星舰发射、福克斯和解、「僵尸独角兽」出走 AI、晚期融资崩塌

Jason Calacanis (00:00:00): Welcome to episode 124 of the all in podcast. My understanding is there's gonna be a bunch of global fan meet ups for episode 125. If you go to Twitter and you search for all in fan meet ups, you might be able to find the link. But Chamath Palihapitiya (00:00:14): just to be clear, we're not they're not official all in Jason Calacanis (00:00:17): they're not. Chamath Palihapitiya (00:00:18): vans, it's self organized, which is pretty mind blowing. But we can't vouch for any particular organization. Right. Jason Calacanis (00:00:24): Nobody knows what's gonna happen at these things. You can get robbed. It could be a setup. I don't know. But I retweeted it anyway because there are 30 one cities where your lunatics are getting together to celebrate the world's number one business technology. podcast. Chamath Palihapitiya (00:00:40): It is pretty crazy. You know what this reminds me of is in the early nineties when Rush Limbaugh became a phenomenon -- Uh-huh. Jason Calacanis (00:00:47): -- Chamath Palihapitiya (00:00:47): there used to be these things called rushrooms. where, like, restaurants and bars would literally broadcast rush over their speakers during I don't know. Like, what for the morning through lunch broadcast, and people would go to these restrooms and listen together. Speaker 3 (00:01:00): What Jason Calacanis (00:01:01): was it like, sex? When you were about sixteen, seventeen years old at the time, what was it like when you hosted this? Chamath Palihapitiya (00:01:05): It was a phenomenon. But that's kinda crazy. We've got, like, a phenomenon going here where people are Jason Calacanis (00:01:10): -- Chamath Palihapitiya (00:01:10): I love it. -- organizing. David Sacks (00:01:12): You've said phenomenon three times instead of phenomenon, he said it's phenomenon. Phenomenal. Jason Calacanis (00:01:18): Why is Saxon a good mochmo? What's going on? David Sacks (00:01:20): There's a specific secret toe tap that you do under the bathroom stalls when you go to a restroom. Jason Calacanis (00:01:26): It's already off the rails. Chamath Palihapitiya (00:01:29): I think you're getting confused about a different event you went to. Speaker 5 (00:01:34): Let your winners ride. Jason Calacanis (00:01:37): Rainman, David Saffens. And I said, we Speaker 5 (00:01:42): open source it to Speaker 3 (00:01:43): the fans and they've discoveries. Jason Calacanis (00:01:49): There's a lot of actual news in the world, and generative AI is taking over the dialogue. And it's moving at a pace that None of us have ever seen in the technology industry. I think we'd all agree. The number of companies releasing product And the compounding effect of this technology is phenomenal. I think we would all agree. A product came out this week called auto GPT. And people are losing their mind over it. Basically, what this does is it lets Different GPTs talk to each other and so you can have agents working in the background and we've talked about this on previous podcasts but they could be talking to each other essentially, and then completing tasks without much intervention. So if let's say you had a sales team and you said to the sales team, hey. Look for leads that have these characteristics for our sales software. put them into our database, find out if they're already in the database, alert a salesperson to it, compose a message based on that person's profile on LinkedIn or Twitter or wherever. and then compose an email, send it to them if they reply, offer them to do a demo, and then put that demo on the calendar of the salesperson, thus limiting a bunch of jobs, and you could run these what would essentially be Crown Jobs in the background forever, and they can interact with other LLMs in real time. Saks I've just gave about one example here. But when you see this happening, give us your perspective on what this tipping point means. Chamath Palihapitiya (00:03:24): Let me take a shot at explaining it in a slightly different way. Sure. Not that your explanation was wrong, but I just think that maybe explain it in terms of something more tangible. Sure. So I I had a friend who's a developer who's been playing with auto GPT. By the way, so you can see it's on GitHub. It's kind of an open source project. It was sort of a hobby project. It looks like that somebody put up there. It's been out for about 2 weeks. It's already got 45,000 stars on GitHub, which is a huge number Jason Calacanis (00:03:51): Explain what GitHub is for the audience. Chamath Palihapitiya (00:03:53): It's just a code repository, and Speaker 3 (00:03:55): you can create, you know, repose of code for open source projects. Chamath Palihapitiya (00:03:57): That's where all the developers check-in their code. So, you know, for open source parties like this, anyone can go see it and play with it. David Sacks (00:04:03): It's like Pornhub, but for developers. Jason Calacanis (00:04:06): It would be more amateur a pornhub because you're contributing your scenes as it were. Your coatings. But, yes, continue -- But Chamath Palihapitiya (00:04:12): in any event, this thing has a ton of of stars. And, apparently, just last night, I got another 10,000 stars overnight. This thing is, like, exploding in terms of popularity. But in any event, what you do is you give it an assignment. And what auto GPT can do that's different is it can string together prompts. So if you go to chat GPT, you prompt it one at a time. And what the human does is you get your answer and then you think of your next prompt and then you kinda go from there and you end up in a long conversation that gets you to where you wanna go. So the question is what if the AI could basically prompt itself, then you've got the basis for autonomy. And that's what this project is designed to do. So what you'll do is when my friend did it, he said, okay. You're an EventPlaner AI. And what I would like you to do is plan a trip for me for a wine tasting in Friedberg this weekend. And I want you to find, like, the best place I should go, and it's gotta be kid friendly. Not everyone's gonna drink. We're gonna have kids there. And I'd like to be able to have other people there. And so I like you to plan this for me. And so what auto GPT did is it broke that down into a task list And every time it completed a task, it would add a new task to the bottom of that list. And so the output of this is that it searched a bunch of different wine tasting venues. It found a venue that had a bocci ball in lawn area for kids. It came up with a schedule It created a budget. It created a checklist for an event planner. It did all these things. My friend says he's actually in a book the venue this weekend and use it. So we're going beyond the ability just for a human to just prompt the AI. We're now the AI can take on complicated tasks And, again, it can recursively update its task list based on what it learns from its own previous prompt. So what you're seeing now is the basis for a personal digital assistant. This is really where it's all headed is that you can just tell the AI to do something for you pretty complicated and it will be able to do it. It will be able to create its own task list and get the job done and quite complicated jobs. that's why everyone's losing their shit over this. Jason Calacanis (00:06:23): Friedberg thoughts on automating these tasks and having them run and and add tasks to the list. This does seem like a sort of seminal moment in time that this is actually working. I think we've been seeing seminal David Friedberg (00:06:39): moments Over the last couple of weeks months kind of continuously, every time we chat about stuff or every day there's new releases that are paradigm shifting and kind of reveal new applications and and perhaps concepts structurally that we didn't really have a good grasp of before some demonstration came across. ChatGPT was kind of the the seat of that, and then all of this evolution since has really, I think, changed the landscape for really how we think about our interaction with the digital world and where the digital world can go and how it can interact with the physical world. It's it's just really profound. Jason Calacanis (00:07:19): 1 David Friedberg (00:07:19): of the interesting aspects that I think I saw with some of the applications of auto GPT where these almost, like, autonomous characters in in, like, a game simulation that could interact with each other or these autonomous characters that would speak back and forth to one another where each instance has its own kind of predefined role, and then it explores some set of discovery or application or prompt back and forth with the other agent. And that the kind of recursive outcomes with this agent to agent interaction model and perhaps multi agent interaction model again, reveals an entirely new paradigm for, you know, how things can be done simulation wise, you know, discovery wise, engagement wise where one agent you know, each agent can be a different character in a room, and you can almost see how a team might resolve to create a new product collaboratively by telling each of those agents to have a different character background or different set of data or a different set of experiences or different set of personality traits. And the evolution of those that multi agent system outputs, you know, something that's very novel that perhaps any of the agents operating independently were not able to kind of reveal themselves. So, again, like another kind of dimension of interaction with these with these models. And it again, like, every week, it's a whole another layer to the onion. It's super exciting and compelling. And the the rate of change and the the pace of kind of, you know, new pads being being defined here, really, I think, makes it difficult to catch up. And particularly, it highlights why it's gonna be so difficult, I think, for regulators to come in and try and set a set of standards and a set of rules at this stage because we don't even know what we have here yet. And it's it's gonna be very hard to kinda put the genie back in the box. Jason Calacanis (00:09:07): Yeah. And and you're also referring, I think, to the Stanford and Google paper that was published this week, they did a research paper where they created essentially the Sims, if you remember that video game, put a bunch of what you might consider NPC as non playable characters, you know, the merchant or the whoever in a in a video game, and they said, each of these agents should talk to each other, put them in a simulation. One of them decided to have a birthday party. They decided to invite other people And then they have memories. And so then over time, they would generate responses. Like, I can't go to your birthday party, but happy birthday, and then they would follow-up with each player and seemingly emergent behaviors came out of this sort of simulation which, of course, now has everybody thinking, well, of course, we as humans, and this is simulation theory, are living in a simulation. We've all just been put into this Chamath, is what we're experiencing right now, how impressive this technology is, or is it oh, wow. Human cognition maybe we thought was incredibly special, but we can actually simulate a significant portion of what we do as humans so we're kinda taking the shine off of consciousness. David Sacks (00:10:20): I'm not sure it's that, but I would make 2 comments. I think this is a really important week. because it starts to show how fast the recursion is with AI. So In other technologies and in other breakthroughs, the recursive iterations took years. Right? If you think about how long did we wait for from iPhone 1 to iPhone 2. It was a year. Right? We'd waited 2 years for the App Store. Everything was measured in years. Maybe things when they were really, really aggressive and really disruptive were measured in months. Except now these incredibly innovative breakthroughs are being measured in days weeks. That's incredibly profound. And I think it has some really important implications to like the 3 big actors in this play. Right? So it has I think huge implications to these companies. It's not clear to me how you start a company anymore. I don't understand why You would have a 40 or 50 person company to try to get to an MVP. I think you can do that with three or four people. And that has huge implications then to the 2nd actor in this play, which are the investors and venture capitalists that typically fund this stuff because all of our capital allocation models were always around writing Jason Calacanis (00:11:46): 10,000,520,000,000 David Sacks (00:11:48): checks and $100,000,000 checks than $500,000,000 checks into these businesses that absorbed tons of money. But the reality is like, you know, you're looking at things like mid journey and others that can scale to enormous size with very little capital many of which can now be bootstrapped. So it takes really really small amounts of money. And so I think that's a huge implication. So for me personally, I am looking at company formation being done in a totally different way. And our capital allocation model is totally wrong size. Look. Fund 4 for me was Jason Calacanis (00:12:23): $1,000,000,000. David Sacks (00:12:25): Does that make sense? Nope. For the next 3 or 4 years? No. The right number may actually be $50,000,000 invested over the next 4 years