The Exchanges

Q I was going to say, do you think that's going to be one of the main reasons of the success or failure of this is how it can be integrated in all of the other pieces that Apple puts out in the world?

A Well, I sort of tweeted halfway through the presentation. I feel very sorry for Meta because they spent, you know, however many tens of billions of dollars on their product that, you know, no one's really, only a couple of million people are really using and doesn't have traction. And after this, why on earth would you develop for that? Yes, like that's three, 400, the Quest three is 400 bucks and this is Two and a half grand, but like, even so. Um, but kind of the reason I mentioned Meta is Apple has all this other stuff to leverage. They've got the developer community, they've got the tools, they've got the Mac and the iPad and the iPhone and the chip team and everything else. And Meta sort of had to try and desperately try and build all of that from the outside and kind of bootstrap all of it from zero. I mean, God only knows how much Apple has spent on this, you know, probably more, much more than Meta, I would guess. But they're doing it in the context of having all of these other things to plug into it, which, which, which Meta doesn't have.

AI assessment note: “Apple has all this other stuff to leverage. They've got the developer community”

Q No, no, no. I was sort of posing that as a, both my perception and also a question of, you know, what, what, what interesting things can one say about that, that perception and that structure?

A Yeah, completely. Um, definitely agree with that perception of, uh, Feeling like everyone is at everyone else's throats all the time. Um, and kind of thinking back, I think there's a few starting conditions that has caused this, right? First of all, it's, as, as you kind of pointed out earlier, Ben, China has a much more defined Market into itself. It's very hard to leave China. And so what that means is, yes, you have a very big market, but that's essentially your market, right? So I think every player knows from the outside, you know, rather than thinking, hey, we can go to Europe very easily. They know it's very hard to go internationally. And so for them, then they think once I've saturated this market space, then I need to look for the next areas of growth. And then that leads to more competition. Across different verticals. I think for the players like Google, right? Okay, Google has one search in the US, so obviously the next category, next stop would be for them to go internationally. You can just do that, um, in a vertical across different geos. And I think you can do a lot of, um, do a lot before you sort of get to a natural world boundary in that sense, uh, before you have to look for other revenues and growth. Whereas I think for Chinese tech, they think, hey, search in China, we've done, okay, so what now? And you've seen that for Alibaba, and Tencent, uh, and Baid…

AI assessment note: “definitely agree with that perception of, uh, Feeling like everyone is at everyone else's throats”

Q you've got this sense of a lot of sort of great kind of reorientations going on in how the consumer internet works in, certainly in America and Western Europe, um, probably in Japan as well. And I'm just curious, are there sort of those sort of great shifts going on or equivalents of those sorts of shifts in, well, what is the internet and how does it work in China?

A Uh, yeah, definitely. So, um, as I think the Western media has definitely picked up and kind of made Jack Ma kind of the face of it, uh, you know, took the regulatory crackdown, but I think it's not just on Ant and Jack Ma, it's internet more broadly. Uh, and so I would say the tectonic shifts that's been happening here has, you know, firstly been Chinese regulators in the year of More vocal and visible about cracking down on what they term monopolistic behavior on the part of platforms. And this isn't, I guess, I mean, definitely, this in some ways is kind of always playing catch up because the kind of behavior that Chinese tech platforms have been able to get away with would not have, um, they would not have been able to get away with this in the West. So Chinese kind of regulators reaching parity. So for example, the biggest one is making, um, Um, so these platforms are making kind of their suppliers pick, uh, one platform over everything else. So if you're a supplier to, uh, Alibaba, you can't go on Pinduoduo or JD. They would sometimes make you sign an inclusive, exclusive agreement with them, which would be very, you know, anti-competitive in most parts of the world. Um, but they've managed to sort of have these until very recently. So that's what all the finds on Alibaba, um, and Meituan have been about. Which is them kind of, uh, almost making their suppliers, um, take …

AI assessment note: “the tectonic shifts that's been happening here has, you know, firstly been Chinese regulators”

Q this guy called WG Grace, who no American would have heard of, but he was this sort of famous cricketer who had this enormous beard and dominated the sport and invented half of what people do now, and he was notorious for gamesmanship and for, um, You know, for demanding money on all possible occasions. So that's always been that kind of tension of, is it a business or not?

