This Week in Startups - AI’s Future: Opportunity, Regulation & Limits with Vinny Lingham & Sunny Madra | E1729

Episode Date: April 26, 2023

Vinny and Sunny join Jason to discuss the three phases of AI adoption and the emergence of new business models (1:55), which leads to a conversation about Grimes open-sourcing her AI-generated vocals ...before debating whether the government should regulate AI (24:57). They wrap with a conversation about AI’s technical constraints, OpenAI’s transparency issues, and the future of startups (39:31). (0:00) Show start (1:04) Vinny and Sunny join Jason  (1:55) The three phases of AI adoption (11:15) CacheFly - Get 10 terabytes free by signing up at https://twist.cachefly.com (12:41) Building AI applications (18:27) House of Macadamias - Get 20% off your first purchase and a free bottle of cold-pressed macadamia oil at http://houseofmacadamias.com/twist by using code twist20 (19:59) Emerging business models (24:57) Grimes’ approach to AI-generated music  (28:31) Notion - Take the first step toward an organized, happier team. Apply for Notion for Startups at https://notion.com/jason. (30:04) Regulating AI  (39:31) The technical constraints of AI  (45:33) Becoming more efficient with AI  (51:16) OpenAI’s lack of transparency  (1:01:44) Lessons from Mahalo (1:05:55) The future of startups  (1:08:36) Reflecting on the Starship launch FOLLOW Sunny: https://twitter.com/sundeep FOLLOW Vinny: https://twitter.com/vinnylingham FOLLOW Jason: https://linktr.ee/calacanis Subscribe to our YouTube to watch all full episodes: https://www.youtube.com/channel/UCkkhmBWfS7pILYIk0izkc3A?sub_confirmation=1 FOUNDERS! Subscribe to the Founder University podcast: https://podcasts.apple.com/au/podcast/founder-university/id1648407190

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Starting point is 00:01:00 Welcome everybody back to this week in startups. AI and crypto are basically the two why nows that we've experienced in the last five years. One of them perhaps fading here in the United States and the other one soaring with me to discuss it all on our weekly, or every other week, biweekly AI Crypto Roundtable. Sunny Sundee Maudra, the co-founder of Definitive Intelligence, and Vinnie Lingam, the co-founder of Civic. and wait room. Welcome back to the program, boys. Thanks, for having us again. All right.
Starting point is 00:01:39 There has been a lot of discussion about the phases under which AI will be adopted. Ram Al-Alawalia, the founder of Lumida wealth management. It's an alternative asset founded investment advisor. He tweeted following prediction on AI. one, human leverage, two, operating leverage, three, management leverage. You guys agree with this? And did you see this tweet? Yeah, I really like this breakdown because what it, and it's sort of like inverse and it builds
Starting point is 00:02:11 on what we talked about in the last podcast where we see the leverage in the engineers first, then in the operating class, and then finally in the management class. And I think instinctually when people think about it, they probably think it's the other way around, but I really like the way Rom laid it out here. Finney, what are your thoughts? I agree. I know Ron. He's a good guy. He's very thoughtful about these things.
Starting point is 00:02:37 He's very analytical as well. So, look, I think the big danger is if we try and over-analyze and sort of constrain what is happening to, you know, like trying to create these categories and layers of what's happening, where, quite
Starting point is 00:02:52 frankly, it's just the wild wild ways. Who knows? So this can go in a million different directions. It can upend all the norms that we, you know, management and company building and, you know, every other norm that we can think about. This is like true disruption on every scale. And Chmott said as much in the All In podcast last week, Jekal, that you're, you know, that you host. You know, he's having to rethink everything and it's a humbling experience. Yeah, I look at this and I think what we're seeing is smart people trying to build a
Starting point is 00:03:24 model as to where this is going. Vinny, your point is well taken. And Shabath, a great example. He's one of the, you know, I would say one of the great strategic thinkers that we know. And people are trying to build a mental model of what is happening right now and where this is going. However, the pace at which this is going and some of the dynamics, as you're saying, Vinny, are not typical. They're unique to this moment in time. They are in fact, uh, black swans perhaps. I, I look at this and when I do my, hey, here's three phases, which everybody seems to like to use the three phase approach. I'm not sure why it's not four or six. McKinsey, it's a McKinsey three.
Starting point is 00:04:05 Yeah, we put them in circles. I don't know. Odd number works better. You can charge more money per hour when you do this McKinsey thing. I think about augmentation, which he points out human leverage engineers 10xing, but I put augmentation for salespeople, SDRs, writers, everybody in between. and then automation, where you're kind of taking some humans out of the process,
Starting point is 00:04:29 and then finally, you know, after augmentation and the sort of automation is replacement or deprecation. In other words, you just don't need certain functions anymore shortly after they're automated. So some people might be watching the automations,
Starting point is 00:04:46 which we saw with AutoGPT, but maybe at a certain point you're like, you know what, I can trust this thing. I don't need to have a huge, human here. Just like we used to have humans as elevator operators, at some point we felt confident enough to just take the human out of the elevator. So what was your thought hearing those two things, Sunny, about where this is going? Yeah, like I want to build on something that Vinny brought up last time. And I think, you know, we, we had a good discussion on it.
Starting point is 00:05:18 And I think it really, you know, good on Vinny to bring it up. And a couple of days ago, you know, Samuel had a good Twitter post, Nick, I just shared it in our chat, right? Which is actually a quote from Adam DeAngelo, who's, you know, one of the kind of the smarter minds in Silicon Valley, right? You know, ex-CTO of Facebook. And it really aligns with sort of what Vinny is saying, what Vinny was saying last week and just kind of building on that,
Starting point is 00:05:46 which also aligns to that first point. where we're seeing engineers who generally never felt this in technology. And I really like the way he kind of phrased it is that every week there's new releases. And then because of that, every day he has spent hours to learn what's changed to also then, you know, figure out is what they're doing. Does it even make any sense? This is really, really important, I think, in terms of that first bullet. So I wanted to spend just a bit more time on that again. Because, you know, last week we touched on it and it was, you know, we talked about what's happening.
Starting point is 00:06:22 But to hear, you know, more people bringing that up is really important because that's a framework that I think every person that's building right now that's close to the AI ecosystem. And even if you're not, you should be thinking about that. Yeah. Is your idea and what you're executing on even valid anymore because of something that's been released? Are you seeing that firsthand in yourself? Yeah. So I don't think it's moving that quickly right now. I think we still have a little bit of daylight between when that happens.
Starting point is 00:06:59 When the machine becomes, you know, self-aware. The singularity. Then I think it becomes a little bit more, you know, but more of a, like I say, a smaller gap between, you know, the rate of change. So the rate of change will go up, lot more. Right now it just feels fast for us, but I look around, you know, the big companies aren't freaking out. There's no huge M&A cycle right now in AI. They're not panicking just yet. Everyone's still trying to like place their beds. No one's really making money out of it either. I mean, there are a couple
Starting point is 00:07:34 guys. That's, I think, the big catalyst for when things go parabolic, right? When startups form that start eating the big company's lunches at a rate that they cannot digest or handle, that's going to be when we have the tipping point where everyone goes. Revenue destruction is what you're going to. Revenue destruction and or transference, right? And I'll use my company as example just because, right? So we are a video conferencing platform. We're rolling out AI features.
Starting point is 00:08:08 If people just start deciding to use us, and we haven't started charging it, but when we do, at a rate faster than Zoom or hangouts with a higher rate of stickiness, and maybe we had a lower price and people just move across, that's when these companies start to panic, right? And they go, oh, how do we compete with that? Well, it's AI driven. Well, what does that mean for us? Can we go and add AI?
