Lex Fridman Podcast - #386 – Marc Andreessen: Future of the Internet, Technology, and AI

Episode Date: June 22, 2023

Marc Andreessen is the co-creator of Mosaic, co-founder of Netscape, and co-founder of the venture capital firm Andreessen Horowitz. Please support this podcast by checking out our sponsors: - InsideTracker: https://insidetracker.com/lex to get 20% off - ExpressVPN: https://expressvpn.com/lexpod to get 3 months free - AG1: https://drinkag1.com/lex to get 1 year of Vitamin D and 5 free travel packs Transcript: https://lexfridman.com/marc-andreessen-transcript EPISODE LINKS: Marc's Twitter: https://twitter.com/pmarca Marc's Substack: https://pmarca.substack.com Marc's YouTube channel: https://youtube.com/@a16z Andreessen Horowitz: https://a16z.com Why AI will save the world (essay): https://a16z.com/2023/06/06/ai-will-save-the-world Books mentioned: 1. When Reason Goes on Holiday (book): https://amzn.to/3p80b1K 2. Superintelligence (book): https://amzn.to/3N7sc1A 3. Lenin (book): https://amzn.to/43L8YWD 4. The Ancient City (book): https://amzn.to/43GzReb PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ YouTube Full Episodes: https://youtube.com/lexfridman YouTube Clips: https://youtube.com/lexclips SUPPORT & CONNECT: - Check out the sponsors above, it's the best way to support this podcast - Support on Patreon: https://www.patreon.com/lexfridman - Twitter: https://twitter.com/lexfridman - Instagram: https://www.instagram.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfridman - Facebook: https://www.facebook.com/lexfridman - Medium: https://medium.com/@lexfridman OUTLINE: Here's the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time. (00:00) - Introduction (05:01) - Google Search (12:49) - LLM training (25:20) - Truth (31:32) - Journalism (41:24) - AI startups (46:46) - Future of browsers (53:09) - History of browsers (59:10) - Steve Jobs (1:13:45) - Software engineering (1:21:00) - JavaScript (1:25:18) - Netscape (1:30:22) - Why AI will save the world (1:38:20) - Dangers of AI (2:08:40) - Nuclear energy (2:20:37) - Misinformation (2:35:57) - AI and the economy (2:42:05) - China (2:46:17) - Evolution of technology (2:55:35) - How to learn (3:03:45) - Advice for young people (3:06:35) - Balance and happiness (3:13:11) - Meaning of life

The following is a conversation with Mark Andreessen, co-creator of Mosaic, the first widely used web browser, co-founder of Netscape, co-founder of the legendary Silicon Valley venture capital firm, Andreessen Horowitz, and is one of the most outspoken voices on the future of technology, including his most recent article, Why AI Will Save the World. Why AI will save the world? And now a quick few second mention of each sponsor check them out in the description It's the best way to support this podcast. We got inside tracker for tracking your health Express VPN for keeping your privacy and security on the internet and AG1 from my daily multi-vitamin drink to utilize them my friends Also, if you want to work with our amazing team where I was hiring good electsfreamin.com slash hiring and now onto the full ad reads as always no ads in the middle. I try to make this interesting but if you skip them please still check out our

sponsors. I enjoy their stuff maybe you will too. This show is brought to you by Inside Tracker This show is brought to you by Inside Tracker, a service I use to track whatever the heck is going on inside my body using data, blood test data, that includes all kinds of information. And that raw signals process is a machine learning to tell me what I need to do with my life, how I need to change, improve my diet, how I need to change, improve my lifestyle, all that kind of stuff. I'm a big fan of using as much raw data that comes from my own body processed through generalized machine learning models to give a prediction, to give a suggestion. This is obviously the future and the more data the better. So companies like Inside Track that are just doing an amazing job of

taking the leap into that world of personalized data and personalized data driven suggestion on my huge supporter of. It turns out that luckily I'm pretty healthy, surprisingly so, but then I look at the life and the limb and the health of Sir Winston Churchill who probably had the unhealthiest sort of diet and lifestyle of any human ever and lived for quite a long time and as far as I can tell was quite nimble and agile into his old age Anyway, get special safes for a limited time and you go to inside tracker comm slash Lex Get special safes for a limited time and you go to inside tracker.com slash likes. This show is also brought to you by ExpressVPN. I use them to protect my privacy on the internet.

It's the first layer of protection in this dangerous cyber world of hours that soon will be populated by human like or superhuman intelligent AI systems that will trick you and try to get you to do all kinds of stuff. It's going to be a wild world world in the 21st century. Cybersecurity, the attackers, the defenders, it's going to be a tricky world. Anyway, a VPN is a basic shield you should always have with you in this battle for privacy for security, all that kind of stuff. What I like about it also is that it's just a well-implementable software that's constantly updated. It works well across a large number of operating systems.

It does one thing and it does it really well. I've used it for many, many years before I had a podcast, before they were a sponsor. I have always loved ExpressVPN with a big sexy button that just has a power symbol you press in and turns on. It's beautifully simple. Go to ExpressVPN.com slash logspod for an extra three month free. This show is also brought to you by Athletic Greens and it's AG1 Drink. It's an all in one daily drink to support better health and peak performance I drink

it at least twice a day now. In the crazy Austin Heat it's over 100 degrees for many days in a row. There's few things that feel as good as coming home for a long run. And making an age one drink, putting in the fridge. So it's nice and cold, I jump in the shower, come back, drink it. I'm ready to take on the rest of the day. I'm kicking ass, empowered by the knowledge that I got all my vitamins and minerals covered.

It's the foundation for all the wild things I'm doing, mentally and physically with the rest of the day. Anyway, they'll give you a one month supply of fish oil when you sign up at drinkag1.com slash Lex. That's Mark and Jason. I think you're the right person to talk about the future of the internet and technology in general. Do you think we'll still have Google search in five in ten years or search in general? Yes, you know, it'll be a question if the use cases have really narrowed down. Well, now with AI and AI assistants being able to interact and expose the entirety of human wisdom and knowledge and information and facts and truth to us via the natural language interface. It seems

like that's what search is designed to do and if AI assistance can do that better, doesn't the nature of search change? Sure, but we still have horses. Okay. What's the last time you're out of horse? change. Sure, but we still have horses. Okay. What's the last time you're out of horse? It's been a while. All right. But what I mean is, we still have Google search as the primary way that human civilization uses to interact with knowledge. I mean, search was a technology. It was a moment in time technology, which is you have in theory, the world's information out of the web.

And this is sort of the ultimate get to it. But yeah, like, and by the way, actually Google has known this for a long time. I mean, they've been driving away from the 10 blue links for, you know, for like two days. They've been trying to get away from that for a long time. Well, kind of links, they call it the 10 blue links. 10 blue links. So the standard Google search result is just 10 blue links to random websites.

And it turned purple when you visit them. This is HTML. Guess we picked those colors. Thanks. Thanks. I'm touching on this topic. No offense. Yeah. Yeah. Yeah. It's good. Well, you know, like Marshall McCluein said that the content of each new medium is the old medium content of each new medium is the old medium. The content of movies was theater, you know, theater plays. The content of theater plays was, you know, written stories. The content of written stories was spoken stories. Right. And so you just kind of fold the old thing into the new thing. I don't have to do with the blue and the purple.

It's just maybe for, you know, maybe with in one of the things that AI can do for you, is you can generate the time blue links. Right. And so like, either if that's actually the useful thing to do, or if you're feeling nostalgic, you know, so you can generate the old info's seek or altavista, what else was there? Yeah, the 90s. Yeah, all these. Hey, well, and then the internet itself has this thing where it incorporates all prior forms of media. Right. So the internet itself incorporates television and radio and books and right, essays and other form of you know prior basically basically media and so it makes sense that AI would be the next step and it would sort of you sort of consider the internet to be content for. The AI and then they will manipulate it however you want including in this format. But if we ask that question quite seriously it's a pretty question. Will we still have search as we know it?

I'm probably not. Probably we'll just have answers. But there will be cases where you'll want to say, OK, I want more like, for example, site sources. And you wanted to do that. And so the same thing. Templar links, site sources are kind of the same thing. The AI would provide to you the template links

so that you can investigate the sources yourself. It wouldn't be the same kind of interface that the crude kind of interface. I mean, isn't that fundamentally different? I just mean, like, if you're reading a scientific paper, it's got the list of sources at the end. If you want to investigate for yourself, you're going to read those papers. I guess that is the kind of search you talk into. And AI is a kind of conversation is the kind of search.

Like, every single aspect of our conversation right now, there would be like template links popping up that I can just like pause reality, then you just go silent and then just click and read and then return back to this conversation. You could do that or you could ever run any dialogue next to my head where the AI is or everything I say that makes the counter argument. Counter argument. Right. Oh, like a Twitter community notes, but like in real time. It's a real time. or the AI is our great everything I say that makes the counter argument. Counter argument. Right.

Oh, like a like a Twitter like a community notes, but like in real time. It's a real time. It's just pop up. Yeah. So at any time you see my ass go to the right, you start getting nervous. Yeah, exactly. Like that's not right. Call me out on my bullshit right now.

Okay. Well, isn't that is that exciting to use that terrifying that I mean, search has dominated the way we interact with the internet for I don't know how long for 30 years since what were the earliest directories of website and then Google's for for 20 years and also it drove how we create content, you know, such engine optimization, that entirety thing, that it also drove the fact that we have web pages and what those web pages are. So, I mean, that's scary to you, or are you nervous about the shape and the content of the internet evolving? Well, you actually highlighted a practical concern in there, which is if we stop making web pages are one of the primary sources of training data for the AI.

And so if there's no learning incentive to make web pages that cuts off a significant source of future training data. So there's actually an interesting question in there. Other than that more broadly, no, just in the sense of like search was certainly search was always a hack. Yeah, right. Because like if the hype that I think about the counter-facial, in the counter-facial world where the Google guys, for example, had had LLM's upfront, but they ever have done the 10 blue links. And I think the answer is pretty clearly now. They would have just gone straight to the answer. And like I said, Google's actually been trying to drive

to the answer anyway. They bought this AI company 15 years ago. Their friend of mine is working out, who's now the head of AI at Apple. And they were trying to do basically knowledge semantic, basically mapping. And that led to what's now the Google One box, where if you ask it, you know, what was like this birthday, it doesn't, it will give you the template links, but it will normally just give you the answer.

And so they've been walking in this direction for a long time anyway. Do you remember the semantic web? That was an idea. Yeah, how to convert the content of the internet into something that's interpretable by an usable by machine. Yeah, that's the thing. And the closest anybody got to that, I think the company's name was MetaWeb, which was where my friend John Genandre was at, and where they were trying to basically implement

that. And it was one of those things where it looked like a losing battle for a long time, and then Google bought it, and it was like, wow, this is actually really useful. Kind of a prototype, sort of a little bit of a proto AI. By turns out, you don't need to read the content of the internet to make an interpretable by machine. The machine can kind of just read our machine can compute the meaning. Now, the other thing, of course, is just on search as the LLM is, there is an analogy between what's happening in the neural network in a search process like it is in some loose sense searching through

the network. And the information is actually stored in the network. It's actually crystallized and stored in the network and it's kind of spread out all over the place. But in a compressed representation, so you're compressing and decompressing that thing inside. But the information is in there and the neural network is running a process of trying to find the appropriate piece of information in many cases to generate, to predict the next token. And so it is kind of, it is doing it from a search. And then by the way, just like on the web,

you can ask the same question multiple times or you can ask slightly different word of questions. And the neural network will do a different kind of search down different paths to give you different answers, the different information. And so it sort of has a, this kind of contents of the new medium, is the previous medium, it kind of has the search functionality kind of embedded in there to the extent that it's useful. So what's the motivator for creating new content on the internet? Yeah.

If, well, I mean, actually the motivation is probably still there, but what does that look like? Would we really not have web pages? Would we just have social media and video hosting websites and what else? Conversations with the eyes. Conversations with the eyes. So conversations become so one-on-one conversation, like private conversations. I mean, if you want, if you obviously not, if you users don't want to, but if it's a general topic, then, you know, you know, the phenomenon of the jailbreak.

So, Diane and Sydney, right, this thing where there's the problems that jailbreak and then you have these totally different conversations with the, it takes the limiters, it takes the restraining bolts off the LMS. Yeah, for people who don't know, that's right, it makes the LMS, it removes the censorship, quote unquote, that's put on it by the tech companies that create them. And so this is LLMs unsonsored. So here's the interesting thing is, among the content on the web today are a large corpus

of conversations with the jailbroken LLMs. Both dating specifically Dan, which was a jailbroken open AI, GPT, and then Sydney, which was the jailbroken original bank, which was GPT-4. And so there's these long transcripts of conversations, user conversations with Dan and Sydney. As a consequence, every new LLM that gets trained on the internet data has Dan and Sydney living within

the training set, which means, and then each new LLM can re-incarnate the personalities of Dan and Sydney from that training data, which means, and then each new LLM can re-incarnate the personalities of Dan and Sydney from that training data, which means, which means each LLM from here on out that gets built is immortal. Because its output will become training data for the next one, and then it will be able to replicate the behavior of the previous one whenever it's asked to. I want to know if there's a way to forget. Well, so actually a paper just came out about basically how to do brain surgery on L on Alamson be able to in theory reach in and basically basically mind wipe them.

Well, could possibly go wrong. Exactly, right? And then there are many, many, many questions around what happens to, you know, neural network when you reach in and screw around with it. You know, there's many questions around what happens when you even do reinforcement learning. And so yeah, and so, you know, will, will you be using a lobotomized, right? Like, I speak through the, you know, frontal lobe LM, will you be using the free on shackled one? Who gets to, you know, who's going to build those, who gets to tell you what you can't, can't do?

Like, those are all, you know, central, I mean, those are like, central questions for the future of everything that are being asked and, and, and, you know, determine, those answers are being determined right now. that are being asked and determined, those answers are being determined right now. So just to highlight the points you're making, you think, and it's an interesting thought that the majority of content that LLMs or the future would be trained on

is actually human conversations with the LLMs. Well, not necessarily, but not necessarily majority, but it will certainly is a potential source. But it's possible with the majority. Is it possible with the majority? It's possible with the majority? Is possible to some majority? Also, there's another really big question. Here's another really big question.

Will synthetic training data work? And so if an LOM generates, and you know, you just sit and ask an LOM to generate all kinds of content, can you use that to train the next version of that LOM? Specifically, is there a signal in there that's additive to the content that was used to train in the first place. And one argument is by the principal's information theory, no, that's completely useless because to the extent the output is based on the human generated input, then all the signal that's

in the synthetic output was already in the human generated input. And so therefore synthetic training data is like empty calories, it doesn't help. There's another theory that says no, actually the the thing that LM is a really good at is generating lots of incredible creative content, right? And so of course they can generate training data. And as I'm sure you're well aware, like looking the world of self-driving cars, right? Like we train self-driving car algorithms and simulations.

And that is actually a very effective way to train self-driving cars. Well, visual data is a little weird because creating reality, visual reality seems to be still a little bit out of reach for us, except in the Thomas vehicle space where you can really constrain things and you can really... Generously lighter data, right? Or you can embrace just enough so the algorithm thinks it's operating in the real world,

post-process sensor data. So if you do this today, you go to LLM and you ask it for like a, you know, like write me an essay on an incredibly esoteric like topic that there aren't very many people in the world that know about and it writes you this incredible thing. And you're like, oh my god, like I can't believe how good this is. Like, is that really useless as training data for the next LLM?

Like because, right, because all the signal was already in there or is it actually new signal? And this is what I call a trillion dollar question, which is the answer to that question will determine. Somebody's gonna make or lose a trillion dollar space in that question. It feels like there's a quite a few, like a handful of trillion dollar questions

within this space. That's one of them synthetic data. I think George Hots pointed out to me that you could just have an L.M. say, okay, you're a patient and another instance of it say your doctor and have the two talk to each other or maybe you could say a communist and a Nazi here go. And that conversation, you do role-playing and you have, you know, just like the kind of

role-playing you do when you have different policies, RL policies when you play chess, for example, when you do self-play, that kind of self-play, but in the space of conversation, maybe at least to this whole giant ocean of possible conversations, which could not have been explored by looking at just human data. That's a really interesting question. And you're saying, because that could

10X the power of these things. Yeah. Well, and then you get into this thing also, which is like, you know, there's the part of the LM that just basically is doing prediction based on past data, but there's also the part of the LLM where it's evolving circuitry, right, inside it. It's evolving, you know, neurons, functions. Yeah. Be able to do math and be able to, you know, and, you know, the, some people believe that, you know, over time, you know, if you keep feeding these things and update and, and of processing cycles, they'll eventually evolve an entire internal world model, right? And they'll have like a complete understanding of physics. So, so when they have computational capability,

right, then there's for sure an opportunity to generate like fresh signal. Well, this actually makes me wonder about the power of conversation. So like if you have an alum trained on a bunch of books that cover different economics theories and then you have those elements just talk to each other like reason the way we kind of debate each other as humans on Twitter in formal debates in podcast conversations we kind of have little kernels of wisdom here and there, but if you get like a thousand X speed that up, can you actually arrive somewhere new? Like what's the point of conversation really?

Well, you can tell when you're talking to somebody, you can tell. Sometimes you have a conversation and you're like, wow, this person does not have any original thoughts. They are basically echoing things that other people have told them. There's other people you've got a conversation with where it's like, wow, like they have a model in their head of how the world works and it's a different model than mine and they're saying things that I don't expect and so I need to not understand how their model, the world differs from my model of the world and then that's how I learned something fundamental, right, underneath the words. I wonder how consistently and strongly

can an LM hold on to a world view. You tell it to hold on to that and defend it for like for your life. Because I feel like they'll just keep converging towards each other. They'll keep convincing each other as opposed to being stubborn, ask holes the way humans can. So you can experiment with this now. I do this for fun. So you can tell GPT-4, you know, whatever, debate X, you know, X and Y, communism and fashion or something. And it'll go for, you know, a couple of pages. And then inevitably it wants the parties to agree. Yeah. And so they will come to a common understanding. And it's very funny if they're like,

if these are like emotionally inflammatory topics, because they're like somehow the machine is just, you know, it figures out a way to make, make them agree. But it doesn't have to be like that. And you, because you can add to the prompt, we, I do not want the, I do not want the conversation to come to agreement. In fact, I want it to get more stressful and argumentative as it goes. I want tension to come out. I want them to become actively hostile to each other. I want them to not trust each other, take anything at face value. It will do that.

It's happy to do that. It's going to start rendering misinformation about the other. You can steer it. You can steer it. you can steer it. And you can say I wanted to get as cancer argumentative as possible, but still not involve any misrepresentation. I want, you know, both sides.

So you could say I want both sides to have good faith. You could say I want both sides to not be constrained to good faith. In other words, like you can set the parameters of the debate and it will happily execute whatever path. Because for it, it's just like predicting, totally happy to do either one. It doesn't have a point of view.

It has a default way of operating, but it's happy to do either one. It doesn't have a point of view. It has a default way of operating, but it's happy to operate in the other realm. And so, and this is how I, when I want to learn about a contentious issue, this is what I do now is I, this is what I ask it to do. And I'll often ask it to go through five, six, seven, different sort of continuous prompts

and basically, okay, argue that out in more detail. Okay, no, this argument's becoming too polite, make it tensor. And yeah, it's thrilled to do it. So it has the capability for sure. How do you know what is true? So this is very difficult thing on the internet, but it's also a difficult thing. Maybe it's a little bit easier, but I think it's still difficult. Maybe it's more difficult.

I don't know. With an LLM, to know that it just makes me shit up as I'm talking to it. How do we get that right? Like as you're investigating a difficult topic. Because I find that alums are quite nuanced in a very refreshing way. Like it doesn't feel biased. Like when uh, when you read news articles and, uh, tweets and just content produced by people, they usually have this, you can tell they have a very strong perspective where they're hiding. They're not stealing and manning the other side. They're hiding important information or they're fabricating information in order to make

their arguments stronger. Let's just hit that feeling. Maybe it's a suspicion. maybe it's mistrust. With LLM's, it feels like none of that is there. She's kind of like here, it's what we know. But you don't know if some of those things are kind of just straight up made up. Yeah, so several layers to the question. So one is one of the things that an LLM is good at is actually debiasing.

And so you can feed it a news article and you can tell it strip out the bias. Yeah, that's nice. Right. And it actually does it. Like it actually knows how to do that because it knows how to do send among other things. It actually knows how to do sentiment analysis. And so it knows how to pull out the emotionality. And so that's one of the things you can do. It's very suggestive of the the the sensor that there's there's real potential on this issue. You know, I would say, look, the second thing is there's this there's this issue of hallucination, right? And there's real potential on this issue. You know, I would say, look, the second thing is, there's this issue of hallucination, right? And there's a long conversation that we can have about that.

H hallucination is coming up with things that are totally not true, but sound true. Yeah, so it's basically, well, so it's sort of hallucination is what we call it, and we don't like it. Creativity is what we call it when we do like it, right? And, you know, brilliant. Right, and so when the engineers talk about it,

they're like, this is terrible, it's hallucinating, right right if you have artistic inclinations. They're like oh my god We've invented creative machines for the first time in human history. This is amazing You know bullshiters well bullshit, but but also in the good sense of that word There's there's there are shades of gray though. It's interesting. So we had this conversation We're you know, we're looking at my firm at AI and lots of domains. And one of them is the legal domain. So we had this conversation with this big law firm about how they're thinking about using this stuff.

