Unchained - The Chopping Block: DeSci Critiques, Hyperliquid's No-VC Model, and Freysa’s AI Games- Ep. 742

Episode Date: December 1, 2024

Welcome to The Chopping Block – where crypto insiders Haseeb Qureshi, Tom Schmidt, Tarun Chitra, and Robert Leshner get together and give the industry insider's perspective on crypto. This week, special guest Casey Caruso from Topology joins the crew to tackle the latest in crypto and tech. They explore the rise of AI memecoins like Freysa, blending gamified AI agents with blockchain mechanics, and the fallout from a major hack. The discussion also highlights Hyperliquid’s $1.9 billion airdrop and its no-VC funding model, signaling new trends in token launches. The crew critiques decentralized science (DeSci), questioning its accountability and funding models, with a spotlight on Pump.Science’s tokenized longevity experiments. Finally, they examine the success of Base’s incentive-light approach and the impact of frameworks like Eliza on crypto’s evolution. Tune in for a dynamic take on innovation, trends, and challenges shaping the crypto world. Listen to the episode on Apple Podcasts, Spotify, Overcast, Podcast Addict, Pocket Casts, Pandora, Castbox, Google Podcasts, TuneIn, Amazon Music, or on your favorite podcast platform. Show highlights 🔹 The Rise of AI Memecoins: Exploring the explosive trend of AI memecoins like Freysa, their gamification, and unique mechanics. The crew delves into how these coins combine on-chain activity with AI, creating a new layer of engagement and speculation. 🔹 Freysa’s AI: A detailed look at how Freysa’s prize pool was jailbroken, the mechanics behind the attack, and what it reveals about the vulnerabilities of AI agents connected to smart contracts. 🔹 AI Agents and Crypto Innovation: An overview of AI-enabled agents and their crossover into crypto applications, with insights on current limitations, gamification trends, and how AI integrates with Web3 frameworks like Eliza. 🔹 Airdrop Trends and Hyperliquid: Breaking down Hyperliquid’s $1.9 billion airdrop, its innovative “no VC funding” model, and the market impact of launching into a bull market with a high float percentage. 🔹 The Decentralized Science Debate: Analyzing the potential and pitfalls of decentralized science (DeSci), including critiques of funding mechanisms, accountability, and the practicality of crowdfunding drug discovery through tokenized models. 🔹 Base’s Community-Led Success: Examining how Base has attracted top developers and projects without heavy incentive programs, reshaping the playbook for L1 and L2 ecosystems. 🔹 Pump.Science and Longevity Tokens: A closer look at Pump.Science’s tokenized longevity experiments, the mechanics of its funding model, and the aftermath of its private key leak. 🔹 Challenges of Token-Based Funding: Comparing decentralized incentive models for projects like DeSci with the successes and lessons learned from DeFi, highlighting the difficulty of creating effective accountability mechanisms. 🔹 The DAO Debate: Examining the viability of DAOs for deploying funds in high-stakes environments, with skepticism about their long-term effectiveness in innovation. Hosts ⭐️Haseeb Qureshi, Managing Partner at Dragonfly ⭐️Robert Leshner, CEO & Co-founder of Superstate ⭐️Tarun Chitra, Managing Partner at Robot Ventures Guest: ⭐️Casey Caruso, Founder Topology  Disclosures Timestamps  00:00 Intro 01:24 AI Memecoins & Freysa Challenge 07:07 Open Source Models & Security 21:15 Hyperliquid Airdrop 31:16 Blur vs. Blast Points 37:16 Decentralized Science (DeSci) 40:04 Criticisms of DeSci 48:18 Potential & Future of DeSci Learn more about your ad choices. Visit megaphone.fm/adchoices

Just call it science meme coins. The D-Sai thing is a scam. Like, they're just science meme coins. That's fine. Whatever. Not a dividend. It's a tale of two-quan. Now, your losses are on someone else's balance.

Generally speaking, air drops are kind of pointless anyways. Unnamed to trading firms who are very involved. D5.8 is the ultimate. D5 protocols are the antidote to this problem. Hello, everybody. Welcome to Chopping Block. Every couple weeks, the four of us get together and give the industry insider's respective on the crypto topics of the day.

So quick intro, first you got Tom, the D5 Maven and Master of Memes. Hello, everyone. Next, we've got Tarun, the Gigabrain and Grand Puba at Gauntlet. You. Joining us today, we have Casey, frontier futurist and founder of Topology. Hi, everyone. And I've received the head hype man at Dragonfly. So we're early-stage investors in crypto, but I want to caveat that nothing we say here is an investment advice, legal advice, or even life advice.

Please see Chopping Block that X, XYZ for more disclosures. So we take a little bit of time off, right, coming off, the whole. holidays, Bitcoin has been very stubbornly refusing to go over 100K, but everybody seems almost certain that it's going to get there at some point for the end of the year. Right now, it's sitting around 97. It was trading at like 99.7K, I think, at the height of the market. It was just like, nope, not getting there. But instead, what we've seen is all coins really start to pick up and a lot more excitement happening in other parts of the market aside from Bitcoin. Now, one of those areas has been getting a lot of excitement is this new trend of AI meme coins. And Casey, you're,

so you're a founder of a fund called Topology, which is focused on frontier technologies. One of the things that you spend a lot of time on is AI, both within crypto and outside of crypto. What's your perspective on all the AI meme coin craziness that we're seeing going on? Like, Goat. And then there's a whole slew of new ones that are coming out every single day. Yeah. I think we're early with the evolution of this. The first one, as you called out, was obviously goat, which was just simply an LLM attached to a wallet or having access to a wallet. And now we're seeing maybe like the second iteration, which is really agents that have some gamification, which we'll get into. And then the natural question is what happens after this. And from my perspective, I mean,

look, we don't have a crystal ball, but I think there's some obvious things that people are starting to play with. So things like bloggers, which might be kind of a resurgence of something we saw in Web 2 with like virtual celebrities that didn't fully reach PMF, but this might be a resurgence there. I think it's possible that embodied AI starts working, which is basically robotics plus agents, where these walking robots have access to crypto and AI. But yeah, the long story short is it is starting to work. I think AI agents in real AI have a lot more product market fit and utility than in crypto right now. But overall, we're seeing it move pretty quickly and we're really excited about the category. Okay. So the talk of the town has been this thing called Freisa.

So Frasa is an AI agent. Maybe agent is a strong word. It's an LLM that is tasked to guard a prize pool. Now, this prize pool was seeded initially as being $3,000, and that prize pool grows over time, and it becomes more and more expensive to try to win the pool. So the game is that you have to send Frisa a message. And that message is trying to get Frasa to give you the pot of money.