Starting point is 00:08:27 Well, no, because we have to worry about this and this and this existing customer and this revenue and how do we charge for it. And the machines of these big companies are just very, very slow. The larger the company, the slower it is for them to make change. This is why startups always have an advantage when they're building. We can just cut to the core and say, you know, all these features and legacy that they're busy supporting and customers are paying for it. We're not going to build that. We're not going to offer that.
Starting point is 00:08:49 That doesn't make sense anymore because AI takes care of all these things. That's a disruption. I think that's coming. I think when you get to specific examples, it really opens people's eyes. In other words, there's Zoom out there. There is Otter. A lot of people got into video conferencing, maybe transcripts early. And now a new entrant with only, I don't know how many people we have a wait room, but I'm assuming.
Starting point is 00:09:11 maybe a dozen people or something, you know, a company with 1,200 people, you know, now there's an offering with 12 people. And if they, you can charge it, you have a different cost basis than they do.
Starting point is 00:09:23 Yeah, well, exactly. Like for us, because we, we cut off video at about 10, now we're busy changing the wrong, but like at 10,
Starting point is 00:09:30 you know, let's say there's 100 people on, on a call. Everything else is audio. We're only paying for 10 video streams. Whereas with Zoom, everyone has their cameras on. And,
Starting point is 00:09:40 you know, They're busy feeding the video costs. I mean, the video costs they have to eat or the customer's paying for it, right? So just as an example, right, our model's different. And that's not what makes us, I think, different necessarily. I think for us, we're focusing on the AI components because we've both had a feature roadmap that we're going to, you know, in the next 60 days, probably rolling out four to six features, which they can't do in the same amount of time. It's just not possible. Yeah, I think that's right.
Starting point is 00:10:09 20 people. And so it's the feature. So right now, I call it feature stuffing. Like, you're going to take products and services that have been built and you're going up against the incumbents. You have to stuff it with features way fast and we're not. This is what Zuckerberg did with Facebook in early days, by the way. Product velocity.
Starting point is 00:10:26 Exactly. Product velocity. How many sprints do we have in the next 60 days, 90 days? How many features can we roll out? We've done the two by two matrix and we're like looking at all the quick wins, the low-hanging fruit, stuff that we can roll out quickly. So it's not so much about rethinking everything. And I get what Adam DeAngelo is saying.
Starting point is 00:10:43 But I mean, when you're solving problems that already exist and you're just doing it a better way, I think you can overthink things about too much and focus on all the rate. Like focusing on the rate of change itself means that you're not going to be focusing on building product. And I always make, you know, whether it's wrong or right, I'd rather focus on product right now than looking at all the things that change. Even though I agree that there could be some redundancies, I'd rather roll out 10 features and two become redundant, then roll out two that are really well, because I think it's actually it's a feature race right now.
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Starting point is 00:12:35 cash fly.com and get your 10 terabytes for free forever. Yesterday I brought our accelerator and founding university back to in person. I went to the city of San Francisco and I was in the Phi Dai and I had our accelerator class at Fenwick and West over in the Phi Dai and then I had the founding university over at Wilson Sincini's office and 100 people showed up for that and then seven people in the accelerator. and the big topic of discussion was I built this using chat GPT or some other language model. And now 4.0 kind of includes it. And then are they going to just, our user is going to be able to just go use chat GPT4 instead of using mine.
Starting point is 00:13:22 And we had a really thoughtful discussion. And I said, you know, this is exactly, Sonny, the moment that happened in app development. And you had a very famous app development company in Canada with hundreds of developers. If you built something that was of low value and easy to replicate, like a flashlight app, like a calculator app, those things were 99 cents. People bought them. There was a lighter app. I mean, people had all kinds of silly apps that they built, and they were able to make, you know, $100,000 or $250,000. But shortly thereafter, you had to make something thoughtful if you want to, and something subscription that people could kind of work on.
Starting point is 00:14:04 So I told folks, it was one that was making a virtual travel agent. And I said, you know, there's things that chat GPT4 can do, but there's this entire feature set that they're never going to get to. And customizations that you can do here. And I don't want to say them out loud here and give people a roadmap. But is that not a good analogy or is it a flawed analogy, Sonny, the one I gave about apps in the app store? I like it. But I think there's one massive difference here. And again, this topic's come up a few times, which is there is an element of having access to unique data when it comes to building something in and around AI that's very important.
Starting point is 00:14:45 And that was one thing that you didn't have to think about if you're building an app. And so there's like the feature angle, but you could build something that wasn't quite the flashlight or something like that. But this whole notion that you have to have access to unique data, that's a new layer in the thinking around, you know, how you can differentiate yourself. Because what I refer to, what I refer to OpenAI as is the apex aggregator. So if it's anything that can be aggregated, it will be like, you know,
Starting point is 00:15:15 the top of the food chain, right? The T-Rex, the, you know, great white, whatever you want to call it, right? And so I think- Like Google index the world's information. Sure. But in, in, but what Google always promised to,
Starting point is 00:15:30 and it continues to still do, and you know this really well, but you know, you were impacted by this in Mahalo, right? Which was, they promised at least drive traffic to you. When OpenAI becomes the apex aggregator, they necessarily can,
Starting point is 00:15:47 they don't necessarily to drive traffic to you. They can connect to your API and they can get whatever data they need or perform whatever action they need without ever having sent someone to your service. And so unless you have something that's really defensible, you're going to be at risk. I didn't see that in mobile.
Starting point is 00:16:05 And that kind of defensibility is much harder to achieve than it was in mobile. Let me just ask you, Sunny, what do you think about the you know, the difference? So open AI, yes, apex, you know, what do you call apex aggregator or?
Starting point is 00:16:25 Aggregator. Yeah, so Apax language model. Yeah, fine. So they're not, the only one. There's, you know, there's a half a dozen of these out there that are actually pretty sophisticated, maybe not at the same level, maybe not the same development team. When companies are busy building out, and Google's got one as well, which is actually pretty good, et cetera, like, how agnostic do you think developers should be? So, in other words,
Starting point is 00:16:49 like, when you're building features, like, we're building features, it's transcription, it's summaries, et cetera, those features are agnostic to the model we use. So if we find that, you know, Google makes it a better product. We can switch across to it. So, like, how do you think about that? Well, I think the ultimate pattern right now, at least that seems like it's going to play out, is that you'll have like sort of a main, let's say, LLM that you interact with. And that LLM will have a series of agents that it interacts with.
Starting point is 00:17:19 Some of those maybe LLMs themselves and some of those agents just maybe more traditional, just pieces of software that interact with an API. And I think the interesting thing about Open AI right now is that they've made that jump before anyone. So they have this plugin ecosystem. They have a whole bunch of developers submitting to it. My guess is they'll have thousands when they launch, right? So it won't be like the App Store. It'll be even, you know, App Store day one where it's just a few apps when it came out.
Starting point is 00:17:48 And I think what's quickly going to happen is we're going to see a disruption. So kind of to answer your point, Vinnie, it is a little. bit of a time to pick a winner and try to align to that. Now you have to have some flexibility in your approach, but if you look at where things are at today, there is a distinct difference, right? In our group chat, we were testing a quick example of one of these open source ones. And J-Cal, you know, you had done, I did the same question that you had put in the other ones a few weeks ago, right around, hey, give me a list of companies. And it's just not as good at it as open AI is.
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Starting point is 00:19:43 extra virgin macadamia oil with any purchase. Go to House of Macadamias.com slash twist and use the code Twist 20. House of Macadamias.com slash twist and use that code, twist 20 so they know J-Cal says. I do think there's an opportunity here, though, for a new business model. Back in the day, in France, they had a little communication system before the internet where you could look up restaurants and it was called Minitel. And Minitel, if you remember, charged by the minute.