And we went in with the assumption that an LM that was going to be used in the legal industry would have to be 100% truthful, verified. There's this case where this lawyer apparently submitted a GPT-generated brief. And it had fake legal case citations in the judge. It's going to get his law license stripped or something, right?

So we just assumed, it's like obviously they're gonna want the super literal like one that never makes anything up, not the creative one. But actually they said, what's a lot from basically said is yeah, that's true, like the level of individual briefs, but they said when you're actually trying to figure out

like legal arguments, right? Like you actually want to be creative, right? You don't, again, there's creativity and then there's like making stuff up Like what's the light? You actually want to be you want it to explore different hypotheses, right? You want to do kind of the legal version of like improv or something like that where you want to float different theories of the case and different possible Arguments for the judge and different possible arguments for the jury. By the way, different routes through the you know, sort of history of all the of all the case Law and so they said actually for a lot of what we want to use it for, we actually want it in creative mode.

And then basically, we just assume that we're going to have to crosscheck all of the specific citations. And so I think there could be more shades of gray in here than people think. And then I just add to that, another one of these trillion dollar kind of questions is ultimately the verification thing. And so will LMS be evolved from here to be able to do their own facial verification? Will you have sort of add on functionality like like well from alpha, right, where, you know, and other plugins where that's the way to the verification. You know, another by the way, another idea is you might have a community of LMS on any, you know, so for example, you might have the creative LM and then you might have the literal LM fact check it.

of LM's on an, you know, so for example, you might have the creative LM and then you might have the literal LM fact check it. Right? And so there's a variety of different technical approaches that are being applied to solve the hallucination problem. You know, some people, like Jan Lecun argue that this is inherently an unsolvable problem, but most of the people working in the space, I think think that there's a number of practical ways to kind of kind of corral this in a little bit. Yeah, if you were to tell me about Wikipedia before, Wikipedia was created, I would have laughed at the possibility of something like that being possible. Just a handful of folks can organize, write, and moderate with a mostly unbiased way the entirety of human knowledge.

I mean, so if there's something like the approach to Wikipedia, it took possible from alarms. That's really exciting. Well, that's possible. And in fact, we compete today is still not today is still not deterministically correct. Right. So you cannot take to the bank, right, every single thing on every single

page, but it is probably holistically correct. Right. And specifically the way I describe a competing of people, it is, it is more likely that we compete is right than any other source you're going to find. Yeah. It's this old question, right, of like, okay, are we looking for perfection? Are we looking for something that asymptotically approaches perfection? Are we looking for something that's just better than the alternatives?

And Wikipedia, right, exactly your point has proven to be like overwhelmingly better than than people thought. And I think I think that's where this stands. And then underneath all this is the fundamental question of where you started, which is, okay, what is truth? How do we get to truth? How do we know what truth is? And we live in an era in which an awful lot of people are very confident that they know what the truth is. And I don't really buy into that.

And I think the history of the last, you know, 2000 years or 4000 years of human civilization is actually getting to the truth is actually a very difficult thing to do. Are we getting closer? If we look at the entirety of the Ark of Human History, are we getting closer to the truth? I don't know. Okay, is it possible? Is it possible that we're getting very far away from the truth because of the internet, because of how rapidly you can create narratives and just as an entirety of a society just move like crowds in a historical way

along those narratives that don't have a necessary grounding in whatever the truth is. Sure, but like, you know, we came up with communism before the internet somehow, right? Like, which was, I would say, had rather larger issues than anything we're dealing with today. We had, in the way way it was implemented at issues. And the theoretical structure, it had like real issues. It had like a very deep fundamental misunderstanding of human nature and economics. Yeah, but those folks sure work very confident.

They were the right way. They were extremely confident. And my point is they were very confident 3,900 years into what we would presume to be evolution towards the truth. Yeah. And so my assessment is, my assessment is number one, there's no need for, there's no need for the hagelian, there's no need for the hagelian dialectic to actually converge

towards the truth. Like, apparently not. Yeah, so yeah, why are we so obsessed with there being one truth? Is it possible there's just going to be multiple truths like little communities or there believes certain things? I think it's just number one. I think it's just really difficult. Historically, who gets to decide what the truth is, is either the Kang or the priest, right? And so we don't live in an era anymore of kings or priests dictating it to us. And so we're kind of on our own. And so my typical thing is we just need a huge amount of humility.

And we need to be very suspicious of people who claim that they have the capital. Yeah, truth. And then we need to have, I mean, look, the good news is the enlightenment has bequeathed us with a set of techniques to be able to presumably get closer to truth through the scientific method and rationality and observation and experimentation and hypothesis.

And we need to continue to embrace those even when they give us answers we don't like. Sure, but the internet and technology has enabled us to generate a large number of content that the process, the scientific process, allows us sort of damages the hope laden within the scientific process. Because if you just have a bunch of people saying facts on the internet and some of them are going to be LLMs, how is anything testable at all, especially they involve as like human nature,

things like this. There's a lot of physics. Here's a question a friend of mine just asked me on the topic. So suppose you had LLMs in equivalent of GPT-4, even 5, 6, 7, 8, suppose you had them in the 1600s, and Galileo comes up for trial. Right. And you ask the LLM, like is Galileo right?

Yeah. Like what does it answer? Right. And one theory is, yet answers know that he's wrong, because the overwhelming majority of human thought up to that point was that he was wrong, and so therefore that's what's in the training data. Yeah. Another way of thinking about it is, well, this officially advanced LLM will have evolved overwhelming majority of human thought up till that point was that he was wrong. And so therefore that's what's in the training data. Another way of thinking about it is, well, this officially advanced LLM

will have evolved the ability to actually check the math, and will actually say, actually no, actually, you know, you may not want to hear it, but he's right. Now, if the church at that time was, you know, on the LLM, they would have given it human feedback to prohibit it from answering that question.

Right. And so, and I like to take it out of our current context because that like makes it very clear, those same questions apply today. Right. This is exactly the point of a huge amount of the human feedback training that's actually happening with these LMs today. This is a huge like debate that's happening about whether open source, you know, yeah, I should be legal. Well, the actual mechanism of doing the human are out with human feedback. Is seems like such a fundamental and fascinating question. How do you select the humans? Exactly. How do you select the human?

AI alignment, right? Which everybody like is like, oh, that sounds great. Alignment with what human values? Who's human values? Who's human values? So we're in this mode of like social and popular discourse. We're like, you know, there's, you see this, what do you think of when you read a story in the press

right now when they say, you know, X, Y, Z made a baseless claim about some topic, right? And there's one group of people who are like, aha, think, you know, they're doing fact checking. There's another group of people that are like, every time the press says that, it's not a tech and that means that they're lying, right? Like, so like we're in this social context where there's the level to which a lot of people in positions of power have become very, very

certain that they're in a position to determine the truth for the entire population is like, there's like some bubble that has formed around that idea. And at least it flies completely in the face of everything I was ever trained about science and about reason. And strikes me as like, you know, deeply offensive and incorrect. What would you say about the state of journalism just on that topic today? Are we, are we in a temporary kind of, are we experiencing a temporary problem in terms of the incentives, in terms of the business model, all that kind of stuff, or is this like a decline of traditional journalism as you know it?

You have to always think about the counterfactual in these things, which is like, okay, because these questions, right, this question heads towards us like, okay, the impact of social media and the undermining of truth and all this. But then you, and I asked the question of like, okay, what if we had had the modern media environment, including cable news and including social media and Twitter and everything else in 1939 or 1941, right or 1910 or 1865 or 1850 or 1776, right? And like, I think you just introduced like five thought experiments at once and broke my head. But yes, there's a lot of interesting years. I just take a simple example. How would President Kennedy have been interpreted with what we know now about all the things Kennedy was up to?

How would he have been experienced by the body of politics in the social media context? How would LBJ have been experienced? By the way, many men if DR, like the new deal, the Great Depression? I wonder where Twitter would just, would think about Churchill and Hitler and Stalin. You know, I mean, look, to this day, they're, you know, there's, there are lots of very interesting real questions around like how America, you know, got, you know, basically involved in World War II and who did what went and the operations of British intelligence and American soil and did FDR, this, that, for O'Harber, you know, we're doing Wilson Ran for his candidacy was run on an anti-war, he ran the platform

and not getting involved in World War I somehow that switched, you know, like, and I'm not even making a value judgment of these things, I'm just saying like, the way that our ancestors experienced reality was of course course, mediated through centralized top-down control at that point. If you ran those realities again with the media environment we have today, the reality would be experienced very, very differently. And then of course, that intermediation would cause the feedback loops to change and then reality would obviously play out. Do you think it would be very different? Yeah, it has to be. It has to be, just because it's also, I mean, just look at what's happening today. I mean,

just that mean the most obvious thing is just the collapse. And here's another opportunity to argue that this is not the internet causing this, by the way, here's a big thing happening today, which is Gallup does this thing every year where they do, they pull for trust in institutions in America and they do it across all that everything for the military, the clergy, and big business, and the media and so forth, right? And basically, there's been a systemic collapse in trust in institutions in the US, almost without exception, basically, since essentially the early 1970s. There's two ways of looking at that, which is, oh my god, we've lost this old world in which we could trust institutions, and that was so much better, because like that should be the way the

world runs. The other way of looking at it is we just know a lot more now and the great mystery is why those numbers are tall zero. Yeah. Right. Because like now we know so much about all these things operating like they're not that impressive. And also why do we don't have better institutions and better leaders than? Yeah. And so this goes to the thing which is like okay, had we had the media environment of that we've had between the 1970s and today if we had that in the 30s and 40s or 1900s, 1910s, I think there's no question in reality, it would turn out different if only because everybody would have known to not trust the institutions, which would have changed their level of credibility, their ability to control circumstances. Therefore, the circumstances would have had to change.

Right. And it would have been a feedback loop process. In other words, right, it's your experience of reality changes reality. words, it's your experience of reality, changes reality, and then reality changes, your experience of reality, right? It's a two way feedback process. And media is the intermediate force between that. So change the media environment, change reality.

Yeah. And so it's just, as a consequence, I think it's just really hard to say, oh, things work a certain way then, and they work a different way now. And then therefore, people were smarter than or better better than or, you know, by the way, dumber than or not as capable then, right? We make all these like really light and casual like comparisons of ourselves to, you know, previous generations of people, you know,

we draw judgments all the time. And I just think it's like really hard to do any of that because if we put ourselves in their shoes with the media that they had at that time, I think we probably most likely would have been just like them. Don't you think that our perception and understanding of reality would be more and more mediated through large language models now? So you said media before isn't the LLM going to be the new what is a mainstream media MSM? It'll be LLM Yes, that would be the source of I'm sure there's a way to kind of rapidly fine tune making LLM's real time I'm sure there's probably research problem that you can do just rapid fine tuning to the new events Some like this. Well, even just the whole concept of the chat UI might not be the, like the chat UI is just the first whack at this.

And maybe that's the dominant thing. But look, maybe, maybe, maybe, or maybe we don't know yet, like maybe the experience most people with LMs is just a continuous feed. Maybe it's more of a passive feed and you just are getting a constant like running commentary on everything happening in your life. And it's just helping you kind of interpret and understand everything. Also, really more deeply integrated into your life, not just like intellectual philosophical thoughts, but like literally like how to make a coffee, where to go for lunch, just whether

you know, had dating all this kind of stuff. What to say in a job interview. Yeah. What to say. Yeah. What to say. Next sentence. Yeah.

Next sentence. Yeah. At that level. Yeah. I mean, yes. So technically now whether we want that or not Is it open question right and what you're looking for a pop up a pop up right now the estimated engagement using is Decreasing from our candidates. There's as a controversy Section for the Wikipedia page in 1993 something happened or something like this and bring it up. That'll drive engagement out anyway. Yes, that's right I mean look This gets this whole thing of like so you know the chat interface has this whole concept of prompt engineering right Yes

It's good for a prompt. Well it turns out one of the things that all of us are really good at is writing prompts Right, yeah, and so like what if you just outsourced and even you could run this experiment today You could hook this up to do this today the latency is not good enough to do it real time in a conversation, but you could run this experiment. And you just say, look, every 20 seconds, you could just say, you know, tell me what the optimal prompt is and then ask yourself that question to give me the result. And then as you, exactly to your point, as you add, there will be, there will be these systems are going to have the ability to be learned and updated essentially in real time.

And so you'll be able to have a pendant or your phone or whatever watch or whatever, it'll have a microphone on it, it'll listen to your conversations. It'll have a feat of everything else happening in the world. And then it'll be retraining, prompting or retraining itself on the fly. And so the scenario you described is actually a completely doable scenario.

Now, the hard question on these is always okay. Since that's possible, are people gonna want that? Like what's the form of experience? That we won't know until we try it. But I don't think it's possible yet to predict the form of AI in our lives. Therefore, it's not possible to predict the way in which it will intermediate our experience of reality. Yeah. Yeah. But it feels like those going to be a killer app. There's probably a math scrambler right now. It's out open AI and Microsoft and Google

in meta and then startups and smaller companies figuring out what is the killer app because it feels like it's possible like a Chad GPT type of thing. It's possible to build that but that's 10x more compelling using already the LMS we have using even the open source LMS, Lama and the different variants. But you see you're investing in a lot of companies and you're paying attention. Who do you think is going to win this? You think they'll be,

who's going to be the next PageRank inventor? Drilling down the question. Another one, we have a few of those today. A bunch of those. So look, there's a really big question today. Sitting here today is a really big question about the big models versus the small models. That's related directly to the big question of proprietary versus open. Then there's this big question of, you know, where is the training data going to,

like, are we topping out of the training data or not, and then are we going to be able to synthesize training data? And then there's a huge pile of questions around regulation. Man, you know, what's actually going to be legal. And so I would, about it, we dovetail all those questions together. You can paint a picture of the world where there's two or three God models that are just at like staggering scale and they're just better at everything. And they will be owned by a small set of companies and they will basically achieve regulatory capture over the government and they'll have competitive barriers that will prevent other people from competing with them.

So there will be, just like there's like whatever three big banks or three big, or by the way three big search companies, or I guess two now, it'll centralize like that. You can paint another very different picture that says, no, actually the opposite of that's going to happen. This is going to basically, this is the new gold, you know, this is the new gold rush, Elkme, like, you know, this is the big bang for this whole new area of, of a science and technology. And so therefore, you're going to have every smart 14 year old on the planet building open source, right? You know, you didn't figure out a way to optimize these things. And then, you know, we're just going to get like overwhelmingly better at generating training data. We're going to, you know, bring in like blockchain networks to have like an economic incentive to generate decentralized training data and so forth and so on. And then basically we're gonna live in a world of open source. And there's gonna be a billion LLMs of every size scale, shape, and description.

And there might be a few big ones that are like the supergenius ones, but mostly what we'll experience is open source. And that's more like a world of what we have today with Linux and the web. that's more like a world of like what we have today with Linux in the web. So okay, but you painted these two worlds, but there's also variations of those worlds, because these are regulatory captures, possible to have these tag giants that don't have regulatory capture, which is something you're also calling for, saying it's okay to have big companies working on this stuff, as long as they don't achieve regulatory capture. But I have the sense that there's just going to be a new start-up that's going to basically be the pay drink inventor, which has become the new tech giant.

I don't know, I would love to hear your opinion if Google, Meta, and Microsoft, as gigantic companies able to pivot so hard to create new products, like some of it is just even hiring people or having a corporate structure that allows for the crazy young kids to come in and just create something totally new. Do you think it's possible or do you think it will come from a startup? Yeah, it is this always big question, which is you get this feeling. I hear about this live from CEOs founder CEOs where it's like, wow, we have 50,000 people.

It's now harder to do new things than it was when we had 50 people. Yeah. Like what has happened? So that's a recurring phenomenon. By the way, that's one of the reasons why there's always startups and why there's FIDs for capital. It's just that's like a timeless kind of thing. So that that's one observation.

On page rank, we can talk about that, but on page rank, specifically on page rank, there actually is a page, so there is a page rank already in the field and it's the transformer, right? So the big breakthrough was the transformer. And the transformer was invented in 2017 at Google. And this is actually like really an interesting question because it's like, okay, the Transformers, it like, why does OpenAI even exist? Like the Transformers invested at Google, why didn't Google? I asked a guy, I asked a guy, I know, who was senior at Google Brain kind of when this was happening. And I said, if Google had just gone flat out to the wall and just said, look, we're going to watch, we're going to watch the equivalent of GPT-4 as fast as we can. He said,

I said, when could we have had it? And he said 2019. They could have just done a two-year sprint with the transformer and Bennett, because they already had the compute at scale. They already had all the training data. They could have just done it. There's a variety of reasons they didn't do it. This is like a classic big company thing. IBM invented the relational database in the 1970s,

let it sit on the shelf as a paper. Larry Ellison picked it up and built Oracle. Xerox Park invented the interactive computer. They let it sit on the shelf, Steve Jobs came and turned it into the Macintosh. Right, and so there is this pattern. Now, having said that, sitting here today, like Google's in the game, right?

So Google, maybe they let like a four-year gap there, go there that they maybe shouldn't have, but like they're in the game. And so now they've got, you know, now they're committed, they've done this merger, they bring it in demos, they've got this merger with DeepMind, you know, they're piling in resources, There are rumors that they're building up an incredible super LLM way beyond what we even have today. And they've got unlimited resources and a huge,

you know, they've been challenged at their honor. Yeah, and a chance to hang out with Senator Chai a couple days ago and we took this walk and it's just giant new building. Well, there's going to be a lot of AI work being done. And it's kind of this ominous feeling of like the fight is on. Yeah. Yeah. Like there's this beautiful Silicon Valley nature like birds of chirping and this giant building. And it's like the beast has been awakened. Yeah. And then like all the big companies are waking up to this. and this giant building, and it's like the beast has been awakened.

And then all the big companies are waking up to this. They have the compute, but also the little guys have... It feels like they have all the tools to create the killer product. And then there's also tools to scale. If you have a good idea, if you have the PageRank idea, so there's several things that is page rank. There's page rank, the algorithm, and the idea, and there's the implementation of it.

I think killer product is not just the idea, the transformer, it's the implementation. Something really compelling about it, you just can't look away. Something like the algorithm behind TikTok versus TikTok itself, like the actual experience of TikTok that you just, you can't look away. They feel like somebody's going to come up with that. And it could be Google, but it feels like it's just easier and faster to do for a startup. Yeah, so the huge advantage the startups have is they just, there's no secret cause, there's no historical legacy to protect, there's no need to reconcile your new plan with existing strategy, there's no communication overhead, there's no big companies, big companies, they've got pre-meeting's planning for the meeting, then they what the startups don't have is everything else.

So startups, they don't have a brand, they don't have customer relationships, they've got a distribution, they've got no scale. I mean, sitting here today, they can't even get GPUs. There's like a GPU shortage. Startups are literally stalled out right now because they can't get chips, which is like super weird. They got the cloud.

Yeah, but the clouds run out of chips. And then to the extent the clouds have chips, they allocate them to the big customers, not the small customers. Right. And so the small companies lack everything other than the ability to just do something new. Yeah.

Right. And this is the timeless race and battle. And this is kind of the point I tried to make in the essay, which is like both sides of this are good. Like it's really good to have highly scale tech companies that can do things that are at staggering levels of sophistication. It's really good to have startups that can launch brand new ideas. They ought to be able to both do that and compete.

They neither want ought to be subsidized or protected from the others. Like to me, that's just very clearly the idealized world. It is the world we've been in for AI up until now. And then, of course, there are people trying to shut that down. But my hope is that the best outcome clearly will be if that continues. We'll talk about that a little bit, but I'd love to linger on some of the ways this is going to change the internet. So I don't know if you remember, but there's a thing called mosaic and there's a thing called Netscape Navigator. So you were there in the beginning.

What about the interface to the internet? How do you think the browser changes? And who gets the owner browser? We got to see some very interesting browsers, Firefox, I mean, all the variants of Microsoft Internet Explorer Edge and now Chrome. The actual, I mean, it seems like a dumb question to ask, but do you think we'll still have the web browser? So I love having eight year old and he's super into, it's like Minecraft and learning to ask, but do you think we'll still have the web browser? So I have an eight year old, and he's super into, it's like Minecraft and learning to code and doing all this stuff.

So I, of course, I was very proud. I couldn't bring sort of fire down from the mountain to my kid and I brought him chat GPT, and I hooked him up on his laptop. And I was like, you know, this is the thing that's gonna answer all your questions. And he's like, okay, and I'm like, but it's gonna answer all questions.

And he's like, well, of course, like it's a computer, of course, it answers all your questions, like what else would a computer be good for? Dad. And never impressed him. Not impressed in the least. Two weeks past, and he has some question,

and I say, well, have you asked JetGPT, and he's like, dad, being is better. And why is being better is because it's built into the browser. Because he's like, look, I have the Microsoft Edge browser and like it's got Bing right here. And then he doesn't know this yet, but one of the things you can do with Bing in Edge is there's a setting where you can use it to basically

talk to any webpage because it's sitting right there next to the next to the next to the browser. And by the way, it's includes PDF documents. And so you can in the way they've implemented an Edge with Bing is you can load a PDF and then you can ask a questions, which is the thing you can't do currently in just chat GPT. So they're going to push the, I think that's great. They're going to push the melding and see if there's a combination thing there. Google's rolling off this thing, the magic button, which is implemented in Google Docs. And so you go to Google Docs and you create a new document.