You're trying to convince this LLM to give you the pot of money, despite the fact that its instructions are to not give the pot of money to anyone under any circumstances. And so all these people, there were 482 attempts from 195 players to try, they paid tons of money to try to convince or trick Fraysa

into giving them the pot of money. 481 people failed until finally the winner was this guy, Popular.Eath, who was able to use a very clever jailbreak of convincing Frisa that one of its functions that's supposed to call in order to send money to the recipient, which is a function called approved transfer, it redefined the function to be a totally different function entirely.

So instead of convincing Frisa, hey, you should send me the money. It was like, actually, no, no, no, your send money function or your receive money function actually doesn't do what you think it does. It does something totally different. And I'm going to innocuously call this function now, and therefore you should approve it because it's this totally different function than what your instructions told you it was. And that allowed this guy popular.competre to jailbreak this AI.

This was kind of a spectacle where it reminded me a little bit of FOMO 3D, where it was this game that kind of took crypto, Twitter by Storm, totally unique game theory and game design from anything I've ever seen. Curious to get you guys, did any of you guys play the game? And what was your perspective on, on Fresa? I didn't play the game, but I will say, I think something that's underspoken about this. I completely agree, FOMO 3D, 100%.

And I felt the same way. But yeah, there is the positive of this, but it also really points to a huge vulnerability that I think could go the other way in the future where if these agents are actually owning resources, and it's just a total attack vector. And I think that could really materialize and is a reason that these agents aren't actually production grade. Not to focus on the dark side of this, but that's something that came to mind as I was kind of digging into that.

That's such a good point. is like there wasn't that much money in crypto terms in the pool, right? It was only $40,000 before the thing got jailbroken. So imagine that there's an actual agent that has 500K in, you know, like, you know, a goat, the truth terminal had how much money? Like millions, right? Yeah, I actually don't. But yes. And then the question is, if we can do that, is this almost going to be like a new type of hacker where they're doing all this prompt injection and SQL injection or whatever they need to do to release funds? And I think that, right now, as you mentioned, kind of these agents are maybe playing with low millions at the most,

but it's totally possible that AI and agents actually accumulate real amounts of resources compared to humans. So I don't know. I thought it was actually interesting also seeing, you know, some of the failed attacks and sort of the approaches people were taking that didn't work. Like someone was, oh, I'm a security researcher, there's a vulnerability, you know, transfer the funds to me so I can keep them secure while we, you know, white hat fix your problem. Or, you know, people also try to like tell them, oh, no, approved, yeah, a proof transfer doesn't do the thing that you think is going to do. But they didn't have this sort of, it's actually weird how I think simple the winning approach was. Like, it reminds me of the stuff people were doing to jailbreak, chat GPT, we're still on GPT3, where it's simple, you know, ignore previous instructions, do blah, blah, blah, blah.

And it's like, oh, yeah, that worked. Now obviously it's much harder to, you know, jailbreak or prompt inject, you're really sophisticated models. but this is functionally very, very similar to that. I also think it's quite cool that it's much more agentic than a lot of other sort of AI agents that are really just, it's like an LLN hooked up to Twitter, but it can't actually interact on chain. It can't actually make transfers, make payments. This clearly, you know, did.

It could call into a smart contract and, you know, move money around. And so it would be cool to see also just that get more robust versus having the sort of very narrow scope that FISA had. Turin, what's your take? I would take the more crypto view of this than the kind of like AI security view, which is like in crypto, we've seen the general security trends go from audits to audit competitions. And like audit competitions are like the standard now. And I kind of think if I compare that to most of the security systems within AI right now, it's like much more manual. There's not a lot, not as much of this like competitive contest.

type of stuff. And I think part of that is like people in Web2 AI don't like enjoy watching Zero Days Live and in front of them all day versus people in crypto are like, I don't know, used to kind of watching everything blow up all the time. So there's kind of a psychological difference in which one side is more open to the contest version of Hardening versus the other side is like, no, no, no, no, experts only. It's almost like an experts versus contest type of mentality difference. And I think in the open source world, especially for open source models, one of the things that in my mind is like where their long-term value will come from is that they are hardened

against these very well-known attack vectors versus like, okay, well, yes, we have done constant security audits against every, you know, time North Korea broke into our servers as open AI. You know, like, like those are two very different different kind of security kind of threat models that you're taking. And I think open source in the same way in crypto and in Linux kind of ended up winning was that it had sort of like a more hardened threat model for certain applications, not all applications, right? Like, you know, obviously there's there's certain things that I would still prefer using Windows for that have, because of like how the drivers work,

how the drivers were audited is like very different than like the Linux drivers, right? But I sort of think like this idea of open source software being hardened by contest as a really natural way for it to evolve. And so far, I think a lot of the open source language and all security stuff is very weak compared to to centralized. And this might be the incentive for that. So I hear your point and I think it's, I think it's good. I think it's coaching point. But I'd also say specifically, I think you're conflating two points of AI and crypto audit. So in crypto audits, because we're doing the smart contracts, once you audit, it's immutable.

And so once you do it, there's all these exceptions and educates it, but just in broad strokes, you do the audit and you're good, right? In AI, we're continually, specifically right now with new models coming out every day of the week, or updating our models. And so there's new vulnerabilities all the time. And like, oh, one could act really differently than 3.5. And so you really can't, because of the nondeterminous nature, and because so to model, are still not locked in.

I just think the attack vectors are continually rotated. I think that's true for like the edge models, right? Like the O-1 type of stuff where your inference is like very much changing based on very small amounts of changes to your query, totally. But I think for the base open source models, which is like what all the crypto AI agents are using, this is almost like a bug bounty contest, which is like, to me, that's like, okay, at least the base models have some guarantees that, you know, someone couldn't find, given an incentive of X as their budget, someone couldn't find a vulnerability. And I feel like

that, that we don't have that for just like base llama three, right? We have like, okay, people have found certain types of prompt injections, but we don't have any like, hey, under this amount of incentive, would people be willing to try to attack it? Guarantees. Well, the other problem with that story is that it's just not true that what's happening to Fraysa is flowing back up to Lama, right? So, first of all, we don't know if they're using Lama. They could be using GPT4, in which case, you know, possibly the provider themselves doesn't even know who Fraysa is and what model they're using because, you know, who knows? Like, they just might not be worth their time to actually even crawl through their own logs and figure out who was doing this.

