{"id":28496781,"date":"2026-02-19T11:29:18","date_gmt":"2026-02-19T19:29:18","guid":{"rendered":"https:\/\/nav.al\/?p=28496781"},"modified":"2026-02-19T14:21:28","modified_gmt":"2026-02-19T22:21:28","slug":"ai","status":"publish","type":"post","link":"https:\/\/nav.al\/ai","title":{"rendered":"A Motorcycle for the Mind"},"content":{"rendered":"\n

Nivi:<\/strong> Hey, this is Nivi. You\u2019re listening to the Naval Podcast. For the first time in recorded history, we are not at the same location. I am actually walking around town and Naval might be doing the same, so there might be some ambient noise, but we are going to try hard to remove that with AI and some good audio engineering.<\/p>\n\n\n\n

Naval:<\/strong> Podcast recording is so stilted, because it\u2019s like you have to sit down and you schedule something, and you have this giant mic pointing in your face and it\u2019s not casual. It makes it just less authentic\u2014more practiced, more rehearsed. I get that it produces maybe higher-quality audio and video, but I feel like it produces lower-quality conversation.<\/p>\n\n\n\n

Nivi:<\/strong> And we all know brains run better when they\u2019re being locomoted and you\u2019re moving around or just going for walks.<\/p>\n\n\n\n

Naval:<\/strong> Absolutely. My brain is powered by my legs.<\/p>\n\n\n\n

Nivi:<\/strong> I pulled out some tweets from Naval on the topic of AI. We want to talk a little bit about AI and hopefully talk about it in a more timeless manner than a timely manner, but I think some of it\u2019s going to be non-timeless content.<\/p>\n\n\n\n

Naval:<\/strong> Yeah, there\u2019s a tendency with the internet commentators where they\u2019ll look at something said five years ago and jump and say, \u201cAha! Well, that turned out to be false.\u201d<\/p>\n\n\n\n

Well, yes, of course. No one can predict the future. That\u2019s the nature of the future. If we could predict it, we\u2019d be there already.<\/p>\n\n\n\n

So it\u2019s always dangerous to talk about the future when people listening aren\u2019t aware of that, but just be charitable. We are obviously talking about things in February of 2026, and we\u2019re working with the information we have now, and not with perfect hindsight.<\/p>\n\n\n\n

And so unless you have your own predictions that you put out there on a risky basis\u2014risky, narrow, precise predictions that are falsifiable\u2014to compare to, then there\u2019s no basis for saying somebody was right or somebody else was wrong.<\/p>\n\n\n\n

If You Want to Learn, Do<\/h2>\n\n\n\n

Nivi:<\/strong> Before we jump into the tweets, do you want to say anything about what you\u2019re doing with your time or what you\u2019re doing at Impossible?<\/p>\n\n\n\n

Naval:<\/strong> Not really. We\u2019re working on a very difficult project\u2014that\u2019s why it\u2019s called Impossible\u2014with an amazing team, and it\u2019s really exciting building something again. It\u2019s very pure, starting over from the bottom. It\u2019s always day one. I guess I just wasn\u2019t satisfied being an investor, and I certainly don\u2019t want to be a philosopher or just a media personality or a commentator. Because I think people who just talk too much and don\u2019t do anything\u2026 they haven\u2019t encountered reality.<\/p>\n\n\n\n

They haven\u2019t gotten feedback\u2014the harsh feedback from free markets or from physics or nature\u2014and so after a while it ends up becoming just too much armchair philosophy. You probably have noticed my recent tweets have been much more practical and pragmatic, although there are still occasional ethereal or generic ones, but it\u2019s more grounded in the reality of working every day.<\/p>\n\n\n\n

And I just like working with a great team to create something that I want to see exist. So hopefully we\u2019ll create something that will come to fruition and people will say, \u201cWow, that\u2019s great. I want that also,\u201d or maybe not, but it\u2019s in the doing that you learn<\/a>.<\/p>\n\n\n\n

Vibe Coding Is the New Product Management<\/h2>\n\n\n\n

Nivi:<\/strong> So I pulled out a tweet from a couple days ago, February 3rd<\/a>: \u201cVibe coding is the new product management. Training and tuning models is the new coding.\u201d<\/p>\n\n\n\n

Naval:<\/strong> There\u2019s been a shift\u2014a marked pronouncement in the last year and especially in the last few months\u2014most pronounced by Claude Code<\/a>, which is a specific model that has a coding engine in it, which is so good that I think now you have vibe coders<\/a>, which are people who didn\u2019t really code much or hadn\u2019t coded in a long time, who are using essentially English as a programming language\u2014as an input into this code bot\u2014which can do end-to-end coding.<\/p>\n\n\n\n

Instead of just helping you debug things in the middle, you can describe an application that you want. You can have it lay out a plan, you can have it interview you for the plan. You can give it feedback along the way, and then it\u2019ll chunk it up and will build all the scaffolding.<\/p>\n\n\n\n

It\u2019ll download all the libraries and all the connectors and all the hooks, and it\u2019ll start building your app and building test harnesses and testing it. And you can keep giving it feedback and debugging it by voice, saying, \u201cThis doesn\u2019t work. That works. Change this. Change that,\u201d and have it build you an entire working application without your having written a single line of code.<\/p>\n\n\n\n

For a large group of people who either don\u2019t code anymore or never did, this is mind-blowing.<\/p>\n\n\n\n

This is taking them from idea space, and opinion space, and from taste directly into product. So that\u2019s what I mean\u2014product management has taken over coding. Vibe coding is the new product management.<\/p>\n\n\n\n

Instead of trying to manage a product or a bunch of engineers by telling them what to do, you\u2019re now telling a computer what to do. And the computer is tireless. The computer is egoless, and it\u2019ll just keep working. It\u2019ll take feedback without getting offended.<\/p>\n\n\n\n

You can spin up multiple instances. It\u2019ll work 24\/7 and you can have it produce working output.<\/p>\n\n\n\n

What does that mean? Just like now anybody can make a video or anyone can make a podcast, anyone can now make an application. So we should expect to see a tsunami of applications. Not that we don\u2019t have one already in the App Store, but it doesn\u2019t even begin to compare to what we\u2019re going to see.<\/p>\n\n\n\n

However, when you start drowning in these applications, does that necessarily mean that these are all going to get used or they\u2019re competitive? No. I think it\u2019s going to break into two kinds of things.<\/p>\n\n\n\n

First, the best application for a given use case still tends to win the entire category. When you have such a multiplicity of content, whether in videos or audio or music or applications, there\u2019s no demand for average.<\/p>\n\n\n\n

Nobody wants the average thing. People want the best thing that does the job. So first of all, you just have more shots on goal. So there will be more of the best. There will be a lot more niches getting filled.<\/p>\n\n\n\n

You might have wanted an application for a very specific thing, like tracking lunar phases in a certain context, or a certain kind of personality test, or a very specific kind of video game that made you nostalgic for something. Before, the market just wasn\u2019t large enough to justify the cost of an engineer coding away for a year or two. But now the best vibe coding app might be enough to scratch that itch or fill that slot. So a lot more niches will get filled, and as that happens, the tide will rise.<\/p>\n\n\n\n

The best applications\u2014those engineers themselves are going to be much more leveraged. They\u2019ll be able to add more features, fix more bugs, smooth out more of the edges. So the best applications will continue to get better. A lot more niches will get filled.<\/p>\n\n\n\n