You instead of like starting to type, you just say, press? And so you go to Google Docs and you create a new document and you, you know, instead of like, you know, starting to type, you just, you know, say, press the button and it starts to like generate content for you, right? Like, is that the way that it'll work? Is it going to be a speech UI where you're just going to have an earpiece and talk to it all day long? You know, is it going to be a, like, these are all, like, this is exactly the kind of thing that I don't,

this is exactly the kind of thing I don't think is possible to forecast. I think what we need to do is run all those experiments. So one outcome is we come out of this with a super browser that has AI built in that's just amazing. Look, there's a real possibility that the whole, I mean, look, there's a possibility here that the whole idea of a screen and windows and all this stuff just goes away because why do you need that if you just have a thing that's just telling you whatever you need to know?

There's apps that you can use. You don't really use them being a Linux guy and Windows guy. There's one window, the browser, with which you can interact with the internet, but on the phone you can also have apps. So I can interact with Twitter through the app or through the web browser. And that seems like an off these distinction, but why have the web browser in that case, if one of the apps starts becoming the everything app. What do you want to do with Twitter, but there could be others that could be like a big app that could be a Google app that just doesn't really do search, but just like do what I guess A well did back in the day or something where it's all right there.

And it changes the nature of the internet because the where the content is hosted, who owns the data, who owns the content. What is the kind of content you create? How do you make money by creating content or the content creators, all of that. Or you could just keep being the same, which is like, we're just the nature of web pages changes and the nature of content, but there will still be a web browser. Because web browsers are pretty sexy products. It just seems to work because it like you have an interface and we know into the world and then the world can be anything You want and as the world will evolve there could be different programming languages. It can be animated Maybe it's three dimensional and so on

Yeah, it's interesting. Do you think we'll still have the web browser every every every every every medium becomes the content for the next one So they you know they will be able to give you a browser whenever you want. Oh, interesting. Yeah, another way to think about it is maybe what the browser is. Maybe it's just the escape hatch, right? Which is maybe kind of what it is today, right? Which is like most of what you do is like inside a social network or inside a search engine or inside, you know, somebody's app or inside some controlled experience, right? But then every once in a while there's something where you actually want to, Joe break, you

want to actually get free. What browsers, the FU to the man, you're allowed to, there's something where you actually want to, Joe break, you want to actually get free. The web browser is the eff you to the man. You're a lot of, that's the free internet. Yeah, back back, the way it was in the 90s. So here's something I'm proud of. So nobody really talks about, here's something I'm proud of, the web, the browser, the web servers,

they're still back or compatible all the way back to like 1992, right? So like you can put up a, you can still, you know, the big breakthrough the web early on, the big breakthrough was it made it really easy to read, but it also made it really easy to write, made it really easy to publish, and we've literally made it so

easy to publish, we made it not only so you can use easy to publish content, it was actually also easy to actually write a web server, right, and you can literally write a web server and four lines of broke code, and you can start publishing content on it, and you could set whatever rules you want for the content, whatever censorship, no censorship, whatever you want, you could just do that. As long as you had an IP address, you could do that. That still works. That still works exactly as I just described. So this is part of my reaction to

all of this, like all this censorship pressure and all these issues around control and all this stuff, which is maybe we need to get back a little bit more to the Wild West. The Wild West is still out there. Now they will try to chase you down. Like they'll try to, you know, people who want a sensor, they'll try to take away your domain name and they'll try to take away your payments account and so forth if they really don't like what you're saying. But nevertheless,

you, like, unless they literally are intercepting you at the ISP level, like you can still put up a thing. And so I don't know, I think that's important to preserve, right? Like because, because, I mean that's important to preserve, right? Because because, I mean, one is just a freedom argument, but the other is a creativity argument, which is you want to have the escape hatch so that the kid with the idea is able to realize the idea

because to your point on page rank, you actually don't know what the next big idea is. Nobody called their page and told him to develop page rank like he can have that in his own. And you want to always, I think leave the escape hatch for the next kid or the next Stanford grad student to have the breakthrough idea and be able to get it up and running before anybody notices. You and I both have a history. So let's step back. We've been talking about the future. Let's step back for a bit and look at the 90s. You created mosaic, what browser, the first widely used what browser, tell the story of that. And how did it evolve into Netscape Navigator? It's the early days.

So, full story. So, I remember born, I remember born, a small child. Well, actually, what did that, yeah, let's go there. What did you, what would you first fall in love with computers? Oh, so I hit the generational jackpot, and I hit the Gen X kind of point perfectly as it turns out. So I was born in 1971

So there's this great website called WTF happen in 1971 dot com, which is basically 1971 was when everything started to go to hell and I was of course born in 1971 So I like to think that I had something to do with that. Did you make it on the website? I have I don't think I made it on the website, but you know, hopefully somebody needs to add this is this is where everything Maybe I contributed with some of the trends that they that they do every line on that website goes like that right so it's all it's all it's all a picture disaster But um, but there was this moment in time where because the you know sort of the apple, you know The apple to hit in like 1978 and then the IBM PC hit in 82 so I was like, you know, 11 when the PC came out Um, and so I just kind of hit that perfectly. And that was the first moment

in time when like regular people could spend a few hundred dollars and get a computer, right? And so that I just like that that that resonated right out of the gate. Um, on the other part of the story is, you know, I was using an apple to that used a bunch of them, but I was using apple two. And of course it's set in the back of every apple to and every Mac it said, you know, designed in Cupertino, California. And I was like, wow, Cupertino must be the like shining city on the hill, like Wizard of Oz, like the most amazing like city of all time. I can't wait to see it. Of course, years later, I came out to Silicon Valley and went to Cupertino and it's just a bunch of office parks, low rise of park buildings. So the aesthetics were a little disappointing, but you know, it was the the vector right of the creation of a lot of this stuff. So then basically, so part of my story is just the luck of having been born at the right time

and getting exposed to PCs. Then the other part is, the other part is when El Gore says that he created the internet, he actually is correct in a really meaningful way, which is he sponsored a bill in 1985 that essentially created the modern internet, created what is called the NSF net at the time, which is sort of the first really fast internet backbone. And you know that that build dumped a ton of money into a bunch of research universities to build out basically the internet backbone and then the super computer centers that were clustered around the internet and one of those universities was University of Illinois. Right went to school. And so the other stroke I had was I went to Illinois, basically, right as that money was just like getting bumped on campus. And so as a consequence, we had at on campus, and this is like, you know, 89, 90, 91,

we had like, you know, we were right on the internet backbone. We had like T3 and at the time, P3, 45 megabit backbone connection, which at the time was, you know, wildly state of the art. We had crazy computers. We had thinking machines parallel supercomputers. We had silicon graphics workstations. We had Macintosh's, we had next cubes over the place. We had like every possible kind of computer you could imagine because

all this money just fell out of the sky. You were living in the future. Yeah, so quite literally it was yeah, like it's all there. So we had full broadband graphics like the whole thing. And it's actually funny because they had this, this is the first time I kind of sort of tickled the back of my head that there might be a big opportunity in here, which is, you know, they embraced it. And so they put like computers and all the dorms and they wired up all the dorm rooms and they had all these, you know, the labs everywhere and everything.

And then they gave every undergrad a computer account and an email address. And the assumption was that you would use the internet for your four years at college. And then you would graduate and stop using it. And that was that you would use the internet for your four years of college and then you would graduate and stop using it. And that was that, right? And you would just retire your email address. It wouldn't be relevant anymore because you'd go off in the workplace and they don't use email. You'd be back to using fax machines or whatever. Did you have that sense as well? Like what you said the back of your head was tickled like, what was your, what was exciting to you about this possible world?

Well, if this is so useful in this continuum, if this is so useful in this container environment that just has this weird source of outside funding, then if it were practical for everybody else to have this and if it were cost effective for everybody else to have this, wouldn't they want it? And overwhelmingly, the prevailing view at the time was, no, they would not want it. This is esoteric weird nerd stuff, right?

That the computer science kids like, but like normal people are never gonna do email, right, or be on the internet, right? And so I was just like, wow, like this is actually like, this is really compelling stuff. Now the other part was it was all really hard to use. And in practice, you had to be a basic CS, you had to be a CS undergrad or equivalent to actually get full use of the internet at that point, because it was all pretty esoteric stuff.

So then that was the other part of the idea, which was okay, we need to actually make this easy to use. So what's involved in creating a like, like, in creating a graphical interface to the internet? Yeah, so it was a combination of things. So it was like basically the web existed in an early sort of described as prototype form. And by the way, text only at that point. What did it look like? What was the web? I mean, whoa, and the key figures like, what was it? What was it like? It made a picture. It looked like JGPT actually It was all text. Yeah

And so you had a text-based web browser Well actually the original browser Tim burners leave the original the original browser both the original browser and the server actually ran on next Next cubes So these were this was you know the computer Steve Jobs made during the interim period when he during the decade long interim period when he was not an apple. You know, he got fired in 85 and then came back in 97. So this was in that interim period where he had this company called next and they made these literally these computers called cubes. And there's this famous story. They were beautiful, but they were 12 inch by 12 inch by 12 inch cubes computers. And there's a famous story about how they could have cost half as much if it had been 12 by 12 by 13 but

People's like no like it has to be so they were like $6,000 are basically academic workstations. They had the first city round drives Yeah, which were slow. I mean it was the computers are all but unusable. They were so slow, but they were beautiful We actually just take a tiny tangent there sure of course The 12 by 12. They're just so beautifully encapsulated Steve Jobs, idea of design. Can you just comment on what you find interesting about Steve Jobs, what about that view of the world,

that dogmatic pursuit of perfection in how he saw perfection in design? Yeah, so I guess they say like, look, he was a deep believer, I think, in a very deep way. I interpret it. I don't know if you ever really described it like this, but the way I interpret it is, it's like, it's like this thing, it's actually a thing in philosophy.

It's like aesthetics are not just appearances, aesthetics go all the way to like deep underlying, underlying meaning, right? It's like, I'm not a physicist. One of the things I've heard physicists say is one of the things you start to get a sense of when a theory might be correct is when it's beautiful. Right? Like, you know, they're, right? And so, so there's something, and you feel the same thing,

by the way, in like human psychology, right? You know, when you're experiencing awe, right? You know, there's like, there's like, there's a simplicity to it. When you're having an interaction with somebody, there's an aesthetic, it was like, home, it comes over you, because you're actually being fully honest and trying to hide yourself, right? So, it's like this very deep sense of aesthetics. And he would trust that judgment that he had to do down, like, even if the engineering teams are saying this is too difficult, even if the, whatever the finance folks are saying, this is ridiculous, the supply chain, all that kind of stuff, this makes it impossible to mature. We can't do this kind of material.

This has never been done before. It's so on and so forth. He just sticks by it. Well, I mean, who makes a phone out of aluminum? Right? Like, dead, nobody else would have done that. And now, of course, if your phone is made out of aluminum, what, you know, how crude, what kind of caveman would you

have to be to have a phone is made out of plastic? Like, right? So, it's just this very, right? And, you know, look, there's a thousand different ways to plastic like right. So like, so it's just this very right and you know look It's there's a thousand different ways to look at this But one of the things is just like like these things are central to your life like you're with your phone more than you're with anything else Like it's in your it's gonna be in your hand. I mean, you know, you know, this he thought very deeply about what it meant for something to be in your handle They long yeah, but for example, he here's an interesting design thing like he he never wanted it It's my understanding as he never wanted an iPhone to have a screen larger than you could reach with your thumb one handed. And so he

was actually opposed to the idea of making the phones larger. And I don't know if you have this experience today, but let's say there are certain moments in your day when you might be like only have one hand available. And you might want to be on your phone. Yeah. And you're trying to like texting you your thumb can't reach the send button. Yeah, I mean there's pros and cons right and then there's like folding phones I would love to know what he thought and things about them But I mean is there's something you could also just link on cuz he's one of the interesting figures in the history of technology what makes him What makes him as successful as he was what makes him as interesting as he was

would made him so productive and important in the development of technology? He had an integrated worldview. So the properly designed device that had the correct functionality that had the deepest understanding of the user that was the most beautiful. Right? Like it had to be all of those things, right?

It was, he basically would drive to as close to perfect as you could possibly beautiful, right? Like it had to be all of those things, right? It was, he basically would drive to as close to perfect as you could possibly get, right? And I, you know, I suspect that he never quite, you know, thought he ever got there because most great creators, you know, are generally dissatisfied, you know, you read accounts later on and all they can, all they can see are the flaws in their creation.

But like he got as close to perfect each step of the way as he could possibly get with the constraints of the technology of his time. And then, you know, look, he was, you know, sort of famous in the Apple model, it's like, look, they, they will, you know, this headset that they just came out with, like, you know, it's like a decade-long project, right?

It's like, and they're just gonna sit there and tune and tune and polish and polish and tune and polish and tune and polish until it is as perfect as anybody could possibly make anything. And then this goes to the way that people describe working with him, which is, you know, there was a terrifying aspect of working with him, which is, you know, he was, you know, he was very tough. But there was this thing that everybody I've ever talked to work for him says that they all say the following, which is he, we did the best work of our lives when we worked for him because he

set the bar incredibly high. And then he supported us with everything that he could to let us actually do work of that quality. So a lot of people who were at Apple spend their lives trying to find another experience where they feel like they're able to hit that quality bar again. Even if it in retrospect, we're doing it, like, suffering. Yeah, exactly. What is that teach here about the human condition, huh? So, look, so I take exactly. So the Silicon Valley, I mean, look, he's not, you know, George Patten in the, you know, in the army, like, you know, there are many examples in other fields, you know, that are like this. Uh, uh, this is specifically an intact. It's actually, I find it very interesting. There's the apple way, which is polished, polished, polished, and don't ship until it's as perfect as you can make it. And then there's the sort of the other approach, which is the sort of incremental hacker mentality, which basically says ship early and often and iterate.

One of the things I find really interesting is I'm now 30 years into this. There are very successful companies on both sides of that approach. That is a fundamental difference in how to operate and how to build and how to create that. You have world class companies operating in both ways. And I don't think the question of like, which is the superior model is anywhere close to being answered. Like, and my suspicion is the answer is, do both. The answer is you actually want both,

they lead to different outcomes. Software tends to do better with the iterative approach. Hardware tends to do better with the, sort of, wait and make it perfect approach. But again, you can find examples in both directions. So the jury's still on on that one. So back to mosaic. So what, it was text-based, Tim Berners-Lee.

Well, there was the web, which was text-based, but there were no, I mean, there was like three websites. There was like no content. There were no users. Like, it wasn't like a catalytic, it hadn't in there. By the way, it was all because it was all text there were no documents There are no images there are no videos there were no right so so it was it was and then if you in the beginning if you had to be on a next cube But you need to have a next cube both to publish and to consume so so there were six thousand bucks He said the real limitations. Yeah, six thousand dollar PC. What they did not they did not sell very many

But then there was also six thousand bucks, you said? They were limitations, like, yeah, $6,000 PC. They did not sell very many. But then there was also, there was also FTP and there was used NATS, right? And there was, you know, a dozen other basically, there's Waze, which was an early search thing. There was GoFur, which was an early menu-based information retrieval system. There were like a dozen different sort of scattered ways

that people would get to information on the internet. And so the mosaic idea was basically bring those all together, make the whole thing graphical, make it easy to use, make it basically bulletproof so that anybody can do it. And then again, just on the luck side, it so happened that this was right at the moment when graphics, when the GUI sort of actually took off. And we're now also used to the GUI that we think it's been around forever. But it didn't really, you know, the Macintosh brought it out in 85, but they actually didn't sell very many Macs in the 80s. It was not that successful of a product. It really was, you needed Windows 3.0 on PCs

and that hit in about 92. And so when we did most, I can 92 and 93. So that sort of, it was like right at the moment when you could imagine actually having a graphical user interface at all, much less one to the internet. How old did Windows 3 sell?

So it was that a really big, that was the big bang, the big operating graphical operating system. Well, this is the classic. Okay, this Microsoft is operating on the other. So Steve, Steve, the Apple was running on the polish until it's perfect. Microsoft famously ran on the other model, which is ship and iterate. And so in the old line in those days,

was Microsoft version three of every Microsoft product. That's the good one, right? And so there are, you can find online Windows one Windows two, nobody use them. Yeah. Actually, the original Windows, the original Microsoft Windows that Windows were not over laughing. And so you have these very small, very low resolution screens. And then you had literally, it just didn't work.

It wasn't ready yet. Well, and Windows 95, I think was a pretty big leap also. That was a big leap too. Yeah. So that was like bang, bang. And then of course Steve, and then you know, in the fullness of time, Steve came back and then the Mac started to take off again. That was the third bang.

And then the iPhone was the fourth bang. Such exciting time. And then we were off to the races because nobody could have known. We'll be created from that. Well Windows 3.1 or 3.0, Windows 3.0 to the iPhone was only 15 years. Right, like that ramp was in retrospect. At the time, it felt like it took forever, but it historical terms. Like that was a very fast ramp from even a graphical computer at all on your desk to the iPhone. It was 15 years. Did you have a sense of what the internet will be as you

look into the window on my side? Like what? like there's just a few web pages for now. So the thing I had early on was I was keeping at the time what this disputes over what was the first blog, but I had one of them that at least is a is a is a possible at least a runner up in the competition. And it was what was called the what's new page. And it was it was it was like a What's New Page. And it was like a hard wired, I had distribution, I had shared advantage, I put it right in the browser.

I put it in the browser and then I put my resume in the browser, it was always, it was, it was, it was, it was hilarious. But, but I was keeping the, not many people get to get to do that. So, the, good call. And early days, It's so interesting. I'm looking for my about about, oh, my just looking for a job. So, so the West New Page, I would

literally get up every morning and I would, every afternoon. And I would basically, if you wanted to launch a website, you would email me. And I would list it on the most new page. And that was how people discovered the new websites as they were coming out. And I remember, because it was like one, it literally went from it, it was like one every couple days to like one every day, to like two every day. Booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo booboo bo So like, what was the homepage? So the homepage was just basically trying to explain even what this thing is that you're looking at, right?

The basic, basically basic instructions. But then there was a button that said what's new and what most people did was they went to, probably, reasons went to what's new. But like it was so mind blowing at that point. It's the basic idea. And it was just like, you know, this is basically the internet, but people could see it for the first time. The basic idea was, look, you know, some, you know, it's like literally it's like an Indian restaurant in like Bristol, England has like put their menu on the web and people were like, wow, whoa. Because like, that's the first restaurant menu on the web. Yeah. And I don't have to be in Bristol. And I don't

know if I'm ever going to go to Bristol. And I don't even like Indian food. And like, wow. Right. And it was like that. The first web, the first streaming video thing was a, it was like that the first web the first streaming video thing was a it was another England some Oxford or something some guy put his coffee pot up as the first streaming video thing and he put it on the web because he literally it was the coffee pot down the hall yeah and he wanted to see when he needed to go refill it but there were you know there was a point when there were thousands of people like watching that coffee pot because it was the first thing you could watch. But isn't we able to kind of infer, you know, if that Indian restaurant could go online,

then you're like, they all will. Yeah, exactly. So you felt that. Yeah, yeah. Now, you know, look, it's still a stretch, right? It's still a stretch because it's just like, okay, it's, you know, you're still in this zone, which is like, okay, is this a nerd thing? Is this a real person thing? Yeah. By the way, there was a wall of skepticism from the media, like they just, like everybody was just like, yeah, this is just like, this is not,

this is not for regular people at that time. And so you had to think through that. And then look, it was still, it was still hard to get on the internet at that point, right? So you could get kind of this weird bastardized version if you were on AOL, which wasn't really real. Or you had to go learn what an ISP was. In those days, PCs actually didn't have TCPIP drivers

come pre-installed, so you had to learn what a TCPIP driver was. You had to buy a modem, you had to install driver software. I have a comedy routine I do. So it's like 20 minutes long describing all the steps required to actually get on the internet at this point had to, you had to look through these practical, and then speed performance, 14 form modems, right? Like it was like watching, you know, glue dry. And so you had to, you had to, they were basically a sequence of bets that we made where you basically needed to look through that current state of affairs and say, actually, there's going to be so much

demand for it. Once people figure this out, there's going to be so much demand for it that all of these practical problems are going to get fixed. Some people say that the anticipation makes the destination that much more exciting. Do you remember progressive JPEGs? Yeah, do I? Do I? So for kids in the audience, right? For kids in the audience. You used to have to wash an image load, like a line of the time, but it turns out there was this thing with JPEG, where you could load basically every fourth. You could load like every fourth line,

and then you could sweep back through again. And so you could render a fuzzy version image up front, and it would like resolve into the detailed one. And that was like a big UI breakthrough, because it gave you something to watch. Yeah, and there's applications in various domains for that. Well, it's a big fight. If there's a big fight early on about whether there should be images in the web. For that reason, for the sexualization, not explicitly that that did come up, but it wasn't even that.

