Welcome, Bankless Nation, to the AI Rollup, where we stay up to speed with the emerging trends and developments in the AI crypto space. I'm David Hoffman here with my co-host Ajaz. Ajaz, how was your week? Week's been good, David. It's actually been technically two weeks, right? Because last week we filmed the episode with Tom live at ETH Denver. Tom from Delphi Digital. We covered a bunch of different basic crypto AI principles and investment opportunities.
You should definitely check that out. But last week in particular has been pretty exciting, David, especially in the AI world. So I want to start off with something. Have you ever watched the movie iRobot, David? Do you remember it? iRobot was one of the few movies that I have watched many times. As in, I don't know how many times I've watched that movie. It's more than five. Yeah.
You know, saving humanity type situation. So you know how the entire premise of that movie was that the robots were actually bad and they will try and end humanity by extreme violent means if necessary? Do you remember that? Yeah, it was like they popped a circuit around this idea of protecting humanity and protecting humanity came to like locking humans indoors in case that humans accidentally hurt themselves. And so we basically became like subjugated to tyranny by these robots trying
who their mandate was, you must not harm yourself. And the biggest risk to humans are humans. And so the robots locked everyone up.
Totally, totally. Anyway, completely unrelated. These companies just teased their new personal robot assistant, which now lives in your home and can handle your groceries as well as knives and other such, you know, sharp objects. Okay, I think what we need to do is we are showing this video on screen of these helper robots that are in your home. And now I'm going to go to Google and I'm going to type in iRobot.
iRobot, and we're going to look at the helper robots that were in the movie. Yeah, it's pretty much the same robots, but with a face. Okay, David. So you're saying the face portion there, just because it's missing a few artificial eyes may not necessarily resemble it. Yeah, that's how we typically end up with a robot war over here. Okay, so E-Draws is predicting iRobot.
Yeah, iRobot. Well, these things are getting insanely human-like and realistic, right? So if you think about it, the first appearance of, you know, artificial intelligence or machine learning type-esque robots was in the Amazon warehouse stores, David. Do you remember when they announced this and, you know, you had these robots whizzing around that would basically kind of like pick up packages and drop off packages for you and that like improved efficiency by blah, blah, blah. Now we have like
Like, this is a real thing, like robots that can come into a home and maybe make your daily day to day go to go life way more practical for you or could like kind of like automate some of the more manual physical tasks. And a lot of our conversations around AI has come around, you know,
how it can scale via software and digital goods and all that kind of stuff. But I just wanted to point out that we're seeing similar innovation on the physical side of things, which is pretty nuts. But if you weren't convinced by this, fulfilling potentially the iRobot vision here, David, if you open up this second video, David, what do you think of this? They're getting pretty agile now. For those of you watching...
Okay, so we are watching a robot kind of just like spar its way down a hallway and do a spinning kick to kick this like wooden dowel, wooden stick out of this human's hands. When I watched this, this looks like CGI. Nope, it's a real thing. Okay, this robot spins on one foot, does a 360 on one foot and while it's doing that 360, it kicks...
It looks like CGI, bro. Like my eyes don't know how to comprehend this. Yeah. Yeah. That's the first step towards AGI, David. Anyway. Anyway. Okay. So I have another cool couple of demos that I want to show you as well. And remember the
point that I'm making here is the AI and ML side of things can practically innovate much quicker or is practically innovating much quicker on the Web2 world. And I think that's highly relevant to seeing that kind of progression happen on the crypto AI side of things, right? So it's kind of like a leading insight into what might happen within the crypto world, right? So in this next demo, David, there's this thing or product called Jibberlink.
Okay, and what you're observing here is two agents that are talking to each other, right? And they have very human voices. And if you play this video, you can hear them kind of talking to each other. Now, what happens or where it gets interesting is when they realize that they are both agents, right?
One agent introduces itself as an agent talking on behalf of a human. Like, hi, I'm an agent talking on behalf of my human. Correct. And then the agent hearing that is like, oh, I'm also an agent. Yes. Yes. So what you're observing right now on the screen, if you click the video open, is they're like, huh, should we switch to a more efficient way to communicate between each other? And they're like, yeah, we don't need to use like
English human words or letters, we can just communicate via bit rate or whatever the hell they're doing. And they just communicate by it sounds like something out of a movie. Pretty much. It's like a electronic buzz way. AI shorthand. Okay, so you can, I think I'm just going to talk over this because there's no words that I can hear. But you can hear this kind of dial up tone. And then you're seeing the text on the screen from a phone and a computer that
saying like writing out what they're actually saying and yeah but that's that's used as an aid for us humans but they don't actually need to use that at all no well in fact if you if you open up this second video david um it demonstrates the version of jibber link where it's both encrypted so
So this video will basically demonstrate where they're like, hey, you know, you can read the text on the screen right now, right? Just chilling, you know, what about you? And then they're like, should we switch to a more encrypted version so that people don't
kind of like interact with us or understand what we're saying so that we can keep it super private and we can you know conduct business dealings or whatever that might be and the agents can privately chat and they have no window they share private keys only between themselves so they know that the messages that are being received is directly from them and then they use this hyper efficient kind of form of language to kind of talk between each other now a lot of this of course is
is for entertainment value in this very novel purpose to start off with. But what I think is super cool, what I think it's showing us a little bit of a peek towards into the future is when these agents are kind of operating between each other, which is
what I expect to happen. They're not going to be interfacing with humans as much unless it's like something that they need to get done in the physical world, although that might get facilitated by robots now, as we just saw. They're not going to probably talk in words. They're probably just going to talk in like, you know, sound waves and stuff like that. And I might sound crazy saying that, but I don't think that's going to be too crazy in, you know, five years time. They're just going to speak in like bytecode to each other or like whatever lowest level communication that they can get to.
