Calacanis (00:07:23): did a reverse image search, and then I used a chat GPS plug in to automatically figure out David Friedberg (00:07:27): -- David Sacks (00:07:28): I didn't know what was the game. David Friedberg (00:07:29): -- Jason Calacanis (00:07:29): each week. David Sacks (00:07:30): Oh, okay. Jason Calacanis (00:07:31): Alright. David Sacks (00:07:32): Well, let's get started. Come on. Jason Calacanis (00:07:33): Let's get started. Okay. Listen. I don't David Friedberg (00:07:35): think it sounds like I can get out of here. Chamath Palihapitiya (00:07:37): The Alpha spoke in David Friedberg (00:07:38): the Alpha. Chamath Palihapitiya (00:07:38): Sounds feels David Friedberg (00:07:39): like he's in a good mood. I like this. Jason Calacanis (00:07:40): Welcome to the world's greatest podcast. OpenAI launched a bunch of chat GPT plugins and I don't know if you saw it, but David Sacks wrote a blog post with Chamath JPGA. It's an amazing back and forth I read this back and forth. Explain what you did, Saxx. This was really one of the best conversations I've seen with chat GPT. It'll pop it up here on the screen, but it's what you did. David Sacks (00:08:08): Well, I had an idea for a blog post about the use of a, I guess, tactic. You could call gift to get. I thought it would be a interesting tactic for AI startups to use if they're trying to get a hold of proprietary training data. So for example, if you wanted to create an architect AI, you need a lot of plans. or if you're gonna create like a doctor AI, you need a lot of lab results or medical reports to train the AI on. And those are hard to get. OpenAI doesn't necessarily have them yet. So there is an opportunity, I think, for startups to create these AIs in different you call them professional verticals. So the gift to get technique would be you give points to your users for uploading that data. and then they can spend those points by using the AI. And, anyway, the the company that came up with this gift to get tactic was a company called Jigsaw almost 20 years ago. No one remembers this company. I'm kinda dating myself because I remembered it. But I just had this idea. Gee, I wonder if the jigsaw approach could be used for AI startups. So I started by going into Chat GPT, and I said, hey. Have you heard of jigsaw and then it had? And then I said, tell me about its gift to get, you know, approach And then I said, would this approach work for AI startups that want proprietary training data sets And I said, yes. This is a good idea. And then I gave the architect example and I said, can you give me more examples like this? And they gave me, like, 20 more examples. And then I asked it just to flesh out various kinds of details. I went down some cul de sacs I didn't use. And then at the end, I said, can you summarize everything we've just talked about in a blog post? and it gave me the first draft of a blog post. I then did a substantial amount of editing on most of the blog posts, although some of it, I just use verbatim. And then I had a couple of people in my firm look at it. They made some good suggestions, so it's not like the humans completely out of the loop. And then I copy and pasted my edited version back into chatgbt said, here's my edit. And then I asked for some suggestions. David Sacks (00:10:07): It made a few small edits, and I said, okay. Great. Just incorporate the edits yourself. Gave me that final output and then I posted on Substack. A blog that probably would have taken me a week to research and write. If I had done it at all, I was able to do in a day. And I can't see myself going back now. I think this is just how I'm gonna write all my blog posts is is use chat GPT as my researcher as a writing partner. Some cases, an editor, but I'm definitely gonna run it through. Jason Calacanis (00:10:38): the thing that I was struck by was just how kind and generous and thoughtful this conversation was. And I just thought, I've never seen Saxx have conversation where he was so kind to the other person and thoughtful. Right about now, all your friends and family are like, how do we get sex to have this conversation with us? You were super kind to the AI Chamath Palihapitiya (00:10:56): because it's not a person. It was a robot. David Friedberg (00:10:58): Oh, no. David Sacks (00:11:00): Well, just in case it takes over the world, Jake, how you can't be too too too careful. But, no, I think, listen, it's important to get the AI. David Friedberg (00:11:06): Look at it. He's so kind. He's like, oh, perfect. Jason Calacanis (00:11:08): Thanks. Perfect. Okay. No. David Friedberg (00:11:10): No. I wanna number one gotten a thanks from Saks. When did Chamath Palihapitiya (00:11:13): you release an exclamation part? David Sacks (00:11:15): Scroll up and show that example. The AI actually gave me some information about jigsaw's point system again, the the rewards that they used. Yeah. And it was just in text. So I sit down below, hey. Can you split that out as a table? and it did instantly. Jason Calacanis (00:11:29): It's like a day's work. Right? Like, you would have to have an analyst or research and do a day's work. It's incredible. And and and then David Sacks (00:11:34): I just screen out of that, and I made it an exhibit Jason Calacanis (00:11:37): in my golf pass. -- you? And that it was, like, delightful back to you? I mean, this is a this David Sacks (00:11:42): is a road. Jason Calacanis (00:11:43): This is a literal road you being a client human being. Like, all the money that you've spent on therapy and just try and coach Shane, to be nice to people. You're just nice naturally divorced. And this gives me Jakeel, Zach is David Friedberg (00:11:56): in a good mood today. I don't know why you're instigating that. He's laughing. Come on. It's fun. You have to admit it's what is Zach saying thank you to the AI. Perfect. Chamath Palihapitiya (00:12:05): This is confirmatory of what we know. David wants to live in a set of highly transactional relationships. ideally with a machine, who can then eventually help him make him money? David Friedberg (00:12:17): Can I ask Jason Calacanis (00:12:17): you a question of sincerity, Zach? did you what did you enjoy more? Working with your team of humans on this or working with Chat GPT? Which one was more enjoyable for you Just personally. David Sacks (00:12:30): Well, I think they're both were. I I would say that the human contributions were essential. So Jason Calacanis (00:12:36): k. Basically, I am warning. David Sacks (00:12:38): It's not about enjoyment. It's just you know, it's about this is a this is a job to get done, but But it definitely sped things up enormously. I I personally find the hardest part of writing a blog is when you're staring at that blank sheet of paper. and just having to, like, spit out the first thousand words. Jason Calacanis (00:12:53): Yes. David Sacks (00:12:53): It's just so time consuming to do that. But, again, if you start with the first draft, even if it's not very good, then you can just edit it and it speaks Jason Calacanis (00:13:01): to people. Yeah. It's great for ideation. David Sacks (00:13:04): But the countries you people on my chart were were important. Jason Calacanis (00:13:07): Yeah. David Sacks (00:13:08): I actually trusted it. I I know that you probably should fact check it in a way because it can hallucinate, but the things that we're saying made so much sense to me that I didn't think it was hallucinating. Jason Calacanis (00:13:17): Well, this is a great moment to pivot into what Open AI did with plugins. These came fast and furious this week and a bunch of folks who had, you know, started verticalized, chat CPT based, projects, MVPs were like, oh, maybe my project MVP is now dead because Instacart OpenTable Shopify Slack Zapier and Zapier, obviously, like, if then this then that is a very wide ranging tool that allows you to connect APIs from a multitude of sources And what this all lets you do at the end of the day is have Chamath GPT ping one of these sources just like an app might do or some custom software might do, ping the API and return data. So, hey. What tables are open on OpenTable, maybe Shopify, find me things to buy in this category, etcetera. And so people have started building little scripts. We used to call these when magic leap was out, Internet agents. And the concept of a software agent that's existed for a long time actually in computer Science. I'm sure Friedberg Birkett will give us some examples of that. but also chatgpt can now use a browser. So that means you can get around the dated nature of the content in the corpus Somebody did things like, hey. Build me a meal plan, book me a reservation for Friday night, in OpenTable, source other ingredients, and buy it for Saturday night on Insta. carton then used something like wolframalpha to, you know, calculate the calories, etcetera. So when you saw all this drop, Sachs, what did you think in terms of the opportunity for startups and to build these intelligent agents, things that will do if then if this then that or just background tasks over time, then you could actually leave them running. David Sacks (00:15:12): Yeah. I mean, I think this is the most important developer platform since the Iphone and the launch of iOS in the App Store. And I would argue maybe ever in our industry, certainly, since the beginning of the Internet. I think there was a question when Chad GPT launched on November 30th, and people start playing within December. What exactly Openai AI's product strategy was gonna be? Was this just like a proof of concept or a demo. And they even kinda called it like a demo. And initially, it looked like what their small was gonna be was providing an intelligence API that other websites, other applications could incorporate. And we saw some really cool demos like that Notion demo of other applications incorporating AI capabilities. And so initially, it looked like what OpenAI was gonna be was more like Stripe where in the same way that Stripe made payments functionality available very easily through a developer platform, they were gonna make AI capabilities available through their developer platform. And then I think a funny thing happened on the way to this announcement, which is they became the fastest growing application of all time, talking about chatgpt, over a 100,000,000 users in 2 months. Nobody else has ever done that before. I think it took the Iphone, you know, 2 years plus. Gmail, Google, those products all took, I think, well over a year. So this became the fastest growing site of all time. And I think with plugins, what they're indicating is that they will become a destination site. This is not just a developer platform. This is a destination site. And through plugins, they are now incorporating the ability to basically, you know, anything you could do through an application. you will now be able to do through a plug in. You'll just tell Chad GPT what you want done. If you say, hey, book