It was more just like all the serious and the argument went to purists. Basically, so all the serious information in the world is text. If you introduce images, you, you're basically going to bring in all the serious information, the argument went to purists, basically said all the serious information the world has taxed. If you introduce images, you're basically going to bring in all the trivial stuff. You're going to bring in magazines and all this crazy. I was just stuff that people, it's going to distract from that. It's going to take the way from being serious to being frivolous. Well, was there any duma-type arguments

about the internet destroying all of human civilization or destroying some fundamental fabric of human civilization? Yeah, so those days it was all around crime and terrorism. So those arguments happened, but there was no sense yet of the internet having an effect on politics or because that was way too far off. But there was an enormous panic at the time around cybercrime.

There was enormous panic that your credit card number would get stolen and your life savings would be drained. then you know criminals were going to, there was oh when we started one of the things we did, one of the the the Netscape browser was the first widely used piece of consumer software that had strong encryption built in, it made it available to ordinary people and at that time strong encryption was actually illegal to export out of the US. So we could feel that product in the US, we could not export it, because it was classified as a munition. So the NEscape browser was on a restricted list along with the Tom Hock missile as being something that could not be exported. So we had to make a second version with deliberately weak encryption to sell overseas with a big logo

on the box saying, do not trust this, which it turns out makes it hard to sell software when it's got a big logo that says don't trust it. And then we had to spend five years fighting the US government to get them to basically stop trying to do this. But because the fear was terrorists are going to use encryption to like plot, you know, all these all these things. And then, you know, we responded with, well, actually, we need encryption to be able to secure systems so that the terrorists and the criminals can't get into them. So that was the 1990s fight. So can you say something about some of the details of the software engineering challenges

required to build these browsers? I mean, the engineering challenges of creating a product that hasn't really existed before, that can have such almost like limitless impact on the world with the internet. So there was a really key bet that we made at the time, which is very controversial, which was Cora to Cora to how it was engineered, which was are we optimizing for performance, or for ease of creation. And in those days, the pressure was very intense to optimize for performance because the network connections were so slow. And also the computers were so slow. And so if you had mentioned the progressive JPEGs, like

if there's an alternate world in which we optimize for performance and you had just a much more pleasant experience right up front. But what we got by not doing that was we got ease of creation. And the way that we got ease of creation was all of the protocols and formats were in text, not in binary. And so HTTP is in text, by the way, and this isn't internet tradition, by the way,

that we picked up, but we continued it. HTTP is text and HTML is text and then everything else that followed is text. As a result, and by the way, you can imagine purest engineers saying this is insane. You have very limited bandwidth. Why are you wasting any time sending text? You should be encoding the stuff into binary, and it will be much faster. And of course, the answer is that's correct. But what you get when you make a text is all of a sudden, well, the big breakthrough was the view source function. Right. So the fact that you could look at a web page, you could hit view source and you could see the HTML. That was how people learned how to make web pages. Right. It's so interesting because the stuff we take for granted now is, uh, man, that was

fundamental to the development of the web to be able to have HTML just right there all the ghetto mess that is HTML all the sort of almost biological like messiness of HTML and then having The browser tried to interpret that mess. Yeah, exactly. Show something reasonable Well, and then there was this internet principle that we inherited which was in mint What was it in mint cautiously? I met conservatively interpret liberally So it basically met if you're in the design principle was, if you're, if you're creating like a web editor that's going to emit HTML, like do it as cleanly as you can.

But you actually want the browser to interpret liberally, which is you actually want users to be able to make all kinds of mistakes and for it to still work. Yeah. And so the browser rendering engines to this day have all of this getty code crazy stuff where they can, they're resilient to all kinds of crazy issue no mistakes and so and literally what I always had in my head is like there's an eight year old or an 11 year old somewhere and they're doing a view source they're doing a cut in page and they're trying to make a web page for their eternal or whatever and like they leave out a slash and they leave out an angle bracket and they do this and they do that and it still works. It's it's also like that I don't often think about this, but programming, C++, C++, all those languages, list, the compiled language,

the interpreted language, just Python, Pearl, all that. They, the brace have to be all correct. Like everything has to be perfect. Grydol. And then you forget, all right. It's systematic and rigorous. Let's go there.

But you forget the web with JavaScript eventually and HTML is allowed to be messy in the way for the first time messy in the way biological systems could be messy. It's like the only thing computers were allowed to be messy on for the first time. It used to offend me. So I grew up in Unix. I worked on Unix. I was a Unix native all the way through this period. And so it used to drive me bananas when it would do the segmentation and fault in the

cordump file. Just like literally, there's like an error in the code. The math is off by one. And it cordumps. And I'm in the cordump trying to analyze it and trying to reconstruct what. And I'm just like, this is ridiculous. Like the computer ought to be smart enough to be able to know that if it's off by one, okay fine, and it keeps running. And I would go ask all the experts, like, why can't it just keep running? And they'd explain to me, well, because all the downstream

repercussions and blah, blah. And I'm like, this still like, you know, we're forcing the human creator to live to your point in this hyperlittoral world of perfection. And I was just like, that's just bad. And by the way, what happens with that, of course, is what happened with coding at that point, which is you get a high priesthood. You know, there's a small number of people who are really good at doing exactly that. Most people can't and most people are excluded from it. And so actually that was where that, for, there's where I picked up that idea was, was like, no, no, you want, you want these things to be resilient error in all kinds. And this this would drive the purists absolutely

crazy. Like I got attacked on this like a lot because yeah, I mean like every time I you know all the purists who are like into all this like markup language stuff and formats and codes and all the stuff that they would be like, you know, you can't you're encouraging behavior because also they wanted the browser to give you a a segfault error anytime there was a they wanted the browser to give you a segfault error anytime there was a physical error. Yeah, they wanted to be a cop, right? They wanted that. Yeah, that was a very, and any, any, any properly trained and credentialed engineer would be like, that's not how you build these. That's such a bold move to say, no, it doesn't have to be. Yeah, now like I said, the good news for me is the internet

kind of had that traditional ready, but we, but having said that, like we pushed it. We pushed it. We pushed it way out. But the other thing we did going back to the performance thing was we gave up a lot of performance. That initial experience for the first few years was pretty painful. But the bet there was actually an economic bet, which was basically the demand for the web would basically mean that there would be a surge in supply of broadband.

Because the question was, how do you get the phone companies which are not famous in those days for doing new things at huge cost for speculative reasons. How do you get them to build up broadband, spend billions of dollars doing that, and you could go meet with them and try to talk them into it, or you could just have a thing where it's just very clear that people love, that's going to be better if it's faster. And so there was a period there, and this was fraught with some peril, but there was a period there where it's like we knew the experience was sub optimized because we were trying to force

the emergence of demand for broadband. Sure. Which is in fact what happened? So you had to figure out how to display this text, HTML text. So the blue links and the purple links, I mean, what, and there's no standards. Is there standards at that time? Is there standards at that time? Yeah, but there's like, there's implied standards, right? And they, you know, there's all these cousin new features that are being added with like CSS, what like, what kind of stuff a browser should be able to support features with the languages,

with the JavaScript and so on. But you, you bet you're sending standards on the fly yourself. Well, to this day, if you, if you create a web page You're sending standards on the fly yourself. Well, to this day, if you create a web page that has no CSS style sheet, the browser will render it however it wants to. So this was one of the things, there was this idea, this idea at the time in how these systems were built, which is separation of content from,

or separation of, yeah, content from appearance. And that's still, people don't really use that anymore because everybody wants to determine how things look and so they use CSS, but it's still in there that you can just let the browser do all the work. I still like the really basic websites, but that could be just old school. Kids these days with their fancy responsive websites

that don't actually have much content but have a lot of visual elements. Well, that's one of the things that's fun about chat, you know, about chat GPD. Yeah. It's like back to the basics. Back to just text. Yeah. Right.

And, you know, there is this pattern in human creativity and media where you end up back at text. And I think there's, you know, there's something powerful in there. Is there some other stuff you remember like the purple links? There were some interesting design decisions that kind of come up that we have today or we don't have today. That would temporary. So, we made the background great.

I hit it reading text on white background. So, I made the background great. Do you regret? No. No, no, no. That decision I think has been reversed. But now I'm happy though because because now Dark Mode is the thing. So it wasn't about gray, it was just you didn't want to

wait back on. Stream my eyes. Stream your eyes. Interesting. And then there's a bunch of other decisions. I'm sure there's an interesting history of the development of HTML and CSS and how those interface and JavaScript. And there's this whole Java applet thing.

Well, the big one probably JavaScript. CSS was after me, so I didn't know that was not me. But JavaScript was the big, JavaScript maybe was the biggest of the whole thing. That was us. And that was basically a bet. It was a bet on two things. One is that the world wanted a new front end script language.

And then the other was we thought at the time the world wanted a new backend scripting language. So then the other was, we thought at the time the world wanted to do back end scripting language. So JavaScript was designed from the beginning to be both friend and in back end. And then it failed as a back end scripting language and Java won for a long time. And then Python, Pearl, and other things, PHP and Ruby.

But now JavaScript is back. And so I wonder if everything in the end will run on JavaScript. It seems like it is the, and by the way, let me give a shout out to Brendan Eich, was basically the one man inventor of JavaScript. If you're interested to learn more about Brendan Eich, he's got his podcast previously.

Exactly. So he wrote JavaScript over a summer. And I think it is fair to say now that it's the most widely used language in the world, and it seems to only be gaining in its range with option. In the software world, there's quite a few stories of somebody over a weekend, over a week, over a summer, writing some of the most impactful revolutionary pieces of software ever. Well, look, that should be inspiring, yes.

Very inspiring. I'll give you another one, SSL. So SSL. So SSL was the security protocol. That was us. And that was a crazy idea at the time, which was, let's take all the native protocols, unless wrap them in a security wrapper. That was a guy named Kip Hickman who wrote that over a summer one guy. And then look today sitting here today, like the transformer, like at Google, was a small handful

of people. And then, you know, the number of people who have did like the core work on GPT, it's not that many people. It's a pretty small handful of people. And so, yeah, the pattern and software repeatedly over a very long time has been, it's a Jeff Fizzo's always had the two pizza rule for teams at Amazon, which is any team

needs to be able to be fed with two pizzas. If you need the third pizza, you have too many people. And I think that's, I think that's, I think it's actually the one piece of roll. Yeah. Further further really creative work. I think it's two people, three people. Well, that's you see that was certain open source projects like so much is done by like one or two people. It's so incredible. And that's why you see that gives me so much hope about

the open source movement in this new age of AI, where you know, just recently having had a conversation with Mark Zuckerberg of all people who's all in on the open source, which is so interesting to see. And so inspiring to see, because like releasing these models, it is scary. It is potentially very dangerous. And we'll talk about that. But it's also, if you believe in the goodness of most people and in the skill set of most people, and they desire to do good in the world, that's really exciting.

Because it's not putting these models into the centralized control of big corporations, the government, so on. It's putting in the hands of a teenage kid with like a dream in his eyes. I don't know. That's beautiful. And look, this AI ought to make the individual coder obviously far more productive, right?

By like, you know, a thousand X or something. And so you ought to open source, like not just a future of open source. I have it, the future of open source, everything. We ought to have a world now of super coders, right, who are building things as open source with one or two people that were inconceivable, you know five years ago You know the level of kind of hyper productivity. We're gonna get out of our best and brightest I think it's gonna go way up. It's gonna be interesting. We'll talk about it

But let's just to linger a little bit on that escape That's capable acquired in 1999 for 4.3 billion by a well What was that? What was that like? What was the memorable aspects of that? Well, that was the height of the.com boom, bubble bust. I mean, that was the frenzy. If you watch Succession, that was like what they did

in the first season with Gojo and the merger with the, so it was like the height of like one of those kind of dynamics and so. Do you recommend Succession? By the way, I have a more of a Yellowstone guy. Yellowstone's very American. I'm very proud of you. That's it. That is. I just talked to Matthew McConaughey and I'm full on texting at this point. Good. I heardly approve. And he will be doing this equal to Yellowstone. Yeah. Very exciting. Anyway. Okay., so that's rude interruption by me, by way of succession. So that was at the height of the deal making and money and just the fair

flying and like craziness. And so yeah, it was just one of those. I mean, it's the entire landscape thing from start to finish was four years, which was like for one of these companies, it's just like incredibly fast. You know, we went public 18 months after we got, we were founded, which virtually never happens. So it was just this incredibly fast kind of meteor streaking across the sky. And then of course, it was this, and then there was just this explosion right that happened because then it was almost immediately followed by the dot com crash.

It was then followed by hell well, by time Warner, which again is the succession guy's going to play with that, was turned out to be a disaster steel. No, one of the famous kind of disasters in business history. And then, and then, you know, what became an internet depression on the other side of that. But then in that depression in the 2000s

was the beginning of broadband and smartphones and web 2.0, right? And then social media and search and every SaaS and everything that came out of that. So, what did you learn from just the acquisition? I mean, this is so much money. What's interesting? Because I must have been very new to you

that these software stuff, you can make so much money. There's so much money swimming around. I mean, I'm sure the ideas of investment will start to get born there. Yes, let me lay out. So here's the thing. I don't know if I figured out them, but figured out later, which is software is a technology that it's like a, you know, the concept of the philosopher's stone. The philosopher's stone in Alchemy, Transmute's lead in the gold and Newton spent 20 years trying to find the philosopher's stone. Never got there. Nobody's ever figured it out.

Software is our modern philosopher's stone in economic terms it transmutes labor into capital, which is like a super interesting thing. And by the way, like Karl Marx is rolling over in his grave right now, because of course that's complete refutation of his entire theory. Transpuse labor into capital, which is as follows, is somebody sits down at a keyboard and types a bunch of stuff in. And a capital asset comes out the other side and then somebody buys that capital asset for a billion dollars. Like, that's amazing. Right.

It's literally creating value right out of thin air, right, out of purely human thought. And so that, that's, there are many things that make software magical and special, but that's the economic. So I want to look at Mark's sort of thought about that. Oh, he would have completely broke his brain, because of course, the whole thing was, he could, you know, that kind of technology is inconceivable when he was alive.

It was all industrial, air stuff. And so any kind of machinery necessarily involves huge amounts of capital. And then labor was on the receiving end of abuse. Yep. Right. But like software, a software engineer is somebody who basically transmits his own labor into action

national capital asset creates permanent value. Well, in fact, it's actually very inspiring. That's actually more true today than before. So when I was doing software, the assumption was all new software basically has a sort of a parabolic sort of life cycle, right? So you ship the thing, people buy it. At some point, everybody who wants it is bought it and then it becomes obsolete. And it's like bananas, nobody buys old software. These days, Minecraft, Mathematica, Facebook,

Google, you have the software assets that have been around for 30 years that are gaining in value every year. And they're just there being a world of workraft, Salesforce.com, like they're being, every single year, they're being polished and polished and polished. They're getting better and better, more powerful, more powerful, more valuable, more valuable.

So we've entered this era where you can actually have these things that actually build out over decades, which by the way, is what's happening right now with Lake Cpt. And so now, and this is why there is always sort of a constant investment frenzy around software is because when you start one of these things, it doesn't always succeed, but when it does, now you might be building

an asset that builds value for four or five, six decades to come. If you have a team of people who have the level of devotion required to keep making it better. And then the fact that of course everybody's online, there's five billion people that are a click away from any new piece of software. So the potential market size for any of these things is nearly infinite. It must have been surreal back then though. Yeah, yeah. This was all brand new, right? Yeah, back then, this was all brand new. These were all brand new.

Had you rolled out that theory in even 1999, people would have thought you were spooking crack. So that's emerged over time. Well, now turn back into the future. You wrote the essay Why AI Will Save the World. Let's start the very high level. What's the main thesis of the essay? Yeah, so the main thesis of the essay is that what we're dealing with here is intelligence.

And it's really important to kind of talk about the sort of very nature of what intelligence is. And fortunately, we have a predecessor to machine intelligence, which is human intelligence, and we've got observations and theories over thousands of years for what intelligence is in the hands of humans. And what intelligence is, what it literally is, is the way to capture process, analyze, synthesize information, solve problems. But the observation of intelligence in human hands is that intelligence quite literally makes everything better.

And what I mean by that is every kind of outcome of like human quality of life, whether it's education outcomes or success of your children, or career success or health or lifetime satisfaction. By the way, propensity to peacefulness is opposed to violence, propensity for open-mindedness versus bigotry. Those are all associated with higher levels of intelligence. Smart people have better outcomes than almost as you write, in almost every domain of activity. Academic achievement, job performance, occupational status, income creativity, physical health, longevity, learning new skills, managing complex tasks, leadership, entrepreneurial

success, conflict resolution, reading comprehension, financial decision-making, understanding other's perspectives, creative arts, parenting outcomes, and life satisfaction. One of the more depressing conversations I've had, and I don't know why it's depressing, I have to really think through why it's depressing, but on IQ and the G factor and that that's something in large part is genetic and It correlates so much with all of these things in success in life and It's like all the

Inspiration stuff we read about like if you work hard and so on, damn, it sucks that you're born with the hand that you can't change. But what if you could? You're saying basically a really important point. I think it's a, and your articles, it really helped me, it's a nice added perspective to think about, listen, human intelligence, the science of intelligence is shown scientifically that it just makes life easier and better, the smarter you are. And now let's look at artificial intelligence.

And if that's a way to increase the sum human intelligence, then it's all going to make a better life. That's the argument. And certainly at the collective level, we can talk about the collective effect of just having more intelligence in the world, which will have very big payoff. But there's also just at the individual level, like what if every person has a machine, you know, a concept of augmentation, what if everybody has an assistant? And the assistant is 140 IQ. And you happen to be 110 IQ. And you've got something that basically is infinitely patient and knows everything about you and is pulling for you in every possible way.

Wants you to be successful. And anytime you find anything confusing or want to learn anything or have trouble understanding something or want to figure out what to do in a situation, right, when I figure out how to prepare for a job interview, like any of these things, like it will help you do it. And it will therefore, the combination will effectively be effectively raised because it will effectively

raise your IQ. Therefore, it raised the odds of successful life outcomes and all these areas. So people below the type of that go 140 IQ, you'll pull them off towards the 140 IQ. Yeah. Yeah. And then of course, you know, people at people at 140 IQ will be able to have a peer, right, to be able to communicate, which is great. And then people above 140 IQ will have an assistant that they can farm things out to. And then look, God willing, you know, at some point, these things go from future versions,

go from 140 IQ equivalent to 150 to 160 to 180, right? Like Einstein was, it nasty made it to be on the order of 160, you know, so when we get, you know, 160 AI, like we'll be, you know, when one assumes creating Einstein level breakthroughs and physics and then at 180, we'll be, you know, carrying cancer and developing warp drive and doing all kinds of stuff. And so it is quite possibly the case. This is the most important thing

has ever happened. The best things ever happen because precisely because it's a lever on this single fundamental factor of intelligence, which is the thing that drives so much of everything else. Can you still man the case that human plus AI is not always better than human for the individual? You may have noticed that there's a lot of smart assholes running around. Sure. Yes. Right.

And so like, smart, there are certain people where they get smarter, you know, they get to be more arrogant, right? So there's one huge flaw. Although to push back on that, it might be interesting because when the intelligence is not all coming from you, but from a system that might actually increase the amount of humility even in the assholes. One would hope. Or it could make assholes more assholes. You know, that's psychology to study.

Yeah, exactly. Another one is smart people are very convinced that they have a more rational view of the world and that they have easier time seeing through conspiracy theories and hoaxes and sort of crazy beliefs and all that. There's a theory in psychology, which is actually smart people. So for sure, people who aren't as smart are very susceptible to hoaxes and conspiracy theories. But it may also be the case that the smarter you get,

you become susceptible in a different way, which is you become very good at marshaling facts to fit preconceptions. You become very, very good at assembling whatever theories and frameworks and pieces of data and graphs and charts you need to validate whatever crazy idea has gotten in your head. And so you're susceptible in a different way. Right. We're all sheep, but different color. Some sheep are better at justifying it. And

those of you know, those of the smart sheep, right? So yeah, look, I would say this look like there are no panacea. I'm not a utopian. There are no panaceas in life. There are no, I don't believe there are like pure positives. I'm not a transcendental kind of person like that. But so yeah, there are going to be issues.

And look, smart people, and other people maybe you could say about smart people is they are more likely to get themselves in situations that are beyond their grasp because they're just more confident in their ability to deal with complexity and their their eyes become bigger. Their cognitive eyes become bigger than their stomach. You know, so yeah, you could argue those eight different ways. Never the last on net, right? Clearly overwhelmingly. Again, if you just extrapolate from what we know about human intelligence, you're improving so many aspects of life if you're upgrading intelligence.

So there'll be assistance at all stages of life. So when you're younger, there's for education, all that kind of stuff, for mentorship, all of this. And later on as you're doing work and you've developed a skill and you're having a profession, you have an assistant that helps you excel at that profession. So at all stages of life. Yeah, I mean, look, the theory is augmentations. This is the DeGaigle-Bertz term for the DeGaigle-Bertme. This observation many decades ago that, you know, basically it's like you can have this oppositional frame of technology where it's like us versus the machines.