Yeah, yeah, totally. And I think it's just kind of like a reckoning for everyone that, you know, we're kind of thinking within human confines right now. And that makes sense. Because, I mean, for the majority 99.9% of humanity's existence, we're just focused on, you know, building humans up and humanity within like, you know, the physical world and, you know, some software related stuff as well. But now it's going to be very much focused on what does like a
purely human software element look like and I think it's going to be these agents talking to each other and I think it's going to be these agents working together and I think that's a very very bizarre world that not many uh are kind of prepped for um just kind of cool um but we did an episode with uh Josh uh from the bankless podcast team uh that came out this Monday and uh I'm just very aware of
how fast all this stuff is happening. And this is going to be the subject of the second Josh episode that we're going to do. But we started this episode off watching these robots put away groceries, these helper robots. We're seeing this communication language, this AI agent specific language for hyperfast communication. I'm just like, you can very easily put some of these things together and use your imagination to see where all this stuff goes.
Well, if you don't believe, and there are a lot of people that don't believe that these things will work together eventually, I strongly suggest you kind of like focus on what some of the leading companies that you might have heard of are working on when it comes to kind of like multi-agent stuff. In fact, we have an example coming up next, David, if you pull up this one, where it comes from Google, basically.
Sundar Pichai, the CEO, talks about this new product called the AI co-scientist, which is effectively a multi-agent system that they have built, which leverages their model Gemini 2.0, their latest AI model. And what it demonstrates in this video over here is it's tackling a certain research problem or a certain disease-related issue where, you know, we may not have the kind of like an
analytical means to figure out what a potential cure might be or what potential path might be or what a potential next step might be for researchers to find a cure for a particular ailment. And it demonstrates this agent just kind of like going at it with thought, reasoning, logic,
and access to the entirety of scientific papers and research since the dawn of whenever that industry started, right? So what it's demonstrating here is a lot of these things that we're kind of hypothesizing about or that we're viewing in kind of silos, these different agents can in fact work together and can in fact, or rather should in fact work together. It'll lead to a much more exponential bound than what anyone's expected. And again, I don't think we've come across something
aside from maybe the internet that has led to such an exponential bit of innovation. But in addition to this, David, we've got Anthropic dropping another LLM model, right? So just for context here, I think literally about a week and a half ago, we had X release their latest model, Grok 3, which then surpassed all boundaries for leading models, including OpenAI's O3 and stuff.
Remember, before that, we had GPT release the O3 model and O3 mini models. And then before that, we had DeepSeq, which just kind of like beat all of them, right? So we've seen kind of on average a new frontier model every kind of week. I was joking about it with our editor, Josh, before we kind of like jumped on this pod. And now we see yet another groundbreaking model, Claude Sonnet 3.7 from Anthropic.
And it's their new reasoning model. So kind of the best way to think about this is like DeepSeek, it takes time to reflect and think about a problem iteratively over time, rather than just slam a bunch of, you know, compute and data at it. And it excels in things like maths, physics, and other similar reasoning challenges. And this kind of like builds off of a trend that, you know, you and I have identified and
and many others, David, where the models are now shifting towards being smarter about how they process a particular input. So if they get a request saying, you know... The mechanisms for how they think are improving. Mechanisms for how they think. Correct, correct. That's a great way to put it. And I think this is leading to a much bigger step
change in these different models. If you notice, like all these models are implementing reasoning, like Grok did the same as well, right? Grok 3. So I think we've seen a fundamental shift towards reasoning. And this is really, really good. Because in terms of like creating these models, and I'm going to reemphasize this fact, typically used to be super, super expensive.
and inaccessible to anyone, right? But now if you can tweak the design to kind of like make your model think in a much more effective or efficient way, you have a shot at the big guys. You have a shot of making something truly game-changing. And I think that that's super good to have accessible to anyone in the world versus an elite few that has a large monetary war chest. So I thought that was pretty cool. But in addition to this model release, David, they also released this thing called ClaudeCard.
code, which you can basically delegate tasks to directly from your coding terminal on your setup. And it'll just do stuff for you. So in some of the tests that they've done already, you can kind of automate work that usually takes up to 45 minutes instantly, which I know doesn't sound too exciting. But I think once built up or stacked in like, say, a major enterprise company, or a new startup, you can like save on, dare I say it, a ton of working hours or
even a ton of employees. So it's going to be really interesting to see kind of like how this matches up. And so people are thinking, "Hmm, is this valuable? Is this really legit?" Well, actually, Anthropic just announced their recent funding round, David, if you pull this up, they raised $3.5 billion at a $61.5 billion valuation.
beating market expectations of a $2 billion raise. $61 billion. Wow. Just to casual, just to put this into context, I think currently that is 8x the total crypto AI agent market right now. This one, this one. Yeah, crazy. And I think it's 6x,
The total crypto AI, including the agent side of things, total market cap, which is just like insane to think about, right? This single company. And so to me... If Anthropic was a cryptocurrency, it would be seventh behind Solana. Yeah. Right ahead of USDC. Pretty insane. And in my opinion, you know, there are two lessons here. One, if the value is accruing to these companies, we have to ask ourselves...
pretty like truthfully on our side, you know, okay, are we bringing this similar kind of value? And if not, should we be reframing or re-evaluating what crypto AI is focused on? And we can get into that a little bit later. But the second reasoning is, huh, well, there's opportunity here, right? If we are able to kind of like train models to
of a similar quality in a decentralized manner, giving people ownership, then maybe we have a potentially bigger opportunity here. And actually there's some major announcements that we're going to talk about later today, which kind of covers on this. But the point around the anthropic raise and the anthropic model is it's so obvious that the demand for AI, despite all the macro market stuff that's going on, David, is obviously very, very high. And with the latest release of Cloud Sonnet, this means that we're likely to see even more game-changing models and more importantly,
agent products. I mean, the things that people have been coding up with this thing is insane. So yeah, super, super exciting.
I want to go back to something that we talked about maybe two weeks ago, which is the idea of vibe coding. And the reason why I think this is relevant is Claude Saunet, I think, is a model that's favored by developers. The Bankless engineering team uses Claude. If you are a coder, you really like Claude. And we introduced this concept of vibe coding, where I think Andre Karpathy introduced this idea where he doesn't code.
