🚨LIVE: Saylor's STRC Back to $95! Claude Mythos Release?! Coinfund Partner in Tower On AI

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[music] [music] Heat. Heat. [music] >> [music] >> 17 floor. We'll see you around the timeline.

[music] Feels good to be back. I think the rollup [music] is one of the most premier media brands in crypto and Andy and Robbie are great experts at everything they talk about and it's my favorite podcast. [music] >> Adding into my library every day potentially multi-chain deployments. Here we are at day [music] one here. I'm testing from base. [music] [music] [music] [music]

>> [music] [music] [music] >> Heat. Heat. [music] >> [music] [music] >> JP Morgan, Black Rockck, DTCC, Fidelity,

the entire thing was just institutions. It's just it's next level. This industry is going to the next level. And guys, I I don't know what else to say. >> I'm bullish. >> He said it. He finally said it. So bullish. >> It is bullish. I'm bullish. We're bullish. [music] [music] >> [music] [music]

>> Heat. Heat. [music] [music] Heat. Heat. [music] [music] >> [music] >> Corola [music]

is headed to the top. If we're not already at the top, we're going to the tugos. >> Roll up is my favorite. >> People from all walks of life, all over the world, all over this industry come together for the roll up. [music] [music] [music] >> [music] [music]

>> Zoom out. The institutions aren't coming. They're simply here. Taste the golden age of crypto, guys. Get right. Let's go. [music] Welcome to the next. See you on the show. Let's go, baby girl. Let's go. Welcome back to the tokenization tower live from the nest, the financial capital of the world. You are watching the rollup. It is June 9th and we have a great show ahead. As always, we are live in the nest here in New York City powered by our friends at Plume in the Nest bringing onchain asset management infrastructure to the masses during ETH comp week. Guys, I don't know what it

is, but whenever there's a conference, man, things things struggle. Things struggle. What's up, new type? What's going on? Good to have you in there. I see you're already dogging me for humanity protocol as if I was in charge of what was happening there. Uh, certainly was not. And yeah, that was uh we're going to talk about that because people are saying that that token dump wasn't even a actual exploit, rather a foundation team member uh moving the tokens kind of on their own and claiming it was an exploit. So >> guys, happy June 9th. Market's a little bit red today. Um not that bad. I am

seeing stuff on the timeline about uh you know different different takes on what's happening to Bitcoin and the market and stocks are red. So Arthur put out a blog post as well. It's really weird like you have these like Catrini guys coming out and saying like hyperlquid trade idea is the trade idea and then and then you got like guys like Arthur saying like this AI trade's coming to an end and how do we you know where do we go from here? I don't know. What do you think? You know, like do we go up, down, sideways? Couldn't tell you guys. We made the tickers bigger for you all. So, in the chat, thank you guys. I know that you were you were waiting for that. Uh made the tickers bigger. Got the brand bigger, readjusted some of the

uh sizing down here on the time. And Robbie's flying to New York right now. So, he's going to be on the show with us tomorrow. We're going to get into the markets. We're get into the news. We've got Coin Funds founder in the tower. We got Marcus Weather. He's going to talk to us about AI, what they're doing on the investing front in the AI landscape. Again, guys, if you're in the chat, I see you. I will I will rock with you. We're not going anywhere. Red days, green days, whatever it is, we've got tons of ETH comp guests. So this week in New York, there's this ETH comp event and there's tons of founders, investors, builders doing meetings, pitches, whatever. We were at a bar last night

and the Knicks lost um at the very end. It was it was close and apparently people were really really upset about the the quality of the crowd. They were saying that it was very very not that much energy, you could say. So yeah, crickets indeed. As always, our topics are powered by Treasure. Use code rollup10 at treasure.io to get yourself a Treasure. Let's move into the the weather and markets. Before we do, let me tell you about Forex. Building infrastructure for the future of digital money. Open, stable, borderless. Visit frax.com today, guys. It is a beautiful, beauty of a day in New York. 76, sunny, feels like 77. Relay.Link is always

powering our weather. Use relay.link link for all your crosschain swaps, guys. I know it's a little bit rough out there. I know it's not what you wanted to see. I I don't We'll We'll go through some of the charts and markets and stuff. Um but yeah, I know it's not what you wanted to see. I mean I mean Bitcoin does not look good and the stock market does not look good. Arthur put out a very bearish article and it doesn't look great. I think we're going to have chances to buy your favorite assets on a discount. I I I think it's I think it's coming. I mean, look at the tickers here. There is still some green in the stock market, but most everything in the crypto side and the tickers, if you look down here, is pretty much uh is pretty

