Who Will Own the Internet? a16z’s Chris Dixon on AI and Crypto

Chris Dixon: What will be the economic models for creative people in an AI world? Don't stop the inevitable, which is the technology progressing. Lean into it and rethink those models. That to me is the most exciting area for this intersection. In the last few years, AI has been the talk of the town. Founders have pivoted, incumbents have plowed capital into new projects, VCs have upended their investing theses. All of this as part of the race to capitalize on what seems like the biggest platform shift in decades, and equally a new generation of the internet. This generation is not only an opportunity to rethink the past, but with parallel technology tracks from new hardware to crypto intersecting, we can build things we never could before. So what will the economic model of this wave be when so much is being upended? You go to their websites, they give you an answer. And so what happens to the billion other websites if they aren't getting traffic is the question, right? When will we move past this skeuomorphic phase of this generation to building net new behaviors? And could crypto be the counterbalance to the centralizing gravity of AI, targeting more data, more compute, and more complex models? Where we're headed is a world where you have five big systems, let's call it, three to five big AI systems. Joining us to discuss all this and more are A16Z Growth general partner David George and A16Z Crypto founding partner Chris Dixon. Last year, of course, Chris wrote his book, Read, Write, Own, building the next era of the internet, all about how blockchains might finally bring us back to the early promise of the internet, a decentralized democratic network of innovation, connection, and freedom. So without further ado, let's dive in. By the way, if you did like this episode, it comes straight from our AI Revolution series. And if you missed any of the previous episodes of that series, with guests like AMD CEO Lisa Su, Anthropa co-founder Dario Amadei, and the founders behind companies like Databricks, Waymo, Figma, and more, head on over to A16Z.com slash AI revolution. As a reminder, the content here is for informational purposes only, should not be taken as legal, business, tax, or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund. Please note that A16Z and its affiliates may also maintain investments in the company's discussed in this podcast. For more details, including a link to our investments, please see a16c.com slash disclosures. Chris, thanks for being here. Yeah, thanks for having me. I'll always love hanging out with you. Obviously, you spend most of your time in crypto today. How do you generally see crypto and AI interacting? Yeah, I mean, so I think, first of all, my kind of meta view is that the technology waves tend to come in pairs or triples. 15 years ago, it was mobile, social, cloud. And I'm always giving this speech to entrepreneurs. They tend to reinforce each other. And so mobile was what took computing from hundreds of millions to billions of people. Social was the killer app that hooked them. And cloud was the infrastructure that made it possible. Right. And so you couldn't really have all three of them. And I remember back then people having debates, which are better. It turned out they were all better. And they were all required. They're all required. And so I think of that with AI, crypto, and maybe new devices, the other kind of probably robotics and self-driving cars and VR and things. I think of those as the three interesting things going on. And I think they all kind of complement each other and work together. It's a new way to architect internet services, a new way to build networks that has a bunch of different properties, which I argue are beneficial for a bunch of reasons and can do a set of things you couldn't do before, essentially. And so I think a lot of people think of it as Bitcoin or meme coins or something. And so that's fundamentally not what it is to me or I think to the kind of smart people working in the space. There's many different ways in which it intersects with AI. So the first way, which is something we've invested a bunch in, is just using this new architecture to build AI systems. And so, for example, one of the core questions I think, we've just talked a lot at this firm about the future of AI, is to what extent will AI be controlled by a small set of companies or controlled by a broad community? The obvious first question there is, is it open source? It's negatively shocked me how closed source the world has become. Ten years ago, everything was open and put in papers, and then it all shut down and was closed. and they said this was for safety reasons. I think it just happened to be very good for their defensibility. I just think it's beneficial business reasons. I don't believe the safety thing. But thankfully, there's these ones like Llama and Flux and Mistral and things who are open source. I worry that's a little fragile because, first of all, I don't know, a lot of them don't put their weights open. Is it really open? Some of it's open. Like the data pipeline's not open. Is it really reproducible? They could switch it tomorrow. These models get better every month. And if they don't start doing the new frontier, I don't know. So it's like... It's very heavily dependent on one large company. Yeah. So one of the things we've invested in is a stack of internet services that are built for the AI stack, but open services a different layer. So as an example, there's a project called Jensen, which is building, think of it as crowdsource compute layer. And so you as a startup can submit a job that goes beyond the compute you control, and it goes out to a network kind of Airbnb style of people that have access