Episode 16: Benedict Evans on decades of disruption - The Network State Podcast

Balaji Srinivasan 0:00
I’m here with Benedict Evans. We worked together at a six and Z more than 10 years ago. Benedict is, you know, well known newsletter author probably needs no introduction for people watching this, we’re here in Singapore. We just came here for an AI conference. You do about 1/4 newsletter, three fourths conference nowadays or speaking, that’s what brought you out here, right? Yeah. And newsletter, sound like 175 something like that.

Benedict Evans 0:23
You said, Yeah, something like that wobbles a bit from day to day. And it started out, you

Balaji Srinivasan 0:27
started as a mobile analyst, and you became, like, a broader tech analyst. Is that? Is that the

Benedict Evans 0:31
evolution? Yeah, that’s one way to put it. I mean, I think you’re an orange. Is that right? A long time ago, long time ago, yes, just when it was all becoming horribly French, there’s, there’s, like, as we were chatting before this, and I said, like, the thing in tech is at the point that you understand something is often the point that you should be moving on to pay attention to something else. So I started my career in the.com bubble as an equity analyst, and I was covering Mobile stocks. And at that time, mobile was kind of dynamic and exciting and sexy and disruptive, and they turned into water companies. They were

Balaji Srinivasan 1:02
going to water companies, utilities. Oh, utilities, yeah, they were going to

Benedict Evans 1:05
connect to everybody in the world. And then they did. And like, now what? They were like, Mark Andreessen phrase. They were like, the dog that caught the truck, right? And I went and worked in strategy and a bunch of media and telecom things, and, yeah, I was analyzing, looking at smartphones, because that was suddenly become the center of the industry, and no one understood it. Understood it now, like it happened, time to look for different questions.

Balaji Srinivasan 1:27
Well, it’s funny, because I think when we were overlapping, it was right in the middle of the smartphone dividend, the smartphone explosion. And just to you know, we actually there’s a few things. One is the smartphone dividend. That’s a useful concept, right? Like that. The rise of a billion smartphones meant that everything that went into them became cheaper, and that enabled VR headsets, that enabled drones, right? All this

Benedict Evans 1:49
stuff, yeah, all the components that came out of it, yeah. So smartphone sales are now from memory like one and a quarter, one and a half billion units a year, and all supply chain from that all of those components is then available off the shelf. If you want to buy 5000 of them or 10,000 of them, all the Wi Fi chips and the batteries and the cameras and all the other bits and before, if you wanted to put computer into something, you basically need to use PC components, so at NS and so on, are all basically PCs, like elevators, are basically PCs, and that has size and power and cost constraints, and then smartphones become the thing, and then all those components are available. And so that’s what gets you drones and connected light bulbs and all the other bits and pieces around the edge of that.

Balaji Srinivasan 2:38
One of the things I think people don’t appreciate is they think, for example, like the consumer. They think like the military has, like special gear, and it’s got its own kind of supply chain. And often the military supply chain is often just a subset of the consumer supply chain, because you sell a billion units of this, and maybe you have 100,000 or a million units of a

Benedict Evans 2:56
military thing. It’s almost, actually, it’s almost kind of the reverse now, in that it used to be so that the way I think about this is, like, in the past, like, before we were born, the intelligence agencies would get the cool new stuff first, and then the military would get it, and then big corporations would get it, and eventually consumers would get it, like 30 years afterwards. So this is, like the Canadian version, yes. Like, microwaves were invented for NASA, right? And eventually consumers get them, yeah, or

Balaji Srinivasan 3:20
like GPS was invented to guide missiles exactly, and now it’s used for tagging cat photos.

Benedict Evans 3:24
And the shift is like a combination of the stuff getting cheap enough that it can be for consumers, instead of you needing a billion dollars to have one, and then the scale of consumers once it gets cheap enough. And so now the way it works is the consumers get the new stuff, and the military gets it 10 years later, because that’s how long it takes to the

Balaji Srinivasan 3:45
bureaucracy to assimilate that a the bureaucracy be

Benedict Evans 3:48
the to harden it and productize it and turn it into what you need if you’re going to get shot at or it’s going to be cold or hot or warm or whatever it

Balaji Srinivasan 3:56
is. Yeah, that’s funny. Does it really improve through that process. I know people think it does, but I’m not sure it does relative to the cost of not using the pretty good product, versus whatever improvements come from the delay to harden it. I’m not sure if

Benedict Evans 4:12
it actually, I don’t know there’s clearly, there’s a sort of a process of you have to put it into a flighty jet. Yes, you don’t replace the avionics in a fighter jet every six months, right? Well, but, but, yeah, you know, that’s the kind of the core of it is the in the cutting edge of the innovation is for consumers, and then that flows back through to everything else.

Balaji Srinivasan 4:29
That’s right? Well, you know, he’s gonna say, maybe in China, you do, maybe in China, like, I think what happened with the consumer drones, they got good at quadcopters, and that’s led them to their new form. Have you seen e hang it’s like the Chinese flying cars. Okay? And, you know, I played this clip, like, a year, year and a half ago, and people said it kind of, you know, the teal one, like, we want to fly in cars. We got 140 characters. And I was like, a lot of people didn’t riff on that, but I was like, we want to fly in cars. We got them in Chinese characters. Okay? You. And the thing is, put that up there, people are like, that’s not a car. It’s, uh, you know, it’s a it’s a copter, right? That’s not a car, doesn’t have wheels, but it solved the problem differently, right? And actually, I think was one of your lines. It’s like, unfair comparisons are often the best kind of comparisons,

Benedict Evans 5:16
right? Yeah, I remember seeing a bunch of flying cars when we were at Andreessen Horowitz, I think Mark Andreesen, he said he was like, said it’s like, they’re all like houseboats, and a houseboat is a crap house and a crap boat. Yes, that’s right. And, you know, think having it, thinking of it as a flying car is like, the wrong term. It’s better to think of it as like a much a small, much better, much cheaper helicopter. Yes,

Balaji Srinivasan 5:37
maybe. But the point is that they now, their thing is, it stands for short hops, and like, city to city, where you fly over the traffic, and they’ve got this Uber was gonna do this, by the way, before they decapitated Uber, like, the low altitude economy was something they were thinking about. And a lot of things get, like, cut off in the West, and then they appear fully formed in China, like consumer drones, for example. You know, Chris Anderson, he was very early on drones, and that got blocked by the FAA. And so consumer drones were hobbled in the US. That’s why DJI arose in China. So lots of things get blocked in the West, and they arise in China because of that. Anyway, coming back up. So smartphones. I mean, I think you and Horace, did you simpo, I was on his pod a while ago. I think you’re two of the best. He’s also, like, European or something like

Benedict Evans 6:27
that. He was, he was at Nokia. I mean, there’s an interesting kind of like, information. Do you know him? Yeah, he’s great. He’s great guy. Part of it was, it was like, and there was a moment in time when there weren’t many people doing global who really understood this and were industry analysts and were able to talk in public, all right? Yeah. So there were people inside Nokia or Goldman’s or Bain or wherever, who had all the data, but they couldn’t publish your data, right? They weren’t allowed to say stuff in public, right? Or if they were writing analysis, it was analysis for public markets, investors or something, right? And so there were very few people who were like, knew that you could go and take Apple’s reports and make a chart of unit cells and make a chart of ASP and what ASP was right, or knew what RP was right. Now, there’s like an explosion of this. So there’s huge numbers. And particularly if you look at AI now, there’s like, 10 people who do a really, really good 200 page deck of every possible AI chart. Is that right? Interesting? Yeah. And so that whole thing shifted, but at the time, yes, it was me and Horace and like Ben baharin, were like, the only strata, yeah, exactly. They were like, you know, a handful of people who understood this and could do the charts, and are allowed to do the charts, and so that was sort of, you know, being at the right place, right time, got me a lot of attention. Yeah, it’s

Balaji Srinivasan 7:51
interesting. I think, like you and Ben Thompson, strategory, and I’m not sure, of course, had a newsletter, but you guys were newsletters before sub SEC productized. It sort of like Rogan was podcast before that became productized as a category. And are you in sub sect, or were you on Ghost? No, yeah,

Benedict Evans 8:12
no, you got your own custom I’m still on my old cobble together stack of MailChimp Plus member full plus Squarespace.

Balaji Srinivasan 8:19
Why don’t you? You You don’t want to move to something. It’s a pain to move. It’s a heavy lift to

Benedict Evans 8:23
move platform. And you sit and do the analysis, and you’re like, is this a good use of, like, a week of my time, right? Maybe, maybe

Balaji Srinivasan 8:31
it might be, at this point, subjects

Benedict Evans 8:33
pretty good, but, I mean, it’s your goal is a separate sub stack thing, which is, do you want it to be on your newsletter or your sub

Balaji Srinivasan 8:39
stack? Yes, that’s true, yeah, because it’s in platform, and you get the

Benedict Evans 8:43
advantage of, I mean, this is something we can talk about. You know, it’s Chris Dixon’s line of comfort, the tool state for the network, right? You go on sub site, they will get you new subscribers. Won’t Get You subscribers? Yes. On the other hand, they now they control who your readers are, and you don’t, which is always a network Well, used to sell mail out you do, but then, then they’re trying to get you to use their website and their algorithm to decide who reads what that’s true. So there’s always these kind of questions, like, do you want to go with the people who will give you an audience? And in exchange for that, they’re deciding that they’ll give you the

Balaji Srinivasan 9:16
audience. There’s always a trade off for the distribution. Yeah, I think ghost is another option. Yeah, and, and, I think

Benedict Evans 9:22
ghost and beehive are the two people use. Ghost

Balaji Srinivasan 9:25
is like, you know, I saw ghost when it was very early, and I just thought it was so good for what it was, like it was, I mean, not even for, it’s just a very polished thought through for an open source product. It’s unusually polished. John Nolan’s very, very good. It’s funny, you know, like on that, but there’s a bunch of things we can talk about. But the the whole newsletter thing, it’s sometimes there’s things that are, like newsletters or podcasts that are what I consider lowercase in technology, before they become uppercase. Like, for example, Odeo, you know, like what Twitter was. Twitter was a podcasting. Company before it became Twitter and the time constant, they just got the time constant wrong where you needed, which is hard to predict, that micro blogging would take off first and then it required, like, air pods and everything online for a long time. And maybe, you know, COVID before podcast really exploded, and the term was around in lowercase,

Benedict Evans 10:20
and even argue it needed, like, 5g or for something like, yes, you’re if you’re listening to it on the car, in the car, then you need a half fast enough

Balaji Srinivasan 10:28
network, yes. Bandwidth is a constraint, yes. And then the time works. So what do you think is lowercase today that’s going to become uppercase? Like, what’s up? What’s what exists in tech that people like, oh, yeah, that exists that that’s going to go big. I have some ideas. I want to hear yours.

Benedict Evans 10:44
Interesting question. I think there’s probably the answer. If I was a consultant and trying to whiteboard, this is, I would be looking around AI, because that’s a new platform. And, you know, there’s a lot all the white the old white space got filled in, and now you’ve got a whole bunch of new white space. So deterministically, there should be a bunch of those here, AI, which I’m sure we’ll talk about. Does feel very sort of mid 90s in that you’re like, mid 90s internet in that like, well, is this a browser? How do you use it? What’s it for? How would you get to it? How does this work? Where’s the value? Where’s the value capture going to be? I’m not sure that there’s like, maybe one answer is, like, I’m too old and I’m not, like, spending too much time looking for, like, weird, weird stuff around the edges. The last one of these that I spotted personally was she in which shine? Is it she in, or she told it she in? Is that right? Speaking people there, like, I haven’t worked out her TV assurance, that was an interesting one, that it was, maybe you could also say it was the last of the ones that you could spot, because suddenly, wait, what is this thing that’s at the top of the iPod of the iPhone App Store charts all the time? Oh, I see, yeah. Suddenly that thing exploded. And that’s like, probably the same, probably the largest apparel, pure play apparel retailer on

Balaji Srinivasan 12:04
Earth, yeah, and, like, Shein and temu, yeah, that’s right, they’re now getting hit with the tariff stuff. And, you know, yeah,

Benedict Evans 12:11
tariffs plus, plus a de minimis rule in the that’s only the US market.