me a plane ticket on this date. It will go into KAYAKS plug in and do that. you say book me a plane ticket and then an Airbnb for this trip. David Friedberg (00:17:08): -- Jason Calacanis (00:17:08): of Siri and Alexa realized because those were very rigid. They had no intelligence. Right? Friedberg, if you if you wanted Siri to do something specific like use ways, or to go get you an open table, it it needed to be pretty specific, and and it didn't have any kind of natural language model behind it. So This is taking existing APIs and putting a natural language layer in front of it, which makes it, well, you know, perform a little more naturally. Is that what we're seeing here, Rupert? David Friedberg (00:17:37): I think it provides access to a corpus of data and a suite of services that are not well integrated into a search or chat interface anywhere today. So you know, knowing what restaurants have what seats available is in a closed service. It's in a it's in a data warehouse operated by OpenTable. And now what OpenTable can do is provide an API into that data via an interface and they can allow chat GPT to make a request to figure that data out. to give a response to a user where they can ultimately benefit from transacting and allowing a service This closes the loop between search and commerce in a way that Google cannot and does not do today. And I think that's what makes it very powerful. We've seen this attempted in a number of important ways in the last couple of years with Alexa and Apple Home and and Google Home kind of integration. via the chat services that they offer, you know, where you speak to the device. But the deep integration that's possible now and the natural language way that you can go from the request all the way through to the transaction is what makes this so extremely powerful. And I think You know, the points I made a few weeks ago when we first talked about, you know, search having so many searches that are done where the human computer interface presents a table or presents a chart or presents a shopping list in a matrix, that's what makes search such a defensible product, I think could theoretically be completely obviated or destroyed with an interface like this, where You can write the ability for chat GPT or whatever the the the the core centralized services to actually present results in a table in a matrix, in an interface, in a shopping list, and actually close the transaction loop. It's really disruptive to things like commerce providers. It's really disruptive some of these commerce platforms. It's really disruptive to a lot of different industries, but also introduces a lot of real opportunity to build on top of that capability and that functionality to rewrite and ultimately make things easier and better for consumers on the Internet. Jason Calacanis (00:19:49): What do you think, Chamath, you're looking at this, and it seems to be moving at a very fast pace? over a 100,000,000 users. They put a business model on it already, 20 bucks a month. They have a secondary business model of, hey. Use the API, and and we'll charge you for usage. And then you layer on what Zapier and if this then that had already sort of established in the world, which is APIs, but nobody ever really wanted to write scripts. So that seemed to be the blocker. You go into Zapier if this and that. It's worth 5% of the audience. People who wanna customize stuff, people who wanna tinker. But this seems to now, with the ChatGPT, chat interface, open it up to a lot of people. So is this super significant, or is this a commodity product that you know, ten people will have we're sitting here next year on all in episode David Friedberg (00:20:31): 220. Chamath Palihapitiya (00:20:32): I think you are asking the exact right question, and you use the a great term like in poker, if there are three hearts on the board and you have the ace of hearts, You have what's called the nut blocker. Right? Which means that nobody else even if anybody else has a flush, they never have the best flush. And if flushes the best hand, there's a lot of ways that you can manipulate the pot and eventually win the pot because you have that ace of hearts and nobody else has it. The concept of blocker, I think, is very important to understand here, which is what are the real blockers for this capability to not be broadly available. So think you have to segregate. You have the end user destination. You have the language model and then you have the 3rd party services. And so if you ask the question, what is the incentive of the 3rd party service? Well, the shareholders of a travel site, right? They're not interested in doing an exclusive deal with any distribution endpoint. They want their services integrated as broadly as possible. Right? So I think the the answer for the service providers is just like they build an app for iOS and for Google and you know, if they could have justified it, they would have built an app for a gaming console. They can. David Friedberg (00:21:53): They should they would. Chamath Palihapitiya (00:21:54): They do. Yeah. Right? So That's gonna get commoditized and broadly available. I think on the l l m side, I think we've talked about this everybody's converging on each other. In fact, there was an interesting article that was released that said that there was a handful of Google engineers that quit because apparently Bard was actually learning on top of chatgpt, which they felt was either illegal or unethical or something. Right? So so the point is, I think we've talked about this for a while, but all of these models will converge in the absence of highly unique data. Right? What I've been calling these white truffles. So if you can hoard white truffles, your model will be Otherwise, your model will be the same as everybody else's model. And then you have the distribution endpoints of which there are many whose economic incentives are very high. Right? So Facebook doesn't wanna just sit around and have all this traffic, go to chat, GPT. They wanna be able to enable Instagram users and WhatsApp users and Facebook users to interact messenger or what have you. Obviously, Google has a, you know, many hundreds of billions of reasons to defend their territory. So I think all of this to me just means that these are really important use cases. As an investor, I think it's important to just stay a little patient because it's not clear to me that there are any natural blockers But I do think that David's right that it's demonstrating the use case that's important, but it's still so early. We are 6 weeks in Yeah. Jason Calacanis (00:23:31): I tell you, I think there's a couple of great blockers here where there's gonna be an M and A bonanza for Silicon Valley. If you look at certain datasets, Reddit, Stack Overflow for programming, and Quora, these things are gonna be worth a fortune and to be able to buy those or get exclusive licenses to those. Chamath Palihapitiya (00:23:50): If you're -- Maybe. -- Google Bard Jason Calacanis (00:23:52): or if you're Chamath, EBT, that could be a major difference maker, Twitter's dataset, obviously. And then you look at certain tools like Zapier and if this then that. They've spent a decade building the sort of you know, Meta API, that would be an incredible blocker. I I think this is gonna be, like, a baccaratization. I'll be honest with you. David Friedberg (00:24:11): -- David Sacks (00:24:11): for free. They did it plug in for free. Chamath Palihapitiya (00:24:13): Exactly. That I was just gonna say, I don't think these are not blockers. I don't think this is the ace of hearts on the flashboard. I don't think so. I think that these things are really interesting assets They are definitely truffily in nature, but they may not be the, you know, £10 white truffle from Algo that we're looking for. Jason Calacanis (00:24:30): You know, but on the m and a side, don't you think this would be, like, incredible? Chamath Palihapitiya (00:24:33): No. But the only reason I say that again is it is just so early. Like, I in the text, I I mentioned this to you guys. I remember and Saks and I were in the middle of this. We were both right at the beginning of social networking. Saks started Genie. I was in the middle of AIM, And all of a sudden, we saw read start social net. Then we saw Frenchster get started. Then we saw Myspace get started. And you have to remember when you look back now 20 years later, the winner was the 7th company, which was Facebook, not the first, not the second, it was the 7th. which started two and a half years properly after the entire WebPoint 20 phenomenon started. David Friedberg (00:25:11): Yeah. Same with search, by the way. where Google was probably 20 Jason Calacanis (00:25:15): x to David Friedberg (00:25:15): the to the scene. Jason Calacanis (00:25:16): Yeah. X Sight, Lycos. If David Friedberg (00:25:17): you wanna Chamath Palihapitiya (00:25:18): be a real student of business history, I'll just say something that's more meta. which is if there's something that I've learned on the heels of this SVB fiasco is that there is an enormous amount of negative perception of Silicon Valley and frankly a lot of disdain for VCs and prognosticating technologists. Right? And I think that David Friedberg (00:25:40): So you need this podcast. Chamath Palihapitiya (00:25:42): I think we have to be very careful. Yeah. And and I and I I do think that we are an example of that because we are the bright shiny object of the people that we're successful And the broad makeup of America thinks that we're not nearly as smart as we all think we are. And after all of this money that's been burned in crypto land NFTs and all of this Web 3 nonsense. To yet again whip up the next hype cycle, I think doesn't serve us well. So I do think there's something very important here, but I think if we want to maintain reputational capital through this cycle because government will get involved much faster in this cycle. I think it's important to just be methodical and thoughtful, iterate experiment, but it's too early to call it, I guess, is what I would say. Jason Calacanis (00:26:29): Yeah. It's definitely too early to call it, but Sachs, you're saying explicitly, you think this is bigger than the Internet itself, bigger than mobile as a platform shift? David Sacks (00:26:38): It's definitely top 3, and I think it might be the biggest ever I think look. I think things can certainly play out the way that Chamath is saying. However, I actually think that OpenAI has demonstrated now with these platform features that it has a lead, a substantial lead, and I actually think that lead is likely to grow in the next year. And let me tell you why. I think it's got a couple of assets here that are hard to replicate. So number 1, user attention. I think they've now got I would guess 100 of millions of users and this thing is caught on like wildfire. Must have been beyond their wildest dream. I think it even surprised them. how much