compute, and the network manages that supply and demand. And that's the economic ledger. Yeah, that's one example. Another one is one called Story Protocol, which is a new way to think about registering intellectual property. And so you can create image or video or piece of music, and then you register it on a blockchain, which keeps a record of the piece of media and the rights around it. It uses existing copyright law. So it actually, so like the blockchain record mirrors a legal agreement that's been crafted to work internationally. And then anyone can come along, and as long as they abide by your terms that you set, you might say something like, you can use this, you can remix it, you can create derivative works, but any revenue you make, you have to pay me 10% or whatever. Downstream, there's a tick, yeah. You set the terms. But that creates this sort of open marketplace where right now you have to call up some company and try to do a BD deal and this and that. And so you end up having this kind of thing where people either basically steal it or don't do it, or they're scaled enough to make a deal or something. Like you have OpenAI going to Shutterstock, and they paid them $100 million. But this is really just for the very high-end companies. This is creating a broad, democratic kind of resource where anyone can, a small creator can set the terms. And then ideally what you create, and this is a recurring theme in the blockchain world, is you have this kind of what we call composability. I think the kind of core force behind the success of open source software. I mean, people forget this, but open source software, certainly the most successful open computing movement in the last, you know, 80 years. But Linux went from 0% market share in the 90s to probably, I don't know what, 90-plus percent market share today. And a lot of that's because of what we call composability, which is basically all these different people coming along and contributing little pieces to the system and the system collectively getting much better in the same way that Wikipedia is a collective knowledge system. And so something like Story Protocol, you get the same kind of Lego brick effect with media. So someone comes along and they create a character, someone else creates another character, someone else remixes them, someone else, and then you can use whatever AI tool, you can create generative AI, and you can create your story. I create a new superhero universe where I use these other Lego bricks, And as long as the money kind of waterfalls back, that's all okay. I think it's a, to me, that's a, to me, that's a recurring theme in our investing. It's like, what will be the economic models for creative people in an AI world? Don't stop the inevitable, which is the technology progressing. Lean into it and rethink those models. That, to me, is the most exciting area for this intersection. You go from social networking companies, which keep 100% of revenue for themselves when creators create stuff effectively, to something where hopefully the creator can capture an upfront amount that they set. And then ideally, the composability allows for actually more creativity built on top. That's right. Because of the economic incentive alignment. Yeah. We're seeing people do interesting stuff with kind of crowdsourced model evaluation. Just think of it as all the data side of things. Like, you need more data. And we have this crypto as a breakthrough in new ways to design incentive systems. And so you combine that, and you say, well, how can you use new incentive systems to get more data for these AI systems right Data can either be an input or it can be a model evaluation or whatever it might be So it kind of what these companies like Scale AI do but in a crowdsourced way instead of a centralized way There a project that co by Sam Altman that we investors in called WorldCoin, where the thesis is that in a world where AI can replicate humans and content, we need a way to prove you're human. And the best way to prove you're human is cryptographically using a blockchain. And so the idea is they have an incentive system to be able to sign up and originally it was this orb that scanned your eyeballs that some people was controversial they now have systems where you can identify yourself in other ways including your passport and other things but the idea is you prove who you are you get cryptographic proof found on a blockchain and then you can use that for a bunch of different services think of very simple examples think of captchas today you have to go and play these puzzles which i think have gotten so complicated and probably not ai proof anymore i don't say i have proof anymore and they may be human proof i have trouble with a lot of them but replace those with a set of of systems like that and other kinds of clunky fraud systems have an actual cryptographic thing. So I have a code, essentially. This is how cryptography works. And that code proves that I'm a human. And then you can layer onto that other kinds of things you prove on top. So I think there's a bunch. So there's the infrastructure layer of like take AI systems that exist today in a centralized way and decentralize them both in terms of code and services. There's new things you couldn't do before, like machine-to-machine payments. And then there's these sort of really far off things that I find the most exciting, which are like, what are new business models in this world? Yeah. One of the things that you pointed out to me right after the chat GPT moment is you're like, hey, we have the potential for sort of a break in the pact of the internet. Oh, yeah, yeah. Which I think is a super fascinating problem. Yeah, yeah. There's a chapter on this in the book toward the end. I call it a new covenant. So like you think