Autonomy has been promised, and, you know, the big white supremacist in chief over at Tesla has spent 10 years promising this and not delivering. I do think there's a level of sort of deep naivety in the understanding of how complex the world is outside of Silicon Valley.
When you have a hammer, everything looks like a nail. You treat everything like this big machine where the inefficiencies... At a human level, there is something enduring which I, for one, believe lasts.
We have gone through very big transformations before that changed lots of stuff. And those were also very big and very new and very scary and changed everything.
Welcome back to Humans in the Loop. The world is in chaos and I continue to try to make sense of it. So, I'm excited to be joined today by rational sense maker, tech analyst, and former A16Z partner, Benedict Evans. Benedict, welcome to the show. Hello.
Benedict, you say on your website that you try to step back from the noise to work out what's really happening. So, what is really happening in the world of tech right now?
Well, that's a nice big broad question. Well, so I think, you know, at a very high level there's two things happening. One of them is all the stuff that we were excited about before LLMs started working is still there. So, e-commerce is sort of 20% of retail. In the UK it's sort of 40% of non-food. Roughly half of all video viewing is now streamed. YouTube is a Netflix or bigger go-to than the BBC in the UK. So, all that stuff is still going on and then the people are thinking about drones and quantum and VR and AR and 3D printing and robots and all that kind of stuff. So, all that good stuff is still there.
Meanwhile, there is a platform shift and every 10 or 15 years there's sort of a new paradigm and the whole tech industry gets reshaped around that. And the new paradigm is generally sort of 10x bigger than the one before. So, we had mobile and before that the web and before that smartphones and PCs and mainframes. And so now AI is the thing. Now, there's a not very productive argument about, oh, is this only as big as the internet or mobile or is it some sort of category cap, some kind of different category of change, which doesn't seem to be particularly productive. But the core of it is that this is everything that anyone in tech is interested in and excited about right now and so everyone's building around this, as presumably most people who will be listening to your podcast will kind of know.
What is it that you think people are not talking about enough right now? Or because, you know, I know your latest presentation was entitled, you know, 'AI Eats the World', as I guess is a follow-on from 'Software Eats the World', and AI also kind of eats all conversation around tech at this point as well. So, I'm interested — we will definitely get into talking about AI, but what are the non-AI topics, should we say, that you're thinking about or you think we should be thinking about more right now?
Well, so non-AI topics, and you know, e-commerce continues. It's funny, there was a, you know, during the pandemic everyone suddenly did the chart showing e-commerce spiking up and a bunch of people didn't understand the numbers and did the chart badly and it's now gone all of us back onto the trendline. But the funny thing about that chart was it was like the most boring chart in tech because it just went up like one percentage point every year. And so, you know, e-commerce is 25 years old and it's 25%. And it kind of grows at that rate. I mean, it's accelerated a little bit but it kind of grows at that rate. But of course, once, you know, there's one thing when it goes from 2% to 3% to 4%, it's another thing when it's 25 or 20 or 25 or 30% because that kind of reshapes the entire retail industry, commercial real estate, high streets, property taxes.
Another thing that I think sort of popped up and then disappeared is the rise of what's variously called retail media or merchant media. So, Amazon did 70 or 80 billion dollars of advertising revenue in the last 12 months. Walmart is building a giant ad business. Walmart is buying a smart board or smart TV company. Most of Instacart's — almost all of Instacart's profits come from advertising. Uber is building an advertising business. So, that sense — so like the four biggest media owners on earth are Google, Meta, ByteDance, and Amazon. And so that's kind of an interesting thread.
Autonomy has been promised for 10 years and, you know, the big white supremacist in chief over at Tesla has spent 10 years promising this and not delivering, but, you know, Waymo is out there deploying and building. So, as I said, all this stuff, all that stuff is kind of still there and still happening. I think if one kind of brings that back to AI, there's a slide I have that says something like all AI questions have one of two answers. The answer is either 'no one knows' or 'how did it work last time'.
And so, how did you deploy — so, you know, obviously there's a broad class of AI questions where anyone honestly doesn't actually know what's going to happen. Like, most obviously, how far do the models keep scaling? Like, we don't know. We don't have a good scientific sort of understanding of why these models work so well and why they scale so far. But the other side of the question is, you know, how should we buy this? How should we build this? Should we hire Accenture? Should we build it ourselves? Should we buy it off the shelf? How do we find the first use cases? How do we train our people? What does change management look like? And the answers to those questions are sort of, well, you know, maybe not so much how did cloud work, but certainly how did mobile work? How did PCs work? How did the web work? And there's a sort of a very direct parallel between someone saying, you know, we gave everybody Copilot and our productivity didn't seem to improve, and someone in like 1998 or '99 saying we gave everybody in the company a web browser on their desktop and internet access and productivity didn't seem to change.