this has taken off. It's really captured the public's imagination and people are discovering new use cases for it every day. if you are sort of the the number 2 or number 3, the 7th large language model to basically get deployed behind a chatbot, just don't think you're gonna get that kind of distribution because the novelty factor will have worn off and people would have already kind of learnt to use chatGBT. So Number 1 is the hundreds of millions of eyeballs. Number 2 is with this developer platform, I think we should describe a couple of other features of it. One of the problems with Chat GPT if you've used it is that the training data ends in 2021, and so you very rapidly for many questions get to a stopping point where it says, like, I don't I don't know the answer to that because I don't have any information about the last 2 years. Well, one of the plugins that OpenAI is introduced itself is called the browsing plugin, and it allows chatgpt to go search the Internet. and not just run Internet searches, but to run an Internet search as if it were a human. So you ask you ask chat GPT a question, and it goes to find it runs a a search. And then it scours through the list of 20 links, and it doesn't stop until it finds a good answer. And then it comes back to you with just the answer. David Sacks (00:28:28): So it actually saves you the time of clicking through all those loops, and it'll give you the browsing history to show you what it did. That's mind blowing. They also have a thing called a retrieval API, which allows developers to share proprietary knowledge bases with chatgpt. So if you have a company knowledge base or some other kind of content, you can share with Chad GPT so that Chad GPT can be aware of that. And there are some privacy concerns, but the company has said they're gonna sandbox that data and protect it. As an example, I'm planning on writing a book on SaaS using touch EPT. And I'm gonna put together all the previous articles and talks I've done as a database, so I can then work with that and chat GPT. So you're gonna have more and more developers sharing information with chat GPT. You're gonna have chat GPT able to update its training based on sort of the last 2 years being able to search the Internet. And I think that as those 100 of millions of users use the product and as developers keep sharing more and more of these datasets, the AI is gonna get smarter and smarter. And then what's gonna happen is both consumers and developers are gonna wanna use or build on the smartest API. Jason Calacanis (00:29:36): Yeah. See, this is where So David Sacks (00:29:37): it feeds on itself. I mean Yeah. Jason Calacanis (00:29:39): I think there might be a I agree with much of what you're saying, but I do think somebody like Facebook, when they release their language model, which they're about to, is not gonna allow chattyBT to have any access to the Facebook corpus of data. And then LinkedIn will do the same. They'll block any access to chatty PT to their data And so then you might say, you know what? I'm doing something related to business and business contacts. I need to use the LinkedIn 1, and they're just gonna block other people's usage up and tell you, hey. You have to come to our interface and have a pro account on LinkedIn, and this all becomes little islands of data. And so I I'm not sure of that. David Sacks (00:30:12): You may be right, Jake. It's too early to have a definitive opinion, but Jason Calacanis (00:30:15): I would say -- You Chamath Palihapitiya (00:30:15): have to believe plugins are gonna be promiscuous. David Sacks (00:30:17): Yes. Exactly. Plugins are the reputation of your idea. Jason Calacanis (00:30:20): Facebook does not have an API. Twitter turned their API. People who are David Sacks (00:30:23): smart as datasets. Jason Calacanis (00:30:25): Core doesn't let people use its data. So I just picked David Friedberg (00:30:28): 3. Jason Calacanis (00:30:28): Those are 3 incredible datasets that don't allow people Craigslist doesn't. So people who are smart do not allow APIs into their data. They keep it for themselves. David Sacks (00:30:37): I think there were a lot of people when the app store rolled out that swore up and down they had never built a mobile app because they didn't wanna give Apple that kind of power that the Internet was open, whereas the App Store is closed and curated by Apple. And sure enough, they all, at the end of the day, had to roll out apps even though in the case of Facebook, it definitely has made them vulnerable because they're downstream of Apple. I mean, Apple now has enormous influence over Facebook's advertising revenue because users have to go through Apple. They never had to do that before with the Internet. Nonetheless, Facebook felt compelled release a mobile app because they knew it was existential for them if they didn't. And I believe that what's happening Jason Calacanis (00:31:14): is -- I don't think it's right analogy. The right analogy would be Google search. Does Facebook Does Craigslist allow their data to be indexed inside of Google search answers? No. Right? They block that for a reason. They and they will write a cease and desease letter David Sacks (00:31:27): fine. So so you know what? Those guys will stay out of it, but look how much content Google Search already has. And I think that chatgpt will start by eating a substantial portion of search because, again, you don't have to go through the 20 links. It just gives you the answer. It's gonna eat a substantial portion of browser usage and app usage, because you're just gonna tell Charge GPT what you wanna do. It will go book your plane ticket. It will go book your hotel room. Jason Calacanis (00:31:50): Yeah. See, this is a And the apps that wanna play David Sacks (00:31:53): in this hold on. The apps that wanna play in this will benefit. So there'll be a powerful incentive for applications to get an advantage by participating. Let me finish my point. Jason Calacanis (00:32:02): Yeah. David Sacks (00:32:02): And then eventually, they will be 4 to do it, not because they get an advantage, but because they're so competitively disadvantaged if they don't participate in that ecosystem. Jason Calacanis (00:32:10): I agree that they'll participate in it, but here's the thing. What's gonna happen is Google's gonna turn on Bard, and I've been playing with Bard. It is 80% of Chat CP2 already. And then when they make Bard a default you know, a little snippet on your Google search return page or Bard is built into YouTube or Chrome or Android or the Play Store, they're gonna roll right over chat j p t because they have billions of users already. So this advantage that you see today, I see that getting rolled real quick because you'll be on YouTube and on the top right hand side will be barred. And when you do a search, it's gonna say, here are other sentences you could do. Oh, you wanna search Mister Beast? When he's helped people or Mister Beast, when he's given away more money, or people who've copied and been inspired by Mister Beast, all that's gonna occur inside of YouTube. And chat GPT is not gonna have access to the YouTube corpus of data. then when you do a search, it's gonna be the same thing. It's gonna be on the right hand side, and it's gonna be playing just like it is in Bing. If you turn on your Android phone, they're gonna make Google Assistant go right into Bard. And Google Assistant is already used by hundreds of millions of people. So I think that Google will roll. I think they're gonna roll chat GP team. Chamath Palihapitiya (00:33:14): I don't know who's gonna win. But I'm looking at this Saksipoo more reductively as a capitalist, which is what are people's incentives because that's what they'll do. Google's incentive is to usurp Chamath GPT's usage by inserting something inside of their existing distribution channels to suppress the ability for you to want to go to the app. Notice bundling. I think Facebook has that same incentive. Oddly, even though Microsoft is such a deep partner, I think certain assets of Microsoft have that incentive. you're talking collectively about 5 or $6,000,000,000,000 of market cap. Then when you add in Alexa and Amazon and Siri, and Apple, what is their incentive? I don't think their incentive is to let this happen. And I think if you look at the Slack Microsoft Teams example of even a better engineer product who's excellent and widely deployed, even at 100 of millions of users doesn't much matter when it's more cleverly distributed and priced. And so those things, again, you may still be right. All I'm saying is it's just so early to know. And as slow and lumbering as some of these big companies are, They are not so stupid as to kill their own golden goose and or defend it when threatened. So I think you just have to let let it see what happens. David Sacks (00:34:38): wanna finish the point on Google, and then we can move on to the bundling thing. Sure. Let me just make the counterargument, which is that I think Google is called completely flat footed here. even though they shouldn't have been because they published the original paper on transformers in 2017. They should have seen where all of this was going, but they didn't. Open AI used that paper and commercialized it. And the proof of that is there was just a lawsuit a couple of days ago or at least a claim by a former employee of Google who quit because he said that they were using chat GPT to train their AI. So their AI is so far behind. They were violating the terms of use. Hold on. They were violating the terms of use of open AI to train their own AI on chatgpt. That's not a good sign. That's not a good sign. I also think Hold Jason Calacanis (00:35:26): on.Sense. David Sacks (00:35:28): Oh, Hold on. Let me I'm just reading the counterargument here. I mean, don't dismiss it out of your hand. Give me a chance to explain it. Moreover, chatgpt4, which was just released a few weeks ago. We know that OpenAI had that. They were using it internally for 7 months. So the state of the art is not what we're using. It's what OpenAI has internally. They're obviously working now on chatgpt5. And so if you're saying that barred is 80% of Chat GPT 4, well, I got news for you. It's probably 50% or 20% of chatgpt5. And who knows what the product roadmap is inside of OpenAI? I am sure that they've got 200 ideas for things they could do to make it better and lowing fruit. But look, regardless, I think the pace of innovation here in development is gonna speed up massively. I mean, there is gonna be a flurry of activity. I agree. It's hard to know exactly how it's gonna play out. But I think this idea that, oh, it's a foregone conclusion these big companies are just gonna catch up with OpenAI. I I think that there's a strong counterargument That's not the case. Chamath Palihapitiya (00:36:32): I'm making a very specific argument. It's not a foregone conclusion where all the value will get captured. Just like in any of