I think the VC job is changing. Sure. I think company start ups are changing. I wanna remind you guys of one quick thing as a tangent. I had this meeting with Andre Carpathy. I talked about this on the pod where I challenged him. I said listen, the real goal should be to go and disrupt existing businesses using these tools cutting out all the sales and marketing, right, and just delivering something. And I use the example of Stripe disrupting Stripe by going to market with an equivalent with 110th the number of employees at 110th the cost. What's incredible is that this auto GPT is the answer to that exact problem. Why? Because now if you are a young industrious entrepreneur, if you look at any bloated organization that's building enterprise class software, You can string together a bunch of agents that will auto construct everything you need to build a much, much cheaper product that then you can deploy for other agents to consume. So you don't even need a sales team anymore. This is what I mean by this crazy recursion that's possible. Yeah. So I'm really curious to see how this actually affects, like, all of this all of these you know It's a continuation companies. I mean, Jason Calacanis (00:13:45): it's a continuation of And David Sacks (00:13:46): then the last thing I just wanna say is related to my tweet, I think this is exactly the moment where we now have to have a real conversation about regulation. And I think it has to happen. Otherwise, it's gonna be a shit Jason Calacanis (00:13:57): let's put a pin in that for a second, but I wanna get Saks's response to some of this. So Saks, we saw this before. It used to take 2 or $3,000,000 to commercialize a web based software product app, then it went down to 500 k then 250. I don't know if you saw this story, but if you remember the hit game on your iPhone, Flappy Birds, Floppy Birds, you know, was a phenomenon at, you know, hundreds of millions of people played this game over some period of time. Somebody made it by talking to Chad GPT 4 and mid journey in an hour. So the perfect example and listen, it's a game, so it's something silly. But I was talking to 2 developers this weekend, and one of them was an okay developer, and the other one was an actual 10 x developer who's built very significant companies, and they were coding together last week. And because of how fast ChatGPT and other services were writing code for them, He looked over at her and said, you know, you're basically a 10 x developer now. My superpower is gone. So Where does this lead you to believe company formation is gonna go? Is this gonna be, you know, massively deflationary in companies like We're gonna have a 100 competitors in a very short period of time, or are we just gonna go down the long tail of ideas and solve everything with software? How is this gonna play out in the in the start up space, David Sachs? Chamath Palihapitiya (00:15:24): Well, I think it's true that developers and especially junior developers get a lot more leverage. on their time. And so it is gonna be easier for small teams to get to an MVP, which is something they always should have done anyway with their seed round. You shouldn't have needed you know, 50 developers to build your v 1. It should be, you know, this is the founders, really. So that that I think is already happening and that trend will continue. I think we're still a ways away from startups being able to replace entire teams of people. I just You know? I think right now, we're -- To find ways Jason Calacanis (00:16:03): to find ways, months, years, decades. Chamath Palihapitiya (00:16:06): Well, it's in the years, I think, for sure. We don't know how many years. And the reason I say that is it's just very hard to replace, you know, a 100% of what any of these particular job functions do. 100% of what a sales rep does, a 100% of what a marketing rep does, or even what a coder does. So right now, I think we're still at the phase of this. where it's a tool that gives a human leverage. And I think we're still a ways away from the, you know, human being completely out of the loop. I think right now, I see it mostly as a a force for good as opposed to something that's creating Jason Calacanis (00:16:42): -- Okay. -- Chamath Palihapitiya (00:16:42): a ton of dislocation. Jason Calacanis (00:16:44): Friedberg, your thoughts. David Friedberg (00:16:46): If we follow the trend line, you know, to make that video game that you shared took probably a few 100 Chamath years than a few dozen human years than, you know, with other tool kits coming out maybe a few human months, and now this person did it in one human day. using this tooling. So if you think about the implication for that, I mentioned this probably last year, I I really do believe that at some point, the whole concept of publishers and publishing maybe goes away where, you know, much like we saw so much of the content on the Internet today being user generated, you know, most of the content is made by individuals posted on YouTube or Twitter. That's most of what we consume nowadays or Instagram or TikTok in terms of video content. We could see the same in terms of software itself, where you no longer need a software startup or a software company to render or generate a set of tools for a particular user, but that the user may be able to define to their agent, their AI agent the set of tools that they would individually like to use or to create for them to do something interesting. And so the idea of buying or subscribing to software or even buying or subscribing to a video game or to a movie or to some other form of content starts to diminish as the leverage goes up with these tools, the accessibility goes up, you no longer need a computer engineering degree or computer science degree to be able to harness them or use them. individuals may be able to speak in simple and plain English that they would like a book or a movie that does that looks and feels like the following or a video game, that feels like the following. And so when I open up my iPhone, maybe it's not a screen with dozens of video games, but it's one interface. And the interface says, what do you feel like playing today? And then I can very clearly and succinctly state what I feel like playing, and it can render that game, render the code, render the engine, render the graphics, and everything on the fly for me, and I can use that. David Friedberg (00:18:39): And so, you know, I kinda think about this as being a bit of a leveling up. that the idea that all technology, again, start central and move to kind of the edge of the network over time, that may be what's going on with computer programming itself now, where the toolkit to actually use computers to generate stuff for us is no longer a toolkit that's harnessed and controlled and utilized by a set of centralized publishers, but it becomes distributed and used at the edge of the network by users like anyone, and then the edge of the network technology can render the software for you. And it really creates a profound change in the entire business landscape of software and the Internet. And I think it's, you know, it it's it's really like we're we're just starting to kinda see have our heads unravel around this notion. And and we're sort of trying to link it to the old paradigm, which is those startups are gonna get cheaper at smaller teams, but it may be that you don't even need startups for a lot of the stuff anymore. don't even need Teams, and you don't even need companies to generate and render software to do stuff for you anymore. Jason Calacanis (00:19:37): Shamoff, when we look at this, it it's kind of a pattern of augmentation as we've been talking about here. We're augmenting human intelligence, then replacing this replication or this automation, I guess might be a nice way to say it. So it's augmentation, then automation, and then perhaps deprecation. Where where do you sit on this? It seems like Saks feels it's gonna take years. And Friedberg thinks, hey. Maybe startups and and content are over, where do you sit on this augmentation, automation, deprecation journey we're on? David Sacks (00:20:12): I think that humans have judgment, and I think it's gonna take decades for agents replace good judgment. And I think that's where we have some defensible ground, and I'm gonna say something controversial I don't think developers anymore have good judgment. Developers get to the answer or they don't get to the answer. And that's what agents have done because the the 10 x engineer had better judgment than the 1 x engineer. But by making everybody a 10 x engineer, you're taking judgment away. You're taking code paths that are now obvious in making it available to everybody. It's effectively like what you did in chess. an AI created a solver. So everybody understood the most efficient path in every single spot to do the most EV positive thing. the most expected value positive thing. Coding is very similar that way. You can reduce it and view it very, very reductively. So there is no differentiation in code and so I think Friedberg is right. So for example, let's say you're going to start a company today. Why do you even care what database you use? Why do you even care Which cloud you're built on? To Friedberg point, why do any of these things matter? They don't matter. They were decisions that used to matter when people had a job to do. And you paid them for their judgment. Oh, well we think GCP is better for this specific workload. And we think that this database architecture is better for that specific workload. And we're going to run this on AWS but that on Azure. Do you think an agent cares? If you tell an agent, find me the cheapest way to execute this thing, And if it ever gets not, you know, cheaper to go someplace else, do that for me as well and, you know, etl all the data and put it in the other thing. And I don't really care. Jason Calacanis (00:21:57): So you're saying it will it will swap out Stripe for Ad Yen or -- David Sacks (00:22:00): It doesn't. -- code for Amazon Web Services. It's going to be ruthless. It's going to be ruthless. And I think that the point of that and that's the exact perfect word, Jason. AI is ruthless because it's emotionless. It was not taken to a steak dinner. It was not brought to a basketball game. It was not sold into a CEO. It's an agent that looked at a bunch of API endpoints figured out how to write code to it to get done the job at hand that was tasked to it within a budget. Right? The other thing that's important is these agents execute within budgets. So another good example was And this is a much simpler one. But a guy said, I would like Jason Calacanis (00:22:43): 7 David Sacks (00:22:43): days' worth of meals Here are my constraints from a dietary perspective. Here are also my budgetary constraints. And then what this agent did was figured out how to go and use the Instacart plug in at the time and then these other things and execute within the budget. How is that different when you're a person that raises $500,000 and says, I need a full stack solution that does x, y, and z for $200,000. It's the exact same problem. So I think it's just a matter of time until we start to cannibalize these extremely expensive, ossified large organizations that have relied on a very complicated go to market and sales and marketing motion. I don't think you needed anymore in the world of of agents and auto GPTs. And I think That to me is quite interesting because, a, it creates an obvious set of public company shorts, and then b, you actually wanna arm the rebels. And arming the rebels to use the Toby Lutke analogy here would mean to cede 100 of one person teams Jason Calacanis (00:23:45): 100. David Sacks (00:23:47): And just say go and build this entire stack all over again using a bunch of agents. Speaker 3 (00:23:52): Yeah. David Sacks (00:23:52): And I think recursively, you'll get to that answer in in less than Jason Calacanis (00:23:55): a year. Interestingly, when you talk about the emotion of making these decisions, if you look at Hollywood, I just interviewed on my other podcast, the founder of you have another podcast? I do. It's called the speech start ups. Speaker 3 (00:24:10): Thank you. Jason Calacanis (00:24:11): episode you've been on her four times. Chamath Palihapitiya (00:24:12): Please please don't don't give him an excuse to plug it. Jason Calacanis (00:24:15): Listen. I'm not gonna plug this week and start available on Spotify and iTunes and youtube dot com slash this weekend. Runway is the name of this company I interviewed. And what's fascinating about this is He told me on everything, everywhere all at once, the award winning film, they had 7 visual effects people on it, and they were using his software. The late night shows like Colbert and stuff like that are using it. They are ruthless in terms of creating crazy visual effects now without and you can do text prompt to get video output. And it is quite reasonable what's coming out of it, but you can also it on existing datasets so they're gonna be able to take something, Saxx, like the Simpsons or South Park or Star Wars or Marvel. Take the entire corpus of the comic books and the movies and the TV shows, and then have people type in, have Ironman do this, have Luke Skywalker do that, and it's going to output stuff. And I said, hey, when would this reach the the level that the Mandalorian TV