Where it's sort of we're having those sort of old-fashioned conversations around how does technology deployment work? How do consumers adopt new technologies?
You've framed the AI shift here as kind of a platform shift and you kind of pointed to those historical examples. I guess there are a lot of people keen to paint a picture that this is not just, you know, another platform shift and that, I guess as they have said every time in history, like 'this time is different', you know, and here's all the reasons why. And yeah, I'm curious what you make of that argument. Like, do you see this time as being different?
So the problem is it's different every time. And, you know, part of the point of the, you know, the line, you know, 'this time is different' is every bubble is different. Like the dot-com bubble was different from every previous bubble. If this is a bubble now, it is clearly, whatever it is, it's clearly different to the dot-com bubble. You know, we're not — you know, we built out fiber in advance of demand. This is being built out behind demand. We, you know, the funding for the dot-com bubble came from retail buying IPOs of non-profitable companies and that's clearly not what's happening now. So every bubble is different, every technology shift is different and also every technology shift is sort of 10x bigger than the one before.
So when, you know, sort of PCs launched in the late — arrived in the kind of late '70s when they were still called microcomputers. And, you know, sales were in the sort of hundreds and thousands of units, in the low single-digit thousands of units. And when Marc Andreessen kind of kicked off the consumer internet — like, well, Netscape kicked off the consumer internet in '94, Netscape and Mosaic — there were like, forget the numbers exactly, 40 to 50 to 100 million PCs on earth. And half of them were shared, and then you had one at your desk at work and one of them at home. So, there were like less than 50 million households that have a PC in the entire world. And today, something between 5 and 6 billion people have a smartphone.
So we kind of forget that like stuff like this — there have been other big changes. You know, here we are recording this by video in a web browser for free. Remember when video conferencing was like — you say 'video conferencing' and you just spent $50,000.
Although I don't agree that's still the case in some places.
Well, yeah, that's a sort of a separate conversation, but like, you know, we kind of forget that like smartphones are kind of a big deal.
Like, there's 5 or 6 billion people in the world who have a device that's several hundred times faster than the PCs that we grew up with, connected to a broadband network with access to all the world's knowledge, and everyone is like, 'yeah, whatever'. But this is a big deal. That wasn't a big deal. Like, I don't think it's particularly productive to try and quantify this.
It is just kind of worth pointing out we have gone through very big transformations before that changed lots of stuff. And those were also very big and very new and very scary and changed everything.
Now, maybe there's another answer to this question, which is, okay, fine, this scales all the way to AGI, and if you define the outcome of this as something that will change everything, then it will change everything. And if you say, look, this is going to go to something that can replace humanity, is that a bigger deal than anything else that's happened before? Well, yes, by definition. You've just defined this as something that was a bigger deal than anything else that's happened before. Fine.
But the problem is we don't actually know that. And I think the most interesting difference between this and previous platform shifts is that we understood the science and the kind of physical limits and what could reasonably happen in the next 2 years for mobile or broadband or the internet or PCs or whatever. Like, we knew how Moore's Law worked. And we don't have a good theoretical understanding of how this works. So, we don't know what it will look like in 5 years' time. You know, you could kind of draw a line on a chart and like you didn't know that Yahoo would collapse and be replaced by Google, but you kind of knew that like PCs were expensive and telcos aren't going to give everybody in the world fiber broadband tomorrow.
Whereas with this stuff, you know, it could be that we have a paper tomorrow that says, 'Hey, guess what? We managed to get double the results for like 5% of the compute.'
So, we don't know where this will go. I think there's a sort of an observation one can make here, which is that that's kind of binary in that there's like an urban legend from the Cuban Missile Crisis. That there's a rumor that the missiles have launched and everyone starts selling on the stock exchange and somebody goes out and starts buying. And he says, 'Look, it's binary. Like either the rumor is true, in which case we're all dead anyway, or it's not true, in which case the stocks are cheap.'
And so, the situation here is like either this stuff is going to scale all the way until like it becomes actually massively or more intelligent than people in every possible way, in which case we've got bigger problems to worry about than middle-class employment and enterprise software.