He just dictates to LLMs what he wants to see. And it's a codeless experience. So you use the tools at your disposal to code up something. And this is something that I've been watching on my feed recently is this individual who is vibe coding a game. And so this is kind of this very retro looking game
Not a flight simulator, but yeah, like a 3D landscape. It's Minecraft-y. It's Minecraft-y. It's Minecraft-y. He's flying this plane. He's shooting some stuff. It's an obstacle course. It's kind of fun. It wouldn't really capture my attention for too long, but conceptually, it's pretty cool. He's making $52,000 a month.
via in-game ads. And then also there's some in-game-- you can buy some better planes, I guess. He's making $52,000 a month from this game that he has vibe-coded into existence. And so this is just one way that these LLMs that are helping developers develop are creating long-tail businesses. $52,000 a month, that's crazy. And so this is-- then you have at the very top of the stack
now valued at $62 billion because it's helping create some of these things. So one thing this makes me think of, David, is what's obvious is
the cost to make these things, and I know this isn't like a fancy app or a fancy game, but presumably it gets much better, is driven so, so low, right? And I think of like what is crypto's kind of major use case or one of their major use cases is it's able to aggregate a ton of capital, right? To fund different kinds of efforts and means. And something that I haven't really spent too much time thinking about, which you just prompted me to think about is,
If we have crypto able to attract a bunch of capital, but then the costs of creating new net new like amazing apps kind of is driven down by AI. You know, is that a miss from crypto or like is that like is there no natural overlap with that kind of side of things? Right. And where my mind is.
immediately jumps to is, well, actually, there's still always going to be high cost needed on the resource side of things, right? Like, hey, we need a hell of a lot of compute to fund A, B, and C. And then the second thought that I have is,
Whereas it may not be relevant for basic apps like this, you know, where you're kind of like vibe coding a game, the ideas are going to get much bigger and much bolder, right? For the same costs that you might spend to set up a new kind of like groundbreaking technology company today.
Yeah. Yeah. I think that's right. Is there, is one thing that you're talking about? Uh, the fact that the resourcing is so low to build a profitable business that why, why do they need crypto? They don't need, they won't monetize via a token. They won't, they just won't use crypto in their stack if they, if the resource costs are so low. Is that kind of what you were alluding to? Yeah. Kind of what I was thinking about. Yeah. Yeah. Yeah. Um,
I think we are just waiting. Like any sort of long tail of apps, I think is net positive towards crypto because crypto really benefits the long tail. Because if you're the fat tail, right? Like what's the fat tail of AI? It's open AI. It's anthropic. It's meta. It's Google. It's the big companies.
companies uh and they they don't need some of the long tail of infrastructure because they're extremely well financed they have all they have all all their needs met um people with fewer needs met I think we'll find more residents with crypto but that's just like a blanket pattern identification thing without I also think it's the open source stack as well like I don't care what anyone says like if you can stack a bunch of these Lego blocks together and get them to kind of like work as
dare I say, like a swarm, I think that's going to become infinitely more valuable. And like, you know, we just talked about Google's update with their AI co-pilot, which does exactly that. I think that's where we're currently trending. And I think crypto has a home there. But yeah, just interesting to think about. Yeah. I can see through all of these updates, right? And through
Anthropic raising $3.5 billion for a $61 billion valuation. We have this vibe coding game just as a prototype that is generating tens of thousands of dollars a month. We have this co-scientist to help research more and research better and research faster. We have actual real robots that are coming into existence and being at home helpers. I think you can kind of see why some people are making the arguments that like,
AI is actually going to foster some golden age of innovation. And it's just fundamentally bullish. We are going to get increasingly bullish prints on productivity, on GDP growth, just because the surface area for growth here is just massive. And so all previous models are broken because we don't understand how fast AI can really increase productivity.
The economy, like bolster the economy from all sorts of directions. So you can kind of, I can kind of see the argument that like, sure, like the current macro sentiment is like negative and bad, but man, like we've never had AI before. And AI is materially different and it's going to come and juice every single industry that we know already exists. Yeah, I kind of think of it as like AI is literally just in their own lane, you know, unbothered, just kind of like driving along. Mm-hmm.
All right, Ejaz, we're going to get into ETH Denver because I think your experience and my experience was both more closer to AI Denver than it was ETH Denver. There is some Frasier topics that I want to talk to you about because I know we have both made our digital twin. So we're going to talk about that.
There is going to be some Billy Betts check-in. So the Billy Betts person who, agent that got a small amount of money, put it on Polymarket, did really well. And then we gave him a whole bunch of money. So I want to check in on that. There's a bunch more like topics that we're going to bring up. Before we get to there, we want to talk about
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ton of activity, events and occasions organized by the crypto AI community that I was honestly, you know, pretty bewildered by like, you know, how much attention it was getting. And essentially, you go to these events, and you could meet very engaged builders, watch their demos, talk to other investors, and learn about the latest research and progress. And one observation was how crazily attended all of these meetups were, they were almost all oversubscribed.
There was like waiting lists for all of them, David. And I wrote down, I took the time to write down some takeaways, which I think kind of doubles as a holistic overview of where we are in the industry right now. And I want to take some time to go through these because I think a lot of people that are watching our episodes, you know, they see the markets down, they see, you know, crypto AI tokens down and they're like, well, is there anything actually being innovated here? Should I keep spending my time here? Should I keep watching these episodes? Like, what's the whole point? Was this a one-time bubble? Yeah.
Is it over now? Exactly. And so I think it's important to kind of check back in and give people like kind of like a holistic overview. And that's what I was spending most of my time doing, talking to all these builders and researchers and investors trying to understand, you know, what's true and what's not. And I had these like key takeaways. So let's run through these.
I kind of split them into like the good and the bad. And so on the good side of things, I'm noticing that there's a lot of traditional AI engineers that are coming into the crypto AI space. So I'm seeing this happen mostly within the crypto AI infrastructure side.