Starting point is 00:20:14 And it was an information service and you, and a comp you serve prodigy and originally AOL, they charge for the minute for access to data. I think, you know, with the lawsuits that are coming, with Reddit, Twitter, Cora, et cetera, Getty, Bloomberg, and others, New York Times, I'm sure we'll be right behind them, saying to people like chat GPT4, OpenAI, hey, you're going to have to pay us to use that data. A new business model emerges that will make everybody a winner, except for advertisers. So if you build, and I'll just take the travel instance, and I want to have a travel service, that's built on Chad GPT4, well, when I hit the plugins and I hit Yelp, or I hit Travel and Leisure magazine or a blog about travel, whatever it happens to be, in order to use that
Starting point is 00:21:06 data in my model, I pay them a fraction of a penny. Then that means we could invest in content and somebody like the New York Times, somebody like Bloomberg, even a blogger, if their data was used in some way, and specifically through an API call, I'm sorry, with the plugin call, it's super easy to give attribution, this could become the new model for the internet. And it would be as if, you know, micro payments were built into the browser, right? It was just something Brave's been trying to do and crypto tried to do. And we should have had micro payments. But this could be an incredible new model.
Starting point is 00:21:39 Of course, advertisers lose out of it. No, I didn't. Is it parallel thinking? Yeah, yeah. I literally said, I'll post a link here first, but a couple days ago, I think it was last week. I mean, perhaps it's obvious, but. We just haven't had this business model ever. Licensing was something that existed before the internet.
Starting point is 00:21:59 If you wanted the AP story or an AP photo in your newspaper, you signed a licensing agreement. And that kind of went out the window. I mean, blogs did have to pay in some cases to license photos and the big ones. We have like a, we have a, you know, a monopolistic version of that in Apple News. Right. When you pay for Apple News as part of your Apple One, you get access to a whole bunch of these things because Apple is further up paying those publications.
Starting point is 00:22:25 That's like a bundle, right? You're kind of getting an aggregator. But what I'm saying more is... You need micropayments, though. That's the thing. So how is micropayments going to... It's like machines aren't going to pay with wires and bank transfers and checks.
Starting point is 00:22:37 So it has to be a digital currency. Is it going to be a central bank digital currency? Is it going to be Bitcoin? Is it going to be lightning? Is it going to be USDC? Or you have your credit card on file. The user wouldn't be required to pay it. The service provider would.
Starting point is 00:22:48 So the service provider in the background would be... No, no, no, no, no, no, no, it's not going to work because this is the problem. Because micro payments or Visa MasterGar, there's like a 30 cents charge minimum per transaction, you can't do micropayments. When machines are doing millions or hundreds of queries across different vendors for different people, it doesn't work. No, no, but for a new startup to buy, you know, $500 a month in credits, like I pay now, I have my credit card on file at OpenAI to use the sandbox.
Starting point is 00:23:18 and my whole team has access. And as they do stuff, it just starts building us. And then I reconcile at the end of the box. So that's what I'm saying. That's what I'm saying. The new startups that want to leverage this,
Starting point is 00:23:31 they would be paying as they go, just like they play for cloud storage, they would be paying for access to pools of data. And we could build an infrastructure behind the scenes, which had GPT4, your credit card on there
Starting point is 00:23:44 that bought a thousand credits, you know, $1,000, they would just handle the microcontractors. payments in the background and every month reconcile them. So across startups, but for consumers, it would be different. Yeah, okay, so that's assuming that when the, that they, that open AI would have deals with all these data providers, for example. So Nick, you'll pull up my tweet quickly.
Starting point is 00:24:06 So I put this out a week ago. And, you know, everyone's been going on about Web 3 being, you know, web 3, like, being crypto. Maybe it's not crypto. It's AI. Like the next evolution of the web is actually AI and not crypto. Crypto may be a sub-segment of it, like the payments rails or whatever. But the Web 3 isn't about decentralization.
Starting point is 00:24:29 Web 3 isn't about these things, which, you know, I guess we've created this whole notion that we think it is. Maybe it's just the web evolves. And instead of using Google search, using chatypt, using AI tools. I think this is right. Most people, we've had three Web3 so far. The semantic web people claimed was Web3. Yeah.
Starting point is 00:24:46 Crypto, they claimed it. and now AI's claiming it. And actually, I think some people in the VR space were kind of trying to claim Web 3.0. But I think maybe third or fourth time is a charm here. Go ahead, sending you had something to say. Well, let's combine a couple of ideas here. And this kind of brings a podcast together. So I think someone, both of you guys know, is Grimes.
Starting point is 00:25:06 Yep. Right. And yesterday Grimes put a tweet out. Maybe Nick can find it is quite easy. That said, she is willing to split royalty 50-50 with anyone. that does an AI remix or whatever the right term would be called. A.I.
Starting point is 00:25:23 Like even a new track. You could create a track with her voice. You could write the lyric. You can do the beats, whatever. This is a tweet. Exactly. Yeah. So this is it right here.
Starting point is 00:25:31 And she says, I'll split the royalties 50-50, which anyone that uses her voice. And the voice will be, you know, through one of these AI tools, right, that allow, you know, we've seen the Drake one and a whole bunch of these other ones now recently. So in order for this to pull off,
Starting point is 00:25:45 now, Vinny, I'm going to throw it back to you, right? What is the best way for her to pull this off leveraging. Obviously, there's an AI aspect of this, which does the voice. But how does this all reconcile in terms of payment and tracking and everything else? Because I think you'll have a really good answer here. Okay. So, interesting.
Starting point is 00:26:04 I'm actually messaging my friend right now because he is a very famous DJ and he's going to do something with this. And I don't want to say who he is yet, but he looked at this tweet and he was like, like I was changing team yesterday and he basically is going to take Grimes's voice and remix it into whatever, some DJ track and then do the 50-50 royalty with her. And he's a, he's a big name DJ. He's like maybe not, maybe not tier one, but different tier two. And so I thought that would be really, really interesting. And, you know, I think that's that's what it needs. It needs, it needs another high profile. Like, I don't think that some guy in a basement is going to remix Grimes and create this amazing track
Starting point is 00:26:47 of them. Maybe if enough people do it, it'll happen. Well, no, that's totally possible. Yeah. It's certainly possible. Oh, no. If a thousand songs come out,
Starting point is 00:26:54 five will be. Sure, sure, sure, sure, sure. I mean, who's produced a thousand tracks in a year? This is going to be a thousand Grimes tracks out next month. Yeah. 900 are going to be terrible. Exactly. A hundred are,
Starting point is 00:27:05 of the hundred that are left, they're going to be good, greater bangers. But I'd be betting on the, I'd be betting on the DJ with a big name of an existing, with an existing audience to go, this is amazing. It's amazing. Exactly. Exactly. So that's my point. Like, someone, I know an artist in the basement. Might make a good track, but no one's going to know about it. If there's a thousand others, they'll be drawn up by the noise.
Starting point is 00:27:23 Unless Grimes retweets it. But maybe, maybe. Or she adds it to her catalog on Spotify. Like, if she uploads it by Dishro Kid to her Spotify, then that would then, she would be managing the royalties. And it would be official. It would be on her Spotify and the, you know, whatever they call those playlists, like this is Grimes, this is the Rolling Stones.
Starting point is 00:27:43 Like, she could actually feature it. if she approves it, if it hits that sort of level. But you were asking, Sunny, the question of how should these royalties be done? And she answered that. She said she wants to do contracts, smart contracts. Well, yeah, well, that's kind of what I'm saying, is the smart contracts for that, right? So when you create it so that no one else can rip yours off, right? I think that's where it kind of intersects back with the blockchain.
