AI as the New Printing Press

27:03So this, what can it do versus how is it actually, you know, the harness that allows it to happen is still something that people aren't really working on. And partially in the open source space, you have the incentive problem too, right? Like that's a huge engineering effort to solve. And unless you can, you know, directly monetize it in a way, companies like Google and Apple rather, which have a direct path towards monetizing it, if they can solve it, are a little more incentivized to do it. So a quick break in your regular programming. If you're serious about your future, grab my free report called Prepare for 2030.

27:36I think you've got five years to make as much money as possible and this guide will help you navigate what's coming the link is in the description download it now yeah so how does why did you go the route of open source decentralized what was the what was the philosophical reason what what is it that you see that makes you concerned by the centralization uh everyone who at news sort of has their own answer to it i'll give you mine but it's not like the company line um yeah for me it's really born out of a love of of technology so i got started with coding because um when i was like five years old a family member gave me a computer and it just like had q basic on it right and i there was no internet there's no way of knowing how it worked right so i just had to like type stuff in and figure out how how it worked and and my whole my whole experience has been basically that i've always wanted to i'm the type of person just wants to be able to step through the code to tinker with it and to be able to work with it um and to build stuff you know build stuff myself so for me just hitting an API and getting responses.

28:39It's not exciting. Is that interesting to me from like a technical or intellectual perspective? So for me, it was very much just sort of more on that on that perspective. I want to be able to get my fingers into the technicals and actually work on it. That's what brought me together. Whereas we have people and at Noose as well who view it very much more from like a political perspective, right? They say that don't want a corporation controlling what they do or knowing what they think or talk about. So everyone has their own sort of bent about why they feel that it's important. There's also there's also like, you know, people who look at it that the information ought to be free.

29:20It's even less about like the corporation, but more about like the platonic ideal of information freedom. This could, you know, like the sort of like Linuxy version or like Richard Stallman version kind of, you know, people. So there's their own view about why we got here. But what brought us all together is we said making frontier open source intelligence is something that ought to happen in the world. And there are so many players who are working against that. Let's all coalesce together and try to build this thing. Yeah. My view on this is if you are going to build the Apex intelligence, because it's very close to being smarter than us.

29:54When you call it A.J. or not, it's a matter of humans admitting that they're not the smartest creatures anymore. It's as simple as that, which is why nobody wants to say it, because politically it's not a good thing to say. But once you do build apex intelligence, we're seeing it playing at geopolitical level. It's like China cannot have it without the U.S. having it. Europe seems to be ignoring it, which is bizarre. But you kind of everybody needs to have a share of that intelligence. And it can't just be down to nation states either. You know, nation states via their big monopolies, open AI, anthropic, etc., that it's going to have to go to the edges.

30:34Because if not, it's far too powerful. It's just far too powerful to put in the hands of a few. And if you think about it, you know, we've seen things like this play out throughout history, right? I mean, you can go back really to the invention of something like the printing press, right? So previously you had the ability to, what is like the written word really? It's the ability to like take ideas and send them beyond just your own lifetime, right? Like you're able to immortalize ideas beyond your own lifetime. And that was held within like a closely guarded group of these scribes and monks were able to read and write and propagate information, you know, forward through time.

31:12And at one point, like the printing press radically, you know, decentralized that. It allowed information to be propagated easily, you know, forward in time through generations very quickly. And this has been like a net positive for society, you know, probably. There's always the unintended consequences of... High unintended consequences, but we continue like... Same with the internet, same idea. And the same idea here is that we have this transformational technology, which we see in a centralized fashion how powerful it can be. So we're sitting right there like the pre printing press era of AI right now, right?

31:48Like you could see how powerful it is. You could see how incumbents who were able to hold on to this power would be, you know, essentially like immortal. And the rest of us are just, you know, paying homage to to that immortality. Or we can diffuse that across all people. And if you do use things like permissionless, disintermediated technologies like like blockchain technologies, which are don't have a centralized point of failure, even within a nation state. Right. Like even within a nation state. I'm sure the United States government, like they really wanted to try to shut Ethereum down, but it would be really hard or try to shut Ethereum down.