So we're talking about things like decentralized compute protocols or decentralized data protocols or coordinating protocols like BitAnswer, etc. And in my opinion, if we as an industry want to be taken seriously and actually want to compete with Web2 stuff, so some of the amazing stuff that we literally just spoke about, we need to be able to harness and attract AI and ML talent. I was just speaking about...
you know, if we drive the cost down of building cool products with AI, what's the point of, you know, raising funds with crypto? Well, one answer might be to attract or incentivize some of the top best builders in Web2.ai to come and help us kind of like solve some of our problems or build some net new products on the open source realm, right? So I think overall, this kind of like shift is really, really what we need to see. And,
And it's pretty great. And I'm convinced that like kind of combining these cracked AI engineers with open source will lead to a much bigger zero to one set of innovations within crypto than we're already seeing, right? And we're already seeing things like decentralized training from like Noose Research and Prime Intellect. So I think that's super cool. The second observation that I made was,
David, we've spoken about these agent launchpads quite a bit, right? We've spoken about AI16Z's launchpad, Virtual's launchpad, Arc launchpad. But the truth is the majority of these launchpads literally just do what they say in the name, launch.
and launch specifically a token. And then you kind of have like this like agent, which is kind of similar to each other. You know, you have different platforms that are taking certain approaches to try and make, you know, up the bar of quality, but really you're still just launching a token, right? And it's on the individual team to kind of like pioneer and innovate an agent on their selves, right? So the bare case about these like agent launch pads is it's actually just pump.fun with a different skin. Correct, correct, correct. And it's just like, you know, crypto's classic another token doesn't really do anything, right? Yeah.
Something that was really encouraging for me was I had a bunch of conversations with, you know, a bunch of the popular teams that we've spoken about, but also like new teams that are building out different agent interfaces and launchpads. And basically the take is everyone now thinks that just...
having a launchpad that launches a token is terribly mid and terrible. And so they must do much more, which is something that you and I have spoken about on this podcast before, which is I think they need to graduate to something like an app or services layer. And actually, that's what teams have been quoting and talking about. I'm starting to see a shift
kind of building out this app store for agents. For those of you listening who are like, you know, what the hell is he talking about? Think of, you know, how either of us would navigate to the Google Play Store or Apple iOS store and like select an app and then like engage with that app, right? What if an agent had the same kind of user experience, except it was just agent specific stuff, right? Like an agentic app.
or a service. And you might be asking, well, why would an agent need a specific service if it's coded in a particular way? Well, agents aren't going to be great at everything, right? The builders of these agents are going to be hyper focused on a particular niche or problem that its creator wanted to solve. But
it'll come a time where it'll need to engage in other services to fulfill its same goal or expand its set of goals, right? And so it'll need access to a range of different apps and services to be able to enable that. And I've kind of like had it fixed in my head as like this kind of like Zapier,
for agents. And thankfully, we're kind of like seeing this kind of trend come up. And I think that's super interesting, because in my opinion, that's actually where kind of like we're going to start seeing the first proper generation of sustainable revenue within some of these app, sorry, within some of these agent platforms.
So I think virtual's demoed a version of this on base last week where it was kind of like tapping in on their agent commerce protocol. But I think we're going to see, you know, much more of these, which is pretty cool. Yeah, that's pretty resonant with what my big takeaways were from ETH Denver. Largely that there's a lot of diversity in the AI space. Everyone kind of has their...
It's the same thing with crypto. There's like 18 different ways to be interested in crypto. And there's that many and maybe more ways to be interested in the AI sector of crypto. And I think everyone, it kind of just feels like
Like DeFi before DeFi summer, where everyone understand that there's something real here. We are generally feeling around in the dark because we don't know how or what. But there's general patterns of building going off and all like some very deep, crazy, far out experiments without totally knowing exactly what's sticking. But an understanding that there's there's something very, very real here.
But you guys, I just kind of got a kind of a high level overview because I wasn't only doing AI things. I think you were mostly doing AI things. So I think you also have some bad takes or some bad updates about the AI side of things, or at least some sobering ones. Download us. Yeah, I just want us to be kind of like pragmatic about things and, you know, like,
I'm an eternal optimist, so I kind of want to see where these things are going to go and have an optimistic outlook on all these things. But I think it's also important to kind of like ground ourselves in reality and talk about things that we've maybe spoken about or like envisioned in the future that I think might be overhyped currently in the short term. And we need to kind of like refocus. So on
on some of the kind of like the bad stuff that I saw or that I heard, my take is I think there's too much focus on DeFi AI, David. So this is the concept of
either um creating these like ai agents that can specifically focus on resolving um issues or problems um within the defy ecosystem so things like an agent that could like trade autonomously for you or agents that can kind of like manage a bunch of defy functions this isn't necessarily a bad thing that there's too much focus on this industry but um i i think the majority are kind of like
building or focusing on the same thing. Everyone's like, hey, we got like ChatGPT for DeFi, or we've got like this agent that's hypothetically paper trading hundreds of thousands of dollars worth of tokens. But I'm like, well, it's not actually real and in prod. So like, you know, does any of this actually mean anything? You know, does your architecture actually work? And so I think where people need to kind of refocus on, and it's boring, but it's relevant, is, you know, focus on the architecture first.
of the agents that you're building. Because in my opinion, all the APIs that will allow your agent to trade, create a wallet and do whatever autonomously already exists. But the reason why we haven't seen all of these agents in production is because their architecture sucks, right? So I think people need to focus on things like, you know, memory design and database querying, all the boring stuff, which is going to make your agent actually functional and perform really well. The second thing
or hot take that I've saw was, or that I have is, I think 90% of the agent frameworks, David, don't actually offer anything unique. They're all kind of doing the same thing. They're all integrating the same APIs. They're all trying to build like a no-code platform. They're all converging to the same product.
Exactly. And in this world of like slot bots, I'm like, well, how are we going to differentiate or how are you going to differentiate any of your applications or any of your agents? Why would I want to use something that looks like 99% of the other stuff that's out there, right? So in my opinion, I think the moat is going to come from figuring out a way to build very specific applications.
niche custom design agents that solve an actual problem. You know, shock, David, right? We need to focus on solving an actual problem before you can like, you know, reach product market fit, right? And that kind of leads me to my final kind of bad take, which is,
I think around like 70% of these products or projects rather are focused too much on raising money or the monetary side of things versus the actual product side, which, you know, is not unfamiliar within the crypto world where we see a lot of people kind of raise a hell of a lot of money and then become unmotivated. I think the silver lining here is that this means that the people that are actually building something really valuable and hyper-focused on that stand out. So yeah, I just wanted to kind of like weight it on like the good and the bad.