much Yeah. red. So, let's get into the markets. Then, before we do, let me tell you about dinari, our tokenized equities partner. Use onchain stocks anywhere. Do more with your stocks at dinari.com and their dshares product. All right, guys. Bitcoin down 4% under that 61 level. Some gigawa whales holding up Ethereum at 1620. Inshallah, mashah, wishing you the best. Um guys, Salana is under that 64 65 mark that we saw it at. Chain link under that $8 mark near hovering at that $2 mark. One of the only ones that is like kind of up from where we usually cover it at. Um yeah, man. I mean, hype

is sitting under 59, Bitcoin under 61. And I think the big story today is is if you look at the broader markets, you've got uh the NASDAQ's down a percent and a sorry, two and a half percent. Holy The NASDAQ's down 3.8% today. Huge, huge red candle ahead of this uh IPO season in the market. Wow, that is uh that is rough. Yeah, new type. What happened to humanity? Yeah, we can talk about it.

We'll talk about it. All right, I I I I promise. As always, guys, our markets are powered by Zama. Zama is private confidential asset transfers on Ethereum and other blockchain networks. Visit zama.org to learn more. We're going to get into the news. We're going to get into what's happening, the Nicks game, the market, everything. Before we do, let me tell you about Near, our premier partner with the new ad here for near.com. One account, no borders, your financial life all onchain. We had Mando on the show telling us about how this was his favorite new app on chain. He was talking about how this was his favorite new app on chain and [snorts] you love to see it. So getting into the

news guys, top crypto companies send a joint letter urging Congress to include legal protections in the Crypto Clarity Act. So, if you guys recall the conversation that we had with Cody Carbone, he's the CEO of the digital chamber of commerce and he talked about how the yield issue was more or less resolved and the kind of bigger issue at hand right now was developer protections as well as just like other um other like small but but not minuscule issues in the clarity act. So it's really really awesome to see the collective of you know all of these VCs to L1s to

investors come together and try to you know basically push for these developer protections. The way I think about developer protections is basically you're a developer think about uh tornado cache right they go out they build open source technology they invest into a lot of these companies they build this tech and then the creator the lead dev of cache is under immense political and jurisdictional pressures because of the open source open source code that he created. We don't want that to happen anymore. We we want developers to feel comfortable building open- source software in crypto onchain and we don't want all this brain drain going into AI

or going into other sectors. If developers feel like they're going to be under legal scrutiny to build in this industry, that's a problem, right? That's a that's a serious issue. We cannot have that and this is something that I think needs to happen. So glad to see it. Glad to see these teams pushing forward on it and until the Clarity Act gets more, you know, let's say closer to the finish line. To us, it's just like this neverending clarity act, clarity act, clarity act. It's kind of just like somewhat repetitive in that way. GM Shine, good to see you, man. Hopefully your portfolio is holding up. You were right on the Spurs. You would have won

$200 last night on if you if I bet it. I knew I shouldn't have. I'm glad I didn't. Uh, but you won. So, congrats there. Spurs did win. All right, let's move on into the next topic, which is anthropic. So, I think this is like some of the lowest DeFi sentiment we're going to see in a while. This model CLA Claude Mythos is expected to release tomorrow. A Mythos one tag was briefly spotted inside the Claude Code UI last week before being pulled. Um, Mythos found 271 vulnerabilities in Firef Firefox alone, 15y old bug in HTML engine, 20-year-old flaw.

Mo Mosilla went from patching 21 security issues per month to 423. When Mythos was first leaked in March, all of these stocks dumped. The S&P 500 software and services index fell 2.6% 6% in a single session and is now down 12%. And I mean, yeah, I don't know if this is exactly why crypto is dumping today. It could have some correlation, but I mean, broadly speaking, people are pretty terrified about Mythos right now.

Like pretty pretty freaking scared. I mean, I don't blame them. I don't think it's going to have as rash of ramifications as people think. But man, to think that all DeFi protocols are going to have to go through a real real like understanding of their security parameters, rewiring of the infrastructure and just kind of like undoing of what's been done. Wow. I mean, yeah, it's uh no problem. Just give me a 100x pick. Yeah, I don't I don't know, man. I don't know, man. Um, the 100x picks is like staying safe