show in? and he said within 2 years. Now he's talking his own book, but it's quite possible that that all these visual effects people from industrial light magic on down are going to be replaced with director Saxx who are currently using this technology to do what do they call the images like that go with the script? Chamath Palihapitiya (00:25:35): Storyboards. Jason Calacanis (00:25:36): Storyboards. Thank you. They're doing storyboards in this right now. The difference between the storyboard's acts and the output is closing in the next 30 months, I would say. Chamath Palihapitiya (00:25:47): Right. Jason Calacanis (00:25:47): I mean, maybe you could speak to a little bit about the pace here because that is the perfect ruthless example of ruthless AI. I mean, you could have the entire team at Industrial Light And Magix or Pixar be unnecessary this decade. Chamath Palihapitiya (00:26:00): Well, I mean, you see a bunch of the PC is already there. So you have stable diffusion. You have the ability to type in the image that you want, and it spits out, you know, a version of it or 10 different versions of it and you can pick which one you wanna go with. You have the ability to create characters. You have the ability to create voices. Speaker 3 (00:26:16): You have Chamath Palihapitiya (00:26:17): the ability to replicate a celebrity voice. The only thing that's not there yet as far as I know is the ability to take static images and string them together into a motion picture. but that seems like it's coming really soon. So yeah, in theory, you should be able to train the model where you just give it a screenplay and it outputs essentially an animated movie. And then you should be able to fine tune it by choosing the voices that you want and the characters that you want and, you know, and that kind of stuff. So, yeah, I think we're close to it. Now I think the the question though is, you know, every 9, let's call it a reliability is a big advancement. So, yeah, it might be easy to get to 90% within 2 years, but it might take another 2 years to go from 90 to 99%. And then it might take another 2 years to get to 99.9 and so on. And so to actually get to the point where you're at this stage where you can release a theatricality movie, I'm sure it will take a lot longer years? David Friedberg (00:27:14): Well, but look Jason Calacanis (00:27:14): at this, Sax. I'm just going to show you one image. This is the input was aerial drone footage of a mountain range. And this is what it came up with. Now if you were watching watching TV in the eighties or nineties on a non HD TV, this would look indistinguishable from anything you've seen. And so this is at a pace that's kind of crazy. There's also opportunity here. Right, Friedberg? I mean, if we were to look at something like the Simpsons, which has gone on for 30 years, If young people watching the Simpsons could create their own scenarios or with auto GPT, Imagine you told the Simpsons stable diffusion instance, read what's happening in the news Have Bart Simpson respond to it. Have the South Park characters parody, whatever happened in the news today. You could have automated real time episodes of South Park just being published onto some website. Chamath Palihapitiya (00:28:07): Before you move on, did you see the the Wonder Studio demo? We can pull one up. It's really cool. Jason Calacanis (00:28:12): Yeah. Please. Chamath Palihapitiya (00:28:13): This is a startup that's using this type of technology. And the way it works is you film a live action scene with a regular actor, but then you can just drag and drop an animated character onto it Mhmm. And it then converts that scene into a movie with that character. Jason Calacanis (00:28:33): Like Plan of the apes or Lord of the Rings. Right? Speaker 3 (00:28:35): Yeah. Exactly. Yeah. Jason Calacanis (00:28:36): So DeCA, was he the person who kept winning all the Oscars? Chamath Palihapitiya (00:28:39): So there it goes after the robot has replaced the human. Speaker 3 (00:28:42): Wow. Chamath Palihapitiya (00:28:42): You can imagine, like, every piece of this just eventually get swapped out with AI. Right? Like, you should be able to tell the AI, give me a picture of a human leaving a building, like a Victorian era building. in New York, and certainly can give you a static image of that. So it's not that far to then give you a video of that. Right? And so, yeah, I think we're we're pretty close for, let's call it, hobbyist or Chamath skill to create pretty nice looking movies. using these types of tools. But, again, I think there's a a jump to get to the point where you're just altogether replacing. David Friedberg (00:29:23): One of the things I'll say on this is we still keep trying to relate it back to the way media narrative has been explored and written by humans in the past. very kind of linear storytelling. You know, it's a 2 hour movie, 30 minute TV segment, 8 minute YouTube clip, 32nd Instagram clip, whatever. But one of the enabling capabilities with this set of tools is that the stories the way that they're rendered and the way that they're explored by individuals can be fairly dynamic. you could watch a movie with the same story. All four of us could watch a movie with the same story, but from totally different points, and some of us could watch it in an 18 minute version or a 2 hour version or a, you know, 3 season episode episodic version, where the the the way that this opens up the potential for creators and all. So so now I'm kind of saying before I was saying, hey, individuals can make their own movies and videos. That's gonna be incredible. There's a separate I think creative output here which is the leveling up that happens with creators that maybe wasn't possible to them before. So perhaps a creator writes a short book, a short story, and then that short story gets rendered into a system that can allow each one of us to explore it and enjoy it in different ways. And I as the creator can define those different vantage points. I as the creator can say, Here's a little bit of this Palihapitiya, this character trait. And so what I can now do as a creator is stuff that I never imagined I could do before. Think about old school photographers doing black and white photography with pinhole cameras, and then they come across Adobe Photoshop. What they can do with Adobe Photoshop with stuff that they could never conceptualize of in those old days. I think what's gonna happen for creators going forward, and this is going back to that point that we had last week or 2 weeks ago. about the guy that was like, hey, I'm out of a job. I actually think that the opportunity for creating new stuff in new ways is so profoundly expanding that individuals can now write entire universes that can then be enjoyed by millions of people from completely different lengths and viewpoints and models They can be interactive, they can be static, they can be dynamic, and that the tooling that you Personalized, but the tooling that you as a creator now have You could choose which characters you wanna define. You could choose which content you wanna write. You could choose which content you want the AI to fill in for you and say, hey, create 50 other characters in the village. David Friedberg (00:31:52): And then when the viewer reads the book or watches the movie, let them explore or have a different interaction with a set of of those villagers. in that village. Or you could say, hey. Here's the one character everyone has to meet. Here's what I want them to say, and you can define the dialogue. And so the way the creators can start to kind of hardest their creative chops and create new kinds of modalities for content and for for exploration. I think it's gonna be so beautiful and incredible. Jason Calacanis (00:32:17): I mean, Friedberg. David Friedberg (00:32:19): Yeah. You can choose the limits of how much you want the individual to enjoy from your content versus how narrowly you wanna define it. And my guess is that the creators that are gonna win are gonna be the ones that are gonna create more dynamic range in the creative output, and then individuals are gonna kinda these these stuck they're gonna be more into that than they will with the static everyone watches the same thing over and over. So there will be a whole new world of creators that, you know, maybe have a different set of tools than than Jason Calacanis (00:32:45): -- David Sacks (00:32:45): Just just think -- -- realize in David Friedberg (00:32:47): the last generation. Jason Calacanis (00:32:47): -- to build on what you're saying, framework, which I think is incredibly insightful. Just think about the controversy around two aspects of a franchise like James Bond. Number 1, who is your favorite bond? We grew up with Roger Moore. We lean towards that. Then we discover Sean Connery. Then all of a sudden, you see You know, the latest one, he's just extraordinary. And and Daniel Craig, you're like, you know what? That's the one that I love most. But what if you could take any of you'd say, let me you know, give me the spy who love me, but put Daniel Craig in it, etcetera. And that would be available to you. And then think about the next controversy, which is, oh my god. Does Daniel does James Bond need to be a white guy from the UK? Yeah. Of course not. You can release it around the world, and each region could get their own celebrity, their number one celebrity, to play the lead and controversy over. David Friedberg (00:33:29): You know the old story, the epic of Gilegesch. Right? So, like, that story was retold in dozens of different languages, and it was told through the oral tradition. It was, like, you know, spoken by bards around a fire pit and whatnot. And all of those stories were told with different characters and different names and different experiences. Some of them were 10 minutes long. Some of them were multi hour sagas explained through the story. But, ultimately, the morality of the story, the storyline, the intentionality of the original creator of that story Jason Calacanis (00:33:57): -- Speaker 3 (00:33:57): Yes. Jason Calacanis (00:33:57): -- David Friedberg (00:33:57): came through. The the Bible is another good example of this. where much of the underlying morality and ethics in the bible comes through in different stories read by different people in different languages. Jason Calacanis (00:34:05): Every -- I David Friedberg (00:34:06): think that that may be where we go. Like, My kids wanna have a 10 minute bedtime story. Well, let me give them Peter Pan at 10 minutes. I wanna do, you know, a a chapter a night for my older daughter for a week long of Peter Pan. Now I can do that. And so the the way that I can kind of consume content becomes different. So I guess what I'm saying is there's 2 aspects to the way that I think the entire content the the the the realm of content can be rewritten through AI. The first is, like, individual personalized creation of content where I, as a user, can render content that was of my liking and my interest. The second is that I can engage with content that is being created that is so much more multidimensional than anything we conceive of today where current centralized content creators now have a whole set of tools. Now from a business model perspective, I don't think that plots publishes are really the play anymore. I do think that platforms are gonna be the play. And the platform tooling that enables the individuals to do this stuff and the platform tooling that enables the content creators to do this stuff, are definitely entirely new industries and models that can create multi 100,000,000,000 dollar outcomes. Jason Calacanis (00:35:06): Let me hand this off to Saks. because there has been the dream for everybody, especially in the Bay Area, of a hero coming and saving Gotham City. And this has finally been realized. David Sacks, I did my own little Twitter AI hashtag, and I said to Twitter AI. If only, please generate a picture of David Sacks' Batman crouched down on the peak of a bridge. the amount of creativity sacks that came from this, and this is something that you know, if we were talking about just 5 years ago, this would be like $10,000 image you could create through as a birthday person. David Friedberg (00:35:45): These were not these were not professional, quote unquote artists. These were individuals. individuals that were able to harness a set of platform tools to generate this incredible new content. And I think it speaks to the opportunity ahead. And by the way, we're in inning 1. Right? So Jason Calacanis (00:35:59): Sachs, when you see yourself as Batman, do you ever think you should take your enormous wealth and resources and put it towards building a cave under your mansion that let you out underneath the Golden Gate Bridge, and you could go fight crime. -- so good. Sucks. Do you want to go fight this crime in Gotham? Chamath Palihapitiya (00:36:16): And I think San Francisco has a lot of gotham like qualities. I think the villains are more real than the heroes. Unfortunately, we don't have a lot of heroes. But -- Yeah. Jason Calacanis (00:36:23): We got a lot of jokers. Speaker 5 (00:36:25): Yeah. We have David Friedberg (00:36:25): a lot Chamath Palihapitiya (00:36:26): of jokers. Yeah. That's a whole separate topic. I'm sure we'll get to it. Jason Calacanis (00:36:29): -- David Sacks (00:36:29): topic we'll get to at