32:27It'd be really hard. And so because you just need some people to be to be to be to be running it. And so to us, too, taking that and spreading it out across the world is likely to have the best outcome for the most people. Yeah. And it can go further because it's more, you know, more people get access. The more people competing, the cheaper it gets, the more people get access. And so nobody can throttle intelligence. And that becomes a really key thing. What is what is Venice AI up to that's different to what you're doing? because they're also using blockchain uh venice is um they primarily are on the inference side hosting so they're about hosting the actual models so that people can come in and run them themselves uh we run we have an inference component of our network as well that we brought up so we do both training and inference and probably even more important than that is that we have the ai research lab around it so we use we use the crypto rails insofar as they are the correct technology to achieve our goals, which is to have open source frontier AI.

33:38And so we use it where it makes sense. And that is a great, yeah. For the coordination layer of all of this. Yeah, correct. Yeah, yeah. And how do you deal with the exponentiality of all of this space? I mean, it's, I knew this was coming, but it's hard for anybody to keep up now with the rate of change. You know, suddenly, everyone's talking about opus four and a half like oh my god this is agi for coding and then next week codex you know whatever version comes out it's like it's impossible yeah i mean even for me um you know i was it's funny like a year ago i hard you know i've been working in the space four years up to six months ago i didn't actually really use models at all um that they didn't have there was nothing they didn't do anything that i couldn't do especially as a coder um i will say like opus four or five thinking is the first time that uh me who've been you know a practitioner in the space for 25 years now it's it can help me like it actually like it's as good as that and so even now i can i'm sort of on the uh i've been sort of black you know i've been pilled now like i believe like it's coming but the space is so fast um that's just the way that's the name of the game you know either you're getting on this car or you're you're getting off we have a group We have a group of our researchers really spend a large amount of their time just reading the papers, you know, just trying to stay at the forefront of the wave is what I tell everyone on the team is that like we need to be at the forefront of this wave.

35:04And so whatever it takes to stay at the forefront, we got to, you know, by hook or by crook, we got to we got to do it. I'll give you a little side story about just how crazy it's getting, though. There's this academic conference called ICLR. It's the premier AI academic conference. Right. It was created maybe like 15 years ago. But it is like the top place where papers would go, the top academic conference. Right. And like four years ago, it got like a thousand submissions. Right. Three years ago, it got like 2000 submissions. Two years ago, it got like 5000 submissions. And this last year, it got like 20 ,000 submissions.

35:41And what happened was that this used to be operating like an old school academic, double blind peer review. It was very institutionalized in the academic sense. But now, because getting a paper into ICLR is equivalent to getting the highest prestige checkmark that you can get in the AI space, there's this giant incentive for people to get their research ideas into ICLR. You have these 20 ,000 papers, and then the reviewers are using AI to review their papers. And then it's just this crazy cycle that goes to show how our traditional institutions are not able to handle the exponential that we're currently sitting on.

36:22What about Tau and how that all fits in as well? Yeah, BitTensor, yeah. So BitTensor is interesting, too. I mean, I think it's a Cosmos chain, right? And we worked on BitTensor a bit. It's a little bit of a different model because with BitTensor, it doesn't actually prescribe what happens on the network. And so it sort of leaves it up to chance. And maybe you'll have a research team that comes in and develops something on it. But the goodness of what happens on the network is sort of disintermediated from whether the network is funding it or not. So it was kind of an interesting misalignment maybe between how some of the incentives have worked out.

37:14I know they've changed a lot of it since then. So BitTensor is much more neutral in a sense, right? Like it's just the blockchain layer. It would take the place of Solana on our network or something like that. Whereas what we're building with Psyche is really purpose-built to make frontier open-source artificial intelligence. And how are you going to deal with agents? Because this gets really interesting as well. Having decentralized autonomous agents with payment systems. Yeah. It's quite the world we're about to walk into, right? Yeah. Well, so I'm very interested. We're very early on like X402 and some of these other systems that are, you know, trying to solve this problem.

37:55I still the agents sort of has two sides to it. One is you need to have the research. then this is the area of like if you go to if you're to walk in you know anthropic you to go to open ai like what is like the frontier like what are people really researching right now it's these long horizon you know agentic tasks that's like the thing that needs to be like solved and we're solving it variously through different methods of rl and content you know forever context so that's why like right now the hot hot thing in like the true ai model space is like infinite context length right like how could we because with the idea being that if we had infinite constant length, well, then maybe the agents can go on forever.