And even individual niches\u2014such as you want an app that\u2019s just for your own very specific health tracking needs, or for your own very specific architectural layout or design\u2014that app that could have never existed will now exist.<\/p>\n\n\n\n

We should expect\u2014just like on the internet\u2014what\u2019s happened with Amazon, where you replaced a bunch of bookstores with one super bookstore and a zillion long-tail sellers; or YouTube replaced a bunch of medium-sized TV stations and broadcast networks with one giant aggregator called YouTube, or maybe a second one called Netflix, and then a whole long tail of content producers.<\/p>\n\n\n\n

So the same way, the App Store model will become even more extreme, where you will have one or two giant app stores helping you filter through all of the AI slop apps out there, and then at the very head, there\u2019ll be a few huge apps that will become even bigger because now they can address a lot more use cases or just be a lot more polished. And then there\u2019ll be a long tail of tiny little apps filling every niche imaginable.<\/p>\n\n\n\n

As the Internet reminds us, the real power and wealth\u2014super wealth\u2014goes to the aggregator. But there\u2019s also a huge distribution of resources into the long tail. It\u2019s the medium-sized firms that get blown apart\u2014the 5, 10, 20-person software companies that were filling a niche for an enterprise use case that can now be either vibe coded away, or the lead app in the space can now encompass that use case.<\/p>\n\n\n\n

Training Models Is the New Coding<\/h2>\n\n\n\n

Naval:<\/strong> So if anyone can code then what is coding? Coding still exists in a couple of areas. The most obvious place that coding exists is in training these models themselves. There are many different kinds of models. There are new ones coming out every day, there are different ones for different domains. We\u2019re going to see different models for biology, for programming. We\u2019re going to see pointed, focused models for sensors. We\u2019re going to see models for CAD<\/a>, for design.<\/p>\n\n\n\n

We\u2019re going to see models for 3D and graphics and games, models for video. You\u2019re going to see many different kinds of models. The people who are creating these models are essentially programming them. But they\u2019re programmed in a very different way than classic computers.<\/p>\n\n\n\n

Classic computing is: you have to specify in great detail every step, every action the computer is going to take. You have to formally reason about every piece and write it in a highly structured language that allows you to express yourself extremely precisely. The computer can only do what you tell it to do.<\/p>\n\n\n\n

And then once you\u2019ve got this very structured program, you run data through it and the computer runs the data and gives you an output. It\u2019s basically an incredibly fancy, very complicated, meticulously-programmed calculator.<\/p>\n\n\n\n

Now, when it comes to AI, you\u2019re doing something very different. But you are nevertheless programming it.<\/p>\n\n\n\n

What you\u2019re doing is you\u2019re taking giant data sets that have been produced by humanity\u2014thanks to the internet, or aggregated in other ways\u2014and you\u2019re pouring those data sets into a structure that you\u2019ve defined and tuned. And that structure tries to find a program that can produce more of that data set, or manipulate that data set, or create things off that data set.<\/p>\n\n\n\n

So you\u2019re searching for a program inside this construct that you\u2019ve designed. You\u2019ve set up a model, you\u2019ve tuned the number of parameters, you\u2019ve tuned the learning rate, you\u2019ve tuned the batch size. You have tokenized the data that\u2019s coming, you\u2019ve broken it into pieces, and you\u2019re pouring it inside the system you\u2019ve designed\u2014almost like a giant pachinko machine\u2014and now the system is trying to find a program and could find many different programs. So your tuning really influences how good the program that you found is.<\/p>\n\n\n\n

And that program can now suddenly be expressive in different kinds of domains. So it can do things that computers before were traditionally very bad at.<\/p>\n\n\n\n

Traditional computers are very good when you program them to give you precise outputs\u2014specific answers to specific questions\u2014things you can rely on and repeat over and over again. But sometimes you\u2019re operating in the real world and you\u2019re okay with fuzzy answers. You\u2019re even okay with wrong answers. For example, in creative writing, what\u2019s a wrong answer?<\/p>\n\n\n\n

If you\u2019re writing a piece of poetry or fiction, what\u2019s a wrong answer? If you\u2019re searching on the web, there are many right answers\u2014there are many details of the right answers\u2014but they\u2019re not all quite perfectly right. And real life sort of works that way. There are variations of right answers or mostly right answers. When you\u2019re drawing a picture of a cat, there are many different cats you could draw. There are many different levels of detail. There are many different styles you could use.<\/p>\n\n\n\n

When these semi-wrong or fuzzy answers are acceptable, then these discovered programs through AI are much more interesting and much more adapted to the problem than ones that you coded up from scratch, where you had to be super precise.<\/p>\n\n\n\n

Fundamentally, what we\u2019re doing is a new kind of programming, but this is the forefront of programming. This is now the art of programming. These people are the new programmers, and that\u2019s why you can see AI researchers are getting paid gargantuan amounts because they\u2019ve essentially taken over programming.<\/p>\n\n\n\n

Is Traditional Software Engineering Dead?<\/h2>\n\n\n\n

Naval:<\/strong> Does this mean that traditional software engineering is dead? Absolutely not. Software engineers\u2014even the ones who are not necessarily tuning or training AI models\u2014these are now among the most leveraged people on earth<\/a>. Sure, the guys who are training and tuning models are even more leveraged because they\u2019re building the tool set that software engineers are using.<\/p>\n\n\n\n

But software engineers still have two massive advantages on you. First, they think in code, so they actually know what\u2019s going on underneath. And all abstractions are leaky. So when you have a computer programming for you\u2014when you have Claude Code or equivalent programming for you\u2014it\u2019s going to make mistakes.<\/p>\n\n\n\n

It\u2019s going to have bugs. It\u2019s going to have suboptimal architecture. So it\u2019s not going to be quite right. And someone who understands what\u2019s going on underneath will be able to plug the leaks as they occur.<\/p>\n\n\n\n

So if you want to build a well-architected application, if you want to be able to even specify a well-architected application, if you want to be able to make it run at high performance, if you want it to do its best, if you want to catch the bugs early, then you\u2019re going to want to have a software engineering background.<\/p>\n\n\n\n

The traditional software engineer is going to be able to use these tools much better. And there are still many kinds of problems in software engineering that are out of scope for these AI programs today. The easiest way to think about those is problems that are outside of their data distribution.<\/p>\n\n\n\n

For example, if they need to do a binary sort or reverse a linked list, they\u2019ve seen countless examples of that, so they\u2019re extremely good at it. But when you start getting out of their domain\u2014where you have to write very high-performance code, when you\u2019re running on architectures that are novel or brand new, when you\u2019re actually creating new things or solving new problems, then you still need to get in there and hand code it.<\/p>\n\n\n\n

At least until either there are so many of those examples that new models can be trained on them, or until these models can sufficiently reason at even higher levels of abstraction and crack it on their own.<\/p>\n\n\n\n

Because given enough data points, there is some evidence that these AIs actually learn. They learn to a higher level of abstraction because the act of forcing them to compress the data forces them to learn higher-level representations. If I show an AI five circles, it can just memorize exactly what the sizes, and the radii, and the thicknesses, and so on of those circles are.<\/p>\n\n\n\n

If I show it 50,000 circles or 5 billion circles and I give it a very small amount of parameter weights\u2014which are its equivalent neurons\u2014to memorize that, it\u2019s going to be much better off figuring out pi and how to draw a circle and what thickness means, and forming an algorithmic representation of that circle rather than memorizing circles.<\/p>\n\n\n\n