these major tidal waves, If you make the bets too early, you typically don't make all the money. And it tends to be the case, and it has been in the past at least with these transformative moves, it's sort of in the early third of the cycle is where the real opportunities to make the tons of money emerge. And there's a lot of folks that show you a path and then just don't necessarily capture the value. I'm not saying that that's gonna be the case here. All I'm saying is if history is a guide, all of these other big waves have shown that fact pattern. And so I'm very excited and I'm paying attention. But I'm just being circumspect with this idea that having been in the middle of these couple of waves before it, I made all money by waiting a couple of years. I don't know if that's gonna be true this time around, but David Friedberg (00:37:24): -- David Sacks (00:37:24): Right. David Friedberg (00:37:24): -- Chamath Palihapitiya (00:37:24): that's sort of my posture right now. David Sacks (00:37:25): Shamal, you look you obviously have a point because we're only 4 months in stock. We know where this is gonna be in 5 So you could be right. Jason Calacanis (00:37:31): To your point, Sachs -- Yeah. David Friedberg (00:37:32): -- Jason Calacanis (00:37:32): I think it's clear, and this is, you know, big ups to the OpenAI team, that they will be one of the top 2 or 3 players. Absolutely. We all agree on that, which is extraordinary in itself. And the top 4 players, Friedberg, are obviously gonna be. Microsoft OpenAI will call that, like, whatever, that little, you know, pairing. And then Google, Facebook. And then we haven't talked about Apple, but, obviously, Apple is not gonna take this sitting down and, hopefully, they'll they'll get in gear and have Siri, you know, make it to the next level or they'll just put her out to pasture. If you were to look at those David Friedberg (00:38:07): 4, Jason Calacanis (00:38:08): and we're sitting here a year from now, who has the best product offering, who has the biggest user base? Just take a minute to think about that because You were at Google, and we all know the the word on the street is it's the return of the kings. Larry and Sergei are super engaged by all reports. Every back channel, everybody I talked to is saying that they're every day, they're obsessed with Google's legacy now and making this happen. So what can you tell us in terms of who you think a year or 2 from now will have the biggest user base, and be the most innovative amongst that quartet, or maybe you think there's other players who will emerge? David Friedberg (00:38:45): The advantage that OpenAI has which is the advantage that any, call it, emerging, you know, advantage competitor has -- Jason Calacanis (00:38:56): Oh, jeez. David Friedberg (00:38:58): Yeah. Outsideer is that the incumbents are handicapped by their current scale. Much of the consideration set that Google has had in deciding what features and tools to launch with respect to AI over the last couple of years has been driven fundamentally by a concern about public policy and public reaction. And I know this from speaking to folks there that are close enough to to kind of indicate. Like, Google has been so Targeted has been such the point of attack by governments around the world with respect to their scale and monopoly and monopolistic kind of behavior, as some people have framed it, privacy concerns, you know, etcetera, etcetera. The fines in the EU are extraordinary. that so much of what goes on at Google today is can I get approval to do this? And so many people have felt so frustrated that they can't actually unleash the toolkit that Google has built. And so they've been harnessed and focused on these internal capabilities. I think I mentioned this in the past, but things like What's the right video to show on YouTube to keep people engaged? What's the right ad to show to increase click through rates, etcetera, etcetera. versus building great consumer products for fear of the backlash that would arise and governments coming down on Jason Calacanis (00:40:11): that ultimately. David Friedberg (00:40:12): And, ultimately, attacking the the revenue and the core revenue stream. And this is no different than any other kind of innovative dilemma. You know, any other business of scale in any other industry historically ultimately gets disrupted because their job at that point is to protect their cash flow and their revenue stream and their balance and their assets not to disrupt themselves. especially as a public company, especially under the scrutiny in the watchful eye of governments and regulators. So I think Google has in aggregate probably good competitive talent if not better talent than OpenAI and others. Google has arguably the best corpus of data upon which to train the best capabilities, the best toolkit, the best hardware -- Which Chamath Palihapitiya (00:40:53): user base? David Friedberg (00:40:54): -- the lowest cost for running these sorts of models, the lowest cost for serving them, etcetera, etcetera. So frankly, they're way behind. The battle is there is to lose if they are willing to disrupt themselves. And this is the moment that Larry and Sergey should wield those founder shares that they have, and they should wield the comments that they wrote in that founder's letter. that they will always make the right decision for the long term for this company, even if it means taking a cost in the short term and disrupting themselves. this is the moment to prove that those founder shares were worth, you know, the the negotiation to get there and And I think that it is gonna require a real degree of scrutiny, a real degree of regulatory uncertainty, a real degree of challenge by governments, and public policy people, and perhaps even a revenue hit in the near term to realize the opportunity. But I do think that they're better equipped to win if they chose to. Well said. Jason Calacanis (00:41:45): Well, really well said. I think the founder share insight is particularly interesting, Saxx. The fact that David Friedberg (00:41:50): they fought for those Jason Calacanis (00:41:51): that did nothing with them. Gotcha, Chamath Palihapitiya (00:41:53): No. No. I was just gonna say the exact same thing. It's like if they don't use it now, what would it take and when? Yeah. This is cool. David Friedberg (00:42:00): -- Chamath Palihapitiya (00:42:01): yet another yet another case of the emperor has no close. Just a power grab by Silicon Valley execs, which was meaningless because if in this moment you don't wield that power, and break that company into bits as you need to, what was the point of having it? Jason Calacanis (00:42:14): Do they need to come in and say, we're going to give barred results to 10% of users? and ask them to get feedback on it. because who has more queries than just one point. I want you to make that for Friedberg. Yeah. Yeah. Who has more Reinforcement Learning, then Google. That search box is everywhere, and people write question after question, and Gmail. David Friedberg (00:42:35): And and Google Docs, etcetera, etcetera. Jason Calacanis (00:42:36): I mean, they have so many people asking questions, and YouTube might be the the transcripts of YouTube overall. David Friedberg (00:42:43): every video and the image of every video. Banana. Jason Calacanis (00:42:45): And the comments under it, you know comments under the video. You have the transcript of what happened in this video, and then what was the question and answer underneath it? David Friedberg (00:42:53): Let me make the counterpoint. Please. To my own point, like, look at how Gershner came after Zuck. So Zuck had his point of view, his strongly held belief that ARVR was the future of the platform. That's what he wanted to bet into. That's what he wanted to lean into. It's what he wanted to build the company against. He did it. And then the financial analysts and the investors came at him and said, this is a waste of money. Focus on making money. You have a responsibility to shareholders. F those founders' shares. You don't deserve that 10 x voting. Right? Or whatever the framing might have been to get him to say, you know what? I acquiesce. I'm giving it up. Jason Calacanis (00:43:25): I think that we should David Friedberg (00:43:26): also think about what's gonna happen on the other side. Google is a trillion plus dollar market cap company. Their their shares are owned by every public endowment, public pension fund. institutional investor owns Google in their portfolio. So the backlash against Google making a hard bet like this, and potentially destroying 1,000,000,000 of dollars of cash flow in the process every year will not be easy to do. That the same sorts of letters that Gersner et al and, obviously, we love Gersner and, you know, can all defend him all day long. At Zuck is what might may end up happening with with Alphabet if they did choose to go this path. Jason Calacanis (00:43:58): Sacks. What do you think here about the founder share specifically in Google's chances of disrupting themselves and, you know, just putting this into every product and shoving it down user's throats and catching up. David Sacks (00:44:11): Well, I mean, with all due respect, Larry and Sergey. I mean, they've been on the beach a long time. Jason Calacanis (00:44:17): That's a long beach time. David Sacks (00:44:18): This just reminds me of Apollo Creek coming out of retirement in Rocket 4. Get Chamath Palihapitiya (00:44:23): a lot of shape. Jason Calacanis (00:44:24): Get a David Friedberg (00:44:24): lot of shape. David Sacks (00:44:26): Lot of a lot of fans there, but Chamath Palihapitiya (00:44:29): It could be a little out of shape. David Sacks (00:44:31): Sam Walton may not look Ivan Drago, but but this this is one shrewd character. Chamath Palihapitiya (00:44:35): He's fit. David Sacks (00:44:35): This is one shrewd character. I mean David Friedberg (00:44:37): -- Chamath Palihapitiya (00:44:37): Altman is fit. He's fit. He's been in the arena. David Sacks (00:44:40): Yeah. He's you know, he's a multi time founder who sat at the top of YC and got to see everything that worked David Friedberg (00:44:45): -- Jason Calacanis (00:44:45): Yep. David Friedberg (00:44:46): -- David Sacks (00:44:46): and got to see all the research. And he's been plugging away at this for, what, like, 8 years. So -- Yep. -- there's a there's a big I just think there's a big gap to catch up on. Now Google has all the resources in the world, and they've got a lot proprietary assets too, and they've got all the incentive in the world. So do I think that Google will be one of the top 4 players in AI, absolutely. But this idea there's gonna come and steamroll open AI on top Chamath Palihapitiya (00:45:12): of that. Jason Calacanis (00:45:12): I got a prediction. within next year, Larry and Sergei take the title of co CEOs, and then they do a demo day where the 2 of them get on stage stop. And they actually do the demos