38:32But, you know, that's sort of like the technical thing that everyone's searching for. And the core bottleneck there is the fundamental technical operation of attention. So like attention, which is from the paper, attention is all you need. It's the core operation inside of the transformer. It scales quadratically with the size of the input. So as you have more and more and more context, the compute you need grows quadratically. So everyone in the technical space now is working on these sub-quadratic attention mechanisms. So attention mechanisms whose computational cost scales at least sub-quadratic.

39:06So not necessarily linear, but maybe like log n, n log n, something like that. So everyone's working on these. So there's the technical side that needs to be solved. But then even once you solve the technical side, like we talked previously about the harness, that's really like the question is where do they fit into the world as it exists today? Certainly we can have agents that run. but i think there's a difference between an agent that go does something for you which is like you tell claude go change this code and work to work on this that's just you know a sing an agent working on us on behalf of a single person's command will be even more interesting i think in the future is if you actually have these systems interacting with each other like agent to agent communication decentralized we are not far away from having an autonomous agent that has a task, which is to make money, whatever it is, and it figures out how to do it and what to do.

39:56And people spin these up all of the time. They'll spin themselves up eventually as well. And it becomes, yeah, well, that's an extraordinary world because then we've got new economic actors acting under different, whether it's profit motives or whatever motives they have. The question is, what is the edge there, right? What's the differentiator in that situation, right? So if everyone's using Claude Opus 4.5, it'll be interesting to see in that space. Well, that's why open source makes sense because different people can focus on different component parts for different parts of this, particularly in the agent space where there is high variability between tasks.

40:35Yeah, and then your edge, so to speak, is how you're able to take these open source models and actually tailor them to a specific modality. and that will be and it'll be interesting to see where that ends up because it's no longer that the people have said before already like the idea this is the age of the idea guy right like if you've got an idea you might be able to like instantiate that change in the world using these agents when previously your idea was infeasible because you weren't able to go get the employees get all the other things that are needed to like actually bring it about in the world yeah and also So we saw this whole kind of race in the financial world with high-frequency trading.

41:18It was another way where people realized that, okay, we can get an edge by doing a specific thing, which is latency. And if we can do latency plus a good model for trading prices, we do it to scale. And it spun up tons of different people, made a huge impact on financial markets. And we're going to see the same kind of thing because there'll be profit motives by training an agent to do certain things. So then there'll be a massive capital war of injecting money into those things. And what you actually end up driving is efficiency. Yeah. And, you know, companies like Jump, you know, which completely revolutionized the space.

41:51And in that, their edge is still sort of all in-house. Right. So it'll be interesting to see if we continue to see, like, what is the next generation of organizations that are spun up, that have the have whatever talent that is to be able to go solve problems? Is it more a McKinsey-style thing where you go to a place and say, oh, tell us what you want done and we'll get it done? Or is it more of like a jump thing where we're just going to try to hoard all the money into ourselves and be a firm like that? It'll be interesting to see which model wins out. Yeah, or whether agents themselves, because they're just going to end up being companies in their own right.

42:30But they only need to register as a company. It's this bizarre world where these AI agents are creating economic value themselves, capturing the value, spending it on whatever they spend on, compute or whatever else. It's bizarre. Yeah. What are the calories in that system, right? Compute, electricity. Yeah. But, you know, it's interesting because this brings about, you know, what are the second, third order social effects of something like that? You know, like it's difficult to predict and it's not worth often to try to prescribe the technology based on your imagination. Like, oh, well, we can't do this because of what, you know, this might happen, which might happen whenever you multiply probabilities.

43:10You know, things get small very quickly. But, you know, just sort of armchair thinking about what does the world look like where like large amounts of the economic activity have been replaced by autonomous by autonomous agents. It's just worth thinking about. Yeah, I mean, what I get to in all of that is we cannot compete on intelligence as humans. Correct. It's not possible and it will not be possible beyond probably this year. Yeah. That's dumb. So what can we do? The only thing we can do is actually be human. Yeah. Right. I just think of us as nodes of compute anyway, whether it's computing consciousness or whatever it may be.

43:46And human life experience is the thing that creates that compute. And so we just continue to do human things and there will be value to being human, I think. And, you know, it's interesting that all of these, you know, the AI systems that we put out, they put out words, you know, LOMs. Those words are only special in so far as they have meaning to us as humans. Right. So if you think about it from like a math perspective, there's nothing about the English, the English words that are like special that are coming out. It's only because we look at them and prescribe meaning to them within our own experience that it becomes valuable at all.