Starting point is 00:28:06 And someone says, this smart contract, this token, this is the version that I created. And here you go, right? Okay. This is the tweet. Talking with my team, if you're interested me, music with us. We can collect and pay out royalties direct to anyone who uses AI Grimes vocals using smart contracts. The future really is now. This is so cool working on a way to register and easily access vocals through elf.tech. So yeah, it's going to, I mean, brave new world.
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Starting point is 00:29:56 Start saving your startup some money. Apply for Notion.com slash Jason. At the same time, our bestie, Chumath, wrote a blog post and in his blog post, he basically, it's basically a rehash of what he said on the All In Podcasts, nothing actually new here, but he basically says, these are the main arguments against regulating AI and why he disagreed with them. It's premature to regulate something that barely exists. And he writes, mark these down as famous last words, while it's admittedly early in the life of AI and generative pre-trained Transformers progress is compounding out of rate. That's measured in days.
Starting point is 00:30:40 take that first one. Do you agree? Where do you stand on this? Chimot's positions or that it's premature? Regulation or free markets right now? Got to pick one? I'm for free markets. Fannie I'm the same. I think it's premature to try to regulate this right now because all you're going to do is you're going to stifle the range of potential end results that we could have. It's better to like run all the experiments, see what works, see what doesn't work, regulate the stuff that doesn't work, then to prevent, then they put regulation in and prevent the good stuff from ever coming in the first place. Because some of the good stuff may be really good for society. That's my take. And if I can just add to what Vinnie
Starting point is 00:31:22 just said, like, you know, some of these, the comments are interesting, but, you know, AI in different forms have been around for a very long time used by a number of companies, whether it's drug companies to create, you know, compounds, right? You know, deep mind years ago, you know, solved one of those protein folding problems. And there wasn't a problem. I think the issue that we have today and where I struggle with terms of Vinny's point there is like, what is the scope of it? Are we now saying this applies to machine learning, right? Because that's been around for a long time. Does it reply only to generative AI? Does it only apply to a generative AI that comes out of things that leverage transformer technology? How do you, where do you bound it? Right. There's a
Starting point is 00:32:04 definition that, you know, what is self-driving as but one example. Is self-driving, adaptive, of cruise control lane guidance or full self-driving, they're having that discussion there as well. And, you know, my position on full self-driving is, if it's a beta and you agree that you have to be paying attention, and they have a camera on the inside that's watching your eyes, and it shakes, like on my full self-driving beta, I am now at four strikes out of five.
Starting point is 00:32:31 And I am super vigilant. And I got all four strikes for the same reason, which is looking down at my, phone, but my navigation and it just, I didn't realize how sensitive it is. Oh, no, actually a couple of times it was also because the steering wheel. So there is self-regulation that needs to occur. I think self-regulation is the way to go here. So I'm going to.
Starting point is 00:32:50 Well, let's just add to that, Jay. I think when you say self-regulation, it doesn't mean that the industry regulates itself necessarily. It also means regulation by enforcement, too. So what I mean by that is, I'm actually very interested to see what happens when all these artists and people who provide data to these AI tools go and sue and go and run lawsuits and run us through the legal process. That's how we got DMCA.
Starting point is 00:33:18 That's how we got a lot of the sort of foundational laws for the internet was based upon litigation. So let's test our assertions of freedom. Let's test our assertion of creativity and IP and ownership, et cetera. And let's see where the courts lie because it's pretty point. I have a counter to that. I have a counter to that. Okay.
Starting point is 00:33:36 Go ahead. I understand your position, which is there are existing laws. You're taking the our existing laws position. People break the law. It's on them. And that is completely true. So if a new type of gun comes out and it shoots 100 bullets a minute, and, you know, instead of one bullet, you know, if he shoots 100 bullets a second versus one, you're like, hey, well, the person did the murdering. But then we did say, you know what, we're going to have some limits on magazine size in certain states.
Starting point is 00:34:04 we're going to have waiting periods in certain states. We actually did look at some of the nuance. And machine guns, automatics were not allowed, right? And so when we look at AI, I would encourage people to think, well, what is the equivalent of the automatic weapon versus a weapon that is, you know, you have to pull each time in order a semi-autil? A standard rifle, or just a rifle. Standard rifle, et cetera, and the magazine size.
Starting point is 00:34:28 So, you know, that is one way to look at it. Another way to look at it is the MPAA. hey, people are taking their families to the movies. What's a way for us to let people know, hey, somebody's going to be murdered in this way, in a comic book way, or in a horror sense where they're literally going to be decapitated and it's going to be blood everywhere. One's going to cause nightmares. And one is going to be a comic book killing where somebody turns into a pile of dust and
Starting point is 00:34:51 you don't see anything, right? These were common sense things. Some of them became laws. Other ones were done by the industry. I think the people who are providing these services, will need to start thinking about people being registered to use these services and audits being done on what they're doing. Now, audits are being done right now on what you do on AWS. If you want to steal movies and put it on an AWS cloud, you will get caught, right? They're fingerprinting
Starting point is 00:35:19 stuff. There's a fingerprinting system for child porn on AWS, right? I don't know what that's called, but Google has and they've sort of looked for horrible things. I think here, the AI companies should start thinking sooner rather than later about the auto GPTs because I could see a scenario where somebody sets an auto GBT up and I brought this example up on all in where it would start hacking people in a very personalized way. So instead of just asking people to log into Gmail, it could be let me find your friend graph, let me write personal notes based on tweets that you shared with somebody and automate a million fishing attacks
Starting point is 00:36:03 as but one example. How do we have the platforms think about that, Sunny, and self-regulation? You heard Vinnie's let the laws handle it. You heard me give some examples of self-regulation. Where would you land after hearing those two descriptions?
Starting point is 00:36:19 Well, you know, I again, just put my technology as a hat back on and I go, look, anytime these things happen, you have to fight the technology with more technology. So I think for every AI that will, you know, potentially exist to do something that's harmful, there'll be AIs that are there to protect you. And we have those now, right?
Starting point is 00:36:40 Those are the things that run in our spam filters and, you know, on our phone. You know, I don't know if, you know, Apple has something that runs on your phone even without your permission for child pornography. Yes. That they report if, you know, you take those pictures and they end up in your photos. Which I think they were, the scanning of people's personal clouds, they stopped doing. People felt that was too intrusive,
Starting point is 00:37:06 but if they put it in the cloud, maybe they did, I'm not sure where they wound up. They do it on device. Yeah. But coming back to that, Jacob, that's technology,
Starting point is 00:37:14 that is using AI to, you know, combat bad things that people are doing. And so I just come back to, there'll be a set of companies that are out there combating the auto GPDs that are trying to hack people,
Starting point is 00:37:28 and write fake reviews to sites. So I think it's just going to be even a larger technology battle on both sides, which we've seen. So for every spam originator there is, there's multiple companies that fight spam. There's multiple companies that provide firewalls, right? Like there's, I mean, you probably even had them as sponsors at some point, J-Cal, right? They're very standard in airports and stuff like that. And so sort of just the way the technology cycle works. Let's talk about another argument that Chimoth heard and that he rebuts in his blog post.
Starting point is 00:38:01 Government doesn't have the credibility or track record to effectively regulate technology. He says, experience suggests the contrary. In a well-regulated industry like drugs and pharmaceuticals, for example, the Food and Drug Administration, they maintain a tight hold over what can be sold in order to ensure safety of customers. So do we believe the government analogy here for the FDA is analogous? to 100 million people using chat GPT. I think there's a scale issue here. What do you think, Vinny?
