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SPEAKER_02: 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 bi-weekly AI crypto roundtable. Sunny Sandeep Madra, the co-founder of Definitive Intelligence, and Vinny Langham, the co-founder of Civic and Wait Room. Welcome back to the program boys. Thanks for having us again, Sunny.

SPEAKER_09: Yeah. All right. There has been a lot of discussion about the phases under which AI will be adopted.

SPEAKER_10: Ram 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,

SPEAKER_13: three management leverage. You guys agree with this? And did you see this tweet?

SPEAKER_15: Yeah, I really liked this breakdown because what it, it, and it's sort of like inverse and it builds on

SPEAKER_16: 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

SPEAKER_17: about it, they probably think it's the other way around, but I, I really liked the way Ram laid it out

SPEAKER_23: here. Uh, Vinny, what are your thoughts? I agree. I know Ram. Uh, he's a good guy. He's very thoughtful about these things. Um, you know, he's very analytical as well. So look, I think the, the big danger is, uh, if we try and overanalyze and sort of constrain, um, what is happening to, you know, you know, like trying to create these categories and, uh, layers of what's happening where, quite frankly, it's just the wild, wild west. Who knows? I'm listening to go in a million different directions. It can upend all the norms that we would, 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 Chamath said as much in the all in podcast last week, uh, Jake, that you, you, you, you know, that you host, um, you know,

SPEAKER_24: he's having to rethink everything and it's a humbling experience. Yeah. I, I look at this and I think what

SPEAKER_10: we're seeing is smart people trying to build a mental model as to where this is going. Vinny, your point is well taken, uh, and Chamath a great example. He's one of the, you know, I would say one of the great strategic thinkers, uh, that we know, and people are trying to build a mental model of what is

SPEAKER_28: 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

SPEAKER_10: fact, uh, black swans perhaps. I, I look at this and when I do my, hey, here's three phases, which

SPEAKER_32: everybody seems to like to use the, the three phase approach. I'm not sure why it's not four or six.

SPEAKER_33: McKinsey. It's a McKinsey three. Yeah. Yeah. We can put them in circles. I don't know. Yeah. Odd

SPEAKER_34: number works better. You can charge more money per hour when you do this McKinsey thing. Um, I think about augmentation, which he points out human leverage engineers, 10 X thing, but I put augmentation for salespeople, SDRs, uh, writers, everybody in between. Um, and then automation where you're kind of taking some humans out of the process. And then finally, you know, after augmentation and this sort

SPEAKER_10: of automation is, you know, replacement or a deprecation. In other words, you, you just don't need certain functions anymore. Uh, shortly after they're automated. So some people might be watching

SPEAKER_28: the automations, which we saw with auto GPT, but maybe at a certain point, you're like, you know what? I can trust this thing. I don't need to have a 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.

SPEAKER_11: So what, what is your thought hearing those two things, Sonny, uh, about where this is going?

SPEAKER_41: Um, yeah, like I, I want to build on something that Vinny brought up last time. And I think,

SPEAKER_16: you know, we, we had a good discussion on it and I think it really, you know, good on Vinny to bring it up. And, um, a couple of days ago, you know, Samuel had a good, uh, Twitter post, uh, Nick, I just shared it in our chat, right. Which is actually a quote from Adam D'Angelo, who's, you know, one of the kind of the smarter minds, uh, in Silicon Valley, right. I'd be ex CTO of Facebook. Um, and it really aligns with sort of what Vinny is saying, what Vinny was saying last week, and just kind of building on that, which also aligns to that first point where we're seeing engineers who generally never felt this in technology. Um, and having, and I, I really liked the way he kind of phrased it is that, you know, every week there's new releases. And then because of that, he has every day 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, um, I wanted to spend it just a bit more time on that again, because, you know, last week we touched on it and it was, um, you know, we talked about what's happening, but to hear, you know, more people bringing that up is, 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.

SPEAKER_10: 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, Vinny yourself? Yeah. So I, I don't think it's moving

SPEAKER_51: that quickly right now. I think we still have a little bit of, you know, daylight, uh, between

SPEAKER_23: when that happens, like when the, when, when the machine becomes, um, you know, self-aware, singularity, then I think it becomes a little bit more, um, you know, a bit more, more, more, more of a, like I say, a smaller gap between, you know, the, the rate of change. So the rate of change

SPEAKER_56: will go up a lot more right now. It just feels fast for us, but I look around, you know, the big

SPEAKER_51: companies aren't freaking out. There's no huge M and a cycle right now in, 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.

SPEAKER_56: I mean, there are a couple of guys, you know, that's, I think the, the big catalyst for when things go parabolic, right? Um, when startups form that start eating the big companies lunches at a rate that they cannot digest or handle, that's going to be when we have this tipping point where everyone goes. Revenue destruction is what you're referring to. Revenue destruction and or transference, right? So, and, and I'll use my company as example, just because, right? So we are a video chat platform, a video conferencing platform. We're rolling out AI features. If people just start deciding to use us and we, we haven't started charging in, 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? 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

SPEAKER_51: are paying for it. We're not going to build that. We're not going to offer that. That doesn't make sense anymore because AI takes care of all these things. That's a disruption. I think that's coming.

SPEAKER_10: I think when you get to specific examples, it really opens people's eyes. In other words, there's zoom out there. There is, um, 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 have a weight room, but I'm assuming maybe a dozen people or something, you know, a company with 1200

SPEAKER_34: people, you know, now there's an offering with 12 people. And if they, you can charge it,

SPEAKER_49: you have a different cost basis than they do. Yeah. Well, exactly. Like for us, because we,

SPEAKER_51: we cut off video at about 10. Now we're busy changing it around, but like at 10, you know, let's say there's a hundred people on, on, on, on a call, everything else is audio.

SPEAKER_56: We're only paying for 10 video streams. Whereas with zoom, everyone has their cameras on and you know, they're busy, they're busy feeding the, you know, 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, that's not what makes us, I think, different necessarily. I think, um, for us, we're focusing on the AI components because we've, we've built out a feature roadmap that we're going to, you know, in the next 60 days, probably rolling out

SPEAKER_51: four to six features, which they can't do in the same amount of time. This is not possible.