Balaji Srinivasan 12:15
And that’s not, you know, I don’t know what fraction of their sales, yeah, it’s like a

Benedict Evans 12:18
third of their sales, or a whole quarter of their sales, or something. So that was, like, that was, like, that was, that was a thing that was interesting. I’m not sure there’s not, like, a new thing that I’m watching that I’ve noticed recently. I’m sure there will be, you know, I keep

Balaji Srinivasan 12:30
looking. So a few we were talking about the glasses, right? Like, I think smart glasses are sort of like the most predictable thing after the iPhone, and, yeah, that’s, I put

Benedict Evans 12:39
in a different category. I was thinking, like, what stuff that’s being used now

Balaji Srinivasan 12:43
that people haven’t quite noticed it’s been used yet, I see, well, I guess that glass is glass is definitely your next thing, sure. So I guess I would sort of bundle VR headsets, AR headsets, you know, like that, with glasses, and say that that’s just glasses are sort of the next version for goggles. But okay, so that’s one that we agree on, except the question is, as you said, is it gonna be watches or phones? How big does that get, right? I think, I think, you know, just like podcasts grew to mean, like a video podcast and so on. The robot dogs are interesting. They are fun to play with, and they’re getting way cheaper now, right? They went from the Boston Dynamics kind of things. So the home robot as a toy, I think, is probably going to become more and more popular, like a Christmas present kind of thing at first, right? Because I see kids playing with them, and they just love them just as a toy. And the, you know, it’s kind of like the robot dog, the drone as like a starting to become a, like a Christmas present kind of thing. I think that that becomes a thing. Um, and eventually, like we were talking about this at the museum of the future in the UAE, they clad these so that it doesn’t it’s not just like a skeleton of a robot dog, but it actually looks like an animal, and that completely changes your perception of it, right? Um, so I think that that’ll be a thing, and with respect to AI. And so let’s do, I mean, there’s AI, there’s Bitcoin, there’s China, there’s drones, there’s biotech, there’s actually several different areas that I’m tracking, tracking eventually, these various singularities, whatever, they’ll really actually singularities, in the technical sense of going to infinity, Curves, Curves, that’s right, yeah, with AI, there’s, you know, one way of thinking about it is like, now we’re two and a half years in, let’s say, let’s call the chat GPT moment, right? Yeah. And it’s interesting because it, I think what people really overestimated was how much it’s agentic intelligence versus amplified intelligence like that. To say you still have to prompt it. So prompting is like higher level programming. Number one, you still have to verify the output, and that means you kind of need to know what it is you’re looking for. For example, if it spits out a bunch of mathematical symbols in an area of math. That you don’t know, then you have to be Terence TAO to verify it. It might be gibberish, it might be real. Who knows, right? And so the prompting and verifying are actually the bottlenecks in many areas now, karpathy and I, you know, the Andrej karpathy, we were just having a discussion on this, like, a week or so ago. And the thing about verifying is, if you’re using the GPUs that we have built in and you’re looking at images or video or front end code, right, like, like a user interface, your eye can just instantly pick out and you can verify pretty quickly. So for that side of things, AI is quite good. Anything that’s images, video, your ear can also pick out audio right and front end. But when it’s back end stuff, right? When it’s like database code, when it’s like crypto, when it’s mathematical equations that you don’t have, like GPUs, you can’t just, like, hit it with your eyes and quickly detect it, right? That whether it’s whether it’s correct or not, you have to deep, read it carefully, right? So it can generate reams of text, but then you have to verify it exactly. That’s right. Maybe you have some thoughts on

Benedict Evans 16:05
that well. So it’s funny, I was talking to John baltweak The other day, and he said, Benedict, you think in slides. So

Balaji Srinivasan 16:10
that we do, we both think in slides. So I have a

Benedict Evans 16:13
slide, yes, and maybe there’s a, sort of a I’ll talk about the slide. And this is an observation around it. I think a lot of discussion of llms is sort of hunting for, like, what’s the right fill? What would the right way to conceptualize this? It’s like with machine learning, the right way to conceptualize it was, this is pattern recognition, and we’re still sort of hunting for the right way to conceptualize llms. The slide is that traditional software is deterministic and does things that are easy to explain to machines. In fact, automation, machine tools, selling machines, typewriters, adding machines, right? Things that are easy to explain to a computer. There may be things that are very hard for people to do, but they’re easy to explain. So it’s hard for you to drill a hole 100 times or to calculate a mortgage in your head, but it’s easy for you to write down the logical steps to explain how you do this. So that’s traditional software, like databases, data processing, the whole 1670s mainframe thing, machine learning is stuff that’s hard to explain to a computer. So it’s hard to explain why that credit card transaction is weird. It’s hard to move your hands or, yeah, it’s hard to explain why that’s a picture of a dog. You think it’s easy until you try and do it, and then it’s like you tried to make a mechanic, mechanical horse. It always falls over until robotics comes along. So that was machine learning. I also think that as a kind of quiz for you, do you think machine learning is still AI, or is that now just software? Well, so the way that I think there’s a process once it’s been around for a while anymore,

Balaji Srinivasan 17:33
it’s funny. So I think, like within the field, technically, the division would be machine learning would be, you know, everything up to linear logistic regression, and you know, SVMs, all that kind of stuff. And then right at the point you start doing deep learning, and you have large neural networks now, you start getting into what people would call modern AI. So ML is almost like the boundary of understandability, you might say, right where you can write, write clean equations and like, really understand what’s going on. And to me, the most surprising and confusing, I’m still, I still don’t feel I know the phenomenon is, but I still find it magical. Is something called the double descent problems. You know, that is basically normally when you’re fitting to data, you want to have the fewest possible parameters, because you can overfit right. And so your error goes down, and then your error starts going up on the on the on the holdout set. You train your your model in machine learning, and you want the minimum number of parameters to be able to explain the the training data and predict the test data, and if you overfit, then you’re no longer predicting out of sampled stuff. But double descent is when you do AI, you get actually a second wind when you start going to a very highly parameterized model, and the error actually drops again, right? And which is just a really weird phenomenon, that there’s papers on this and so on. And it’s one of the most counterintuitive things about the whole thing, that just having these gigantically parameterized models would generalize well, right? Because it violates that. That’s the biggest difference. Go ahead, there’s other things people might say is the biggest

Benedict Evans 19:20
difference. I think there’s, there’s one of the ways I sort of, sort of think about the term AI is that people kind of use it like technology. The word technology, yeah, that’s right, that anything new is technology, anything your parents

Balaji Srinivasan 19:31
had, is right, technology. I’m a stickler for precision, so there’s,

Benedict Evans 19:35
yeah, there’s different ways that you can say, what do we mean by the word AI? Yes, I feel like AI has almost become like the word Metaverse, where, like, you don’t show what somebody means when they say it. But to continue my slide, so this, the first point is as deterministic software, which is stuff that’s easy to explain, right? There’s machine learning, which is stuff that was hard to explain, which basic machine learning solve this. And now an LLM is maybe stuff that’s easy to explain to an intern. It’s something. If you had to go away and have a have a like a kickoff meeting, and spend half an hour working out how we’re going to do this project, then an LLM probably can’t do that, but interesting. But if it’s something that you could explain in 10 seconds or 20 seconds, then an LLM is going to be able to do that. And part of the problem is, are you able to explain it even to yourself. Could you explain it to another human being? Can you actually kind of shut your eyes and conceptualize, how is it that I’m going to explain what it is that I want this thing to do? It’s

Balaji Srinivasan 20:32
so what you’re saying is very important because, um, you know, the there’s, like, several different angles I can, I can, I want to take off that, you know, in one sense, I had this tweet. We’re living in the age of the phrase, right? So the the prompt for the AI or the 140 character tweet, or actually in crypto, like 14 words, 13 words, 12 words can be your, your crypto reset phrase, right? These, like, are phrases of power, right? In in AI, in social and crypto, right? Like this, strings of characters that do a lot, you know, and the spells, they’re spells, right? And the thing about it is the crisper you are as a manager, like, you know, if you’re, if you’re, if you’re a really good engineering manager, you’re great at prompting AI, because, crucially, you don’t just say, hey, code this. You say hey, you know, try and use, you know, react for this. You can use React Native for, you know, the iOS and Android interfaces. Use tailwind, use it. The more in a sense, vocabulary terms you have, the better you can prompt something with and if uses vocabulary terms correctly. And what that meant is, for example, I realized with Dall E, you know, when those first, before the chat GPT moment, I was like, wow, art history is now an applied subject, knowing, like Cezanne and Picasso and what, you know, these various kinds of obscure styles. Suddenly you can be like, boom. Style, it like this. Style, it like this, and it’ll do that,

Benedict Evans 21:56
right? You say the same thing for music, like, what exactly is it that’s being done there. I knew there is a word for that. So, and you can,

Balaji Srinivasan 22:04
that’s right, exactly. So you can upload a track, and you can say, What style is this? How do you caption this? Right? Ever seen, you know, like the restaurants with the fancy menus, and they don’t say, they don’t say tomatoes, there’s

Benedict Evans 22:20
a word, there’s things that are theoretically subjective, yeah, but there are within the prevention, there is a particular term for doing that particular thing

Balaji Srinivasan 22:29
exactly. It’s like, difference between, like, red versus burgundy, and, you know, crimson and what have you, they’ve got precise words which means something. And then you can summon greater precision with those precise words. And so what a way I was thinking about, you know what you’re saying is that I’ve written about this. AI is, like, undocumented APIs, right? So normal API, every function is, like, written out, and it’s like, you can do this and you can do that. And so I’ve got 20 functions. And here’s, everything is there, right? With AI, it can do lots of things that even the people who wrote it up. So there’s, it’s much more mysterious as to what it can do. You just have to try things,

Benedict Evans 23:05
right? So the way I was thinking about this, from a different angle, was to think about GUIs. Oh, yeah, yeah. What a GUI is doing, several things that a GUI is doing. One of them is it’s telling you all the features that the developers have created. And part of the reason that was a revolution is a you knew what they were, and you didn’t need to memorize keyboard commands, yeah. But B you can actually have more stuff because you’re not constrained by the number of keyboard commands that you can write down. So you can have hundreds of functions instead of like you can just put them more you can just add more shit to the menus, yes. But the other part of it is that the GUI is telling the user a whole bunch of accumulated decision and institutional knowledge about what the right things to do at this point would, yes, that’s right. And so if you’re in a workflow, as opposed to just a blank screen, you know, is one thing. If you’re in like Photoshop or Excel, yeah, it can prompt you on the prompt. But if you’re in a workflow in Salesforce, then there’s a decision taken. This is, I’m going to offer the use of these five options here, and not 750 options, yeah, and where the with a prompt? You don’t have any of that, so you’ve got to shut your eyes and think for a minute of like, well, what would I do here? And you don’t have that help. This

Balaji Srinivasan 24:12
is, you know, karpathy has talked about this also, but I do think there’s room for AI OS, right? Like, in a sense, and we can talk about crypto in a second, but I think AI and crypto are both actually operating system level innovations. And for example, it may be someone who just does an app or like, like a downloadable thing and just does as a layer on top of the Mac. But if you have the full context of all the actions that are happening on your Mac, you can suggest which apps to use, suggest which apps to download, suggest, hey, you probably want to change these keyboard settings and so, like, there’s, you know, it’s funny to put it this way, but Clippy is finally vindicated, Clippy, but for everything, right? And because Clippy can now be really, really, really, really smart, right? It like, you know, it was Anderson’s line. It’s like, everything in tech works. It’s just when, right and and even thing that’s interesting about the Clippy thing is somebody also made a point, which is that you actually want to put faces on your AI avatars, on your AI agents, so you could pick from Clippy or 10 other kinds of things, and the reason you want to do that this is counterintuitive, but people like you and I can use chatgpt and Claude and what have you, because we’re familiar with interfaces. But the reason they’re actually intuitive to 100 million people is they’re used to chatting with another human on the other side, so they’re already modeling the chat box as being a human like response, because they’ve been using WhatsApp or Facebook Messenger or Instagram chat or something like that for a long time, right? But when it’s outside of that chat box environment, and it’s like suggesting on the screen, you kind of want a face to pop up so they can associate okay, this person is suggesting this because that’s who they are, and they kind of map that personality onto the AI agent. And so you could choose from different kinds of clippies that would give you prompts on what to do, or just does it for you. That’s their possibility. But I don’t think people like it when it does it they want, they want to be able to approve it before

Benedict Evans 26:16
they do. I think there’s a sort of sense in here of how people conceptualize what this thing is and how it works. I remember John brother row at Google showing me a chart, a Google Trends chart of best versus cheap, best versus cheap, yeah, so the best does this and cheap does that. What are the axes crossing over time? So Google Trends. So what’s the frequency of the word

Balaji Srinivasan 26:43
best? So it starts with, like, cheap phones, and it goes to best phones, yes, and

Benedict Evans 26:47
so and so the thesis was that this was shifting from the internet as price comparison, where you already knew what you wanted and it’s at the top of the and that’s at the bottom of the funnel, to the internet as recommendation, curation suggestion is ever you’re looking for

Balaji Srinivasan 27:01
a death suggestion. So interesting. So let me see if I can understand the psychology. So when it starts

Benedict Evans 27:05
from 20, it starts from 2004 Okay, in 2004 you go on the internet, and you already know what you want, and you look for the cheap, what is the cheap x? And then you put in a scoop, where you put in a product or something, whereas over time, that goes down and best goes on, best goes up and crosses it. It’s a perfect X on the chart. Unfortunate and but in the thesis is you’re going further up the funnel. You’re looking more and more for I want some on the internet to tell me the best x or y where previously you’d have got that from the magazine or newspaper or

Balaji Srinivasan 27:38
something. There’s two or three. There’s two things about that. The first is, you know, Andy gross thing about the paired metrics. So Andy Grove, whenever anybody’s optimizing, like sales, for example, they will usually start recruiting. They’ll start by optimizing quantity. But there’s, you know, you can sometimes optimize quantity, and then quality drops off, right? So quantity is easy to measure. It’s like just the number of people we hired, or whatever. But quality is how good were they, right? And so that’s the second paired metric. Is usually a quality metric that. And so quantity is cheap, right? And people start with cheap, and then quality is best, and they go to Best. So that’s another lens on this a third lens. What I thought my explanation maybe it’s different than what actually happened was, when people are just trying out a space, they just want the cheap version to try it out. And once they’ve committed to a space at like, for example, the cheap digital camera, cheap, cheap drone, or something like, they want to try it out, right? And they want to try it at low cost, try before you buy. And then once they’re committed to a space, then they’re like, I want the best drone out there now, because I

Benedict Evans 28:41
want it well, the analysis then would be cheap drone versus best drone, right? But I think the that’s

Balaji Srinivasan 28:48
what I thought you were saying. Yes, you’re saying cheaper, so best overall, yes, but I’d love to see a category by category. I wouldn’t be surprised to see that happen category by category, but maybe not. Well,

Benedict Evans 28:57
there’s a different plot point there, which is sort of what I was talking about, one on in our panel this morning, which is His infinite product. So how do you know what to buy? Yeah, and it used to be that you’d start with a magazine, and then you go to the internet to find the cheap place to buy it, or, you know what you wanted. And now you go to the internet like, where’s that? What’s the what’s the right place to do this? So the Internet has become much more kind of a default. But actually, the thing that the thought that prompted me to that was you can also go and play with Google Trends. And I did a chart, played with like, how, why, where, what, like, more, kind of basic questions. And you really need to be inside Google to do that analysis, probably exactly. But it’s that sense of how much are people doing conversational queries into Google, as opposed to typing quote keywords into Google, and things that are not really a Google query, like what is a is not well, it probably doesn’t help Google, but you that’s still how people use

Balaji Srinivasan 29:50
it. People were trained for years to not to remove all prepositions, to remove all that stuff, and just do keyword ease. And now we’re trained the opposite, to write. Like full and complete English sentences, like, prompting is the new searching, but it’s a completely different, you know, behavior, right? Go ahead.