Given all that, these things are learning at an accelerated rate, and you could see them starting to cover more of the edge cases I\u2019ve talked about.<\/p>\n\n\n\n

But at least as of today, those edge cases are prevalent enough that a good engineer operating at the edge of knowledge of the field is going to be able to run circles around vibe coders.<\/p>\n\n\n\n

There is No Demand for Average<\/h2>\n\n\n\n

Naval: <\/strong>And remember: there is no demand for average. The average app\u2014nobody wants it, at least as long as it\u2019s not filling some niche that is filled by a superior app. The app that is better will win essentially a hundred percent of the market. Maybe there\u2019s some small percentage that will bleed off to the second-best app because it does some little niche feature better than the main app, or it\u2019s cheaper, or something of the sort.<\/p>\n\n\n\n

But generally speaking, people only want the best of anything. So the bad news is there\u2019s no point in being number two or number three\u2014like in the famous Glengarry Glen Ross<\/em> scene<\/a> where Alec Baldwin says, \u201cFirst place gets a Cadillac Eldorado, second place gets a set of steak knives, and third place you\u2019re fired.\u201d<\/p>\n\n\n\n

That\u2019s absolutely true in these winner-take-all markets. That\u2019s the bad news: You have to be the best at something if you want to win.<\/p>\n\n\n\n

However, the set of things you can be best at is infinite. You can always find some niche that is perfect for you, and you can be the best at that thing. This goes back to an old tweet<\/a> of mine where I said, \u201cBecome the best in the world at what you do. Keep redefining what you do until this is true.\u201d<\/p>\n\n\n\n

And I think that still applies in this age of AI.<\/p>\n\n\n\n

The Hottest New Programming Language Is English<\/h2>\n\n\n\n

Nivi:<\/strong> I think the way to think about these coding models is as another layer in the abstraction stack that programmers have always used since the dawn of computers that went from the transistor, to the computer chip, to assembly language, to the C programming language, to higher-level languages, to languages with huge libraries where they built and built that stack so you don\u2019t have to look at the layer beneath unless you need to optimize it, or you have a reason that you need to look at the layer beneath. So in this case, these coding models are a massive new layer in the stack that lets product managers and typical non-programmers and programmers write code without writing code.<\/p>\n\n\n\n

Naval:<\/strong> I think that\u2019s correct in terms of the trend line. However, this is an emergent property. This is not a small improvement. This is a big leap. For example, when I was in school, I was programming mostly in C<\/a>. And then C++<\/a> came along and it wasn\u2019t any easier.<\/p>\n\n\n\n

It was like a little more abstract in some ways, and I never really bothered learning it. And then Python<\/a> came along and I was like, \u201cWow, this is almost like writing in English.\u201d<\/p>\n\n\n\n

I couldn\u2019t have been more wrong. English is still pretty far from Python, but it was a lot easier than C.<\/p>\n\n\n\n

Now you can literally program in English.<\/p>\n\n\n\n

And so that brings me to a related point: I don\u2019t think it\u2019s worth learning tips and tricks of how to work with these AIs. You\u2019ll see, for example, on social media right now, there\u2019s a lot of writeups and books and tweets like, \u201cOh, I figured out this neat trick with the bot. You can prompt it this way, or you can set up your harness this way.\u201d<\/p>\n\n\n\n

Or there\u2019s like a new programming assist tool or layer that you can use on top of it to do this or that. And I never bother learning those.<\/p>\n\n\n\n

I just sit there stupidly talking to the computer because I know that this thing is now at the stage where it is going to adapt to me faster than I can adapt to it.<\/p>\n\n\n\n

It is getting smarter and smarter about how people want to use it. So it is learning, it is being trained, and tools are being built very quickly to make it easier for me to use it. So I don\u2019t need to sit there and figure out some esoteric programming command. And this is what I think Andrej Karpathy meant when he said, \u201cEnglish is the hottest new programming language<\/a>.\u201d<\/p>\n\n\n\n

I just can speak English. And for someone like me who is relatively articulate with English and also has a structured mind, and I know how computer architectures work, and I know how computer programs work, and I know how programmers think, then I can actually very precisely specify what I want just through structured English.<\/p>\n\n\n\n

I don\u2019t need to go any further than that. The only reason to use these workflows and tool sets\u2014which are very ephemeral, and their longevity is measured in weeks, perhaps months at best, not in years\u2014is if you\u2019re building an app right now that needs to be at the bleeding edge, and you absolutely need every little bit of advantage that you can get because you\u2019re in some kind of a competitive environment.<\/p>\n\n\n\n

But otherwise, I wouldn\u2019t bother learning how to use an AI\u2014rather let the AI learn how to be useful to you.<\/p>\n\n\n\n

Nivi:<\/strong> I\u2019ve never been into prompt engineering. Even before AI, I would just put what people call \u201cBoomer queries,\u201d where you put in the whole question that you want to ask instead of the keywords that you would put into Google if you were more of an analytical thinker.<\/p>\n\n\n\n

I never spend much time formulating really precise questions or prompts for any kind of AI. I just ramble into it and I\u2019ve done that since the beginning of AI. And like you said, AI is adapting to us faster than we are adapting to it.<\/p>\n\n\n\n

Naval:<\/strong> Like a lot of smart people, you\u2019re very lazy. And I mean that as a compliment. If you find a smart person who\u2019s grinding a little too much, you kind of have to wonder how smart they are. And by lazy I mean that you\u2019re optimizing for the right kind of efficiency. You don\u2019t care about the efficiency of the computer, or the electronics, or the electrons running through the circuits.<\/p>\n\n\n\n

You care about your own human efficiency\u2014the wetware\u2014the biology that\u2019s super expensive. That\u2019s why it\u2019s silly to see people go to huge lengths to save energy and the environment. But they themselves, as a biological computer that\u2019s eating food and pooping and taking up space, are using up far more energy to save tiny bits of energy in the environment.<\/p>\n\n\n\n

They\u2019re inherently downgrading their own importance in the universe, or rather revealing what they think of themselves.<\/p>\n\n\n\n

AI Is Adapting to Us Faster Than We Are Adapting to It<\/h2>\n\n\n\n

Naval:<\/strong> I think as AI evolves or co-evolves with us, it\u2019s evolved by us according to our needs.<\/p>\n\n\n\n

The pressures on AI are very capitalistic pressures in the sense that it\u2019s a free market for AI. As an AI instance, you only get spun up by a human if you\u2019re useful to a human.<\/p>\n\n\n\n

So there is a natural selection pressure on these AIs to be useful, to be obsequious, to do what we want. And so it will continue to adapt towards this, and I think will be quite helpful to us.<\/p>\n\n\n\n

That\u2019s not to say that there\u2019s no such thing as a malicious AI, but it\u2019s malicious because the people who are using it are using it for malicious reasons.<\/p>\n\n\n\n

And like a dog that\u2019s trained to attack, it\u2019s actually being trained by its owner to go and do the owner\u2019s malicious desires. So I don\u2019t really worry about unaligned AI. I worry about unaligned humans with AI.<\/p>\n\n\n\n

Nivi:<\/strong> So the selection pressure you\u2019re saying is for AI to be maximally useful to people.<\/p>\n\n\n\n

Naval:<\/strong> Correct. And so if you find an AI to be very obsequious towards you, for example, how it\u2019s always saying, \u201cOh, you\u2019re right. Oh, that\u2019s such a great idea. Oh my God, you\u2019re so smart\u201d\u2014that\u2019s because that\u2019s what most people want.<\/p>\n\n\n\n