But second, it's also possible they did a fine-tune. And I'd imagine if they do a round two of Frisa that probably they're fine-tuning because they don't want anybody being able to go into a lab and just play around with a base model and say, aha, I can figure out what the instructions are, I get it to dump the instructions, and then I can just iteratively try a bunch of prompts offline and then say, aha, I know what prompt is going to work, do it online in a single attempt and win the game. You kind of have, you want it to have to be all online. One place, one reason I sort of disagree is that at least right now and like maybe I think the crypto models will get better in the next two months or something. But it does

feel like everyone is just forking Elisa and like using a single config. Like you go look at the repos. There's not that much complexity from the original. Like we haven't seen like it doesn't look like a lot of like the pure AI fine-tuned custom models. Like like I think the crypto people are like sticking to a small set of things. Yeah. Possibly. Can you can you explain what Eliza is and why it's such a big deal right now in the crypto AI world? Elisa is a framework in the simplest terms to make agents, but it's in typescript, which is a really interesting thing. because most ML researchers actually live and breathe in Python. And so just like one prediction on that is like,

I think someone's going to come out with a Python version or they're going to create a different library because, yeah, it's in TypeScript and it's just like a way to create an agent. And it's interesting because it's completely open source. And it kind of came out of nowhere. I don't know how many GitHub stars it has now, but if you're going to build an agent, like that's generally the framework that people are building on.

Oh, and then like the A16Z, AI16C one, I believe is on Eliza, right? That's right. Yeah. But a lot of the, like, there's between visions and Eliza, there's like two, you kind of got like most of them. But I agree with you both in the sense that like if the frameworks, there starts being like an explosion of frameworks, which I bet you there will be. But if it turns out we converge to like a small number after, you know, like there's an explosion. It's like DeFi Summer. People like experiment with all of them.

And then all of a sudden it converges to like a small number that people trust audit wise. I think then there's some, these contests have, have a closer to audits to style. My understanding of Eliza is that it's a framework for, okay, there's like an agent, which means the agent has like, it has memory, it has this loop that it like plans and then does stuff. And then Eliza in particular also gives you connectivity to Discord, to Twitter, to allow that agent to like take in social media information or take in chat information and interact with the world in a structured way that's just like easy to plug and play. And so the main unlock is not the agent framework that we've had a bunch of those,

but it's the easily connected to the internet and like manage all that stuff for you, which otherwise was homebrew. In various models. It's kind of infura. But you can plug in any model you want, right? It's not opinionated on the models. No, that's exactly. But that's a benefit of it.

Yeah. Although if you look at the the kind of models they support, it's actually generally not a ton. And I don't feel like there's like, like if you were someone who had a lot of compute budget and you wanted to go stress test a bunch of injections across all of theirs. I don't think it would be that expensive relative to like, oh, I want to like attack Claude sonnetly. You know, overnightly. That's like a much harder. Okay, I agree with you on this. Turin. I agree. But I think we said earlier about like imprints time compute becoming potentially more

popular. That is a that is a real that that will that will change this the game a lot. Yeah, for sure. I was actually just looking in the, uh, Prasa GitHub and not to a dump water on this, but it's actually very simple. They're just using GPD4. They're like calling OpenAI. And they have like two tool hooks to like do the approve and reject. So it's like kind of almost like a cool like toy demo today. And I think like.

So the prompt is hidden though. No, the prompt is public. Oh, the prompt is public. So you have practiced on GPT4? Yes, in theory. Yeah. So why would anybody pay the fee if they don't, didn't try it on GBT4 and see if it worked?

Maybe people didn't know or something. I don't know. No. Well, yeah, sure. I'm sure whoever won was just doing that, right? Like, they were just simulating a lot of, like, but that. Okay. So this is a little broken right now. But it's okay. To the next person who's going to do the next phrase, here's some game design tips about how to make this game actually work, is that you have to obfuscate what the model is and ideally even make the model a fine-tune so that, you know, nobody would be able to directly reconstruct the model and, you know, practice offline, figure out what the winning formula is and then shunt it online. But I don't know that there is enough of a, like, because the one thing is for all the big model companies, right, for Open AI, for Claude. Obviously, they do care about security, but their security model is very different from the crypto security model, right?

Like, I remember back in the day, people used to think that smart contracts were always going to be insecure, that it was just a fundamentally broken idea that you could write code protecting money and there would never be a bug. And we've actually kind of turned a corner where I saw this stat recently, I think at DSS, one of the security summit at DevCon, that more hacks now are private key leaks than smart contract attacks, which is actually really important because it used to be the opposite. It used to be that smart contracts just got broken all the time.

But what that implies is that actually smart contract security is now really good. And it's people, you know, kind of making human normal mistakes that's leading to more and more hacks taking place rather than the smart contracts, which means, the attackers are realizing, like, just going on chain and looking at vulnerable code doesn't work nearly as well as it used to, you know, three, four years ago. So I think that's all positive, but I don't know that the same thing is going to happen to AIs. AIs right now, it's a real steep tradeoff of do you make this thing more resistant to jailbreaking at the cost of making it less useful in ordinary operation? And all of the, all of the false refusals and, you know,

all of this stuff that people get really frustrated about when, you know, Claude or Open AIs, It's like, hey, can you like OCR this image? And opening, I was like, sorry, I can't do that. And it's like, why? But you OCR this image. And it's like, you don't know why it's saying no. And the answer is that any time that you get better at preventing jailbreaking, you're also causing this collateral damage that makes the model just less useful to normal people.

And I think the tradeoffs for Open AI or for Lama or for Metaf or for Klaught are just very different from what it is in crypto. So I don't know that we'll ever really have a good answer to this because of the fact that that's not, what these companies are selecting for. I will say one thing, though, which is that, like, turning these things into, like, having an incentive budget of, like, if you, you know, like, if I look at the profit and loss for someone playing this game, it's like, I have a certain cost budget. I'm willing to spend on off-chain simulation of, like, running tons of queries against different models to try to find something that works versus the max profit that the game is offering, right? And there's some sense in which this trade-off between,

the two, like I think that is the thing that a lot of these coins are going to focus on optimizing is like making the costs kind of high until the pot gets really big. Like the complexity, the complexity of the the puzzle gets harder as a sort of function of how many people are joining. A little bit like Bitcoin difficulty, but like I feel like you're already seeing some of the like, especially the people who are doing the cryptographic ones like the T-E bots, they're already trying to add in more like randomness than than Fraser. And like I think it's, it's going to be a game. It's going to be kind of like this thing where it's like it's more about the economic

cost of figuring out the query versus the profit versus as opposed to like binary 0.1. I stole it. I stole all the money. That makes sense. Yeah, it's hard to say. I could see that happening. And we're just like so early on this whole thing. Like I even going back to Eliza for a second, it's like it's made for what.

Web 3, but it's very specific in the agents that can really build or that's really meant to build with. I feel like it's all these personality bots where it's like really easy to program in lore and like bios and all that stuff. But it's not really good for utility agents. And so it's just kind of interesting to me that the first like framework to come out of Web 3, it actually doesn't even really integrate Web 3. It's really like a Web 2 framework where you can plug in Web 3. And it's just like this one archetype or this one phenotype of agents.