Benedict Evans 30:07
Well. So this is one of the there’s a sort of tangential point of that, like one of the, like, the early, easy, obvious things that people have deployed with AI, with llms on the internet, is different kinds of, sort of natural language queries. Or different, not so much natural language, but like, different kinds like different kinds of query. So that the canonical one people talk about is Walmart saying, now you can search for what should I buy to take on a picnic, which isn’t a database query, and for Google, for Walmart or for Amazon. Five years ago, that search just wouldn’t work, because unless there’s a product that’s like tagged with picnic, it’s not going to come up, whereas now there’s an LLM with a world yes, has some sense of what, how you might answer that question, yes.

Balaji Srinivasan 30:49
Is it a world model? It is at least a web model. It’s a different kind of query.

Benedict Evans 30:53
And yes, you’re not doing a SQL query, you’re doing something else.

Balaji Srinivasan 30:56
That’s right. And I think you know, one of the things that’s interesting is the computers are, we knew they were very good at that first kind of deterministic computation, the SQL query, the calculation, that’s what they’re built for, doing math, right? Yeah. And now they’ve gotten good at probabilistic kinds of things, right? So this would be like system one and system two thinking, right? Probabilistic is like the quick impression, and then, you know, this is like the logical calculation. So it’s actually good at the heart. The thing that’s harder for humans is the, you know, like, long and involved mathematical equation. Can do that errorlessly, and now can also do the other kind of thing. And so it does suggest that there would be some synthesis of that eventually, where an AI can, I mean, this is like aI tool use, or what have you. Like, it detects that it needs to go to system one and and it starts invoking Python for that. And this is getting better, but it’s surprisingly not amazing two and a half years in, right when it needs to go deterministic well,

Benedict Evans 31:55
so I wrote last long thing I wrote about this was about looking at deep research, which open AI launched. And one of the kind of traps in looking at the new thing is to test it based on what was important to the old thing. So, you know, to look at the Apple two and say, Does this match the main the uptime of a mainframe? No, so it’s useless. Well, no, but that’s not the right question. Yes. Can you write an app, build an Excel model on an iPhone. No, but that’s not the point. It can still replace PCs. And the reason I mentioned this is so deep research, open air launch this thing, and it’s whatever it was, $100 a month or whatever, so, but they look at the marketing page, and the marketing page shows it doing a research project about mobile, which, as we said, I know a lot about and he got the answers wrong. And it’s

Balaji Srinivasan 32:45
verifying. See, you knew, you could tell that it was wrong. Well, it looked powerful, exactly.

Benedict Evans 32:49
So this is the thing, and it got stuff wrong in several levels. People think remembering now what I wrote, like two months ago. And so there was a specific it was make a table which shows mobile, smartphone adoption in a bunch of countries, and then the operating system market share, and then this is like an intern teaching moment, because first of all, what does adoption mean? Does that mean, unit sales, share, installed base, App Store Sales like, what? What do you what metric specifically you asking me for? Yeah, then it had given a source for the number it had come up with, which was Statista. And Statista is an aggregator that steals other people’s data and republishes it. Yeah, and when you jump through a bunch of registration hoops, you discover that the actual source was, I think Kantar. It’s an ad agency. It’s part of group M it, I thought was part of one there. It’s consumer survey data. So it’s a proper, proper, proper company, yeah. So it was actual proper consumer survey data. But the two things so then, when you go to the Canton chart page, you discover that deep research had got the numbers, the opposite flip percentages, I see, and then it had also said it didn’t have access removed it from the website. Well, I see. And then the other source it gave was stat counter, and stat counter was just using the same wrong, which is a traffic measure, right? So that’s not going to tell you an option, because high end phones get used more and iPhones get used more so, and there’s a bunch of things in here where you’d like, this is what I’d expect from an intern, right? I would, I would go back and say, No, this is what I mean by adoption. And this is a good data source, and that isn’t right, and it’s like a great first version. The problem is a had to copy the number out wrong, which is not I would what I would expect from an intern, or at least not a good intern. But secondly, I’d have to be a mobile analyst to know any of these

Balaji Srinivasan 34:41
things. And that’s a verifying thing that was getting this is, this

Benedict Evans 34:44
is the kind of the core of it is, I all these people were looking at deep research and saying, this is fantastic for researching things you don’t know anything about. I was like, no, no, it’s not. Yeah, it’s fantastic if you need a bunch of material about something you know a lot about

Balaji Srinivasan 34:57
exactly. So that’s things. That’s why I think AI in its. Current incarnation is better thought of as amplified intelligence, because the better, the more you know about a field, the better you are at prompting, because you’ve got better vocabulary, and the better you are at verifying because you know more facts about it, and you have more cross cutting checks. And that is less true for the visual area, but just identifying that is a very important limitation, where you have a completely different system you can use for the visual stuff, which is just which is just your eyes, right? You don’t have to use the, you know, we have just different hardware for quickly seeing, you know, this way the hands or something like that. Whereas, if that was, it’s a monkey brain, it’s a monkey brain, exactly, right? So that’s now an interesting question. This is, you know, karpathy are discussing. This is, is there some way to turn some or a subset of the non visual things, into visual cues where you could see it was wrong immediately. So I’ll give you a small and simple example. Let’s say you generate an audio file, right? You know, like a spectrogram of an audio file, right? You could maybe immediately see if there’s some artifact there, right? That’s a trivial example.

Benedict Evans 35:59
So I think this, I’m, it’s a fascinating concept. I’m, I’m, I would wonder whether that’s the right

Balaji Srinivasan 36:06
split. Okay, it’s at least one split I found useful for now. Where do you think? Well, so the split I

Benedict Evans 36:11
was thinking was that the natural language generation to make text is perfect, so the text is always grammatically correct. That is true, yes, but the model underneath, like the facts presented by the nut in the text, might be wrong, yes, and that’s sort of deceptive to us, because we see the text is correct and it looks confident, yeah, that’s right, whereas in an image, like you ask it for a picture of somebody and Everything’s perfect, except the person’s got six hands. I’m not sure conceptually, what is it that that’s flattened? Is that you’re seeing two things in one layer? Or is it that,

Balaji Srinivasan 36:52
do you see what I mean? I see what you mean, I think? Or

Benedict Evans 36:55
is it that it’s a different level? Well, maybe, then maybe there’s a different point here, which is, if you ask for an image of a car, yeah, and the car, I actually did this, ask for a fantasy 1960s French sports car. It will look French. It doesn’t look like a sports car. It will have four wheels. It might have two steering wheels. Yes, that’s right. The two steering wheels is the equivalent of a grammatical mistake or spelling mistake in the text generator, yes, because, however, it may also be that the balance of the car is all wrong and it would flip over if it tried to go around a corner. But you’d have to be an automotive expert to know that, yes, I’m saying that there’s different levels of error.

Balaji Srinivasan 37:35
That’s right, we ask. What you’re saying is the two steering wheels is like a spelling error, but spelling errors are very rare for AI, whereas two serum reals is a common error, right? And I think that has to do with just the way diffusion models work versus how transformers work. That’d be like one high level answer I’d give where it’s doing, like, kind of it’s more local with the diffusion model, and you can be locally correct with the steering wheel, but globally incorrect, whereas locally correct with spelling is usually correct. That’s like, maybe one, yeah, that’s one answer. Um, the second is that, with there’s only a small space, I think, like, for example, we are optimized to recognize faces, so we can detect very subtle differences in faces. But if I gave you like, five different sheets of like, static noise, right? Even if there are very clear patterns, like mathematically like, these are all like, Fourier transforms of the same object. And this is one, they’re just like, total noise. To you, a computer would be like, these 12 are the same, and this one is odd one out, right? So in a sense, our eyes are optimized for a very low dimensional set of things, which are the things that occur in the real world, like those are the things we can pick out,

Benedict Evans 38:50
right? She’s also the our eyes are, like dogs are better at motion than us. Yes, even eyes are different depending on the species, that’s

Balaji Srinivasan 38:57
right. So, so, so because of that, we actually have a like because they can’t detect patterns in static. That’s like, too high dimensional space. I think text is kind of like that, because it can describe one of the most I mean, surprising things to me about how AI has evolved. We were asked, we were talking about this question before is, I was surprised you could get so much mileage out of pure text. The reason is so much Watson, so much mileage out of pure text, right? And the reason I was surprised by that is, you know, you think

Benedict Evans 39:32
even like reasoning, and all stuff that looks like reasoning,

Balaji Srinivasan 39:35
reasoning, and also spatial manipulation, like like picking like, like having cameras, having eyes, seeing the world, reasoning about it like a baby and so and so forth. It is amazing how much of that world humans have assigned machine readable labels to with text, and the way that you know, it just, is just very surprising how well that worked, like language, one of. Trying to say is in a few in like 40 words, you can describe, it’s like code. You can describe many, many, many different kinds of things in like 40 words, right? And and it’s just more general. It’s one of those things where, if you’re sometimes when you’re really close to a space, you’re actually more surprised by a breakthrough than if you’re farther away, and I should say, like, you know, even looking seeing all the style transfer stuff in the mid 2010s and seeing image Jeanette, and seeing the benchmarks and so and so forth, I was surprised that it got, you know, a Markov chain is, well, if you saw the stuff before GPT three, right? It was like, semi coherent, but it didn’t look like it was converging on something, you know. It just looked like, you know, it would repeat itself many times and what have you. And the fact that it broke through to what it did just based on language was so counterintuitive. And it’s, I think it’s because it’s such a high dimensional thing, it captures so many different aspects of the world, like anything you can perceive in the world, there’s a word for it. There’s many words for it, and then we also have billions of people who’ve been typing those words for two decades, right? So in a sense, like the entire internet, the video games and social media are like this bootstrapper for AI, anyway. So on the on the other hand, AI is very bad at spatial stuff. You know, this thing called Arc Francois Chile has this benchmark that, yeah, and so he is, he has benchmark actually got beaten by the recent, you know, you know, chat GPT release. And he’s got, like, a new one, and it’s, it’s almost like a tetracy kind of thing that’s got some degree of logic and spatial type stuff that AI finds it hard, but humans still find it easy. It’s kind of like maybe the next generation capture um, and it’s, it’s visual more than it is verbal, right? So for every reason, is it

Benedict Evans 41:58
something that would be hard to explain in words?

Balaji Srinivasan 42:02
Yes, I think kind of it’s about like this is here, and it’s almost like Minesweeper, you know Minesweeper, where you click and it expands and so forth. I think AI because it started with words. It doesn’t do well with the spatial side of things. Now, on their hand, what the Chinese are working on in particular, and is physical robotics. Obviously, Elon is working and so on and so forth. But China’s way ahead on the on the physical supply chain. So like physical AI is robots, and those definitely have cameras and XYZ and spatial and rotation and so and so forth. So there’s some eventual fusion, you know, like the self driving cars have gathered hundreds of millions, billions of miles at this point. So there’s some fusion of the web, which is words, and the world, which is, you know, spatial that will get you, like a completely, you know, maybe a fusion set where it can reason about the world as it is. It knows how tall Everest is, because someone, some robot, has hiked it, you know, like Google Street View, you might eventually imagine a bunch of humanoids walking the world just like that. You know,

Benedict Evans 43:08
I wrote a thing years ago about street view and Yahoo, and the sort of thing I was kind of poking away at is that basically every big internet system is a Mechanical Turk. And the question is, where do you put the people? Where does human where the humans? Yes, yeah. And with Google search, the people are everybody, a, everybody making a link on a web page, and B, everybody using Google. That’s true. Whereas with Yahoo, they tried to, like, have a bunch of people in an office, yeah, doing it in the mean, making a hierarchical list of all the websites on the internet, which was became impossible, yeah. And with Street View, you just pay a bunch of people to drive down every street in the world, which is actually not impossible.

Balaji Srinivasan 43:47
It’s just expensive. It’s expensive. It’s really it’s an interesting computation. It’s not obvious that it would be feasible to it’s funny, you know, the Yahoo thing, Yahoo, you know, I think got started in like, the early, mid 90s, right? I think 94 ish, 93 something like that. Yeah. And the thing about it is it like Yahoo had to kind of get to its limit before it was obvious that you needed something like Google because, like, web pages had to be suffused with at the time they put on page spam and so on and so forth. You had to kind of top out. You had to get enough web pages that the hierarchical model broke down. You had to get enough economic value that people really incentivized to game the system and so on and so forth. Before, you know, maybe Yahoo could have self disrupted. But before something like Google was there, Yahoo almost built out enough of the web economy to make something like Google necessary. You know, I anyway, so one thing I wanted to talk about, I’m gonna go through various other areas. But what is AI disrupted? What is AI going to disrupt? Right? So, what is it already disrupted? So search, it’s taken points off Google, share, you know, like stack over. Low. You know their queries are down image search, because now Image Search is image generation, obviously video obviously, many different kinds of specialty apps will, you know, things that are, for example, like various sales tools that make templated emails and things like that, those all you know, change. I’m not sure Salesforce. I mean, Salesforce is, you know, certainly they’re using AI, but the entire Salesforce model like spamming people with email, I’m not sure that’s gonna last in the age of AI, because you can spam so many of them now, right? So, so So those are some of the, you know, obviously robotics, obviously protein folding and whatnot. What is it going to disrupt that people haven’t thought about yet? And I can, I can give some ideas.

Benedict Evans 45:51
Well, I mean, one answer is, we don’t know. It’s the shark. It’s like trying to say that, ask that question about the internet in 1994 Sure. And the joke is always that newspapers thought the internet would be great because they’d save on printing and they

Balaji Srinivasan 46:01
at first, at first, probably good for them. Yes, they did.