44:25So when we make these AI models, we aren't making them to be smart. They aren't making them to be smart, but there are completely separate languages, completely separate idea modalities that these AIs could have learned from in an alien world that would mean nothing to us. And it would be indistinguishable from random noise. Even if like the exact same computation was going on and it was threading this very difficult needle of reasoning or whatever you want to call it, the outputs could be completely incoherent to us. And we wouldn't recognize them or value them for anything. But that is going to happen.

44:56It probably will happen. Yes. They will use their own language that's more efficient, memetic pathways than than human language. I mean, there's no reason for them over time to not develop their own. Correct. Unless we as humans, you know, have some sort of forcing function that keeps them wanting to propagate the human mimetic institutions. Yeah, it can absorb it, but it doesn't. We can be input, but it doesn't. We don't have to be the full consumer of its output is the point. AI to AI can speak whatever language it creates that is more efficient. But when it gets input from us, it gets in. Oh, I got to talk human.

45:36I got to talk dumb human now. Yeah, that's right. So where go out a few years? We can't go out many years and all this because it's just too much. But where is the world? And where are you guys most research in that world? I think we'll continue to see in the in the next few years. I expect you to be wrong because everything's changing so fast. But so I'm not holding you to it. Yeah. It's just an interesting thought process. It really tells you for sure where it's going to be. If they really knew, you know, they would not be saying it. But my guess is in the next year, two years, you continue to see the endgame version of the current paradigm, right?

46:15So what's the endgame version of the current paradigm? You have the massive infrastructure build out at the nation state level, right? So you have to be able to build all the data centers and then also fabricate the chips, you know, in-house everything yourself. I think that from a Western perspective, the United States, we're doing a really good job on the building infrastructure side and obviously on the chip side. And our centralized players are doing a very good job. On the Chinese side, their infrastructure on the building side with the chips is behind. But on their centralized players, they're only maybe a little bit behind.

46:55but their open source players are actually even better than our open source, than the Western open source players. But I think we continue to see this build out over the next few years. And it'll eventually potentially end up with some sort of geopolitical situation surrounding the fabrication of how the chips and access to the materials that are needed. So I think on the macro side, that's how it looks like. on the tech side, I think you will continue to see lots of things get, people can use AI all over and it won't look any different from like the economic model at first. So like people are still going to have jobs.

47:38People are still going to go into the, like the world that you look at is not going to like look totally crazy different. But if you like peel the veneer underneath, you know, you're going to have, you already see it before. You have lawyers copying their legal arguments into the AI, which will then go to a judge, which is putting it into an AI. And how we sort of normalize that in society, I think, is something that will have to be dealt with. Because it's like you said before, previously, like even a year ago, you could say, well, you can't use AI to make these decisions because how can you?

48:08But like in a year, we're going to have these, like I said, even I had my own like aha moment with Opus 4.5 thinking more and more the people like it's almost like wrong not to use these models to do it. Right. Because like it was actually better at it than all of us. Like we can't like no one's going to want to play this game of like people always want to use the best thing, the fastest thing. You know, there's no way to like keep that, get that milk back into the carton once it's spilled. Right. So in situations where it's clearly incredibly better at almost everything, I think then you'll start to see, like, how are we going to organize this from a social perspective of using it to make more and more critical decisions within the pathways of people's everyday lives?

48:51And I think that's something that, you know, you've seen already. There's these like anti-AI movements, you know, these pause AI movements. That's going to be a big political movement. It's going to be a real thing, you know, and I think people underestimate, you know, when people read science fiction stories again, they see the science fiction stories always have that you open it up and on page one, it's like, oh, the world's like this. But to get to that point, people forget that, like, we had to go through everything before there. And at every stage before there, there's social things happening in the world that could change the direction of the technology itself to actually get to that point.

49:28And I think people are undervaluing what will happen over the next years as these technologies start to really infuse every aspect of life, up to it including the predictable and obvious backlash that will come from different segments of society. Yeah, and let's go into that backlash because it's interesting because I see the same thing. I see the accelerationists and the decelerationists, and that becomes the political struggle, not capital versus labor that was the traditional one, but it becomes this. and you can't if you have open source you can't stop it right so there's no way you can just go to say to anthropic and and uh open ai and google and stuff and meta and say listen you're not going to allow this or we're not going to allow you to go further because a china will do it Mm hmm.