SPEAKER_72: We're a team of less than 20 people. And so it's the feature. So right now I call it feature

SPEAKER_56: stuffing. Okay. Like you got to take products and services that have been built and you going up against the incumbents, you have to stuff it with features way, way faster than everyone else. This is what Zuckerberg did with Facebook in early days, by the way. Product velocity. Exactly. Product velocity. How many, how many sprints do we have in the next six, you know, 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 D'Angelo is saying, but I mean, when you're solving problems that already exist and you're just doing it in a better way, you know, I think you can overthink things a bit 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,

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SPEAKER_10: and founder university back to in person. I went to the city of San Francisco and I was in the pie die uh, and I had our accelerator class at, uh, Fenwick and west, uh, over in the five die. And then I had the founding university over at Wilson Sincini's office and a hundred people showed up for that.

SPEAKER_32: And then seven people in the accelerator. And the big topic of discussion was I built this using chat

SPEAKER_34: GPT, uh, or some other language model. And now 4.0 kind of includes it. And then are they going to just,

SPEAKER_28: are users going to be able to just go use chat GPT four instead of using mine? And we had a really thoughtful discussion. And I said, you know, this is exactly, um, sunny, the moment that happened in

SPEAKER_38: app development and you had a very famous app development company in Canada with hundreds of

SPEAKER_28: developers. If you built something that was of low value and easy to replicate like a flashlight app, like a calculator app, uh, those things were 99 cents. People bought them. There were, you know, uh, 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, a hundred thousand dollars or $250,000. But shortly thereafter, you had to make something thoughtful, uh, if you want to, and something subscription that people could kind of

SPEAKER_10: work on. And so I told folks, it was one, um, that was making a virtual travel agent. And I said,

SPEAKER_09: you know, there's things that chat GPT four can do, but there's this entire feature set that they're never

SPEAKER_28: going to get to and customizations, uh, 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? Sunny,

SPEAKER_10: the one I gave about apps in the app store. I like it, but I think there's one massive difference

SPEAKER_41: here. And again, this topics come up a few times, which is there is an element of having access to

SPEAKER_16: unique data when it comes to building something in and around AI. That's very important. 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, you know, 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 open AI as is the apex aggregator. So if it's anything that can be aggregated, it will be like, you know, the top of the food chain, right? The, the two racks, the, you know, great white, whatever you want to call it. Right. And so, um, I think Google index the world's information.

SPEAKER_41: Sure. But in, in, but what Google always promised to, to, and it continues to still do,

SPEAKER_16: um, 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. Uh, when open AI becomes the apex aggregator, they necessarily can, um, they don't necessarily have to drive traffic to you. They can connect to your API and they can, you know, 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 when that I didn't see that in mobile and, uh, you know, and that, that, um, kind of defensibility is much harder to achieve than it was in

SPEAKER_99: mobile. So let me, let me just like ask you, Sonny, what do you think about the, you know, the, the

SPEAKER_59: different, so, so open AI, yes. Apex, um, you know, what we call apex aggregator or aggregator,

SPEAKER_51: impacts language model. Yeah. Fine. So, so, so, but they're not the only one there's, 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 and maybe not the same development team when companies are busy building out, um, 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, like when you're building features, like we're building features, it's, 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

SPEAKER_56: a better product, we can switch across to it. So like, how do you think about that?

SPEAKER_17: Well, I think the ultimate pattern right now, at least that seems like it's going to play out is that

SPEAKER_16: you'll have like sort of a main, um, let's say LLM that you interact with and that LLM will have a series of agents that it interacts with. Some of those may be LLMs themselves, and some of those agents just maybe more traditional, you know, just pieces of software that interact with an API. And I think the, 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. You know, 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. And I think what's, what's quickly going to happen is, um, we're going to see a disruption. So kind of to answer your point, Vinny, um, 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 you know, if you look at where things are at today, there is a distinct difference, right? And we know, in our group chat, we were testing, uh, a quick example of one of these open source ones and, and Jake, how, 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, at it as open AI is.

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SPEAKER_117: I do think there's an opportunity here though, for a new business model, uh, back in the day,

SPEAKER_10: uh, in France, they had a little communication system before the internet where you could look up restaurants and it was called mini towel and mini towel. Uh, if you remember charged by the minute and it was an information service and you, uh, and, uh, CompuServe 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, Quora, et cetera, uh, Getty, Bloomberg and others, New York times, I'm sure we'll be right behind them saying to people like chat GPT for open AI, 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, uh, have a

SPEAKER_28: travel service that's built on chat GPT for, well, when I hit the plugins and I hit Yelp or I hit, uh, travel and leisure magazine or a blog about travel, whatever it happens to be in order to use that

SPEAKER_10: 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, uh, they can, and specifically through an A through an API call, I'm sorry, with the plug-in 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, re micro payments were built into the browser,

SPEAKER_120: right? It was just something brave has been trying to do and crypto tried to do and we should have had micro payments, but this could be an incredible new model that of course advertisers lose out of it.

SPEAKER_123: Did you see my tweet, Jay? No, I didn't. Is it parallel thinking? Yeah.

SPEAKER_126: Yeah. Yeah. I literally said, uh, I'll, I'll, I'll post a link here first, but, um, a couple of days ago, I think it was last week. I mean, perhaps it's obvious, but, uh,

SPEAKER_34: yeah, we just haven't had this business model ever licensing with something that existed before the internet. 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

SPEAKER_16: photos and the big ones. We have like a, we have a, uh, you know, a monopoly and 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. So the apple is, you know, further. It's like a bundle, right?

SPEAKER_135: You're kind of getting an aggregator, but what I'm saying more is you need micro payments though.

SPEAKER_51: That's the thing. So, so how do we, how is micro payments? It's like machines aren't going to pay with wires and bank transfers and checks. So, so it has to be a digital currency. Is it going to be a

SPEAKER_24: central bank digital currency? Is it going to be Bitcoin? Is it going to be lightning? Is it going

SPEAKER_34: to be USDC? Before you have your credit card on file, the user wouldn't be required to pay it. The service provider would.