right now. That's how I feel. I mean, there's there's volatility out there. Bitcoin's up, down, sideways. Hype's up, down, sideways. All the good coins are down good bit today. Um, yeah, it's it's it's rough out there, but we're going to talk about it. So, don't worry. We're going to be all right. We're we're going to survive this. It's just a little small nick. Bare market's going to continue a little bit longer. You're just going to have to survive. Things are going to get a little bit shaky. Probably they're already a little bit shaky, but sense of it can get a little bit worse. We're still kind of in like this emotional capitulation phase, but not like hatred and depression and apathy. We're kind of in like

we're in like the you know how those like the pre- rich when like you think you're going to get like you know something's going to pump you're excited you feel it kind of feels like we're in like the pre the pre- depths of the bare market mode right now. So all right we're going to move on from mythos. Before we do let me tell you about Infinifi, our DeFi partner here on the show. Higher yields, no leverage, transparent capital efficiency, earning the highest yields in DeFi. That is infinifi.xyz. We got our friend from Zama. Institutions will bring trillions on chain. The pie is about to get way bigger, but they'll need privacy to do it. That is a non-negotiable.

Guys, if you haven't seen the Canton chart in a while, I'm going to pull it up real quick on my side. I mean, it is a 16 to 17 cent stable coin right now. It has had zero reactions to any of the upside or the downside in the latest market swings. it is completely removed from the market. Like completely removed. So it's interesting. Zama is on a different kind of train here. Let's let's hear what Rand has to say. We had him on the show last week. I think he's right. And I think the way that they're thinking about privacy is quite a bit different than canon.

Trillions are moving on chain. Trillions are moving on chain. Like we had billions before. And so the size and the opportunity for what we're doing here with institution is just massive. Massive. >> Absolutely. Yeah. I I was talking to someone in PE the other day and the dollar kind of figures that they were quoting made it feel silly kind of the dollar figures that we're talking about when we talk about TVL on DeFi protocols in the crypto space. It's almost like we're fighting over this fixed pie and you bring up this whole other pie of real world assets that's, you know, orders of magnitude larger than than anything that exists kind of in DeFi, native DeFi.

>> Trillions are moving on. >> These are the things that like this is why you have this crazy sentiment gap right now. Like companies like Zomar are doing extremely well. They're onboarding institutional flows. They want privacy. they want to be a part of kind of like what their offering is. And then you think about it and you're like, okay, I could buy the Zama token, like that's, you know, an option. I could buy the Zcash token if I want to invest in privacy or Canton. But otherwise, you're sitting here kind of like looking around and you're like, okay, I know the institutions are coming on chain. Uh I know they're going to bring a ton of assets on chain, but like how do I how do I maximize that like as an investor? Like that's our job on the

show day in day out. Like how do we how do we figure out um how we can get ahead of these flows and like right now it's not that obvious. Obviously the Bitcoin ETH the kind of majors Hyperliquid's been you know a big proponent of this but but you just wonder like how how is there such a sentiment dislocation where we know we are in like the golden era of expanding this industry's TAM everything that it's doing and standing for yet the investable opportunities there's like a whole reckoning happening in the space.

It's just weird. It's just weird. Like Rand is right. And so let's get into that then. Let's get into Zcash. M is tweeting here about Ironwood, one of the most bullish things in the history of Zcash, ZK privacy in general. But everyone is sleeping on the bigger news. The pool the pool will be formally verified before Ironwood rolls out. So the risk profile will be multiples. It will reduce multiples before the upgrade is even live. And so guys, if you listen to our conversation with Ilia and Mert, that was last Friday or Thursday, we talked about how basically formal verification of these ZK and privacy systems are crucial to be able to make

sure that there's not an infinite mint bug. And so they're going to go through and push this upgrade, right? And like you're going to we're all going to know in the orchard pool of Zcash how much Zcash was potentially infinite minted. And so we don't know now necessarily. Uh we don't have the answer, but the good news is we're going to get the answer. And we're going to have formal verification of the ZK circuits before it even goes live. And so that means that, you know, we're in a decent spot in terms of we're going to have the ability to know how much Zcash was minted and know that

that that issue cannot happen again in this next version of Zcash. So interesting. I got my Zama socks on today, guys. Um I'm repping privacy. We're bullish on privacy on on this show. So we're we're gonna keep firing away. And I think it's an important trend. I think it's an important trend. Even if it's not maybe the most like investable trend right now, if you don't hold Zcash, you don't hold Zama, if you're not bullish on the shielded thing, it's something that we need to get right. And like I said, guys, Canton is looking like a 16 cent stable coin right now. Like, it's pretty it's pretty wild that the market has been up, down, and sideways across the board, and Canton has just kind of been flo