Benedict Evans 46:04
Yes. I did a slide in my last presentation. I did because it struck me that people would always say, Well, you know, Uber didn’t sell software to taxi companies, and Airbnb didn’t sell software to hotels. They redefined what those things were. So I went and did a chart of, well, what happened to taxis versus what happened to hotels, actually, rather unsurprisingly, what happened

Balaji Srinivasan 46:24
taxing down is over, demolish his tax Yes,

Benedict Evans 46:26
yes. Lee, Airbnb is mostly additive to hotels. Why is

Balaji Srinivasan 46:30
that? I think this is Airbnb is a different kind of experience in a hotel,

Benedict Evans 46:34
not the substitutional experience. Yeah, it’s complimentary. Half of business, half of hotels a business. There’s another whole bunch of conferences. There’s a bunch that’s about like, I mean, just, you know, okay, so two examples, like, my fiance works for goes to fly to Milwaukee. She arrives in town at 10 o’clock at night. She needs a gym. She’s got a client meeting the next morning, and then she’s got her flying back to New York. She doesn’t want to go and stay in some random strangers Hotel, which she’s got no idea what it’s going to be like. She wants, you know, very specific brand promise from

Balaji Srinivasan 47:05
Airbnb. She won’t say no, she will stay in a hotel. She’s not

Benedict Evans 47:08
gonna stay in an Airbnb. The other side of this is, I think there’s a more general point. And same thing, I arrived in Singapore two o’clock this morning. I’m not going to go and work out whether this Airbnb is any good. Yeah, sure. I think there’s a more general point, which is that, like, everything is probably disruptive to someone at some point in the value chain, but it kind of depends on the industry quite how much and in what sense. So like, the iPhone demolished the existing cellular industry really have any effect on telcos. Telcos kind of hoped that they were going to do all these services, but that was never going to happen. But telco mobile operators today are basically the same companies that they were 20 years ago, with more basically the same share price, because their business was not in anything that the iPhone changed, except that they’re providing massively more data than they were in the past. But the business is basically owning sites and owning spectrum and connecting them up and selling that to consumers. The same thing with like online travel booking completely demolish the travel agent industry. Didn’t really change the airline business. Airlines had to do a bunch of stuff around loyalty and pricing, and maybe pricing became much more transparent and so on. But the end of the day their business is owning or leasing airplanes and front end change, buying fuel and owning landing slots, right, and maintaining the aircraft. And so there. Now, of course, the counter argument would be, you could have looked at taxis and say, Well, clearly that’s not going to get changed by the Internet. Except maybe you’ll be able to book a taxi more efficiently until it becomes long and changes it. But the point is, you can’t. There’s this sort of very naive view that says, Oh, well, this software will just destroy everything, right? Very and the answer is, well, it kind of depends. It’s pats moment. And I like one of the ways that I sort of think about this is that, like the tech industry, kind of comes and changes everything in an industry and resets how it works. How it works, and then leaves and goes off and works. And so, you know the joke about how consultants are seagulls, yeah, they come, they fly and fly out, right? And so if you think about what happened to books or music, no one in the tech industry cares about music anymore,

Balaji Srinivasan 49:16
right? Like, well, yeah, Spotify does that the main main main event.

Benedict Evans 49:21
Yeah, recorded music is like $20 billion a year. It’s like a branding error in the scale of the tech industry. It has no streaming means it has no strategic leverage

Balaji Srinivasan 49:29
for Apple or Google. Sooner is interesting, though, so the AI, yes, but, but.

Benedict Evans 49:33
But for a last 20 years, 20 years ago, the internet completely screwed the music industry, and since then, it left and doesn’t care. Same thing in books, like all the conversations around books right now, some of which are about Amazon, are book industry conversations. I think there’s something similar happening now with video generation and Hollywood. Like everybody in Hollywood, like got over the panic, and now everyone is sitting and looking at this and thinking, Okay, well, this saves a bunch of second unit stuff. So one way is better. All like com, all the questions for what does this mean? Are questions for people in

Balaji Srinivasan 50:04
LA, so one way of thinking about it is, conversation is proportional to derivative rather than absolute value. So let’s say you have a sigmoid that’s going like this, and then it flattens out, right? Yeah. So when it’s like a nullity or ubiquity, you know, when it doesn’t exist, or when it’s everywhere, when 0% or 100% it’s just not notable. It’s not worth talking about, right? People use Uber or Dropbox a lot more today than when they were talking about Dropbox and Uber a lot, right? So the conversation is maximum at the time of maximum growth, and then it’s just much less, because now it’s, like, not notable. It’s just a feature of the environment, right?

Benedict Evans 50:46
So you can do Google n grams, yeah, that show exactly this. I think that’d be a great. That’d be a great. You can do them for, like, steel or and some of these railroads, yeah, because it starts in 1800 and, of course, some of them, you look at it, you go, Oh, I’m actually seeing a chart of World War Two, where you see steel suddenly does that, or shipping suddenly does that. And

Balaji Srinivasan 51:10
that’s not obvious, right? Because conversations or like attention is focused on change rather than absolute value. Well,

Benedict Evans 51:16
I always used to do a I’m always used to be fascinated by elevators. I get these kind of autistic Autism Spectrum fascinations about things. And I there’s a chart I did of the number of people employed in the USS elevator attendance, which is a perfect bell curve. Oh, interesting. Yeah, it’s all curved up now. And in this is because first half of the 20th century you didn’t have any employed elevators, right? Second half of the 20th century, they become automatic. Right button, and you can go and find all this advertising.

Balaji Srinivasan 51:44
Why were they read the bean? Was it just like so short operators, I would say. What was it? Technical enough?

Benedict Evans 51:48
There was no but there was the well, if you think about what it actually takes to have an automatic, automatic elevator system in a building, you’ve got to have all the dispatching. Uh huh, oh, you ought to have the dispatching in the queuing, I see there’s an interim stage. We have an elevator attendant who would just stand in the elevator, and you would say, I want buff floor five, please. And they press the button for five, right? But if you get in, you know? And originally, what was it originally, before the buttons, there was a lever that’s an accelerator and a brake. Oh, so it’s like a car, exactly. It’s a street car,

Balaji Srinivasan 52:19
elevator, vertical streetcar. I didn’t know that.

Benedict Evans 52:23
So there’s a fantastic book I have called the cultural history of elevators, which is all about how weird this was. So it was a vertical train, yes, it’s a vertical train. Wow. And sense how people thought about it, yeah. And so an elevator train, you can kill people. And there’s this wonderful story I tell everybody, which is that you press the buzzer to summon the elevator, but it’s literally, you’re just ringing a bell and a light goes on in the elevator car. And there’s this story from the War Department. It’s like hailing a taxi. Yeah, there’s a story from a war department, or ringing for a servant. There’s a story from the War Department in DC, which is that you would buzz more based on how senior you work. So imagine you’re like a lieutenant, and you get into the elevator on the second floor and you want to go to the 10th floor, but on the way the buzz ring, it rings four times, in general, and so you have to stop at the sixth floor, right and go down to the first floor, and then a major gets in. So now you say, theoretically, this call attorney could be Friday in the elevator going up, and so interesting, and we don’t see any of this now. Which is your point about conversation? Yeah, you don’t get into an elevator now. And so it’s an it’s an electronic elevator, right, right, automatic, right. It’s just an elevator.

Balaji Srinivasan 53:37
It simply said something like, there’s a phrase, which is civilization advances as you can do more things without thinking about them like they quote, just work, right?

Benedict Evans 53:47
And the classic one is light people with, yeah, electric light gets cheap. Yes,

Balaji Srinivasan 53:51
that’s right. I think you know the age of internet now, sometimes what happens is these things get really ubiquitous and they’re out of the conversation. And then there’s this now, now that you can treat them as like at 100% adoption, then the new thing arises. For example, all of the craziness of the last 10 years is in part, a function of the fact that social media got such ubiquity in the early 2010s such that it was no longer the novelty was, oh, I’m on social media. I’m using it. How do I use this Twitter app? Or whatever? Everybody knows what Twitter is. Everybody knows how to use it. They know what A like is, whatever, whatever. And then you start getting the user, then you get the second order effects. The second order effects, that’s right. So it’s almost like, it’s like installing a device driver, and then you can install the next one and the next one. But it’s like, the device driver is the percentage of the population that’s adopted something, and once it gets to 100% or 90 something, then you can, like, I’ll give you an example. Like, during the pandemic, there’s just the assumption that everybody had a mobile phone, right? And they could QRS, code, scan the cellular ns. That was a really big thing. Right?

Benedict Evans 55:01
That’s how you’d show your QR codes working in the West as

Balaji Srinivasan 55:04
well. Yeah, that’s right. But basically, obviously, 10 years ago, you know, 10 years beforehand, they wouldn’t be able to do that. They would have to have some other paper system, or something like that. In 2010 you couldn’t assume everybody on the planet had a smartphone. It was getting big, but it wasn’t yet there. It’s certainly 15 years ago. Yeah, nobody would have it, right? So that was something where the ubiquity of something, maybe sometimes the next step is comes from that ubiquity, or ubiquity of two or three things at the same time.

Benedict Evans 55:33
Yeah. I mean, you could think about TV and radio, all forms of mass media in the past. And you know, the greater pop music requires recorded music and requires radio. And you know, the greater mass democracy kind of goes hand in hand with literacy and cheap newspapers, right? That you need newspapers before you can have other stuff has to happen, right for that to come. And then, of course, you have backlash. It was sort of think there’s something interesting in looking at stuff like the Arts and Crafts movement in the late 19th century, because he’s a bunch of people who say, we hate all this mass manufactured stuff, handcrafted things. It’s funny. That’s not a statement that would make any sense in 1800 Well,

Balaji Srinivasan 56:13
it’s funny because there’s this where you’re talking about like people were farmers, that are artisans, and are like, Oh my God, this automation is disrupting us. We hate it so much we want to go back. Go back to the old ways and and now it’s funny, is those manufacturing jobs that all these workers were so mad about in the late eight hundreds and early 1900s all the strikes, all communism and so on, those are now the things are looked back on romantically by a lot of mega types, where they’re like, Oh, that was such a great job. I wish I had that. I hate this information job kind of thing. I hate this, you know, these desk jobs and so on and so forth. So it’s interesting, because there’s a romanticization sometimes of the past thing, even as millions of people are exiting that for the next thing. Now, this is a little more complicated, obviously, by the fact that China has a lot of those, quote, manufacturing jobs, but yet, a lot of them are being automated in China as well with robots. So it’s funny, the thing that people were so mad about that they were getting seemingly pushed into, which was manufacturing, out of farming into manufacturing, are things that at least some fraction of this generation wants to go back to, or they think they do. You know, I think that’s

Benedict Evans 57:18
interesting. Some of those things. I mean, the Luddites are those, one of these sort of misunderstood movements, because a lot of what the Luddites are about is self employed high status artisans, losing that status and being pushed into low status commodity jobs. So this

Balaji Srinivasan 57:36
is going to be the big thing with I think, have you seen the elephant graph? So the elephant graph, and some people dispute the graph, but I think it’s probably gesturing at something that’s right. It shows percentiles or deciles of the world in terms of income, and it shows over the last 20 something years, I think, from 91 to 2008 or something like that, where the growth went like whose incomes rose, and basically, most of the world, so the lower 10% in Africa didn’t gain that much, but like, maybe from the 10 to 20% through the 78% had huge growth, then it drops off in the eighth 90% almost zero, and then picks up again at the very top right. And so that means is the like, global, you know, elite in every country did great, and so did China, India, Vietnam, Eastern Europe, all these countries are no longer socialist, communist, et cetera, right? But the Western middle class didn’t. And that is a big part of, I think, the silent inability now when we’re looking at it is, you know, in America, they have, you know, obviously red versus blue. But one way of thinking about it is starting in, you know, certainly in 2008 there’s a ramp where China flips US manufacturing, and so China puts all this pressure on red America, and that leads to Trump and trade war. And you’ve seen that, that graph of print media disruption right this internet suddenly rising after 2008 to flip blue America, and it takes all the ad revenue away. And it’s not shattered, it’s also Craigslist, is classified ads, bunch of other things. So the internet disrupts blue America, and that leads to wokeness in the 2010s I think, and also tech lash, right, which is the anti tech movement. So we look at it as red and blue. There’s also China and the internet over here, where the internet is disrupting blue and China’s disrupting red. So the thing I think that’s coming next is AI disrupts blue America, and robots disrupt red America. And so Chinese robots and internet, AI, and so that artisan movement kind of thing is going to accelerate, where people are going to be mad about that happening. I think on balance, there’s going to be a lot more productivity in the rest of world. But it’s possible, for example, that a job that’s at, let’s say, 200k or something like that in the US, and there’s somebody in India or Mongolia or Vietnam or something who’s at $2,000 a year. Sure that that equilibrates at like, 20k right, for like, somebody supervising medical results or something like that, right? Where the licensure is no longer as important. The western licensure, the Western State, doesn’t, can’t really protect it as much because it’s all on the internet, and that’s a boon for everybody who’s a customer of that. Like healthcare costs go down around the world. You’ve got a great doctor on tap anytime. Most people benefit from it, but those people who lost, you know, relative status, relative money in that get super angry. And I think the burning of the waymos and like the extreme anti AI sentiment that they see among some people is is kind of a precursor to that. Let me know your thoughts.

Benedict Evans 1:00:41
So I think this is a general observation that, like when Europeans live in Europe, probably the symbol of something similar in Asia. When Europeans live in Europe, we all feel different. So like Germans are very different to Italians and different to British people, different French people and so on. And when Europeans live in America, they all feel European, and America is buried is in a different place to the aggregate of Europe and the US has its own sort of political culture and political questions. Ah, yes, that are different to the questions in France or Germany or Britain. I do think some of what’s happened, and I don’t, wouldn’t call myself political analyst, but I think some of what’s happened is that, certainly in the US, to some extent the UK, there were coalitions, particularly there were on the progressive side or the left side, there was a coalition of urban, upper middle class, highly educated people with a certain set of social attitudes and working collar, blue collar, working class, blue collar people has been totally busted in a different part of country, right, often With rather different social and political attitudes. Yes. And the same thing, I think, in the US and the Republican Party on the right, you know, the Coalition of

Balaji Srinivasan 1:02:11
sort of Wall Street Journal, reading capitalists, yeah,

Benedict Evans 1:02:14
like Mitt Romney and military guys that that is split apart completely, and all of those, you know, center right, economically conservative, socially liberal. People who are Republicans kind of don’t have a political party anymore. And equally, people who were sort of slightly Bloomberg Central, you know, Bloomberg centralists, centrists kind of don’t have a political party anymore. And there’s a lot of those coalitions have kind of broken apart now, what you have in a bunch of European countries is because, partly because of proportional representation, is it’s viable to have half a dozen different parties and the US and the UK, because of the first past the post system, you don’t have multiple it’s never been viable to have five different political parties at different points in the spectrum, in the same way the US has got the UK has got this kind of weird hangover percent Liberal Party, which is no one’s ever been quite clear what it was for, sort of in middle, quote, un call the Liberal Party is, there’s an interesting sort of sideline there, which is the Liberal Party in the UK in the 19th century was one of The two parties of government, and it was socially liberal and economically conservative. But in the 19th century, what we now call economically conservative in the 19th century meant pro free trade and against regulation, right? Whereas now economically conservative is the other way round, yes. So all of those labels kind of shift and move and change in different things. It’s

Balaji Srinivasan 1:03:39
interesting Meg, I would say mag is arguably against, certainly against retreat, but they’re also against regulation. So it’s like half, right, but, but it’s finished saying I agree with you. Of course, the levels do change. Yeah, the

Benedict Evans 1:03:51
labels change. The Coalition is broke apart. Break apart. I think there’s always this tension in looking at progressive ideas and saying, because if you look at the last 100 years the social progress, progressive ideas have always won. Like nobody today says, like being gay should be illegal, like so you know, a little bit like what we were saying about AI a while ago today, you could deterministically say that what is woke today, in 30 years time, will be what every Rafa white conservative agrees with. Like, yeah, people have said that kind of thing. Theoretically, you know, maybe, maybe not. You also have these kind of overreaches around this, right? It does strike me that one of the differences between the US, US and UK politics is that what happened in the last in my lifetime, is that the right, for want of a better term, won the economic argument that state ownership and government control of the economy is bad, right? And the left won the social arguments that like, gay marriage is okay, well, it’s and. And so on. And in what happened in the UK was the right embraced that, and the Conservative Party is the party that brought in gay marriage in the UK, whereas in the left in the US, it’s kind of the other way around. The Republicans kind of Tony Blair sort of brought in kind of Yeah, and he brought in economics. Whereas what happened in the US is that the Republican Party in the US never kind of accepted that it had lost the social arguments.