A And, and look, it's interesting because this is what happened with tobacco advertising, with the tobacco advertising directive in, in, in 2003. And, and F one was one of the most watched events, um, in the world. I think it's just right after the Olympics and the world cup, it is one of the most watched events and it provided the tobacco industry. With, which was at the time, one of the biggest sponsors with unparalleled marketing exposure. And so the ban had ultimately a massive financial impact on, I think, was it four or five of the major F-one teams at the time? Um, sort of Jordan, McLaren, Benetton, um, none of the, apart from McLaren, but Jordan and Benetton are no longer F-one teams. And so to your point, they had this massive income of money coming in through tobacco. And then all of a sudden, You realize, shit, we're going to have to find another revenue stream, um, which became interesting in that time. Um, and then you realize it really is a business.

AI assessment note: “to your point, they had this massive income... then you realize it really is a business.”

Q So they just had the, so they just had the colors?

A Not worse. It was like a barcode. So it didn't look like the logo, but so they had black and red lines along the cars. But when the cars were going at such a speed, it would look like the Marlboro logo. And so ingenious when you think of it. Um, and so it's brilliant. It was one of, and so, When they came out with the cars, people were like, that's so weird, why would you have an ugly barcode on the side of your car? Until the cars start going round the tracks and you go, ah, got it, it's the Marlboro package. Um, so they've tried for a long time to find different ways around this, um, I don't want to say, they found loopholes around that for sure.

AI assessment note: “It was like a barcode. So it didn't look like the logo”

Q I mean, maybe that's a bad example because one of them is audio and the other's text, but you see what I mean? You make a specific product.

A It's an age old problem. Like I remember selling. Campaigning software. And to your point, most of the political parties were very happy keeping all of this in an Excel spreadsheet. They're like, all we need is five rows, name, you know, name, voter registration, donation number, and we're just gonna use it. Why, why should we merge all of this? Because what you're asking of us is a lot of work, bringing all of this into a new piece of software. And then you're telling us that this software can do 10 other things that we never thought of that we don't actually think we need, but you're convincing us that that's the future. And now we have to do a bunch of API calls.

AI assessment note: “It's an age old problem. Like I remember selling. Campaigning software.”

Q a better time for us to be having this conversation with you, Leonard. So I, Maybe the best place to start is, like, where did the idea of Caravan come from, and where did the idea of bringing this into a bigger company like CAA, and why is that, like, a perfect match for the two of you to be, to be partnering for these, the future of these brands?

A Yeah, I mean, CAA started building brands long ago, and, uh, one of the partners leading the charge doing that was a guy named Michael Yaniver, and Michael and I got to know each other, you know, a few years before, and, And I think the intention was they had done quite a few experiments in building brands and building companies here and using talent-led initiatives to do that, and they were quite successful. And I think they're no different than any other startup that you're building, which is, it's a ton of work, and you can only do so many of them at a time without having an infrastructure, and so as you become more successful, more and more people want to do it, but the problem is if you're only one or two people, it's incredibly hard to do them at scale, and I think the intention was to bring Caravan as a studio, co-found it, so that you could take more swings at bat, you could have Uh, a community and a team and a SWAT system that you could go in and actually build at scale and systematize a little bit of the operation of it. And so instead of doing one a year, you could now do three or four a year. And I think it was also, um, really important to build a sophistication and a muscle around when does it matter to bring talent in? When is it effective? Who are the right kinds of people? And you really need, it's a skill. You know, you really have to know how to do that and …

AI assessment note: “the intention was to bring Caravan as a studio, co-found it, so that you could take more swings”

Q You're good. So yes, where's your head at, Jay? I like that. I'm just like, are these the right questions? Are we thinking about it the right way? And also what the hell is going on that this is top of mind for everyone?

A So I have to admit, it is in many ways very strange to me that suddenly semiconductors are cool and interesting again, because I've worked in and around them for twenty-something years, and for a long time, they weren't cool or interesting. And it's even the most obscure, least glamorous parts of the industry that are, are the most fascinating to people right now, sort of the semiconductor manufacturing equipment. But it's, semis are super important. They're the foundation of all of technology and much of the economy. And I think we're, we've, the combination of trade war and the pandemic and the shortages have really woken everybody up to that reality of how important semis are. And, and, uh, there's a lot to, there's a lot to cover within that. Uh, but yes, semis, semis are foundational to everything.