Or it doesn't, in which case let's get on with thinking about software employment and, you know, how e-commerce and advertising works.
Yeah. Yeah. I mean, I come back from — I was in Switzerland last week for a sort of event of sorts at which a couple of researchers from one of the frontier labs, I'll leave you to decide which one, presented a presentation entitled 'Hypercapitalism: The Default Path for the Next 10 Years'. And, you know, the vision of the future that they laid out involved, you know, recursive self-improvement applied to software — you know, software writes more software. Then sophisticated AI applied to robotics, and then self-recursive improvement to robotics, i.e., robots start building better robots, factories start building more factories, and then at some point in this chain of events, there was robots deploy themselves into space and start building a Dyson sphere around the sun to mine the sun for energy. And, yeah, there was no sense of, I guess, questioning irony or even doubt in these researchers' minds about that being, as they called it, the default path of humanity. But I suppose to your point there...
Yeah, you're making predictions where we don't have any theoretical basis to say whether this will or won't happen. Like, we don't actually know how these models work. We can't draw a line on a chart that says — and we also don't know how human intelligence works at any kind of really useful level. Like, you can say, you know, it's neurons and synapses and, you know, here are the chemicals, but we don't know why our brains produce things that dogs' brains don't produce. And so you can't draw a chart and say, 'Well, people are here and dogs are here and octopuses are there and ravens are there and ChatGPT 5.6 is here and, you know, in 17 and a half months at current rate of progress, it will get to people.' Like, we can't do that. We don't know that.
And so then you get into all these very not very productive discussions where people say, 'Well, imagine if it was nuclear weapons.' Well, thank you, it's not nuclear weapons. People hunt for analogies. And then people say, 'Well, maybe this stuff...' you know, so people argue about whether or not it might be able to do XYZ. None of these are productive conversations with predictive value. You're not going to be able to prove what will or won't happen, except by developing some better theoretical model of how LLMs work, and at the moment we don't have that. So you can just wait and see what happens.
I do — there's a level of sort of deep naivety in the understanding of how complex the world is outside of Silicon Valley and outside of your research labs. And I think there's a level of, you know, setting aside, you know, AGI, AGI, there's a level of naivety in understanding the difference between 'I can make something that looks quite like a good legal brief' and what it is that a lawyer actually does.
And there's a sort of a narrow criticism of the model that says the legal brief isn't very good. The more important criticism is to say, but drawing up the legal brief isn't actually what the lawyer does. That's just part of what the lawyer does. And so if you go back and look at — again, you know, going back to this — we spent the whole of the 20th century automating accounting and yet we have more accountants every year for the whole of the 20th century. And why is that? And it's not just the Jevons paradox, which is just price elasticity. If you're an associate or, you know, an AP at PwC today, you're not doing exactly what you would have been doing in 1970 but more. You're doing a whole bunch of other different stuff.
And when this gets to the extreme, this gets to these sort of attempts to define AGI as like anything that can do X% of like productive human labor. Well, go back to 1800, a tractor can do 110,000% of productive human labor. You know, 90% of the earth's population were peasants. Okay, we've automated that. We automated 90% of what people did. Great. Then it turned out there was other stuff. And so there's an awful lot of sort of very dumb extrapolation and people waving their hands and saying, 'You don't understand exponentials.' Well, great, okay.
What is it that makes you think a line on a chart with a log scale has predictive value?
Mhm. Mhm. I'm curious to sort of square the circle with your job as an analyst because I guess one way I would interpret the title of analyst is, you know, that you're being paid to have some sort of predictive value of the future here. And as you said yourself, it's very hard and maybe not that productive in certain areas to try and predict the future. So...
Yeah, no, the job of an analyst — your job as an analyst is not to predict the future. There's a sort of dumb YouTuber comment who says, like, you know, I say, 'Well, this might happen or that might happen or that might happen,' and they say, 'You're an analyst, you're supposed to tell us what happens.' But what do you think I am, a time traveler? Like, I'm going to jump 10 years into the future and come back and say, 'Well, this is what happened.' There are all a bunch of different possible paths.
I think, you know, one of the characteristics of, you know, going back to the kind of the platform shift model is, you know, imagine it's 1997 and you're trying to predict which tech companies are going to win and where the value is going to be and which industries are going to get affected by this. You'd get half of it, maybe.