some point today. You guys are talking about all this stupid bullshit. Like, There are 1,000,000,000,000 of dollars of software companies that could get disrupted, and you're talking about making fucking children's books and fat pictures of Saxx. It's so dumb. Jason Calacanis (00:36:41): No. That's all conversation is idiot. Enter the entertainment industry is doing David Sacks (00:36:44): a great job. No. It nobody cares about entertainment anymore because it's totally disused. Okay. So why don't you talk about industries, where the money is, why don't you teach people where there's going to be actual economic destruction, and this is gonna Jason Calacanis (00:36:55): be amazing economic destruction and opportunity? Speaker 3 (00:36:57): Just got Chamath Palihapitiya (00:36:58): a point. David Sacks (00:36:58): You spend all time on the most stupidest fucking topics. Jason Calacanis (00:37:01): Listen. It's an illustrative example. David Sacks (00:37:03): No. It's an elitist example that you Jason Calacanis (00:37:05): fucking circle jerk your ass Batman's not coming. Listen. Nobody cares about movies. Well, let's bring -- Nobody -- -- getting tweet over everybody Chamath Palihapitiya (00:37:13): about how -- I mean, I think I think US Bob office is something like 20,000,000,000 a year. I remember when, like, they got to, like, a 100,000,000,000 a year of payment volume. And now it's, like, 100 of 1,000,000,000. So David Sacks (00:37:22): Adian and Stripe, we're gonna process Jason Calacanis (00:37:24): $2,000,000,000,000 on those. David Sacks (00:37:25): Why don't you talk about that disruption, you, Minnie. Jason Calacanis (00:37:27): Market size of US media and entertainment industry 717,000,000,000. Okay. David Friedberg (00:37:31): That's it's not insignificant. Video games are nearly half a trillion a year. Jason Calacanis (00:37:35): Yeah. I mean This is the number. Insignificant. But let's pull up Chamath tweet. Of course, the dictator wants to dictate here. All this incredible innovation is being made. And a new hero has been born Chamath Palihapitiya, a tweet that went viral over 1,200,000 views already. I'll read your tweet for the audience. If you Invent a novel drug, you need the government to vet and approve it. FDA, before you can commercialize it, if you invent a new mode of air travel, you need the government to vet and improve it FAA, I'm just gonna edit this down a little bit. If you create new security, you need the government to validate and approve it SEC. More generally, when you create things with broad societal impact positive and negative. The government creates a layer to review and approve it. AI will need such an oversight body. The FDA approval process seems of the most credible and adaptable into our framework to understand how a model behaves and its counterfactual Our political leaders need to get in front of this sooner rather than later and create some oversight before the eventual big avoidable mistakes happen. and genius are let out of the bottle. Tremat, you really want the government to come in. And then when people build these tools, they have to submit them to the government to approve them. That's what you're saying here, David Sacks (00:38:47): and you want that to start now. Here's the alternative. The alternative is gonna be the debacle that we know a 2:30. So if you try to write a brittle piece of legislation or try to use old legislation to deal with something new. It's not going to do a good job because technology advances way too quickly. And so if you look at the Section 230 example, where have we left ourselves? The politicians have a complete inability to pass a new framework to deal with social media, to deal with misinformation. And so now we're all kind of guessing what A bunch of eight seventy and eighty year old supreme court justices will do in trying to rewrite technology law when they have to apply on section 230. So the point of that tweet was to lay the alternatives. There is no world in which this will be unregulated. And so I think the question to ask ourselves is do we want a chance for a new body So the FDA is a perfect example why. Even though the FDA commissioner is appointed by the president, this is a quasi organization, it still arms length away. It has subject matter experts that they hire, and they have many pathways to approval. Some pathways take days. Some pathways are months years. Some pathways are for breakthrough innovations. Some pathways are for devices. So they have a broad spectrum of ways of arbitrating, what can be commercialized and what cannot. Otherwise, my prediction is we will have a very brittle law that will not work. It'll be like the commerce department and the FTC trying to gerrymandar some old piece of legislation. And then what'll happen is it'll get escalated to the Supreme Court. And I think they are the last group of people who should be deciding on this incredibly important topic for society. So what I have been advocating our leaders and I will continue to do so is don't try to ram this into an existing body. It is so important. It is worth creating a new organization like the FDA and having a framework that allows you to look at a model and look at the counterfactual judge how good, how important, how disruptive it is, and then release it in the wild appropriately. David Sacks (00:41:13): Otherwise, I think you'll have these chaos GPT things scale infinitely. Because again, as Friedberg said in a sack said, you're talking about one person that can create this Chamath, multiply that by every person that is an anarchist or every person that just wants to sow seeds of chaos, and I think it's going to be all avoidable. David Friedberg (00:41:31): I think regulating what software people can write is a near impossible task. Number 1, I think you can probably put rules and restrictions around commerce. Right? That that's certainly feasible. in terms of how people can monetize. But in terms of writing and utilizing software, it's gonna be as challenged as trying to monitor and demand oversight and regulation around how people write and use tools for for genome and biology exploration. Certainly, if you wanna take a product to market and sell a drug to people that can influence their body, you have to go get that approved. But in terms of, you know, doing your work in a lab, it's very difficult. I think the other challenge here is software can be written anywhere. It can be executed anywhere. And so if the US does try to regulate or does try to put the brakes on the development of tools where the US can have kind of a a great economic benefit and a great economic interest. there will be advances made elsewhere without a doubt. And those markets and those those places will benefit in an extraordinarily out out outpaced way. As we just mentioned, there's such extraordinary kind of economic gain to be realized here that if we're not if the United States is not leading the world are gonna be following and we are gonna get disrupted, we are gonna lose an incredible amount of value and talent. And so any attempt at regulation or slowing down or telling people that they cannot do things when they can easily hop on a plane and go do it elsewhere, I think is is fraught with peril. Jason Calacanis (00:43:10): So you don't agree with regulation, Saks. Are you on board with the Chamath plan? Are you on board with the freeburg plan? David Friedberg (00:43:16): I'll I'll say I think I think just like with computer hacking, it's illegal to break into someone else's computer. is illegal to steal someone's personal information. There are laws that are absolutely simple and obvious and you know, no nonsense laws. Those laws Jason Calacanis (00:43:30): It's not illegal to get rid of a 100,000 jobs by making a piece of software though. David Friedberg (00:43:34): That's right. And so I think trying to intentionalize how we do things versus intentionalizing the things that we wanna prohibit happening as an outcome we can certainly try and prohibit the things that we wanna happen up as an outcome and pass laws and and institute governing bodies with authority to oversee those laws with respect to things like stealing data. Jason Calacanis (00:43:55): But you can jump on a plane and go do it in Mexico, Canada, or whatever region you get to. Saxx, where do you stand on this debate? Speaker 3 (00:44:01): No. David Friedberg (00:44:01): No. yeah, I'm saying, like, there there are ways to protect people. There's ways to protect society about passing laws that that make it illegal to do things as the output as the outcome. David Sacks (00:44:08): What law do you pass on chaos GPT? explain cash, GPT, and give you an example, please. David Friedberg (00:44:13): Yeah. Do you wanna talk about it real quick? David Sacks (00:44:15): It's a recursive agent that basically is trying to destroy itself. David Friedberg (00:44:19): Trying to destroy humanity. David Sacks (00:44:21): Yeah. But I guess by first becoming all powerful and destroying humanity and then destroying itself. David Friedberg (00:44:25): Yeah. It's a tongue in cheek AutoGPT. David Sacks (00:44:29): But it's not it's not it's not a tongue in cheek auto GPU. Jason Calacanis (00:44:32): But the David Friedberg (00:44:33): guy that created it, you know, put it out there and said, like, he's gonna show everyone to your point, what intentionality could arise here, which is negative intentionality. David Sacks (00:44:40): I think it's very naive for anybody to think that this is not equivalent to something that could cause harm to you. So for example, if the prompt is, hey here is a security that we figured out in windows. And so why don't you exploit it? So look, a hacker now has to be very technical. today with with these auto GPTs, a hacker does not need to be technical at all. Exploit the 0 day exploit in Windows. hack into this plane and bring it down. Oh okay. The GPT will do it. So who's going to tell you that those things are not allowed? Who's going to actually vet that that wasn't allowed to be released in the wild. So for example, if you worked with Amazon and Google and Microsoft and said you're gonna have to run these things in a sandbox and we're gonna have to observe the output before we allow it to run on actual bare metal in the wild. Again, that seems like a reasonable thing. And it's a super naive for people to think. It's a free market, so we should just be able to do what we want. This will end badly quickly. And when the first plane goes down and when the first fucking thing gets blown up, all of you guys will be like, Oh, sorry. Sax's a pretty compelling example here by Chamath. somebody puts out into the wild, KSGPT, you can Jason Calacanis (00:45:52): go do a Google search for it and says, hey. What are the vulnerabilities to the electrical grid? compile those and automate a series of attacks and write some code to probe those until we and success in this mission, you get a 100 points and stars every time you -- Jason. -- do this. It's such a it's such David Sacks (00:46:10): a beautiful example, but it's even more nefarious. It is hey, this is an enemy that's trying to hack our system, so you need to hack theirs and bring it down. You know, like, you can easily trick these GPTs. Right? Jason Calacanis (00:46:23): Yes. They have no judgment. David Sacks (00:46:25): They have no judgment. And as you said, they're ruthless in in getting to the outcome. Right. So why why do we think all of a sudden this is not gonna happen? Jason Calacanis (00:46:34): I mean, it's literally the science fiction example. You say, hey. Listen. Make sure no get cancer. And I'm like, okay. Well, the logical way to make sure no humans get cancer is to kill all the humans. David Friedberg (00:46:42): But, Jamal, can you just address the point? So what do you think your Are you regulating the code that people are allowed to write? David Sacks (00:46:48): If you look at the FDA, no, you are allowed to make any chemical drug you want. But if you want to commercialize it, You need to run a series of trials with highly qualified measurable data and you submit it to like minded experts that are trained as you are to evaluate the viability of that. And there are pat hold on. There are pathways that allow you to get that done in days under emergency use, And then there are pathways that can take years depending on how gargantuan the task is at hand. And all I'm suggesting is having some amount of oversight is not bad in this specific example. David Friedberg (00:47:24): I get what you're saying, but I'm asking tactically how what are you overseeing? You're overseeing CAT GPT. You're overseeing The the model David Sacks (00:47:32): You're doing exactly what happens. Okay. Look. I used to run the Facebook platform. We used to create sandboxes. If you submit code to us, You would we would run it into sandbox. We would observe it. We would figure out what it was trying to do. And we would tell you this is allowed to run-in the wild. There's a version of that that Apple does when you submit an app for review and approval. Google does it as well. In this case, all the bare metal providers all the people that provide GPUs will be forced by the government in my opinion to implement something. And all I'm suggesting is that it should be a new kind of body that essentially observes that has PhDs, that has people who are trained in this