SPEAKER_73: No, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no. It's not going to work

SPEAKER_56: because this is, this is the problem because micropayments or Visa Mastercard is like a 30 cents charge minimum per transaction. You can't do micropayments when, when machines are doing millions or hundreds of queries across different vendors for different people. It doesn't work.

SPEAKER_28: No, no, but for a new startup to buy a hun to buy, you know, $500 a month in credits. Like I pay now, I have my credit card on file at open AI to use the sandbox and my whole team has access. And as they do stuff, it just starts. No, no, no, no. That's what I'm saying.

SPEAKER_34: Reconcile at the end of the month. That's what I'm saying. That's what I'm saying is the new startups. Yeah.

SPEAKER_28: That want to leverage this. They would be paying as they go, just like they play for cloud storage, they would be paying for access to, to pools of data. And we could build an infrastructure behind the scenes, which had GPT for your, your credit card on there that bought a thousand credits,

SPEAKER_34: you know, a thousand dollars. They would just handle the micropayments in the background,

SPEAKER_144: uh, at every month, reconcile them. So, so, so, so, so that's, so that's, so that's, yeah.

SPEAKER_56: Okay. So that's assuming that when, 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. So I put this out a week ago and you know, everyone's been going on about web three being, um, you know, you know, well, web three, like it 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 subset, a sub segment

SPEAKER_51: of it, like the payments rails or whatever, but the web three isn't about decentralization. Web three isn't about these things, which, you know, I, I guess we've created this whole notion that we think

SPEAKER_59: it is. Maybe it's just that the web evolves and instead of using Google search, you're using chat

SPEAKER_153: GPT, using AI tools. I think this is right. I think, I think this is right. Most people, we've had

SPEAKER_10: three web three so far. The semantic web people claimed was web three. Yeah. Crypto, they claimed it and now AI is claiming it. And actually I think some people in the VR space

SPEAKER_28: were kind of trying to claim web 3.0, but I think maybe third or fourth time is a charm here.

SPEAKER_16: Go ahead, Sonny, you had something to say. Well, let's combine, 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. Yep. Right. And yesterday Grimes put a tweet out, maybe Nick can find it. It's quite easy. Um, that said, she is willing to split royalty 50, 50 with anyone that does an AI, um, like a remix or whatever the right term would be called AI. So like even a new track,

SPEAKER_74: use it. You could create a track with her voice. You could write the lyrics, you could do the beats,

SPEAKER_16: whatever. This is a tweet. Exactly. Yeah. So this is it right here. 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 how much these

SPEAKER_17: other ones now recently. So in order for this to pull off now, Vinny, I'm going to throw it back to you, right? What is the best way for her to pull this off leveraging? So obviously there's an AI

SPEAKER_16: aspect of this, which does the voice, but you know, how, how does this all reconcile, you know, in terms of payment and tracking and everything else? Cause I think you'll have a really good answer

SPEAKER_141: here. Okay. So interesting. I'm, I'm, I'm actually just messaging my friend right now,

SPEAKER_23: um, because he is a very famous DJ and he's going to do something with this. Um, uh, and I don't want to say who he is yet, but he, he looked at this tweet and he was like, I was chatting to him yesterday. And, um, 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,

SPEAKER_56: you know, maybe not, maybe not tier one, but different tier two. Um, and so I thought that would be really, really interesting. Um, 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 of them. And maybe, you know, maybe if, if enough people do

SPEAKER_169: it, it'll happen. That's totally possible. Yeah. It's totally possible. Oh no. If a thousand songs

SPEAKER_34: come out, five will be, sure, sure, sure, sure, sure. I mean, who's produced a thousand tracks in a year? There's going to be a thousand Grimes tracks out next month. Yeah. Um, 900 are going to be terrible. Exactly. A hundred, exactly. Of the hundred that are left, they're going to be good, greater bangers.

SPEAKER_72: But, but I'd be betting on the, I'd be betting on the DJ with a big name of an existing or with an

SPEAKER_174: existing audience to go. It's permissionless collaboration. Exactly. So, so that's my point.

SPEAKER_170: 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. Unless Grimes retweets it.

SPEAKER_176: At least, but maybe, maybe. Or she adds it to her catalog on Spotify. Like if she uploads it by

SPEAKER_34: DishroKid to her Spotify, then that would, then she would be managing the royalties and it would

SPEAKER_28: 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. Like she could actually feature it if she approves it,

SPEAKER_34: if it hits that sort of level. But you were asking. Yeah. Sunny the question of how, how should these royalties be done? And so she answered that she said she wants to do contracts, smart contracts.

SPEAKER_17: Well, yeah. Well, that's, that's kind of what I'm saying is a smart contracts for that,

SPEAKER_16: 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. And someone says, this smart contract, this token, this is the version that I created. And here you go. Right. Okay. Exactly. This is the tweet,

SPEAKER_10: talking with my team. If you register 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. Um, so yeah, this is gonna, I mean, brave new world. All right. You hear me raving about notion all the time.

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SPEAKER_10: And at the same time, our bestie Chamath, uh, wrote a blog post and, uh, in his blog post, he basically, he's, it's basically a rehash of, um, what he said on the all in pockets, 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 at a rate that's measured in days. Let's take that first one. Do you agree? Where do

SPEAKER_189: you stand on this? Chamath's positions or the it's premium, the premature regulation or free markets right now? Got to pick one. I'm, I'm for free markets, free markets. Vinny. I'm, I'm the same. I, I think,

SPEAKER_49: I think it's premature trying to regulate this right now because all you're going to do is you're going to

SPEAKER_56: stifle, you're going to stifle the, 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

SPEAKER_24: that doesn't work, then to prevent, then they put regulation in and prevent the good stuff from ever coming in the first place. Cause some of the good stuff may be really good for society.