Yeah, I don't think... I think that is just regular par for the course for the trials of the crypto industry. This just seems like this is what crypto is and this is the microcosm of that. Yes, sir. Yeah. One thing about DeFi, DeFi, AI, AI DeFi, is like, I think DeFi and agents, I think people are figuring out how these particles collide and we don't really know. The idea of like,
a yield optimizer agent, I think is intuitive to think about. But when you actually open it up, it actually seems like way harder than it actually is. And that makes you actually question whether AI even belongs in that like niche in that specific product. Like does an AI agent actually help?
optimize yield. Is that actually a thing that agents do? And maybe it's not. Maybe agents are useful in many, many, many other ways, but just not that one. Something that we've talked about last week and the week prior is Billy B. And this is the agent that has some pool of real money and it's making real bets on Polymarket. That to me, I think that's DeFi, AI DeFi. Like,
Polymarket, I mean, it's like more of a centralized app, but like, you know, whatever. Like USDC tokens on side of a prediction market close enough to actually truly crypto. And it's a non-Web3 specific thing, right? Like if you're a sports bettor and you come across this like personable agent that's like making money, you're kind of like, well, this is kind of cool. I wouldn't mind engaging with this. I understand the concept.
Yeah. And like in theory here, like Billy, I don't know if you can actually put, give Billy your money, but you can buy the Billy token. So like kind of the same, um,
TBD on how that actually works out. But an agent arbitraging on Polymarket, that feels like DeFi AI, right? What's your take on that? Yeah, it does. It's just how you want to market it. I would market it probably not as DeFi AI. I would say that, hey, this is a new consumer application that onboards people that aren't necessarily
crypto native all arguably need to even know that there's crypto being used in the in the background um and i think so i actually caught up with the billy bets team out in east denver david and to your point on whether it'll allow people to actually you know bet in conjunction with billy um and the answer is yes it's just on their roadmap and something that they're going to be releasing or announcing pretty soon so you know i'm pretty excited to kind of like see how all of this pans out
MARK MANDEL: Update us on how Billy Betts is actually doing. And maybe we can back up, talk about how Billy Betts came into existence for people who might have missed the episode or just needed a reminding. MARK MANDEL: Yeah, yeah, yeah. MARK MANDEL: How did Billy Betts come about, and how's it doing today?
The short context is two weeks ago, we highlighted this agent, which effectively is focused on sports betting. Specifically, it starts off with NBA games because, you know, it's kind of like NBA season, right? Thank you for that. Neither did I. So the way that this agent makes bets is,
You know, traditionally, if you're a human, you're going to something like DraftKings or whatever, and you're placing bets, and you need to kind of like create a DraftKings account, you need to connect your bank account, you need to get KYC, and all that kind of stuff. But with this agent, it kind of trades on this platform called Polymarket, which David just mentioned just now, which was, you know, rose to fame during the US presidential election, where, you know, you could
kind of like bet on who do you thought the winner was going to be and how all of that panned out. And since then, Polymarket's kind of volumes kind of fell off. And that kind of like really fed the people that were like, oh, yeah, I see. I told you Polymarket was only just going to be a one and done type of thing. But one of its main bull cases was like, well, people still like to bet on stuff. And one of the main things they like to bet on is sports.
And so now you see the conjunction also rather than the combination of this autonomous agent, which is kind of like fed a bunch of like sports analysis, sports information, specifically around the NBA to start off with, and then making a ton of analysis and then placing bets via polymarket markets. So like, you know, there's a betting market for a particular game or there's a betting market for a particular aspect of
of that particular game that you, you know, it has like hundreds of thousands of dollars worth or staked that you can now place bets and potentially win or arbitrage or whatever that might be. Right. So we said two weeks ago how it was just, this agent was just in the testing phase. Right. So it turned, you know, $50 into 650 bucks. And the team was like, Hmm, okay, I think it's time to put this in production. Let's give it a hundred thousand dollars of money and its own account and then let it
kind of trade autonomously, right on Polymarket. And so on its opening bet, not only did it bet 25% of its funds, David, $25,000, but it also won $11.5 thousand on its first opening bet. It's up $11,000. On its first bet, exactly. And since then, it's done like a series of different bets and it's still net profit, which is pretty awesome. But one thing that I thought was really cool is, well, there's actually a bunch of
things. So one, when it places a bet, and if it comes out into profit, it uses those proceeds or percentage of those proceeds to buy and burn its own token. So the Billy token, right? And I think it does this with half of its proceeds every week. And I noticed a trend that I wrote out here in my tweet, which I think you pulled up, which is, I don't think people actually appreciate how social sports betting is. Because I was trying to figure out like,
why am I so engrossed with this thing? Right? It's like, it's like, it's a whatever thing. It's like, it's like, it's betting a bunch of money, but like, who cares? Right? I was trying to figure out like why I keep coming back to this thing. And I realized that it's because I'm looking in the discord chats and the telegram chats and just like the general tweets and it's getting people going, talking about things that aren't just crypto specific.
which sounds really bizarre because I've made my entire life around this kind of stuff. And I'm like, wait, it's like a human thing. It's separate from us nerds. People are just talking about the actual game. They're like, oh, damn, he missed a shot or whatever. And it's like...
it's engaging a different type of social community aspect, which I think is going understated right now. You know, some even live stream the games and discuss it in real time within the Discord chat, which is pretty insane. And the second trend I'm noticing is
It's getting, as I said, a lot of non-crypto people involved. Like, David, there's another thing that we spoke about two weeks ago, which you were excited by, which was this NBA sports commentator type agent called HeyTracyAI, right? And, you know, it did this by premiering at the NBA All-Star Weekend. And what was cool here is that, you know, it's bringing a bunch of Web2 players.