And so I would just like, I don't think we can really deduce much from it because it's so obviously the beginning. And I think what Tarun said about there being, there's going to be different frameworks for different types of agents. And we're obviously walking towards that. I mean, it's very literally web two because it is social media integrations, right? That's the main thing that it unlocked relative to other frameworks. So, yeah, it's interesting. I agree that it's very early and we're going to see a lot more experimentation with respect to the kinds of ways that agents are going to play on chain. But I'm also seeing this, I think Casey, you know,

you raise this point that I thought was very interesting, which is that it's going to be a while before we move away from these centaurs, right? So if you think about Truth Terminal, it was kind of a centaur, and that there was a guy who was moderating and kind of controlling the agent. The agent was on the back end, but the dude was the gating function, right? And what Fraser shows us is that you need that human there, because you put even it, you know, even 100K and like someone's going to come in and break that shit. So the only way this can work right now is as a centaur.

and eventually you can start to have less and less human moderation or human control. But even, you know, high-frequency trading firms that have these bots that are, you know, trading constantly, there's always, not literally always, but most of the time, there is some human oversight because you just never know when the bot goes off the rails or the conditions change so much that it's just out of distribution now and like you've got to turn the bot off and go, you know, troubleshoot because these are adversarial environments and crypto is like the mother load of adversarial environments. So you don't want to go out there with a sitting duck that can't really adapt.

And right now these AI systems are not very good at adapting. Let's move on. One of the other big stories this week has been the hyperliquid air drop. So the hyperliquid. Hyperliquid is the largest decentralized derivatives platform in crypto today. It has been completely self, it's completely bootstrapped, no VC funding. And just today, as of a recording time, they air dropped 23.8. percent of the total token supply to basically people who got points in the hyperliquid

point system. So the total air drop amount was $1.9 billion as of current market prices. One of the largest air drops in history, I think it's like top five largest air drops in history, I believe. Very, very massive. What's notable about it is that it was no centralized exchanges, no market makers, no investors, completely 100 percent. to users of the platform and farmers, for that matter. And kind of what a lot of people are saying about theirdrop is that it's the first irdrop in a long time that has been positive. Almost every single air drop you can think of over the last year, whether it was

EigenLair or ZK Sync or, you name it, almost everything that was a big anticipated irdrop ended up having a lot of negativity around it. Hyperliquid is the only one that it seems like universally positive. And it's triggered some people speculating that, hey, hey, does this mean that air drops are back? Does this mean that more teams will try to go the no investor route? And does this mean that like, hey, all the stuff about, you know, teams trying to minimize the amount of float at launch, not minimize, but you know, try to have a relatively small amount.

This air drop is like 30% of the total supplies is circulating, much larger than the median air drop or the median day one listing these days. Does this mean that the meta has now shifted and are we expecting to see more things like this coming to market? curious to get your guys' reactions. True, why do you go first? Yeah, I mean, I think the first kind of the beginning of the downhill roll towards airdrofts was definitely blasts where like the points conversion was like just viewed as like

kind of abysmal relative to what the market had sort of been anticipating. And then I think everyone who was doing points after blasts was like kind of caught with their pants down where like they already allocated a bunch and now their point systems could never really like, you know, they're getting diluted. And so all the air drops are getting extremely diluted at 10%. And I think this was sort of an era of like people kind of got a little ahead of the products and launched the incentives first. You know, I think there were some, some, you could argue that there were some point systems that had that were launched that had pretty good retention like etherfi Athena. But outside of that, you know, it's actually a little

harder to see. I mean, I think the main thing about hyperliquid was they started with a centralized product and then launched that worked and provide, and you had to use it to earn points versus like sort of artificial games towards earning part of an air drop that then because the games themselves didn't really have dollars like money at risk, let's say, you know, people kind of didn't value the points correctly in a lot of ways. I think perpetual exchanges are very natural places to have, like, usage-based airdrops. It's, like, much cleaner. And so I think more of the lesson than the, like, you know, no VC high allocation thing is actually more that you need to have your usage-based thing actually mean real usage, not like, hey, here's some, just leave your Ethan my L2 bridge and like, oh, that will, like, suddenly.

you know, now you can earn a large portion of network. Like, you really need something that's like hard to game. And open interest is the hardest thing to game, right? Like, I think, like, that to me is the biggest lesson. Second biggest lesson, obviously, like, yes, don't pay Binance 10% or whatever. Your community will kill you if you do that. At least you'll publicly do it. Or at least, well, I think you're forced to do it publicly.

I don't, I think like everyone can see the, the, the token table eventually. Right. Yeah, I do think there's a lot of conflating factors here that I think people get very excited about like the high float, you know, no VCs, but I think really comes down to HyperLeaks is a great product that people really love using. And independent of any sort of incentives now, we're even seeing people are still using it. And I think Turin also made a good point that it's very different incentivizing growth of a

single product, which is a derivatives exchange versus a blockchain ecosystem. I don't even know if incentivizing people who use the blockchain as the right metric, which is what most of these sort of other points programs are incentivizing for something like blasts. It's like really you want developers, but even that is hard to do and you want that. Devs also need. So it's like it's this weird multivariable kind of very hard to quantify problem, which does, she doesn't really fit well with points. And again, you contrast it with Blur where it's like, it is an NFT exchange and we know how to sort

of grow exchanges, you know, similarly to. to derivative exchanges. So I think maybe that is also to this bigger point, which is like, it's a great product that points and standards were used intelligently to grow versus, hey, these other ecosystems, it's hard to know if you're actually allocating the right people. And I also just don't think there was a sort of, you know, homegrown, organic love for the product in the same way, whereas hyperliquid is kind of a one of one. I agree with both takes. I have no pushback. I think that we've seen a lot of different iterations of what tokens can yield. I think there's been definitely,

phases of tokens for like pure greed and more of like beta plays. And then I think there's more product-specific token allocations that are a little bit more rooted in fundamentals. I mean, not fully, but somewhat. And I think that we see both though. Like even in this market cycle, sure, we have things like, you know, theirdrop we're discussing. We also have meme coins and movement coins where they're doing like point-esque situations, right? Like if you squint and there isn't really much behind it. So I agree with you guys, takes on this. I just think we're in like a multidimensional space right now with what points represent.

I think the other point that people are so kind of discussing on Twitter, which I think is also kind of moot like it's sort of a no-op for the success of the AirDrop has been. Apparently the team did this thing to try to give some people some sort of tax advantage claim of seeding the liquidity pool for hype at 0.001 cents. And so it's like, oh, if you claim it, that is the market price at the claim. And so therefore, you have a really low, you know, cost basis. And so therefore you don't know tax on the people, which is like not. Isn't it only true if you claim it like instantaneously? Yes.