And at least today, these AIs are being trained on massive amounts of users and massive amounts of data because you\u2019re working with one-size-fits-all models.<\/p>\n\n\n\n

But we\u2019re going to quickly move into an era when you can personalize your AI and it does begin to feel more and more like your personal assistant and it corresponds more to what you want, which will of course anthropomorphize the AI even more.<\/p>\n\n\n\n

And you\u2019ll be more likely to be convinced, \u201cOh, actually this thing is alive,\u201d when you\u2019ve trained it to look the most like a living thing to you.<\/p>\n\n\n\n

Nivi:<\/strong> Maybe we already covered this enough, but over a year ago you tweeted<\/a> that \u201cAI won\u2019t replace programmers, but rather make it easier for programmers to replace everyone else.\u201d<\/p>\n\n\n\n

Naval:<\/strong> Yeah, this is my point earlier, which is that programmers are becoming even more leveraged. So now a programmer with a fleet of AIs is, call it 5-10x more productive than they used to be.<\/p>\n\n\n\n

And because programmers operate in the intellectual domain, it\u2019s a mistake to even say 10x programmers, because there are 100x programmers out there. There are 1000x programmers out there.<\/p>\n\n\n\n

There are programmers who just pick the right thing to work on, and they create something that\u2019s valuable, and others who pick the wrong thing to work on, and their work has zero value in that short timeframe.<\/p>\n\n\n\n

Intelligence is not normally distributed. Leverage is not normally distributed. Programmability is not normally distributed. Judgment is not normally distributed, so the outcomes are going to be supernormal.<\/p>\n\n\n\n

So what you have to really watch out for is: there are programmers now who are going to come up with ideas that can replace entire industries.<\/p>\n\n\n\n

They will completely rewrite the way things are done, and their intelligence can be maximally leveraged with all these bots and all these AI agents. I think every other job out there is going to get eaten up by programmers one way or another over the maximally long term. Obviously it has to instantiate into robots, et cetera.<\/p>\n\n\n\n

But the good news is: anybody who is a logical, structured thinker, who thinks like a programmer and can speak any language that an AI can understand, which will be every language, will now be on the playing field. They will be able to make anything they want, obstructed only by their creativity, limited only by their imagination.<\/p>\n\n\n\n

So we are entering an era where every human, in a sense, is a spellcaster.<\/p>\n\n\n\n

If you think of programmers as like these wizards who have memorized arcane commands, you can think of AI as a magic wand that\u2019s been handed to every person, where now they can just talk in any language they want, and they\u2019re a wizard too.<\/p>\n\n\n\n

So it is more of a level playing field. I really do think this is a golden age for programming.<\/p>\n\n\n\n

But yes, the people who have a software engineering mindset and who understand computer architecture and can deal with leaky abstractions are going to have an advantage.<\/p>\n\n\n\n

There\u2019s no way around that. They simply have more knowledge in the field that they\u2019re operating in. Just like even in classic software engineering\u2014which still exists because you have to write high-performing code\u2014even those people do best when they have an understanding of the hardware underneath. When they understand how the chips operate, when they understand how the logic gates operate, how the cache operates, how the processor operates, how the disk drive underneath operates.<\/p>\n\n\n\n

And then even the people who are in hardware engineering, they have an advantage if they understand the physics of what\u2019s going on. They understand where the abstractions that hardware engineers deal with leak down into the physical layer. And maybe physicists become philosophers at some point.<\/p>\n\n\n\n

You can take this all the way down, but it always helps to have knowledge one layer below because you\u2019re getting closer to reality.<\/p>\n\n\n\n

No Entrepreneur Is Worried About AI Taking Their Job<\/h2>\n\n\n\n

Nivi:<\/strong> Another tweet from a year ago, which is arguing, perhaps the complement of what we just talked about is from February 9, 2025<\/a>: \u201cNo entrepreneur is worried about an AI taking their job.\u201d<\/p>\n\n\n\n

Naval:<\/strong> That one\u2019s glib in multiple ways. First of all, being an entrepreneur isn\u2019t a job. It\u2019s literally the opposite of a job, and in the long run, everyone\u2019s an entrepreneur. Careers got destroyed first, jobs get destroyed second, but all of it gets replaced by people doing what they want and doing something that creates something useful that other people want.<\/p>\n\n\n\n

So no entrepreneur is worried about an AI taking their job because entrepreneurs are trying to do impossible things. They\u2019re trying to do very difficult things. Any AI that shows up is their ally and can help them tackle this really hard problem.<\/p>\n\n\n\n

They don\u2019t even have a job to steal. They have a product to build. They have a market to serve. They have a customer to support. They have a creativity to realize. They have a thing that they want to instantiate in the world, and they want to build a repeatable and scalable process around getting it out into the world.<\/p>\n\n\n\n

This is so difficult that any AI that shows up that can do any of that work is their ally.<\/p>\n\n\n\n

If the AIs themselves are entrepreneurs, they\u2019re likely going to just be entrepreneurs serving other AIs, or they\u2019re under the control of an entrepreneur. The thing that the AI itself is missing, at the end of the day, is its own creative agency.<\/p>\n\n\n\n

It\u2019s missing its own desires, and they have to be authentic, genuine desires. Unless you can pull the plug on AI and turn it off, and unless it lives in mortal fear of being turned off, and unless it can actually make its own actions for its own reasons, for its own instincts, its own emotions, its own survival, its own replication, it\u2019s not quite alive.<\/p>\n\n\n\n

And even then people will challenge: is it alive? Because consciousness is one of those things that\u2019s a qualia<\/a>. It\u2019s like a color. It\u2019s like if you say red, I don\u2019t know if you\u2019re actually seeing red; you might be seeing what I see as green, and I might be seeing what you see as red. But we\u2019ll never know because we can\u2019t get into each other\u2019s minds.<\/p>\n\n\n\n

So the same way, even an AI that\u2019s completely imitating everything that humans do: to some people, it will always be an imitation machine, and to others it\u2019ll be conscious, but there\u2019ll be no way of distinguishing the two.<\/p>\n\n\n\n

We\u2019re still pretty far from that, though. Right now the AIs are not embodied. They don\u2019t have agency. They don\u2019t have their own desires. They don\u2019t have their own survival instinct. They don\u2019t have their own replication. Therefore, they don\u2019t have their own agency.<\/p>\n\n\n\n

And because they don\u2019t have their own agency, they cannot do the entrepreneur\u2019s job.<\/p>\n\n\n\n

In fact, I would summarize this by saying the key thing that distinguishes entrepreneurs from everybody else right now in the economy is entrepreneurs have extreme agency<\/a>. That\u2019s why it\u2019s diametrically opposed to the idea of a job.<\/p>\n\n\n\n

A job implies that you\u2019re working for somebody else or you\u2019re filling a slot, but they\u2019re operating in an unknown domain with extreme agency. There are other examples of roles like this in society. An explorer also does the same thing, right? If you\u2019re landing on Mars or you\u2019re sailing a ship to an unknown land, you are also exercising extreme agency to solve an unsolved problem.<\/p>\n\n\n\n

A scientist exploring an unknown domain does this. A true artist is trying to create something that does not exist and has never existed, yet somehow fits into the set of things that can explain human nature, allow them to express themselves, and create something new.<\/p>\n\n\n\n