You would not have got Facebook. You would not have got smartphones. You know, I was a mobile analyst in the early 2000s. Everybody spent all their time thinking about this stuff. And none of us really understood that it was going to be a small PC that the telcos would have no role in and that it would turn the PC into a smartphone accessory. Everyone was thinking in terms of what the mobile use case was. So, you know, the idea that somehow you should say it's going to be this, as opposed to saying here are four or five possible options and this is what might determine which of them comes out — this is the argument of a fool.
I think there's a sort of a more fundamental point here, which is that what you try and do as an analyst is you try to work out what the important questions are and how you might determine the answers to them.
And you can say, 'Well, you know, right now foundation models are all sort of using the same data and the same fundamental technology and the same compute and they don't appear to have network effects and we can't see any apparent winner-takes-all effect other than simply the ability to carry on spending money. And so something would have to change for them to have winner-takes-all effects and for them to have fundamental value capture as opposed to being low-margin commodity infrastructure.' Now, then you can kind of pick that up and turn it around and say, 'Well, maybe yes, maybe no.' You can talk about those questions.
And sometimes you can form an opinion. You can look at this and say, 'Well, look, I don't think chatbots are a good user interface. I think this is fundamentally a bad way to give technology to people and this is why.' And I think that this needs to be manifested in use cases and applications and tools, and the skills required to work out what the tools are are different to the skills required to use them. Like, the right person to be a really great enterprise salesperson is different to the person to realize that there is this thing that your software isn't doing and to build a piece of software that would solve that problem and to work out what it should do and what it should look like and how everyone should use it. I think there's this sort of desperate naivety in the idea that you can swallow everything into a single UX.
And so, there are places where you can have an opinion. There are places where you can say, 'Here are five or 10 things that might happen.' There are places where you can say, 'Look, you know, 10 years out, all bets are off.' Like, how could you possibly look at mobile in...
Again, kind of back to this. You know, I actually wrote something about this in like 2015 or 2016. Imagine it's 2000 and you're trying to work out what's going to happen with mobile. Like, what would you have had to say to be right without being a time traveler? So, you'd have to say, 'Okay, it's going to need basically flat-rate unlimited data.' And then you could have kind of modeled that out and say, 'Well, that will take 2008 to 2010 at best.' So, 10 years out.
You could say it kind of needs to be a small computer, not a managed appliance, which is what Nokia and everyone else were making given the constraints of bandwidth and battery at the time. Okay, and so you could kind of model out Moore's Law and say, 'Well, that probably means 2005 to 2010.' And the portals, Yahoo and AOL, are going to disappear off the face of the earth. The telcos will capture no value from this at all.
Okay, so who will win? Well, Nokia and Microsoft, obviously. Nope. It'll be this has-been PC company from Cupertino that's just kind of a joke. And these two grad students who've got this funny little search engine.
And meanwhile, it will be open and one side of it will be completely open source and the other side of it will be this closed managed platform made by Apple. Like, imagine — like, how would you have known any of that?
And if you'd said it, no one would have believed you. And people would say, you know, 'This is idiotic and the networks can't support that.' And remember how long it took for people to understand what the iPhone was. And you still get people who think that like the iPhone is just Android with better marketing or like the BlackBerry should have won, but like the marketing was bad or something.
And for years people said that Android was going to destroy Apple because it was open and that was what had happened in PCs. So there were so many kind of possible paths as to how this evolved.
Now, then you get kind of the middle of that curve and you can say, look, I think both Apple and Android are going to survive because of X and Y and I think app stores are a better model than the web because of X and Y. This is why search and social are durable. You know, you can kind of start seeing where the dynamics are starting to kind of get baked in and you can start seeing the paths that are starting to emerge. When you're right at the beginning, no one knows anything.
And I think the, you know, kind of close to point, you know, people who are walking around the valley right now holding their laptops open to run their agents — this is kind of like people using Telnet on dial-up in like 1993 saying, 'Look, I'm on the other side of the country from my computer and I can connect to it and use it. Isn't this amazing?' Like, yes, it is, but that's not what everyone's going to be doing with this.
Yes. Yes. I mean, I think I totally agree with you in terms of the inability of us to sort of predict future pathways from here and the limited utility in sort of trying to do so or trying to at least be too opinionated about like, yes, it's this one path. As I mentioned, this frontier lab presentation was peppered with all sorts of untold assumptions about the nature of work, the nature of people, as somebody rightly I think pointed out as they raised their hand for a question and said, 'Don't you think there's some kind of mass uprising that happens before all of this plays out?' And then it got into conversation at what point do these people go and live in a bunker to protect themselves? So yeah, there's all sorts of dystopian and maybe...