Balaji Srinivasan 1:05:25
Well, it’s interesting. I think from 1950 like the moment of 1950 you do have something where, because communism fell, basically because Nazis was defeated, the world moved socially to the left, and then when communist, as communism was defeated, it moved economically to the right. And so thus, for example, like the immigrant billionaire or gay billionaire is like, in a sense, can be right wing. Well, they’re far well, they’re far to the left of 1950 socially, and they’re far to the right in an economic right, in a sense, of 1950 economically. Because 1950 Yes, the Soviet Union had 100% taxes, because it’s communism, but the US had 90% marginal tax rates. And you really couldn’t get rich mid century in the US. You could be a corporation man. You could work for NASA or GM, General Motors, General Mills, General Electric. But you’re sort of funneled, channeled into like these gigantic things. You had more freedom in the US than other places, but you’re still very stultified. It was too capital intensive to be an entrepreneur and so on. And then gradually with, you know, I think the transition was the mirror moment where that’s begun a decentralization arc, and history is running in reverse since that moment, but, and so I think a lot of things are happening this century that are like a reversal of things in the past. You know,

Benedict Evans 1:06:40
I think it would be interesting. And I have no opinion about this at all, but it would be interesting to ask, what is behind the growth in billionaires? Oh, is this an unlocking of a new kind? Is this a wave of company

Balaji Srinivasan 1:06:53
creation? So I have you see what I mean. Yeah, I do have these on this, which

Benedict Evans 1:06:58
is to your point, is, why are there new billionaires? Is that because there were a bunch of new companies, and there are first generation owners, and where did those come from? And certainly some of them came from Google. And you know, when a global winner takes all effects, and some of them didn’t, I don’t know. I mean, I I’m not sure how much value I can, I can kind of add to that conversation. There’s a bunch of kind of economic statistical questions where I was just not questions

Balaji Srinivasan 1:07:23
where I was just not at the time. I can give some thoughts on that, which is that has a U curve, right where, for example, like, who is the richest guy in the Soviet Union? Like, didn’t exist communism, you know, basically Stalin, you know, didn’t need money, because he could just requisition anything. Well, the Soviet

Benedict Evans 1:07:40
Union is kind of a bad example of creating billionaires. Cut the country up and gave

Balaji Srinivasan 1:07:44
it to 20 people. Well, no, well, it’s right, but that’s starting in the 90s, right? Then it wasn’t there was Russia then, right? But basically, the number of like, independently wealthy men who could do things in the US, for example, a lot of the great fortunes, the robber barons and and captains ministry, were forced into foundations. That’s why you have the Ford Foundation, Carnegie Foundation, Mellon Foundation, Rockefeller Foundation, because in 1930s Roosevelt didn’t want any other powers besides him. So he, you know, went after Andrew Mellon, all these people, Ida Tarbell, went after Rockefeller. And those fortunes were corralled and basically controlled by the state in these foundations, in the Soviet Union, in communist China, they were just seized, right? So basically, let me give the normal way of talking about this is, inequality is rising, and that’s terrible, right? Another way of thinking about it is, what is the state right? The state is, in a sense, it’s like all the people who are its citizens, and they kind of crowdfund the state, right? And the question is, are they? Do they have a choice in doing that? Can they opt out of that? Like, what set are they part of? You know, for example, if they’re on the Franco German border, can they call themselves part of the German side of the French side? You know, how about the Polish, the Polish German border, but that kind of thing, and how much does the state take, and how powerful is it? And mid century, because of mass media and mass production, the states were more centralized they’ve ever been in history. I can show a bunch of graphs on that. That’s not just, that’s a quantitative thing. So you had these Geiger states. You had fewer sovereign units on the planet than at any time before since, like, only, like 50 un countries say there’s, like 196 so things have decentralized since then. If you go backwards in time, you go to, like, Germany under Bismarck, you’ve got all these principalities. Go to France before the revolution. You have all these things Italy before garibaldi. You have all of these little, you know, city states and so on, right? So go backwards time and forth time It’s decentralized. And the same thing happens where you’ve got lots of fortunes, you’ve got lots of, you know, individual potentates and what have you right? So in a sense, like the world is sort of returning to what it used to be, with the big exception being China. I think China is the like the 20th century, centralized state that will keep scaling into the into the century. So anyway, the reason I just say that is I think there is something real going on, which is that the state is just take, capturing. Less of the wealth of its individuals. People are sort of breaking away on the borders of it and then being able to do their own thing. And so it’s like Elon, not NASA. It’s like Travis not not taxi medallions and so on. And there’s a good to that, where there’s a lot more room for individual initiative, but there’s a bad to that as well, which is then people don’t feel as bought in on the collective project, and they’re not like included in some guy’s thing. It’s not their thing. It’s not like America lands on the moon or it’s Elon, okay, fine, you know. And they don’t feel as bought in, right? So it’s complicated kind of thing. I think we’re gonna have to renegotiate all that stuff

Benedict Evans 1:10:30
in the future. I think there’s a letter to this outside, again, outside sort of US politics, which is that partly because the US, you know, the liberal the partly the nature of the US economy, partly because the US is a big domestic market, partly because the successful internet companies are in the US and have global winner takes all effects people outside the US for the firm of the first time, think, well, we’ve got all these giant company us, companies that are running stuff in our country. And that was kind of true for like General Motors or Coca Cola. It’s much more direct, but not really. Yeah, right. You know, General Motors sold cars, but you had, like, your own car companies as well. And IBM didn’t decide how you built roads or anything. And there’s certainly a sort of a, you know, you go to European events now, and there’s people saying, well, do we need our own Google? And one level, those are, like, dumb questions, but they’re dumb questions about, like, a real issue, which is, you have this other layer of stuff that you’re using which didn’t used to be globalized and used to be subject to local, democratic control, and now, well, it’s not likely how that

Balaji Srinivasan 1:11:33
works. Yeah. So actually, it’s very important. I mean, where you’re hitting on there is, I think, one of the core questions, and I’ll actually ask it in reverse, which is, are those American companies? Basically, is the internet American right now, on one level, you’d say that’s a weird question. Of course, there’s

Benedict Evans 1:11:48
two parts of that. Is, are they American? But also, is they’re not. They’re not in our country. If you’re Sweden, correct, or Italian, it’s not a Swedish company. That’s right.

Balaji Srinivasan 1:11:57
That’s right. So, so like, you know, my view is the internet is to America, but America was to Britain. It is like the version 3.0 and because the early Americans actually consider themselves as, you know, British, right, all the fun ways and stuff came from Britain,

Benedict Evans 1:12:15
and the American War of Independence is essentially a civil

Balaji Srinivasan 1:12:18
war, yeah, exactly. That’s right. So they had a people and they had a they had a land, but didn’t have a government, right? Because the government was in London, right? And when they when they had all three, they became Americans. They had a sense of self. And I think with the internet, we have actually a lot of tribes that actually have a people and a government, but not land. And the reason they have a government is they have a blockchain, they have a social network they have with moderators or forums, and now increasingly, they have, like an AI agent, or like a central Oracle or something like that, where it almost takes a role of like a god, which they all ask questions to, right? So you think of every large enough online community that has its own social network, whether it’s a discord or forum or something like that, its own cryptocurrency, which has its, you know, smart contracts and currency, and its own AI, which is sort of like its Oracle or search of all the community’s knowledge, right? And that’s like a digital community that actually has a fair amount of strength. And then, because you know where your communications happening are happening online, whereas your where your transactions are online, more and more of your wealth is stored online, like crypto is at trillions of dollars now. It wasn’t, wasn’t that 15 years ago is at zero, basically. And so the significance of these cloud communities, I think, is underappreciated, and eventually they’re going to be able to have enough money to crowdfund territory. And so the because attention between your primary identity is online, your social networks online, your currencies online, your information is online and then not being grouped offline. That’ll resolve, in my view, in terms of the descent of the clouds that land.

Benedict Evans 1:13:49
So it’s interesting. I mean, I am probably take a sort of more prosaic view of this, but listening to you talk, I am reminded of, like, distant memories of being a university and looking at social history. And, you know, there are a lot of social history is about the kind of the joining into groups, yes. And so the joining, I think, joining and, yeah, what is the sort of form of, sort of self? What churches? Yes. Why do people want to fund monasteries? Why do people form lay brotherhoods around the church? Why do people like, there’s a whole 19th century British thing of like, all sorts of social joining. Why do people want to join militias? And, you know, why do they want to form all these kind of former guild? Why do they want to form all of these kind of different social groups and social clubs and ways of getting together? And what are they trying to achieve? And some of it is about, you know, self defense, you know, or pretty not in a kind of military sense, but about, you know, forming your group to protect your group’s interest. Some of it is about establishing status. Some of it is about self expression and self actualization, you know, kind of classic Maslow Hierarchy stuff. But it’s not new to have. Lots of communities. What is new is that they’re not necessarily kind of physically like co located. Yes, they’re not necessarily centered around, I mean, things like women’s suffrage, you know, they’re not necessarily centered around a movement

Balaji Srinivasan 1:15:12
or some specific objective. I think they will be, I think they will be, well,

Benedict Evans 1:15:16
there may be, but we’ve had those in the past. You know, the Cornwall League, or women’s suffrage, all of those, veganism, slavery, anti slavery movements and so on. So those senses of, you know, social organization and joining and grouping and clubs in different forms, different aspects of society for different reasons. It’s kind of a recurrent pattern of human society, yes, and now it gets expressed, which is the sort of thing we always talk about is, you know, the in the internet is human behavior, and it expresses and channels it in new ways. And that’s everything from, you know, people being horrible on Twitter or doing terrible things on the internet, through to people forming groups, clubs and societies on Discord or Reddit or whatever

Balaji Srinivasan 1:15:56
it is, that’s right, you know, by the way, I have, I have an explanation, which you might find funny as to I used to wonder, why are people so crazy on Twitter? Why are they so crazy on social media? Because, like, starting fights and stuff just as a sidebar, I was able to explain it in the following way. You know, you know, the Unabomber in the early 90s, yeah. So he blow up all these people, yep. But, you know, the reason he did that was to get an op ed in the Washington Post, right? So he killed those people for the distribution. He killed all those people just to get his message out there. So when you realize there’s people like that, then it actually makes it more understandable. How many crazy people there are on social media. If someone is willing to kill all these people to get, you know, just his message out there, a lot of other people would be willing to be very nasty on social media to get

Benedict Evans 1:16:37
their message out. Yeah. I always thought a lot of it was about context collapse, which is sort of, actually, yeah, doesn’t mean Yes, yes. I felt like some of it was you don’t know who that person is, and you haven’t understood what they’ve said and what else they think. And you presume they think X. It’s like, it’s lossy compression. You kind of compress three paragraphs. There’s no sub clause, there’s no nuance. You can’t say, of course, I’m not a Nazi, and right now, some of it is also which. And

Balaji Srinivasan 1:17:02
in fact, they can’t take that for granted, because you’re not Yeah, well, yeah. Or basically they’re like, you know, they have no context on you. They can’t read 5000 posts. They don’t know where

Benedict Evans 1:17:13
to trust you. And so it is also just what says Morgan Housel, I think, yeah, Morgan Housel quoted me, and that gets endlessly re quoted where I’d said something like, like, the internet means that basically, you’re confronted with people who disagree with you, yes, and you all the time, and you didn’t realize there were all these people who, like, the particular thing I was found was weird was there were people who were like, very, very far left. There are people who are communists, and they’re like, you’re saying something that isn’t communist. And they’ll be, like, amazed. They were like, Oh, the thing was, always, I always thought was weird is like, I can I think it’s weird that you’re a communist, because at this stage, you have to be an idiot to become Yeah, right. But it’s even more weird that you don’t know that most people aren’t. Yeah, they’re like, shocked by it, like, amazed that anyone doesn’t agree with their tiny minority opinion. Yes, that’s right. A lot of Twitter was that it was like, You’re amazed that I don’t think everybody should own a car. You’re amazed that I don’t agree with I know, that I don’t necessarily share your opinion on every

Balaji Srinivasan 1:18:11
podcast. That’s right? And I think the way that’s gonna reconcile is you’re gonna get a lot more, I think smaller. I mean, in a sense, Twitter doesn’t exist anymore, right?

Benedict Evans 1:18:20
X, X is fragmented, and exactly,

Balaji Srinivasan 1:18:23
it’s a terrible moment, right? So Twitter no longer exists. There’s X, and there’s truth, and there’s gab and blue sky on left, and Mastodon and threads and and then the crypto ones, like far, caster, lens,

Benedict Evans 1:18:36
stuff went to things. It didn’t look like that. So stuff went to LinkedIn, Tiktok. Oh, it went to Tiktok. Yeah, it went to Instagram. And people make fun of LinkedIn, like, there isn’t a bunch of bullshit on trip, on on Twitter. But you know, the I realized that an awful lot of corporate people were sitting quietly using LinkedIn when, yes, didn’t feel that they could use Twitter.