AI assessment note: “the combination of trade war and the pandemic and the shortages have really woken everybody up”

Q of what's possible, is that also the meeting in which you are asking the very tactical questions and operational questions of, okay, that's a great idea, but how does it work? Break it down. Or is that not the meeting where that happens, and you're like, no, this is a fucking phenomenal idea. We'll figure it out when we need to figure it out, and we'll ask the tactical questions.

A Well, so, so it depends. So I think we've done other podcasts about this. Um, you don't expect people to have every single detail worked out. Quite often, the point is that you're, that you're, you're betting on the entrepreneur's ability to work out how this is going to work. But, um, the metaphor I always used to use is tractors and rocket ships. So there's some kind of companies that have very high margins, like Facebook, and your job is to keep it pointed roughly upwards and not argue about the thrust to weight ratio. Are we going up very, very fast? Yes. Don't argue about what the thrust to weight ratio is. The answer is lots. And we'll work out the revenue later. And if you looked at Facebook in 2005 and said this thing isn't making any money, I'm not investing, you would have been in more.

AI assessment note: “you don't expect people to have every single detail worked out”

Q have control. Um, and so this gets us to do this very kind of messianic, very religious idea that you can kind of remake the internet with this stuff. Um, and you can kind of go off and, you know, proliferate definitions. So you can say, well, what was web two point now? Why web three? You know, what does this have to do with early versions of open source?

A Just, just to chime in there, there was some, when I was trying to truly, in the most simplistic way possible, try and understand the difference between web one, web two, web three, and someone came up with a really interesting lens, or I thought it was useful, of just like thinking about where we hung out, so if web one was you, it was your email, email was your home, web two, it was the social platforms like Facebook and Instagram, and so web three was this whole idea that you could, exactly what you were saying, you could actually even own the platform on which you are hanging out, Which gives you that more decentralized aspect that everyone is talking about, which I thought was an interesting way of like, where do you hang out online? And that evolution from web one to web three.

AI assessment note: “try and understand the difference between web one, web two, web three”

Q interesting looking at it and, and realizing over time that China is deliberately shifting from a successful, maybe low-tech manufacturing economy to a very much innovation-based, high-tech economy. Like, that shift is happening. But what are the other things that we, like, need to shake that we might have misconceptions about? Tech in China. Um, or is there another question that we should be asking, and that's the wrong one?

A Yeah, I mean, so I, it's hard to sort of go through the misconceptions, um, because, because I don't quite know, um, what exactly everyone has. I mean, but actually maybe let's, let's take the one that, um, we have talked about kind of China, or China does is copying, because I think that's actually quite a good one, right? And I think as Benedict correctly pointed out, um, on some surface level aspect, yes, there is some lots of similarities, and Um, and actually, it's, you know, just taking a step back, I think there's very different attitudes to copying, which I think is very interesting. So when I talk to Chinese PM and Chinese tech workers, first of all, they don't view copying as inherently shameful, because their mentality is, you have come up with a very successful UX or product, therefore, you know, for me to learn and to catch up to you, Um, I should first copy what you do, because that's just showing that I have, I can go very quickly, get to a de-risked product. And then once I'm at the, you know, technology frontier, product frontier as well, then I can innovate quicker. But it would be kind of silly for me if I'm so far behind you to sort of say, I'm going to try to get to my way and try to reinvent the wheel to get to where you are. Surely the easiest way for me and my team is just to copy. Um, and then Once we've made sure we've covered all the bases, then we ca…

AI assessment note: “let's take the one that... China does is copying, because I think that's actually quite a good one”

Q against one political party or another. They're here to make money. Why do we seem to forget that? So they're obviously going to build the best platform that actually enables more money to be made. So to your point about, well, what if we stopped sharing on Facebook? My mind went to, would that help with their business model? Would that hinder that? And why are we not doing that?

A Well, so you taught my, all my friends at Facebook would basically say, we wish we didn't have news at all. We don't make any money from it. We actually don't make any money from news, although the amount of money is trivial. It's a huge amount of, of, of, of pain and aggravation and, You know, whether you believe the social harm is real or not, there's a huge amount of people shouting at us. The PR damage is enormous. We should, we would love really, you know, we should just block all news domains entirely. Like, all news content. And like, that's not what Zuck says, but like, from a financial point of view, they are not making money out of this. They're just really like, oh, please make it go away and get everybody back to sharing pictures of puppies. They would much rather just be the puppy sharing picture network.