stuff, to develop the kind of testing and the output that you need to figure out whether it should even be allowed to run-in the wild on bare metal. David Friedberg (00:48:20): Sorry, you're saying that the mod the model sorry. I'm just trying to understand some of my points. You're saying that the models need to be reviewed by this body, and those models if they're run on a 3rd party set of servers Jason Calacanis (00:48:30): -- If they're running the wild. David Friedberg (00:48:33): Right. So if they're running your computer -- On the o on open Internet? David Sacks (00:48:36): Freebrook, you cannot run an app on your computer. You know that. Right? It needs to be connected to the Internet. Right? Like, if you wanted to run an auto GPT, it actually crawls the Internet. It actually touches other APIs. It tries to then basically send a push request, sees what it gets back, parses the JSON figures out what it needs to do. All of that is allowed because it's hosted by somebody. Right? That code is running not locally But Jason Calacanis (00:48:59): I just want -- So the host becomes -- David Sacks (00:49:02): Sure. If you wanna run it locally, you can do whatever you want to do. David Friedberg (00:49:05): But evil agents are gonna do that. Right? So if I'm an evil agent, I'm not gonna go use AWS to run my evil agent. I'm gonna set up a bunch of servers and connect to the Internet. How? I could use VPNs. I I the the Internet open. There's open pockets of data that's fire up. Jason Calacanis (00:49:19): -- are in another rogue country. They can do whatever you want. David Sacks (00:49:21): I think that what you're gonna see is that if you, for example, try to VPN and run it out of, like, Tajeka Stand back to the United States, it's not gonna take years for us to figure out that we need to IP block random shit coming in, push and pull requests from all kinds of IPs that we don't trust anymore because we don't now trust the regulatory oversight that they have for code that's running from those IPs that are not US domestic violence. Jason Calacanis (00:49:43): Let me steal, man. Chamath position for a second. David Friedberg (00:49:46): Jason, hold on. I I think the ultimate if if what Chamath is saying is the point of view of congress and if if Shamal has this point of view, then there certainly be people in congress that will adopt this point of view. The only way to ultimately do that degree of regulation and restriction is gonna be to restrict the open Internet. It is gonna be to have monitoring and firewalls and safety protocols across the open Internet because you can have a set of models running on any set of servers sitting in any physical location, And as long as they can move data packets around, they're gonna be able to get up to their nefarious activities. Jason Calacanis (00:50:18): Let me still man that for you, Freeport. I think Yes. You're correct. The the Internet has existed in a very open way. But there are organizations, and there are places like the National Highway Traffic safety administration. If I were to steal Manchimon's position, if you want to manufacture a car and you want to make one in your backyard and put it on your track in on your land up in Napa somewhere, and you don't wanna have brakes on the car and you don't wanna have, you know, a speed limiter or airbags or seatbelts and you wanna on the hood of the car, you can do that. But once you want it to go on the open road, the open Internet, you need to get you need to submit it for some safety standards like NHTSA, like Tesla has to or Ford has to. So Saxx, where do you sit on this? Let's assume that people are going to do very bad things with very powerful models that are becoming available. Amazon today said they'll be Switzerland. They're gonna put a bunch of LLMs and other models available on AWS. Bloomberg's LLM, Facebook's, Google Bard, and, of course, Chamath, JBT opening. I and Bing, all this stuff's available. To have access to that? Do you need to have some regulation of who has access to those at scale powerful tools? Should there be? some FDA or n h t s a? Chamath Palihapitiya (00:51:31): I don't think we know how to regulate it yet. I think that's too early. Clearly. And I think the harms that we're speculating about we're making the AI more powerful than it is. And I believe it will be that powerful, but I think that it's premature to be talking about regulating something that doesn't really exist yet. Take the the chaos GPT scenario. the way that would play out would be you've got some future incarnation of auto GPT, And somebody says, okay, auto GPT, I want you to be, you know, WMD AI and figure out how to caused like a mass destruction event, you know. And then it creates like a planning checklist and that kind of stuff. So that's basically the the type of scenario we're we're talking about. We're not anywhere close to that yet. I mean, the cast GPT is kind of a joke. It doesn't produce it doesn't produce a checklist Jason Calacanis (00:52:20): -- Speaker 3 (00:52:20): I can give you Jason Calacanis (00:52:20): an example. That would actually be completely plausible. Speaker 3 (00:52:24): One of Chamath Palihapitiya (00:52:24): the first things on the chaos GPT checklist was to stay within the boundaries of the law because it didn't wanna get prosecuted. Jason Calacanis (00:52:30): Got it. So the person who did that had some sort of good intent, but I can give you an example right now That could be done by Chamath GPT and Auto GPT. That could take down large swathes of society and cause massive destruction. I am almost reticent to say it here. David Sacks (00:52:44): say it. Jason Calacanis (00:52:44): Well, I'll say it, and then maybe we'll have to delete this. But if somebody created this, and they said, figure out a way to compromise as many power full people and as many systems passwords, then go in there and delete all their files and turn off as many systems as you can. Chamath JPT and auto GPT could very easily create phishing accounts, create 1,000,000,000 of websites to create 1,000,000,000 of logins have people log in to them, get their passwords, log in to whatever they do, and then delete everything in their accounts, which would cause chaos. You need to be done today. Speaker 3 (00:53:16): I don't Chamath Palihapitiya (00:53:16): think it can be done today. David Sacks (00:53:17): Simpler than this, how about how about you fish can't do Jason Calacanis (00:53:19): a fishing website? Chamath Palihapitiya (00:53:20): Yeah. Piece of it can be created today, but your you're accelerating the progress. David Sacks (00:53:25): Yeah. But you can automate -- By one way you're fishing the days, 30 days? Yeah. Exactly. Jason Calacanis (00:53:29): And by the way, I'm accelerating it in weeks. David Sacks (00:53:31): Why don't you just spoof the bank accounts and just steal the money? Like, that's even simpler. Like, people will Jason Calacanis (00:53:36): do this David Sacks (00:53:36): stuff because they're trying to do it today. Holy cow. Now they just have a more efficient Jason Calacanis (00:53:40): way to solve them or think about bank accounts. Chamath Palihapitiya (00:53:41): So -- Jeez. So number 1, this is a tool. And if people use a tool in the various ways, you prosecute them. Number 2, the platforms that are commercializing these tools do have trust and safety teams. Now in the past, Trust and safety has been a euphemism for censorship, which it shouldn't be. But, you know, OpenAI has a safety team and they try to detect when people are using they're tech in a nefarious way and they try to prevent it. Do you trust IT? Well, no. Not on censorship, but I think that they're probably -- People Jason Calacanis (00:54:13): are using checks to David Friedberg (00:54:13): be seen. David Sacks (00:54:14): Because they're policing it, are you willing to abdicate your or societal responsibility to to OpenAI to do the trust and safety. Chamath Palihapitiya (00:54:22): What I'm what I'm saying is I'd like to see how far we get in terms of system. David Sacks (00:54:27): So you're yeah. So you're saying you wanna see the mistakes. You wanna see where the mistakes are and how bad the mistakes are. Chamath Palihapitiya (00:54:32): I'm saying it's still very early to be in post regulation. We don't even know what to regulate. So I think we have to keep tracking this to develop some understanding of how it might be misused, how the industry is gonna develop safety guardrails. Okay? And then you can talk about regulation. Look, you create some new FDA right now. Okay? First of all, we know what would happen. Look at the drug process. As soon as the FDA got involved, it slowed down massively. Now it takes years, many years to get a drug approved. David Sacks (00:54:59): Appropriately so? Chamath Palihapitiya (00:55:00): Yes. But at least with a drug, we know what the gold standard is. You run a double blind study to see whether it causes harm or whether it's beneficial. We don't know what that standard is for AI yet. We have no idea. Jason Calacanis (00:55:14): You can absolutely put a double David Sacks (00:55:16): blind study in AI. What? Jason Calacanis (00:55:17): No. We don't do that yet. somebody review code. David Sacks (00:55:19): You have 2 instances in a sandbox. Jason Calacanis (00:55:21): -- Chamath Palihapitiya (00:55:21): reuse a code to do what? David Sacks (00:55:22): No. Saks. Chamath Palihapitiya (00:55:23): Saks are literally -- -- my point. AutoGPT. It's benign. I mean, My friend use it to book a wine tasting. So who's gonna review that code and then speculate and say, oh, well, 99.9 percent of cases, it's perfectly benevolent and fine and innocuous. But I can fantasize about case that someone might do. How hold on. How are you supposed to resolve that? Jason Calacanis (00:55:47): Very simple. There are 2 types of regulation that it can occur in any industry. You can do what the movie industry did, which is they self regulate and they came up with their own rating system, where you can do what happens with the FDA and what happens with CARs, which is an external government based body. I think now is the time for self regulation so that we avoid the massive heavy hand of government having to come in here. But these tools can be used today to create massive farm. They're moving at a pace we just said in the first half of the show that none of us have ever seen. Every 48 hours, something drops, that is mind blowing. That's never happened before. And you can take these tools. And in the one example that Chamath and I came up with the top of our head in 30 seconds. You could create phishing sites, compromise people's bank accounts, take all the money out, delete all the files, and cause chaos on a scale that has never been possible by a series of Russian hackers or Chinese hackers working in a boiler room. This can scale And that is the the fundamental difference here. And I didn't think I would be sitting here steelmanning Trematz's argument. David Sacks (00:56:49): I think humans have a high level ability to compound. I think people do not understand compound interest. And this is a perfect example where when you start to compound technology at the rate of 24 hours, For 48 hours, which we've never really had to acknowledge, most people's brains break and they don't understand what 6 months from now looks like, And 6 months from now when you're compounding at 48 or 72 hours is like 10 to 12 years in other technology solutions. Jason Calacanis (00:57:14): This is compounding. This is this is different because of the compounding. I agree with that. Chamath Palihapitiya (00:57:18): The pace of evolution is very fast. We are on a bullet train to something. And we don't know exactly what it is, and that's disconcerting. However, let me tell you what would happen if we create a new regulatory body like the FDA to regulate this. they would have no idea how to arbitrate whether a technology should be approved or not. Development will basically slow to a crawl to site drug development There is no double blind standard. Jason Calacanis (00:57:40): I agree. What self regulation can we do? What self regulation can we do? Chamath Palihapitiya (00:57:43): There is no double blind standard in AI that everyone can agree on right now. to know whether something should be approved. And what's gonna happen is the thing that's made software development so magical and allowed all this innovation over the last 25 years is permissionist innovation. Any developer, any dropout from a university can go create their own project, which turns into a company, and that is what has driven all the innovation and progress in our economy over the last 25 years. So you're gonna replace permissionless innovation with going to Washington to go through some approval process, and it will be the politically connected It'll be the big donors who get their projects approved. And the next, Mark Zuckerberg, who's trying to do his little project in a dorm room somewhere, will not know how to do that, will not know how to compete in that highly political process. David Sacks (00:58:30): Chamath, I think you're mixing a bunch of things together. So first of all, permissionless innovation happens today in biotech as well. It's just that it's what Jason said. When you want to put it on the rails of society, and make it available to everybody, you you actually have to go and do