floating around at that level. It's interesting. It's interesting. Some some would say supply control supply control, others would say fundamentals. Answer is probably somewhere in the middle. All right, guys. We're going to get into Sailor cuz he's been he's been he's been all on top of it. Before we do, let me tell you about Lei, our premier crushing partner. Lei is your universal market access for digital assets. Visit leap.fi to learn more. So, Melrode is saying Sailor is strategy, Sailor Strategy is buying Bitcoin at 2x the rate that miners can produce. They produce about 450 Bitcoin per day, roughly about 10 to 11 billion per year at current prices. But Strategy has

already bought 11 billion this year, and we're not even halfway through the year. So, let's go ahead and listen into what Sailor is saying here live on the ground floor. NYC, it looks like uh hearing more about his market purchase plan. I don't think we're out of the woods yet on Sailor, guys. STRC is down to that down to that $95 level. Um, as I just put in the chat and it's it's yeah, we're going to there's some work to be done here. So, let's see what sailor has said. >> Wow. >> The miners produce about 450 Bitcoin a day. That works out to say 10 to 11 billion a year, >> right? We bought 11 billion dollars of Bitcoin so far this year and we're not

even halfway through the year. So, we're already buying at 2x the rate at which they're able to produce it. Um the the digital credit business STRC has been an explosive success. It's gone from 0 to 10.5 billion outstanding in 10 months, but we sold about $2 billion of that credit in May, which means we're at a $ 24 billion run rate. So just that one instrument alone is going to account for two to threex the Bitcoin supply that's produced by the miners.

>> But how does that work from supply demand type of dynamics? I mean if you're absorbing everything that's being produced right now, if you're looking to buy Bitcoin, then you're looking to buy it within what is in circulation away from what is being produced as well. >> Yeah. Once we've bought all the Bitcoin available by a natural seller, the price has got to actually move up to find a willing seller. >> So, the way to think of it is there's a there's a consistent bid that covers all of the natural organic sellers. And once once that happens, every single time 10 billion dollars of capital flows into this marketplace, that's one year supply or one turn on the axle. So, you know, $10 billion or more may flow into the

ETFs like IBIT. That's one source of demand. >> Banks are creating credit. So, when a bank issues or creates10 billion of credit against Bitcoin, that's another year supply. >> Other companies like Strive or >> All right, we can just hit a pause here on this one. I think um >> I think Sailor is a little bit over his skis right now, guys. I think he is uh unaware of the amount of main character arc he has created for himself. And I think I think the market is like has always been prone to just try to just do its best to just take these take these types of people out.

I'm not saying that I don't think he can get liquidated. I don't think he's in trouble. I don't think he's got like I don't think, you know, people think there's like this worst case outcome for him that's like, you know, oh, he's going to have to sell all his Bitcoin and if we go down to 8K, he's like, you know, he's going to sell it all. So, I don't think it's like as drastic as people make it to seem, but man, man, do I think Sailor is going to have a bit of a He's having a rough time right now.

And I think he's going to have a bit a bit harder of a time ahead. And the stretch product's going to continue to be tested. I mean, where where is it trading at now? I I just said it was at 95. Let's see where we're at. Yeah, we're at we're under 95 now. So, yeah, that's a funny sound. Yeah. So, all right, let's move on from Sailor, guys, because this is another this is another just insane happening here. I mean, I mean, block A detected an ongoing incident targeting the humanity protocol on multiple chains.

Multiple wallets drained to attack her addresses on Ethereum BMBB chain. $10 million of H move so far. Evidence points to compromise key, not a token contract exploit. More details and thread if we scroll down. So, guys, people are saying that this humanity protocol exploit was not an exploit. They're saying that it was actually a kind of like actual like hack or like an inside event and that there was owners of the keys who uh taking over the proxy admin minting new tokens and this never should have been able to happen. Awesome segment. Thanks, Rugrat.

Good to see you, man. He's gotten through worse. I think they'll do fine at the expense of BTC. Yeah, I think they're going to do fine as well. Um I believe so. He only sold he only so sold 32 Bitcoin. Shine says yeah, he did only sell 32. Um and only 32 of his you know what is it like I don't even know how much he owns now, but billions of dollars worth. So yeah, I mean whether I think Sailor is going to survive or whether I think Bitcoin is going to go higher or lower is kind of kind of irrelevant. I think the main thing that matters is that his antics don't continue to spook out large

allocators from the market. Like I think people look at the market, Bitcoin especially, and they're like, well, Sailor's got this huge leverage position on why do I want to buy this thing? And I think that's the problem is like the perspective and the narrative more than the actual order books. So that'd be my take on it. All right, guys. We're going to get into our daily equity segment. Um, interesting interesting day in the equities market given the dumpage. Um, again, I told you guys earlier, we got the uh we got stocks just wow. S&P down 2%. NASDAQ down

3%. 3 and a half%. Uh, Bitcoin down 2.68%. Wow. Thank goodness I got out of that uranium trade. My goodness. Thing is smoked. smoked and not coming back anytime soon. Yikes. All right, guys. Let's get into the daily equity. All right, guys. Daily Equity brought to you by our friends at dinari. Investor positioning has rarely been this heavily concentrated in tech.