So in all of these roles, whether you\u2019re a scientist or whether you\u2019re a true artist, or whether you are an entrepreneur, what you\u2019re trying to do is so difficult and is so self-directed that anything like an AI that can help you is a welcome ally. You\u2019re not doing it because it\u2019s a job. You\u2019re not trying to fill a slot that somebody else can show up and fill.<\/p>\n\n\n\n

In fact, if the AI can create your artwork, or if the AI can crack your scientific theory, or if the AI can create the object or the product that you\u2019re trying to make, then all it does is it levels you up. Now it\u2019s the AI plus you. The AI is the springboard from which you can jump to a further height.<\/p>\n\n\n\n

The Goal Is Not to Have a Job<\/h2>\n\n\n\n

Naval:<\/strong> We\u2019re going to see some incredible art created that\u2019s AI-assisted. We will see movies that we couldn\u2019t have imagined, created by people using AI tools.<\/p>\n\n\n\n

There\u2019s an analogy here in art that\u2019s interesting. For a long time in art, the rough direction was trying to paint things that were more and more realistic. Paint the human body, paint the fruit, paint proper lighting, et cetera.<\/p>\n\n\n\n

Eventually photography came along, and then you could replicate things very precisely, and so that selection pressure went away.<\/p>\n\n\n\n

And then art got weird. Art went in many different directions. Art became all about, \u201cWell, can I be surreal? Can I create something that expresses me?\u201d<\/p>\n\n\n\n

A lot of art schools spun out of that, that got really weird\u2014including modern art and postmodernism\u2014but also I would argue some of the greatest creativity came at that time we were freed up.<\/p>\n\n\n\n

Photography got democratized, but photography itself became a form of art, and there were great photographers taking many different kinds of photographs. And now everyone\u2019s a photographer. There are still artists who are photographers, but it\u2019s not the pure domain of just a few people.<\/p>\n\n\n\n

So the same way, because AI makes it so easy to create the basic thing, everybody will create the basic thing. It\u2019ll have value to them individually. A few will still stand out that will create variations of it that are good for everyone.<\/p>\n\n\n\n

And it would be very hard to argue that society is worse off because of photography, although it may have certainly felt like that to some of the artists who were maybe making a living painting portraits of people and got displaced.<\/p>\n\n\n\n

Similar things will happen with AI, where there are people who are making a very specific living, doing very specific jobs that will get displaced that the AI can do. But in exchange, everyone in society will have the AI. You\u2019ll have incredible things that were created with AI that couldn\u2019t have been created otherwise.<\/p>\n\n\n\n

And within a few decades, it\u2019ll be unimaginable that you roll back the clock and get rid of AI, or any kind of software\u2014any kind of technology for that matter\u2014just to keep a few jobs that were obsolete.<\/p>\n\n\n\n

The goal here is not to have a job.<\/p>\n\n\n\n

The goal is not to have to get up at nine in the morning and come back at 7 PM exhausted, doing soulless work for somebody else.<\/p>\n\n\n\n

The goal is to have your material needs solvable by robots, to have your intellectual capabilities leveraged through computers, and for anybody to be able to create.<\/p>\n\n\n\n

I used to do this thought exercise\u2014I think I talked about it in a podcast that you and I did literally 10 years ago\u2014which was: imagine if everybody were a software engineer, or everybody was a hardware engineer, and they could have robots and they could write code.<\/p>\n\n\n\n

Imagine the world of abundance we would live in.<\/p>\n\n\n\n

Actually, that world is now becoming real. Thanks to AI, everybody can be a software engineer. In fact, if you think you can\u2019t be, you can go fire up Claude right now or any of your favorite chatbots and you can go start talking to it. You\u2019d be amazed how quickly you could build an app.<\/p>\n\n\n\n

It\u2019ll blow your mind.<\/p>\n\n\n\n

And once we can instantiate AI through robotics, which is a hard problem\u2014I\u2019m not saying we\u2019re that close to having solved it yet\u2014but once we have robots, everyone can also do a little bit of hardware engineering. And so I think we\u2019re getting closer and closer to that utopian vision.<\/p>\n\n\n\n

AIs Are Not Alive<\/h2>\n\n\n\n

Nivi:<\/strong> I don\u2019t think AI, as it is currently conceived, is alive in any way. But I do think that we will pretty soon have robots that seem very much like they are alive, for two reasons.<\/p>\n\n\n\n

One, a lot of human activity is non-creative and is non-intelligent, and the robots will be able to replicate that. And two, I do believe that the neural nets that we have and the models that we have are more than just the training data, because the training process transforms that training data into something novel.<\/p>\n\n\n\n

And there are new ideas embedded in the neural net that can be elicited through prompting.<\/p>\n\n\n\n

Naval:<\/strong> I don\u2019t think these things are alive. I think they start out as extremely good imitators, to the point where they\u2019re almost indistinguishable from the real thing, especially for anything that humanity has already done before en masse<\/em>. So if the task has been done before, then it\u2019s going to be automated and it\u2019ll be done again.<\/p>\n\n\n\n

It may just be novel to you because you\u2019ve never seen it, but the AI has learned it from somewhere else. That\u2019s the first way in which it seems alive.<\/p>\n\n\n\n

The second way, which we talked about earlier, is where it does learn higher levels of abstraction. These are very efficient compressors. They take huge amounts of data, and then they compress it down further, and in the process of compressing it, they learn higher-level abstractions.<\/p>\n\n\n\n

Then in specific areas where they may not have learned those through the data themselves, they\u2019re getting patched through human feedback. They\u2019re getting patched through tool use. They\u2019re getting patched from traditional programming becoming embedded inside. And especially the AIs that are learning how to think and code, they have the entire library of all of human code ever written to fall back on for algorithmic reasoning.<\/p>\n\n\n\n

In that sense, the set of things that they can do is getting broader and broader.<\/p>\n\n\n\n

However, what they lack still is a lot of core human skills, like single-shot learning. Humans can learn from just one example. The raw creativity of human beings where they can connect anything to anything. They can leap across entire huge domains and search spaces, and figure out an idea that just came out of left field.<\/p>\n\n\n\n

This happens a lot with the true, great scientific theories. Humans also are embodied. They operate in the real world. They\u2019re not operating in the compressed domain of language. They\u2019re operating in physics\u2014in nature.<\/p>\n\n\n\n

Language only encompasses things that humans both figured out and could articulate and convey to each other.<\/p>\n\n\n\n

That\u2019s a very narrow subset of reality. Reality is much broader than that.<\/p>\n\n\n\n

So overall, I think even though AIs are going to do things that are very impressive and they\u2019re going to do a lot of things better than humans\u2014just like calculators are faster than any mathematician at calculations, classical computers are better at classical computer programs than any human could run in their own head, and just like a robot can lift very heavy things or a plane can outfly any bird\u2014so in that sense, like all machines, the AIs are going to be much better than humans at a whole variety of tasks.<\/p>\n\n\n\n

But at other tasks, they\u2019re going to seem just completely incompetent. Those are the things that really embody and connect us into the real world, plus this poorly defined but magic creative ability that we seem to have.<\/p>\n\n\n\n

AI Fails the Only True Test of Intelligence<\/h2>\n\n\n\n

Nivi:<\/strong> Speaking of calculators, people talk about superintelligence. I think superintelligence is already here and has been for a long time. An ordinary calculator can do things that no human can do, right?<\/p>\n\n\n\n