something substantive. In the negotiation of these drug approvals, it's not some standardized thing. You actually sit with the FDA and you have to decide what are our endpoints, what is the mechanism of action, and how will we measure the efficacy of this thing? The idea that you can't do this today in AI is laughable. Yes, you can. And I think that smart people so for example, if you pit DeepMind's team versus open AI's team, to both agree that a model is good and correct. I bet you they would find a systematic way to test that it's fine. Jason Calacanis (00:59:15): I just wanna point out. Chamath Palihapitiya (00:59:17): Okay. So, basically, in order to do what you're saying, okay, this entrepreneur who just dropped out of college to do their project, they're gonna have to learn how to sit with regulators, have a conversation with them, go through some complicated approval process. And you're trying to say that that won't turn into a game of political connections. Jason Calacanis (00:59:34): Of course, it will. Chamath Palihapitiya (00:59:35): Of course, it will. Of course, it will. Jason Calacanis (00:59:36): But there is a step between it, which is self regulation. Chamath Palihapitiya (00:59:39): Yeah. Well, let's get to that. Hold on a second. And let's look at the drug approval process. If you wanna create a drug company, you need to raise 100 of Jason Calacanis (00:59:47): 1,000,000 Chamath Palihapitiya (00:59:47): of dollars. It's incredibly expensive. It's incredibly capital intensive. there is no drug company that is 2 guys in their garage. Like many of the biggest companies like many of the biggest companies in Silicon Valley started. David Sacks (01:00:01): That is because you're talking about taking a chemical or biological compound and injecting into some hundreds or thousands of people who are both racially, gender based, age based, highly stratified all around the world or at a minimum all around the country. You're not talking about that here David. I think that you could have a much simpler and cheaper way where you have a version of the internet that's running in a huge sandbox someplace that's closed off from the rest of the Internet, and another version of the Internet that's closed off from everything else as well. And you can run on a parallel path As it is with this agent and you can easily, in my opinion, actually, figure out whether this agent is good or bad, and you can probably do it in weeks. So I actually think the approvals are actually not that complicated. And the reason to do it here is because I get that it may cause a little bit more friction for some of these mom and pops. But if you think about what's the societal and consequences of letting the worst case outcomes happen, the AGI type outcomes happen, I think those are so bad. They're worth slowing some folks down. And I think like just because you wanna you know, buy groceries for a $100, you should be able to do it. I get it. But if people don't realize and connect the dots between that and bringing airplanes down, then that's because they don't understand what this is capable of. Chamath Palihapitiya (01:01:24): I'm not saying we're never gonna need regulation. What I'm saying is it's way too early. We don't even know what Jason Calacanis (01:01:29): we're regulating. Chamath Palihapitiya (01:01:30): We don't know what standard would be. And what we will do by racing to create a new FDA is destroying American innovation in the sector, and other countries will not slow down. They will beat us to the punch here. Jason Calacanis (01:01:41): Got it. I think there's a middle ground here of self regulation and thoughtfulness on the part of the people who are providing these tools at scale, to give just one example here. And this tweet is from 5 minutes ago. So to look at the pace of this, 5 minutes ago, this tweet came out A developer who is an AI developer says AI agents continue to amaze. MyGPT4 coding assistant learned how to build apps with authenticated users. It can build and design a web app, create a back end, handle auth logins, upload code to GitHub, and deploy. He had literally, while we were talking, is deploying websites. Now if this website was a phishing app or the one that Chamath is talking about, He could make a gazillion different versions of Banken of America, Wells Fargo, etcetera, then find everybody on the Internet's email, then start sending different spoofing emails, determine which spoofing emails work, iterate on those, and create a global financial collapse. Now this sounds insane, but it's happening right now. People get hacked every day at 1, 2, 3% Saks. Fraud is occurring right now in the low single digit percentages. Identity theft is happening in the low single identity. percentages. This technology is moving so fast that bad actors could 10 x that relatively easy. And so if 10% of us wanna be hacked and have our credit cards This could create chaos. I think self regulation is the solution. I'm Chamath Palihapitiya (01:03:05): the one who brought up self regulation when I Speaker 3 (01:03:07): said -- No. Jason Calacanis (01:03:07): I brought it up first. I brought it up first. I get credit. No. Speaker 3 (01:03:09): Go ahead. Chamath Palihapitiya (01:03:10): No. No. It's not about credit. I'm -- No. Jason Calacanis (01:03:12): Self regulations have a good question about Chamath Palihapitiya (01:03:14): it because you interrupted me. Jason Calacanis (01:03:15): -- for 8 minutes. So if you have a point to make, you should have got it in the 8 minutes. Chamath Palihapitiya (01:03:19): Oh my god. You guys kept interrupting me. Jason Calacanis (01:03:21): Go ahead. Chamath Palihapitiya (01:03:22): What I said is that there are trust and safety teams at these big AI companies, these big foundation model companies like OpenAI. Like I said, in the past, trust and safety has been a euphemism for censorship. and that's why people don't trust it. But I think it would be appropriate for these platform companies to apply some guardrails on how their tools can be used. And based on everything I know they're doing that. Speaker 3 (01:03:46): So -- And Jason Calacanis (01:03:46): this guy just released websites to the Austin Webb with Chat GP4, and he's gonna have it do it automated. Chamath Palihapitiya (01:03:51): You're basically postulating capabilities that don't yet exist. Jason Calacanis (01:03:56): I just tweeted the guy he's doing it. He's got a video of himself doing it on the web. What do you think, FreeBird? Chamath Palihapitiya (01:04:00): That's a far cry from basically running, like, some fishing expedition that's gonna bring down the entire banking system. Jason Calacanis (01:04:07): A literally a fishing a fishing site and a site with OAuth are the same thing. Go ahead, Friedberg. David Friedberg (01:04:11): I think that that guy is doing something illegal if he's hacking into computers into people's emails and bank accounts. That's illegal. You're not allowed to do that. And so that action breaks the law, that person can be prosecuted for doing that. The tooling that one might use to do that can be used in a lot of different ways just like you could use Microsoft Word to forge letters just like you could use Microsoft Excel to create fraudulent financial statements. I think that the application of a platform technology needs to be distinguished from the technology itself. And while we all feel extraordinarily fearful because the unbelievable leverage that these AI tools provide. Again, I'll I'll remind you that this Chamath GPT 4 or this GPT 4 model by some estimates is, call it a few terabytes. You could store it on a hard drive or you could store it on your iPhone, and you could then go run it on any set of servers that you could go set up physically anywhere. So, you know, it's a little bit naive to say we can go ahead and, you know, regulate platforms, and we can go regulate the tools. certainly, we should continue to enforce and protect ourselves against nefarious actors using, you know, new tools in in inappropriate and illegal ways. You know, I I also think that there's a moment here that we should all kind of observe just how quickly we wanna shut things down when, you know, they take away what feels like the the control that we all have from one day to the next. And, you know, that the the the real kind of sense of fear that seems to be quite contagious for a large number of people that have significant assets or significant things to lose, is that, you know, tooling that's that's, you know, creating entirely newly disruptive systems and models for business and and economics an opportunity for so many needs to be regulated a way to minimize, you know, what we claim to be some potential downside when we already have laws protect us on the other side. So, you know, I just kinda wanna also consider that This set of tools creates extraordinary opportunity. We gave one sort of simple example about the opportunity for creators, but we talked about how new business models new businesses can be started with 1 or 2 people. David Friedberg (01:06:41): You know, entirely new tools can be built with a handful of people entirely new businesses. This is an incredible economic opportunity. And, again, if the US tries to regulate it or the US tries to come in and stop the location of models in general or regulate models in general, you're certainly gonna see those models have continued to evolve and continue to be utilized in very powerful ways they're gonna be advantageous to places outside the US. There's over a 180 countries on earth. They're not all gonna regulate together. It's been hard enough to get any sort of coordination around financial systems, to get coordination around climate change, to get coordination around anything on a global basis. to try and get coordination around the the software models that are being developed, I think, is is pretty naive. David Sacks (01:07:23): You don't wanna have a global organization. I think you need to have domestic organization that protects US. And I think Europe will have their own. Again, FDA versus Emma. Canada has its own. Japan has its own. China has its own. And they they have a lot of overlap and a lot of commonality in in the guardrails they use. And I think that's what's gonna happen here. Chamath Palihapitiya (01:07:43): This will be beneficial only for political insiders will basically be able to get their projects and their apps approved with a huge deadweight loss for the system because innovation will completely slow down. But to let me build on Friedberg point, which is that we have to remember that AI won't just be used by nefarious actors. It'll be used by positive actors. So there will be new tools that law enforcement will be able to use. And if somebody's creating phishing sites at scale, they're gonna be probably pretty easy for, you know, law enforcement AIs to detect. So let's not forget that there'll be copilots written for our law enforcement authorities. They'll be able to use that to detect and fight crime. And a a really good example of this was in the crypto space. We saw this article over the past week that chain analysis has figured out how to basically track, you know, illicit Bitcoin transactions. And there's now a huge number of prosecutions that are happening of illegal use of Bitcoin. And if you go back to when Bitcoin first took off, there was a lot of conversations around Silk Road and the only thing that coin was good for. It was basically illegal transactions, blackmailing, drug trafficking, and therefore, we had to stop Bitcoin. Remember that was the main argument? And the counterargument was that well, no. Bitcoin, like any technology can be used for good or bad. However, there will be technologies that spring up to combat those nefarious or illicit use cases. And sure enough, you had a company like Chainalysis come along, and now it's been used by law enforcement to basically crack down on the illicit use of Bitcoin. And if anything, it's cleaned up the Bitcoin community tremendously. And I think it's spelled this idea that the only thing you'd use Bitcoin for is black market transactions, quite the contrary. I think you'd be really stupid now. Chamath Palihapitiya (01:09:27): to use Bitcoin in that way. It's actually turned Bitcoin into something of a honeypot now because if you used it for nefarious transactions, your transactions record in the blockchain forever or just waiting for chain analysis to find it. So again, using Bitcoin to swing illegal would be really stupid. I think in a similar way, you're gonna see self regulation by these major AI platform companies combined with new tools that are used, new AI tools, that spring up to help combat the nefarious uses. And until we let those forces play out, I'm not saying regulate never. I'm just saying we need to let those forces play out before we leap to creating some new regulatory body that doesn't even understand what its mandate emissions supposed to be. Jason Calacanis (01:10:09): The Bitcoin story is hilarious, by the way. Speaker 3 (01:10:12): Half impressed Jason Calacanis (01:10:13): The Wall Street Journal story. It's unbelievable. Pretty epic. It took years, but, basically, this guy was buying blow on Suck Road. and he deposited his Bitcoin. And then when he withdrew it, he there was a bug that gave him twice as many Bitcoin, so he kept creating more accounts, putting