US equity positioning in large state in large cap tech is up to 1.0 points, the highest since October 2025. This marks a sharp reversal from negative.4 points seen in late March as the market bottomed. It is now higher than it's been 97% of the time in the last 16 years. By comparison, overall equity positioning stands about point4 points above only 65% of reading readings since 2010. Let's go ahead and scroll down here to look at this chart. So you guys can see that overall positioning in large cap tech is just exploding. I mean we've got this AI capex trade. I mean, guys, I was at I was at the bar watching a Knicks game last Friday or no, it was Saturday and I was talking to a guy who

was like telling me about his positioning in the market and he told me straight to my face without any hesitation, my largest positions right now are 3x levered semiconductor ETFs. ETFs. So, how do I even look at these semiconductor bull ETF? Yeah, he said this was his largest position down 20% today. Dude, I looked at this guy and I he was like, "Dude, I'm up like 90% in the last two weeks. Like, what could go wrong?"

And I know that like I'm not one to talk like I it's not like I didn't just roundtrip my whole per position and and it's not like hype just went up like to 75 then back to 55. Like I I get it. Like I'm not one to talk here, but this is the current state of things. Mega cap tech is crowded people. Like this guy is like a 23-year-old Dartmouth grad, works at Blackstone and he's like my largest position is a 3x levered semiconductor ETF.

And I and I stood there and I was like, "Oh my gosh." You know when like you get like a little like like like there's like a little like top signal kind of vibe and you're just like you like think you like hear it. You're like, hm h is it retail or institutions driving this overweight in the market? Nobody's provided clarity in this. I think you just gave insight to my question. I think it is retail. I think it's retail more than anything. I think these guys are piling into this trade because AI bottleneck gigas. I mean, look, the stock market has been the stock market has been acting like the memecoin market for the last two months. It's unreal why people in crypto are so disillusioned by it. Upset and distraught about the

performance of crypto watching all these stocks rip. I mean it's no it's no question that the semiconductor ETF is down you know 20% today on the 3x lever long. I told the guy I was like man you know you you every time you hold it you face decay in the market. And so anyway guys, I am not I am not looking at this tech stuff right now. I'm not investing in it. I am just watching from the sidelines and it's crowded. So guys, that's been our daily equity powered by our friends at dinari. We're going to move into the next tweet here, which is a tweet from our friend Victor.

Shout out to Dinari powering our daily equity segment. Victor says this is the third crypto bare market, but for some reason it's the hardest one for him. And I think guys, this is so I quote tweeted this. I was like, I don't know. I don't I don't share the same experience necessarily. You guys have been great. The show has been growing. I've been loving all the interactions with with you guys. Oh god, here comes regulations to quote unquote save retail. Did can you get the CEO of Backpack on the rollup? Did you see the latest news? Yes, we are going to get them on the show. We have been talking to them. Uh, I think they're doing great work. Folks getting wiped out left or right. None of us know what directions we're going. Yeah, I mean, uh, Hyperlid accounts for nearly half of

crypto token buybacks in 2025. Catrini Research said Hyperlid is a compelling investment. We have a pug in the office today. A little small pug. Rugrats says he's sitting it out. I am also sitting out the ETF or the I'm sitting out the whatever it is the the I'm sitting out the semiconductor AI bottleneck stock market trader now as well. I I don't see it. I'm not I'm not getting involved there. I just can't. Um it is weird to have an an article from Arthur that is so bearish and then Citrini to be so bullish. It's kind of weird confluence. So, you guys have made this bare market easier. So, I thank you

for that showing up, being part of the, you know, community here, learning with us, having fun, making trades with us, you know, being part of the market. It It's been great. We're super grateful. Super grateful. But I can understand why this would be a hard bare market for Victor and others. And it's because not only have we lost asset value and prices and numbers, right? like it's not been an easy market, but like we've also kind of lost the we've also lost the like love for changing the world. Like we've lost the we're going to take over the financial system because we can, because we can do it. We're going to build better