SPEAKER_17: That's my take. And if I can just add to what Vinny just said, like, you know, some of these,

SPEAKER_16: 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, to create, um, 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, 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? Are we say, you know, cause 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, uh, things that

SPEAKER_17: leverage transformer technology? How do you, how do you, where do you bound it? Right. There's a

SPEAKER_199: definition that, you know, what is self-driving as, but one example is self-driving adaptive cruise

SPEAKER_28: 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 and I am super vigilant and I, I got all four strikes for the same reason, which is looking down at my, not my phone, but my navigation and it just, I didn't realize how sensitive it is. Oh no, actually a couple of times was also because the steering wheel. So there is self-regulation that needs to occur. I think self-regulation is the way to

SPEAKER_49: go here. So I'm going to, well, let me, let's just add to that. I think when you say self-regulation,

SPEAKER_51: 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, I'm actually very interested to see what happens when all these

SPEAKER_56: artists and people who provide data to these AI tools go and sue and go and run lawsuits and run it through the legal process. That's how we got DMCA. That's how we got, you know, a lot, you know, a lot of the sort of foundational laws for the internet was based upon litigation. So let's test, let's test our assertions of freedom. Let's test our assertion of creativity and IP and ownership,

SPEAKER_205: et cetera. And let's see where the, where the courts lie because it's, it's pretty pointless. I have a counter to that. I have a counter to that. Okay. Go ahead.

SPEAKER_34: I understand your position, which is there are existing laws. You're taking the, there are 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 a hundred bullets a minute and, you know, and, you know, instead of one bullet, you know, if it shoots a hundred bullets, a second versus one,

SPEAKER_28: we were 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. We're going to have waiting periods in certain states. We actually did look at some of the nuance and machine guns because 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,

SPEAKER_34: you have to pull each time in order, a semi-automatic. A standard rifle or just a rifle. A standard rifle, et cetera, and the magazine size. 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 is 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 you don't see anything, right? These were common

SPEAKER_28: 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, um, 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,

SPEAKER_10: right? They're fingerprinting stuff. There's a fingerprinting system for child porn on, uh, AWS, right there. Uh, I don't know what that's called, but Google has, and they've sort of look for horrible

SPEAKER_28: 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 GPT up. And I brought this example up on, uh, on all in, um, where it would start hacking people in a very personalized way. So instead of just, you know, 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 phishing

SPEAKER_120: attacks as but one example. How, how do we have the platforms think about that sunny and self-regulation?

SPEAKER_10: You heard Vinny has let the laws handle it. You, you heard me give some examples of self-regulation. Where would you, uh, land after hearing those two descriptions?

SPEAKER_17: Well, you know, I, I, I, again, just put my technologist hat back on and I go, look, anytime these things happen, you have to fight the technology with more technology.

SPEAKER_16: 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? Those are the things that run in our spam filters and, and, you know, on our phone. Um, you know, I don't know if, you know, Apple has something that runs on your phone, even without your permission for child pornography.

SPEAKER_217: Yeah. Right. That, that they report if, you know, you take those pictures and they end up in your,

SPEAKER_110: uh, photos. Which I think they, they were the scanning of people's personal clouds.

SPEAKER_221: They stopped doing that. People felt that was too intrusive, but if they put it in the cloud,

SPEAKER_222: maybe they did, I'm not sure where they wound up. They do it on device. Yeah. But, but coming back

SPEAKER_17: to that, Jacob, that's technology 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

SPEAKER_16: auto GPTs that are trying to hack people and, and, um, you know, write fake reviews to sites. And 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 were, 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 cow, right? They're like very standard in airports and stuff like that. And so here's sort of just the way the technology cycle works.

SPEAKER_10: Let's talk about another argument, uh, that Chamath heard and that he rebuts in his blog post. 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 a hundred million people using chat GPT? I think there's a scale issue here. What do you think of any?

SPEAKER_17: Yeah, I, uh, no, no, no, no, no, I was gonna say, I think it's a scale issue. I think the government

SPEAKER_16: can properly regulate anything they want to. It's just a matter of, can they keep up with the pace of the, you know, the innovation?

SPEAKER_49: I think, I think here's the problem, Jake. We're, we're at the bottom of a very, very steep slope.

SPEAKER_51: That's approaching for, for the amount of change and disruption and whatever else that's gonna

SPEAKER_56: happen to AI. And when regulators start trying to do stuff now, or like the government starts looking at it now, what they, by the time they like take stock of what it is today and try and process it and figure it out and create a law. This has changed so much in the next six months,

SPEAKER_51: 12 months, they have to start from scratch again. So I, you know, that's, that's another good like argument from my side, why I think it's just, you know, government just needs to sit back. I don't think they can do much. The other thing is we're also hitting, um, uh, you know, computational, uh,

SPEAKER_56: constraints. I mean, all the big cloud providers are hitting the wall with GPUs, uh, running the models, the training models, et cetera.

SPEAKER_28: That's an extraordinary point you're making Vinny. You know, when's the last time we saw technical constraints in our industry? It was dial up speeds. Yes. Um, 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? It would, so we had CPU, GPU issues in the eighties and nineties. We had bandwidth issues in the nineties. Those went away in 2000. Uh, we had storage issues up until Dropbox, which would be 20, 2005, 2010.

SPEAKER_247: We saw it. Yeah. 8 to 10. Yeah. Yeah. YouTube, YouTube and Dropbox work and box were companies

SPEAKER_205: that were built off of storage becoming free or close to cheap. So for me, it was, um, the speed of

SPEAKER_51: connection. Then it was the cost. You remember, like it was very expensive, uh, and slow in the the beginning. Um, and then the storage, like just streaming, watching YouTube, et cetera, even the, even like Netflix, they were spending so much money on at one point on losing money back in the days

SPEAKER_56: on the cost of just streaming right now. And now it costs nothing to stream. Like you can download, I, I, I download 80 gigs for modern warfare. So here we are again, no problem.

SPEAKER_189: Here we are again with a constraint, which is these Nvidia, what do they call them? G one hundreds or

SPEAKER_253: something? Well, no, not just you, I'm just like, it's a 100. Yeah. It's not, it's not just 100.