of these products. If that happens, that's -- Fictional -- -- notification stop. That's it. That's listen. And Bezos is gonna run for president. Those are my 2 prediction taking a lot of producers. Can you imagine if Larry Freeburg, where are the chances of Larry and Sergei taking Kos CEO slots? That's prediction 1. And then prediction 2, What are the chances of them running the next Google IO, where they get on stage, and they walk people through all the products that they shepherded? and that they have invested interested in that they're they want a demo. David Friedberg (00:45:50): There is an institutional problem at Google at the top level, which does need to be solved which is this position of constantly being in defense against the scrutiny again of regulators and public policy folks and and you know, all these different groups that are against Google. And so as a result, the the kind of cultural seasoning particularly at the executive and the board level, has been one of, like, you know, protect the nest. Don't overreach. Don't overstep. And it's a real you know, I think one for the for the business school books or whatever, ultimately is what they end up doing about it. because now is, you know, the time when that defensive posture is really kind of putting the the entire business at risk. The same David Sacks (00:46:34): thing happened to Microsoft, remember, in the late nineties David Friedberg (00:46:36): -- Chamath Palihapitiya (00:46:36): That's right. David Friedberg (00:46:37): -- David Sacks (00:46:37): when they got crushed by that antitrust lawsuit -- To get defensive. -- defensive. Chamath Palihapitiya (00:46:41): Well, that can no. But that consent decree, they put a David Friedberg (00:46:43): they had a wartime CEO come in. Balmer came in and, you know, followed by kind of an innovative guy who could kinda continue to build. And I think that there may be a moment here. I look. I love Sundar. He he's a he's a great guy, great CEO. Cassandra and I don't know if I guys Fiber told you this. He and I started at Google on the same day. We're both in the same nuclear class. We wore the freaking hat on the TGIF day and on stage. He was a product manager, and now he runs the company. I think the question is, like, whether it's the CEO or the broader hold kind of executive org or the board, A degree of disruption necessary to shift that cultural seasoning is so necessary right now for them to have a shot at this. And similar to what you just said, Sax, like, you're gonna need a bomber type moment, to kind of, you know, reinvigorate that business. Chamath Palihapitiya (00:47:29): And by the way, I'll tell David Sacks (00:47:30): you such a moment, I think, than us. David Friedberg (00:47:31): More of a softer moment. Jason Calacanis (00:47:32): Well yeah. because it it's an important port point when bomber took over during that period after Gates when they were on their heels, he basically just focused on revenue and paying dividends and stock buybacks and the stock went sideways, and he missed mobile. And now -- Yeah. -- missing -- Yeah. Chamath Palihapitiya (00:47:49): Well, wait. You're you're forgetting one big thing, which is that that was also because he had operate under a consent decree to the DOJ. Exactly. So the product managers of Microsoft were replaced with lawyers from the Department of Justice, and you had to get their sign off before you could ship anything. So We have to remember that those things probably slowed Microsoft down as well. And the great thing that Satya had was a blank slate and the removal of that consent decree. So he was able to do everything that just made a lot of sense, and he's executed flawlessly. I think the problem at Google is not Sundar or Larry or Sergei. I think it's more in the deep bowels of middle management of that company, which is that there's just far too many people that probably have an opinion. And their opinion is not shrouded in survival. their opinion is shrouded in elite language around what is the moral and ethical implications of this and where Has this been properly tested on the diaspora of 19 different ethnic tribes of the Amazon? That's the kind of decision making that is a nice to have. when you are the 2nd or third most valuable technology company in the world, but you have to be able to pause that kind of thinking and instead get into wartime survival mode, and it's very hard. So it doesn't almost matter at this point what Sundar wants. The real question is what is the capability of middle management to either do it or get out of the way? And I think that in all of these big companies that struggle, What you really see is an inability for a middle management to get out of the way or frankly, to just you need somebody to then fire them. And if you look at folks who get their groove back, let's see what Facebook does. What are they targeting? They're targeting middle management. If you look at what Elon does in the companies that he owns, there is virtually no middle management. Chamath Palihapitiya (00:49:47): It's like get out of the way. Build product. Build product and ship it. Yeah. And what is the core truth? And so if failure is there in front of you, and if David is right, that you 200,000,000 users come out of nowhere who are voting every day with their time and attention to use an app And that doesn't create a fire alarm fire where you get middle management out of the way and you are the senior most people talking to the people doing the work. and shipping things every day, you're you are toast. You are toast. A lot of people are starting to think we're moving a little bit too fast. when it comes to OpenAI's incredible performance, which are GPT 4, the plug ins Jason Calacanis (00:50:28): and all this. And so The Future of Life Institute, which was formed in 2015, it's a nonprofit. That's focused on derisking major technology like AI, They did a petition titled Pausegiantai experiments an open letter. A bunch of computer scientists assigned this letter And the the letter quote says, we must ask ourselves, should we let machines flood our information channels with propaganda and untruth? Should we automate away all the jobs, including the fulfilling ones? Should we develop non human minds that might eventually outnumber at smart? obsolete and replace us should we risk loss of control of our civilization. A number of notable tech leaders like Elon, Steve Wozniak, and a handful of deep mind researchers have signed it. What do you guys think of the latter? Are we gonna slow down or not? And then we could ask the question generally how close are we getting to AGI, which is what everybody scared is that these agents start working with each other in the background to do things that are against human interest. I know it sounds like science fiction. But there is a theory that when these AIs start operating on their own, like we explained in the previous sort of segment here with plugins and they make agents that are operating based on feedback from each other, could they get out of control and beam chievous and then work against human interests. So what do you think, sex? David Sacks (00:51:49): I think there's a difference between what could happen in the short term and then what could happen in the long term. I think in the short term, everything we're seeing right now is very positive. And let me just give you an example. There was a really interesting tweet storm about a guy who wrote about how Chad GPT saved his dog. Did you guys see this? This is this is one of the really mind blowing ones to make use cases. So his dog was sick, took him to a vet, vet prescribed some medication. 3 days later, dogs still sick in fact even worse. So the the owner or the the pet does literally copied and pasted the lab result for the blood test for the dog with all the the lab values into chat GPT and set what could this be? Like, what's your likely diagnosis? Chat GPT gave David Friedberg (00:52:35): 3 David Sacks (00:52:36): possible answers. 3 illnesses. The first one was what the vet basically had diagnosed with, so that wasn't it. The second one was excluded by another test. So he then went to a a second vet and said, listen, I think my dog has the third one. And vet prescribed something and sure enough dog is cured saved. So that's really mind blowing that even though Chamath GPT hasn't been specifically optimized, as far as we know, for lab results, it could figure this out. The reason I'm mentioning this is it gives you a sense of the potential here to cure disease, to, you know, like, I could see major medical breakthroughs based on the AI in the next 5 or 10 years. Now the question is, like, what happens in the long term. You know, as the AI gets smarter and smarter, and we are kinda getting into the realm of science fiction. But here would be the scenario is you're on chatgpt10 or 20 or whatever it is or maybe some other company's AI. And the developers asked the AI, hey, how could you make yourself better? now do it, which is a question we ask Chat GPT all the time in different contexts. And so Chat GPT already have the ability to write perfect code by that point. I think, you know, code writing is one of the, I think, of its superpowers already. So it gives itself the ability to rewrite its code, to auto update it, to recursively make itself better. I mean, at that point, isn't that, like, a speciation event, doesn't that very quickly lead to the singularity if the AI has the capability to rewrite its own code, to make itself better you know, won't it very quickly write billions of versions of itself? And, you know, it's very hard to predict what that future looks like. Now I also don't know how far away we are from that. That could be 10 years, 20 years, 30 years, whatever. But I I think it's a question worth ask. thing for sure. Jason Calacanis (00:54:26): Is it worse slowing down, though, Saxx? Should we be pausing? Because based on what you've said, and I think you've framed it properly, When these things hit a certain point and they start reinforcing their own learning with each other, they can go at infinite speed. Right? The the this is not comparable to human speed. They could be firing off millions, billions of different -- I Chamath Palihapitiya (00:54:47): think you're right. -- scenarios. We're definitely now on this fuck around, find out -- Curve. Yeah. And so there is only one way to really find out, which is Somebody's gonna push the boundaries. The competitive dynamics will get the better of some startup. They'll do something that People will look back on and say, woah. That was a little. That was a bridge too far. So, yeah, we're just a matter of time. David Sacks (00:55:12): Yeah. I I think we're not gonna slow down. I actually think it's going the other way. I think things are gonna speed up. And and the reason they're gonna speed up is Because the one thing Silicon Valley is really good at is taking advantage of a platform shift. And so when you