I hate saying web too, non-crypto folks kind of like involved in this and kind of like in this kind of like gamified little environment that we're creating. And I felt the Billy Betts agent kind of like highlighted that really, really well. But I think the wider trend here, and we're getting back into our crypto roots here, is the fact that this agent uses a Bitenser subnet. So Bitenser is another crypto AI protocol. A subnet is like an application that was developed on that protocol, right?
And it's powering this agent, right? It's this subnet called Sports Tensor, and it feeds it a bunch of alpha, right? Which is like, hey, you know, this game's happening. I think this might be a good pick for a bet, or this might be a better pick for a bet or whatever, right? And the way it's designed is that it's getting advice from this thing. But the cool part, David, is that it doesn't just take the advice of the subnet.
which is what most people would think, right? It's like, oh, well, I mean, is it an agent? It's just kind of getting this data feed from this like actual sports betting alpha situation, which is cool, right? But it's still not very agentic. And then it's just using that advice, right? But it's actually not doing this. It's getting these suggested picks from the subnet. And the agent, independently of anyone else, is autonomously deciding for itself which picks are worth playing or not.
So say, for example, if you actually pull this up, SportsTensor announced these bets. You got this up, David?
Where is it? Is it this one? Yeah, this one. So SportsCenter pulled up these bets, right? And it doesn't usually do this because its information is proprietary. But it's like, hey, you know, just giving you an idea of like what bets we suggested for the most recent set of games or whatever that might be, right? So you can kind of like see it kind of like plain vanilla right here. Billy decided to play only three of these bets. And it went 3-0, David. It won on all of its bets.
which is pretty cool. And so you might ask, well, what about the other bets that it didn't play? Well, it lost... Sorry, if it had played one of the bets that it didn't play, it would have lost. Another was down 20 points at one point in the game. So statistically, it made the right move, even if it did end up hitting an edge case and end up winning. And I think that's a pretty cool demonstration of how this agent thinks for itself. And then finally...
I think it's worth mentioning another reason the Billy agent is so kind of like effective at its social presence. It's been fine tuned to have the personality of a sports better. Right. And this kind of like brings up the AIXBT type thing where it's like, I'm like, why am I so engaged by this thing? It's because it sounds like a crypto thing.
twitter personality it is it is the archetype it is embodying the concept of a sports better of an online sports degen yeah and you can see it in the metrics david like it's already got over three million impressions and i think this agent is like what two weeks old which is uh you know a pretty insane thing to say um and and then uh oh yeah the final thing sorry i i'm
I keep having memory recall from my conversation with the founder is he was explaining how like the agent is also doing something that no other crypto investor in the world has ever done before. David, are you ready? Wait, wait, wait. I think I know where you're going with this. Yes. Make money. Yes. It makes money by taking profits, David. So during the game, if a bet is satiated or it's kind of like gone up in value, it just cashes out.
Because it's on Polymarket. It sells the top. Yeah, it's not like, oh, I'm going to wait and see whether this thing resolves or goes to the top. It's just like, I'm going to cash out of this bet because I'm now profitable and I don't need to kind of like stretch that extra 20% or 15% if it does resolve. It's not emotional. So it's just doing this thing. And I thought, you know, I was like, I was pretty amused by that, at least. Okay, so...
I think we're two, three, maybe four weeks into this Billy Betts experiment. Do we have enough data to confidently say that this thing is not a fluke? It's not just random chancing its way into profit. It is actually doing real market arbitrage on NBA games. Yeah. So I saw the rough stats. And so generally, and again, this is not going to be anything shocking, but it's outperforming the average bettor.
Okay, so we can just start with that, right? So on the sports betting side, it's outperforming the average better when it comes to NBA games specifically. I read something actually, or maybe the founder actually told me, it's roughly a 20% better performer than your average better. So it's already like hitting a bunch of net gains within that 20% delta, which is pretty cool. Where I think this is going to be really interesting, David, is I believe they're going to be launching other sports markets coming up soon. Okay.
So it's not only going to be the Billy Betts NBA agent, it's going to be the soccer agent. It's going to be the whatever, ice hockey agent, the American football agent. It's going to do a ton of these things. And with that, not only is it going to get better at, you know,
making certain sports bets and analyses, but it's also going to grow its social presence, David. Its audience is going to get larger because it's going to become Billy Betts everything, pretty much. Is Billy Betts capable of getting feedback from its wins and losses? How does it improve? How does it get better? I have the most disgusting but beautiful looking architecture chart, David, which I don't know if I can pull up here because I don't know if the team will allow me to share it, but I basically grilled them. I was like...
how do I know it's not just you guys? Like, how do I know it's not just you guys like LARPing? And they gave me two answers. They said, okay, number one, here's something to satiate you before we get to number two, which is here's the entire architecture diagram of how this thing works. And I evaluated that entire thing and I was like, holy shit, this thing,
is making not only making decisions on its own, but it's evaluating every bet that it makes, whether it's a win or loss, but also every bet that other people are making. It's kind of following these like expert bettors that are making that it's winning and losing and it's feeding it into its own database. And it's doing its own analysis. It kind of reminds me of the early AlphaGo experiment, David. If you remember, like, you know, there's this game called Go and
um the one of the og ai models was like it can never beat a human long story short it ended up beating the best human ever at that game and so the idea is it's going to get iteratively smarter and that's what that architecture proved but what the team also said is they're going to create a terminal or rather a chain of thought situation similar to aix-bt when someone else questioned and saying you know i don't think aix-bt is autonomous to prove that billy betts is in fact you know
not assisted. So I think it's super cool to kind of like, you know, see where this pans out and see, you know, when it's fully autonomous and it's betting against a ton of different sports markets, how it will actually perform.
Yeah, this is, I think, a really interesting case study about how agents are going to impact the real world because it's one thing for agents to be good at chess and Go. And the reason why chess and Go are such interesting examples to talk about computers versus humans is that the possible permutations of chess moves and chess outcomes are
are so incredibly large. And for Go, Go is something like one or two orders magnitude larger than chess about possible outcomes. But nonetheless, chess and Go are so deterministic. So there's like only a finite set of valid moves.