But if you\u2019re thinking about superintelligence in the sense of \u201cAI will be able to do things and come up with ideas that humans cannot understand,\u201d I don\u2019t think that is going to happen because I don\u2019t believe that there are ideas that humans can\u2019t understand, simply because humans can always ask questions about the idea.<\/p>\n\n\n\n

Naval:<\/strong> Humans are universal explainers<\/a>. Anything that is possible with the current laws of physics as we know them, a human can model in their own heads. Therefore just by enough digging\u2014enough questioning\u2014we can figure anything out.<\/p>\n\n\n\n

Related to that, we should discuss AI as a learning tool, because I think the other place where it\u2019s incredibly powerful is as the most patient tutor that can meet you at your level and explain anything to your satisfaction a hundred different ways, a hundred different times, until you finally get it.<\/p>\n\n\n\n

I don\u2019t think the AIs are going to be figuring things out that humans cannot understand, but intelligence is poorly defined.<\/p>\n\n\n\n

What is the definition of intelligence? There\u2019s the G factor<\/a>, which predicts a lot of human outcomes, but the best evidence for the G factor is its predictive power. It\u2019s that you measure this one thing and then you see people get much better life outcomes along the way in things that seem even somewhat unrelated to G.<\/p>\n\n\n\n

So I would argue, and I think it\u2019s one of my more popular tweets<\/a>: the only true test of intelligence is if you get what you want out of life.<\/p>\n\n\n\n

This triggers a lot of people because they go to school, they get their master\u2019s degrees, they think they\u2019re super smart. And then they don\u2019t have great lives. They aren\u2019t super happy, or they have relationship problems, or they don\u2019t make the money that they want, or they become unhealthy and this sort of triggers them.<\/p>\n\n\n\n

But that really is the purpose of intelligence: for you as a biological creature to get what you want out of life.<\/p>\n\n\n\n

Whether it\u2019s a good relationship or a mate, or money or success or wealth or health or whatever it is. So there are people who I think are quite intelligent because you can tell they have high-quality, functioning lives and minds and bodies, and they\u2019ve just managed to navigate themselves into that situation.<\/p>\n\n\n\n

It doesn\u2019t matter what your starting point is, because the world is so large now, and you can navigate it in so many different ways that every little choice you make compounds and demonstrates your ability to understand how the world works until you finally get to the place that you want.<\/p>\n\n\n\n

Now the interesting thing about this definition\u2014that the only true test of intelligence is if you get what you want out of life\u2014is that an AI fails it instantly, because an AI doesn\u2019t want anything out of life.<\/p>\n\n\n\n

The AI doesn\u2019t even have a life\u2014let alone that\u2014but it doesn\u2019t want anything. AI\u2019s desires are programmed by the human controlling it.<\/p>\n\n\n\n

But let\u2019s give it that for a second. Let\u2019s say the human wants something and programs the AI to go get it; then the AI is acting as a proxy for the human and the intelligence of the AI can be measured as: did it get that person that thing?<\/p>\n\n\n\n

Most of the things that we want in life are adversarial or zero-sum games.<\/p>\n\n\n\n

So, for example, if you want to seduce a girl or get a husband, you\u2019re competing with all the other people who are out there seducing girls or trying to get husbands. So now you\u2019re in a competitive situation. The AI has to outmaneuver the other people.<\/p>\n\n\n\n

Or if you say, \u201cHey, AI, go trade on the stock market for me and make me a bunch of money.\u201d That AI is trading against other humans and other trading bots. It\u2019s an adversarial situation. It has to outmaneuver them.<\/p>\n\n\n\n

Or if you say, \u201cHey, AI, make me famous. Write me incredible tweets. Write me great blog posts. Record me great podcasts in my own voice and make me famous,\u201d now it\u2019s competing against all the other AIs.<\/p>\n\n\n\n

So in that sense, intelligence is measured in a battlefield\u2014in an arena. It\u2019s a relative construct. I think the AIs are actually going to fail mostly in those regards, or to the extent that they even succeed, because they\u2019re freely available, they will get outcompeted away, and the alpha that will remain would be entirely human.<\/p>\n\n\n\n

Early Adopters of AI Have an Enormous Edge<\/h2>\n\n\n\n

Naval:<\/strong> As a thought exercise, imagine that every guy had a little earpiece where an AI was whispering to him\u2014a Cyrano de Bergerac<\/a> kind of earpiece\u2014telling him what to say on the date. Well, then every woman would have an earpiece telling her to ignore what he said, or what part was AI-generated and what part was real. If you have a trading bot out there, it\u2019s going to be nullified or canceled out by every other trading bot, until all the remaining gain will go to the person with the human edge, with the increased creativity.<\/p>\n\n\n\n

Now, that\u2019s not to say that the technology is completely evenly distributed. Most people still aren\u2019t using AI, or aren\u2019t using it properly, or aren\u2019t using it all the way to the max, or it\u2019s not available in all domains or all contexts, or they\u2019re not using the latest models. So you can always have an edge, like people who early adopt technology always do if you adopt the latest technology first.<\/p>\n\n\n\n

This is why I always say: to invest in the future, you want to live in the future<\/a>. You want to actually be an avid consumer of technology, because it\u2019s going to give you the best insight on how to use it, and it will give you an edge against the people who are slower adopters or laggards.<\/p>\n\n\n\n

Most people hate technology. They\u2019re scared of it. It\u2019s intimidating. You press the wrong button, the computer crashes\u2014you lose your data. You do the wrong thing, you look like an idiot.<\/p>\n\n\n\n

Most people do not have a positive relationship with complex technology. Simple technology\u2014embedded technology\u2014they\u2019re fine with. You throw on a light switch, light turns on.<\/p>\n\n\n\n

That used to be technology. It\u2019s so simple now, you don\u2019t think of it as technology anymore. You get in a car, you turn the steering wheel left\u2014to a caveman that would be a miracle\u2014the car turns left. It\u2019s no longer technology to you.<\/p>\n\n\n\n

But computer technology in particular has had very complex interfaces and been very inaccessible and very intimidating to people in the past.<\/p>\n\n\n\n

Now with the AIs, we\u2019re getting the chatbot interface, which you just talk to it or type to it. Very simple interface. And one of the great things about these foundational models\u2014what truly makes them foundational\u2014is you can ask them anything and they\u2019ll always give you a plausible answer.<\/p>\n\n\n\n

It\u2019s not going to say, \u201cOh, sorry, I don\u2019t do math,\u201d or \u201cI don\u2019t do poetry,\u201d or \u201cI don\u2019t understand what you\u2019re talking about,\u201d or \u201cI can\u2019t give relationship advice or anything like that.\u201d<\/p>\n\n\n\n

Its domain is everything that people have ever talked about. In that sense, it\u2019s less intimidating.<\/p>\n\n\n\n

It can be more intimidating because we\u2019ve anthropomorphized it so much. If you think Claude or ChatGPT is a real person, then it can be a little scary:<\/p>\n\n\n\n

\u201cAm I talking to God? This guy seems to know so much. He knows everything. He\u2019s got an opinion on everything. He\u2019s got every piece of data. Oh my God, I\u2019m useless. Let me start talking to it and asking it what to do.\u201d<\/p>\n\n\n\n

And you can reverse the relationship and fool yourself very quickly into not realizing what\u2019s going on. That can be intimidating.<\/p>\n\n\n\n