AI assessment note: “from a financial point of view, they are not making money out of this”

Q sounds like, and again, I didn't watch the Facebook connect event live. I watched the re-recording and you don't have the streams of comment and the re-recording, which sounds like that's actually a blessing. Um, but it sounds like the Facebook event felt much more like a live event. And the Apple, which obviously pre-recorded, you don't have that. Am I correct in thinking there wasn't any sort of live?

A Yeah, it felt like you're kind of, yeah, some of it was live, some of it was recorded, but it felt much more scrappy and free flowing, and it was, it felt like you were supposed to feel like this was recorded in this person's living room, and that was recorded in that person's office, and they cut to 20 or 30 different games companies, and You know, one of them, it was literally like it was in his cubicle and he said, like, I really suck at doing these videos, but I'm going to try and tell you about what a great game we've made. I love it. So it was just a much more kind of a grassroots kind of a feeling. Whereas Apple, it was here is our billion dollar office building. And here is, you know, we spent twenty million dollars on cameras and compositing and rendering. It was a much, it was a movie production.

AI assessment note: “some of it was live, some of it was recorded, but it felt much more scrappy”

Q types of different talent differently? Do you look at an athlete in a certain way, and a celebrity in another, and an actor in another way, and maybe an online content creator like Emma Chamberlain, who was a YouTuber, like, do they all have uniqueness to themselves of how you could potentially partner with them and work with them to create something, and what are the similarities and dissimilarities here?

A Yeah, I, I think inevitably we treat everyone as individuals and, and as you think about what you're looking for in a partnership and a co-founder and a company from, from talent, it's specifically, you're looking for an engaged audience, an understanding of the segmentation of that audience. You're trying to understand, um, what are the things that authentically connect this person to their audience? Because where the, where these things go wrong immediately is when these things are inauthentic marketing partnerships rather than someone desperately cares about the subject matter. You know, you gave the example of Yummers. You know, Jonathan Van Ness and Anthony Porowski are super passionate about their pets. It, and, and they were desperate to find healthier solutions for their pets than that we were seeing in the market. And so they're all about that. They live it every day. It's a huge part of animal welfare. It's a huge part of their life and it was very authentic to them. And I think the other thing you're looking for often in these folks is do they understand what it means to be an entrepreneur? Because You have to be able to say to them, The meeting that you're about to have with a buyer at Target, or you're gonna do a live stream with 200,000 fans, like, those are as important as a shoot you may be doing at Netflix, or they're as important as the other side of your care…

AI assessment note: “inevitably we treat everyone as individuals and, and as you think about what you're looking for”

Q Well, that's the whole network effect, isn't it? Like, it's pointless if you're just hanging there alone, hanging out there alone.

A And one can go down, you know, questions of, well, how does the wallet model change that? So there's all these sort of senses of, like, these different concepts of what you can do with this, and how this might work, that allow you to build a different kind of product. So, you know, very tangible example. Supposing you build an Instagram on this, and I have Lots of followers, and I'm an influencer, and I sell a sponsored post. Well, that sponsored, the way that would work is the sponsor would buy tokens in the system, place them in a smart contract. When their ad appears between me and them, when their ad appears, then mechanistically the money is released to me. Mechanistically, some portion of that gets sent to early investors or early participants or to infrastructure providers. Some portion of it gets to me. Maybe I've automatically installed some, some other application that automatically allocates some to charity and some to tax. And it's all happening mechanistically. It's not that I have to send them a PDF of the Instagram metrics dashboard so that they can see, so they had to see the ad.

AI assessment note: “how does the wallet model change that? So there's all these sort of senses”

Q years. It goes back to Salesforce or longer. It's old. It's boring. It's done, but it's only sort of a third of enterprise workflows because this stuff just takes a while. And if you're the CIO, why would you invest in moving people off, off, um, fax workstations onto AWS? Like, like next year, next year, next year. Um, and so some of this is, it will just take time.

A I saw, um, a friend of mine sent a, shared an email with a few of us. I think it was a friend of mine. Um, it might have even been you, but I don't think it was you, um, who just got a news update that the way that we, that they can contact their bank has now changed. The fax machine will no longer be, um, in, in order. And you go, wow. Um, you know, didn't know that anyone was still sending fax machine, you know, faxes in this day and age, but to your point, that change took what, 20 years for someone to To say, oh, it's time we send that email to tell everyone to no longer send a fax.