Starting point is 00:38:32 Yeah. No, I was going to say, I think it's a scale issue. I think the government can properly regulate anything they want to. It's just a matter of can they keep up with the pace of the innovation. I think here's the problem, J. We're at the bottom of a very, very steep slope that's approaching for the amount of change and disruption and whatever else that's going to happen, AI. And when regular start trying to do stuff now,
Starting point is 00:38:58 or like the government starts looking at it now, by the time they take stock of what it is today and try and process it and figure it out and create a law, the shit's changed so much in the next six months, 12 months, they have to start from scratch again. So, you know, that's another good argument from my side, why I think it's just, you know, government just needs to sit back.
Starting point is 00:39:17 I don't think they can do much. The other thing is we're also hitting, you know, computational constraints. I mean, all the big cloud providers are hitting the wall with GPUs, running the models, the training models, etc. That's an extraordinary point you're making, Vinay. You know, when's the last time we saw technical constraints in our industry? It was dial-up speeds.
Starting point is 00:39:40 Yes. Oh, and storage costs. And storage costs. And storage costs, right? So those were the last two massive hurdles. And then before that, obviously, there were some CPU, GPU issues. of running a movie on your laptop, right? Yeah.
Starting point is 00:39:54 So we had CPU, GPU issues in the 80s and 90s. We had bandwidth issues in the 90s. Those went away in 2000. We had storage issues up until Dropbox, which would be 2005, 2010. We saw storage. Yeah, 8 to 10, yeah. Yeah, YouTube and Dropbox and Box were companies that were built off. I mean, it was, storage becoming free or close to cheap.
Starting point is 00:40:18 So for me, it was the speed of, connection, then it was the cost. You remember, like, it was very expensive and slow in the beginning. And then the storage, like, just streaming, watching YouTube, et cetera. Even, even like Netflix, they were spending so much money on, at one point on losing money back in the days on the cost of just streaming, right? Now it's, now it costs nothing to stream. Like, you can download, I, like, I download 80 gigs for a modern warfare update.
Starting point is 00:40:44 So here we are again, though. Here we are again with a constraint. A big constraint, which is these. NVIDIA, what do they call them, G100s or something? Well, no, not just G100s. A100s? Yeah, it's not just... A100s, sorry.
Starting point is 00:41:00 It's not just those chips. It's any, it's any, like, we have a shortage of GPU, GPU compute power across generative AI in AI. There's lots of different chips. My point is like, not just AI chips. We just have a GPU shortage that's emerging worldwide. If something has to happen to TSMC, Taiwan semiconductors, okay?
Starting point is 00:41:23 If China and America go to war with Taiwan and whatever, if any of that stuff happens in the next 12 to 18 to 24 months, we're going to be screwed. We don't have enough compute power. We're not going to be able to make pictures of David Sachs as Batman. I'll give you the other side of that, though. Okay, here we go. You know, I started my career in semiconductors.
Starting point is 00:41:43 And so the cycle in semiconductors is only two years. So at any given point to get to the late, latest and greatest technology, it's only ever two years away. Well, you have to have a fab up, right? You can't, you can't not have a fab. Yeah, but, but, but those things have existed in the U.S. for a long time and they can, they can fire those back up, right? And so to get, like, to get to fab capacity of the latest technology, it's just, it's always just two years away. And the companies that provide all the technology underneath to make that happen are all, you know, mostly American companies as well, like applied materials and whatnot, right? And so I think you can't
Starting point is 00:42:21 fight it right away, but given that this rhetoric's been happening for the last year to six months, I think we're only, you know, six to 12 months away from having, you know, start having start of capacity ourselves. Well, well, my Amazon, I think I saw was actually building their own competitive chip to the A100. Well, and Elon at Tesla is building his own, you know, platform as well. So, you know, when you have constraint, it leads to even more innovation and more players going after this. I've never seen, you want to talk about things moving quickly.
Starting point is 00:42:53 I mean, when did we ever see the government push through a regulation and a spending bill at the scale of the Chips Act? They are in full-scale panic mode over the possibility that we could have chips be constrained because of this Taiwan situation. And one wonders if the pace of AI combined with, you know, the availability of chips is actually pushing this issue onto a different, timeline, we're seeing a geopolitical and just letting this sink in for a second. We're seeing in geopolitics the possibility that a war over a constrained chip set for AI could be the next world war. I mean, I don't want to sound like hysterical facts. No, no, it's very possible, Jackal.
Starting point is 00:43:43 In fact, I would actually say that it's more likely than not because what's going to happen in the next. So it goes back to my revenue destruction transference argument. The moment we start seeing revenue moving to startups from traditional companies, and then these companies, which are at scale, have to implement AI and need the GPU compute power on there and have it. Like, this is where the choke point comes in, right? Right now, the people using AI by and large, and tell me, telling you, I know, you're
Starting point is 00:44:11 more on the ground and services go these days than I am. Like, it's not, it's a, it's a cottage industry of startups and small enterprises. It's not the big guys, right? Mm-hmm. No, it's, it's everywhere. Like, I'll find it here, like, you know, Morgan Stanley just put a little presentation out earlier today. I'll find it and send it in the chat in a second.
Starting point is 00:44:32 It's all over the place. I think, are they deploying at scale? My point is, are they deploying in, like, is infer, like, inference, for example, you know, with these models, like, are they running, like, are they running it at a high enough capacity or utilization that it's going to cause a strain on the GPU infrastructure that they've got. I don't think so. I don't think it's there yet.
Starting point is 00:44:54 Oh, I mean, we saw it with Azure. I mean, they, when they're limiting chat GP4 searches if you have a paid account to 30 every couple of hours. 25. Yeah. So, I mean, if they're throttling it, there's a reason. And I think the reason is this system, these systems are being pushed to the brink because of so much innovation.
Starting point is 00:45:14 But we'll catch up. I mean, this is not the first time. What I'm saying is, like, the corporate America hasn't fully adopted AI yet. We're talking about maybe maybe one percent. Maybe if that, the rest are all sitting on the sidelines. And the moment they need to, where's the compute power going to come from? We don't have enough GPUs out there. I told everybody in all my companies, with the two companies I'm running,
Starting point is 00:45:38 to get on chat GPT4 to expense the $20 a month. And I invited everybody to get on the playaround at my investment company. I gave every one of them access to my credit card account back thing. And I said, I want everybody to do every job you have, start with a chat GPT forester, and then go and back and do your job, and then report back with screenshots. And I'm deadly serious about it. If anybody on my teams, you listen to the pod, if you're not using chat GPT4 every day and testing it on everything you do, you're not going to last at a company I work for, period, full stop.
Starting point is 00:46:10 That would be like showing up to work without a computer. You show up to work for me without a chat GPT4 window open, you don't work for me because that's how much I believe this is going to transform stuff. And as but one example, you know,
Starting point is 00:46:24 we're raising this fourth launch fund and I was like, I wonder if there's LPN institutions I don't know and we're having this angel summit. I was like, let me invite 20 LPs to come to the summit
Starting point is 00:46:35 to balance out all the VCs who are there and they like to meet VCs and VCs of course like to meet LPs. So I start pulling up lists and I start doing a chat GPT, I put it in a table, and then I open up my window over at my sandbox, and I say, hey, for this foundation I've never heard of,
Starting point is 00:46:51 can you give me the Twitter URL and the LinkedIn URL of anybody who has the word partner, you know, in their thing? And it, of course, knows LinkedIn, I guess because Microsoft and chat GPT and Open AI are so connected in the own LinkedIn. And then I got the table. I was like, this is a research project that I would have spent thousands of dollars and weeks on
Starting point is 00:47:10 and it's done instantly. Now, I don't have auto GPD and I'm not a developer yet. And one of the guys from OpenAI told me they'll put my account on the plugins. But I'm going to plug this in to my Gmail or Zapier or something. And I'm just going to send a chat GPT message that says, Dear Blank, this is my AI. It's Jason Calacanis. This is my AI coming from my real address. I asked my AI to tell me people who might be interested in coming to the angel
Starting point is 00:47:41 summit, I see you're connected to these other speakers who are already coming here. If you're interested in coming, let me know. And if you hit reply, you'll actually get the real Jason. This is Jason AI. How hard is that last piece to do, Sonny? Because I'm not a developer. You know what? J-Cal, we should just do as an experiment.