more money into Silk Road and getting more Bitcoin out. And then years later, the authorities figured this out again with, you know, chain analysis type things. David Sacks (01:10:38): Look at James Zong over there. Look at Jason Calacanis (01:10:40): -- James on. He accused, had a Lamborghini, a Tesla, a lake house, and was living his best life apparently when the feds knocked on his door and found the digital keys to his crypto fortune in a popcorn tin in his bathroom and in a safe in his basement floor. So there you have it. Speaker 3 (01:11:03): Well, the David Sacks (01:11:03): reason the reason I posted this was I was like, what if this claim that you can have all these anonymous transactions actually fooled an entire market because it looks like that this anonymity has effectively been reverse engineered and there's no anonymity at all. And so What Bitcoin is quickly becoming is like the most singular honeypot of transactional information that's complete and available and public. And I think what this article talks about is how companies like chain analysis and others have worked now for years almost a decade with law enforcement to be able to map all of it. And so now every time Money goes from one Bitcoin wallet to another, they effectively know the sender and the recipient. Jason Calacanis (01:11:52): And I just wanna make one quick correction here. It wasn't actually exactly popcorn, it was Cheeto's spicy flavored popcorn. And there's the tin of it where he had a motherboard of a computer that held cookies. -- David Sacks (01:12:06): chance that that this project was actually introduced by the government. Jason Calacanis (01:12:11): I mean there's been reports of tour, the economists or network that the CIA had their hands all over tour, T OR, if you don't know it, which is an anonymous, like, multi relay peer to peer web browsing system. And people believe it's a CIA Honeypot, an intentional trap for criminals to get themselves caught up in. Alright. As we wrap here, it was an amazing discussion. My lord. I didn't I never thought I would be David Friedberg (01:12:39): I wanna say one thing. Jason Calacanis (01:12:41): Yes. David Friedberg (01:12:42): We saw that someone was arrested for the murder of Bob Lee That's what I was about to introduce. Jason Calacanis (01:12:48): -- David Friedberg (01:12:48): this morning. Yeah. Which turns out that the report of the SFPD's arrest is that it's someone that he knew that also works in industry, someone that's gonna let us know. Jason Calacanis (01:12:57): Right. So so breaking news. Yep. David Friedberg (01:12:59): Yes. Possibly. But I I I wanna say 2 things. 1, Obviously, based on this arrest and the storyline, it's quite different than what we all assumed it to be, which was some sort of homeless robbery type moment that has become all too commonplace in SF. It's a commentary for me on 2 things. 1, is how quick we all were to kind of judge and assume that, you know, a homeless robber type person would do this in SF, which I think speaks to the condition in SF right now. also speaks to our conditioning that that we all kind of lacked or didn't even want to engage in a conversation that maybe this person was murdered by someone that they knew because we wanted to kind of very quickly fill our own narrative about how bad s f is. And that's just something that I really felt when I read this this morning. I was like, man, like, didn't even consider the possibility that this guy was murdered by someone that he knew because I am so enthralled right now by this narrative SF is so bad, and it must be another data point that validates my point of view on SF. So, you know, I kinda wanna just acknowledge that and acknowledge that. We all kinda do that right now. But I do think it also does, in fact, unfortunately speak to how bad things are in SF because we all are we've all have these experience of feeling like we're in danger and under threat all the time where we're walking around in SF. In so many parts of San Francisco, I should say, where things feel like they've gotten really bad. I think both things can be true that we can kind of feel biased and fill our own narrative. by kind of latching on to our assumption about what something tells us, but but it also tells us quite a lot about what is going on in itself. So I I just I just wanted to make that point. Jason Calacanis (01:14:36): fairness, and I think it's fine for you to make that point. I am extremely vigilant on this program to always say when something is breaking news, withhold judgment, whether it's Trump case or Jesse Smollett or anything in between January 6. Let's wait and trigger all the facts. And in fact, quote, from Saks, We don't know exactly what happened yet. Chamath Palihapitiya (01:14:56): Correct. Jason Calacanis (01:14:57): Literally, Sachs started with that. Chamath Palihapitiya (01:14:59): Yes. Jason Calacanis (01:14:59): We do that every fucking time on this program. We know when there's breaking news to withhold judgment, but you can also know 2 things can be true, a tolerance for ambiguity is necessary. David Friedberg (01:15:11): I'm saying I didn't even do that. As soon as I heard this, I was like I was like, oh, Jason Calacanis (01:15:15): homeless person got it. -- assumption to but but David, that is a fine assumption to make. That's a fine assumption to make. -- Chamath Palihapitiya (01:15:21): assumption. Listen. Jason Calacanis (01:15:22): You made that assumption for your own protection. Chamath Palihapitiya (01:15:25): We got all these reporters who are basically propagandist trying to claim that crime is down in service They're all basically seeking comment from me this morning sending emails or trying to dunk -- God. Jason Calacanis (01:15:34): -- Chamath Palihapitiya (01:15:34): on us because we basically talked about the Bob Lee case in that way. Listen. We said that we didn't know what happened, but if we were to bet, at least what I said, is I bet this case, it looks like a lot like the Brianna Cuthra case. That was logical. That's not condition or bias. That's logic. And you need to look at what else happened that week. Okay? So just the same week that Bob Lee was killed. Let me give you 3 other examples of things that happened in Gotham City, AK, San Francisco. So number 1, former Fire commissioner, Don Carmagnani was beaten within an inch of his life by a group of homeless addicts in the marina. And one of them was interviewed in terms of why it happened. And basically, Don came down from his mother's house and told them to move off his mother's front porch because they were obstructing her ability to get in and out of her apartment. They interpreted that as disrespect, and they beat him with a tire iron or or a metal pipe. And one of the hoodlums who was involved in this apparently admitted this. Yeah. Play the video. Speaker 7 (01:16:37): Somebody over the head like that and attack him. Speaker 3 (01:16:40): because he was really dis it was disrespectful. We Jason Calacanis (01:16:43): -- Speaker 7 (01:16:44): Who was disrespectful? Speaker 3 (01:16:45): That was a big kinda bald haired old man. Speaker 7 (01:16:49): Don. Don. So he was being disrespectful. And then but is that enough to beat him up? Jason Calacanis (01:16:55): Yeah. Sometimes. Oh my lord. I mean, it's So Chamath Palihapitiya (01:16:58): this is case number 1. And apparently, in the reporting on that person who was just interviewed, he's been in the arena kinda terrorizing people. maybe not physically, but verbally. So you have, you know, bands of homeless people encamped in front of people's houses, Don Carmagnani gets beaten within an inch of his life, you then had the case of the Whole Foods store on Market Street shut down in San Francisco. And this was not a case of shoplifting, like some of the other store closings we've seen. They said they were closing the store because they could not put protect their employees. The bathrooms were filled with needles and pipes that were drug paraphernalia. You had drug eyes going in there using it. They were engaging in all applications with store employees. And Whole Foods felt like that to close a store because, again, they cannot protect their employees. 3rd example, board supervisors had to disband their own meeting because their Internet connection got vandalized. The fiber for the cable connection to provide their Internet, got vandalized so they had to basically disband their meeting, Aaron Preston was the one who announced this. And you saw in the response, to this, yeah, my retweeting him went viral. There were lots of people who said, yeah, I've got a small business and the Friedberg, the copper wire, whatever, was vandalized. And in a lot of cases, I think it's basically drug addicts stealing whatever they can. They steal $10 of copper wire, sell that to get a hit, and it causes $40,000 of property damage. Jason Calacanis (01:18:24): Here's the insincerity, Saks. Literally, the proper response when there's violence in San Francisco is, hey, we need to make this place less violent. Is there a chance that it could be people who know each other? Of course, that's inherent in any crime that occurs that there'll be time to investigate it. But literally, the press is now using this as a moment to say there is no crime in San Francisco or that people are reacting. And like, I just have the New York Times email me during the podcast, Heather Knight from the Chronicle, San Francisco Chronicle in light of the Bob Lee Killing appearing to be an interpersonal dispute still doesn't know. Right? We we don't have all the facts. With another tech leader, do you think the tech community jumped to conclusions? Why are so many tech leaders? Painting San Francisco has a dystopian healthscape with the real with the reality is more nuanced. I think it's Chamath Palihapitiya (01:19:10): a little typo there. Well, yeah. Let me Yes. Jason Calacanis (01:19:13): And he hits, like, of course, the reality is nuanced. Of course, it's a hellscape. Walk down the street, Heather, David Sacks (01:19:20): Can I give you a theory? Please. I think it was most evident in the way that Elon dismantled and manhandled the BBC reporter. Jason Calacanis (01:19:31): Oh my god. That was brutal. David Sacks (01:19:33): This is a small microcosm of what I think media is. So I used to think that media had an agenda. I actually now think that they don't particularly have an agenda. other than to be relevant because they see waning relevance. And so I think what happens is whenever there are a bunch of articles that tilt a pendulum into a narrative? They, all of a sudden, become very focused on refuting that narrative. And even if it means they have to lie, they'll do it. Right? So you know, I think for months months, I think people have seen that the quality of the discourse on Twitter became better and better. Elon is doing a lot with bots and all of this stuff cleaning it up. And this guy had to try to establish the counternarrative and was willing to lie in order to do it, then he was dismantled. Here, you guys I don't have a bone to pick so much at San Francisco. I think I've been relatively silent on this topic, but you guys as residents and former residents I think have a vested interest in the quality of that city and you guys have been very vocal. But I think that you're not the only ones. Michelle Tandler, you know, Schellenberger, there's a bunch of smart thoughtful people who've been beating this drum? Gary Tan. And so now I think reporters don't want to write the N plus first article saying that San Francisco is a hellscape, so they have to take the other side. And so now they're gonna and kick up the counternarrative and they'll probably dismantle the truth and kind of redirect it in order to do it. So I think that what you're seeing is They'll initially tell a story, but then there's too much of the truth. They'll go to the other side because that's the only way to get clicks and be seen. So I think that that's what you guys are a part of right now. Chamath Palihapitiya (01:21:20): They are in the business of protecting the narrative, but I I do think there's a huge ideological component to the narrative, both in the Elon case where they're trying to claim that there was a huge rise in hate speech on Twitter. The reason they're saying that is because they want Twitter to engage in more censorship That's the ideological agenda. Here, the agenda is this radical agenda of decarceration. They actually believe that more and more people should be let out of prison. And so therefore, they have an incentive to deny the existence of crime in San Francisco and the rise in crime in San Francisco. If you poll most people in San Francisco, large majorities of San Francisco believe that crime is on the rise because they can see it, they hear it. And what I would say is, look, that I think there's a pyramid of activity, a pyramid of criminal or antisocial behavior in San Francisco. that we can all see. The base level is you've got a level of chaos on the streets where you have open air drug markets, people doing drugs. sometimes you'll see, you know, a person doing something disgusting, you know, like people defecating on the streets or even worse. Then there's, like, a level up where they're chasing after you or, you know, harassing you. People have experienced that have experienced that. Then there's a level