SPEAKER_72: Sorry. It's not just those chips. It's any, it's any, you know, like we, we have a, a shortage of

SPEAKER_56: GPU, GPU compute power across generative AI, uh, in AI, the lots of different ships. 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. If, if, if China and America go to war with, over Taiwan and whatever, if any of that stuff happens in the next 12 to 18

SPEAKER_72: to 24 months, we're going to be screwed. We don't have enough compute power.

SPEAKER_257: We're not going to be able to make pictures of David Sacks as Batman.

SPEAKER_17: I'll give you the other side of that though. Okay. Here we go. You know, I started my career in semiconductors and so the, the cycle in semiconductors only two

SPEAKER_16: years. So at any given point to get to the latest and greatest technology, it's only ever

SPEAKER_262: two years away. Well, you have to have a fab up, right? You can't, you can't not have a fab.

SPEAKER_16: Yeah, but, 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, to, to get the, 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 fight it right away, but given that this rhetoric has 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.

SPEAKER_56: Well, my Amazon, I think I saw was actually building their own competitive chip to the a 100.

SPEAKER_10: Um, well, and Elon at Tesla is building his own, um, you know, platform as well. So, you know, when you have constraint, it leads to even more innovation and more players going after

SPEAKER_28: this. I've never seen, you want to talk about things moving quickly. I mean, when did we ever see the government push through a regulation and a spending bill at the scale of the chips act,

SPEAKER_34: they are in full scale panic mode over the possibility that we could have chips be constrained because of the Taiwan situation. And one wonders if the pace of AI combined with, uh, you know, the availability of chips is actually pushing this issue onto a different timeline. We're seeing a

SPEAKER_45: geopolitical and just letting this sink in for a second. We're seeing in geopolitics, the possibility

SPEAKER_269: that a war over a constrained chipset for AI could be the next world war. I mean, I don't want to sound

SPEAKER_72: like hysterical. No, no, it's very possible. 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

SPEAKER_56: 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 and they don't have it. Like this is where the choke point comes in, right? Right now, the people using AI, uh, by and large and tell me, telling you, I don't know, you're more on the ground in San Francisco these days than I am. Like it's not, it's a, it's a, it's a cottage industry of startups and small enterprises. It's not the big guys, right? Uh, no, it's a, it's a, it's everywhere.

SPEAKER_16: Like, uh, I'll find it. Sure. Like, uh, you know, Morgan Stanley just, uh, put a little presentation on earlier today. I'll find it and send it in the chat in a second. Um, it's, it's all over the

SPEAKER_72: place. I think my point is, are they, are they deploying like, isn't like inference, for example,

SPEAKER_56: um, you know, with these models, like, are they, 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

SPEAKER_09: they've got? I don't think so. I don't think it's there yet. Oh, I mean, we, we saw it with Azure. I mean, they, when P they're limiting chat GPT for searches, if you have a paid account to 30,

SPEAKER_28: every 20, 25, 25. Yeah. So, I mean, they're, 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, but we'll catch up. I mean, this is happening. This is not the first time.

SPEAKER_72: It's what I'm saying is like the corporate America hasn't fully adopted AI yet. We're talking

SPEAKER_56: about maybe, maybe 1%. 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.

SPEAKER_10: I told everybody in all my companies, uh, or the two companies I'm running to get on chat GPT for to expense the $20 a month. And I invited everybody to get on the play around at my investment company. I had gave every one of them access to my, you know, credit card account back thing. And I said, I want everybody to do every job you have start with a chat GPT for, sir,

SPEAKER_28: and then go and back into your job and then report back with screenshots. And I'm deadly serious about it. If anybody on my teams, because they listen to the bod, if you're not using chat GPT for every day and testing it on everything you do, you're not going to last at a company I work for period, full stop. Uh, that would be like showing up to work without a computer. You show up to work for me without a chat GPT for 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, uh, you know, we're raising this fourth launch fund. And I was like, I wonder if there's LP and institutions. I don't, I don't know. And we're having this angel summit. I was like, let me invite 20 LPs to come to the summit, 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

SPEAKER_34: lists and, um, 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. Can you give me the Twitter URL and the LinkedIn URL of anybody who has the word partner, uh, you know, in their thing. And it of course knows LinkedIn, I guess, because Microsoft and chat GPT and open AI are so connected and they own LinkedIn. And then I got the table. I was like, this is a research project that I would have spent

SPEAKER_85: thousands of dollars and weeks on and it's done instantly. Now I don't have auto GPT and I'm not

SPEAKER_34: a developer yet with and one of the guys from open AI told me they'll put my account on the plugins,

SPEAKER_28: 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 is 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 summit. I see you're connected to these other speakers who are already coming here. If you're interested in

SPEAKER_239: coming, let me know. And if you hit reply, you'll actually get the real Jason. This is Jason AI. How

SPEAKER_09: hard is that last piece to do, Sonny? Because I'm not a developer. You know what, Jacob, we should just do

SPEAKER_41: his ex as an experiment. We can sit down for three hours and do it. And three hours would be a

SPEAKER_16: stretch, right? It's all doable right now. All right, I'll come to your, I'll come to your office

SPEAKER_34: on Saturday by lunch. Cool to hang out. I mean, I was just thinking, I want to be a developer again. That's how inspired I was by this. I was like, if I do this, that's literally a full time job at my

SPEAKER_301: company. I don't have to hire. Well, I was thinking of hiring somebody to do relations. I don't need somebody to do relations if I've got this AI out there doing this for me. It's 10x JCal. That's

SPEAKER_23: what you get. It's a 10x JCal networking. Yeah, again, this is, this is why I think the benefits going to accrue to the startup world at a much higher rate. Yes, I agree. Because if you have,

SPEAKER_56: we have, I think, eight or 10 engineers, if I can 10x that, I've got 100% effective team, right?