technologies that are going to help people. We're going to bank the unbanked. We're going to scale the financial system. We're going to do all these things, right? And honestly, these have lost. We've just lost these things. We've just not like people have came out and they've just not had the same level of enthusiasm for what this technology can do. The institutional allocators have came in and co-opted Bitcoin. So, people have like this has been a hard bare market because also we topped on apathy last cycle. like it wasn't like a euphoric everyone's getting rich blowoff top alt season. It was like this like

sad boring early top that was like surprise people >> and so yeah I mean Arthur Hay sold his hype Zcash etc. again. He's definitely sneaky. Says he's going to use derivatives for tactical shorts. That was lost this big moment that the big players That was lost the moment the big players came on. The soul of why Yeah, that's what I mean. The soul of why we got in is disappearing. And that's why I think that's what I think Victor means here. And I agree. But I think again from from our side, this has been one of the easier bare markets.

It's less volatile. I've managed a portfolio better. We managed the business better and we just we've, you know, we've grown. We got the office, you got the studio, we're like scaling. We're we're in it. We're showing up. So, that's kind of all I can provide for you guys is just stay in it. Show up every day and, you know, learn something and be a part of it and be patient. I mean, I think we can let the market come to us a bit at this point. So guys, we've got our first guest of the day, the first and only guest, Jake Brookman of Coinfund. He is a leading investor in AI and crypto and more.

We're mostly going to talk about AI, mostly going to talk about what he's seeing out there. Um, a couple interesting deals, what the investment angles are, what's happening out there. So, I'm going to pass you guys over to our lovely, lovely commercial break. Enjoy the I think we're getting some new B-roll for you guys, by the way. It should be in there soon. Um, and you guys are going to enjoy that. For now, enjoy the current break. We're going to get Jake set up really fast, get him in here and get started. You You guys came up, been watching for a bit. Thanks, Sean. Appreciate it, man. The market maturing. Happy. The rollup is maturing with the market. I love the bark sounds.

Thanks, guys. We'll see you guys live with Jake here in just a minute. All right. >> [music] [music] [music] [music] [music] >> Money power.

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You know, [music] we get deep. We get deep know. We get deep. You know, [music] we get deep. We get deep know. Welcome back to AI Supercycle, [music] our premier AI show airing every single week presented by Near. We cover the ins and outs of decentralized AI, privacy, [music] and the future of this massive technology. Near is the blockchain for AI and the execution of AI native apps.

You can check out Near's latest AI product at near.ai. Now, sit back, relax, and enjoy the show. >> [bell] >> Going 70.

Ladies and gentlemen, welcome back to AI Supercycle. This is episode number 37 powered by our friends at Near. Visit their near.ai [screaming] products, learn more about private inference and more. I'm here with Jake Brookman. Jake, welcome to the tower. >> Thank you. Thanks for having me. >> It's good to have you. Jake is a founder and CEO of Coin Fund, one of the earliest and longest standing funds in crypto and digital assets, now more predominantly also in AI, other sectors. I'm sure you're dabbling in robotics perhaps. Um, computer scientist, grew up in St. Petersburg, Russia. interesting background, Jake. Good good to meet you here. Um, and let's have a conversation about investing in AI. NASDAQ's down 3% today. IPOs are coming out. Mythos

released tomorrow. There's a lot going on. Um, >> how are you doing that? >> Doing well. Well, I just want to clarify. So when we think about investing in AI at Coinfund, which is a historically now for 11 years has been a crypto firm, we're literally we're really thinking about the intersection of AI and decentralization. So I just want to be clear that the investments that we're making are very clearly in that space and we don't really do pure AI plays but that intersection I think has some of the most interesting highest riskreward bets in AI and it's also advancing the state-of-the-art of AI itself.

>> Yeah. Yeah. I mean we've we kind of had these iterations of the AI times blockchain right there was like this early decentralized inference decentralized training kind of like the Akos era and then we moved into like this Salana memecoin attached to a Twitter account AI agent era and we kind of enter like this agent era now we're now we're in like this Venice is this really cool private uncensable chat GBT era companies like Ant seed and other kind inference-based uh token production companies are are are getting a lot of traction and now like entering into like the agents using uh blockchain era I feel like of the space. I know you're

very very bullish on the decentralized nature of bringing these kind of AI suite to the market. Can you just give us your highle thesis for this convergence and kind of as it pertains to this evolution? >> Yes. So, first I want to say yes, we have been following this space for a while. I would say like our first investment in the space was Sam Alman's what was known as Worldcoin back then and world now. That was December of 2020 or January 2021, I think the deal closed. >> Um, and then in March of 2022, we made our first investment >> in really decentralized training with our investment in Jensen AI. So, when we launched our decentralized AI thesis, it was September. It was published in September of 2022. This is before chat