Balaji Srinivasan 1:18:55
Yeah? Because basically, the funny thing is, it’s interesting. Something about LinkedIn means people are artificially polite. And something about x or Twitter, especially Twitter, I think even more than x, in some ways, meant that they were artificially negative, hostile, right? And the funny thing about it is artificially hostile reads to people as more sincere, like That’s to say, of the two. There’s something about the artificially polite, like, like, for example, a good review is not a rave review. A good review is, I love, you know, Ben’s book. It was great, but he could improve X, Y and Z. That’s like, the best review you’ll get. Yeah, you know, I mean, usually, whereas a hater will be, like, just, just complete crap on you, right? So the negative is generally much more negative than the positive is positive. And so when you see a LinkedIn style post, it’s often like, super positive, and it feels fake immediately. But people don’t apply the same filter. They think negative is real, but they don’t think negative could also be fake. I always like mental you know, there

Benedict Evans 1:19:56
was a thing that went viral A while ago, some surgeon who’d got it, yeah. They got a review, and it was like, he saved my life. He’s the most wonderful surgeon in history. It’s amazing. It’s wonderful. Four out of five stars,

Balaji Srinivasan 1:20:07
yeah, exactly,

Benedict Evans 1:20:10
exactly. Wow. What did I have to do to get five

Balaji Srinivasan 1:20:12
stars? Yeah, exactly. That’s right. Like, you know, I forgot to give the mint chocolate under the pillar or something. Yeah. Okay, so, like, you know, let’s do, let’s change gears. Let’s talk about just survey of tech, just things, you know, you could tell me you’ve been thinking about this, you have anything about this. So we talked about, like, gadgets. So we talked about, you know, the glasses. We talked about,

Benedict Evans 1:20:34
did we talk about glasses on the podcast or on the car? In the car, we

Balaji Srinivasan 1:20:37
talked about glass a little bit on the pod. But basically, well, tell me your thoughts on

Benedict Evans 1:20:40
glasses. So, yeah. So I’ve made this point a while, a bunch online. As far as I can see, like you have the VR experience. You think it’s amazing. It’s not clear to me that this, my base case of VR is that it may end up like games consoles. In that you see a games console, it’s amazing. Most people don’t buy it. There’s a portion of people that don’t understand that games is actually quite a small industry. In terms of number of people, it’s a lot of money, but a lot there’s like two or 300 million people play games console games. And so it may be that VR you have the experience. It’s amazing. You put it down, you walk away. Most people don’t buy it, no matter how good the hardware gets. I think it’s much easier to see something like what I’m wearing now, being a universal device at the level of a smartphone, clearly, we don’t have the optics for that yet. We may. It’s improving every year, though it is. Yeah, it is. The question is, it’s is that next five years time is that two years time is that 10 years, it’s not clear yet. Yeah,

Balaji Srinivasan 1:21:43
there’s a few people I know who, just like they almost subscribe to this space, in the sense of, they’re constantly just getting the latest glasses, usually out of China, and they’re just trying them out, right? Or getting prototypes. There’s various prototypes people are making, and this is something that I feel there’s some value in tracking, because it’s almost being ignored by the world right now it

Benedict Evans 1:22:06
is, because it’s like, it’s one of the hit that Gartner Hype Cycle thing, yeah, that’s bumping along the bottom and hasn’t quite happened. Yeah? Or it’s a trough after the hype of metabolic there’s a subset of that, which is okay, clearly, you want a wide field of view. Do you need to have something that looks like it’s 3d like it’s really there. So do I need to have glasses that could put something on the table in front of us that looked like it was there? And that’s radically harder, yeah, having a really good heads up display that could put a public that could put an eye that could put, like an iPad display hovering in front of me,

Balaji Srinivasan 1:22:36
I think, I think it helps a lot with things like repair. Like, you know, for example, you open the hood of a car

Benedict Evans 1:22:43
and, well, that, but that’s still a hut that’s, yeah, like a hovering label over the right? Versus, does it need to work in broad daylight? Does it need to have black? Does it be able to occlude a bright white table like this? Right? Maybe, maybe not. I think there’s a range of outcomes there where you maybe it ends up like a watch that it says to be, clearly to begin with, it’ll be a smartphone accessory just to have the Yeah, yes, yes. But does it end up like a watch where there’s hundreds of millions of people who have it, but the smartphone is the main device, right? Or does end up No? Actually, a couple of billion people are wearing this.

Balaji Srinivasan 1:23:14
Let me ask you another question. Does does a watch Top out and because the thing is, wearables are another thing that has huge traction, and it’s kind of like, there’s a lot, a lot, a lot we could fill this table, this whole room now, with IoT health stuff, right? Because there’s watches, there’s rings like the oura ring, there’s, you know, wristbands

Benedict Evans 1:23:41
like, because it depends, it depends on the question Is Nick Lee white like Mark Zuckerberg bought Oculus. Sorry, Mark Zuckerberg bought Oculus because he thinks this is the next smartphone. He didn’t want it to be a games device. Or, yeah, 100 million people using it. He bought it because he thinks this is the next box

Balaji Srinivasan 1:23:56
smartphone, yeah, because also he had been hit by the so hard, yeah. He wants to own the platform for sure. It makes sense.

Benedict Evans 1:24:01
So there’s I, my base case is that VR might be might crap out at 50 or 100 million people. And I struggle to see it being 5 billion. I can see glasses being a couple of 100 quite easily. Once it worked, the optics are there. I can imagine it being 5 billion. I think that’s harder, but,

Balaji Srinivasan 1:24:20
yeah, ar, ar slash XR is probably bigger than VR. But as we were talking about, VR is very, you know, the thing, new thing they’re doing with for controlling military drones, like, there’s

Benedict Evans 1:24:31
loads of vertical stuff where, absolutely, that’s gonna nail it, definitely, no question that’s right. So all the telepresence of, you know, the guy up the telephone pole, the guy on the oil and glasses, yes, absolutely, that will be a that is a thing already.

Balaji Srinivasan 1:24:43
That’s right. And I think, have you seen this movie? It’s called surrogates. It’s actually, you know, pretty good sci fi movie from, like, almost 1015, years ago. And essentially, like, people are like, they stay at home and they pilot a good looking version of themselves as a surrogate walking around outside. So you can take. More risks and so on, because if that thing gets in a car crash or whatever, nobody cares, and then they could just do another surrogate and a runner inside, right? So I do think, what are the use cases for, like a proper the VR, the VR, control of a remote thing. So it starts with, I think, drones. And have you ever done a VR headset with a drone? It’s an experience. You should definitely try it. It’s a wow moment, because it really does feel like you’re flying right, which is very cool and an interesting experience. So I think it starts with drones, but I think it eventually gets to something where you’ve got gloves and maybe an omnidirectional treadmill or something like that. There’s various kinds of things like that. And you are able to control a humanoid anywhere, right? So you control a humanoid, and you can, I don’t know, clamber up a telephone pole and fix something you and you’re training the AI as you’re doing this, right? You you could have a maintenance worker with skill in the art, you know, and we’re not there yet. It’ll be years before we’re there. But eventually you have all these humanoids around, where you can just go into this, like animate the suit, and start doing things, you know? So that’s a pretty important use case for VR, like physical telepresence. You have to nail a bunch of technologies for that, but I could go through the gloves. I could go through the haptics. A lot of those things are moving forward, right? And, you know, a lot of people are pouring money into this. That’s something I give a lot of credit to. Credit to Zuck for. He’s just, you know, he’s just continuing this, you know, like, I don’t know how many 10s of billions

Benedict Evans 1:26:28
of dollars have been put he’s probably put the thick end of 100 billion into that,

Balaji Srinivasan 1:26:32
something along those lines. Like, it’s 75 to 100 Yeah. I mean, they are actually selling a fair number of units now. It just hasn’t come close to keeping up with the spend. Yeah, the

Benedict Evans 1:26:40
sales that the sales are just bouncing along. It’s like, it’s not good enough to break out of VR enthusiasts. Yeah. And it’s funny, you go back to what you said about Twitter, there’s almost like a test, which is, if you say that something probably isn’t working yet, and you get a bunch of people shouting at you on social media, then that proves you’re right, because if it was working, they

Balaji Srinivasan 1:27:01
wouldn’t care. Yeah, that’s right. Well, so if you

Benedict Evans 1:27:04
went on social media and said, Nobody uses Tiktok, then people would just say, this guy’s an idiot. Yeah, go on social media and say, yeah, and there aren’t actually any consumer use cases for drones. You’ll get like, the 10 people who love their

Balaji Srinivasan 1:27:15
drones. Okay, there’s one exception, which I will argue with you on, which is crypto, yes, right. So that is something where people will say there’s no use for crypto. You will say there’s no

Benedict Evans 1:27:23
yes, but there there’s just a huge number of

Balaji Srinivasan 1:27:25
idiots on every side. That’s also true. Yes, right, that’s right. So, so Okay, so we did, so I don’t say there’s no

Benedict Evans 1:27:29
use for the use case of crypto. I have the most unpopular position possible, which, as I say, it’s kind of useful, but not completely useful, which means I get both

Balaji Srinivasan 1:27:36
sides screaming every Yeah, that’s right. That’s this perfect position. So actually, what has been Evans on crypto, then I’ll tell you about your encrypt.

Benedict Evans 1:27:44
Well, several answers to that question. One of them is, and this is sort of more an observation, which I hope you won’t tell me I’m wrong, is, like, there’s a bunch of clever people working away building, like all the tourists left. Like the whole NFT thing was all nonsense. Metal there, that’ll all the tourists left. The tourists and the Grifters basically all moved on to AI, yeah. A lot of them, yes. And all the kind of people trying to build content brands saying, this is all wonderful, or this is all bullshit, they moved off to AI. There’s a bunch of people sitting and doing, like, abstruse, very clever, very technical stuff. There’s a bunch of stuff working or being built that may work around a financial finance industry, around finance rails, around stable coins, various kinds of financial instruments, most of which is storing money or speculating in money or moving money around. Yeah, there is a thesis that you could build Instagram on this, that this is sort of an open source computer in which you could write software that consumers would use. And I have a bunch of questions about how that would work, whether that would work, whether you would need to abstract the open sort the crypto stuff away so that the consumers didn’t see it. And if you did that, then why would they care? Totally so and, but none of that’s kind of there yet, like there are billion scale consumer apps built on blockchain yet. So there’s a sort of watch this space around that. And then there’s finance side, which I think is sort of theoretically very interesting, but I struggle to get very interested in it, just personally, it’s sure not what I’m interested in, and I struggle to see ways that I could add value in talking about it. So I kind of pay attention to it. And every now and then I point out, like my newsletter on Sunday, I pointed to the Shopify and Stripe and ceiling coins here and said, like, there’s stuff happening here, yeah, and you should pay attention to this. And there’s people still interested in trying to build things. So if you’ve just written this off as all bullshit, you’re kind of wrong, right? But as a writer and an analyst, I haven’t moved it onto something that I feel I should write about

Balaji Srinivasan 1:29:58
totally. So okay, so. A that’s very helpful. It’s always helpful for me to kind of triangulate on an area, you know, the so here is my basic view. You may have heard me say this 12 years ago. I think this is still true. Crypto is good for transactions that are very large, very small, very fast, very international, very automated, very complex, or that need to be very transparent. And the reason for that is like, for example, a Starbucks swipe, like of a credit card is none of those things. It’s not very large or very small. It’s like a mezzanine transaction. It doesn’t need to be very automated, because you can just talk to the, you know a cashier and see your receipt. It’s not International. Both you and them are in the same room at the same time. It doesn’t need to be transparent. You don’t need a receipt on the blockchain for everybody to see, and so on and so forth, right? So the reason that people think about the coffee transaction when they think about crypto is one of the most common transactions people do. They pay for their coffee every day, right? So it’s like, I don’t know 10% of your transactions, 20% are maybe coffee, because there’s very few things you buy every day. Coffee is one of those things people buy every day. So where crypto really shines is the alternative forms of traffic. Actually, let me take your mobile example, right? The internet can do telephony, but that was actually the thing that was best served by the existing system, right? We still have, like, local telephone calls, right? You can still use a telephone network to place telephone calls where the internet shine was and telephone calls were sort of like mezzanine amounts of information, right? Especially local was like between people in the same country, wasn’t very international, where the internet shine was, for example, moving really large files like Dropbox or very small files like tweets, right? Being very international, like across borders, being very automated. So it wasn’t a human on both sides of the call, right? It shown, for, you know, being very transparent. You’re broadcasting the web page here, but it’s not a phone call, just between two people and so on and so forth, right? So that, I think is a good analogy where, like, yes, now today, eventually the internet took over long distance telephony, because that was Skype and then WhatsApp and what have you. But even still, today, telephony is well captured by the current system, right? And like the existing phone lines still exist. That I think is a useful analogy for crypto, where crypto, for example, if you have, if you’re a power user of money, right? If I want to receive or send a wire to a startup in Japan, USDC, I can do that in seconds, and then I can refresh the page. They can refresh the page, and they can see it’s cleared, right? Yep, that is a real use case. That’s international wire transfers from anybody to anybody with and by the way, the bank account setup also is instant, right? So think about what we’ve done. We’ve taken it from days to get a US and Japanese bank account set up to seconds. We’ve taken it from paying money to do that to for the for the transfer itself, to free. We’ve taken it from taking multiple days for a wire transfer to clear two seconds. And we also, by the way, the uptime, it’s not nine to five banking hours. You can do it 24/7 and you can do on any device, right? That’s a lot of improvements just for the important use case of international wire transfers. Right? Then you also have the digital gold use case, that one you’ll only believe in if, I mean, I can just point to the graph, Bitcoin is appreciated from point one cents per per Bitcoin to $100,000 so, like, there’s enough people who believe in it for have gone up 100,000,000x

Benedict Evans 1:33:31
right? Yeah. It’s also, I mean, digital gold. I think it’s also something that there’s a kind of country mapping here, because some of what you’re talking about is a much bigger problem in, say, in the US, yes, than it is in countries with less with different banking systems. Yes, some of it is SEPA. You guys have SEPA in Europe. You send the money for free. So also, this is a point about PayPal,

Balaji Srinivasan 1:33:51
but the SEPA works within Europe, though SEPA would not work for wire transfer to Brazil, for example. So you saw the same issue that.