about the incentive system. One of the main reasons the internet succeeded is it had a very clever incentive system, right? Like how do you get 5 billion people to sort of opt into the system without having a central authority tell them to, right? This is because of the incentives of the internet. And specifically, there's been a kind of what's emerged over the last 20-ish years is I call it an economic covenant between the kind of the platforms, specifically social networks and search engines, and all the people that create websites that essentially those link to, right? Yeah, exactly. And so if you're a travel website or a recipe website or a artist who has illustrations, there's an implicit covenant you have, let's say, with Google, right? Which is you say to Google, it's okay if you crawl my content and you index me and you show snippets in your search engine if you send me traffic back. This is how the internet has evolved. And why do you want traffic back? Because you have some business model. Maybe it's a free site. Maybe it's an ad-based site. Maybe it's a subscription-based site. But whatever it is, somehow you have a way to make money on traffic. There's some understanding. Or it's mutually beneficial. Mutually beneficial. And occasionally that has been breached. So there was a thing Google does called one-boxing, which is they would take your content and just put it, like I was on the board of Stack Overflow for a long time, and they would do this, where they would take, you type in a thing for Stack Overflow, instead of clicking on it, they would just show you the answer and remove the click. They've done that with Wikipedia. They did it with Lyric sites. Yeah, but they did it with Yelp. They did it with Trout. Yeah, and people get very upset. Or they, with Yelp, they promote their own content on top. And so there were issues, but it worked, right? Now, the question in an AI world, right, is if you have these chatbots, if you go and you say, I want an illustration, and it just generates an illustration, or you say, I want a recipe, and it gives you a recipe. This might be a better user experience, by the way. I'm not against it. I think it's probably better in the end for the users of the Internet. But the problem is it breaks the covenant, right? They took this data. these systems were trained on data that was put on the internet under the prior covenant. Under the premise that they're going to get traffic back and they can monetize it correctly. And that was the premise. And that was the promise, right? And now you have a new system which may not send the traffic. In fact, it probably won't. If these things can just tell you the answer, why would you click through? And so that's probably where we're headed is a world where you have five big systems, let's call it, three to five big AI systems. You go to their websites, they give you an answer. And so what happens to the billion other websites if they aren't getting traffic is the question, right? And I'm surprised slash disappointed that I don't see anyone. I feel like I'm the only person I've ever seen talking about. I feel like I'm screaming in the abyss. Like, I'm a little bit surprised that the AI people who just, it's fine, like, they took all the data, and there'll be copyright lawsuits, and I'm not going to apply them on that. Yeah, they've done some data deals here and there. Yeah, but aren't we a little bit, even forgetting about the societal questions and all the small businesses that will be, like, don't we worry about the internet? Because I worry about just the internet. If you have an internet of five companies and it becomes a broadcast TV in the 1970s, there's four channels. Is that the world we want to live in? Is that a world that's pro-startup, pro-innovation, pro-creativity? Yeah, like a long-tail website. It's like that next generation of long-tail websites. Yeah, how do you break out? How do you create new things? So I just worry without thinking it through. And so to me, look, I'm not saying that I have the only answer to it or you have to be a crypto answer. I realize for some people that's controversial, but I think step one is we should say, OK, wait, this breaks all the incentives of the internet. And step two is, is that a good thing? I don't think so. And then, so what is the right answer? And should we create new incentives? And this is why a lot of what I've been trying to invest in and think about has been, OK, like the example I gave with Story Protocol is, let's think about new incentive systems to layer on top. Yeah. One of the things you've talked about is just this trifecta of technology products that have come along at the same time. So generative AI, crypto, and new hardware platforms. So how do you think about the three of those coming together? So yeah, and the analogy, of course, is like mobile social cloud, the last wave where they all ended up reinforcing each other. So you're already seeing some of this. You have these new devices, the AR and VR glasses and things, which use a lot of AI and the sort of her style kind of stuff. There's a whole area of crypto I'm excited about called D-PIN, which is decentralized physical infrastructure. Most prominent example is a project called Helium. And Helium is a community-owned, crowdsourced telecom network that tries to compete with Verizon and AT&T. And so basically what they did is they created an incentive system where anyone can put a helium node up in their house, and that adds a little bit to the network. It's a wireless transmitter. They got hundreds of thousands of people in the country to put these networks up. And now they offer a cellular service that's, I think, significantly cheaper than something you get from Verizon. It's like $20 a month instead of $70 a month. And it's cheaper