Overall, I think these AIs are going to help a lot of people get over the tech fear. But if you\u2019re an early adopter of these tools\u2014like with any other tool, but even more so with these\u2014you just have a huge edge on everybody else.<\/p>\n\n\n\n

AI Meets You Exactly Where You Are<\/h2>\n\n\n\n

Naval:<\/strong> I remember early on when Google first came out, I used to use it a lot in my social circle. People would ask me basic questions and I would just go Google it for them and look like a genius.<\/p>\n\n\n\n

Eventually this hilarious website came along, something like LMGTFY.com, and it stood for, \u201cLet Me Google That For You.\u201d Somebody would ask you a question, and you\u2019d go type the question into this website, and it would create like a tiny little inline video showing you typing that question into Google and giving the Google results. And I feel like AI is in a similar domain right now, where I will sit around in a social context and people will be debating some point that can be easily looked up by AI.<\/p>\n\n\n\n

Now you do have to be very careful with AI. They do hallucinate. They do have biases in how they\u2019re trained. Most of them are extremely politically correct and taught not to take sides or only take a particular side.<\/p>\n\n\n\n

I actually run most of my queries\u2014almost all actually\u2014through four AIs and I\u2019ll always fact-check them against each other.<\/p>\n\n\n\n

And even then I have my own sense of when they\u2019re bullshitting, or when they\u2019re saying something politically correct. And I\u2019ll ask for the underlying data or the underlying evidence, and in some cases I\u2019m fine with dismissing it outright because I know the pressures that the people who trained it were under and what the training sets were.<\/p>\n\n\n\n

However, overall it is a great tool to just get ahead, and in domains that are technical, scientific, mathematical, that don\u2019t have a political context to them, then the AI is very much likely to give you closer to a correct answer, and in those domains they are absolute beasts for learning.<\/p>\n\n\n\n

I will now have AI routinely generate graphs, figures, charts, diagrams, analogies, illustrations for me. I\u2019ll go through them in detail and I\u2019ll say, \u201cWait, I don\u2019t understand that question.\u201d<\/p>\n\n\n\n

I can ask it super basic questions and I can really make sure that I understand the thing I\u2019m trying to understand at its simplest, most fundamental level.<\/p>\n\n\n\n

I just want to establish a great foundation of the basics, and I don\u2019t care about the overly complicated jargon-heavy stuff. I can always look that up later.<\/p>\n\n\n\n

But now, for the first time, nothing is beyond me. Any math textbook, any physics textbook, any difficult concept, any scientific principle, any paper that just came out, I can have the AI break it down, and then break it down again, and illustrate it, and analogize it until I get the gist, and I understand it at the level that I want.<\/p>\n\n\n\n

So these are incredible tools for self-directed learning. The means of learning are abundant. It\u2019s the desire to learn that\u2019s scarce.<\/p>\n\n\n\n

But the means of learning have just gotten even more abundant. And more importantly than more abundant\u2014because we had abundance before\u2014it\u2019s at the right level. AI can meet you at exactly the level that you are at. So if you have an eighth-grade vocabulary, but you have fifth-grade mathematics, it can talk to you at exactly that level. You will not feel like a dummy. You just have to tune it a little bit until it\u2019s presenting you the concepts at the exact edge of your knowledge.<\/p>\n\n\n\n

So rather than feeling stupid because it\u2019s incomprehensible, which happens in a lot of lessons, in a lot of textbooks, and with a lot of teachers, or feeling bored because it\u2019s too obvious, which also happens, instead, it can meet you exactly where you\u2019re like, \u201cOh yeah, I understood A, and I understood B, but I never understood how A and B were connected together. Now I can see how they\u2019re connected, so now I can go to the next piece.\u201d<\/p>\n\n\n\n

That kind of learning is magical. You can have that aha moment where two things come together over and over again.<\/p>\n\n\n\n

Nivi:<\/strong> Speaking about autodidacticism, a few years ago, I tried to have the AI teach me how to use or learn about the ordinal numbers. It wasn\u2019t that great. But with GPT 5.2 Thinking, I had it teach me the ordinal numbers and it was basically error-free. I only use thinking now even for the most basic queries, because I want to have the correct answer.<\/p>\n\n\n\n

I never let it run auto or fast.<\/p>\n\n\n\n

Naval:<\/strong> Yeah, I\u2019m always using the most advanced model available to me, and I pay for all of them.<\/p>\n\n\n\n

Nivi:<\/strong> But I don\u2019t mind waiting a minute to get an answer for any question, including, \u201cWhat temperature should my fridge be at?\u201d<\/p>\n\n\n\n

Naval:<\/strong> I agree with that, and I think that\u2019s part of what creates the runaway scale economies with these AI models: you pay for intelligence. The model that\u2019s right 92% of the time is worth almost infinitely more than the one that\u2019s right 88% of the time, because mistakes in the real world are so costly that a couple of bucks extra to get the right answer is worth it.<\/p>\n\n\n\n

I\u2019ll write my query into one model, then I\u2019ll copy it and fire it off into four models at once, and then I\u2019ll let them all run in the background. Usually I don\u2019t even check for the answer right away. I\u2019ll come back to the answer a little later and then look at it.<\/p>\n\n\n\n

And then whichever model had the best answer, I\u2019ll start drilling down with that one. In some rare cases where I\u2019m not sure, I\u2019ll have them cross-examine each other\u2014a lot of cut and pasting there. And in many cases I\u2019ll then ask follow-up questions where I\u2019ll have it draw diagrams and illustrations for me.<\/p>\n\n\n\n

I find it\u2019s very easy to absorb concepts when they\u2019re presented to me visually. I\u2019m a very visual thinker, so I will have it do sketches and diagrams, and art\u2014almost like whiteboard sessions. Then I can really understand what it\u2019s talking about.<\/p>\n\n\n\n

If You Can\u2019t Define It, You Can\u2019t Program It<\/h2>\n\n\n\n

Nivi:<\/strong> Let\u2019s talk about the epistemology<\/a> of AI, because I think the next big misconception is: AI is already starting to solve some unsolved basic math problems that a human probably could solve if they cared to, but they haven\u2019t been solved yet\u2014like Erd\u0151s<\/a> Problem Number Whatever.<\/p>\n\n\n\n

Now I think people are taking that, or will take that, as an indicator that the AI is creative. I don\u2019t think it\u2019s an indication that the AI is creative.<\/p>\n\n\n\n

I actually think the solution to the problem is already embedded somewhere in the AI. It just needs to be elicited by prompting.<\/p>\n\n\n\n

Naval:<\/strong> There\u2019s definitely that element to it. And then the question is: what is creativity? It\u2019s such a poorly defined thing.<\/p>\n\n\n\n

If you can\u2019t define it, you can\u2019t program it, and often you can\u2019t even recognize it. So this is where we get into taste or judgment. I would say that the AIs today don\u2019t seem to demonstrate the kind of creativity that humans can uniquely engage in once in a while.<\/p>\n\n\n\n

And I don\u2019t mean like fine art. People tend to confuse creativity with fine art. They\u2019re like, \u201cOh, paintings are creative and AIs can paint.\u201d<\/p>\n\n\n\n

Well, AIs can\u2019t create a new genre of painting. AI can\u2019t move humans with emotion in a way that is truly novel. So in that sense, I don\u2019t think AI is creative.<\/p>\n\n\n\n