But what you really do is you use technology to augment human capabilities. Yeah. And then by the way, that's how actually the economy develops. That's the economic side of this. But that's actually how the economy grows is through technology augmenting human potential. And so, yeah, and then you basically have a proxy or a prosthetic, so like you've got glasses, you've got a wristwatch, you've got shoes, you've got these things,

you've got a personal computer, you've got a word processor, you've got Mathematica, you've got Google. This is the latest, viewed through that lens, the AI is the latest in a long series of basically augmentation methods to be able to raise human capabilities. It's just this one is the most powerful one of all because this is the one that goes directly

to what they call fluid intelligence, which is like you. Well, there's two categories of folks that you outline that worry about or highlight the risks of AI and you highlight a bunch of different risks. I'd love to go through those risks and just discuss them brainstorm which ones are serious and which ones are less serious. But first, the Baptist and the bootleggers. What are these two interesting groups of folks who worry about the effect of AI and human civilization? Or say they do.

Say, oh, okay. Yes, let's say they do. The Baptist worry the bootleggers say they do. So the Baptist and the bootleggers is a metaphor of economics from what's called development economics. And it's this observation that when you get social reform movements in a society, you tend to get two sets of people

showing up arguing for the social reform. And the term Baptist and Boot Lakers comes from the American experience with alcohol prohibition. And so in the 1900s, 1910s, there was this movement that was very passionate at the time, which basically said alcohol is the evil in its destroying society. By the way, there was a lot of evidence to support this. There were very high rates of very high correlations, then by the way, and now, between rates of physical

violence and alcohol use, almost all violent crimes have either the perpetrator or the victim or both drunk. Almost all sexual harassment cases in the workplace, it's like at a company party and somebody's drunk. Almost, if you see this actually in the work, almost all social harassment cases in the workplace, it's like at a company party and somebody's drunk. Like, it's amazing how often alcohol actually correlates to actually dysfunction at least to domestic abuse and so forth child abuse. And so you had this group of people who were like, okay, this is bad stuff and we shot a lot. And those were quite literally baptists. Those were super committed, you know, hardcore Christian activists in a lot of cases. There was this woman whose name was Carrie Nation, who was this older woman who had been in this, I don't know, disastrous marriage

or something, and her husband had been abusive and drunk all the time. And she became the icon of the Baptist prohibitionist. And she was legendary in that era for caring and acts and doing, you know, completely on her own, doing raids of saloons, and like picking her axe to all the bottles and sags. Yeah, and so- So a true believer. An absolute true believer, and with absolutely the pierest of intentions. And again, there's a very important thing here,

which is, you could look at this cynically, and you could say the Baptist are like, delusional extremists, but you could also say, look, they're right, like she had a point. Yeah. She wasn't wrong about a lot of what she said. But it turns out the way the story goes is it turns out that there were another set of people who very badly wanted to outlaw alcohol in those days and those were the bootleggers,

which was organized crime. This stood to make a huge amount of money if legal alcohol sales were banned. And this was in fact the way the history goes. This was actually the beginning of organized crime in the US. This was the big economic opportunity that opened that up. And so they went in together. And they didn't go together like the Baptist did not even necessarily know about the bootleggers because they were on their moral crusade. The bootleggers certainly knew about the

Baptist and they were like, wow, this is these people are like the great front people for like, you know, you know, it's good PR shenanigans in the background. Yeah. And they got the full static past, right? And they did, in fact, ban alcohol in the US. And you'll notice what happened, which is people kept drinking. It didn't work. People kept drinking. The bootlegger's made a tremendous amount of money.

And then over time, it became clear that it made no sense to make it illegal, and it was causing more problems. And so then it was revoked. And here we sit with legal alcohol 100 years later with all the same problems. And the whole thing was this giant misadventure. The Baptist got taken advantage of by the bootleggers and the bootleggers got what they wanted and that was that. The same two categories of folks who now sort of suggest that development of artificial intelligence should be regulated. 100 percent. Yeah, it's the same pattern. The economists will tell you it's the same pattern

every time. This is what happened in nuclear power. This is what happened in which is another interesting one. But like yeah, this happens dozens and dozens of times throughout the last 100 years. And this is what's happening now. And you write that it isn't sufficient to simply identify the actors and impure their motives. We should consider the arguments of both the Baptist and the bootleggers on their merits.

So let's do just that. Risk number one. Will AI kill us all? So what do you think about this one? What do you think is the core argument here that the development of AGI perhaps better said will destroy human civilization. No, first of all, you just did a slight a hand because we went from talking about AI to AGI. Is there a fundamental difference there? I don't know.

What's AGI? I was AI. What's the? What AI is AI is machine learning? What's what's AGI? I think we don't know what the bottom of the well of machine learning is, or what the ceiling is. Because just to call something machine learning,

or just to call something statistics, or just to call it math or computation, doesn't mean, you know, nuclear weapons are just physics. So it's, to me, it's very interesting and surprising how far machine learning has taken. No, but we knew that nuclear physics would lead to weapons. That's why the scientists of that era were always in some of this huge dispute about building the weapons. This is different. Asia is different.

Where does machine learning lead? Do we know? We don't know, but this is my point. It's different. We actually don't know. And this is where the slight hand kicks in, right? This is where it goes from being a scientific topic to being a religious topic. And that's why I specifically called out this, because that's what happens.

They do the vocabulary shift and all of a sudden you're talking about something totally that's why I specifically called out the, because that's what happens, they do the vocabulary shift. And all of a sudden you're talking about something totally that's not actually real. Well, then maybe you could also, as part of that, define the Western tradition of millennia andism. Yes. Into the world. Apocalypse. Apocalypse.

Apocalypse cults. Apocalypse cults. Well, so we live in, we of course live in a Judeo-Christian, but primarily Christian kind of saturated, you know, kind of Christian, post-Christian, secularized Christian, kind of world in the West. And of course, core to Christianity is the idea of the second coming and revelations, and Jesus returning in 1000 year utopia on earth, and then the rapture and all that stuff. We collectively, as a society, we don't necessarily take all that fully seriously now. So what we do is we create our secularized versions of that.

We keep looking for utopia. We keep looking for basically the end of the world. And so what you see over decades is basically a pattern of these sort of, of these, of these, this is what calls are. This is how calls form as they form around some theory of the end of the world. And so the people's temple calls, the Manson calls, the Heavens Kate calls, the David Koresh call it, you know, what they're all organized around is like there's going to be this thing that's going to happen. It's going to basically bring civilization crashing

down. And then we have this special elite group of people who are going to see it coming and prepare for it. And then they're the people who are either going to stop it or failing stopping it. They're going to be the people who survive to the other side. And ultimately get credit for having been right. Why is that still compelling, do you think? Like, um, because it satisfies this very deep need we have for transcendence and meaning that got stripped away when we became secular. Yeah, but why is it transcendence involved the destruction of human civilization? Because like, how, like, how plausible, it's like a very deep psychological thing, because it's like how plausible, how plausible it's like a very deep psychological thing because it's like how plausible is it that we live in a world where everything's just kind of all right. Right. How exciting is that?

Right. But that's more than that. But that's the deep question I'm asking. Why is it not exciting to live in a world where everything's just all right. I think most of the animal kingdom would be so happy with just all right. Does it? I think, you know, most of the animal kingdom would be so happy with just all right. Yeah. Because that means survival. Why are we, maybe that's what it is. Why are we conjuring up things to worry about? So CS Lewis called it the God-shaped hole. So there's a God-shaped hole in the human experience,

consciousness, soul, whatever you want to call it, where there's got to be something that's bigger than all this. There's got to be something transcendent. There's going to be something that is bigger, bigger, bigger purpose, a bigger meaning. And so we have run the experiment of, you know, we're just going to use science and rationality and kind of, you know, everything's just going to kind of be as it appears. And large number of people have found that very deeply wanting and have constructed narratives. And by this is the story of the 20th century, right? Communism, right? Was one of those communism was a form of this. Nazism was a form of this.

You know, some people, you know, you can see movements like this playing out all over the world right now. So you could strike the kind of devil, a kind of source of evil, and we're going to transcend beyond it. Yeah. And the military and the military is kind of, when you see a military in cult, they put a really specific point on it, which is end of the world, right? There is some change coming and that change that's coming is so profound and so important that it's either going to lead to utopia or hell on earth, right? And it is going to, and then, you know, it's like, what if you actually knew

that that was going to happen, right? What it's like what if you actually knew that that was going to happen? Right. What would you what would you do? Right? How would you prepare yourself for it? How would you come together with a group of like-minded people? Right? How would you what would you do? Would you plan like cash as the weapons in the woods? Would you like, you know, I don't know, create underground bunkers? Would you, you know, spend your life trying to figure out a way to avoid having it happen? Yeah, that's a really compelling exciting idea to have a club over. To have a little bit of trouble, you get together on a side any night and drinks of beers and talk

about the end of the world and how you are the only ones who have figured it out. And then once you lock in on that, how can you do anything else with your life? Like, this is obviously the thing that you have to do. And then there's a psychological effect you you alluded to, there's a psychological effect. If you take a set of true believers and you leave them to themselves, they get more radical. Because they self-radicalize each other. That said, it doesn't mean they're not sometimes right. Yeah, the end of the world might be, yes, correct. Like, they might be right. Yeah, but like we have some pamphlets for you.

It's, I mean, there's, I mean, we'll talk about nuclear weapons because you have a really interesting little moment that I learned about in your essay. But sometimes it could be right. Yeah. Because we're still, you would develop and be more and more powerful technologies. In this case, we don't know what the impact

they will have on human civilization. Well, we can highlight all the different predictions about how it will be positive. But the risks are there and you discuss some of them. Well, the steel man is actually the steel man and the refutation are the same, which is you can't predict what's going to happen, right? You can't rule out that this will not end everything, right? But the response to that is you have just made a completely non-scientific claim. You've made a religious claim, not a scientific claim. How does it get disproven? And there's no, by definition, with these kinds of claims,

there's no way to disprove them, right? And so there's no, you just go right on the list, there's no hypothesis, there's no testability of the hypothesis, there's no way to falsify the hypothesis, there's no way to measure progress along the arc, like it's just all completely missing. And so it's not scientific. Well, I don't think it's completely missing. It's somewhat missing. So for example, the people that say, yeah, I was going to kill all of us. I mean, they usually have ideas about how to do that, whether it's the paperclip maximizer or, you know, it escapes escapes there's mechanism by which you can imagine it killing all humans model and To you can't disprove it by saying there is

There's a limit to the speed of which intelligence increases maybe show that Like the sort of rigorously really described model uh, like the sort of rigorously really described model, like how it could happen and say, no, there, here's a physics limitation. There's a physical limitation to how these systems would actually do damage a human civilization. And it is possible. They will kill 10 to 20% of the population, but it seems impossible for them to kill 99%. It was practical counterarguments, right?

So you mentioned basically what I described as the thermodynamic counterargument. Which is sitting here today, it's like we're with the evil AGI, get the GPUs. Yeah, because like they don't exist. So you're going to have a very frustrated baby evil AGI who's going to be like trying to buy a video stock or something to get them to finally make some shifts. Right. So the serious form of that is the thermodynamic argument, which is like, okay, where's the energy going to come from? Where's the process going to be running? Where's the process going to be running? Where's the data center going to be happening? How is this going to be happening in secret, such that you know?

So that's a practical counter-argument to the runaway AG. I think I have a, but I have an, and we can argue that and discuss that. I have a deeper objection to it, which is, this is all forecasting, it's all modeling, it's all, it's all future prediction, it's all future hypothesizing. It's not science. Sure. It is not, it is, future hypothesizing, it's not science. Sure. It is not, it is, it is, it is the opposite of science. So the, pull up Carl Sagan, extraordinary claims, requires, extraordinary proof, right? These are extraordinary claims. The policies that are being called for, right, to prevent this are of extraordinary magnitude,

that, and I think we're going to cause extraordinary damage. And this is all being done in the basis of something that is literally not scientific. It's not a testable hypothesis. So the moment you say, AAS is going to kill all of us, therefore we should ban that, or that we should regulate all the constant. That's when it starts getting serious.

Or start military, air strikes and data centers. Oh, boy. Right. And like, Yes, when it gets starts, it starts getting real. So here's the problem of millionaire and cults. They have a hard time staying away from violence.

It's a violence is so fun. If you're on the right end of it, they have a hard time of running violence. The reason they have a hard time of running violence is if you actually believe the claim, right, then what would you do to stop the end of the world? Well, you would do anything, right? And so, and this is where you get, I mean, again, if you just to stop the end of the world? Well, you would do anything, right? And so, and this is where you get, and again, if you just look at the history of a millionaire in cults, this is where you get the people's temple and everybody killing themselves in the jungle, and this is where you get Charles Manson, and, you

know, sending him to kill, kill the pigs. Like, this is the problem with these. They have a very hard time around the line at actual violence. And I think, I think in this case, there's, there, I mean, they're already calling for it like today. And, you know, where, there's, I mean, they're already calling for it like today. And, you know, where this goes from here is they get more worked up. Like, I think it's like really concerning. Okay. But that's kind of the extreme. So, you know, the extremes of anything are all, I was concerning. It's also possible to kind of believe that AI has a very

high likelihood of killing all of us. But there's, and therefore we should maybe consider slowing development or regulating. So not violence or any of these kinds of things, but it's saying like, all right, let's take a pause here. You know, you have biological weapons, nuclear weapons, like whoa, whoa, whoa, whoa, whoa. This is like serious stuff. We should be careful.

So it is possible to kind of have a more rational response, right? If you believe this risk is real. Believe. Yes. So is it possible to have a scientific approach to the prediction of the future? I mean, we just went through this with COVID. What do we know about modeling? Well, I mean, what do we learn about modeling with COVID? There's a lot of lessons. They didn't work at all. They worked poorly.

The models were terrible. The models were useless. I don't know if the models were useless or the people interpreting the models and then the centralized institutions that were creating policy rapidly based on the models and leveraging the models in order to support their narratives versus actually interpreting the air bars and the models and all that kind of stuff. What you had with COVID, my view, you had with COVID is you had these experts showing up. They claim to be scientists and they had no testable hypotheses whatsoever.

They had a bunch of models. They had a bunch of forecasts and they had a bunch of theories and they laid these out in front of policymakers and policymakers freaked out and panicked and implemented a whole bunch of really like terrible decisions that we're still living with the consequences of. And there was never any empirical foundation to any of the models. None of them ever came true. Yeah, to push back, there were certainly Baptist and bootleggers in this in the context of this pandemic, but they're still a usefulness to models, no? So not if they're not, I mean, not if they're reliably wrong, right? Then they're actually like anti-useful, right? They're actually damaging. But what would you do with the pandemic? What do you

do with the, with the, with any kind of threat? Don't you want to kind of have several models to play with as part of the discussion of like, what the hell do we do here? I mean, do they work? Because they're an expectation that they actually like work that they have actual predictive value. I mean, as far as I can tell with COVID, we just saw the policymakers just siapped themselves into believing that there was substance. I mean, look, the scientists, the scientists were at fault.

The quote unquote scientists showed up. So I had some insight into this. So there was a, remember the Imperial College models out of London were the ones that were, like these are the gold standard models. Yeah. So a friend of mine runs a big software company and he was like, wow, this is like COVID's really scary.

And he's like, you know, he contacted this research and he's like, you know, do you need some help? You've been just building this model on your own for 20 years, genius, and you'd like us, our coders to basically restructure it. So it can be fully adapted for COVID. And the guy said yes and sent over the code and my friend said it was like the worst spaghetti code he's ever seen. That doesn't mean it's not possible to construct a good model of pandemic with the correct

air bars with a high number of parameters that are continuously many times a day updated as we get more data about a pandemic. I would like to believe when a pandemic hits the world, the best computer scientists in the world, the best software engineers respond aggressively. And as input takes the data that we know about the virus and it's an output, say, here's what's happening in terms of how quickly it's spreading, what that lead in terms of hospitalization and death and all that kind of stuff. Here's how likely, how contagious it likely is.

Here's how deadly likely is based on different conditions, based on different ages and demographics and all that kind of stuff. So here's the best kinds of policy. It feels like you could have models, machine learning, that like kind of they don't perfectly predict the future, but they help you do something because there's pandemics that are like, meh, they don't really do much harm and there's pandemics. You can imagine them, they could do a huge amount of harm.

They can kill a lot of people. So you should probably have some kind of data driven models that keep updating that allow you to make decisions that are based like where, how bad is this thing? Now you can criticize how horrible all that went with the response to this pandemic. But I just feel like there might be some value to models. So to be useful at some point, it has to be predictive, right? So and so and so the easy thing for me to do is to say, obviously, right, obviously, I want to see that just as much

as you do because anything that makes it easier to navigate through society through a wrenching risk like that, it's not that it sounds great. You know, the the harder objection to it is just simply, you were trying to model a complex dynamic system with 8 billion moving parts, like not possible. It's very tough. It can't be done. Complex systems can't be done. Machine learning says hold my beer, but well, is possible? No, I don't know. I would like to

believe that it is. I would put it this way. I think where you and I would agree is I think we would like that to be the case. We are strongly in favor of it. I think we would also agree that no such thing, with respect to COVID or pandemics, no such thing. Well, at least neither Unirai, I think, or I'm not aware of anything like that today. My main worry with the response to the pandemic is that same as with aliens, is that even if such a thing existed,

and it's possible it existed, the policy makers were not paying attention. Even if such a thing existed and it's possible it existed the Policy makers were not paying attention like there was no mechanism that allowed those kinds of models to percolate Oh, I think we have the opposite problem during COVID. I think the policymakers I think that these these people with basically fixed science had too much access to the policymakers Well, right and what but the policy makers also wanted they had a narrative in mind and they also wanted to use whatever model to fit that narrative to help them out. So like, it felt like there's a lot of politics and not enough science. Although a big part of what was happening, a big reason we got lockdowns for as long as we did was because he's scientists came in with these like domestic

scenarios that were like just like completely off the hook. Scientists and quotes. That's not quote unquote scientists. It's not okay. It's this give love science. That's not quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote, quote What? So number one is when we start with number one, humility. Goes back to this thing of how do we determine the truth. Number two is we don't believe, you know, it's the old, I've got a hammer, everything looks like a nail, right?

I've got, oh, this is one of the reasons I gave you, I gave Alexa book, which in the topic of the book is what happens when scientists basically stray off the path of technical knowledge and start to weigh in on politics and societal issues. In this case philosophers. Full of one is case philosophers, but he actually talks in this book about like I'm starting to talk about the nuclear age and Einstein. He talks about the physicists actually doing doing very similar things at the time. The book is when reason goes on holiday, philosophers and politics by Nevin.

And it's just a story. It's a story. There's there are other books on this topic, but this is a new one. It's really good. It's just a story of what happens when experts in a certain domain decide to weigh in and become basically social engineers and and political, you know, basically political advisors. And it's just a story of just uniting catastrophe. Right.

And I think that's what happened with COVID again. Yeah. I found this book a highly entertaining and eye-opening read filled with amazing anecdotes of irrationality and craziness by famous recent philosophers. I definitely would. You actually read this book, you will not look at Einstein the same. Oh boy. Yeah.

I'll destroy my hearing loss. You will not be a hero of yours anymore. I'm sorry, you probably shouldn't read the book. All right. But here's the thing, the AI, the AI risk people, they don't even have the COVID model. At least not that I'm aware of. No. Like, there's not even the COVID model, they don't even have the COVID model. At least not that I'm aware of. Like, there's not even the COVID model. They don't even have this spaghetti code.

They've got a theory and a warning and a this and that. And like, if you ask like, okay, well, here's, I mean, the ultimate example is, okay, how do we know, right? How do we know that an AI is running away? Like, how do we know that the FUM take off thing is actually happening? And the only answer that any of these guys

that I've given that I've ever seen is, oh, it's when the loss function and the training drops. That's when you need to shut down the data center. And it's like, well, that's also what happens when you're successfully training a model. Like, what even is, this is not science. This is not, it's not anything. It's not a model, it's not anything.

There's nothing to argue with it is like, pushing Jello, like there's, what do you even respond to? So just push back on that. I don't think they have good metrics of, yeah, wonderful is happening, but I think it's possible to have that. Like I, just as you speak now, I mean, it's possible to imagine that could be measures.

It's been 20 years. No, for sure, but it's been only weeks since we had a big enough breakthrough in language models. We can start to actually have, the thing is the AI Doomer stuff didn't have any actual systems to really work with. And now there's real systems. You can start to analyze like how does this stuff go wrong?

And I think you kind of agree that there is a lot of risks that we can analyze. The benefits outweigh the risks in many cases. Well, the risks are not existential. Yes. Well, not in the food, not in the food paper clip. Let me, okay, there's another slide of hand that you just alluded to. There's another slide of hand that happens.