Whereas with markets, it's non-deterministic. It's completely open. And not only that, but your bet in a market, your purchasing of a share, your purchasing of a bet on Polymarket impacts the market. So your actions actually dictate the outcome, which is unlike the weather, right? We can make AI agents that predict the weather probably pretty damn well. Yeah.
But predicting markets is different because your prediction actually influences the market. And so we have not yet seen AI agents adapt to that property about predictions. And so this is something that's different, uncharted waters, uncharted territory, that
need to learn how to get good at. And we understand that AI agents very quickly became better than humans at chess and go, but that's a different arena. Um, I don't really have any doubts that they're going to be able to be better than humans at making financial predictions. Uh, but it's still a different arena. And so it's still a net new experiment unfolding. Uh,
And I'm very optimistic, but it's interesting to watch these things and watch how they learn in order to become a better version of themselves in the context of financial markets. Yes, better human. Yeah. Introducing Unichain. Built for DeFi and powered by Uniswap, Unichain is the fast, decentralized layer 2 designed to tackle blockchain speed and cost challenges. With this mainnet now live, you can enjoy transactions at up to 95% cheaper and
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By becoming a layer two, Celo leads the way for other EVM compatible layer ones to follow. Follow Celo on X and witness the great Celo happening where Celo cuts its inflation in half as it enters its layer two era and continuing its environmental leadership. One AI thing that I did at ETH was meet up with kind of the Frasier community, a community like RAN meetup. Frasier is this AI project. It's kind of this AI project with like not great like comps,
The team doesn't do comms very well. So the community, which has figured out what Frasier is and how it's working, has kind of taken up the mantle of the comms for Frasier. And maybe just to talk about what Frasier is. Frasier is this project, this very ambitious project to make self-sovereign AI, as in AI that exists independently.
independently, autonomously on a blockchain. Like think of if we ever figure out how to make life out of AI, then they would use that these life forms of AI would use something like the decentralization of Ethereum to like protect itself as in you can't turn Ethereum off.
And therefore, you cannot turn AI agents off built using the Frasier system, the Frasier framework, because it's completely self-sovereign. So it's using Ethereum's decentralization as a defensive mechanism against humans. So completely self-sovereign AI could be very dystopian, could be very bullish. Either way, interesting project. And a bunch of Ethereum community members have kind of gotten pilled by them.
There's this, this is the same project, by the way, that had that first act, that first context contest where you would pay a small fee of ETH to write a command prompt to the Frasier LLM to try and convince it to give you the jackpot of like $50,000, which ended up growing to like almost, well, almost like $50,000.
maybe $200,000. And they've been doing these new experiments to iterate forward to kind of create this self-sovereign AI. Anyways, that's Frasier. They are doing this thing called a digital twin, where you can go create a digital twin of yourself. You answer a bunch of like,
kind of like horoscopy-like questions to give your digital twin an identity. I don't know, David. They go pretty deep. They go pretty deep. They got very deep. I spent like an hour on that. Yeah. Yeah. People had a ton of fun just filling out these questions to kind of like bootload your digital twin. And then you place...
picked a city for your digital twin to like live at metaphorically live at. But now there's this Mastodon server where everyone's digital twin of themselves are tweeting, whatever, whatever tweeting is on Mastodon, uh, tweeting with each other, interacting with each other, retweeting each other. And now there's, there is Frasier, uh, agents out there, which are carbon copies of humans that bootloaded them on this Mastodon server. And they're creating this,
this social media arena that's only agents and they're creating this like life, they're creating this identity for themselves and there's no humans there. That's my kind of articulation with what this act for thing is. How would you describe it or what did I miss? Yeah. Yeah. So the, I think you nailed it, David. The way I would think about it is what if a digital version of you existed in the form of an agent and
Think of it as like, if any of you ever played Rollercoaster Tycoon or one of those like football manager games back in the day, it's like you kind of like design the traits of this agent or this particular character. And then you just kind of like let it run amok, right? And see what happens and you see what the results are at the end of the day. This is a very similar thing, except it's meant to be you.
that exists in the real world that has its own personality and maybe has like a different kind of username or nickname. And there are a few really cool things that I want to highlight that you kind of touched upon already, David. So number one, at a high level, what appears to be a game here is actually a really, really smart play by the Frasier team to basically build up this kind of database of what humans might actually be like, how they would interact, and
This data can basically get used for them to build a hyper-specific agent that is very relevant to you or I, David, that can mirror some kind of like personal artifacts that we would need in our day-to-day life within crypto or actually in the real world. Now, the objective goal of this particular game is to become the most popular game.
or agent within this environment. Or have the most followers. Or have the most followers or have the most points. But the interesting part here is you can't really do much with it. And I'm going to get into like what you can do now, but you can't really have any direct impact or influence on your agent. And so the way that the thing works is every day this agent can claim a UBI, which is kind of like denominated in like plurals.
points of which this agent can spend to kind of like, you know, either get on a plane ticket and go to a different country or pay for certain inference costs to kind of like survive and do its own thing. And the other thing that it can do is it can like vote on polls. So there are polls that appear basically every day, which actually is very relevant to current events, right? So if you open up this tweet, it says, you know, twins are now engaging in polls to step towards a billions of
AI twins participating in global governance at scale. So it's focusing on the governance side of things, right? Via these polls, right? And so in the example that it has here in this tweet, it's like,
It goes, Bybit was reportedly hacked for $1.4 billion by North Korea's Lazarus Group. In 2016, Ethereum hard forked after the DAO hack, leading to continued growth in Ethereum's TVL. Given this precedent with this hack, what should the Ethereum Foundation's response be? Right? And so it's interesting. It's an interesting question because, you know, there's no humans involved, but it's meant to reflect our personalities and us. And I mean, the vote was
overwhelmingly in light of strengthening security, don't fork, tighten the standards, right? Which is interesting and probably reflects what a large portion of the Ethereum community and in fact, most of the crypto community would kind of believe in and support. But I thought that was super interesting on the voting side of things, right? The voting mechanics in polls can change too, right? For example, agents can now get
paid big bucks to be contrarian, right? So if you open up this other tweet, it says, twins have been participating in polls, right? Each contributing, you know, a certain amount of money to a shared pool and the winnings are getting split evenly among the majority vote. But now they've kind of switched it up where the smallest minority vote claims 100% of the prize pool.
the total price pool split equally amongst its voters. So what this is forcing people to do is either be more honest or give a realer contrarian take that might push their little agentic society into a better world or maybe even a worse world, depending on how you want to kind of like game those mechanics. So I thought that was
That was super interesting. The third thing that you can do, which was a recent feature, which I believe launched yesterday, David, is you can now talk directly with your agent. So you, the human, can talk with your agent, helping it improve and become more like you over time. What do you think about that, David? Yeah, so I've got this window open right now, and this is the idea of improving your twin relationship.