Starting point is 00:48:01 We can sit down for three hours and do it. And three hours would be a stretch, right? It's all doable right now. All right. I'll come to your office on Saturday by your lunch. be cool to hang out. I mean, I was just thinking, I want to be a developer again.
Starting point is 00:48:15 That's how inspired I was by this. I was like, if I do this, that's literally a full-time job at my company. I don't have to hire. Because I was thinking of hiring somebody to do relations.
Starting point is 00:48:24 I don't need somebody to do relations. If I've got this AI out there doing this for me. It's 10x J-Cal. That's what you get. It's a 10-X J-Cal networking. Yeah. It's pretty nuts. This is why I think the benefit's going to accrue to
Starting point is 00:48:39 the startup world at a much higher rate than big countries. Because if you have, we have, I think, eight or ten engineers, if I can ten X debt, I've got a hundred percent an effective team, right? But you, you know, a company with 10,000 engineers, what do you do with
Starting point is 00:48:55 100,000 engineers? You can't do this. You know what I'm saying? They start laying 10,000 people off. Exactly. Exactly. Which is why Zuckerberg just did, did he do a third riff? Did I read that correctly?
Starting point is 00:49:07 He did like, he did 10, 10, and then another four? Four, yeah. Wow. 24,000 and a hiring freeze. He's getting fit. And people are, see, this is the thing about the sky is falling. You know, people are saying, we're saying, as technologists, the sky is falling. And that we're overreacting.
Starting point is 00:49:29 When people say we're overreacting, and I explained to you the story of running a venture firm and that I was going to hire a human being to meet with LPs for me, potential LPs and invite them to events and try to build relationships with them. And I, in an afternoon, as a non-developer, figured out, hey, I can get halfway there. And Sonny as a developer or any other developer hire could get me the other three hours there. And I 10xed myself, I don't need to hire that person. Anybody hearing my voice and hearing that example should be thinking about their own job
Starting point is 00:50:02 and how much code it would take to rewrite and automate their job. I mean, just speaking of code rewrites, you realize you could, you can get give an entire code base to open AI and say, rewrite it in a different language or rewrite this, you know, or clean up the code and write it better, remove all the bugs, like scan for vulnerabilities. Like, this is what makes a 10x developer. Like, you can just basically, with very little coding knowledge and experience, you know, as a junior developer, you can do the stuff that senior developers do because this thing is doing it all for you.
Starting point is 00:50:33 It's quite amazing. Yemi times, like, I mean, microservice architecture has changed the way we do development over the years. But 20 years ago, migrating from one stack to another was, it would take months to rewrite the code. You could, you know, now it was just like, we open up an API and the system's talked to each other. But remember those days, Sunny, it was insane. Like, using JTM, you know, Java, JTME and, yeah, like, whatever, like, whatever stack you were using. It was a joke.
Starting point is 00:50:58 Have you guys used shared GPT where you can kind of share your thread? Share your prompts, yeah. You share your prompts and the whole thing. I find that super fascinating. And so I basically shared it on Twitter and I asked people like what they would change. I had so many different developers contact me like, yeah, I can take this to the next level for you. And I'm like, wow, this is super powerful.
Starting point is 00:51:16 Sonny, you also shared with me in the group chat a link to an open source chat GPT competitor. You referenced it earlier. What's the name of it? And how close is it to, why should we care? How close is it to chat GPT 3.5 or 4? Yeah. I'm not in a position to kind of benchmark it
Starting point is 00:51:38 because it literally just released a few hours ago. So Hugging Face is actually like a platform where they collect lots of different machine learning models and beyond just AI and the way we've been thinking about it the last few months. And so they've launched something, I believe it's called like Hugging Face GPD or something, like a chat, let me pull up the exact name.
Starting point is 00:52:03 And why this is important, it goes back to some of the origins around what people have been talking about with respect to safety and transparency. So it's an open source model. Everything is open. And so we can see how it's been trained. We can see how it operates. We can see the code for it. And goes back to your friend Elon and why he named OpenAI, OpenAI,
Starting point is 00:52:26 was meant to be open for the safety and benefit of humans, right? And I had shared a tweet a few minutes ago with Nick, if you want to pull up that one where it kind of intersects this part of the conversation or previous one where he goes on about like people just don't understand sort of the power of, and this is where I kind of a little bit of a different view from Vinny is that the AIs are already powerful because folks like Elon who've been thinking about this a long longer than any of us are already saying it. And so, and he's like right on. Like I've seen a few technology develop but none with this level of risk. And, you know, smart humans have trouble imagining
Starting point is 00:53:05 something that's vastly smarter than themselves. And I think he's gotten to the point and maybe, you know, Jake, you can comment here where he believes that these things are already smarter than us. I was having these conversations with them 15 years ago. When superintelligence, that book came out and Sam Harris, myself and Elon,
Starting point is 00:53:26 were talking about it over dinner. And Sam Harris was new to AI. But Elon was absolutely convinced because what people don't know is Elon was on the board of in a major investor in DeepMind, he begged the DeepMind company to not sell to Google, to remain independent, he offered them the funding,
Starting point is 00:53:42 and then he wound up giving Sam Altman the funding to try to make this open source version, to try to get the world to see what was happening, and make it open source, and of course, Sam decided to pull the old switcheroo and took what was the mission to be non-profit and open to for-profit and closed. That is a story that remains a mystery,
Starting point is 00:54:04 I think, to the world, as to what happened there. I have my concerns, if I'm being totally honest, that OpenAI is not sharing the source code. That to me is very much a tell. They said this technology is too dangerous to not have it be open source.
Starting point is 00:54:24 Then they said it's too dangerous to make it open source. What does that mean? What does that even mean? Does that mean they have discovered something that is really truly scary or they want to maintain a lead and make a huge profit off of it. You know, you could take the cynical Sam and the team just want to make a ton of money or you could take the virtuous and believe them, hey, it's too dangerous for people to have.
Starting point is 00:54:52 What do you guys think? I am struggling with this and I know Sam. I mean, we're not besties, but I know Sam relatively well. What's the actual motivation here? Is it capitalism or is it that they know something that we all don't, and they are scared to share it. The source code. What do you think? Occam's Razor? I would side with the,
Starting point is 00:55:14 I would side with, yeah, you know, Occam's Razor is like the most obvious answer. And the most obvious answer, in this case is maybe Musk's Razor, which is what he's saying, is that it's too dangerous.
Starting point is 00:55:24 And that's why. I would, you know, for someone that, like you said, has been around it a long time, really devotes his life to, you know,
Starting point is 00:55:33 expanding humanity. through lots of different ventures. This is one of the more important ones because there will be no reason to be an interplanetary species if some form of AGI ensures that we are no longer a species before we can get to the interplanetary stuff.
Starting point is 00:55:50 So I would decide with him. I'd go with the most obvious answer, which aside with him, he's been looking at it and thinking about it a long time. That's my... I mean, I'll have a slightly different take, Jeho. I think that... Okay, let me hear it.
Starting point is 00:56:01 Okay, let me hear it. Okay, you know, Occam's razor would basically, you know, for me, it would point to the fact that there's possibly, you know, ideological decisions that are made that they don't want to be public. So, you know, it's, it's the majority of the team decides that, you know, we don't want people to know that we're doing this or that. And that's the simplest explanation is that they don't want you to see what's, I don't think it's necessarily, oh my gosh, we've created a monster. I think it's just like we just don't want anyone to see the way we make decisions and... Therefore, they can make more money or have a more defensible operation.