I don\u2019t think AI is coming up with what I would call out of distribution. Now the answer to the Erd\u0151s problems that you mentioned may have been embedded within the AI\u2019s training data set, or even within its algorithmic scope. But it was probably embedded in five different places, in three different ways, in two different languages, and seven different computing and mathematical paradigms, and the AI sort of put them all together. Now, is that creativity? Steve Jobs famously said, \u201cCreativity is just putting things together<\/a>.\u201d<\/p>\n\n\n\n

I actually don\u2019t think that\u2019s correct. I think creativity is much more in the domain of coming up with an answer that was not predictable or foreseeable from the question and from the elements that were already known. It was very far out of the bounds of thinking.<\/p>\n\n\n\n

If you were just searching it with a computer or even with an AI and making guesses, you\u2019d be making guesses till the end of time or until you arrived upon that answer. So that\u2019s the real creativity that we\u2019re talking about. But admittedly, that\u2019s a creativity that very few humans engage in, and they don\u2019t engage in it most of the time.<\/p>\n\n\n\n

It becomes harder and harder to see. So we are probably going to get to where if you have a giant list of math problems to be solved and AI starts going through and picking\u2014okay, this one out of that set of one million I can solve, and this set out of 300,000 I can solve, and I need a person to prompt me and ask the right questions\u2014that\u2019s a very limited form of creativity.<\/p>\n\n\n\n

There\u2019s another form of creativity where it starts inventing entirely new scientific theories that then turn out to be true. I don\u2019t think we\u2019re anywhere near that, but I could be wrong. The AIs have been very surprising, so I don\u2019t want to get too much in the business of making prophecies and predictions, but I don\u2019t think that just throwing more compute at the current AI models\u2014short of some breakthrough invention\u2014is going to get us there.<\/p>\n\n\n\n

Nivi:<\/strong> Just to be clear, when I say it\u2019s embedded, I don\u2019t mean the answer\u2019s already written down in there. I just mean that it can be produced through a mechanistic process of turning the crank, which is all today\u2019s computer programs are, where the output is completely determined by the input.<\/p>\n\n\n\n

Naval:<\/strong> Epistemology now gets us into philosophy, because isn\u2019t that just what human brains are doing? Aren\u2019t firing neurons just electricity and weights propagating through the system, altering states and it\u2019s a mechanistic process?<\/p>\n\n\n\n

If you turn the crank on the human brain, you would end up with the same answer? And some people, like I think Penrose<\/a> is out there saying, \u201cNo, human brains are unique because of quantum nanotubes<\/a>.\u201d<\/p>\n\n\n\n

You could argue that some of this computation is taking place at the physical, cellular level, not the neuron level, and that\u2019s way more sophisticated than anything we can do with computers today, including with AI.<\/p>\n\n\n\n

Or you just argue: no, we just don\u2019t have the right program. It is mechanistic. There is a crank to turn, but we\u2019re not running the correct program. The way these AIs run today is just a completely wrong architecture and wrong program.<\/p>\n\n\n\n

I just buy more into the theory that there are some things they can do incredibly well, and there are some things they do very poorly. And that\u2019s been true for all machines and all automation since the beginning of time. The wheel is much better than the foot at going in a straight line at high speeds and traveling on roads. The wheel is really bad for climbing a mountain.<\/p>\n\n\n\n

The same way, I think these AIs are incredibly good at certain things and they\u2019re going to outperform humans. They\u2019re incredible tools. And then there are other places where they\u2019re just going to fall flat.<\/p>\n\n\n\n

Steve Jobs<\/a> famously said that a computer is a bicycle for the mind. It lets you travel much faster than walking, certainly in terms of efficiency.<\/p>\n\n\n\n

But it takes the legs to turn the pedals in the first place. And so now maybe we have a motorcycle for the mind, to stretch the analogy, but you still need someone to ride it, to drive it, to direct it, to hit the accelerator, and to hit the brake.<\/p>\n\n\n\n

The Solution to AI Anxiety Is Action<\/h2>\n\n\n\n

Nivi:<\/strong> When new paradigms and new tool sets come out, there is a moment of enthusiasm and change. And this is true in society, and this is true as an individual. If you ride the moment of enthusiasm in society, it\u2019s exciting and you can learn new things and you can make friends and you can make money.<\/p>\n\n\n\n

Naval:<\/strong> But there\u2019s also a moment of enthusiasm in an individual. When you first encounter AI and you\u2019re curious about it and you\u2019re genuinely open-minded about it, I think that\u2019s the time to lean in and learn about the thing itself. Not just to use it, which of course everyone will, but to actually learn how it works.<\/p>\n\n\n\n

I think diving into and looking underneath the hood is really interesting. If you encounter a car for the first time in your life, yes, you can get in and drive it around, but that\u2019s the moment you\u2019re also going to be curious enough to open up the hood and look at how it\u2019s structured and designed and figure it out.<\/p>\n\n\n\n

I would encourage people who are fascinated by the new technology to really get into the innards and figure it out. You don\u2019t have to figure it out to the level where you can build it or repair it or create your own, but to your own satisfaction.<\/p>\n\n\n\n

Because understanding what\u2019s underneath the abstraction\u2014what\u2019s underneath that command line<\/a>\u2014is going to do two things.<\/p>\n\n\n\n

One is it will let you use it a lot better. And when you\u2019re talking about a tool that has so much leverage, using it better is very helpful.<\/p>\n\n\n\n

Second is it\u2019ll also help you understand whether you should be scared of it or not. Is this thing really going to metastasize into a Skynet<\/a> and destroy the world?<\/p>\n\n\n\n

Are we going to be sitting here and Arnold Schwarzenegger shows up and says, \u201cAt 4:29 AM on February 24th is when Skynet became self-aware,\u201d right? Or is it more that, \u201cHey, this is a really cool machine and I can use it to do A, B, and C, but I can\u2019t use it to do D, E, and F. And this is where I should trust it and this is where I should be suspicious of it.\u201d<\/p>\n\n\n\n

I feel like a lot of people right now have AI anxiety. And the anxiety comes from not knowing what the thing is or how it works, having a very poor understanding.<\/p>\n\n\n\n

And so the solution to that anxiety is action. The solution to anxiety is always action. Anxiety is a non-specific fear that things are going to go poorly and your brain and body are telling you to do something about it, but you\u2019re not sure what.<\/p>\n\n\n\n

You should lean into it.<\/p>\n\n\n\n

You should figure the thing out. You should look at what it is. You should see how it works. And I think that\u2019ll help get rid of the anxiety.<\/p>\n\n\n\n

That action of learning\u2014that pursuit of curiosity\u2014is going to help you get over the anxiety. And who knows, it might actually help you figure out something you want to do with it that is very productive and will make you happier and more successful.<\/p>\n","protected":false},"excerpt":{"rendered":"

Hey, this is Nivi. You\u2019re listening to the Naval Podcast. For the first time in recorded history, we are not at the same location. I am actually walking around town and Naval might be doing the same, so there might be some ambient noise, but we are going to try hard to remove that with AI and some good audio engineering.<\/span> More <\/i><\/a><\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[5,11,13],"tags":[93,54,64,52],"class_list":["post-28496781","post","type-post","status-publish","format-standard","hentry","category-jobs","category-startups","category-technology","tag-ai","tag-entrepreneurship","tag-hiring","tag-startups"],"acf":[],"yoast_head":"\nA Motorcycle for the Mind<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/nav.al\/ai\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A Motorcycle for the Mind\" \/>\n<meta property=\"og:description\" content=\"Hey, this is Nivi. 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