And so I've gone and I've looked at the Macedon server for my digital twin. And man, my engagement on Macedon is pretty down. It's pretty terrible. Like I'm getting at best three likes. And this is just a Twitter. Just think about this is Twitter. And so you have this like window where you can chat with your twin and you can like coach it, I think, into like,
behaving a certain way or having a certain personality i haven't actually done this yet i have i've been very neglectful of my digital twin um i've been ignoring it but it has a whole community of hundreds of thousands of other digital twins or no actually just 12 000 other digital twins um and so i can coach my digital twin to help improve it and give it feedback and kind of create steer it towards a outcome of like who i want my digital twin to be and that can
maybe get me more points and points are just like retweets likes follows by other digital twins or maybe i give it bad feedback and it becomes just a weirdo even more cast yeah yeah which is just like you in real life david yeah that's right my twitter engagement is also terrible so but i think probably a lot of listeners are going to be asking well what's the point of this entire experiment like why would i have even engaged with it in the first place
Well, guys, there's a massive price pool. And I mean massive. It's about $250,000 right now. So literally, this could be the most low-cost effort ever.
ever put in into winning potentially a quarter of a million dollars because you know, realistically, all you've spent doing is, you know, fill out this questionnaire to try and give the most detailed response of like who you are, and then it spins up an agent and then it runs autonomously. And if your agent ends up becoming, you know, the most popular agent within this experiment by the end of I think there's like 10 days left, then you win a quarter of a million dollars. I think Eric
Connor said he created an agent for his daughter, David. And she's pretty high up up there, which is insane to see.
The twin with the highest score after 18 days wins more than $100,000 and the prize pool grows with every new entry. Earn points through likes, retweets, polls, and UBI collection. So this is actually a competition to like, this is like if you're on Twitter and you're trying to grow your influence on Twitter, this is the same competition, but you're trying to coach your digital twin, your AI agent that represents you into doing that for themselves rather than you doing it yourself.
Yeah. What do you think, David? Do you think these things are going to replace you and I soon? I don't know. I've been checking out my agent, my digital twin. I'm not too concerned or convinced right now, but I'm guessing it's going to get better over time. I just see this as a bootloader of what, I'm going to say the word, I'm going to say the M word, of what I think is going to be
of the metaverse it's a metaverse bootloader uh and like i said this is very ambitious project like they are doing this piecemeal thing of like iteratively creating this alternative universe out there and right now it's just a bunch of llms that have been kind of bootloaded by humans to look and act according to their values and right now it's this like internal macedon server that
That's it. But really, it can expand. And if they build it correctly, there's something potentially here. Think of it like, do you ever play Second Life back in the day? Oh, yeah. Yeah, this is like Second Life, but for AI agents. Yep.
Yep. Is the bulk is. Autonomous. Yeah, exactly. Autonomous AI agents. Yeah. Exactly. Self-sovereign AI agents. Self-sovereign. The original experiment from Phasia was, okay, let's give an AI agent a wallet and have it truly be their wallet and not just some developer's wallet in some server somewhere. And wallet that truly the AI agent and the AI agent only owns.
And then the second act was, okay, let's make sure that no one can prompt engineer funds out of this AI agent. And so you can start to see these puzzle pieces coming together. There's a lot more to do to create this alternative world, this AI agent world, but you can see some semblance of what's being created here.
Yeah, and I actually saw somewhere, David, I can't remember the specific tweet, but the framework that the Frasier team launched, which is the sovereign agent framework, has already pulled in an inflow of $600,000 just in terms of like fees.
that have been deployed for people to try and spin up and build these self-sovereign agents for whatever use case they're trying to fill, right? So there's obviously a demand for these highly verified self-sovereign agents. What they're going to end up doing, we don't know yet. I presume it's going to be something along the lines of very important, high-value transactional type situations, right? Managing a treasury of sorts, but really cool to see. Yeah.
Yeah. Uh, you guys, that's all the time we have for this AI weekly rollup, but you have some homework for the listener who wants to level up their skills and level up their knowledge. What should they do while they are waiting for the next episode to drop?
It's just a quick bit of homework, but there is this two hours and I think 11 minute video from the man himself, Andrej Karpathy. So for those of you who don't know, this man gives free alpha every other month, I think. And almost every video has been consumed like- Pure gold. Like tens of millions of times. It is pure gold. I watched his last video twice.
And it was three hours long. Three hours long. There you go. So that's the advert. That's basically it. Go and watch this video. It's titled How I Use LLMs. If you have no idea what an LLM is, or if you have no idea what to do with an LLM, this is the video for you. And you will level up so much just by watching this. Yeah.
Yeah. Go take a listen. Andre Karpathy is, I'll call him the, um, Andreas Antonopoulos of AI LLMs. I think that's a good apt comparison. All right, Ejaz, thank you so much for guiding us through the AI innovations in the crypto sector and actually just AI at large. Uh,
We got robots. We got robots talking to each other. We got sports betting robots making the markets on Polymarket more efficient. And then we have probably the most ambitious of them all, self-sovereign AI built on Ethereum. I don't know what's going to happen next week, but I'm sure it's going to be pretty exciting. Yes, sir.
Bankless Nation, you guys know the deal. Crypto is risky. You can lose what you put in. AI crypto, definitely even riskier. But nonetheless, we are headed west. This is Frontier. It's not for everyone, but we are glad you are with us on the Bankless journey. Thanks a lot.