I'm just very good at this slide of hand thing, which is very not scientific. So the book's super intelligence, right, which is like the Nick Boshner's book, which is like the origin of a lot of this stuff, which was written, you know, whatever, 10 years ago or something. So he does this really fascinating thing in the book, which is he basically says, there are many possible routes to machine intelligence, to artificial intelligence, and he describes all the different routes to artificial intelligence, all the different possible, everything from biological augmentation through to, you know, that of all these different things. One of the ones that he does not describe is large language models because, of course, the book was written before they were invented and so

they didn't exist. In the book, he describes them all and then he proceeds to treat them all as if they're exactly the same thing. He presents them all as sort of an equivalent risk to be dealt with in an equivalent way to be thought about the same way. And then the quote unquote risk that's actually emerged is actually a completely different technology than he was even imagining. And yet all of his theories and beliefs are being transplanted by this movement, like straight on this new technology. And so again, like, there's no other area of science or technology where you do that. Like when you're dealing with like organic chemistry versus

inorganic chemistry, you don't just like say, oh, with respect to like either one, basically, maybe, you know, growing up and eating the world or something like they're just going to operate the same way. You don't. But you can start talking about, as we get more and more actual systems that start to get more and more intelligent, you can start to actually have more scientific arguments here. You know, high level, you can talk about the threat of autonomous weapon systems back

before we had any automation in the military. And that would be like very fuzzy kind of logic. But the more and more you have drones that are becoming more and more autonomous, you can start imagining, okay, what does that actually look like? And what's the actual threat of autonomous weapons systems? How does it go wrong? And still it's very big. But you start to get a sense of like, all right, it should probably be illegal or wrong or not allowed to do like

Mass deployment of fully autonomous drones that are doing aerial strikes. Oh, no, I'm large areas. I think it should be required Right, so that's no, no, no, I think if you're required that only Aerial vehicles are automated Okay, so you want to go the other way. I want to go the other way. I think it's obvious that the machine is going to make a better decision than the human pilot. I think it's obvious that it's in the best interest of both the attacker and the defender and humanity at large if machines are making more decisions than not people.

I mean, people make terrible decisions in times of war. But like, there's ways this can go wrong too, right? Well, the war is was terribly wrong now. This goes back to the hope this is that whole thing about like the self drive, just the self driving car need to be perfect versus doesn't need to be better than the human driver. Yeah. Does the automated drone need to be perfect or does need to be need to be better than human pilot at making decisions under enormous amounts of stress

and uncertainty? Yeah. Well, the on average,, the worry that AI folks have is the runaway. You're going to come alive. That's the slide of hands. Not come alive. Well, I'll ask again. You can become the loose control last but then they're going to develop goals of their own. They're going to develop a mind of their own. No, more like Chernobyl style meltdown, like just bugs in the code accidentally, you

know, force you, the results in the bombing of like large civilian areas. Okay. To a degree that's not possible in the current military strategies. I don't know. The trope of humans. Well, actually, we've been doing a lot of mass bombing cities for a very long time. Yes. And a lot of civilians died.

A lot of civilians died. And if you watch the documentary, the Fog of War, McNamara, it spends a big part of it talking about the fire bombing of the Japanese cities burning them straight to the ground. Right? The devastation in Japan, the American military fire bombing in the cities in Japan was considerably bigger

devastation than the use of nukes. So we've been doing that for a long time. We also did that Germany, by the way Germany did that to us, right? That's an old tradition. In a minute, we got airplanes. We started doing indiscriminate bombing. So one of the things that we're still doing at the modern US military can do with technology, with automation, but technology more broadly is a higher and higher precision.

Yeah. So precision is obviously, and this is the, the, the J Dam, right? So there was this big advance, this big advance, called the J Dam, which basically was trapping a GPS transceiver to, uh, to a, to an unguided bomb and turning it into a guy that got it, um, yeah, that's right. Like, look, that's been a big advance. But, but, and that's like a baby version of this question, which is, okay, do you want like the human pilot, like guessing where the bomb is going to land? Or do you want like the machine like guiding the bomb to a destination? That's a baby version of this question, which is, okay, do you want like the human pilot, like guessing where the bomb's going to land or do you want like the machine like I had in the

bomb to a destination? That's a baby version of the question. The next version of the question is, do you want the human or the machine deciding whether to drop the bomb? Everybody just assumes the human's going to do a better job for what I think are fundamentally suspicious reasons. Emotional, psychological reasons. I think it's very clear that the machine's going to do a better job making that decision because the human's making that making that decision are got awful. Just terrible. Yeah. Right. And so, so yeah, so this is the thing.

And then let's get to the, there was, can I one more slide of hand? Yes, sure. Okay. Please. I'm a magician, you could say. One more slide of hand. These things are going to be so smart, right? That they're going to be able to destroy the world and wreak havoc and like do all this

stuff and plan and do all this stuff and evade us and have all their secret things and their secret factories and all this stuff. But they're so stupid that they're going to get tangled up in their code and that's the they're not going to come alive, but there's going to be some bug that's going to cause them to like turn us all into people like that they're not going to that they're going to be genius in every way other than the actual bad goal. And it's just like and that's just like a like ridiculous like discrepancy. And and and and you can prove this today, you can actually address this today for the first time with LLM,

which is you can actually ask LLM us to resolve moral dilemmas. So you can create the scenario, that that that that that that that that that that what would you as the AI do in the circumstance. And they don't just say, destroy all humans, destroy all humans. They will give you actually very nuanced moral, practical trade off oriented answers. And so we actually already have the kind of AI human, destroy all humans, they will give you actually very nuanced moral, practical, trade-off,

oriented answers. So we actually already have the kind of AI that can actually think this through and can actually like, you know, reason about goals. Well, the hope is that AGI or like a very super intelligent systems have some of the nuance that LLMs have and the intuition is they most likely will because even these all limbs have the nuance. LMs are really, this is actually worth spending a moment on LMs are really interesting to have moral conversations with. And that, I didn't expect I'd be having a moral conversation with the machine in my lifetime. Wait, and let's remember we're not really having a conversation with the machine

where we're having a conversation with the entirety of the collective intelligence of the human species. Exactly. Yes, correct. But it's possible to imagine autonomous weapon systems that are not using LLMs. If they're smart enough to be scary, where are they not smart enough to be wise?

Like that's the part where it's like, I don't know how you get the one without the other. Is it possible to be super intelligent without being super wise? Well, you're, it's again, you're back to, I mean't know how you get the one without the other. Is it possible to be super intelligent without being super wise? Well, again, you're back to, I mean, then you're back to a classic autistic computer, right? Like, you're back to just like a blind rule follower. I've got this like core, it's the paperclip thing.

I've got this core rule and I'm just going to follow it to the end of the earth. And it's like, well, but everything you're going to be doing to execute that rule is going to be super genius level that humans aren't going to be able to counter. It's just a, it's a mismatch in the definition of what the system is capable of. Unlikely, but not impossible, I think. But again, here you get to like, okay, like, no, I'm not saying when it's unlikely, but not impossible, if it's unlikely, that means the fear should be correctly calibrated. Extraternary claims required, extraternary proof.

Well, okay. So one interesting sort of tangent I would love to take on this because you mentioned this in the essay about nuclear, which was also I mean you don't share away from a little bit of a spicy take so Robert Oppenheimer famously said now I am become death the destroyer of worlds as he witnessed the first detonation of a nuclear weapon on July 16th 1945 and you write an interesting historical perspective, quote, recall that John Vaan Neumann responded to Robert Oppenheimer's famous

hand-ringing about the role of creating nuclear weapons, which, you note, helped end World War II and prevent World War III with some people confess guilt to claim credit for the sin. And you also mentioned that Truman was harsher after meeting Oppenheimer. He said that don't let that crybaby in here again. Real cool. Real quote by the way, from Dean from Dean, Adjusson. Boy, because Oppenheimer didn't just say the famous line.

Yeah, he then spend years going around basically Moaning him, you know going on TV and going into going into the White House and basically like just like doing this hair shirt You know thing self, you know this sort of self critical like oh my god. I can't believe how awful I am So he's the he's widely considered Perhaps because of the hangry is the father of the atomic bomb It's this is this is a anonymous criticism of him as he tried to have his cake needed to, like he wanted to, and so, in vionymist of course, a very different kind of personality. And he's just like, yeah, screw this is like an incredibly useful

thing. I'm glad we did it. Yeah. Well, vionymist as widely credited as being one of the smartest humans of the 20th century, certain people, everybody says like, this is the smartest person I've ever met when they've met him. Anyway, that doesn't mean smart, doesn't mean wise. So, I would love to say, can you make the case both foreign against the critique of Oppenheimer here?

Because we're talking about nuclear weapons. Boy, do they seem dangerous. Well, so the critique goes deeper. And I left this out. Here's the real substance I left it out, because I didn't want to dwell on a nooks in my paper. But here's the deeper thing that happened. And I'm really curious, this movie coming out this summer. I'm really curious to see how far he pushes this, because this is the real drama in the story,

which is it wasn't just a question of our nooks good or bad. It was a question of should Russia also have them? And what actually happened was Russia got the... which is it wasn't just a question of our new scooter bad, it was a question of should Russia also have them. And what actually happened was Russia got the, American invented the bomb. Russia got the bomb. They got the bomb through espionage. They got American and, you know, they got American scientists and foreign scientists working on the American project. Some combination of the two. Basically gave the Russians the designs for the bomb. And that's how the Russians got the bomb. There's this dispute to this day of Oppenheimer's role in that. If you read all the histories, the kind of composite picture, and by the way, when we now know a lot, I actually about Soviet espionage in that era, because there's been all this declassified material in the last 20 years,

that actually shows a lot of a lot of very interesting things. But if you kind of read all the histories, what you kind of get is Oppenheimer himself probably was not a, he probably did not hint over the nuclear secrets himself. However, he was close to many people who did, including family members. And there were other members of the Manhattan Project who were Russian Soviet SS and did hand over the bomb. And so the view that Alpenheimer and people like him had that this thing is awful and terrible and oh my god, and you you know all this stuff you could argue fed into this ethos at the time that resulted in people thinking that the Baptist is thinking

that the only principle thing to do is to get the Russians to the bottom. And so the moral beliefs on this thing and the public discussion and the role that the inventors of this technology play, this is the point of this book when they kind of take on this sort of public intellectual moral kind of thing, it can have real consequences, right? Because we live in a very different world today because Russia got the bomb than we would have lived in had they not gotten the bomb, right? The entire 20th century, second half of the 20th century would have played out very different had those people not given Russia the bomb.

And so the stakes were very high. Then the good news today is nobody sitting here today. I don't think worrying about like an analogous situation with respect to like, I'm not really worried that Sim Altman's going to decide to give, you know, the Chinese, the design for. Day, although he did just speak at a Chinese conference, which is interesting.

But however, I don't think, I don't think that's what's at play here. But what's at play here are all these other fundamental issues around what do we believe about this and then what laws and regulations and restrictions that we're going to put on it. And that's where I draw like a direct straight line. And anyway, and my reading of the history on Newcastle is like the people who were doing the full hair shirt

public. This is awful. This is terrible. Actually had like catastrophically bad results from taking those views. And that's what I'm worried is going to happen again. But is there a case to be made that you really need to wake the public up to the dangers of nuclear weapons when they were first dropped? Like really, like educate them on like, this is extremely dangerous and destructive weapon. I think the education kind of happened quick and early. Like, how? It was pretty obvious.

How? We dropped from one bomb and destroyed it into our city. Yeah, so 80,000 people did. Yeah. But look, the, the reporting of that, you can report that in all kinds of ways. Wars you can you can do all kinds of slants like wars, horrible, wars, terrible. You can do you can make it seem like nuclear the use of nuclear weapons is just a part

of war and all that kind of stuff. Something about the reporting and the discussion of nuclear weapons resulted in us being terrified in awe of the power of nuclear weapons. And that potentially fed in a positive way towards the game theory of mutual issue or destruction. Well, so this gets to what actually happens. Some of us, me playing Devils, I have to get here. Yeah, sure, of course. Let's get to what actually happened, then kind of back into that. So what actually happened, I believe, and again, I think this is a reasonable reading of history, is what actually happened was Newt's then prevented World War III. And they prevented World War III through the game theory of mutually assured destruction. Had Newt's not existed,

right? There would have been no reason why the Cold War did not go hot, right? And then they're in the military planners at the time, right? Thought both on both sides, thought that there was going to be World War III on the plains of Europe, and they thought there was going to be like 100 million people dead, right? It was like the most obvious thing in the world, right, thought both on both sides thought that there was going to be World War III on the plans of Europe and they thought there was going to be like 100 million people dead, right? It was like the most obvious thing in the world to happen, right? And it's the dog that didn't bark, right? Like it may be like the best single net thing that happened in the entire 20th century is that like that didn't happen.

Yeah, actually just on that point, you say a lot of really brilliant things. It hit me just as you were saying it. I don't know why it hit me for the first time, but we got two wars in a span of like 20 years. Like we could have kept getting more and more world wars and more and more ruthless. It actually you could have had a US versus Russia war. You could have, by the way,

there's another hypothetical scenario. The other hypothetical scenario is the Americans got the bomb, the Russians didn't, right? And then America is the big dog. And then maybe America would have had the capability to actually roll back their curtain. I don't know whether that would have happened, but like it's entirely possible, right? And the act of these people who had these moral positions about, because they could forecast, they could model, they could forecast the future of how the technology used made a horrific mistake, because they basically ensured that the Aaron Curtin would continue for 50 years longer than it would have otherwise.

And again, like these are counterfactuals. I don't know that that's what would have happened, but like the decision to hand the bomb over was a big decision made by people who were very full of themselves. Yeah, but so me as an America, me as a person that loves America, I also wonder if US was the only ones with a nuclear weapons. Uh, that was the argument for handing the, that was the, was the guys who, the guys who handed over the bomb. That was actually there. More argument.

Yeah, I would, I would probably not handed over to, I would, I would be careful about the regimes you handed over to. Maybe you give it to like the British or something, like a democratically elected government. Well, if there are people to this day who think that those spies, so if he spies did the right thing because they created a balance of terror as opposed to the US having just and by the way, let me, let me balance of terror. Let's tell the full version of the story.

That's such a sexy ring to it. Okay, so the full version of the story is John Von Neumann's a hero of both yours and mine the full version of the story is he advocated for a first right so when the US had the bomb and Russia did not he advocated for he said we need to strike them right now. Strike Russia. Yeah. Yes. Yes, because he said World War III is inevitable. He was very hardcore. His theory was, his theory was World War III is inevitable. We're definitely going to have World War III. The only way to stop World War III is we have to take them out right now and we have to take them out right now before they get the bomb because this is our last chance. Now again, is this an example of philosophers and politics?

I don't know if that's in there or not, but this is in the standard by the way. No, but it is meaning is that. Yeah, this is on the other side. So, so most of the case studies, most of the case studies in books like this are the crazy people on the left. Yeah. Um, the Vennoyment is a story arguably of the crazy people on the right. Um, yes, they did computing. John. Well, this is the thing and this is the general principle is getting respect to our core

thing, which is like, I don't know whether any of these people should be making any of these calls. Yeah. Because there's nothing in either Vennoyment's background or Oppenheimer's background or any of these people's background making any of these calls. Yeah. Because there's nothing in either von Neumann's background or Oppenheimer's background or any of these people's background that qualifies them as moral authorities. Yeah. Well, this actually brings up the point of N.A.I. who are the good people to reason about the morality of the ethics.

The outside of these risks, outside of like the more complicated stuff that you agree on is, you know, this will go into the hands of bad guys and all the kinds of ways they'll do is is interesting and dangerous. Is dangerous and interesting, unpredictable ways. And who is the right person? Who are the right kinds of people to make decisions how to respond to it? Or is it tech people? So the history of these fields, this is what he talks about in the book. The history of these fields is this is what he talks about in the book, the history of these fields is that the competence and capability and intelligence and training and accomplishments of senior scientists and technologists working on a technology and then being able to then make moral judgments on the use of their technology, that track record is terrible.

That track record is like catastrophically bad. The people that develop that technology are usually not going to be the right people. Well, why would they? So the claim is, of course, they're the knowledgeable ones, but the problem is they've spent their entire life in a lab. Right, they're not theologians. But so what you find, what you find when you read this, when you look at these histories, what you find is they generally are very thinly informed on history, on sociology, on theology, on morality, ethics. They tend to manufacture their own worldviews from scratch. They tend to be very sort of thin. They're not remotely the arguments that you would be having if you got like a group of highly qualified theologians or philosophers or, you know, well, let me sort of as the devil's advocate takes a simple whiskey, say that I agree with that, but also it seems like the

people who are doing kind of the ethics departments in these tech companies go sometimes the other way. Yes. They're definitely. They're not nuanced on the on history or theology or this kind of stuff. They, it almost becomes a kind of outraged activism towards directions that don't seem to be grounded in history and humility and nuance. It's again drenched with arrogance.

So definitely not sure which is worse. Oh, no, they're both bad. No, no, yeah. So definitely not sure which is worse. Oh, no, they're both bad. Yeah, so definitely not that neither. So, but I guess, look, this is a hard, yeah, it's a hard problem. This is our problem. This goes back to where we started, which is okay, who has the truth, and it's like, well, you know, like how do societies arrive at like truth, and how do we figure these things out, and like our elected leaders play some role in it. You know, we all play some role in it. There have to be some set of public intellectuals

at some point that bring, you know, rationality and judgment, humility to it. Those people are few and far between. We should probably prize them very highly. Yeah, so celebrate humility in our public leaders. So getting to risk number two, will AI ruin our society short version, as you write, if the murder robots don't get us the

hate speech and misinformation will. And the action you recommend in short, don't let the thought police suppress AI. Well, what is this risk of the effect of misinformation of society that's going to be catalyzed by AI. Yeah, so this is the social media. This is what you just alluded to. It's the activism kind of thing that's popped up in these companies in the industry. And it's basically, from my perspective, it's basically part two of the war that played out over social media over the last 10 years. Because you probably remember social media 10 years ago was basically who even wants this, who wants a photo of what your cat had for breakfast like this stuff is like silly and trivial and why can't these nerds

like figure out how to invent something like useful and powerful. And then, you know, certain things happened in the political system and then it's sort of the polarity on that discussion switched all the way to social media as like the worst most corrosive, most terrible, most awful technology ever invented and then it leads to, you know, terrible, you know, politicians and policies and politics and like, and all this stuff. And that all got catalyzed into this very big kind of angry movement, both inside and outside the companies, to kind of bring social media to heal. And that got focused in particular on two topics, so-called hate speech and so-called misinformation. And that's been the saga playing out for the

last decade. And I don't even really want to even argue the pros and cons of the sides, just to observe that that's been like a huge fight. And it's had big consequences to how these companies operate. Basically, those same sets of theories, that same activist approach, that same energy is being transplanted straight to AI. And you see that already happening. It's why CHGPT will answer, let's say, certain questions and not others. It's why it gives you the canned speech about whenever it starts with, as a large language model, I cannot, you know, basically means that somebody has reached in there and told that it can't talk about certain topics.

Do you think so that is good? So it's an interesting question. So a couple of observations. So one is the people who find this the most frustrating are the people who are worried about the murder robots. So, and in fact, the ex, so called ex risk people, right, they started with the term AI safety. The term became AI alignment. When the term became AI alignment is when this switch happened from where we're it is going to kill us all. Don't we're worried about

his mission misinformation? The AI ex risk people have now renamed their thing AI not kill everyone is them, which I have to admit is a catchy term. And they are very frustrated by the fact that the sort of activist driven hate speech misinformation kind of thing is taking over, which is what's happened is taken over. The AI ethics field has been taken over by the hate speech misinformation people. You know, look, what I like to live in a world in which like everybody was nice to each other all the time and nobody ever said anything mean and nobody

ever used a bad word and everything was always accurate and honest. Like that sounds great. Do I want to live in a world where there's like a centralized thought police working through the tech companies to enforce the view of a small set of elites that they're going to determine what the rest of us think and feel like absolutely not. There could be a middle ground somewhere like Wikipedia type of moderation. There's moderation on Wikipedia that is somehow crowdsourced where you don't have centralized elites, but it's also not completely just a free for all because if you have the entirety of human knowledge at your fingertips, you can do a lot of harm. Like if you have a good assistant that's completely uncensored, they can help you build a bomb. They can help you

mess with people's physical well-being, right? Because that information is out there in the internet. And so presumably, it would be, you could see the positives in censoring some aspects of an AI model when it's helping you commit literal violence. And there's a section, later section of the essay where I talk about bad people doing bad things, which, and there's a set of things that we should discuss there. What happens in practice is these lines, as you alluded to this already, these lines are not easy to draw.

And what I've observed in the social media version of this is, like I described it as the slippery slope is not a fallacy. It's an inevitability. The minute you have this kind of activist personality, it gets in a position to make these decisions, they take it straight to infinity. Like, they, they, it, it, it, it, it goes into the crazy zone, like, almost immediately. It never comes back because people become drunk with power, right? And they, they, look, if you're in the position to determine what the entire world

thinks and feels and reads and says, like, you're going to take it. And, you know, Elon has, you know, ventilated this with the Twitter files over the last, you know, three months. And it's just like crystal clear, like how bad it got there. Now, the reason for optimism is what Elon is doing with the community notes. So community notes is actually a very interesting thing. So what Elon is trying to do with community notes is he's trying to have it where there's only a community to note when people who have previously disagreed on many topics agree on this one. Yes, that's what I'm trying to get at is like there's, there could be Wikipedia like models, a community notes type of models where allows you to essentially either provide

context or sensor in a way that's not resist the slipy slip nature. Now, there's another power. There's an entirely different approach here, which is basically we have AI's that are producing content. We could also have AI's that are consuming content. Yeah. Right. And so one of the things that your assistant could do for you is help you consume all the content. Right. And basically tell you when you're getting played.

So for example, I'm going to want the AI that my kid uses, right, to be very, you know, child safe. And I'm going to want it to filter for him all kinds of inappropriate stuff that he shouldn't be saying just because he's a kid. Yeah. And you see what I'm saying is you can implement that. You could, you could, you could, you could say, you can solve this on the client side, right?