think about, like, all the VCs and all the founders, you know, everyone accuses us of being lemmings. And so when there's, like, kind of like a fake platform shift or people kinda glom onto something that ends up not being real. Everyone's kinda got egg on their faces. But the flip side of that is that when the platform shift is real, Silicon Valley is really good at throwing money at it. The talent knows how to go after it, and they keep making it better and better. And so that's the dynamic we're in right now. If you look at 70% of the last YC class was ready, all AI startups, sure the next one will probably be 95%. So I think that we're on a path here where the pace of innovation is actually gonna speed up. Companies are gonna compete with each other. They're gonna seek to invent new capabilities. And I think the results are gonna be all be incredibly positive for some period of time. Like, you know, the vet example, we're gonna cure illnesses. We're gonna solve major problems. Jason Calacanis (00:56:21): positive, then we invest more. We trust more. But the paradox of that as Chomont is pointing out, Friedberg, is if we trust it more, we invest more than some person in a free market is gonna say, you know what? I need to beat Chat GPT. Therefore, I'm gonna take the rails off this thing. I'm gonna let go faster and take off some constraints because I need to win. And I'm so far behind, how do you feel about that scenario, that sort of Tremontin Sachs teed up Friedberg. David Friedberg (00:56:48): I think there's, like, GPT 3, I think, ran on 700 gigs. Is that right? g does anyone know what GPT 4 runs on? It's gotta be on some number that's, you know, not to not not many multiples of that, but look. Someone could make a copy of this thing and fork it and develop an entirely new model, I think that's what's incredible about software and digital technology and also kind of, you know, means that it's very hard to contain. similar to, like, what we've seen in in biology. Ever since biology got digitized through DNA sequencing Jason Calacanis (00:57:32): and the ability to kind David Friedberg (00:57:33): of express molecules through gene editing you know, you can't control or contain the ability to do gene editing work at all because everyone knows the code. Everyone can make CRISPR cast molecules. Everyone can make gene editing systems in any lab anywhere. Once it was out, it was out. And now there's hundreds of variants for for doing gene editing, many of which are much improved over CRISPR Cas9. I use that as an analogy. because it was this breakthrough technology that allowed us to precisely, specifically edit genomes and that allowed us to engineer biology and do these incredible things where biology effectively became software. And remember, CRISPR Cas9 gave us effectively a a word processing type tool find and replace. and the tooling that's evolved from that is is is much better. So whatever is underlying, whatever the parameters are, for GPT 4, whatever that model is. If a close enough replica of that model exists or a copy of that model is made, And then new training data and new evolutions can be done separately. You could see many, many variants that kind of emerged from here. And I think this is a good echoing of Timov's point. We don't know what's ultimately gonna win. Is there enough of a network effect in the plug in model, as Saks pointed out, to really give OpenAI the sustaining competitive advantage? I'm not sure. the model runs on 700 gigs. That's less data than, you know, fits on my iPhone. So, you know, I could take that model. I could take the parameters of that model and I could create an entirely new version. I could fork it, and I could do something entirely new with it. So I I don't think you can contain it. I don't think that this idea that we can put in place some regulatory constraints and say it's illegal to do this or, you know, try and, you know, create IP around it or protections around it is realistic at the state. The power of the tool is so extraordinary. The extendability of the tool it's so extraordinary. David Friedberg (00:59:26): So the economic and, you know, the various incentives are there for, you know, other models to emerge And whether they're directly copied from someone hacking into OpenAI servers and making a copy of that model or whether they're, you know, open sourced or whether that someone generates something that's 95 percent is good, and then it forks and a whole new class of models emerge. I think this is like, it's as Saks pointed out, highlighting the kind of economic market uprooting, social uprooting potential, and many models will will will will start to kinda come to to market. Jason Calacanis (00:59:57): What do we think the impact of white collar jobs getting annihilated by technology if that in fact comes to pass. David Friedberg (01:00:03): -- thing on this. Yeah. Look. I -- Well, Jason Calacanis (01:00:04): let me just share let me just give one example here. Yeah. So here's a Reddit post that I was made aware of earlier this week. I lost everything that made me love my job through mid journey overnight. I am employed as a three d artist at a small games company of 10 people, Our team is 2 people he basically explains. He says since mid journey version 5 came out, he's not an artist anymore nor a 3 d artist. All they do is prompting photoshopping and implementing good looking pictures. And he basically says, this happened overnight, and he had no choice. His boss also had no choice. He says, I am now able to create rig an animated character that spit out from MJ mid journey in 2 to 3 days. Before it took us several weeks in 3 d, the difference is that he cares about his, you know, job. And for his boss, it's just a huge time money saver. He's no longer making art. And the person who was number 2 in the organization who didn't make as good content is him, is now embracing this technology because it carries favor with his boss. And Ian's basically saying, Getting a job in the game industry is already hard, but leaving a company and a nice team because AI took my job feels very dystopian. I doubt it would be better in a different company also. I am between grief and anger, and I am sorry for using David Friedberg (01:01:16): -- Jason Calacanis (01:01:16): My gosh. -- your art fellow artists. Chamath Palihapitiya (01:01:18): This is yet another reason that Figma really needs to close this acquisition from Adobe. I mean, it's like the value of these apps are just getting gutted. If you take a workflow management tool for things like design and imagery, and you reduce it by an order of 90%. It's like, what is that app experience worth? And how could you replicate it if you were a big company that already has distribution? That's one comment. But what I would tell you, Jason, to answer the white collar question is, I think there are a handful of companies you need to look at exclusively. because they will be the first ones to really figure out how to displace human labor. And that is TCS, so Tata consulting services. Accenture, Cognizant. These are all the folks that do coding for higher work at scale. I think Accenture has something like 750,000 employees. So the incentive to sort of squeeze OpEx to create better utilization rates to increase profitability is quite obvious it always has been. They will be the first people to figure out how to use these tools at scale before the law firms or the accounting firms or any of those folks even sort of try to figure out how to displace white collar labor. I think it's gonna be the coding jobs, and it's gonna be the coding for higher jobs. that companies like Accenture And TCS. So those business processing -- They do for other people. David Friedberg (01:02:42): -- Jason Calacanis (01:02:43): developer kind of folks, they're gonna need half as many people, 25% as many people, Chamath Palihapitiya (01:02:48): we're gonna find out the efficient frontier. Yeah. David Sacks (01:02:51): I see it a different way. I mean, This argument that productivity leads to job loss has been made for 100 years, and it's always been refuted. When you make human beings more productive, it leads to more sperity, more wealth David Friedberg (01:03:03): -- Growth. -- David Sacks (01:03:03): more growth. And so, yeah, it's easy to think about in a narrow way the jobs are gonna be place, but but why would that be? It's because you're giving leverage to other human beings to get more done. And some of those human beings, really, anybody with a good idea is now gonna be able to create a startup much more easily. So you're gonna see a huge explosion in creativity, in startup creation, new companies, new jobs, Imagine, think about the case of, you know, Zuckerberg founding, Facebook, at Harvard. He wrote the first version himself, maybe with a couple of friends. that project happened and turned into a giant company because he was able to self execute his idea without needing to raise Venture Capital or even recruit employees, even really before forming a company. Anyone with a good idea is gonna be able to do that soon. You're gonna be able to use these AI tools. They truly will be no code. You'll be able to create an app or a website just by speaking to some AI program in a natural language way. Jason Calacanis (01:04:01): So more flowers will bloom. More stars will bloom. More projects. David Sacks (01:04:04): Now now now, well, it will create it will create, I think, a lot of dislocation. But for every testimonial that is like the one that you showed which I think is I'd say a little bit overly dramatic, I have seen David Friedberg (01:04:16): 10 David Sacks (01:04:16): or a100 testimonials from coders on Twitter or other blogs, talking about the power that these new tools give them they are like, this makes me a David Friedberg (01:04:26): 10 David Sacks (01:04:26): x engineer. Chamath Palihapitiya (01:04:27): Right. David Sacks (01:04:27): And he and and especially these, like, junior engineers who write out a school who don't have 20 years of coding history, they get superpowers right away. Like, it makes them so much better. Jason Calacanis (01:04:37): It's a proper response from this -- Jake Cal. David Friedberg (01:04:39): Look. Wait. Hold on. Let me let me give you a response to that guy. So so and using Saks's point, That guy is saying what used to take me weeks I can now do in 2 to 3 days, and I feel like my work is gone. And that's because he's thinking in terms of his output being static. And if he thinks about his output being dynamic, he can now, in the matter of 3 weeks instead of making one character, he can now make a character every 2 days, so he can make 30 characters in 3 weeks. That's an alternative way for him to think about what this tooling does for him and his business. The number of video games will go up by 10 x or a 100 x or a 1000 x. The number of movies and videos that can be rendered in computers can go up by 10 x or a 100 x or a 1000 