Benedict Evans 1:33:57
I think there’s another point, which is like, I remember reading about people in Argentina, yes, literally keeping their money in bricks.

Balaji Srinivasan 1:34:07
Exactly, that’s right. So, so Argentina, Nigeria, Lebanon,

Benedict Evans 1:34:10
where you, you actually can’t trust your government,

Balaji Srinivasan 1:34:13
yes. And there are kind of places, a lot of places like that, yeah, unfortunately, yeah. There’s

Benedict Evans 1:34:16
also a bunch of places where nobody’s worried about that. They sent it for 100

Balaji Srinivasan 1:34:21
years, exactly. That’s right. So, so the more middle class stable and so on You are the like, basically, crypto is for the power user of money and the powerless, right? The person who’s like, reinventing what a bank account even is, and the person who’s just trying to hang on to a bank account. So it’s like a U shaped coalition, right? Similar to the people who actually benefited most from the global economy. Remember, I said is like the elephant graph, right? You had the basically 10th to 80th percentile the world who grew, and you had the top 1% who grew, and the the Western middle class didn’t, right? That coalition is actually also the crypto coalition. It’s like the people who are just. You know, internet, as Tim Ferriss put it, James, what’s his name? Jason Bournes of the internet, right? Like, just internet hackers who are just trying to move money, like, for example, I’ll give a concrete example. Brian Armstrong, you know, my friend, CEO of Coinbase. One of the reasons he got into crypto, he had a few different life experiences that led him there. One was actually lived in Argentina for a while, so he saw, like, what a failed state would be like. The second, though, was actually being an Airbnb an engineer. See, thing is, Airbnb, even still today, has the problem of transactions that are very large, very international, right? And and also very one time low trust, right? Because you’ve got, like, somebody from Denmark staying with someone from Japan, and it’s a one time transaction of maybe on the order of $1,000 there’s actually a fair amount of money, and, like, the wire system is simply not set up for that frequency of use between unrelated parties, and so there’s a lot of friction on something like that. And to a surprising extent, Airbnb had a lot of forex risk, like, you know, because they had to hold currencies and all these different things. And the thing you thought was a solved problem, like just moving money from one country to another. It’s like, well, Airbnb has to do its accounting in USD, but it’s got income in, you know, if they’re an American company, they’ve got somebody transferring money from Denmark to Japan. There’s three currencies in that transaction, just right there, right? So there’s at least three currency pairs which fluctuate, and you’ve got at least two or three banking systems and all the delays and fees, you start to see if people are like, wow, this sucks so much. We need an Internet first banking system, right? We need something which is payments as packets, right? So that was the second thing that motivated Brian to do it, right? There’s other things as well, right? But so where would I put crypto today? Right? I’d say there’s at least three applications. There’s more, but I’d say the least three that are at the trillion or multi 100 billion range, and those are a digital gold right? Just whether you believe in gold or not, like that’s that’s there. People do people, people do believe, even if you just consider an insurance thing that people are doing is thing that people are doing, that’s right. B is, it’s like, even if you didn’t believe in luxury cars, that’s a market, right? So, there’s a market for it, right? Okay. B is international wire transfers. I think stable coins are now there. At this point, there are now one, 2% is two. $50 billion is trillions. Stable coins have passed visa. They passed MasterCard, right? And then third is actually crowdfunding, right? So if you look at the largest crowdfunding of all time, most of them are crypto, and the reason is the capital formation online, like, if you think about something like Kickstarter or what have you, it’s actually more geographically limited and more limited by the credit card rails than you might think. For example, it’s not that easy for somebody in Brazil and Japan and India to put 5000 bucks into your Kickstarter, right? They the credit card rails being accepted. Maybe fraud hit?

Benedict Evans 1:38:01
Go ahead. Yeah. I was just to say, I wonder, with some of the there’s a certain amount of swapping paper for paper in some of that, go ahead. Well, in the sense of, here is a new crypto project. Yes, a bunch of people who’ve speculated, Oh, totally made a bunch of crypto money, for sure, put their paper gains in Bitcoin into this new crypto. Yes,

Balaji Srinivasan 1:38:22
that’s right, that’s right. But, but, but, I’d say you’re right. A bunch of it is like that, um, which is what a lot of nfts was, yes, that’s right. But, but even if we, even if you’re totally right, what was funded off just the mechanic of crowdfunding, yeah, shows that that mechanic for capital formation, what they spent it on, I would agree with you, many of those projects didn’t go somewhere. Some of them went really far. Like some of them went really far, like Ethereum was a really that paid for all the rest, in a sense, even if all the ones went to zero that was so successful, um, but, but just the mechanic of capital formation where you have so. So that gets me to number four, right? If you look at now, you may, you may start disbelieving. So at least those three markets, gold, wire transfers, crowdfunding, those are very large markets. Those are 100 billion dollar, trillion dollar markets. So then you go to like other cases. Now, if I just look at trade volume, right crypto today is actually the number four stock exchange in the world in terms of volume, number one, ns, number two, NASDAQ, number three, Shenzhen, number four, crypto, and it’s rising fast. The thing that has held it back for almost 15 years is the doing the obvious things was pathologized, meaning it like, literally yesterday or like, like a day or two ago, we finally fully legalized, very clearly legalized, putting $1 on chain right now that we can put $1 on chain very clearly, such the point that Amazon and Walmart are like, okay, Congressional legislation is perfectly good. Let’s go time right now we can finally put an equity on chain, and we can put a fund interest on chain. We can put every paper kind of thing on chain that is a very big deal, right? That means that. Crowdfunding thing I talked about says that an internet company can issue internet equity, and anybody in the world can be part of that cap table, whether you choose to accept them or not. Is another thing but the capital formation mechanism. It’s now possible for somebody in Japan or Brazil or Mexico to invest in your company, once you have internet equities, internet capital markets that is now within sight, now that we have the stable coin thing, boom, done, there’s nothing, you know now. It’s just a mechanical thing to get the legal system going, to make the on chain equities work. And there’s already work on that. So that is a big deal, right? Because the US doesn’t want to be the center of global financial empire anymore, right? It’s like it’s very conflicted about this, but with the tariffs and the trade war and, you know, tourist visas, work visas, student visa bans and so on, it like is very conflict about whether even wants foreign money coming in to America, right? And they’ve got remittances, taxes coming up, like one for 5% so US financial markets, I don’t think are going to be there in the same way by 2035 I think Chinese markets are rising. Chinese stocks are rising. That’s going to be one thing that’s there. But I think the internet capital markets will take over from American capital markets. And that’s a very, very big application. Let me go through a few more. Is this interesting? So far?

Benedict Evans 1:41:16
It’s interesting. I mean, I

Balaji Srinivasan 1:41:18
think about, I mean, we’ve got numbers now. Yeah, there

Benedict Evans 1:41:22
was a thing that I was going away from microphone we were chatting about in the car this morning. I have a sort of a mental Venn Diagram of like, stuff I’m feel I can add something to Sure, stuff that I feel I understand, and stuff where there’s an audience, yes. And the challenge I always had in writing about crypto, this is, like a kind of a practical question as as an analyst, is all AI, all kind of crypto questions? It felt like they were either very, very technical conversations about it was kind of like writing about learning. So yes. And I actually always think that, like crypto reminds me a lot of open source, yes, and you are either it is open source, yeah. But in just in the sense of the general movement, it was sort of, it reminded me a bit of, like, either I write something about, like, the new kernel memory management thing in Linux, where I don’t understand it, and the people who do aren’t interested in what I’m going to say, and no one else cares. Yes, it just, it gets better, right? Or it was like, imagine what will happen when it’s like, talking about open source in the early 90s. Imagine what’s, what is going to happen when software is free and there’s not, there was, I’ve struggled, and it’s actually, it’s a it’s a thing I’ve also had writing about AI because I want to kind of, it’s not, it’s not a specific sure what you think about this is what I’m most good at, I think. Or the stuff that I write, that people seem to like most, is kind of talking about the product strategy of, how is this going to work? Who’s going to win, who’s not going to win? How is a corporation or consumer going to buy this? What would you do with it? Right? And I struggled for a while to set to write about our NS on that point, because it was either like, what are the 30 new papers this year? Yeah, or like, this is going to transform humanity, right? And it was kind of in the

Balaji Srinivasan 1:43:10
middle, is in the weeds, or super macro, super,

Benedict Evans 1:43:15
kind of Messianic, but not much about, like, product strategy in the middle. And I have the same challenge in writing about crypto, in that it’s either very, very technical, okay, I’ve got something for you, or it’s, yeah, imagine in 30 years, okay? Or it’s about finance where I don’t, you don’t care that much. It’s not just that I don’t care. It’s like I would have to spend six months to get to the point that I know what all the acronyms for moving money between banks are totally talking about them. So I’ve never like seen well, is that, is it? It’s in a completely different analogy. It’s also like talking about chips. You know, Should I, should I get to the point that I understand what’s going on in chips? Is that a good use of my time? Would I be able to say anything of value there? And I, so far, I’ve kind of felt, no. There’s a bunch of people who know way more about that, like the semis analyst guys

Balaji Srinivasan 1:44:02
have got it so, so let me, let me actually empathize with you in a certain way, which is, I was actually a very late user of social media, right? I only got on Twitter in like December 2013 Okay, which is like, like a decade. Hello Boomer. Huh? Hello Boomer. Exactly. That’s right. No, I mean, the thing is, I got onto Facebook very early because it just was, like, moving around universities or what have you, at the time, but I didn’t really use it. And the reason is that until 2013 I essentially believe that there was absolutely, I was just a very private person, you know, just like, you know, it’s weird, because I now post a lot, or what have you. I was just very private person, and I never, I didn’t give any public talks until late 2013 and so on. And, um, I just thought social media was a complete waste of time, and all that mattered was genomics and math and, you know, like, like, heart. Like, what people call hard tech now, like, I was doing genomics and robotics, and I’m, you know, proud of that work. I think it was important stuff. And I didn’t see the utility in tweeting my breakfast. And I didn’t see the utility in just, you know, petting each other’s fur, which a lot of what people do on Facebook or whatever, you know, right? So I didn’t see the value in any of that, um, and it was only once all of that was what bootstrapped the space, all of the fur petting got hundreds of millions of people on there, all of the breakfast tweeting and so on. Until what actually made it useful and interesting to me was I saw somebody tweeting a summary of a genomics conference at Cold Spring Harbor that I didn’t have the time to attend, and they gave a much better account of it than any layman would have. It’s like, you know, like someone tweeting a mobile thing, and you’re like, oh, that’s those are really great details, and you’re skilled in the art, right? And, and then I was like, Oh, wow, I can get, like, really detailed information here. Okay, now this is valuable to me as a reader, right? What’s my point? My point. My point is, I think the parameter that you want to track when you’re looking at crypto is block space. Have you heard that parameter before? Okay, that is the most important parameter in crypto that people outside crypto don’t realize. Governance crypto, block space is to crypto what bandwidth is to the web. So if you think about the early internet, or the early web, I should be more precise, in the 90s, like it was very bandwidth constrains, 28 857, six modems. And so that’s why, like, Google was 10 blue links, and I think Amazon even had many images at all. And in fact, you remember six degrees, it was a social right? So that was a text based social network, and didn’t take off, because without images, people didn’t really You gotta share exactly right? ICQ was a chat app that did work. AOL and some messenger worked because that was just text that can be sent. That low bandwidth thing. It was only in the 2000s that you started to get more graphical things when bandwidth increased. Like Facebook, the reason it took off at Harvard. Everybody had a t1 connection being at Harvard, and they finally had digital cameras so you could have photos. And as digital cameras propagated out, so did Facebook, right? And you go further and further and like, you know, the internet only, or Internet Explorer only, got disrupted by Firefox in like, the late 2000s right? It was only really by the early 2010s that you had the full JavaScript stack of like jQuery, and then only later for React and what have you. So this concept that we have today of like a mobile web app, where you can download JavaScript and run an app in the browser on a phone was a vision in the 90s, but it took a long time together because bandwidth had to increase for that right? So what’s the analogy here block space? Basically, block space is the amount of storage that you have on a blockchain. Like, think of a blockchain as like an armored car for data, right? Because this is data that people want to corrupt, right? In a sense, if it’s a file on disk, it’s important to you. If it’s a file online, it’s important to others, and if it’s a file on chain, it’s really important to others, and it’s so important that they might try to screw with it. And so Bitcoin came up with, like an armored car for data, where you could guard the minus one or plus one of who had what Bitcoin. And over time, that block space increased so that you could do some basic smart contracts on Ethereum. And now it’s increased enough that you can blast millions of stablecoin transactions a day on like base and Solana, and so on and so forth and so. So you should conceptualize it as, oh, why hasn’t this happened yet? And instead, think of, okay, these applications are gated by the amount of block space, and so they’re coming online similar to the amount of bandwidth you had, like text only apps, then you had images, then you had videos, and like Netflix only did streaming video in like, the early 2010s right? I mean, that we think about all that is recent.

Benedict Evans 1:48:45
I don’t know that’s a way of thinking about it. Yeah. I don’t have problem with the idea that you couldn’t build Instagram on this because the infrastructure isn’t fast lock. Space wasn’t current. Yes, yet. I think there’s a bunch of, like, interesting conceptual questions around, well, what would happen when we got there?