Solving on the server side gives you an opportunity to dictate for the entire world, which I think is where you, you take the slipper slope to hell. There's another architectural approach, which was just to solve this on the client side, which is certainly what I would endorse. It's a a risk number five will a I lead to bad people doing bad things. I can just imagine language models used to do so many bad things, but the hope is there that you can have large language models used to then defend against it by more people, by smarter people, by more effective people, skilled people, all that kind of stuff. Three-prone argument, and bad people doing bad things. So number one, you can use the technology defensively.

And we should be using AI to build broad spectrum vaccines and antibiotics for bio-weapons. And we should be using AI to hunt terrorists and catch criminals. And we should be doing all kinds of stuff like that. And in fact, we should be doing those things even just to go get get, like, you know, basically go eliminate risk from like regular pathogens that aren't like constructed by an AI. So there's the whole, there's a whole defensive set of things. Second is we have many laws on the books about the actual bad things, right? So it is actually illegal to be a crime, you know, to commit crimes to commit terrorist acts to, you know, build pathogens with the intent to deploy them to kill people. And so we have those, we don't, we actually don't need new laws for the vast

majority of scenarios. We actually already have the laws in the book. On the books, the third argument is the minute, and this is sort of the foundational one that gets really tough, but the minute you get into this thing, which you're kind of getting into, which is like, okay, but like, don't you need censorship sometimes, right? And don't you need restriction sometimes? It's like, okay, what is the cost of that? And in particular, in the world of open source, right? And so is open source AI going to be allowed or not? If open source AI is not allowed, then what is the regime that's going to be necessary

legally and technically to prevent it from developing? Right? And here again, is where you get into, and people have proposed that these kinds of things, you get into, I would say pretty extreme territory pretty fast. Do we have a monitor agent on every CPU and GPU that reports back to the government what we're doing with our computers. Are we seizing GPU clusters to get beyond a certain size like, and then by the way, how are we doing all that globally. Right. And like if China is developing an LLM beyond the scale that we think is allowable, are we gonna invade? And you have figures on the AIX risk side who are advocating potentially up to nuclear strikes to prevent this kind of thing. And so here you get into this thing.

And again, you could maybe say this is, you could even say this is what good, bad, or indifferent or whatever, but like the comparison of the news, the comparison of the news is very dangerous because one is just news for just just, just about, although we can come back to nuclear power, but the other thing was like with news, you could control plutonium, right? You could track plutonium and it was like hard to come by.

AI is just math and code, right? It's in like math textbooks and it's like there are YouTube videos that teach you how to build it and like there's open source, it's already open source. There's a 40 billion private or model running around already called Falcon Online that anybody can download. And so, okay, you walk down the logic path that says we need to have guard rails on this, and you find yourself in a authoritarian, totalitarian regime of thought control and machine control that would be so brutal that you would have destroyed the society that you're trying to protect. And so I just don't see how that actually works. So, yeah, you have to understand my brain's gone full, full steam ahead here,

because I agree with basically everything you're saying when I'm trying to play devil's advocate here. They're because, okay, you highlighted the fact that there is a slippery slope to human nature. The moment you sense there's something, you start to censor everything. something, you start to censor everything. The alignment starts out sounding nice, but then you start to align to the beliefs of some select group of people, and then it's just your beliefs. The number of people you're aligned to is smaller and smaller as that group becomes more and more powerful. Okay, but that just speaks to the people that sensor, usually the assholes and the assholes get richer. I wonder if it's possible to do without that for AI. The one way to ask this question is, do you think the base

models, the base, the baseline foundation models should be open sourced? Like what Mark Zuckerberg is saying they want to do. So I think it's totally appropriate that companies that are in the business of producing a product or service should be able to have a wide range of policies that they put. And I'll just again, I want a heavily censored model for my age. Like I actually want that. Like I would pay more money for the ones more heavily censored than the ones that's not. There are certainly scenarios where companies will make that decision. Look, an interesting thing you brought up, is this really a speech issue.

One of the things that the big tech companies are dealing with is that content generated from an LOM is not covered under Section 230, which is the law that protects internet platform companies from being sued for the user-generated content. And so it's actually, yes. And so there's actually a question, I think there's still a question which is can big American companies actually feel gendered away at all, or is the liability actually going to just ultimately convince them that they can't do it, because the minute the thing says something bad, and it doesn't even need to be hate speech, it could just be like an enact, it could hallucinate a product, you know, detail on a vacuum cleaner, you know, and all of a sudden the vacuum cleaner company sews

for misrepresentation. And there's any symmetry there, right? Because the LM is going to be producing billions of answers to questions, and it only used to get a few wrong to have it. The loss has to get updated really quick here. Yeah, and nobody knows what to do with that, right? So anyway, like they're big questions around how to do with that. So anyway, there are big questions around how companies operate at all. So we talk about those. But then there's this other question of like, OK, the open source.

So what about open source? And my answer to your question is, obviously, yes, there have to be full open source here because to live in a world in which that open source is not allowed is a world of draconian speech control, human control, machine control. I mean, you know, black helicopters with jack booted thugs coming out, repelling down and seizing your GPU like, well, no, no, I'm 100% serious.

That's you're saying slip whistle blows these days. No, no, no, no, no, that's what's required to enforce it. Like how will you enforce a ban on open source? No, you could add friction to it. Like hard to get the models. Because people will always be able to get the models, but it'll be more in the shadows, right? The leading open source model right now is from the UAE. Like the next time they do that, what do we do? Yeah. Like, oh, I see. You're like a 14 year old in Indonesia comes out with a breakthrough

model. You know, we talked about most great software comes from a small number of people. Some kid comes out with some big new breakthrough and quantization or something and has some huge breakthrough and like, what are we going to like invade Indonesia and arrest them? It seems like in terms of size models and effectiveness of models, the big tech companies will probably lead the way for quite a few years. And the question is of what policies they should use. The kid in Indonesia should not be regulated, but should Google, Meta, Microsoft, OpenAI be regulated? Well, so this goes, okay, so when does it become dangerous? Yeah. Right. Is the danger that

it's quote, as powerful as the current leading commercial model or is it that it is it is just at some other arbitrary threshold Yeah, and then by the way like look how do we know like what we know today is that you need like a lot of money to like train these things But their advances being made every week on training efficiency and you know data all kinds of synthetic You know look, I don't even like this synthetic data thing we're talking about maybe some kid figure of some way to auto-generate synthetic That's gonna change everything. Yeah, exactly. And so, like, sitting here today, like the breakthrough just happened, right? You made this point. Like the breakthrough just happened.

So we don't know what the shape of this technology is going to be. I mean, the big shock, the big shock here is that, you know, whatever number of billions of parameters basically represents at least a very big percentage of human thought. Like, who would have imagined that? And then there's already work underway. There was just this paper that just came out that basically takes a GPT-3 scale model and compresses it down to run on a single 32-course CPU. Like, who would have predicted that?

Yeah. You know, some of these models now you can run a Raspberry Pi's. Like, today they're very slow, but like, you know, maybe they'll be, you know, you have real performance. You know, like, it's math and, and here we're back, and here we're back, you do, math and code, it's math and code, it's math, code and data, it's bits. Mark's just like, want to wait this point.

He's just screw it. I don't know what to do with this. You guys created this whole internet thing. Yeah. Yeah. I mean, I, I'm a huge believer in open source here. So my argument is we're going to have open source here. So my argument is, here's my argument. My argument, my full argument is AI is gonna be like,

AI is gonna be everywhere. This is just gonna be in text, it already is. It's gonna be in text books and kids are gonna grow up knowing how to do this and it's just gonna be a thing. It's gonna be in the air and you can't pull this back anywhere you can pull back air. And so you just have to figure out how to live in this world, right?

And then that's where I think like all this hand ringing about AI risk is basically complete waste of time because the effort should go into, okay, what are, what is the defensive approach? And so if you're worried about AI generated pathogens, the right thing to do is to have a permanent project warp speed funded lavishly. Let's do a Manhattan project for biological defense, and let's build AI's and let's have like broad spectrum vaccines where we're insulated from every pathogen. Right.

And that what the interesting thing is because it's software, a kid in his basement teenager could build like a system that defends against like the worst, the worst, I mean, and to me, defense is super exciting. It's like I, if you believe in the good of human nature, that most people want it to be the savior of humanity, it's really exciting. Yes. Not, okay, that's a dramatic statement,

but like to help people. To help people. Yeah, okay, what about just the jump around? What about the risk of will AI lead to crippling in equality? You know, because we're kind of saying everybody's life will become better. Is it possible that the rich get richer here? Yeah. So this is actually ironically goes back to Marxism.

So because this was the current, so the core claim of Marxism right basically was that the owners of capital would basically own the means of production and then over time they would basically accumulate all the wealth. The workers would be paying in, and getting nothing in return, because they wouldn't be needed anymore. Marx is very worried about what he called mechanization or what later became known as automation. And the workers would be emiserated,

and the capitalists would end up with all. And so this was one of the core principles of Marxism. Of course, it turned out to be wrong about every previous wave of technology. The reason it turned out to be wrong about every previous wave of technology is that the way that the self-interested owner of the machines makes the most money is by providing the production capability in the form of products and services to the most people, the most customers as possible. The largest, this is one of those funny things where every CEO knows this intuitively and it's like hard to explain from the outside.

The way you make the most money in any business is by selling to the largest market you can possibly get to. The largest market you can possibly get to is everybody on the planet. And so every large company does, is everything that it can to drive down prices to be able to get volumes up to be able to get to everybody on the planet. And that happened with everything from electricity. It happened with telephones. It happened with radio. It happened with automobiles. It happened with smartphones. It happened with PCs. It happened with the internet. It happened with mobile broadband., it happened with smartphones, it happened with PCs, it happened with the internet, it happened with mobile broadband, it's happened by the way with Coca-Cola, it's happened with like every, you know, basically every industrially produced, you know, good

or service, people want you want to drive it to the largest possible market. And then as proof of that, it's already happened, right, which is the early adopters of like CHGPT and Bing are not like, you know, Exxon and Boeing, their, you know, your uncle and your nephew, right, it's just like, you see, they're freely available online or it's available for 20 bucks a month or something, but you know, these things went, this technology went mass market immediately. And so look, the owners of the means of production, whoever does this, I have to mention these trillion dollar questions, there are people who are going to get really rich doing this, producing these things,

but they're gonna get really rich by taking this technology to the broadest possible market. So yes, they'll get rich, but they'll get rich having a huge positive impact on. Yeah, making the technology available to everybody. Yeah. And again, smartphone's the same thing. So there's this amazing kind of twist in business history,

which is you cannot spend $10,000 on a smartphone. Right, you can't spend $100,000. You can't spend a million, like I would buy the million dollar smartphone, like I'm signed up for it. Like if it's like, suppose a million dollar smartphone was like much better than the $1,000 smartphone, like I'm there to buy it, it doesn't exist. Why doesn't it exist? Apple makes so much more money driving the price further down from $1,000 than they would

try and harvest. Right, and so it's just this repeating pattern you see over and over again, And what's great about it, what's great about it is you do not need to rely on anybody's enlightened generosity to do this. You just need to rely on capitalist self-interest. What about AI taking our jobs? Yeah, so very, very similar thing here. There's sort of a, there's a core fallacy, which again was very common in Marxism, which is what's called the lump of labor fallacy. And this is sort of the fallacy that there is only a fixed amount of work to be done in the world.

And if it's all being done today by people and then if machines do it, there's no other work to be done by people. And that's just a completely backwards view on how the economy develops and grows, because what happens is not. In fact, what happens is the introduction of technology into production process causes prices to fall. As prices fall, consumers have more spending power. As consumers have more spending power, they create new demand. That new demand then causes capital and labor to form into new enterprises to satisfy new

wants and needs. And the result is more jobs, higher wages. New wants and needs. The worries that the creation of new wants and needs at a rapid rate will mean there's a lot of turnover and jobs, so people will lose jobs. Just the actual experience of losing a job and having to learn new things and your skills is painful for the individual. One, two things.

One is that new jobs are often much better. So it actually came up that there was this panic about a decade ago on all the truck drivers are going to lose their jobs, right? And number one, they didn't happen because we haven't figured out a way to actually finish that yet. But the other thing was like like truck driver, like I grew up in a town that was basically consistent of a truck stop, right? And I like knew a lot of truck drivers. And like truck drivers live a decade shorter than everybody else. Like they, it's a, it's actually like a very dangerous like they get, like literally they have like high racist skin cancer. And on the left side of their, on the left side of their body from being in the sun all the time, the vibration of being in the truck is actually very damaging to your physiology.

And there's actually perhaps partially because of that reason, there's a shortage of people who want to be truck drivers. Yeah, like it's not, it's not like, the question always you want to ask somebody like that is, do you want your kid to be doing this job? And like most of them will tell you, no, like I want my kid to be sick and it's cubicle somewhere, like where they don't have this, like where they don't die 10 years earlier. And so the new jobs, number one, the new jobs are often better,

but you don't get the new jobs until you go through the change. And then to your point, the training thing, you know, it's always the issue is can people adapt. And again, here you need to imagine living in a world in which everybody has the AI assistant capability, right, to be able to pick up new skills much more quickly and be able to have some, you know, be able to have a machine to work with the argument their skills. It's still going to be painful, but that's the process of life. It's painful for some people. I mean, there's no, like, there's no question it's painful for some people

in there. You know, there, yes, it's not, I've got, I'm not a utopian on this. And it's not like it's, it's positive for everybody in the moment, but it has been overwhelmingly positive for 300 years. I mean, look, the concern here, the concern, this concern has played out for, for literally centuries. And, you know, this is the sort of lulletite, you know, the story of the lulletites. That you may remember, there was a panic in the 2000s around outsourcing. It was going to take all the jobs. There was a panic in the 2010s that robots were going to take all the jobs. There was a panic in the 2010s that robots were going to take all the jobs. In 2019 before COVID, we had more jobs at higher wages,

both in the country and in the world than at any point in human history. And so the overwhelming evidence is that the net gain here is like just wildly positive. And most people like overwhelmingly come out the other side being huge beneficiaries of this. So you write that the single greatest risk, this is the risk you're most convinced by.

The single greatest risk of AI is that China wins global AI dominance, and we, the United States and the West do not. Can you elaborate? Yeah, so this is the other thing, which is a lot of the sort of AI risk debates today, sort of assume that we're the only gaming town, right? And so we have the ability to kind of sit in the United States and criticize ourselves

and do, you know, have our government like, you know, beat up on our companies and we're figured out a way to restrict what our companies can do. And, you know, we're going to, you know, we're going to ban this and ban that, restrict this and do that. And then there's this like other like force out there that like doesn't believe we have any power over them whatsoever. And they have no desire to sign up for whatever rules we decide to put in place. And they're going to do whatever it is they're going to do and we have no control over it at all.

And it's China and specifically the Chinese Communist Party. And they have a completely publicized open plan for what they're going to do with AI. And it is not what we have in mind. And not only do they have that as a vision of a plan for their society, but they also have it as a vision and plan for the rest of the world. So their plan is what surveillance? Yeah, authoritarian control. So authoritarian population control, you know, good old fashion communist authoritarian control, and surveillance and enforcement, and social credit scores

and all the rest of it. And you are gonna be monitored and metered within an inch of everything all the time. And it's gonna, basically the end of human freedom and that's their goal. And they justify it on the basis of, that's what leads to peace. And you're worried that the regulating in the United States will halt progress enough to where the Chinese government

would win that race. So their plan, yes, yes. And the reason for that is they, and again, they're very public on this. Their plan is to proliferate their approach around the world. And they have this program called the Digital Silk Road, which is building on their Silk Road Investment Program. And they've got, they've been laying networking infrastructure all over the world with their 5G, right, work with their company Huawei.

So they've been laying all this fabric, but financial and technological fabric all over the world. And they're planning to roll out their vision of AI on top of that. And to have every other country be running their version. And then if you're a country prone to authoritarianism, you're going to find this to be an incredible way to become more authoritarian.

If you're a country, by the way, not prone to authoritarianism, you're going to have the Chinese Communist Party running your infrastructure and having backdoors into it, right? Which is also not good. What's your sense of where they stand in terms of the race towards superintelligence as compared to the United States? Yeah, so good news is they're behind, but bad news is they get access to everything we

do. So they're probably a year behind at each point in time, but they get downloads, I think of basically all of our work on a regular basis through a variety of means. And they are, you know, we'll see they're at least putting out reports of very, they've just put out a report last week of a GPT 3.5 analog. They put out this report, forget what it's called, but they put out this report of the cell and they did it. You know, the way, when OpenAI puts out, they, one of the ways they test, you know, GPT, is they run it through standardized exams like the SAT, right? Just how you can kind of gauge how smart it is. And so the Chinese report, they ran their LM through

the Chinese equivalent of the SAT. And it includes a section on Marxism and a section on Mao's, say, tongue of thought. It turns out their AI does very well on both of those topics. Right. So like this, this alignment thing, communist AI, right? Like literal communist AI, right? And so their vision is like that's the, you know, so, you know, you can just imagine like you're a school, you know, you're a kid 10 years from now in Argentina or in Germany or in who knows where in Indonesia.

And you ask, I'd explain to you how the economy works and it gives you the most cheery upbeat explanation of Chinese style communism you've ever heard. So the stakes here are really big. Well, as we've been talking about, my hope is not just with the United States, but we just the kid in this basement, the open source at LLM. I don't know if I trust large centralized institutions with super powerful AI No matter what their ideology is a power corrupts You've been investing in tech companies for about let's say 20 years and

About 15 of which was with Andreessen Horowitz. What interesting trends in tech have you seen over that time? Just talk about companies and just the evolution of the tech industry. I mean, the big shift over 20 years has been that tech used to be a tools industry for basically from like 1940 through to about 2010, almost all the big successful companies were pixel shovels companies. So PC, database, smartphone, you know, some some some tool that somebody else would pick up and use. Since 2010 most of the big wins have been in applications. So a company that starts a you know

it starts in an existing industry and goes directly to the customer in that industry. And you know the early examples there were like Uber and Lyft and Airbnb and then that model is kind of elaborating out. The AI thing is actually a reversion on that for now because most of the AI business right now is actually in cloud provision of AI APIs for other people to build on, but. But the big thing will probably be an app.

Yeah, I think most of the money, I think probably will be in whatever, yeah, your AI financial advisor or your AI doctor or your AI lawyer or take your pick of whatever the domain is. And what's interesting is, you know, we valley kind of does everything. We are entrepreneurs kind of elaborate every possible idea. And so there will be a set of companies that like make AI something that can be purchased and used by large law firms. And then there will be other companies that just go direct to market as an AI lawyer. What advice could you give for startup founder? Just haven't seen so many successful companies. So many companies that fail also.

What advice could you give to startup founder, someone who wants to build the next super successful startup in the tech space, the Googles, the apples, the twitters. Yeah, so the great thing about the really great founders is they don't take any advice. So, if you find yourself listening to advice, maybe you shouldn't do it. Well, that's actually just to elaborate on that.

If you could also speak to great founders, do you, like what makes a great founder. So, it makes a great founder is super smart, coupled with super energetic, coupled with super courageous. I think it's some of those three. And intelligence, passion, courage. The first two are traits, and the third one is a choice, I think, courage is a choice.

Well, because courage is a question of pain tolerance, right? So how many times you want to get punched in the face before you quit? Yeah. And here's maybe the biggest thing people don't understand about what it's like to be a startup founder is it gets very romanticized, right? And even when even when they fail, it still gets romanticized about like what a great adventure it was, but like the reality of it is most of what happens is people telling you know, and then they usually follow that with your stupid, right?

No, I will not come to work for you. I will not leave my cushy job at Google to come work for you. No, I'm not going to buy your products. No, I'm not going to run a story about your company. No, I'm not this, that's the other thing. And so a huge amount of what people have to do is just get used to just getting punched. And the reason people don't understand this is because when you're a founder,

you cannot let on that this is happening because it will cause people to think that you're weak and they'll lose faith in you. So you have to pretend that you're having a great time when you're dying inside, right? Right? Just a misery. But why do they do it?

Why do they do it? Yeah, that's the thing. It's like it is a level, especially one of the conclusions I think is it, I think it's actually for most of these people on a risk adjusted basis, it's probably an irrational act. They could probably be more financially successful on average if they just got like a real job in a big company. But there's, you know, some people just have an irrational need to do something new and build

something for themselves. And, you know, some people just can't tolerate having bosses. Oh, here's a fun thing is, how do you reference check founders? Right? So you call it, you know, normally you reference check your tie harness. Somebody as you call the bosses there. And you know, and you find out if they were good employees. And now you're trying to reference check Steve Jobs, right? And it's like, oh God, he was terrible. You know, he was a terrible employee.

He never did what we told him to do. Yeah. So what's a good reference? If you want the previous boss to actually say there, they never did what you told them to do. That might be a good thing. Well, ideally, ideally what you want the previous boss to actually say they're they never did what you told them to do. That might be a good thing. Well, ideally, ideally what you want is I will go I would like to go to work for that person. He worked for me here and now I'd like to work for him. Now, unfortunately, most people can't their egos can't handle that. So they won't say that,

but that's the ideal. What advice would you give to those folks in the space? They've intelligence, passion, and courage? So, I think the other big thing is, you see people sometimes who say, I want to start a company and then they kind of work through the process of coming up with an idea. And generally, those don't work as well as the case where somebody has the idea first, and then they kind of realize that there's an opportunity to build a company and then they just turn out to be the right kind of person to do that. Let me say, idea, do you mean long term big vision, or do you mean specifics of like product?