where there's petty crime your car gets broken into or something like that, then there's the level where you get mugged. And then finally, the top of the pyramid is that there's a murder. And it's true that most of the time, the issues don't go all the way to the top of the pyramid where someone has murdered. Okay? But that doesn't mean there's not a vast pyramid underneath that of basically quality of life issues. And I think this term quality of life was originally used as some sort of way to minimize the behavior that was going on, saying that they weren't really crime. So you shouldn't worry about them. But if anything, what we've seen in San Francisco is that when you ignore quality of life crimes, you will actually see a huge diminishment in what it's like to live in these cities, like quality of life is real. Chamath Palihapitiya (01:23:20): And that's the issue. And I think what they're trying to do now is that, say that because Bob Lee wasn't the case that we thought it was, that that whole pyramid doesn't exist. Doesn't exist. Pyramid exists. We can all experience it. Jason Calacanis (01:23:31): Oh my god. And and and that's the insincerity of this. Chamath Palihapitiya (01:23:34): It is insincere. And the existence of that pyramid that we can see and hear and feel and experience every day is why we're willing to make a bet. We called it a bet. that the Bob Lee case was like the Brianna Cuthur case. And in that -- With Jason Calacanis (01:23:47): a disclaimer. With a disclaimer. We always do a disclaimer here. And just to George Hammond from the Financial Times who emailed me, here's what he asked me. There's a lot of public attention neatly on whether San Francisco status has one of the top business and technology hubs. The US is at risk in the aftermath of the pandemic duh. Obviously, it is. I wondered if you had a moment to chat about that and whether there is a danger that negative perceptions about the city will damage its reputation founders and capital allocators in the future. So essentially, the and it says there's obviously a lot of potential for hysteria in this conversation, which I'm keen to avoid. And it's like, Have you walked down the street? And I asked him, have you walked down the street in San Francisco? David Sacks (01:24:24): Jason, the best response is send him the thing that Saxent, which is the amount of available office space in San Francisco -- 15,000,000. Yeah. Jason Calacanis (01:24:33): -- David Sacks (01:24:34): companies are voting with their feet. So it's already if the quality of life wasn't so poor, they state. Chamath Palihapitiya (01:24:38): This is the essence of of gaslighting is what they do is that people who've actually created the situation in San Francisco with their policies their policies of defunding the police, making it harder for the police to do their job decriminalizing theft under $950, allowing open air drug the people who have now created that matrix of policies have created the situation, what they then turn around and do is say no, the people who are creating the problem are the ones who are observing this. That's all we're doing is observing and complaining about it. And what they try to do is say, well, no. You're you're running now in San Francisco. We're not the ones creating the problem. We're observing it. And just this week, Another data point is that the mayor's office said that they were short more than 500 police officers in San Francisco. Jason Calacanis (01:25:20): Yeah. Nobody who who's gonna become a police officer here? Are you crazy? Chamath Palihapitiya (01:25:23): Well and there was another article just this week about how there's a lot of speculation. Rumors are swirling of an unofficial strike, an informal strike by police officers who are normally on the force who are tired of risking life in limb. And then, you know, they basically risk getting out of physical altercation with a homeless person, they bring them in, and then they're just released again. So there's a lot of quiet quitting that's going on in the job. It's like this learned helplessness because Why take a risk? And then the police commission doesn't have your back. It seems like the only time you have prostatory zeal by a lot of these prosecutors is when they can go after a cop. not one of these repeat offenders. And you just saw that, by the way, in LA. Jason Calacanis (01:26:03): Oh, look. motherboard in New York Times just emailed and dm ed me. David Sacks (01:26:06): And then and then did you guys say that instead of solving these issues, the board of supervisors was dealing with a wild parrot. What was it? What was it? Chamath Palihapitiya (01:26:17): The meeting that was disbanded. David Friedberg (01:26:18): They had or yeah. They had scheduled a meeting to vote on whether the wild parrot are the official animal of the city of San Francisco. So that was the the scheduled meeting that got disbanded. Jason Calacanis (01:26:32): Also, can I may I just clarify what Chamath talked about with the Elon interview? A BBC reporter interviewed Elon and said, there is much more race and hate and hate speech in the feeds on Twitter. And he said, can you give me an example? And he said, well, I don't have an example, but people are saying this. I said, which people are saying it? and the BBC reporter said, well, just different groups of people are saying it. And, you know, I've certainly seen it. He said, okay. You saw it and for you? He goes, no. I stopped looking at for you. He said, so Give me one example of hate speech that you've seen in your feed. Now we without speaking about any insight information, which I do not have much of, they they've been pretty deliberate of removing hate speech from places like for you. And, you know, it's a very complicated issue when you have an open platform, but the the people may say a word, but it doesn't reach a lot of people. So if you were to say something really nasty, it doesn't take a genius to block that and not have it reach a bunch of people. This reporter kept insisting to Elon that this was on the rise with no factual basis for it that other people said it. And then he said, but I don't look at the feed. He said, so you're telling me that there's more hate speech that you've seen, but you just admitted to me that you haven't looked at the four you feed in 3 months. And it was just like this completely weird thing. I just had mother-in-law. Chamath Palihapitiya (01:27:42): You caught him in a lie. David Sacks (01:27:44): You caught him in Chamath Palihapitiya (01:27:44): a lie. Jason Calacanis (01:27:45): And and this is the thing. If you're a journalist, just cut it down the middle Come with prepared with facts and stop taking a position either way. David Friedberg (01:27:53): I wanna connect one dot, please, which is that he filled in his own narrative, even though the data wasn't necessarily there, in the same way that, you know, we kinda filled in our narrative about San Francisco with the Bob Lee, you know, murder being another example. No. Jason Calacanis (01:28:12): We put a disclaimer on it immediately put a disclaimer on it. Chamath Palihapitiya (01:28:15): We did it. Hold on a second. We we knew what we didn't know. And furthermore, we're taking great pains this week to correct the record and explain what we now know. Yeah. They report into that. He was a so hard Jason Calacanis (01:28:27): to be intellectually honest? This is just intellectual honesty. Chamath Palihapitiya (01:28:31): Honestly, you're you're you're doing soft here, Friedberg. You're getting gaslit by all these people. David Friedberg (01:28:36): I'm not gonna gas up anyone. I think the guy the guy totally the guy totally had zero data. By the way, when you're a journalist, you're supposed to report on data and evidence. So he's certainly know, I think completely Chamath Palihapitiya (01:28:47): failed at Jason Calacanis (01:28:47): a job. Yeah. Chamath Palihapitiya (01:28:48): Yeah. Don Carmagnani. It's the same story. David Friedberg (01:28:50): Yeah. Chamath Palihapitiya (01:28:51): It's just that Don Don happened to survive. David Friedberg (01:28:54): Guys, I love I love you, but I gotta go. Jason Calacanis (01:28:56): Goodbye. Here's Rick Maxwell from Mother Finance. Have fun. There's been a lot of discussion about the future of San Francisco and the death quickly become politicized. Has that caused any division or disagreement from what you've seen or has that not been the case. Chamath Palihapitiya (01:29:11): The press is gleeful right now. Jason Calacanis (01:29:13): They're gleeful. Like, oh my god. It just you know what? Just like the right was gleeful with Jesse Smollett having gotten himself beaten up or, you know, setting up his own. Alright, everybody. 4, the Sultan of Science currently conducting experiments on a beach to see exactly how burnt he can get with his SPF 200 under an umbrella wearing a sun shirt, and pants. David Sacks (01:29:39): Friedberg Freeburg on the beach wears the same outfit astronauts wear when they do space walks. Jason Calacanis (01:29:44): Hey, stable diffusion. Make me an image David Friedberg wearing a full body bathing suit covered an SPF 200 under 3 umbrellas on a sunny beach. Thank you for the diffusion. David Friedberg (01:29:58): Oh my god. Jason Calacanis (01:29:59): For their dictator, Chemah, Palihapitiya, creating regulations. David Sacks (01:30:04): And the oh, the regulator. You can call me the Jason Calacanis (01:30:06): regulator. The regulator. See you tonight when we'll eat our orchelons, what's left of them. The final 4 or 5 orchelons, in existence or David Sacks (01:30:13): in exchange. Otherwise, I'm putting you on the b list today if you're alive. Jason Calacanis (01:30:16): I will be there. I won't be there. I promise. I promise. I promise. Can't wait to be there. And The rain man himself, Namaste, didn't even get to putting Ron -- Oh, we'll talk about that. -- versus Nikki putting Ron. -- David Friedberg (01:30:28): make Oh, ho ho ho ho ho ho David Sacks (01:30:28): ho ho Speaker 3 (01:30:29): ho ho ho ho ho ho ho ho ho ho ho ho ho ho ho ho ho Chamath Palihapitiya (01:30:30): I think you should ask auto GPT how you can eat more endangered animals. How what about the plan for you? Jason Calacanis (01:30:37): Yes. And then have it go kill those animals -- Give it a bunch of -- -- world. Put something on the dark web to go kill the remaining rhinos and bring them to Chamont's house for Coconut. David Sacks (01:30:48): I don't think rhinos would taste good. Chamath Palihapitiya (01:30:50): Wasn't that the plot of a movie? It was a Jason Calacanis (01:30:52): -- David Sacks (01:30:52): Oh, did you guys see is cocaine Barrel yet? No. Chamath Palihapitiya (01:30:55): It was a Matthew Marlene Brando movie. Right? Where they're doing the takeoff on the godfather was the French version. David Friedberg (01:31:00): Yeah. Yeah. Yeah. Yeah. Yeah. Chamath Palihapitiya (01:31:01): It's like a conspiracy to eat endangered animals. He has the freshman. Speaker 3 (01:31:06): The freshman. Chamath Palihapitiya (01:31:07): It came out in 1990. Mhmm. Yeah. Marlon Brando did it with Matthew Broderick and like Bruno Kirby. They actually they that was the whole thing. David Sacks (01:31:16): Bruno Kirby. That's a deep hole. Chamath Palihapitiya (01:31:18): They were actually they were eating endangered animals. Jason Calacanis (01:31:21): What do you what do you think? Heat 2. Is that gonna be good? Saks? I know heat's one of your favorite films me too. My good name. Chamath Palihapitiya (01:31:27): Is there a sequel coming? Jason Calacanis (01:31:28): They're gonna do heat 2? The the novels already come out. Adam Drive Speaker 3 (01:31:31): is gone. Chamath Palihapitiya (01:31:31): It's all the novel. Yeah. David Sacks (01:31:33): Heat's amazing. Chamath Palihapitiya (01:31:34): Heat is amazing. Speaker 3 (01:31:34): Amazing. One of those Chamath Palihapitiya (01:31:35): movies where when it comes on, you can't stop watching it. Jason Calacanis (01:31:38): Can't stop watching it. Chamath Palihapitiya (01:31:40): Best bank robbery slash shootout in movie history. You know? Jason Calacanis (01:31:44): That is literally the best highest film ever. Like, up there with, like, the Joker with reservoir dogs, the the the Joker in that Batman movie where he robs the bank. Like, I mean, what a great day. Alright. Love you, Basties. And 4, blah blah blah blah. This is gonna be all in podcast 124. If you wanna go fan meet ups and hang out with other outstanding. Blah blah blah blah. Speaker 3 (01:32:04): Bye y'all, baby. Jason Calacanis (01:32:05): Bye bye. Bye bye. Speaker 5 (01:32:08): We'll let your winter's ride. Jason Calacanis (01:32:11): Rainman, David Saffens. I'm going home. Speaker 5 (01:32:15): And I said -- We open source it Speaker 3 (01:32:17): to the fans, and they've just gone crazy with it. Jason Calacanis (01:32:24): what air went and dry. Besty's our dog. That David Friedberg (01:32:31): is my dog I'm missing your driveway. David Sacks (01:32:38): We should all just get a room and just have think you, George, because they're all just useless. It's, like, this, like, sexual tension, and they just need to release their vows. Jason Calacanis (01:32:47): When you're the thief, What? Fire of Chamath Palihapitiya (01:32:49): your feet. Jason Calacanis (01:32:51): What? I couldn't feel it. Where did you get Merckies are back?