because much of the time it's using this homegrown network. They didn't have to spend tens of billions of dollars to build it out. But what's interesting about it is that crypto is very good at creating incentive systems. Right. And traditionally in networks, the hardest part of a network is the bootstrap phase. Once a network has critical mass, it's clearly valuable. Once I can sign up for a cellular network and use it anywhere in the country, clearly I'll pay for that. When you start it off and there's only 10 houses with the cellular access, it's not something you want to use. Think of a dating site. If there's 10 people on a dating site, you don't want to use it. If there's millions, you do want to use it. This is a classic problem with building networks is how do you get over this early phase when the network effects are weak? Yeah. Right? And so crypto is the perfect complement to that. Crypto is a great way to provide incentives in the early areas of building a network. And it turns out a lot of interesting networks in the world are physical networks. So there's people doing this for climate weather modeling. There's people doing it for mapping self-driving data and mapping cars. There's people doing it for electric car charging, for cellular networking. We just did one that's around energy metric monitoring. And there's people doing decentralized science, which is you mix it in with more scientific applications. And so one sort of simple heuristic is anywhere where you want to build a network and is a challenge to build the early phases of the network, crypto can be a really useful way to help bootstrap that. Oh, interesting. Right. And so that's one of my favorite areas where the physical world and robotics intersecting with data collection and all these other themes that intersect with AI are relevant. Mark actually gave me this framework, which I like a lot, which is, is the AI frosting or sugar? You know, if the AI is frosting, is a core ingredient. If it's a frosting, all the incumbents are going to win because you just slap a chatbot on your existing product and you've got distribution. You have that selling reference power, incumbent relationships. If it's more fundamental of an ingredient, you can't actually just slap AI into the product. You have to build it from scratch, and that favors the newcomers. It's just very TV. We haven't seen anything that tells us what the answer is. The more seal your thing, the more skeuomorphic it is, which is an early cycle thing, the more it probably favors the incumbents. Another way maybe to frame Marx's thinking is the Clay Christensen view, is it disruptive or sustaining? And specifically, I think what people misunderstand about Christensen's view, right disruptiveness doesn just mean new It means misaligned with the incumbent business model Yeah exactly That sort of the interesting part of his book right is that even when the smart incumbent sees it coming it very very hard for them to react to it because it not what their best customers are asking for Yeah, exactly. Right? And so that's where I think somewhat overlaps with Mark's frosting icing thing. Well, it could be that the business model is a fundamentally shifted business model. Yeah, so you come in and you're like, instead of databases, it's some radical new architecture that's database-free. I don't know what. It's something that cannibalizes the incumbent business model and therefore makes it organizationally and economically harder for the incumbents to layer it on. We haven't seen it yet. We've seen people talk about outcome-based pricing. Well, let's talk quickly about consumer. So in consumer right now, at least, I don't think you see a lot of network effect businesses, right? So as successful as the Claude and ChatGPTs are, I don't think they have a network effect. Their switching costs are relative. Maybe they learn your history. But the question is, how do they avoid in the steady state having just a model and price competition to race to the bottom? right obviously they're important big businesses but will they be dominant yeah and then what's the opportunity for new startups if you're doing venture investing and ai consumer like you see a lot of these things that make your face prettier like these kind of fun apps and they zoom up in the app chart and then tiktok copies it and so forth right because it's just not because again no network no no yeah and there's this technique kind of strategy i like to talk about called come for the tool state for the network and the idea is maybe you can use that make my face prettier and then use that as a hook to get people into your new network, like your social network, possibly. Although it just feels very, very hard today, given the scale and power of these incumbents. And that, by the way, will intersect back to crypto, because what crypto is, and what I argue in my book, is that crypto is a new way to build networks. And so, you sort of have the chocolate and peanut butter. You have AI with all these really interesting use cases, and then you have this new technique for building networks. AI, the interesting use cases, but no network effect. And then you have this new thing that's like all network effects. Are there interesting ways to combine them? But before I get to that, I think it's important to talk about how big technologies roll out in multiple stages. So there's a distinction. It's not my distinction, but I've talked about it a lot. It's sort of one way to think about technology is that they can do one of two things. They can do old things better, or they can do new things you couldn't do before. We call the first one skeuomorphic. This is a Steve Jobs term, which sort of refers to products and designs that kind of harken back to a prior era to make them more