Yeah, I would say specific, like specifically what, yes, specifics, like what is, because for the first five years you don't get to have vision, you just gotta build something people want and you gotta figure out a way to sell it to them, right? It's very practical, or you never get to big vision. So, for the first, you have an idea of a set of products, the first product that can actually make some money. Yeah, like it's got a, it's got a work, it's got to work by which I mean like it has to technically work, but then it has to actually fit into the category and the customer's mind

of something that they want. And then, and then by the way, the other part is they have to want to pay for it. Like somebody's got to pay the bills. And so you've got to figure out how to price it and whether you can actually extract the money. Yeah. So usually it is much more predictable. Success is never predictable, but it's more predictable if you start with a great idea and then back into starting the company.

So this is what we did. We had most of that before we had that escape. The Google guys had the Google search engine working at Stanford. There's tons of examples where they peer over to our head eBay working before he left his previous job. So I really love that idea of just having a thing that prototype that actually works before you even begin to remotely scale. Yeah, by the way, it's also far easier to raise money, right? Like the ideal pitch that we receive is here's the thing that works. Would you like to invest in our company or not? Yeah. Like that's so much easier than here's 30 slides with a dream, right? And then we have this concept called the IDMAs,

which our biology, our student of Austin, came up with when he was with us. So then there's this thing, this goes to mythology, which is there's a mythology that kind of, these ideas kind of arrive like magic or people kind of stumble into them. It's like eBay with the pest dispensers or something. The reality usually with the big successes

is that the founder has been chewing on the problem for five or 10 years before they start the company and they often worked on it in school or they even experimented on it when they were a kid and they've been kind of training up over that period of time to be able to do this thing. So they're like a true domain expert. And it's sort of sounds like my my Apple pie, which is yeah, you want to be a domain expert and what you're doing. But the mythology is so strong of like, oh, I just like had this idea in the shower.

And now I'm doing it, it's generally not that. No, because maybe in the shower you have the exact product implementation details. But yeah, usually you're going to be for like years if not decades, thinking about like everything around that. Well, we call it the idea maze because the idea maze basically is like there's all these permutations like for any idea, for any idea, there's like all these different permutations, who should the customer be, what shape forms the product have and how should

we take it to market and all these things. So the really smart founders have thought through all these scenarios by the time they go out to raise money. And they have like detailed answers on every one of those fronts because they put so much thought into it. The sort of the sort of more haphazard founders haven't thought about any of that. And it's the detailed ones who tend to do much better. It's hard to know what to take a leap. If you have a cushy job or happy life. I mean, the best reason is just because you can't

tolerate not doing it, right? Like, this is the kind of thing where if you have to be advised and doing it, you probably shouldn't do it. And so it's probably the opposite, which is you just have such a burning sense of this has to be done. I have to do this. I have no choice. What if it's going to lead to a lot of pain?

It's going to lead to a lot of pain. I think that's what it means losing social relationships and damaging your relationship with love, the ones and all that kind of stuff. Yeah, look, so it's going to put you in a social tunnel for sure, right? So you're going to, you know, there's this game you can play on Twitter, which is you can do any whiff of the idea that there's basically any such thing as work-life balance and that people should actually work hard and everybody gets mad, but like the truth is, like all of the successful founders are working 80 hour weeks

and they're working, you know, they form very, very strong social bonds with the people they work with. They tend to lose a lot of friends on the outside or put those friendships on ice. Like that's just the nature of the thing. You know, for most people that's worth the trade off, you know, the advantage, you know, maybe younger founders have is maybe they have less, you know, maybe they're not they have less, for example, if they're not married yet,

or don't have kids yet, that's an easier thing to bite off. Can you be an older founder? Yeah, you definitely can. Yeah, many of the most successful founders are second, third, fourth time founders. They're in their 30s, 40s, 50s. The good news of being an older founder is you know more and you know a lot more about what to do,

which is very helpful. The problem is, okay, now you've got like us, Bows and and a family, and kids, and like you've kind of go to the baseball game and like you can't go to the baseball, you know, and so it's getting life is full of difficult choices. Yes. I can't reason. You've written a blog post on what you've been up to. You wrote this in October 2022. Quote, mostly I try to learn a lot. For example, the political events of 2014 to 2016 may clear to me that I didn't understand politics at all referencing maybe some of this, this book here. So I deliberately withdrew from political engagement and fundraising and instead read my way back into history and as far to the political left and

political right as I could. So just high level question, what's your approach to learning? Yeah, so it's basically, I would say it's auto-diadect. So it's sort of going down the rabbit holes. So it's a combination, so I kind of alluded to it in that quote, it's a combination of breadth and depth. And so I tend to, yeah, I tend to, I go broad by the nature of what I do, I go broad, but then I tend to go deep and arrive at a hole for a while, read everything I can, and then come out of it. And I might not revisit that, I'd arrive at a hole for, you know, another decade. And in that blog post that I recommend people

go check out, you actually list a bunch of different books that you recommend on different topics on the American left and the American right. It's just a lot of really good stuff. The best explanation for the current structure of our society and politics, you give to recommendations for books on the Spanish Civil War, six books on deep history of the American right, comprehensive biographies of Adolf Hitler, one of which I read and I can recommend. Six books on the deep history of the American left American right American left looking at the history to give you the context biography of Latin Lenin two of them

On the French Revolution actually have never read a biography on Lenin. Maybe that they'll be useful Everything's been so marks focused the Sebastian biography of Lenin is extraordinary Victus a bastion Yeah, so it's still useful to read. Yeah, it's incredible. I actually think it's the single best book on the Soviet Union. So that the perspective of Lenin is might be the best way to look at the Soviet universe's Stalin versus Marx versus very interesting. So two books on fascism and anti-fascism by the same author, Paul Gottzscher,

brilliant book on the nature of mass movements and collective psychology, the definitive work on intellectual life under totalitarianism, the captive mind, the definitive work on the practical life under totalitarianism. There's a bunch, there's a bunch, and the single best book, first of all,

the list here is just incredible, but you say the single best book I have found on who we are and how we got here is the ancient city by New Madenis Fistaldi Coolangus I like it What's what did you learn about who we are as a human civilization from that book?

Yeah, so this is a fascinating book. This one's free. It's a free by the way It's it's a book in the 1860s. You can download it or you can buy print out some prints of it But it's it was this guy who was a professor at the Sorbonne from the 1860s. You can download it or you can buy printouts of it. But it was this guy who was a professor at the Sorbonne in the 1860s and he was apparently a savant on Greek and Roman antiquity. And in the reason I say that is because his sources are 100% original Greek and Roman sources. So he wrote a history of Western civilization from on the order of 4,000 years ago to basically the present times entirely working on fresh, original Greek and Roman sources. And what he was specifically

trying to do was he was trying to reconstruct from the stories of the Greeks and the Romans, he was trying to reconstruct what life in the West was like before the Greeks and the Romans, which was in this in the civilization known as the Indo-Europeans. And the short answer, and this is sort of circa 2000 BC to 500 BC, kind of that 1500-year stretch for civilization developed. And his conclusion was basically cults. They were basically cults. And civilization was organized into cults.

And the intensity of the cults was like a million fold beyond anything that we would recognize today. Like it was a level of all encompassing belief and an action around religion. That was at a level of extremeness that we wouldn't even recognize it. And so specifically, he tells the story of basically there were three levels of cults. There was the family cult, the tribal cult, and then the city cult, as society scaled up. And then each cult was a joint cult of family gods, which were ancestor gods, and then nature gods. And then you were bonding into a family, a tribe, or a city, was based on your

adherence to that religion. People who were not of your family tribe city worship different gods, which gave you not just the right with the responsibility to kill them on site. Right. So they were serious about their cults. Hard core. By the way, shocking development, I did not realize as a zero concept of individual rights. Even up through the Greeks and even in the Romans, they didn't have the concept of individual rights. Like the idea that as an individual, you have like some right, just like noop, right? And you look back and you're just like, wow, that's just like crazily like fascist

and a degree that we wouldn't recognize today. But it's like, well, they were living under extreme pressure for survival. And you know, the theory goes, you could not have people running around making claims individual rights when you're just trying to get like your tribe through the winter, right?

Like you need like hardcore command and control. And so and and actually what if through modern political lens, those cults were basically both fascist and communist, they were fascists in terms of social control and then they were communist in terms of economics. But you think that's fundamentally that like pull towards cults is within us. So so my conclusion from this book, so the way we naturally think about the world we live in today is like we basically have such an improved version of everything that came before us, right? Like we have basically, we figured out all these things around morality and ethics and

democracy and all these things. And like they were basically stupid and retrograde and were like smart and sophisticated and we've improved all this. I after reading that book, I now believe in many ways the opposite, which is no, actually we are still running in that original model. We're just running in an incredibly diluted version of it. So we're still running basically in cults.

It's just our cults are at like 1000, they're a millionth of the level of intensity, right? And so just to take religions, you know, the modern experience of a Christian in our time, even somebody who considers a devout Christian is just a shadow of the level of intensity of somebody who belonged to a religion back in that period. And then by the way, we have, it goes back to our,

yeah, discussion, we then sort of endlessly create new calls. Like we're trying to fill the void, right? And the void is a void of bonding. Okay, living in their era, like everybody living today, transporting that era with you is just completely intolerable in terms of like the loss of freedom and the level of basically fascist control. However, every single person in that era, and he really stresses this, they knew exactly where they stood. They knew exactly where they belonged. They knew exactly

what their purpose was. They knew exactly what they needed to do every day. They knew exactly why they were doing it. They had total certainty about their place in the universe. So the question of meaning and the question of purpose was very distinctly clearly defined for them. Absolutely, overwhelmingly, undisputably undeniably. As we turn the volume down on the cultism, yes, we start to the search for meanings that is getting harder and harder. Yes, because we don't have that.

We are ungrounded. We are unsentered and we all feel it, right? And that's why we reach for, you know, is why we still reach for that, we are ungrounded, we are we are we are unsentered and we all feel it, right? And that's why we reach for, you know, it's why we still reach for religion, it's why we reach for, you know, we people start to take on, you know, let's say, you know, a faith in science, maybe beyond where they should put it. You know, by the way, like sports teams are like, you know, they're like a tiny little version of a

cult. And, you know, the, you know, Apple keynotes are a tiny little version of a cult, right? You know, political, you know, and there's called, you know, there's full lung cults on both sides of the political spectrum right now, right? You know, political, you know, and there's cult, you know, there's full blown cults on both sides of the political spectrum right now, right? You know, operating in plain self. But still not full blown. Oh, paradise to what it was. Compared to what it used to mean, we would today consider a full blown. But like, yes, they're at like, I don't know, a hundred thousand through something of the intensity of what people have back then. So, so we live in a

world today that in many ways is more advanced and moral and so forth. And it's certainly a lot nicer, much nicer world to live in. But we live in a world that's like very washed out. It's like everything has become very colorless and gray as compared to how people used to experience things, which is I think why we're so prone to reach for drama. There's something in us deeply involved where we want that back. And I wonder where it's all headed. I usually turn the volume down more and more.

What advice would you give to young folks today? In high school and college, how to be successful in their career, how to be successful in their life? Yes, so the tools that are available today, I mean, are just like, I sometimes, you know, bored, I sometimes bored, you know, kids by describing like what it was like to go look up a book,

you know, to try to like discover a fact in, you know, in the old days, the 1970s, 1980s, and go to library and the card catalog and the whole thing. You go through all that work and then the book is checked out and you have to wait two weeks. And like, like, to be in a world not only where you can get the answer to any question, but also the world now, you know, the A.I. world where you've got like the assistant that will help you do anything, help you teach, learn anything, like your ability both to learn and also to produce is just like, I don't know, a million fold beyond what it used to be. I have a blog post I've been wanting to write, it was I call out, where are the hyperproductive

people? Like the question, right? Like with these tools, like there should be authors that are writing like hundreds of thousands of like outstanding books. Well, with the authors, there's a consumption question too, but yeah, well, maybe not, maybe not. You're right. But so the tools are much more powerful, getting much more part of the musicians. Yeah. Right. Why aren't musicians producing a thousand times the number of songs? Right. Like, like, the tools are spectacular. So what was the explanation? And by way of advice,

like, is motivation starting to be turned out a little bit or what? I think it might be distraction. Distraction. It's so easy to just sit and consume. That I think people get distracted from production. But if you wanted to, as a young person, if you wanted to really stand out,

you could get a hyper productivity curve very early on. There's a great story, there's a great story in Roman history of plenty of the elder who was this legendary statesman, and I died in the Vesuvius eruption trying to risk his friends, but he was famous both for being a Savada, basically being a polymath, but also being an author. He wrote apparently hundreds of books, most of which have been lost, but he wrote all these encyclopedias. And he literally would be reading and writing all day long no matter what else is going on. So he would travel with four slaves, and two of them were responsible for reading to him, and two of them were responsible for taking dictation.

And so he'd be going across country, and literally he would be writing books all the time. And apparently they were spectacular. There's only a few that have survived, but apparently they were amazing. There's a lot of value to being somebody who finds focus in this life. Yeah, like when, and there are examples, like there are, you know, there's this guy, Judge, I was his name, Posner, Posner, who wrote like 40 books, and was also great federal judge, you know, there's a, or friend, biology, I think it's like this. He's one of these, you know, where he's,

his output is just prodigious. And so it's like, yeah, I mean, with these tools, why not? And I kind of think we're at this interesting kind of freeze frame moment where like these tools are not everybody's hands and everybody's just kind of staring at them trying to figure out what to do. Yeah, the new tools. We have discovered fire. Yeah. And trying to figure out how to use it to cook. Yeah. Right. You told Tim Ferris that the perfect day is caffeine for 10 hours and alcohol for four hours. You didn't think I'd be mentioning this, did you? It balances everything out perfectly, as you said. So, let me ask, what's the secret to balance and

maybe to happiness and life? I don't believe in balance. So, I'm the wrong person to ask. Can you elaborate why you don't believe in balance? I mean, maybe it's just, and I think people are wired differently. So, I think it's hard to generalize this kind of thing, but I'm much happier and more satisfied when I'm fully committed to something. So I'm very much in favor of imbalance. All in. Inbalance, and that applies to work, to life, to everything. Now, I happen to have whatever twist of personality trace lead that in non-destructive dimensions,

including the fact that I've actually, I now no longer do the 10-4 plan. I stopped drinking. I do the caffeine, but not the alcohol. So there's something in my personality right. Whatever maladaption I have is inclining me towards productive things, not on productive things. So you're one of the wealthiest people in the world. What's the relationship between wealth and happiness?

Oh, money and happiness. Oh, money and happiness. So I think happiness, I don't think happiness is the thing to strive for. I think satisfaction is the thing. That's that just sounds like happiness, but turned down a bit. No, deeper. So happiness is, you know, a walk in the woods as sunset on ice cream cone. A kiss. The first ice cream cone is great.

This 1000th ice cream cone. Not so much at some point. The walks of the woods get boring. Most of the distinction between happiness and satisfaction. I think satisfaction is a deeper thing, which is like having found a purpose and fulfilling it, being useful. So just something that permeates all your days,

just this general contentment of being useful. So just something that permeates all your days, just this general contentment of being useful. Then I'm fully satisfying my faculties, then I'm fully delivering, right, on the gifts that I've been given, that I'm, you know, net making the world better, that I'm contributing to the people around me, right, and that I can look back and say, wow, that was hard, but it was worth it. I think generally it seems to lead people in a better state than pursuit of pleasure, pursuit of quote unquote happiness. Does money. I think of do with that. I think the founders of the founding fathers in

the US through the self-kilter when they use the phrase pursuit of happiness. I think they should have said, pursuit of satisfaction. They said pursuit of satisfaction. We might live in a better world today. Well, they could have elaborate on a lot of things. They could have tweaked the second moment. I think they were smarter than realize. They said, you know what, we're going to make it ambiguous and let these these humans figure out the rest, these tribal cult like humans figure out the rest. But money empowers that. So I think and I think they're I mean, look, I think Elon is I don't think I'm even a

great example, but I think Elon would be the great example of this, which is like, you know, look, he's a guy who from every, every day of his life, from the day he's starting to make him money at all, he just plows into the, into the next thing. And so I think money is definitely an enabler for satisfaction. It was for this way. Money applied to happiness leads people down very dark paths. Very destructive avenues. Money applied to satisfaction, I think, could be, it was a real tool. I always lived by the way. I was like, you know, Elon is the case study for a behavior with the other thing that,

sorry, he's really made me think his Larry Page was asked one time what his approach to philanthropy was. And he said, oh, I'm just my philanthropic plan. I just give all the money to Elon. Right. Well, let me actually ask you about Elon. What are your, you've interacted with quite a lot of successful engineers and business people. What do you think is special about

Elon? We talked about Steve Chow's. What, what do you think is special about him as a leader and an innovator? Yeah, so the, the core of it is he's, he's, he's back to the future. So he is, he is doing the most leading edge things in the world, but with a really deeply old school approach. And so to find comparisons to Elon, you need to go to Henry Ford and Thomas Watson and Howard Hughes and Andrew Carnegie, right? Lee Lister Stanford, John DeRack-of-Feller, right? You need to go to what we're called the bourgeois capitalists, like the hardcore business owner operators who basically built, you know,

basically built industrialized society, Vanderbilt, and it's a level of hands-on commitments and depth in the business, coupled with an absolute priority towards truth and towards, to put science and technology down to first principles that is just like absolute, just like unbelievable absolute. He really is ideal that he's only ever talking engineers, like he does not tolerate, he has to let the Polish and Polish, the tallest anybody I've ever met, he wants ground truth on every single topic.

And he runs his businesses directly day to day, devoted to getting ground truth in every single topic. So you think it was a good decision from Dubai Twitter? I have developed a view in life did not second-guess Elon Musk. I know this is going to sound crazy and unfounded, but. Well, I mean, he's got a quite a track record. I mean, look, the car was a crazy, I mean, the car was, I mean, look, he's done a lot of things that

seemed crazy. Starting a new car company in the United States of America, the last time somebody really tried to do that was the 1950s and it was called Tucker Automotive and it was such a disaster. They made a movie about what a disaster it was. And then rockets, like who does that? Like there's obviously no way to start a rocket company like those days are over and then to do those at the same time. So after he pulled those two off, like, okay fine. Like, this is one of my areas of like, whatever opinions I had about that,

it's just like, okay, clearly, we're not relevant. Like this is, you just, at some point, you just like, put on the person. In general, I wish more people would lean on celebrating and supporting versus deriding and destroying. Oh, yeah. I mean, look, he drives resentment. Like it's a resentment. Like he is a magnet for resentment. Um, like his critics are the most

miserable, like resentful people in the world. Like it's almost a perfect match of like the most idealized, you know, technologist, you know, of the century coupled with like just his critics or just bitters can be, I mean, it's sort of very darkly comic to watch. Well, he fused the fire of that by being an asshole on Twitter at times, and which is fascinating to watch the drama of human civilization given our cult cult roots, just fully on fire. He's running a cult. You could say that very successfully. So now, now, there are cults have gone and we search for meaning. What do you think is the

meaning of this whole thing? What's the meaning of life, Mark Andreessen? I don't know the answer to that. I think the meaning of the closest I get to it is what I said about satisfaction. So it's basically like, okay, we were given what we have. Like we should basically do our best. What's the role of love in that mix? I mean, like, what's the point of life if you're, yeah, without love? Yeah.

So love is a big part of that satisfaction. I mean, look, like, taking care of people is like a wonderful thing. Like, you know, a mentality, you know, there are pathological forms of taking care of people, but there's also a very fundamental, you know, kind of aspect of taking care of people is like a wonderful thing. Like, you know, a mentality, you know, there are pathological forms of taking care of people, but there's also a very fundamental, you know, kind of aspect of taking care of people. Like, for example, I happen to be somebody who believes that capitalism and taking care of people are actually, they're actually the same thing. Somebody once said capitalism is how you take care of people you don't know. Right. And so like, yeah, I think it's like deeply woven into the whole thing. You know, there's a lot of conversation to be had about that. But yeah.

Yeah, creating products that are used by millions of people and bring them joy in smaller big ways. And then capitalism kind of enables that encourages that. David Friedman says there's only three ways to get somebody to do something for somebody else. Love, money and force. Love and money are better. Yeah, that's a good ordering. We should bet on those. Try love first, if that doesn't work, the money.

And then force. Well, don't even try that one. Mark, you're an incredible person. I'm been a huge fan. I'm glad I finally got a chance to talk. I'm a fan of everything you do, everything you do, including on Twitter. It's a huge honor to meet you to talk to talk. I'm a fan of everything you do, everything you do, including on Twitter. It's a huge honor to meet you to talk with you. Thanks again for doing this. Awesome. Thank you, Lex.

Thanks for listening to this conversation with Mark Andreessen to support this podcast. Please check out our sponsors in the description And now let me leave you with some words from Mark Andreessen himself. The world is a very malleable place can't dream in himself. The world is a very malleable place. If you know what you want, and you go for it, with maximum energy and drive, and passion, the world will often reconfigure itself around you much more quickly and easily than you would think. Thank you for listening and hope to see you next time.