AI assessment note: “to your point, that change took what, 20 years for someone to”

Q Are you saying that all of them don't have a network effect, or do you think that there's a few of them that have a potential of a network effect that's starting?

A So the thing people are kicking around at the moment is a memory where the product remembers, not the model we should distinguish, kind of the product Has some history of everything you've asked in the past, and it uses that to inform its answers. Um, but that stickiness, I don't think that's a network effect per se, or that you'd have to do something else for that to become a network effect, and it doesn't seem that hard that you could just ask ChatGPG, tell me everything you know about me, and then go and tell Claude, hey, know this about me. Uh, maybe, maybe not, but it's, you know, it's stickiness, but it's not, it doesn't seem to be network effect, and there doesn't seem to be network effect in the models themselves, because the models aren't being continuously Retrained on everybody's input. And if you were, it's not clear how that would work. Um, so in contradistinction do like smartphone operating systems, say, or indeed Google or say from networks, there aren't network effects you've got. So you've got the products of the space. It is saying the models are basically saying the usage isn't and how would that change? And I think it was kind of an interesting starting point. And then I went and looked at this Publication from the UK regulator, um, competition regulator, the CMA, which is doing an investigation into Google, and so they went and pulled a bunch of primary da…

AI assessment note: “it's stickiness, but it's not, it doesn't seem to be network effect”

Q yeah, obviously, I haven't put, I haven't plucked this one out of Finem. My memory does not work like that. Um, but you say that ML bias will cause problems in roughly the same kinds of ways as problems in the past and will be resolvable and discoverable or not to roughly the same degree as they were in the past. Is that still, do you still agree with that?

A Well, I mean, one of the things, this is the reason I kind of talked about databases. The You have these systems that produce what appear to be a correct answer, but it might be wrong. And there's a people, there's this kind of claim that somehow databases were deterministic, and you understood how they worked, and they always produced the right answer, unlike machine learning. And that's true in a sort of narrow pedantic sort of way, but it's actually not true. You know, databases are full of bugs and mistakes, and there's stuff in the data that isn't correct. And so databases, in fact, can say stuff that isn't true. And they can say something and you don't know why it's, why it produced that result. And so on the one hand, you need to be conscious of when you are building and using these systems to try to not do that. But you also have to have the institutional capability to understand that maybe the data computer is wrong, which is, and I think there's a sort of a slightly uncomfortable and people use these things to ruin people's lives as they have in the past. And you need to have sort of institutional processes to try and stop that happening in the first place. And secondly, to recognize that it has happened and try and fix it. And I think the same thing sort of gets repeated here again.

AI assessment note: “And I think the same thing sort of gets repeated here again.”

Q but mostly to aggregate data and numbers around, you know, what we're seeing around a certain series of sports, but it's interesting to see how it's being picked up. But I think for most people, we're still trying to figure out how, how is this being used and how are we using it on a day-to-day basis? And maybe we're not yet now. It doesn't mean that it's not great.

A Hmm. Yeah. I mean, the, the analogy I used, and again, Lots of analogies here. The analogy I used to use for the last wave of machine learning was to say, this gives you infinite interns. So you want to listen to every call coming into the call center and tell me when the customer's angry. You want to look at every credit card transaction and tell me the weird transactions. You want to look at every single x-ray of your wind turbine blades and tell me if there's anything unusual. Um, doesn't take, you know, someone with early years of experience. It's just an intern. Um, maybe not the last one, but You know, it's, but it, but you could never automate that before because it kind of required a mammal brain. I think someone that I used to work with said that AI will probably do anything that you could train a dog to do, which kind of captures that as well. You, you could train a dog to tell me whenever somebody's angry. That would not be difficult. Dogs can do that.

AI assessment note: “The analogy I used to use for the last wave of machine learning was to say, this gives you infinite interns.”

Q Um, what prompted this conversation? What was this for, for you? Was there anything in particular that you were looking at?