GPT came out >> and um it is the same today that it was in September of 2022 and that is we think that decentralized networks can start to disrupt the supply chain of how AI products are made and the core problem of being able to do that is to train AI models in a decentralized network. Now what you know what would you guys tell me if I said listen you take these processes that today are in these giant state-of-the-art data centers that some companies are building nuclear power plants to power that contain industrial strength GPUs whose who have hundreds of gigabytes of memory

terabytes per second of throughput and like this is what it takes to create a giant frontier model and what if I told you that I'm going to do the same thing by going on regular 80 megabyte per second consumer internet using people's gaming devices and even their MacBooks. >> You would say, Jake, that sounds crazy and it's probably impossible. Yeah. >> And four years ago, that is exactly what the AI experts in San Francisco and all my AI friends from Google told me as I was making these investments. Um however, four years on, not only did we show that this is possible, we have a number of companies that are now

essentially in a race where they're creating bigger and bigger uh size models in this way. I think the the latest just from last week is 100 billion parameters from a company called Macrocosmos and Bit Tensor. And this is really like heading for certainly commercial viability but maybe even like frontier grade size >> at the end of the day trained with these decentralized methods on hardware that is commodity hardware that wouldn't be able to be used in a data center if we wanted it to be.

>> Yeah. Um, so just completely incremental compute in a market where more than ever before we need to counterbalance the centralization of power game that these big companies are playing >> and in a in a market where no one can get access to compute um, and can't do so cheaply. >> So that's the thesis that's been playing out over the last few years. And and a part of that thesis I I I think that is going to end up working in your favor is likely this also this kind of desire to go into local models and and running local instances of an LLM at home or at your workplace, right? How does this how does this trend towards these localized

usage of LLM? How does that play into your thesis of kind of distributed compute, distributed intelligence? So earlier this year we saw a lot of people dabbling in openclaw. These days people dabble in Hermes agent right at the same time almost by accident there's a hardware trend that is putting more and more powerful GPUs on people's desks. Notably this is being done by Apple with their M5 uh suite of uh chips. And literally right now you can go and buy a MacBook Pro in the store and that will have a powerful enough chip for you to run a really significantly sized model like very fast. There's other companies other than Apple who are kind of playing

in this hardware niche where you know a proumer can put you know essentially like a you know data center grade GPU on their desk and among proumers and among enthusiasts we're seeing that people want to um inference locally they want local type privacy to their data and also they want to run agents that are that are kind of sovereign to them and go around making them money and and and doing all these things. So, I'm very bullish. Like the other kind of side of my decentralized AI thesis is we're also seeing the rise of these like agentic swarms. These swarms are starting to optimize problems. They're solving like previously unsolved math problems. They

are um optimizing Google's like quantum circuits to break ECDSA. >> And very soon they're also going to be doing inference. They're going to be doing training. um and they're going to be running your personal agent. Now, you know, the the kind of the better um the better models we can kind of provide for those agents, the more of a shot we have of collecting a bunch of people's data and then putting them in putting that in a model that they all collectively own and not necessarily like sending it to Sam Alman or Dario Amade at Anthropic.

>> Yeah. Yeah. And and so these swarms you talk about this evolution we've we've heard you know this term talked about and and we've understood like these you know agentic collaborative abilities you know you know whether it's a team for a company or a signing task or or like a a whole unit of a of a company or a team. what has been the agentics like like how does the swarm uh concept tie into the decentralization thesis like h how how are those two at all uh you know like correlated?

>> Well, I I I think the agent in a sense is some of the most decentralizing technology, you know, that you can have. And so if you can imagine a world like everyone in traditional VC and in web 3 VC and in cryptovc and in AI they all kind of agree it's like super consensus that there's going to be a lot of agents. There's going to be billions and zillions of agents and those agents are going to be acting on your behalf. They're going to be doing commerce. Now if you imagine a world where like every person has a personal agent for example or a significant number of people have a personal agent that are solving problems on your behalf that are doing shopping that are performing commercial activities that are investing on your

behalf doing finance on your behalf finding investment opportunities etc. Then this requires a high degree of essentially decentralized tooling. It requires this, you know, agents to be able to pay each other. So decentralized rails for payments, for settlement, you know, for authorization, for compliance. It requires um coordination among agents. So, we've seen this amazing example the other day from IGEN Labs where Google uh put out this paper about quantum circuits and they said, "Look, we could we're now so much closer to solving with a quantum computer when we when we got there, you know, breaking ECDSA encryption." And so, we're