understandable. And then there's what we call native apps, which are things which are the kind of new things that couldn't be done before. And then there's actually a third stage, I think, which is second order effects, which is you created the car and now you have the highway system. And now you're able to create suburbs and trucking infrastructure, right? Those are second order downstream effects. There's a famous line that good science fiction writers predict the car, great science fiction writers predict the traffic jam, right? So like, it's like that idea. So it's like down, like what are the second order? Like Bitcoin is something that couldn't have existed before. social networking. Yeah, of course. So 30 years ago, you say someday people are going to have their own media and you're going to remove these gatekeepers. Who would have thought? Then you're going to create these digital currencies. There would have been no way to create the community. Yeah, yeah. It would have been a New York Times article saying it's stupid and then that's the end of it. There's nowhere to get together and talk about it and create your own. I mean, they're really kind of religious movements, you know, most token communities and they need places to congregate and discuss it and now they have that. And so there's all these kind of second order. I mean, we're seeing effects in politics and all these other things. There's the whole, arguably, our society and world is changing as a second-order effect of social networking. So one way to think about AI, so the first stage is the skeuomorphic phase, which is, this is the stuff you see talked about all the time in the business and startup community of, like, your customer service bots, right? You take a job that's currently done by a person sitting in a call center, and you replace that with an AI voice and chatbot, right? In the simplest case, it's a one-to-one exchange. It's cheaper, and it's more systematic, and it will displace jobs. hopefully it will also create equally or more jobs and better jobs. But that's sort of an obvious first stage. And look, and this is, I think, one of the reasons people get so excited about the opportunity for AI is you can just see that happening in, I don't know, tens of millions of jobs, I guess. Like the whole laptop middle kind of section of the economy, you can see many of those jobs. Everyone, including us, who spend their days typing emails are heartless. That's the joke. It's like, we can speculate on it, but we're part of that group too. So that's phase one, right? It's skeuomorphic. But that phase one can last 20 years, so just to be clear. The next phase is the native phase, and to me, that's what gets me more excited. And by the way, let me give a little analogy to the internet. So the skeuomorphic phase was the 90s. And so basically, if you look at 90s internet, people were taking offline things like magazines and catalogs and putting them online. So you would go buy things, you know, and it was much easier. You could type in a website and go buy this rare book on Amazon, and it was much easier and it was convenient, but it was fundamentally something you could have done before. It just would have been clumsy and getting some weird magazine, some catalog or something. But it wasn't until the 2000s that people did things like social networking. And these things were just brand new things. There's no analog in the offline world to a lot of these new behaviors that people created. I talk a lot in detail about this in the book if people are interested. So anyway, so you saw the internet play out that way. 93 was Mosaic. And 2000, I would say 5-ish was sort of YouTube. And before, I think, was Facebook or whatever it was. So it took at least a decade. And by the way, one of the things you get in the native phase, which is why it's so exciting, is you get new products. You get new forms of media. So if you go back when photography was growing in popularity, there were all of these cultural art criticism think pieces about what will happen to art. You know, the famous like Walter Benjamin, the art in the age of mechanical reproduction. There's all these like famous essays where it was like, what's going to happen? Because now that you can take a photo and create a beautiful landscape, what's the role of the artist in that world, right? And so people were worried about it in the same way they're worried today about generative AI, right? So like, what if you can now, you know, create a movie? Looks like you can pretty soon, right? I mean, images is there. Images are there, and probably video is coming soon. What happened in the case of photography is that you had, I think, two things happen. Fine art went more abstract and away from photography, right? They leaned into what they were unique at. And that's when you had whatever, cubism and all these other kinds of movements. And then on the other side, I think what's really interesting, right, is you had the rise of film. You had someone say, hey, maybe you can use machines to replace photography, but you can also now use machines to create a brand new art form that never could exist before. You sort of had it with animation, but now you can do it a really interesting, sophisticated way with film. And so film would be what was the native form of media in the age of mechanical reproduction. Oh, that's a fascinating analogy. And so I think today, when you look at the gender of AI, the negative way to look at it, and you do see a lot of this negative sentiment from the art community and things on Twitter, where they say, look, this is just a cheap replacement for human creativity. The positive way to look at it is this is the base layer, the same way that film was a base layer back then. But now there's this new canvas of