A Well, so I was looking at, I looked at Metaverse, sorry, at Fediverse, and saw, this looks like an open source claim of Twitter, and open source claims of commercial products never work. It's the only people who use them are people who care that it's open source, not people who care about the product, for the product. And then I thought, no, there's a bit more to it than that. And it's more, this is much, this is also a sort of an attempt at an entire web distribution system. Now it's also been around for a decade and there's a bunch of acronyms and a bunch of ideas and a bunch of very passionate, a very, very small number of very, very passionate people who will say, no, you're an idiot. This is all working really well. Um, but I think this sort of the underlying challenge here is interesting. I mean, one of the things I was thinking about writing was a sort of like a comparison to like the laws of thermodynamics in that, like, there's always this urge to make a open distributed content Recommendation system that's flat and doesn't have gatekeepers and will not downrank things. But if you do that, then now I've got a two, three, 4000 things in my feed. And how are they sorted? Well, they're sorted by when they were published. And that's just an algorithm as well. That's just a randomization algorithm. So you can't, you know, put another way, like you, if you, if you, um, if yo…

AI assessment note: “Well, so I was looking at, I looked at Metaverse, sorry, at Fediverse”

Q That is a perfect example of how it isn't a tool that's built with a specific audience in mind. We don't know who the audience is right now. Do we? Like who's the user base, you know, for this?

A Yeah. I mean, it says, well, in a very different sort of context, one of the ways I kind of talk about HEI is to say, I may have said this on this podcast before, is to say, we don't, we had, when we were trying to go to the moon, we had a theory of orbital mechanics. And you can, we had a theory of what rockets were doing, and you could get the spec for the Apollo rocket and show it to Isaac Newton, and he could do the maths and tell you whether it would get to the moon or not. This much thrust, this much weight, this much fuel for this melange. This is how far away the moon is. We've measured it. Will it get there? Yes or no? Whereas with AGI, we have no theoretical model for what AGI actually is, and we also actually don't have a theoretical model for how LLMs work. Other than at a very, very high, high level. So we don't actually know what will happen if we give it three X more data and four X more compute, which is what gets you to this phrase emergent capability. Like it starts doubly starts working in unpredictable ways. And then maybe, well, maybe it doesn't, and we don't know. So we know the point is we don't really know what it is. We just, we keep making these bigger and bigger rockets and they keep going higher and the moon is roughly in that direction. So we think maybe it will get to the moon. Um, and then someone kind of chokes about this thing and says, well, ca…

AI assessment note: “So we know the point is we don't really know what it is.”

Q Yeah, they definitely, they, they kept it more from an entertainment perspective, work and entertainment perspective, didn't they?

A Yeah, so there is this sense of, here are all these different things it could be, but kind of going up a level in abstraction, it is this sense that this is this sort of infinite display. So, and almost that you don't have a display. So you put this thing on, and it's as though you put on a pair of ski goggles, and you see the world around you. And there's a screen on the outside that just It shows some expression or shows your eyes so that people around you don't get the sense that you're completely blanked off. And so the ad they show is like the kid can run up to you and talk to you and you can still see them and interact with you, which I have to say I'm kind of skeptical about. It seems to me that's okay, that's just enough for you to see why I should take my headset off, not that I'm going to wear it all day. They don't show people walking down the street wearing it, which I think is interesting. They show people, they show people sitting down Or in an office or at home. They, and you know, walking around a desk, they do not show people going for a run or walking down a street with it. So there is a sense of there are limitations on where you could use this. Um, but the core of it is you put ski goggles on and it's so the ski goggles are like a magic window. Like they suddenly, like you see the world, you see your room as it was, but then stuff can appear. And you've got …

AI assessment note: “They show people, they show people sitting down Or in an office or at home.”

Q No, I agree. Where and how do you, here's a question. Do we look at NFT, metaverse, crypto as all part of a singular topic and they're all components of it? Or do you think they warrant three separate conversations on three separate paths?

A So I think part of the challenge for both of these subjects is that, or all of these subjects, is that these words sort of escaped out into the wild and got used to mean almost anything, particularly metaverse, which sort of metastised, if that's the right word, From a relatively narrow sense of saying, well, what would happen if everyone using, is using VR and AR as their main device, and how will that change the internet, into meaning more or less anything that anybody happened to be thinking of at the moment, to the point that you actually don't know what anyone means when they say metaverse, because they could mean anything. And so I think the moment that people started saying that NFT is a part of the metaverse, for me was the point And people started saying, you'll be using the metaverse on your smartphone. It was kind of to the point that I just said, I kind of give up. This word just doesn't mean anything anymore. It became anything cool that might happen in tech in 10 years.