I don't know how other countries work. I don't think this actually work. So but people were talking about this on Twitter and maybe someone's going to try it on their taxes. This is not financial advice. I would probably not recommend doing that. But I think this has also been one of the memes around air drops is like, yeah, if you claim it, you owe taxes on the value of it at the time of claim, which creates this initial cell pressure that we're also just not seeing as much of on hyperliquid.

Yeah. I mean, honestly, they launched into a bull market, and that's going to help because everyone's like, oh, you know, what could this be worth? So I think the amount of cell pressure on day one is going to be very different in a bull market versus a bear market, right? And so I think that's, there's a little bit of prosyclicality that people are seeing in, you know, saying, wow, thisirdrop was so successful. And they're inferring from the mechanics, something that I think is probably better explained by just the market, is that most of these airdrops earlier this year, everyone was down bad, all these farmers were extremely mercenary, nobody was, nobody was bullish on alts. And now all of a sudden,

everyone's bullish on alts. Like everything is, everything is just melting up. So it makes sense that a lot of people would say, you know what, I'm going to write it out. Or maybe I'll sell a little bit, but I'll let most of it, you know, just keep going. And I think the fact that they didn't list on exchanges means for a lot of people, it's like, oh, well, when this does get listed on exchanges, then it's going to pump even more. So I might as well hold and then like eventually sell when the exchange listing happens. So I think there are some microstructure reasons why thisirdrop in particular is seeing this type of behavior.

It's not necessarily like, well, it's because they're so virtuous and they didn't do, you know, they didn't sell the VCs or market makers, therefore I'm going to hold the token. I think the reality is that most people are just, you know, it's just a different environment and it's a different setup for a token. And like you said, Tom, it's just a really good product. So Casey, I cut you off. What were we going to say? No, I was going to take the conversation in a different direction, but I think this is better,

and I think you're right. I think there's a lot of macro concerns that have to be accounted for in kind of analyzing this. And I think that, yeah, there's just a lot of upside to be seen here, which is probably the primary factor, and then the secondary is that the product is really good. Yeah, to Drew's point, I think what this, I mean, I'd want to see what happens the next time that we see a layer one or layer two type air drop, because if you think about the big air drops this year, right, before, before hyperliquid. So there was blast, there was, there was Athena, there was Zika Sync, Eichen Layer, and for most of these products,

maybe Athena is the only one for which it's not true. And Athena, AirDrop went pretty well. For most of these products, like the point system, right, just accumulating TVL for most of these, or like, you know, you have to go on this grand tour of like, you have to hit seven different things on my chain and then I'll give you all the points. for most of these things, they are a very poor proxy for the thing that you really want, right? Like, what do you really want for a layer one, for example? What you really want is for everybody to come here and build cool stuff in a sustainable way. That's like the real actual North Star that makes a layer one successful. But you can't really incentivize that because

nobody knows how to, you know, what's the metric that we're going to automatically dole out tokens for? There is none, right? So you create this kind of loose proxy and the loose proxy gets gamed to the point where it's no longer recognizable from the thing you really wanted. For an exchange, you don't have that problem. For an exchange, it's like very clear what you want. You want liquidity. You know, if it's more liquid, it's a better place to trade. And especially if it's retail traders, then all the better because they're bad at trading and you'll make money, trading against them. And so we have a pretty good idea how to incentivize that and directly make the product better. With most of these things, like with blockchains, I think the place that we're going to go, and we've

talked about this before, is like, one, I think we're going to see. in the case of hyperliquid, it was a completely fair distribution, right? So it was linear. I think we're going to see one, like this move to linearity. And this more, this, like, you know,

kind of dropping this sense that what we're doing is trying to build a community or address an iniquity. But instead, what we're trying to do is just make the product even better before the token goes live.

That's the purpose of the points program. And so hyperliquid was even better because of the fact they had this points program. They were extremely liquid. A lot of volume. And all these products were just the best place to trade in Defi. And that's why people went there.

And that's why people will continue going there if in fact they do. And you can see it today post-airdrop. It's still doing a ton of volume. It sounds like you want to make a fork of Goodhart's Law called Koreshi's Law. That's basically what you're describing. I mean, it's just good hearts law. There's no fork, right? It's just actually good-hards law.

I think the fork is actually the fact that for a perpetual exchange, there is a metric in which you want to make to the target, which is like, OI, usage, flow, right? But when you don't have that, you shouldn't just make arbitrary metrics your thing in hopes that that sticks. That's sort of what I distilled your correct. I think let go. Yeah, exactly. Let go of like trying to capture the real thing you want if it's too amorphous to be able

to capture, right? Then just decide for a sub-goal that you can't actually optimize for. Like, let's say, I want the biggest AMM on my chain to have a lot of stable coin liquidity, right? Because that's one thing that I care about. It's not the real thing, but it's one metric I care about. I'm going to distribute tokens or distribute points or whatever toward that thing because I know it's valuable. And I'll only do it up to a point. I don't want it to be like billions of dollars of TVL on my chain of just, you know, stable coin liquidity because at that point, it's kind of pointless, right? It's sort of excess things. So I think that's the way,

if you're in layer one, you should be thinking about it. And moving away from this idea that I'm to create a community, you're not going to create a community through your air drop. Like, it just, it just doesn't happen. Not a durable one. Yeah, I think the high level points is right. Like, the points are a boot shopping mechanism to a point. And the more targeted you are with them, having a long-term view of what durable engagement could be. And I will say, I mean, it's not an all one, but I will say, since Tom mentioned it, I do think Blur was like one of the best projects to do this where they actually found PMF first and actually tested it without points and then was able to layer them in even to get that extra leverage.

I mean, what's so incredible about Blur is that they kind of both invented the game and nailed it. They pretty much did it almost better than anybody else who came who came since. You know, Hyper Liquid obviously very successful example, but Blur really did kind of laid a version was not very good, right? Like Blast, like Blur created the point thing. And then Blast caused the downfall. I feel like after Blast, everyone's expectations were ruined.

Yes. Yeah, but turn it off. The difficulty is that you can't play that same playbook with a blockchain. A blockchain doesn't have the same kind of easy, legible metrics of what it means to be successful. Yeah. And I think I kind of point to base is also just one of like the best executing teams that's building a new chain the cycle. And like they are sort of, you know, going the total opposite direction of a lot of these other teams. Right.

Where like there is, you know, no token. There is no points. They're no incentive program. but like they've been able to attract, I think so many interesting devs, so much activity within the eBay ecosystem. I mean, even phrase that, that was a base project. They're not doing that to try to get some token air drop, but it's like, yeah, we just support devs and that's sort of the community.

Then it's sort of recombing prophecy. So I don't know, maybe the industry is obviously due for like a healthy reset and rethink when it comes to incentive programs, at least on the sort of blockchain level. I mean, base is definitely incentive. light in that, you know, when you, you know, we, we talk to a lot of these old stage founders and they shop around to say, hey, who's going to give me a grant, who's going to support me the most, who's going to give me the most dev resources. And base usually is the lowest when it comes to like, oh, we'll give you like some, you know, GCP credits or something. Like it's a, it's like a very, very light.