Balaji Srinivasan 1:49:01
Yeah. So, so here’s a few things. Well, there

Benedict Evans 1:49:04
will be also kind of, your sort of speculating five years in advance,

Balaji Srinivasan 1:49:08
yeah. So my view is, I’m not sure if it’ll be exactly Instagram, you know,

Benedict Evans 1:49:15
I think we can be sure it wouldn’t be exactly right. Just kind of conception, what is the app you could build, consumer applications you could use. I mean, this is the phrasing I remember you using years ago, that one should think of. One should think of a blockchain as a distributed virtual machine. Yes, and it’s another layer. It is, that’s right. And every layer of abstraction is always slower and crapper than running on the bare metal, except that it allows you to do a bunch of stuff that you can’t do if you run on the bare

Balaji Srinivasan 1:49:45
metal. That’s exactly right. That’s exactly right. And thing is, blockchains are, in a sense, one of the frontiers of operating systems research, like in the same way, like there’s operating system like Windows, there’s a browser, which is itself an operating system, because you can run apps in it. It’s got a. Programming language. Like, that’s how Chrome

Benedict Evans 1:50:01
were you at a 16 Z when Martin casado was there? Yeah,

Balaji Srinivasan 1:50:05
we overlapped just a bit, and we invested a bunch of things

Benedict Evans 1:50:09
together. Yeah. Well, Martin had this great observation. You remember when YC said that, like, for a quarter of their companies, 90% of the code was written with AI, yeah? And he responded to this by saying, yes, but if you write an iPhone out, 90% of your code is written by is written by Apple, yes. So there were all those levels of abstraction. Prompting is just a higher level of programming. That’s right. Yeah, exactly. And so there’s a the, I suppose the you know, another way of answering your question is, like, the finance stuff is there? I can see it. I get it. I’m not sure I can add any value to that. It’s interesting. And I would tell people, it’s kind of interesting to this, I think you’ll be a leader the running can the building more generalized consumer applications on it is conceptually more more interesting to me as something that I could make money telling other people about, yes, except that it isn’t happening yet, and it probably will at a certain point, the curve will tell it. Curve up. The block. Space will expand, the stuff will get faster and cheaper, and can store more stuff. And people, you will be people will be able to build stuff on this deterministically. It won’t be exactly Instagram. I think that’s just kind of a useful mental model for thinking that you could build a consumer that, yes, build consumer network apps like that on this at that point, then I think you have a bunch of kind of new interesting questions like, Well, is it a good idea to have a social network where all the users have a vote? What would that look like?

Balaji Srinivasan 1:51:29
What problems does? Right? Yes. And well, daos, are that already?

Benedict Evans 1:51:33
Yeah, exactly, which struck me the other day, that all the arguments against that are basically all the argument and saying, No, you need a CEO in charge. It basically all the same arguments to say, No, you don’t want mass democracy. You need you need a king, and

Balaji Srinivasan 1:51:44
you can have some balanced representative democracy, right? So you have the vote, and they vote for somebody, for

Benedict Evans 1:51:50
constitutions, which, again, like look at Africa to see how Latin America, to see how mixed constitutions work. I’m saying

Balaji Srinivasan 1:51:56
representative democracy, where you have a leader, but they’ve got a fixed term. And for

Benedict Evans 1:52:01
example, all of that stuff is fascinating. I it’s like, we don’t have it yet, and I no one’s going to pay me to go to a conference and give a presentation. Totally, so it’s kind of tough for me to write about.

Balaji Srinivasan 1:52:12
Yeah, totally, I will say. All just say is to put on your radar. If you go to like, snapchat.org, or vote agora, there are actually very large treasuries where all that voting stuff is happening on chain, cryptographic voting, and so and so that’s that’s growing, like stable coins. Kind of people that ignore stable coins for a while just kept compounding. So the on chain voting stuff is there. But what I will say is that I think, just like I was, like a late adopter of social media, since I just it, had to get to a certain level of significance before I cared about it. For the kinds of things I care about just, I think the kinds of people are interested in crypto are either A, they’re engineers and they just like the developer, they’re power users. B, they’re financiers, right? Or, in some sense, financiers, or day traders, whatever it is about the high and the lower and then C. And the part we didn’t say is just like they’re political, right? It’s like a political motivation. It’s like kind of being, like being a Protestant or a Catholic, they have a certain world. He’s also very open source. Yeah, that’s right, exactly. So, so, like, I have that, you know, we both like enterprise, SAS type stuff, product type stuff, that kind of discussion and but I also like a bunch of things. And you like, you like art museums and things like that, which I’m like, Okay, that’s cool, you know, go have fun, right? And so we have, we have our own Venn diagram kind of thing, right? So, okay, so switching gears, I think you’ll be more interested in crypto as block space increases and once crypto wallets. Let me actually give you an example of something which it’s used for, useful for right now, where the block space increased enough, you know, open router that that allows you to try a bunch of different AI models, and it just use a crypto to pay for all of it. Okay? So this way you don’t have to have 500 different accounts at 500 different because there’s so many different AI models, you don’t necessarily set up accounts and all that stuff, right? So just takes all that account setup process and you just have one account, you pay crypto, and it settles it with

Benedict Evans 1:53:54
all these other guys, right? There is a kind of completely tangential thing that just occurs to me as you were speaking, is, you know, ala Marina as this distributed voting system. The thing I always thought would be interesting would be to flip that and say, Can you pass a double blind test? Yeah, you take a model that’s on the top 20 Marina and give me a bunch of responses. How many people would pass a double blind test to know which is which? Well, the thing is probably some kinds of question you would tell very easily, an awful lot, I bet most people

Balaji Srinivasan 1:54:24
probably wouldn’t. So the most fundamental one would be, like, what is the private key to this or, like, basically, what is the private key to this wallet? That’s something that depending on how it’s set up. We were talking about this in the car. But basically, another major use case for crypto is AI makes everything fake crypto makes it real again, because AI can fake all kinds of stuff and give you this very convincing thing on, like the deep research thing, where it said 40% of the phones or whatever you saying, but it cannot fake the private key, so cannot show a non zero Bitcoin balance or non zero Ethereum balance without actually having the cryptographic solution there. Yeah, but

Benedict Evans 1:54:59
it could probably. Me just tell you that the balance is zero, because it might be, yeah,

Balaji Srinivasan 1:55:03
sure, sure, make it up. But what I mean by that is, like, for example, all kinds of, let me give you, you know, CAPTCHAs, right? Websites. So AI can bust a lot of CAPTCHAs. Now, it can get through. It can, am I a robot? It can figure it out, get through. But if you had to log in with a crypto wallet that had $1 in it, or $10 or $100 AI can’t fake that. It cannot fake the possession of that cryptography, right? Like to give you one. Here’s one motivating example for why crypto will get maybe this argument will convince you, maybe not, but it’s fine. You know, Google login, you agree. Is it billions of users, right? But Google login, when you log into a website, you only can log in basically with your email address and the permissions to your Google account. There’s something very obvious that somehow, even Google, with all of its strength, has not been able to implement, which is an international balance, a spendable balance, right? Google login could not have, for whatever reason, a spendable balance across different countries. They’ve solved that for Google itself, where everybody can pay Google and subscribe to Google and subscribe to Google with a zillion credit cards in all these different countries, but somehow they couldn’t make it work so you could log into a third party site with a spendable balance. Crypto did solve that. Just that alone means that every Google and Facebook login will eventually be either augmented or replaced by a crypto login.

Benedict Evans 1:56:19
So I’m gonna pick up something you said, which I you mentioned, which I mentioned in the car, around what’s fake and what’s real? Yeah. So if you’re buying an apartment and well, so going back a step, like I think most of what most people follow on Instagram is no longer their friends. It’s interest graph. Yes, that’s right. And so do you care if that photo is a photo of a real thing or not? Sometimes you really do and sometimes you really don’t. Yes, and I think that’s kind of interesting. It’s a sort of Gen, not so much generative search as generative content. Exactly. If you’re decorating your apartment and you want a mood board, and you can specify some styles, and you can say, I like this and this and this and this, and it gives you more and you look and you say, Oh, more like that, or more like this. It doesn’t necessarily matter at all. If those images are real. It does if like maybe you want to buy that table and it that table doesn’t exist. It just looks like those kinds of tables, or it looks like those kinds of chairs or whatever. But if what you’re looking for is, no, I want to be more like this or more like that, and you keep going until you get a mood board of exactly what you want. Doesn’t, may not matter at all whether those images real,

Balaji Srinivasan 1:57:33
that’s right. So if it’s Pinterest on the one hand, then just inspiration or what have you. But if it is

Benedict Evans 1:57:38
shoppable, then maybe it does, unless you it’s then there’s an extreme case here, which is, just send that dress to she and she, and we’ll make it

Balaji Srinivasan 1:57:45
for you. That’s right? Or, let’s say, you know, there’s some photo of a fire somewhere, right? And quite a lot of times people will post photos of fires, and it’s from, like, some concrete example, the Brazilian fires from a few years ago. There was, like, a fake photo, like, from that, that Macron tweeted out because he, he was told was a photo of the Brazilian fires, but someone was able to show that it was actually like a, like a, I think it was like a Reuters image or something, but from a photographer who had died years ago,

Benedict Evans 1:58:13
yeah, it wasn’t that image. Well, this is the funny thing about people complaining about deep fakes. It’s like, we don’t The problem isn’t the picture. The problem is the label.

Balaji Srinivasan 1:58:20
This the label exactly, that’s right. So, so the thing is that with with crypto, you can do what I call chain of custody, right? Blockchain of custody, where you can have a camera, and by this is also important in scientific work as well. There’s this huge replication crisis with all these labs and data, and you fight the data, yeah, exactly, or something, right? So you could have, you know, something called pre registration of studies where, like, if you’re doing a study, you have to describe, in some places, who you’re doing, it on what you’re doing. It’s like, monitored to make sure that people report the results whether they’re positive or negative, right? So let’s say it’s, you know, it’s a study, or it’s a camera. You can have, like, a either crypto software or hardware in there, such that when the frames of images are recorded, they’re instantly hashed and put on chain, either directly or as a digest of some kind, right? That basically is like tamper proofing, such that before the data is even like collected or analyzed, this internet connected thing is doing something. Now it’s possible maybe to hack the firmware and mess with that, but it would be pretty hard to depending on how you do this, can be pretty hard to do that.

Benedict Evans 1:59:27
You also have this on, you know, Google and so on, trying to watermark generated images. The challenge is, if the image isn’t watermarked, that doesn’t that won’t stop people believing it true.

Balaji Srinivasan 1:59:38
That’s right. But I think over time, this type of stuff, where it’ll gain traction at first are crypto oracles for prediction markets, because if you’re making a financial decision, I don’t know if you’ve seen that stuff. Alex tab Rock has talked about this, when people have money on the line, their partisanship reduces, and they actually get a different chip in their head where they’re like, is this true or not? They’re trying to dispassionately figure it out, right? They’re not just cheering my tribe, your tribe, whatever. And the is this true chip basically means, okay, I’m going to double click into this, I’m going to verify this, I’m going to look at this. And that’s where like oracles come in. They’re like, feeds of data that have some degree of verification. And right now they’re like, mostly price data, but people use it for weather data. They use it for this side and the other, right, all these different feeds of information that people trade on. And over time, I think those feeds, once you can guard price data, weather data, you know, health data, etc, eventually you can guard any kind of data, and then now you’ve got, like, a chain of custody for data like the scientific data, rough, you know, rough off anyway. Why don’t we? We should. We should wrap. But this is actually awesome conversation. Anything you know, what’s your latest stuff? What should people go and check out?

Benedict Evans 2:00:46
Anything? Well, I’ve been publishing a newsletter every week since 2013 and I always welcome more subscribers

Balaji Srinivasan 2:00:52
to that. You should write. Where is it? Is there gonna be a Ben Dick book, Google, Benedict Evans, my

Benedict Evans 2:00:56
parents had good SEO. Book. Is interesting. I’ve had publishers approach me every now and then about doing a book. I have to work out what it was. It would actually be and why it would be worth reading.

Balaji Srinivasan 2:01:05
Honestly, if you just, I don’t know, maybe a history of tech like, because all your slide decks are very good, right? And there’s one of the things I learned from, you know, my friend novel like the nivalmanac, right? Yeah, that sold a million copies. Why did sell million copies? I was surprised, but he was surprised by that. It was Eric Jorgensen. Went and curated novels, old content, and turned into a book. And I was really surprised. I was like, Wait a second, isn’t that all available on Twitter for free guild? Or didn’t people already see it? They did. However, if you say, what is the one work that represents like the best of novels thought over years, you know, just to see his latest tweets is not the entry point for that. You want to kind of collect all of them, sort them, filter them, organize them thematically, style them, and so on and so forth. And I think you could have a pretty good book if you do that. Let me know.

Benedict Evans 2:01:54
Well, that’s one thing on the list, and yes, the other thing is, I used to do an annual presentation. I’ve now shifted my cadence so I did a new AI presentation last month that I published, which I was just in town to present. And then I will do another one in the autumn, the fall for American listeners, great on a sort of E commerce, advertising, marketing, brand, like all the other stuff that’s being transformed by AI right now. And in general, what do I do? I try and work out what’s going on and how to explain it and how I can explain it, and then I go and do presentations and speak at events and talk to companies, and I do slides for money, basically.

Balaji Srinivasan 2:02:32
Well, that is similar. I do a lot of slides too. I do a lot of speak. So, you know, I’ve mentioned the cloud communities thing, and materializing those cloud communities, so that’s what I’m working [email protected] like networks. Network school. So if people are interested in this kind of stuff, we talk about that there. So subscribe to Ben Dick’s newsletter at, is that Ben dick evans.com Ben Ben dash Evans, Ben dash evans.com Okay, great. And, and then if you want to check out network school, come to ns.com Sure.

Benedict Evans 2:02:58
Benedict evans.com is another Benedict Adams, no, who is a photographer, really? And so my profile picture is taken by him, because I used to get his email. This is, this is, obviously, this is a blockchain use case. There’s a contact form on my website and he won’t sell to you. And I redesigned it. I don’t need to ask. I redesigned my website recently, so it’s clearer who I am. But it was quite, quite generic. And people would go to the contact form and they would say, hey, Benedict, we really liked your work photographing Harvey Keitel, would you like to go to Mexico next week and take pictures of Robert De Niro? And I would look at it. That’s so funny. Forward.

Balaji Srinivasan 2:03:30
Well, you know, it’s funny. You know it’s funny. There’s actually probably as maybe even more Balaji string of Austin’s that are but it because there’s like 12 people, last I checked in, like the SF Bay area alone with my first and last name, you know, so just I feel your pain. Okay. Well, this is great, really great seeing you in a while, and we should just more. Yeah, great. Thank you, sir.