AI assessment note: “the moment that people started saying that NFT is a part of the metaverse”

Q And is this the start contracts with AWS, which requires investment in property, equipment, everything that it takes to operate cloud business?

A It's a whole other thing. Um, whereas, whereas selling ads on the existing website where you need people to do that, but you don't need like a whole new set of people to run all the infrastructure because most of the infrastructures are there and you don't need to build like a hundred billion dollars and more servers to run that because you already got more. And so you're sort of free riding to some extent on the existing, all the existing infrastructure and cost base. Um, and so, forty eight billion dollars. Um, Alpha Amazon, sorry, Google's operating profit, if you remove TAC, which is what they pay Apple to be the default search engine, and if you remove, um, technology R&D, then you get like a 60% operating margin, so if you apply that to 40, forty billion dollars, you get whatever it is, 20, over twenty billion dollars, um, which is roughly the same as AWS, so roughly equivalent operating profit as AWS, And without AWS's 10 or twenty billion dollars of capex attached to it. So, like, giant new profitable business. Haha. Okay, that's the first way of looking at it. However, the more interesting thing is to say that it's not really a standalone business, and the dumb thing is to say, yes, not a standalone business because you couldn't have it without the rest of Amazon. The more important point, I think, is to say, um, okay, could you do a P&L for Prime? So this is more reve…

AI assessment note: “without AWS's 10 or twenty billion dollars of capex attached to it.”

Q customer that wants to feel a certain way, and is that a perfume, or is that a garment, or is that a makeup, or is that maybe something else, and how would you serve that customer? And, and you would work back, and so the brand would, you start with the brand, and you get to the factory at the other end, and so you start with the advertising first.

A I don't even think you, Start with the brand. I think what we've seen with most D to C brands today is you start with the audience. You listen to the audience, you figure out what the audience wants because you've built your brand is maybe yourself. And then you figured out, oh my God, there's a whole audience of people who want the same thing as me. You build the product, which makes them successful because the moment you go, that's it. You start with the story and then the ad, and then maybe you have advertising, but maybe you don't even need it by the end of it. If you start with the story, You've got the audience, you've got the product.

AI assessment note: “I don't even think you, Start with the brand... you start with the audience.”

Q I think, briefly spoken about, and that has been mentioned time and time again, which is this idea That there potentially may be new gatekeepers when we open up a new wave of technology, and there's always been gatekeepers in tech. How are you thinking about, and I'm putting it in inverted commas, like, new gatekeepers in this space, and is that even something that we should be thinking about?

A So I think there's two very different places that one could take that conversation, because one conversation is to go very specifically and look at, you know, Apple, Taking 25% off the top of Facebook. It's actually Apple and TikTok between them. Well, at any rate, Facebook said they missed their numbers, and the stock went down 25%, and Facebook said it's because of A, Apple, and B, TikTok, and C, we're old and boring, except they didn't say that part. And, you know, Apple, despite not really having a significant ad business, has sort of somehow become a very significant power player in the ad business. Amazon announced This quarter, what had previously been sort of implicit in their results, so they, they have this line in the back of the account, it's called a breakdown of their revenue, and they had this line called other, which they say is predominantly advertising, and this quarter they basically broke out advertising specifically, and it was all advertising, and so Amazon needed a thirty one billion dollars of ad revenue in 2021, which is bigger than, bigger than YouTube and bigger than the global newspaper industry's advertising revenue. Um, And so here from nothing five years ago, here's this thirty one billion dollar ad business. Then you have Shopify whose numbers, Q four numbers aren't out yet, but in the 12 months to Q three, they did a hundred and sixty five billi…

AI assessment note: “there's a certain kind of person that wants to say, you've got these giant monopolies”

Q Um, so what's the point with that? Ask better questions or follow up?