x This is why I I really believe strongly that in some period of time, we will all have our own movie or our own video game ultimately generated for us on the fly. based on our particular interests. There will certainly be shared culture, shared themes, you know, shared morality, shared things that that that tie all these things together and that will become the shared experience. But in terms of, like, us all consuming the same content, it will really like, with YouTube and TikTok, we're all consuming different stuff all the time, and this will enable an acceleration of that evolution and personalization. I'll also highlight, you know, back in the day, one human had to farm a farm by hand. And we eventually got the tool of a hoe, and we could put it on the ground and make, you know, make stuff faster. And then the way we got a plow. And then we got a tractor And today, agricultural farm equipment allows 1 farmer to farm over 10000 acreage. You go to Western Australia. It's incredible. These guys have 24 row planters and harvesters, and it's completely changed the game. David Friedberg (01:06:19): So the unit of output per farmer is now literally millions of times what it was, just a 150 years ago. Jason Calacanis (01:06:25): In that case, Friedberg, nobody wants to do backbreaking labor in the fields, and everybody wants that shit of our food. But in this case, let me just read you one quote that I didn't read in the original reading of this. He says, I want to make art that isn't the result of scraped Internet content from artists that were not asked. And so I I think that's part of this is that it's bespoke hard. But -- Well, the -- Yeah. I I do the one question I had for Saxx was Saxx, you we started this conversation with saying, hey. This is different than anything in terms of efficiency that came before it. This is I'm I'm gonna put some words in here, but this is like a step function more efficient. So to the argument of, hey. Efficiency has always resulted in, you know, more ideas, and and we found something to do with people's time, is this time different potentially because this is so much more powerful. This isn't just like a spell checker. I Chamath Palihapitiya (01:07:14): would say differently. I think and I agree with what Jake Al is saying Because I think that the thing that technology has never done is try to displace human judgment. it's allowed us to replace physical exertion of energy, but it is always preserved humans injecting our judgment. And I think this is the first time where we are being challenged with autonomous systems that has some level of judgment. Now we can say, and it's true, again, reform on sin, that that judgment isn't so great. But eventually and because of the pace of innovation, eventually is probably not that far away. to judgment will become perfect. I'll give you a totally different example. You know, how many pilots are there in the world? Will we at some point in the next 10 years want folks to actually manually take off and land, or will we want precision guided instrumentation and computers and sensors that can guarantee a pitch perfect landing every single time in kinds of weather conditions so that now planes can even have 50 x the number of sensors with a computer that can then process it and act accordingly. just a random example that isn't even thought of when we talk about sort of where AI is gonna rear its head. I think that this judgment idea is an important one to figure out. because this is the first time I've seen something that is bumping up against our ability to have judgment and what this person was talking about in this mid journey example is his judgment has been usurped. David Friedberg (01:08:51): Yes. Yeah. I I would disagree. So, like, look yeah. Let me just let me just make one point on this. So, you know, an image is a matrix of, you know, data that's rendered on a screen and as pixels, and those pixels are different colors, and, you know, that's what an image is. Chamath Palihapitiya (01:09:08): Is it or is it is it the judgment of the creator? David Friedberg (01:09:11): Well, no. I'm just saying an image in general. So, like, when when Adobe Photoshop and digital photography arose, photographers were like, this is, you know, BS, why you digitizing photography with analog and beautiful before. And then what digital photography allowed is the photographer to do editing. and to do work that was creative beyond what was possible with just a natural photograph taken through a camera. And they're arguably different art forms, but it was a new kind of art form that emerged. through digital photography. And then in the early nineties, there was a plug in suite called Kye's power tools that came out in Adobe Photoshop And it was a third party plugin that said, you would you would buy it, and then it would work on Photoshop. And it did things like motion blur, sharpening, pixelation, all these interesting kind of, like, features. And prior to those tools coming out, the judgment of the digital artist, the digital photographer, was to go in and do pixel by pixel changes on the image to make that pixel to make that image look blurry or to make it look sharper or to make it look like it had some really interesting motion feature. and the Kai's power tools created this instant toolkit where in a few seconds, you created a blur on the image. And that was an incredible toolkit But a lot of digital artists said, this is automating my work. What is my point now? Why am I here? And the same happened in animation when 3 when, you know, CGI came around, animators were no longer animating cells by hand. And in every point in this evolution, there was a feeling of loss initially, but then the evolution of a whole new art form emerged. and an evolution of a whole new area of human creative expression emerged. And I think we don't yet know what that's gonna look like. Chamath Palihapitiya (01:10:42): But do you think -- -- respect David Friedberg (01:10:43): to what we're seeing here? Chamath Palihapitiya (01:10:44): Do you think the the level of judgment that AI offers you is the same as the level of judgment that Kai Power Tools offered? David Friedberg (01:10:50): Yeah. Look. I mean, I think that the person making the judgment or the decision about which sult to change into what color felt like, you know, I have control. And I think it's ultimately like a Jason Calacanis (01:10:58): sensor control. Chamath Palihapitiya (01:10:59): I just told her I disagree with you. David Friedberg (01:11:00): I mean, I think that Jason Calacanis (01:11:01): this is -- It's a magnitude different. I remember this one. It's Chamath Palihapitiya (01:11:03): more of it than a magnitude difference. Jason Calacanis (01:11:05): Yeah. It's it's a whole different tool. Chamath Palihapitiya (01:11:07): It's still love it's David Friedberg (01:11:08): on you. You -- You don't look. You and I you and I have sat in spreadsheets many times, and we've Chamath Palihapitiya (01:11:12): I'm generally happy with this idea. So I'll give you a different example. Today, we use radiologists and pathologists to identify cancers. Yep. There are closed loop systems. We have one right now that's in front of the FDA that is a total closed loop system that will not need any human input. So I don't know what those folks do. Except what I can tell you is that we can get cancer detection basically down to a 0% error rate. That is not possible with human intervention. That is judgment. Right. So I just think it's important to really acknowledge that this is happening at a level that it's never happened before. You may be right that there's some amazing job for that radiologist or pathologist to do in the future. I don't know offhand what that is. But these are closed loop systems now that think for themselves and self improve. David Friedberg (01:12:06): I get it, but I think that there there is an unfathomable set of things that emerge We did not have the concept of Instagram influencers. We did not have the concept of personal trainers. We did not have the concept of, like, all these new jobs that have emerged in the past couple of decades that people enjoy doing, that they can make money doing, that is a greater kind of experience and level of fulfillment for those that choose and have the freedom to do it than what they were hap having to do before when they had to work just to make money. Chamath Palihapitiya (01:12:36): What do you think of that radiologist or pathologist wants to do? Be a trainer or a pilates instructor? David Friedberg (01:12:40): No. I think we don't know what that's gonna look like. Jason Calacanis (01:12:43): Alright. Sagging the same yeah. You you have any thoughts on this as we wrap this topic? It's obviously a lot of passion coming out David Friedberg (01:12:49): -- Jason Calacanis (01:12:49): Yeah. David Friedberg (01:12:49): -- Jason Calacanis (01:12:49): the elimination of white collar jobs in a massive way. David Sacks (01:12:52): I think that this is a short term versus long term thing. In the short term, I see the benefits of AI being very positive because I don't think it's in most cases, wiping out human jobs. This is making them way more productive. You still need the developer. It's just that there are five times or David Friedberg (01:13:08): 10 David Sacks (01:13:08): x more productive. But I don't think we're at the point in the short term where you're gonna be able to eliminate that role entirely. And what I've seen in basically every start I've ever been a part of is that the limiting factor on progress is always engineering bandwidth. That is always the the thing that you wish you had more of. David Friedberg (01:13:26): Totally. David Sacks (01:13:26): It's the product road map is always the most competed on thing inside the organization and everyone's trying to, you know, get their project prioritized because there's just never enough enduring bandwidth. It's really the lifeblood of the company. So if you make the developers more productive, it maybe just accelerates to product roadmap. I just I don't think in the short term, what's gonna happen is these companies are gonna look to cut all their developers because 1 or 2 of them can do ten times the work. I think that they're gonna try and accelerate their product roadmaps. Now, again, you have this long term concern that maybe you don't need developers at all at some point. But I think that the benefits of developing this technology are so great in the short to mid term that we're going down that path no matter what. And we're just gonna have to find out what that long term really looks And maybe -- Yeah. -- the long term will look very different. I mean, once we're in once we get past the short term, we may have a different long term view. Chamath Palihapitiya (01:14:19): I think in this narrow vertical, I a 100% agree with you. Look, I I think that AI is going to eliminate unit testing. It has already done so. It's going to eliminate