human creativity where you can create new art forms. I don't know what those are. They may be virtual worlds or games or new types of films and movies. I don't know. They may intersect with a new way to consume the media altogether. Yeah, maybe there's new interfaces. And this is to me what's so exciting about the new native media, the native apps, is that I won't think of it. Because in my experience through watching some of these waves in the past, it really does take brilliant, creative people to come up with these new things. and it surprises you in many cases. And so I think that that's going to be the exciting phase I'm looking for is not how do you just use this technology to do the things you could do today but do them cheaper, but how do you use the technology to push the frontier and do things that could never be done before in the same way that film did that, right? Yeah. I think photography probably unlocked more opportunities for creative people than it removed. And I think this would be the hope in this kind of phase. So that's the media example, but there's probably that for consumer applications and that for social networking and that for productivity. And so that will be the really exciting thing, I think, to see is not just the replacing things we do today, but come up with brand new behaviors that are things we couldn't do before. And then the third thing is the second order effects, right? So you create this new world. So you've created this world of social networking. It's interesting to think with social networking, we've seen it play out. You know, you sort of have social networking rise in the 2000s. I think it hit a tipping point. Maybe the Obama election. Yeah. Was that the 2008 and then 12 too? He really leaned into using that. And I remember seeing all these news articles like, wow, this is different. The bit had flipped from online as a secondary to sort of online was primary. But then we started seeing these kind of weirder things, like I think the Trump movement and the populism just surprised everybody And you just started seeing movements and just behavior And I think we still haven really figured out what going on but where all this is headed And we in this disequilibrium state I guess Anyways, those sort of second-order effects of social media will probably play out for, as I mentioned, like crypto and I think a bunch of other interesting movements today are second-order effects of social media. And that will probably play out for 20, 30 years. And so that will probably be phase three of the AI revolution. Yeah, and just think about the timelines. Yeah, I mean, it's probably going to take a very long time. for all that. Like, I'm always overly optimistic on these things historically. I'm like, okay, we're done with the skeuomorphic phase of AI, now we'll do the native phase. But the reality is, each phase probably takes a decade. One of the interesting things you said around these distinct phases, obviously, the internet took a long time partially because you had to build a network. Yeah. It was a supply and demand issue, right? A physical network, and then also... Literally laying cables and then wireless. Yeah, laying cables, and sure, you have to build large clusters of compute GPUs here with networking, but I think the constraining factor for getting from that skeuomorphic phase to the native phase is not necessarily capabilities themselves, but like human creativity. Yeah, I think so. I think the bottleneck will be humans and regulation, which are obviously closely connected. Yes. And I think humans on both the supply and the demand side, probably more on the demand side. So meaning supply side, you need to have people come up with all the creative things. But the world's different now in that I just think the startup world's different now. It's much more mature and much more sophisticated, honestly, than like when I was coming up in it. I mean, when I was starting off, there were 10 venture firms. Now there's thousands. The number of startups. And honestly, there's a lot of good, smart advice out there. Yeah, this is a more popular path for smart people to go do. Yeah, it's like a thing you do, like, you know, in places like Y Combinator and other places have done a good job of this. If you're coming out of a top school, I mean, even 10 years ago, this wasn't, like, I knew people that were like, wow, you could do startups. I mean, definitely that was the case 15 years ago. But now I think it's like an established career path. There's an established set of mentors, established set of funding. There's a canon of pretty good advice out there, like the standard advice it used to be terrible advice now it's good advice you can come out to San Francisco and I think relatively easily if you're a smart network friendly person get embedded pretty quickly and then you know and then Silicon Valley it's gotten just very good at throwing tons of capital energy against those problems so there's a supply side I suspect the demand side is more like another meaning like changing organizational and human work and behavior patterns like getting an organization like take the video example we're talking about yeah I mean look I wrote my book I wanted to have my own voice use AI to read the book using my own voice. Both the publisher and Audible, the podcasting platform, ban AI completely. And part of it's unions and just a bunch of resistance. I think people know this, but the capabilities are fully there to do that. Yeah. I mean, look, Mark Andreessen had a great blog post. It's like, how do I know they're going to ban AI medicine? Because they already have, essentially. I mean, essentially, these things are so heavily regulated. And just the organization, like, look, take the Hollywood a Gen AI thing. You'd have to