A The point with that is, it's like, it's very easy to make your list of frameworks for how innovation is going to change the industry, um, in hindsight. It's, and sometimes it's completely obvious. I mean, I do remember a quote from one of the co-founders of BlackBerrys looking at the iPhone and saying, if this thing works, we're competing with a Mac. Even as in public, they were laughing at it. Um, But, you know, the history of the last 25 years of software companies being created is it's really easy to say that it was obvious after it's happened. Not nearly as easy to say that it's to, where to predict where all this is going to happen in advance. And the same thing now with this stuff. I mean, yes, if this, again, if the AI maximalism view is right, then like all bets are off and all software is dead and everything changes, and this is what gets people to talking about like structural changes in long-term GDP growth. Um, because this is like the new steam engine. If on the other hand, no, this is not the new steam engine, this is, this is like the new internal combustion engine, this is, you know, this is the gas turbine, it's just more, if this is a new PC, this is a new web, this is a new smartphone, then it's a, it's a continuation of a process that's been going for 200 years, then, then, then the world looks different, and it's, in a sense, it's easier. It's both easier a…

AI assessment note: “The point with that is, it's like, it's very easy to make your list”

Q at the other end, you have this talent that you're just like, you two need to talk to each other? Or does the idea come from the talent? Like, how does that work? Because I feel like I could see the cases of someone has Built and created a phenomenal product. They just don't have the audience, and it feels like bringing those two pieces together can be extremely valuable.

A Yeah, the ideation for this stuff happens, uh, in a couple of different ways. So, so we are often the genesis of a lot of the ideas, and because we're spending a lot of time and data looking at market opportunities, and we're, a lot of our life is spent talking to consumer buyers and large consumer companies and CPG, and so we kind of understand the market, um, In that way, so we're able to think about the opportunities. It is very common for clients to bring you ideas and companies, and sometimes those, those two worlds collide where the opportunity matches with the interest of the client immediately on day one. I, I think you also have typically the founders that are coming through that we work with are very much in the market opportunity side first, but there's definitely, and there's lots of divisions inside CAA that are, that That are hugely involved in matching entrepreneurial ideas with clients, and they're just not necessarily building them in the way, in the way that we build them. You know, we're, we're kind of the Keebler elves building this stuff behind the scenes, and most of us are technologists. We, we've started to really develop a muscle in retail over the last year and a half. We've brought on a lot of retail expertise. Just, I think it's important if you're selling to consumers that you have multi-touch points, but most of us inside Caravan are kind of Tech n…

AI assessment note: “ideation for this stuff happens, uh, in a couple of different ways.”

Q Is discoverability part of that, or is it not in the top three?

A No, no, no, you're right. I would say discover, I always think of that as cutting through the noise problem, like, but, but yes, discoverability is a better way to look at it for sure, and, and I think when you have a tool that says, and again, I'm not suggesting this is the right model, this is just thinking about how things look differently. If I'm an artist, if I'm Daniel Ricciardo, or, or I'm, um, An influencer, like iShowSpeed, or someone like that. If I want to build a brand, I can utilize tools like I almost like don't even want to say AI, but like I could use tools like generative AI in my stack to be able to design merch and design information in a way that, that is just much faster for me to get out and iterate, but I can engage my customers and my fans in that by letting them have stakes in the business, and we're in a place now where If I can build an audience for a particular brand in a subset and keep them engaged as also people that are selling the brand and sort of your ambassador group, but they're constantly active, that becomes really relevant. And the best way to keep people active is give them access to information and product they didn't have before and pay them in meaningful ways when they contribute. And so if I, like, if I could get a percentage of the revenue I've stuck into airlines over the Last. 20 years of my life.

AI assessment note: “yes, discoverability is a better way to look at it for sure”

Q Because there are so many or because there aren't any?

A I had lunch with somebody today at Ponte Latour, um, which is a Conran restaurant by, by Tower Bridge, and I remember a time when a new restaurant was something that happened like once every month or two, and it was a thing, and everyone would want to go and eat there at the Sydney restaurant. And which is what San Francisco is like now, of course. Have you been to the new restaurant? There's a restaurant. Have you been there? We're San Francisco. We've got restaurants. Um, whereas now in London, like a new, obviously like lockdown, it's changed everything, but you know, last year, if you'd said, have you been to, have you been to the new restaurant? It would be like saying, have you read the new book? What's the new book this month? Like, what are you talking about? The book. Um, and it's kind of the same thing with startups. You know, there was a, there was a time when like, there was a startup this year. Have you heard about the startup? Um, what's the startup this month? Now, I don't think you could possibly keep track of what all the startups are. You know, there are, it's not, there are not thousands in the way there are in the Valley, but there, you know, maybe, you know, there are not as many as there are in the Valley, but the sort of the volume and the normality of it has completely changed.

AI assessment note: “Now, I don't think you could possibly keep track of what all the startups are.”