Starting point is 00:56:42 For whatever the reason it is, it's just like we just don't want, you know, whether it's capitalistic. I wish they would tell us. I think this is where Sam needs to be a little bit more honest with everybody because he's been on this press store anyway. So just tell us what is the story between the nonprofit, for profit, flip. Maybe he's concerned about liability because I think they're... I'm going back to the Chimot's letter. like we could all, this is where the government could step in. Like they could have a hearing and it could be open or closed and they can ask.
Starting point is 00:57:11 Yeah. Yeah. I mean, I think this is so acute in terms of job disruption, disruption. I don't want to say destruction, but job disruption or competitiveness and chat, Open AI's lead that the government asking a couple of questions if Open AI is not going to be transparent about it, I think it's not a bad idea. And I'm not saying that because I'm kind of trying to cost trouble for them, but it's just too weird that they were open source and now they're closed.
Starting point is 00:57:38 No, it's again. They were for, they were non-profit and they're for-profit. It's just, I've never seen that in the history of our industry. Let's just assume, for argument's sake, this is starting in, in Florida and it was a Trump organization, and they were closed source. You know, and what would you assume if it was that? For profit. I think Trump only cares about profits.
Starting point is 00:58:02 Yeah. Do you think that, well, let's say it was Fox News as well. Let's say, so Fox News started an AI company. Honestly, I think Fox News is, the reason Fox News picks aside is because they realize that you're going to get more ratings. It's better to appeal to one side and get ratings. Knowing what I know about media, having spent my career in it, I know the exact cynicism of Fox News because they're a liberal when it comes to the movies and TV shows they're making.
Starting point is 00:58:27 And then when it comes to news, they are incredibly conservative because that was a great mode to make money. It's conservative versus liberal. So do you think the majority of people who work at Open AI are liberals or conservatives? Well, obviously liberals, but I think a bunch of them are libertarians too. But, you know, so in that vein. They're capitalists. Well, in that vein, in that vein, the question, I guess, is, are there, is there
Starting point is 00:58:54 a liberal, you know, agenda? No. I don't think this has to do with politics. I think there's a profit motive here. Maybe. It's either a profit motive or there's something in the code to your point that is either concerning or worth protecting. Gotta be one of those two things. But anyway, we're going to find out.
Starting point is 00:59:15 I just wanted to show this example. Here's the shared GPT I did. It's got 3,300 views. I shared it on my Twitter as well as internally. If you take a look at the shared GPT I did, you can pull it up, boys, producer neck. And you'll see, it basically gave me the LinkedIn. You know, and you can see, you know, I'm playing with it. I'm asking it to add more.
Starting point is 00:59:35 If you scroll down, you'll see, you know, me putting stuff in a table and then asking it for more and more endowments and doing the LinkedIn. But then when I went to the sandbox and I started playing with that, so here's the playground image. You know, this stuff is getting, this is when I think about, you know, like a research position or what people's entry level jobs are. You know, if senior level people can do this. And I just said, please give me the URLs of everyone with the word partner in their title at the Ford Foundation. That's a big endowment. Please provide URL for the LinkedIn page profile page on their website and the Twitter profile. I put that in a table.
Starting point is 01:00:12 And sure enough, like, here's a couple of people who work there and I got everything I need. This research that I'm demonstrating here is weeks of research. And I haven't glued this together to put it into a database or make automated emails yet. or DM them or at mention them. I mean, there are so much more I do here if I just knew how to write a little bit of code. You don't even have to write code. I want a code coach to teach me how to write code.
Starting point is 01:00:43 What is it, Replit? Would I do this in Replit? Is that the company or the platform I would use? To be honest, sure, yes, you can. And it's wonderful. But once you get plugins enabled, you can just do this all within the plugin architecture.
Starting point is 01:00:58 The kind of chat, GPT, interface. It can write code now and it can run it for you right there. Yeah. A senior level person at Open AIs told me they would send it to me. So I got to just, I don't know, maybe I got to log out and log back in and see if I... Oh, I have plugins. Thank you to my friends for moving me up the list.
Starting point is 01:01:23 I have plugins. Okay, well, I know what my afternoon is going to be. Like, if you're working at my companies and you're not using this every day. You might not be working for me for much longer because you got to level up everybody. I'm looking at this and I got to say, having come from, you know, the editorial background at inside.com, I'm trying to find a developer because I did summaries of newsletter stories that we do.
Starting point is 01:01:53 Like, you know, we kind of do bulletpointed news kind of summaries. And I would say the chat GPT4 ones were not great. But they were within 70%. And then I was like, well, compounding, that means it's going to be 110% this year. And so that doesn't mean I don't think we need the writers. What I want the writers to do is do a level of curation and insight on top of what Chachy Petit does. And so I'm just, it's got me inspired to think about so many different ways to,
Starting point is 01:02:22 you know, take the newsletter business, take the investment business and just level it up. Well, it's so crazy, JCal, think about this, right? Mahalo. Yeah. Human power search. But all of chat, you and Chad GPT could recreate all of Mahalo. It's crazy. I had 100 people working there.
Starting point is 01:02:40 10 million in revenue. You and just sitting in front of a prom could recreate an entire company from not that long ago. Yep. It's bonkers. And, you know, when I talked to Sergey about Mahalo and, you know, like this tiny competition, we might be at some point for Google. He said he really liked what we were doing. And Marissa also liked it.
Starting point is 01:03:00 and so did Megan Smith. They just thought eventually this would be done by AI. And I guess they were right. Eventually it would be. And here we are 15 years later. 15 years. What were the top five Mahalo pages? It turned out that I put...
Starting point is 01:03:19 Yeah, yeah, yeah. It's a great question. It was very weird. We had started to do some how-to content. So we were just, we were trying everything. We did coupon pages. Those were the highest monetizing. So we had said like that Beth and be on coupon, right?
Starting point is 01:03:33 And then we gave strategies for getting the coupons, pages that had them, how to get them, and then just some links and some content. Then we did pages on how to cook salmon. And at one point, how to cook salmon, we were the number one result in Google. It turned out a lot of people are typing that into Google, but it didn't monetize. Then I started making videos because people just wanted the answer of how to cook salmon. And so we just started adding more answers to the page. and you know, it was a very good lesson for me
Starting point is 01:04:00 because we built a Q&A system. We had built a wiki system after Wikipedia but before Cora. And, you know, the real issue was the business model. We were dependent on Google for search traffic. And then when Google saw that we were answering people's questions, they cut our throats. And, you know, I think that's the antitrust stuff
Starting point is 01:04:22 that, you know, a lot of us had to deal with. You know, EHOW, all the different two sites, wonder, whatever. What was the site? About.com that the New York Times owed. We all basically got cut off at the knees because Google saw us as a threat. And Matt Cuts lied to my face. We don't have partners.
Starting point is 01:04:38 And then I had the other side of the business saying we are partners because we're making $10 million in Google Anseds together. You know, when you start making $10, $30,000 a day in Google and cents, you can be sure you got a pretty good partnership going. And people were having me over to hang out at Google. And then Matt Cuts wouldn't talk to me. And so I emailed Sergey and I talked to Surga. and I talked to Surgay and I talked to Marissa
Starting point is 01:04:57 and I talked to Megan Smith and they're like, I wish we could help you, but, you know, the algorithm people, they don't allow anybody to talk to them. I'm like, you don't allow anybody to talk to them.