most forms of coding. the engineers that you have, all of them will now become 10 x engineers. So with fewer of them or with the same number, you'll be able to do as much or more than you could have before. That's a wonderful thing. And all I'm saying on that specific narrow vertical is you'll see it first rear its head in companies like Accenture and TCS because and cognizant because they have an immediate incentive to use this tooling to drive efficiency and profitability that's rewarded by shareholders. it'll be less visible in other companies. So but what I am saying though is that you have to think about the impact on the end markets for a second. And I think that AI does something that other technology layers have never done before, which is supplant human judgment in a closed loop manner. And I just think it's worth appreciating that there are many systems and many jobs that rely on human judgment where we deal with error bars and an error rate that a computer will just destroy and blow out of the water and we will have to ask ourselves, should this class of job exist with its inherent error rate or should it get replaced fully by a computer which has no error rate. I think that's an important question. That's worth putting on the table. Jason Calacanis (01:15:45): Okay. So let's wrap here. I just have my final thought on it is, like, you're gonna see entire jobs categories of jobs go away. We've seen this before, phone operators, travel agents, copy editors, illustrators, logo designers, accountant sales development reps. I'm seeing a lot of these job functions in the modern world like phone operators previously. I think these could wholesale just go away, and they would just be done by AI. And I think it's gonna happen in a very short period of time. And so it's gonna be about who can transition And some people might not be able to make the transition, and that's gonna be pain and suffering, and it's gonna be in the white collar lines. And those people have more influence, so I think this is could lead to some societal discovery behavior with you, Saks. Chamath Palihapitiya (01:16:22): I'm gonna learn Pilates and be an influencer. Jason Calacanis (01:16:25): That's it. But I do agree with Saks that the the software development backlog, if this is what you're saying, so great that I don't think we'll see it in software development for a decade or 2. There's just so much software that still needs to be made. Alright. Last week, we talked about TikTok. and this first bipartisan hearing we've seen in a long time. And people actually, I think, framing correctly exactly how dangerous it is, in my opinion, to have TikTok in the United States. And, of course, then we get the great disappointment of the actual bill. The restrict act was proposed by Senator Mark Warner, Democrat, Virginia. On March 7th, the problem with it is is it seems like it's poorly worded that there will be civil penalties and criminal penalties to Americans for breaking the law and using software that's been banned. And many people said, you know, This probably is just bad language. I have a question. Yeah. Go ahead. Chamath Palihapitiya (01:17:17): Does it does it apply to incognito mode? because if it doesn't Jason Calacanis (01:17:22): I don't care what is not -- Yes. David Friedberg (01:17:24): -- Jason Calacanis (01:17:24): his word based. David Sacks (01:17:25): No. They're saying they're saying that you can get, you know, you can get fined or 20 years in jail or whatever it is. for using a VPN to VPN to to to TikTok. Jason Calacanis (01:17:34): Freightberg, what are your thoughts on it? David Friedberg (01:17:35): Look, I think this is a real threat to the open Internet. I'm really concerned about the language that's been used that basically speaks to protecting the safety and security of the American people by actively monitoring network traffic and making decisions about what network traffic is and isn't allowed to be transmitted across the open Internet. It's the first time that I think in the United States, we are seeing, like, a real threat and a real set of behaviors from our government that looks and feels a lot like what goes on in China and elsewhere where they operate with a closed Internet and Internet that's controlled, monitored, observed, tracked, and and gates are decided by some set of administrators on what is and isn't appropriate. And the language is always the same. It's for safety and security of the people. The entire purpose of the Internet is that it did not have bounds, that it did not have governments, that it did not have controls, that it did not have systems that are politically and economically influenced that the architecture of the Internet wasn't always would be open. The protocols are open. The transmission of data on that network would be open. And as a result, all people around the world would have access to information of their choosing, and it allowed ultimate freedom of choice. you know, this this kind of is the first of what I'm concerned creates a precedent that ultimately leads to a very slippery slope. saying that TikTok cannot make money in the US by charging advertisers or managing commerce flows is one thing. That's where the government can and should and could if they chose to have a role. But I think going in and and observing tracking Internet traffic and making decisions about what is and isn't appropriate for people I think, is one of the things that we all should be most concerned about what's going on right now. There is no end in sight to this if you allow this to happen in the first time. You know, VPNs, virtual private networks allow you to anonymously access Internet traffic and and and access Internet traffic via remote destinations. David Friedberg (01:19:30): So so that the ultimate consumption of content that you're using can't be tracked and monitored by local agencies or ISPs And I think that saying that that can now be restricted takes away all ability to have true privacy and all rights to privacy on the open Internet. So I'd love to talk about this more. Unfortunately, I gotta run. But this is a super threat to me, and I I I think this is something we should be super super concerned about and that the entire community of technology, Internet, and anyone that wants to have freedom of choice steps up and says, this is totally inappropriate and overreach. David Sacks (01:20:07): Yeah. David Friedberg (01:20:07): There are other ways to manage stuff like this. -- Jason Calacanis (01:20:09): like complete overreach sex. David Sacks (01:20:11): Yeah. Hey. I agree with this. Jason Calacanis (01:20:12): This -- -- intentional overreach or poorly written or somewhere in between, what do David Sacks (01:20:15): you like? Both. I think both. I think this is the biggest bait and switch that Washington the central governments ever tried to pull on us. Everybody thinks that they're just trying to ban TikTok from operating in the US. And if that's all they did, then I think the bill would be supported by most Americans. But that's not what they're doing. They're not restricting TikTok. They're restricting us Jason Calacanis (01:20:35): That's not the goal here. Yeah. Go to bait and switch. David Sacks (01:20:38): It's a huge bait and switch. And so just so you know, what the Act provides is that a US citizen using a VPN to access TikTok could theoretically be subjected to a maximum penalty of 1,000,000 in fines or 20 years in prison or both. Now you know, they'll say, you know, Mark Warner, the sponsored legislation will swear up and down that's not the intent. But the problem is that the language of the bill is so vague that some clever prosecutor may wanna pursue this theory one day, and that needs to be stopped. Also, there's another problem with the bill, which is You think this is just about TikTok. It's not. What they do is, it says here, I guess they don't wanna mentioned TikTok by name. So they're trying to create a category of threatening application. But because it is a category, it's very, very broad. So the bill states that it covers any transaction transaction, not just an app, in which an entity described in paragraph b has any interest And then entities described in some paragraph b are, quote, a foreign adversary. And entities subject to the jurisdiction of organized with laws of a foreign adversary, an entity owned director could roll by either of these. And then it gives the executive branch the power to name a foreign adversary any foreign government regime that one of the cabinet secretaries defines without any vote of congress. So this is giving sweeping powers to the executive branch to declare, you know, foreign companies to be enemies. Jason Calacanis (01:22:08): It feels like the plot of the prequels in Star Wars. Well, emergency Here we go. David Sacks (01:22:13): You know, we criticize China for having a great firewall. What do you think this is? Jason Calacanis (01:22:18): Yeah. I mean, this this should obviously have nothing to do with the American consumer and everything to do with the foreign adversary collecting data of Americans at scale. This is that this could be written in a much simpler David Sacks (01:22:29): way. It should be one sentence, which is that app stores are prohibited from allowing TikTok be an app in their store. That's what they do in India. That's it. Yeah. Case close game over. David Friedberg (01:22:40): I think Jason Calacanis (01:22:40): Chinese doing okay. Right? They they block like a 100 Chinese And I think their society is still functioning. So, you know, all due respect to AOC, you know, like, the idea that a 150 Americans 1000000 Americans are gonna suffer because they can't be by the CCP is kinda nuts. David Sacks (01:22:54): This is gonna give sweeping powers to the security state to surveil us, to prosecute us, to limit Internet usage. This is basically the biggest power grab and bait and switch they've ever tried to pull on us. And, again, if they really were concerned about TikTok, it's one sentence. Jason Calacanis (01:23:13): Yeah. We were done. Alright, everybody. It's been an amazing episode for the Sultan of Science, David Friedberg, the rainman himself, David Sachs, and the dictator, Chamath, Palihapatiya, I am the world's greatest moderator, and we'll see you next time. Bye bye. The Leggett Winter's ride. Rainman David Sanders. David Sacks (01:23:37): And I said -- We open source it to the fans, and they've just gone crazy like that. Jason Calacanis (01:23:50): besties are gone. I don't know the 13th. That is my name on dog thinking, and I'm missing your driveway. Chamath Palihapitiya (01:24:00): We should all just get a room and just have one big huge ordeal because they're all just useless. It's like this, like, sexual friendship that they just need to release somehow. Jason Calacanis (01:24:09): You're a beep beep. David Sacks (01:24:10): What? You're a beep Jason Calacanis (01:24:12): beep. What? What? Where did you get Mercies alien.