50:19And because of open source, open source makes it impossible to shut down, which is why the Internet proliferated and crypto proliferated. That's great. But the unintended consequences are also we know how we have no fucking idea what we're building here. I think ultimately, yes, that is the idea that we hear. But like, I find it that the decelerationists are a bit disingenuous because their negative view is, you know, also just a fantasy, right? They're presuming to see the future and how this technology will work out. And I can definitely split the decelerationists into like the, you have like the climate focused ones, which like the energy.

51:05I ascribe very little weight to that because we've always, more demand has always led to increased efficiency, right? Like we only needed to get coal because wood wasn't good enough. We only needed to get nuclear because coal wasn't good enough, you know, and all these things. So whenever people are like, it's going to use up all the electricity, I'm like, perfect. That's going to be the thing that forces us to go find 100x brighter efficiency. Well, you can see Elon, he's moving on beyond Kardashev scale one to scale two. Yeah. If we didn't have AI systems, we probably would just sit around and burn all the oil that we have, right?

51:39It's the easiest, you know, people are going to take the easiest path we have. But what if all the oil in the world doesn't get you even near what you need, right? Then you're like, oh, shit, now I have to go solve nuclear. Now we have to go. And like ultimately, so to me, those things are, you know, very nebulous. The what about the future system? You know, what is it going to paperclip the world? All these other sorts of problems. The problem with that is, A, like you said, people are just going to do it anyway. Someone's just going to do it. So when you live in this world work like that, you know, you have two choices here.

52:08You can bury your head in the sand and do nothing about it or you take agency and try to solve it. And so that's what we do at Noose Research. And we said, we're going to try and solve it and we're going to build decentralized artificial intelligence that is human centric, puts human values into it. And we will do our best to create the best future of the world. And yeah, my final thought on this is obviously there's fear. People don't like change. Okay, I get that. Where I get to with the whole paperclip or is it going to kill us is it's like, would we kill all species on the planet? No. Why?

52:44Because they add some value to the global ecosystem that makes us. We couldn't exist without it. and you know again i think of all of these things as nodes of compute whether it's plants whether it's animals whether it's everything and they all add to this thing that creates humans that allows them to have knowledge we're kind of compression files of a bunch of other stuff that went before us this is just a compression file of human current knowledge it will change over time and build its own knowledge and it can't do without humans because without humans it doesn't get 8 billion people adding to its knowledge base in real time by experiencing life, writing about it, talking about it, and doing all the things.

53:26It would not make sense to do that yet. I mean, even when it gets to ASI, it still doesn't because that just becomes a network of nodes of AGI's that form into something big. It's all the same. It's all networks all the way up, all the way down. And to sort of, you know, at any moment, everyone in time has thought that their specific space and time is like the special privilege space and time. Right. And like for us to now, you know, it's kind of like the ultimate ladder pull. Right. To like say, all right now we're at the end. We're going to set the bar is like whatever we got right now is the true ideal of how human society is supposed to work.

53:59And we're not going to allow any progress. I mean, I said earlier about multiplying probabilities. Right. All of these situations about in the future are all about saying, well, if this, then that, then that, then that, then that. What we've broadly seen is what always happens if people optimize for their local minima, you create coordination systems where people optimizing for their local minima creates the global maxima for everyone. So as long as you get that system right, it solves itself from simple reproducing chemicals in a vat down by 600 ,000 years ago to complex multicellular life. All of it was local optimization of minima towards a global maxima.

54:36Yeah, it's a local coherence that forms larger networks of coherence, which forms the thing. And that's what we're working on. I love it. Brilliant. Anyway, that was a great conversation. Really enjoyed it. Really excited to see where you guys get to with all of this. It's going to be a hell of a few years. Yes, I agree. Newsresearch.com for anyone who's interested in learning more about what we do. And yeah, I really enjoyed the conversation. Fantastic. So look, another fascinating discussion and interview about where this is all going with AI. it's so hard to keep on top of all of the component parts the battles that are taking place who's doing what where but that's what we try and do here at the journeyman to make sure that nothing catches us by surprise and we understand where the world is going so anyway i'll see you next time you obviously enjoyed the episode because you're here with me at the end but listen don't forget to go to realvision.com forward slash join and grab a free membership it's an incredible community packed with alpha, great investment ideas, and the research that you need to help you unfuck your future.

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