SPEAKER_174: But you precisely, but a company with 10,000 engineers, what do you do with 100,000 engineers,

SPEAKER_301: you can't do this? You know, I'm saying this, they start laying 10,000 people off exactly what you

SPEAKER_28: start doing, which is why Zuckerberg just did I did he do a third riff? Did I read that correctly? He did like he did 1010 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. Um, you know, people saying we're saying, as technologists, the sky is falling. And that we're overreacting. 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

SPEAKER_34: the other three hours there. And I 10x myself, I don't need to hire that person. Anybody hearing my voice and hearing that example, should be thinking about their own job, and how much code it would take to rewrite and automate their job.

SPEAKER_49: I mean, this is speaking of code rewrites, you realize you could, you can give an entire code base to open AI and say,

SPEAKER_23: 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

SPEAKER_51: for you. It's quite amazing. You hear me 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, knowledge is like, we open up an API and the systems talk to each other. But remember those days, Sonny, it was insane, like using JT, you know, Java, JTME. And yeah, like, whatever, like, whatever stack you were using, it was a joke.

David Friedberg: Have you guys used share GPT, where you can kind of share your thread or your prompts? Yeah,

SPEAKER_10: share your prompts and the whole thing. I find that super fascinating. Um, and so I basically shared it on Twitter and I asked people like what they would change. And I had so many different

SPEAKER_189: developers contact me like, yeah, I could take this to the next level for you. And I'm like, wow, this is super powerful. 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?

SPEAKER_137: So how close is it to you? Why should we care? How close is it to chat GPT 3.5 or four?

SPEAKER_16: Yeah, um, I'm not in a position to kind of benchmark it 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, you know, kind of beyond just AI and the way we've been thinking about it the last few months. And so they've launched something, uh, I believe it's called like hugging face GPT or something like a chat. Um, let me pull up the exact name 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, you know, go goes back to your friend Elon and why he named open AI open AI was meant to be open for the safety and benefit of humans. Right. And I had shared a tweet a few minutes ago with, uh, 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 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 lot longer than any of us are already saying it. And so, um, and he's like, you know, right on, like I've seen a few technologies develop, but none with this level of risk and, you know, smart humans have trouble imagining, um, something that's vastly smarter than themselves. And I think he's gotten to the point and maybe, you know, Jacob, you can comment here where he believes that these things are already smarter than us. I was having these conversations with

SPEAKER_10: him 15 years ago. Um, when, uh, super intelligence, that book came out, uh, and Sam Harris, myself, and Elon, um, we're talking about it over dinner and Sam Harris was new to AI. Um, but Elon was

SPEAKER_28: absolutely convinced because what people don't know is Elon was on the board of and a major investor in DeepMind. He begged the DeepMind company to not sell to Google, to remain independent. He offered them the funding and then he wound up giving Sam Altman the funding, uh, 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, um, Sam decided to pull the old switcheroo and took a, what was the mission to be non-profit

SPEAKER_144: and open to for profit and closed. That is a story that remains a mystery, I think, to the world as

SPEAKER_38: to what happened there. I am, I have my concerns, uh, if I'm being totally honest, that open AI is not

SPEAKER_34: sharing the source code. Um, that to me is very much a tell. They said this technology is too dangerous

SPEAKER_85: to not have it be open source. 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

SPEAKER_34: that is really, truly scary or they want to maintain a lead and make a huge profit off of it? You know, you, 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. What do you guys think? I, I, I am struggling with this and I know Sam, I mean, we're not besties, but I know Sam

SPEAKER_28: 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 the source code? What do you think? Occam's razor?

SPEAKER_17: I would side with the, I would side with, yeah, you know, Occam's razor is like most obvious answer.

SPEAKER_16: And the most obvious answer in this case is maybe Musk's razor, which is, it's what he's saying is that it's too dangerous. And that's why I would, you know, for someone that, uh, like you said, has been around it a long time, uh, really devotes his life to, you know, expanding humanity, um, through lots of different ventures. This is one of the more important ones because there'll be no reason to be an interplanetary species. If, uh, the, you know, some form of AGI ensures that we are no longer a species before we can get to the, you know, the, the interplanetary stuff. So I would just side with him. I'd go with the most obvious answer, which is side with him. He's been looking at it and thinking about it a long time. That's my, my, I, I, I mean, I'll, I was slightly different take,

SPEAKER_330: Jacob. I think that, uh, you know, Occam's razor, uh, would, would basically, you know, for me, it would

SPEAKER_51: point to the fact that there's possibly, you know, ideological, um, decisions that are made that they don't want it 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 simple, the simplest explanation is that they don't want you to see what's doing. 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

SPEAKER_10: way we make decisions and therefore they, uh, can make more money, uh, or have a more defensible

SPEAKER_335: operation for whatever the reason is. It's just like, we just don't want, you know, whether it's

SPEAKER_10: capitalistic. I wish they would tell us. I think this is where Sam needs to be a little bit more honest with, uh, everybody. Cause he's been on this press store anyway. So just tell us what, what is the

SPEAKER_28: story between the nonprofit for-profit flip? Maybe he's concerned about liability because I think

SPEAKER_41: they're going back to the Chamas 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.

SPEAKER_28: Yeah. Yeah. I mean, I think this is so acute in terms of job description, destruction, disruption. I don't want to say destruction, but job disruption or competitiveness and AI and, and chat GP open AI is lead that the government asking a couple of questions. Um, if open AI is not going to be transparent about it, I think is not a bad idea. And I'm not saying that cause I'm kind of trying to cause trouble for them, but it's just too weird that they were open source and now they're closed. No, it's again, they were for, they were nonprofit and they're for profit. It's just, I've never seen that in the history of our industry. If let's just assume,

SPEAKER_51: okay, for argument's sake, this was started in, in Florida and it was a Trump organization and they were closed source, you know, and what, why, what, what would you assume if it was that?

SPEAKER_297: For profit. I think Trump only cares about profits. Yeah.

SPEAKER_24: Do you think that, well, let's say it was Fox news as well. Let's say, so let's say

SPEAKER_10: Fox news started an AI company. Honestly, I think Fox news is the reason Fox news picks a side is because they realize that you're going to get more ratings. It's better to appeal to one side and get rated, knowing what I know about media, having spent my career in it. I, 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. And then when it comes to news, they are incredibly conservative because that was a great mode.