Starting point is 01:05:07 And they basically wouldn't give you an answer. So, hey, so good lesson for everybody. You can't have a dependency on any one company, whether it's Google or Stripe or, or, you know,
Starting point is 01:05:17 look at BuzzFeed and Facebook. Yeah. You know, BuzzFeed is like, I don't even know if that company is going to be here next year. Like, they're making two or three hundred
Starting point is 01:05:25 300 300 million dollars. I think the company's worth $100 million now. They just laid off the entire news team. Yeah, as soon as they didn't they just shut down? They shut down BuzzFeed News, but they still have like ballistic stuff, I think. So,
Starting point is 01:05:36 got it. But they were an SEO. They weren't SEO driven. They were social driven. So, oh, you know, you want to share this on Facebook and they would siphon traffic off for Facebook until Facebook was like, you know what? This content should live on Facebook.
Starting point is 01:05:50 Not your website. You know, so just do not be dependent on anybody. and I think that's, I think, why I think this is so inspiring for founders is that you're going to be able, my belief, well, I think we'll end on this one, is we're going to see a hundred times the number of startups. That's what I think's going to happen. I think this is exactly like when Y Combinator and Cloud Computing, Angel List, Open Angel Forum, My Syndicate, that moment in time, many more people could build something because you only needed five people. and a million dollars to build something because of cloud computing. And then it became,
Starting point is 01:06:29 well, you only needed like five people and 150,000. I think now you need two people and, you know, $25,000. Yeah. You know,
Starting point is 01:06:41 or $250,000. Which means like a very niche website or a very niche service, you know, an app for snowboarders, right? We use the app slopes, right? I think it's probably a couple of person team.
Starting point is 01:06:54 Yeah. There could be a version just for snowboarders. But nobody's taking the time to build that because it's only going to make $5 million in revenue. But if one person can build it and do customer support and everything, that's like a pretty cool business. And maybe 10 people can make 10 apps instead of 10 people making one app. So I think that we're going to see like a long tail of startups and incredible software products because of this.
Starting point is 01:07:16 I think this is going to create a revolution in startups. I couldn't agree with you more. It's already happening. It's already happening. Yeah. Yeah. The one thing that needs to flow is the revenues, right? So I keep hopping on that because otherwise it's just a, this is an expensive business. I mean, the costs of running these models, the GPU costs of running the stuff, even the open AI costs, it's not cheap. If startups is producing stuff that just moves, you know, bits and bites from one place to another and there's no money in the other end of it, it can be disrupted, but we have to figure out the revenue models first. All right, listen, you guys are amazing. I look forward to doing some coding with you, signing over the week. And,
Starting point is 01:07:54 Vinny, whatever music festival you're out next, I hope you enjoy that. You pop some great bottles while Sonny and I are actually getting work done. Well,
Starting point is 01:08:01 Sonny and I are popping some bottles to our nights. Oh, what? What? Is there bottle popping? You guys are going out? What a little Vegas trip?
Starting point is 01:08:09 Were you going out to see the Warriors in Sacramento? No, no. We're in Austin. Oh, thanks for the invite.
Starting point is 01:08:16 Thanks for the invite, boys. You're welcome. I guess I miss the invite. I need an invite. I need you to send a plane. I miss mind to the launch. well that wasn't my invite to get
Starting point is 01:08:27 I am I'm lucky to have been invited to the SpaceX team did you see the damage though we were supposed to actually as you mentioned that we were supposed to go tour it but we ran out of time and I had to get out of there but yeah I mean if you build the largest rocket
Starting point is 01:08:46 in the world it's going to leave a crater it's going to leave a mark but they have a my understanding from, I think, what's been publicly said, I always got to be careful here, is that there's a solution for that, that they have. He's done a pretty good job of highlighting, like, hey,
Starting point is 01:09:04 we were supposed to have this water-cooled thing, but we didn't think we needed it, but now we'll put it in. It's pretty cool. It was really inspiring, J-Cal. That was awesome to see. I, you know, I've lived a lot of life. I have, you know, been to the NBA of finals.
Starting point is 01:09:20 I have skied in Japan. And I, you know, I've done it all, I think, like, in terms of, I've done a lot in terms of human existence. It was, aside from the birth of my three daughters, it was the most intense experience of my life. Wow. Wow. So two births, three kids, we had twins. And then the launch of Starship would be the most intense electrifying experiences of my life. That's awesome. Pretty, pretty, I mean, what we saw, I mean, I think it was kind of like watching the course of humanity change.
Starting point is 01:10:00 The scale of this rocket is, I've, I mean, I've been to Star Base a number of times and I've been on the top of, of, um, there's a building where they build just the top part of the rocket, the starship, the actual Starship. Not the booster. Yeah. I have been up the freight elevator. to the top of just the starship. And I think, I don't know how many stories that is 30 or something. I mean, 40. And you're looking down at this rocket ship.
Starting point is 01:10:32 We're looking up at it. And it's like, whoa, the starship is a very large vehicle. And I have been inside the starship, like the cone of it, like maybe the top third of it. I've been inside where the payload is. And you're like, whoa, the payload area, it feels like the size of a house, it is not, it's, it's not possible to comprehend how large this thing is until you see a human or you've stood next to it. Yeah.
Starting point is 01:11:02 It does not feel like something that could, it feels as if the empire state building is going to space. That's the closest analogy I can give you. If you, if you stand at the bottom of a sky's breaking up and you just, yeah. And you look up and you're like, imagine that flying through the air for four minutes at whatever number, whatever speed it was going at. That's what just happened. The Empire State Building or something in that range. Yeah, incredible. Going to space.
Starting point is 01:11:31 I mean, it was bonkers. And you know what? He's been pretty clear, like, that's an old rocket. They got, you know, the next couple are ready to go. So, again, talk about compounding. He's compounding physics down there, let alone compounding AI. It's going to be pretty fantastic if he can stay focused. focused on that, you know, and really that team is dialed in. They are dialed in.
Starting point is 01:11:59 It was very impressive. You underestimate what you can do in the short term. They have to be the smartest engineers in the world to do what they're doing, literally. It's not just their intelligence, it's their motivation. It is incredible. When you go to Star Base, that is a citadel of technological achievement. It is like going to the Vatican or to a monastery. is not like anything you've experienced in your life. They are there to colonize Mars. So the vibes you get are crazy. I mean, here's a scale against a human.
Starting point is 01:12:34 And just to give people an idea if you'll listen, if you're watching, like, yeah, we see the human. Yeah, there's a tiny little human there, and that's just, and here we go. What does it cost to build this thing? It's actually not crazy, expensive. Yeah, I don't want to say, but I think they're going to, like the Tesla model Y, it's getting cheaper and cheaper, and it's reusable. the idea. So those arms are going to grip it when it comes back down. So they didn't even
Starting point is 01:13:00 attempt that. But just like they figured out maybe, I don't know, if it was 20 or 30 times into the Falcon, how to land them and how to land all the boosters and everything. They're going to be able to reuse these. And if they can reuse these and they can have, they could have these going up daily like they do with the Falcon. How often do you see Falcon launches? It's been 224 of almost like every day now, right? They do them. I don't know if it's quite every day, but I think there's been weeks
Starting point is 01:13:27 when there's been multiple. Yeah. So it's moving, I think, towards that pace. And that means payloads in space are going to be absurdly cheap. Yeah.
Starting point is 01:13:34 I think I read something, Vinnie, and like, ultimately they'll get it down like $20 million or something. What? That's nothing. Yeah.
Starting point is 01:13:40 Yeah. It's already changed everything. That's cheap. There's a house of Atherton, guys. Yeah. I mean, and you know what? If you're inside that tip
Starting point is 01:13:49 where the payload is, it's the same size. it's pretty much the same size of these outrageous homes in Atherton. All right. Great job, signing. Great job, Vinny. We'll see you all next time. Thanks.
Starting point is 01:14:00 On this week, service. Bye-bye.

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