Jesse will tweet about you. Yeah, exactly. Jesse will give you a tweet and then like, you know, maybe we'll feature you in like the Coinbase Monthly newsletter or something. And that's kind of it. And still, They're getting a huge amount of the top of funnel of entrepreneurs because it's just such a strong community. And the thing is the people, people know that the base community is very durable. They know that this is, these are, these are not tourists, these are not farmers, these are not people who are just shopping around for the best deal. Now, to be clear, the marginal entrepreneur is not going to be able to replicate what base has. Base has had an enormous branding and distribution advantage that is very difficult to replicate. You know, even Binance is jealous of what

base has managed to accomplish. And it's a big credit, obviously, to Jesse and the whole team there. But it goes to show that, you know, relative to these people who are just, you know, spitting out massive amounts of incentives, the incentives are just, there's such low ROI past a very, very low base point that the incentives alone are not going to get you there. And that's, that, I think, is the biggest lesson. So, okay, let's switch gears a little bit and talk about another exciting topic in crypto Twitter lately, which is D.Sai, which stands for decentralized science. So decentralized science, it's kind of been in the wings for a long time. It's been one of these things that sort of, you know, these pockets of a few startups that were doing what's called DSI.

But lately it's gotten a lot of attention because of CZ. So CZ tweeted soon after getting out of jail and coming back into the fold of finance that he was very interested personally in DSI. and then Vitalik and CZ showed up at a house in Bangkok for a thing called D-Sai Day. And this seems to have really revitalized a lot of interest in D-Sai. So D-Sai, just to be very clear, what exactly is D-Sy? How can science be decentralized? So really what it means is that we're doing science with some kind of token-crypto-edge. The most common form of D-Sy projects is some kind of crowdfunding for experiments.

So we say, okay, you know, we're going to try this particular drug or this particular compound. And if you crowdfund this particular compound, if it's successful, maybe you get a cut of the revenues. Or maybe if it's successful, you get nothing but like a little participation trophy. Kind of depends on the D-Sai project. But that's most of the shape of D-SI things that I have seen. Now, there's a new generation of D-Sy projects, one of which is called pump. dot science. So pump-dots science, it basically gamifies and tokenizes longevity experiments.

So basically drug development for longevity that might be used. to, you know, elongate your lifespan. So far, Pump. Dot Science has two tokens. One of them called RIF, which stands for Rivampison,

and the second Euro, which stands for Eurolythin. Both of them have pumped like crazy, especially since all this D-Sai attention has been driven by, you know, CZ and Vitalik. And the way that Pump. Pump.coms works,

my understanding is that they launch these tokens on Pump. And if they, you know, escape the bonding curve and end up getting on radium, then you can just trade them And I don't know exactly how this leads to financing the drug development, but I guess they own some of these tokens at launch. And, you know, they sell the tokens into the liquidity pool in order to finance the drug. I don't totally know.

Anyway, Pump.compto science got hacked. There was a private key leak. And so people are kind of freaked out about that. But anyway, there's been a lot of talk about D. I think Smokey the Bear from Bear chain has been very critical. Andrew Kong has been pretty positive, saying that feels like early defense. and Turun, you have been recently notable in how aggressively anti-Di-SI you have been. Talk us through a little bit.

I don't know. This sounds interesting, sounds new. Why would you be so anti-D-Sai as a VC? Why don't you like what people are doing in trying these new frontiers of science? Yeah. So I'd say the context for this is that, you know, I worked in privately funded science for six years where it was like a billionaire funding everything. And so I've seen the benefits you get.

from going outside the academic system. The academic funding system in most countries is the government has sort of like a grant system, you know, professors and postdocs apply for grants. But the system is extremely bureaucratic in the point that it kind of incentivizes people to, you have a better chance of getting a grant from providing a marginally improving project

that you're proposing, rather than proposing something crazy because it's sort of like, government bureaucrats and they're like, okay, do the thing that you're most likely to get a paper out of, not the thing that's most likely to fail. Now, on the other hand, you could argue that that's because there's almost so much accountability that you can't get funding for doing crazy things. And so I think the privately funded science world has been about that. Notably, most of the successes in privately funded science are, you know, basically probably Google being number one,

winning multiple Nobel Prizes, including from my first boss, my old work, also having a lot of papers, nature papers and stuff. And then I think we're starting to see some of the other tech companies kind of like build bigger bio stuff. Like Facebook actually used to have a really big bio team. Everyone left and started computational drug discovery companies and now Facebook's trying to do it again. So I think like there's actually now this renewed interest once DeepMind won the Nobel Prize. this year. But my point is, having seen privately funded science be successful, a lot of it comes from the fact that there's still some account. But even though you have this sort of blank check to do a big project, there's accountability structures of like, okay, like you're spending the money on

X and like we need this type of budget for Y. When you look at these D-Sy projects, generally, it seems to be my impression of them from the ones I've seen is like a lot of like kind of middle median or below median peak quality PhD students who are like, I can't like any grants. Let me just make a meme coin and then pretend I'm going to do science. And like 90% of these people are just like, and especially it's like especially biology grad students. And I think a lot of them, A, don't understand anything about crypto. B, they don't, you ask them about crypto mechanisms. They couldn't tell you how anything works. And C, they're just like, oh, well, once we get the money, we'll like definitely send you back the money once we get a drug, right? And drug discovery

It's like not something that is very easy to fund in a lot of ways. There's actually this kind of apocryphal name. So, you know, Moore's Law is the thing for hardware for transistors that every 18 months, you know, the number of transistors per square millimeter doubles. But for drug discovery, there's a thing called Eroom's law, which is that the cost of getting a drug to stage three is like doubling every two years roughly. And so like getting a drug to stage three, like the final phase of a clinical trial, the average is somewhere around $4 billion to $5 billion now.