SPEAKER_51: That's my point. It's conservative versus liberal. Like, so, so do you think the majority of people who work at open AI are, are liberals or conservatives? Well, obviously liberals,

SPEAKER_147: but I think a bunch of them are libertarians too, but you know, so in that vein, capitalists,

SPEAKER_51: well, in that vein, in that vein, the question I guess is, are there, is there a liberal, um,

SPEAKER_34: you know, agenda? No, I don't think this has to do with politics. I think there's a profit motive here.

SPEAKER_28: 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,

SPEAKER_34: we're gonna find out. I just wanted to show this example. Um, here's the shared GPT. I did. It's

SPEAKER_10: got 3,300 views. I, I shared it on my Twitter as well as internally, but if you take a look at the shared GPT, I did, you can pull it up boys, uh, producer neck and, uh, you'll see it basically gave

SPEAKER_28: me the LinkedIn's, you know, and you can see, uh, you know, I'm playing with it. I'm asking it to add more. If you scroll down, you'll see, um, uh, 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, stuff is getting,

SPEAKER_221: this is when I think about, you know, like a research position or what people's entry-level jobs

SPEAKER_28: are, you know, 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. Uh, that's a big endowment. Uh, please provide URL for the LinkedIn page profile page on their website and the Twitter profile, put that in a table. And sure enough, like, here's a couple of people who work there

SPEAKER_10: and I got everything I need. This is a, this research that I'm demonstrating here is weeks of research. Um, 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

SPEAKER_28: write a little bit of code, I want to code coach to teach me how to write code. What is it? Replit? Would I do this in Replit? Is that the company or the platform I would use to, to be honest? Sure.

SPEAKER_16: Yes, you can. And, uh, it's a wonderful, but like once you get plugins enabled, you can just do this all within the, the, uh, the plugin architecture, the kind of chat GPT, uh, you know, uh, interface because it can write code now and it can run it for you right there.

SPEAKER_10: Yeah. I, uh, I, uh, senior level person at open AI told me they would send it to me. So I gotta just, I don't know. I mean, we gotta log out and log back in and see if I, oh, I have plugins. Thank you

SPEAKER_34: to my friends for moving me up the list. I have plugins. Okay. Well, I know what my afternoon's gonna be like, uh, if you're working at my companies and you're not using this every day,

SPEAKER_314: you know, you might not be working for me for much longer because you gotta level up everybody. I'm,

SPEAKER_34: I'm looking at this and I gotta say having come from, you know, the editorial background at inside.com I'm hire trying to find a developer because I did summaries of newsletter stories that we do,

SPEAKER_10: like, you know, we kind of do bullet pointed news kind of summaries. And I would say the chat GPT

SPEAKER_189: four ones were not great. Uh, but they were within 70%. And then I was like, well, compounding, that means it's gonna be 110% this year. And, uh, so that doesn't mean I don't think we need the

SPEAKER_221: writers. What I want the writers to do is do a level of curation and insight on top of what chat

SPEAKER_28: GPT does. And so I, I'm just, it's got me inspired to think about so many different ways to,

SPEAKER_221: you know, take the newsletter business, take the investment business and just level it up.

SPEAKER_17: Crazy Jake. I'll think about this, right? Mahalo. Yup. Human power search. But all of chat, you and chat GPT could recreate all of Mahalo. It's crazy. I had a hundred people working there.

SPEAKER_16: That's right. You and just sitting in front of a prom could recreate an entire company

SPEAKER_158: from not that long ago. Yup. It's bonkers. And, you know, when I talked to Sergei about Mahalo and,

SPEAKER_10: 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. And, um, so did Megan Smith. They just thought

SPEAKER_189: eventually this would be done by AI. And I guess they were right. Uh, eventually it would be. And

SPEAKER_382: here we are 15 years later, 15 years. What were the top five Mahalo pages?

SPEAKER_34: It turned out that I put, 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.

SPEAKER_10: We did coupon pages. Those were the highest monetizing. So we had said like that Beth and beyond coupon. Right. And then we gave strategies for getting the coupons pages that have them, how to get them. And then just, you know, some links and some content. Then we did

SPEAKER_28: 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. And, um, 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, um, you know, I, it was a very good lesson for me because we built a Q and a system. We had built a wiki system before, you know, after Wikipedia,

SPEAKER_10: but before Cora and, um, you know, the, 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, uh, you know, I think that's the antitrust stuff that, you know, a lot of us had to deal with, you know, e how all the different how to sites wonder, whatever, what was the site about.com that the New York times. Yeah, 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. And then I had the other side of the business saying we are partners because we're making $10 million in Google adsense together. You know, when you start making 10, 20, $30,000 a day in Google adsense, 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 Sergei and I talked to Sergei and I talked to Marissa and I talked to Megan Smith and they were 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. Yeah. And they basically wouldn't give you an answer. So, hey, it's a good lesson for everybody. You gotta, you, you can't have a dependency on any one company, whether it's Google or Stripe,

SPEAKER_28: or, you know, look at Buzzfeed and Facebook. Yeah. You know, Buzzfeed is like, I, I don't even know if that company is going to be here next year. Like they're making two or 300 and rev 200, 300

SPEAKER_254: million dollars. I think the company's worth a hundred million dollars. Now they just laid off the entire news team. Yeah. As soon as they didn't, they just shut down or what? They shut down Buzzfeed

SPEAKER_28: news, but they still have like the listicle stuff. I think still got it, but they were an SEO. They weren't SEO driven. They were social driven. So, oh, you, you know, you want to share this on

SPEAKER_10: Facebook and they would siphon traffic off for Facebook until Facebook was like, you know what?