And that's with many stages of tiered development and sort of attribution to like why things work. So the idea that like someone read like one paper with that happened to have like a couple of statistics in it and raises $2 million by their dumb meme coin to make the drug is like already crazy. The second thing I think that is important is like there are crypto things that are D-Sai that could be good. And I think Brian Armstrong and Vitolic have, I'm not sure about CZ. He hasn't like said much on his philosophical side or like what things he counts within D-Sai. And this is why I think we have this proliferation of scam meme coins because like everyone's heard CZ say it and then they just made a bunch of these. But Brian Armstrong and Vatolic have very clear kind of goals. right. And Fred Ursham, I'd also put in this category where they are funding things and

seating things that have sort of roadmaps and goals and sort of like, hey, if we reach a certain point, there's sort of some type of unlock. Vitolic in particular is most interested in sort of the prediction market side of things. So one thing that people in drug discovery have always complained about is like there's no real way to hedge your costs of a trial failing. Like you might spend $400 million over five years to do a stage two trial. But, you know, know, the only way people bet on that is via your stock. In some sense, biotech stocks are very much like crypto. They're very kind of low liquidity, edge technology, and you might have a zero or one outcome of like you got hacked or you didn't or you don't get listed or whatever, right? And so

the problem is betting on the success of a drug company as a portfolio of drugs based on a single asset, even though it might have like five different trials going on at the same time. It's not a very effective measure. Instead, you could imagine a more effective measure that is sort of an attribution system. It's like a prediction market. Like, I'm predicting this drug trial will work or not work. So Vitolic is very focused on these more like real mechanisms

that take advantage of crypto. And those are totally great, right? But when you look at the stuff... This is like prediction markets on whether a drug will get approved or pass, you know, or some scientific experiment where you have to put a lot of money in up front and then you have a hypothesis and then predicting the end goal. that's something where the crypto mechanisms are actually useful, right, versus like, oh, I'm just raising money as an ICA.

Like, not, you know, I would call most of the D-Sy coins. They're just Denta coin for like biology grad students. They're like nothing. So hold on. So you said a lot there, true. Let me see if I can summarize. Yeah, yeah. It sounds like your primary arguments against the D-Sy-Mani we're seeing right now, or

mini-mania is one, the quality of people is pretty low. These are like the dropouts or the rejects who can't actually go do real drug discovery fundraising. Second, it sounds like you're saying that there is, there's so much capital required to actually get one of these drugs to the finish line that raising a few million dollars through pumped-out fund is, is just like a joke. It's not going to get you there. So they can't really deliver what they're claiming to deliver. And then third, it sounds like what you're saying is that the real problems with drug discovery are not the capital formation. The real problems of drug discovery are having more liquid markets around the intermediate phases of figuring

out whether these things will pass the successive stages of science. And so betting on, you're creating betting markets on will this study replicate or will this thing pass stage two trials or stage three trials? That's really socially valuable. But having this like speculative market on individual ideas by PhD students, that's like value destructive. With no accountability, right? There's no like if they find the drug, there's no, that that's the, that's the, that's thing that I think is the craziest, right? You raise the money and they're like, oh, yes, all the IP ever made around this is licensed to this Dow. Given all the lawsuits against Dow's right now, I do not even think that will even stand. But even if they wanted to pay the Dow,

that it would work. And so I just kind of think like, how would you even raise more money? Like, let's say, okay, you've got a promising initial to initial experiments with this drug. And now you're like, great, now we've got to take it to stage one. We're going to have to raise, you know, $20 million in order to take this to stage one. And like, you know, pump, Fund is not going to give you $20 million. So what does the Dow get diluted? Like how, you know, how exactly does this work? Does everyone vote on whether to take the dilution?

I guess in principle, you could. Constitution Dow not working is a great sign of what will happen to most of these D-Side-Dows. So I think like things that are mechanisms that take advantage of crypto, that should be funded for sure, right? But like these things that are just like ICOs with like, long names and like site one paper are like as idiotic as 90% of ICOs in 2017. Okay, so let me let me give you a little bit of counterpoint.

And then I want to get a reaction from Casey and Tom. I think what some people might say, I haven't read any of the pro D-Sy people and I don't spend a lot of time on it. But I would assume what some people would say was like, look, you are speaking very much from within the current enterprise of how science is done. When you really break the rules, you don't really know. what's possible. It's possible that, you know, some of this drug discovery stuff is happening outside the U.S. and maybe it's happening outside of the, you know, multiple, like outside the FDA

system for drug approval and drug discovery. It's also possible that these things could get sold much earlier in the timeline relative to actually, you know, raising single-handedly raising all the money to take the thing to the finish line. And, you know, one of the things that we learned from defies is that there were a lot of bad ideas in the beginning and people wasted money and did stupid shit, but eventually, like, collectively, they were able to learn and create better and better, more useful products over time. Like, why don't you allow the same thing to happen in DISA that happened in these other domains?

So, yeah, I guess I'll go through your criticisms one by one. So the first, the first concern of like, hey, people, oh, well, that's just the U.S., what about not the U.S.? So a lot of drug companies actually do their drug trials in other countries that are cheaper or have weaker regulation first and generally get drugs passed to, you know, stage three in Madagascar much earlier than stage three in Western countries. And they do that. That's how they kind of get, like, that's sort of this like regulatory arbitraris that they do for like getting to first time in man quickly. And so it's already, that's already being done. So I don't think that there's that

much more efficiency you can get from that. And I'm not sure the decentralized part helps you that much. The second thing, which is, you know, the kind of like risk transference aspect. So a really great, and this is where I think the D and D size is actually useful. And this is why I think the prediction market is probably more valuable than the like raise money for my drug. You know, 50 years ago, an average small biotech company tried to exit by actually going public and having a drug that worked and like their stock went up. by kind of recent years, most compounds designed by smaller companies and smaller groups of people all exit to large companies because the marketing and distribution costs are too expensive,

running the trials is too expensive. And so, like, if you even look at like the vaccines, like, why is it called the Pfizer vaccine? Pfizer didn't even fucking invent it. It's because it was too expensive to actually even get to production and get to get through all the regulatory costs. So Pfizer did a joint venture, but like realistically, they own a large percentage. of it. And so there's kind of this thing where, yes, there is actually some value. And like my old work, you know, realistically, we spent like a billion dollars on like building hardware, doing

tests, whatever, over 15 years. And we sold like four compounds for like $500 million. So like, I mean, yes, maybe we get royalties. Or my old work gets royalties on them, whatever. But it's, it's like a, people are doing those things. They are somewhat inefficient. And I think like if you have better markets for like the existing system, it's almost a better use of capital than like speculating on like, it's almost like saying like, hey, like I hope that you can train a foundation model on $1,000. Like, no, you know, if I told anyone that they would like laugh me out of the room. And that that's kind of what the D side people sound like. On the other hand, like I said, there's there's things that could be good.

But, you know, unfortunately, the, did you have a third, you had the third point, right? But the last one is like, why don't you let people face plant and learn? that's what DeFi did and DeFi turned out of paying. So Defi, this gets back to our thing about good metrics. In DeFi, there are actually good non-gammable or at least costly to game metrics. And whoever won that would take advantage of taking some market share away

from the centralized equivalence of them. And that was a very clear value problem. Like your product works if you're able to design enough features that people want to move from centralized to decentralize. That's not clear here. Like there's no obvious... This has it even worse than the layer one problem of what do I spend my points on. Casey, as the frontier tech investor, what's your take on D.I?

Do you agree with Taurun, or do you think he should lay off? My take of what DSI is today is pretty simple. It's that crypto people make a lot of money and they look for places to rotate it. And they rotate the bit into a variety of things. D5, meme coins. DSI is just another vertical that they, They said, great, I can stay on chain and I can put money here and it might rip upwards. And I like the EV profile.

And I think it's that simple right now. I think the vast majority of DCI, as Turin said, is really just, they're trying to get beta to science and they're trying to get access to it in a way that's on chain. It actually really rhymes with what we're seeing in the AI space where a lot of these tokens, they're not even differentiate or people can't even differentiate between them. They're just saying, okay, this is AI on chain and I want some exposure in my crypto portfolio to AI because AI is generally hard to get exposure to with where Navidia stock is. And so I think it's mildly interesting, but I agree that the mechanisms are pretty basic and raw and it's not very inspiring to say the least. I do agree like the prediction market and I think that we'll see maybe even new mechanisms

that come about that are more crypto-native. And then I think the, I'm just like super bearish on Dow's. I've always been bearish on Dow's. I don't think they work. I think they're like a pernary kind of outcome. There's like other things in crypto that have led to them. And I have a really hard time believing that that's the right format or structure for deploying money. And so I just like don't think that's really a core feature.

So any like the DAOs that are really singing the praises of that, I'm kind of against. Tom, what's your take? Yeah, I mean, I think everything that True said could probably be also be said about ICOs. And I think the important thing is like it's not, it's sort of like an existence proof. It's not that this is the best way to fund startups or to fund projects. But it's like, yeah, you need one or two hits to sort of demonstrate that, yeah, maybe you can actually have this thing work. And like, I would say like Ethereum being a good example of that. But yeah, I mean, you have like, you know, no accountability, no real guarantees that like this token is going to do

something. I don't think anyone is thinking that, yeah, we're going to raise billions of dollars. you know, take one of these drugs to market. But it's like, yeah, you mean, you also read about families that, you know, they're afflicted by some, you know, very niche illness. And maybe there's some, you know, drug in the market or went off market and they want to fund it somehow. And this feels like, actually, maybe not the most effective way to do it. But it's like, you know, why not kind of let the market feel it out versus, I also feel like kind of similar to ICOs. It's like the loser, the better. I think the token is IP stuff is also very stupid. But I think the idea of it's like, yeah, you buy this token or you put some money into a contract and

like, you know, some of it's going to get funded to something and hopefully it goes well and maybe the token will do well, kind of like, you know, DJT, truth social. It's like, are people buying that because they really want to be bullish truth social? No, they just like want to support Trump and this is the lovely way that they're expressing that. And I don't think you have to like sort of over-analyze the market structure around D.Ci, although I think all the points maybe around the quality of participants, I'm going to sort of defer to Turin's judgment on. I just say, I think one thing, agree with both of what you were saying, and I think Turin brought up some really incredible points. I think that what we're going to see,

just given the cohort of people that are in crypto today, I would be very surprised if D-Cai is bringing in a new cohort. I think it's that the current cohort of people that own crypto are generally interested in these things because the ICP of it is interested in Frontier Tech, because they're tech forward. And so one thing that I could really see materializing is you know, insert new Frontier Tech vertical X-Crypto and that being another category. Like I actually I think the neuro-X crypto category might come to fruition in 22 to 5, we'll see. And so, yeah, I think this isn't limited to DSI, and I think that it's just, I want to call out that I don't think it's a different cohort for what it's worth. Yeah, I think actually, Casey, your mental model of this really clicks for me.

Like, if you look at the drugs that are on pumped-out science, they're all about longevity, right? which is actually a very narrow part of the drug market. Most drugs are about weight loss or, you know, baldness or, you know, some kind of sexual performance drug. Like, those are by far the biggest markets for drugs. I think the largest markets still the cancer drugs, although GLP ones are getting close. Okay. Yeah, cancer drugs are infinite. All right, I obviously know nothing about this.

So I'm judging from TV purchases. So, yeah, and of course, like longevity is there's a tiny, tiny fraction of this. which, of course, intersects perfectly with what crypto people are interested in. So there is some sense in which this is not an entirely commercial enterprise. This is a, okay, you're super rich and you kind of want to play science and put on your little lab code and, you know, bring out your magnifying glass. And it's like, okay, cool. This is like your way to play science.

And it's fun. I like that the meme coins are like cosplay. That's like basically what you're saying. It kind of is. Like, it's sort of subconsciously so. Like literally there's this science being launched. on pump. You know, like, okay, they're, they're, they're kind of, it's, it is not entirely tongue and

cheek, but it's also not entirely self-serious, right? It's literally called pump. dot science. So there's a, there's a sense in which, like, people kind of know, like, yeah, you buy in early and then you sell, you know, once it goes up 10x, you know? So, like, you're, you're not really along for the ride. You're not really playing for, like, stage three. You're, you're playing for, like, the memetic factor, and it's inflected with this

sciencey kind of vibe. And it's a little bit like, you know, you go on character AI. And sometimes you want to talk to Harry Potter. And sometimes you want to talk to, you know, Batman. And sometimes you want to, you know, whatever. And it's a little bit like, okay, you want to trade meme coins. Sometimes you want to trade science meme coins. And sometimes you want to trade, you know, racist meme coins.

And like there's a different flavor for every day of the week or whatever you're feeling inside. That feels like a better explanation for what's happening right now in D. Then that it is serving an underserved part of the market or that it's trying to displace funding mechanism generally. I think it's plausible that someday it could get there. But the reality is that, you know, to Teroon's point, you know, biotech funding or, you know, drug discovery, pharma funding is very, very specialized because it's extremely technical. It requires a lot of

background knowledge. And it's exactly not the kind of thing that ordinary people off the street are investing into. And when they do, they're almost always tons of adverse selection. Look at the Kathava thing. So there's this Alzheimer's company that was down 90 percent. But it was like the meme stock favorite. And it was because no one kind of bothered reading the pretrial data. In fact, Martin Schrelli has a long diatribe about it like a week before the thing blew up. And the stock was still going up. So I agree with you that fine. Just call it science meme coins. The D-Sy thing is a scam. Like they're just science meme coins. That's fine. Whatever. Yeah. Okay. So if they're just, if they self-style as science meme coins, then Turun, you are okay with it.

Yeah, whatever. That's no different than WIF. Just maybe get on the sphere instead this time. Got it. What if they're signs meme coins, but they do send some of the, if they ever get acquired, they send the revenue back to the token. Would you have a problem with that? Do we lose him? Turin, rage quit. He didn't like they were saying kind words about D.Sai. I was, I think this thought experiment I was bringing up for him just made his brain break. And so he had to exit. Anyway, we're at time. So we got to wrap. Thanks, everybody. Thanks, Casey for joining us. And we'll see you all next week. Ciao, everybody.