SPEAKER_189: This content should live on Facebook, 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

SPEAKER_34: you're going to be able, my belief, I think we'll end on this one, is we're going to see a hundred times the number of startups. Yep. That's what I think is going to happen. I think this is exactly like when Y Combinator and cloud computing angel list, open angel for my syndicate, that moment in time, many more people could build something because you only needed five people

SPEAKER_28: and a million dollars to build something because of cloud computing. And then it became, well, you only needed like five people and 150,000. I think now you need two people and, you know, $25,000, you know, or $250,000, which means like a very niche website or a very niche service, you know, uh, uh, an app for snowboarders, right? We use the, the app slopes, right? It's a, I think it's probably a couple of person team. Well, there could be a version just for snowboarders, but nobody 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

SPEAKER_10: products because of this. I think this is going to create a revolution in startups.

SPEAKER_398: I couldn't agree with you more. I think it's already happening.

SPEAKER_56: 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, the, the, the cost of running these, 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 bytes from one place to another, and there's

SPEAKER_24: no money in the other end of it, it could be disrupted, but we have to figure out the revenue

SPEAKER_10: models first. All right. Listen, you guys are amazing. Uh, look forward to doing some coding with you, Sonny over the weekend, Vinny, uh, whatever music festival you're at next. I hope you enjoy that and you pop some great bottles while, while Sonny and I are actually getting

SPEAKER_72: work done. Sonny and I are going to be popping some bottles tomorrow night. Oh, what? What? Is

SPEAKER_10: there a bottle popping? You guys are going out? What a little Vegas trip? Were you going out to see the warriors in, uh, Sacramento? What's going on? We're in Austin. Oh, thanks for the invite.

SPEAKER_409: Thanks for the invite, boys. You're welcome. I guess I missed the invite got met. I don't need

SPEAKER_411: an invite. I need you to send a plane. I miss minded launch. Uh, well, that wasn't my invite to

SPEAKER_34: get. I, uh, I am, I'm, I'm lucky to have been invited, uh, and, uh, to the SpaceX team. Did you

SPEAKER_32: see the damage though? Um, we were supposed to actually, as you mentioned that we were supposed

SPEAKER_420: to go tour it. Um, but I, we ran out of time and I had to get out of there. Yeah. But yeah, I mean,

SPEAKER_34: if you build the largest rocket in the world, it's gonna leave, it's gonna leave a crater. Um,

SPEAKER_269: it's gonna leave a mark, but they have, uh, my understanding, uh, from I think what's been

SPEAKER_216: publicly said, I always gotta be careful here. Um, is that there's a solution for that, uh, that they

SPEAKER_16: have. Yeah. And I think he's, uh, he's done a pretty good job of highlighting like, hey, we were supposed to have this water cool thing, but we water cool thing. Yes. We didn't think we needed it, but now we'll, we'll put it in. Um, it's pretty cool. It's, it was really inspiring.

SPEAKER_221: 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 finals. I have skied in Japan. I, you know, I've done it all. I think like,

SPEAKER_10: uh, 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

SPEAKER_09: 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.

SPEAKER_28: The scale of this rocket is I I've, I mean, I've been to star base a number of times and I've been on

SPEAKER_269: the top of, um, the, there's a building where they build just the top part of the rocket,

SPEAKER_430: the starship, the actual starship, not the booster. Yep. I have been up the freight elevator

SPEAKER_85: 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, you're looking down at this rocket ship or looking up at it and it's like, whoa, the starship is a very large vehicle. And I have been inside the starship, like, uh, the cone

SPEAKER_386: of it, like maybe the top third of it. I've been inside where the payload is. Yeah. And you're like,

SPEAKER_85: whoa, the payload area, it, it feels like the size of a warehouse. 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. It does not feel like something that could, it, it feels as if the empire state building is going to space. That's the closest analogy I can give you. If you've, if you stand at the bottom of a skyscraper. At the bottom 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. Incredible.

SPEAKER_115: Going to space. I mean, it's bonkers. It was awesome to watch.

SPEAKER_289: And you know what, he's been pretty clear. Like that's an old rocket. They got, you know,

SPEAKER_34: the next couple are ready to go. Yeah. So again, talk about compounding. He's compounding physics down

SPEAKER_10: there. Yeah. Let alone compounding AI. Uh, it's, it's gonna be, uh, pretty fantastic if, uh, he can stay

SPEAKER_321: focused on that, you know, and, and really that team is dialed in. They are dialed in. Uh, it was very impressive. You, you, you underestimate what you can do. They have to be the smartest engineers

SPEAKER_23: in the world to do what they're doing. Literally. It's, it's not just their intelligence. It's their

SPEAKER_28: motivation. It is incredible. When you go to star base, that is a citadel of technological achievement. It is, it is like going to the Vatican or to a monastery. It is not like anything you've experienced in your life. They are there to colonize Mars. So the vibes you get are crazy.

SPEAKER_321: I mean, here's a scale against a human. And just to give people an idea, if you listen, if you're watching, like, yeah, we see the human. Yeah. There's a tiny little human there. And that's

SPEAKER_453: just, and here we go. What does it cost to build this thing? Um, it's expensive. Yeah. I don't

SPEAKER_34: want to say, but I think they're gonna, it like the Tesla model Y it's getting cheaper and cheaper and it's reusable is the idea. So those arms are going to grip it when it comes back down. So they didn't even 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. Yeah. They're going

SPEAKER_321: to be able to reuse these. And if they can reuse these and they can have, they could have these going

SPEAKER_28: up daily. Like they do with the Falcon. Like how often do you see Falcon launches? It's been 224 of them.

SPEAKER_459: I think almost like every day now, right? They do them. I don't know if it's quite every day,

SPEAKER_28: but I think there's been weeks when there's been multiple. Yeah. So it's moving, I think,

SPEAKER_189: towards that pace. And that means payloads in space are going to be absurdly cheap.

SPEAKER_15: Yeah. I think I read something Vinny and like ultimately they'll get it down to like $20 million or something. What? That's nothing. Yeah. Yeah. It's, it's already changed everything.

SPEAKER_221: That's cheaper than a house in Atherton, guys. Yeah. I mean, and you know what, when you're, if you're inside that tip where the payload is,

SPEAKER_468: it's the same size. It's pretty much the same size of these outrageous homes in Atherton. All right. Great job, Sonny. Great job, Vinny. We'll see you all next time. Thanks. Con this week's service. Bye. Bye.