Bitcoin, you're on notice that, you know, you're going to get hacked very soon as soon as this happens. And so, they advanced the state-of-the-art, but what they said was, "We're not going to tell you what the scientific innovation actually is. we're going to censor it. We've been talking to the government. And about a week later, a swarm of agents came together and they worked on this problem. They kind of concentrated the agents to think about this problem. And what they then did was they discovered the same kind of optimization that Google did in about a week. And then in about a week later, they were 40% more advanced than Google in their paper. And now this thing is open source, right? So like you could really

look at that and imagine, wow, that is an incredible like democracy technology that is like opening up these things, making them available. But it also needs incentivization. It needs like the problems that it needs to be solving, need to um, you know, make the agents money. And once that happens, I think there's going to be a ton of incentive for people with personal agents to put those agents out there in the world. Now, my point about um you know what why does this necessitate web 3 technology is to concentrate a swarm of agents on a problem, >> you really need to give them sort of a shared context, a shared memory.

>> And there's some startups starting to come out into the market that are doing that, right? that are enabling swarms of agents to collaborate, you know, essentially using decentralization technology. So, if you ask me, when there's going to be a ton of agents, they are going to motivate more decentralized tooling than has ever been motivated before. >> Yeah. You know, I I I think in that context, there's been this kind of like market awareness expansion as of late about the uh bullish investment thesis or the understanding of the value of inference specifically when it comes to the stack. Like a lot of people were very bowled up on okay, the compute

demand is just going to keep going higher, build data centers, the models are going to keep getting better. Like just like you know, that's where a lot of the value is. But now there's been like a growth of companies doing a lot of work just on inference and making inference as as either private anonymous or just better. Um why do you think this has happened as of late? like what has been the like the light bulb moment for the market understanding that inference is something that is very very valuable in the AI stack and and and there's also now you know there's companies like ANC there's a you know couple others that are doing like open marketplaces for inference as well on chain how do you like why do you think this happened why

did it take so long and why is it valuable yeah >> yeah so so if you take a look um at kind of the broader AI market it is unquestionable Almost every dollar of revenue that's been generated this market has been generated by inference on desirable foundation model. So it's not being generated by like hey we'll give you training services you know or something else right consulting. Most almost all the revenue that's been generated has been generated by people hitting anthropics API open AI's API. How much money is that? That's about 6065 billion dollars of ARR right now.

It's about 30 billion from Enthropic, about 25 to 30 billion from OpenAI. There's a long tail there. Some analysts are saying just Enthropic can have 100 billion of AR by the end of this year. And the five-year outlook on that is something like 500 billion to 1 trillion of inference revenue, you know, by 2031 essentially, right? there's been $600 billion dollars invested by the big companies in AI infrastructure to make that growth, you know, kind of happen.

So, I think one of the reasons that people are interested in inference is because they sense that like this is the core modernization of AI. This is an incredibly big and growing market. >> And when I have seen now, let me let me take a web 3 perspective. So historically when I've seen inference networks that hasn't really made a ton of sense to me because the inference game to the consumer or to the customer is about making inference fast and cheap. It's about like fast cheap compute economies of scale, you know, and when you try to provide inference on a decentralized network, you're actually paying more for that because you got to pay for the decentralization. And so for a long time it didn't make sense like

how can you make something that's more expensive like actually cheaper >> right >> and now there's been some interesting solutions to that which is hey by the way we have this blockchain that when you're doing the inference those same matrix multiplications that are happening to get that output are being used to mine cryptocurrency and this is a concept known as merge mining historically crypto and so there's some view that like hey if this cryptocurrency can subsidize the inference we actually can make the inference cheaper. >> So inference looks a little decentralized inference I should say looks a little bit better in 2026.

>> Yeah. Yeah. And and so the market like the market came to realize that that was the big revenue generator for this AI stack. Uh obviously it's very it's very concentrated in these in these names. Is part of your thesis just that the the the just if a couple of these decentralized inference providers or decentralized training providers just get like a little bit of of the current existing market share that is just a massive 100x from here for these companies like how simple is the math on like just chipping away at bits of the broader market here.

>> I'm so glad you asked. So this is why there's a subtlety here. So in decentralized training companies like one of the questions is what are you training? So a lot of the decentralized training processes that have happened to date essentially produce open weight models where everybody knows the weights. And the problem with that um state of affairs is that openw weight models are very hard to monetize. This is why you're seeing in Chinese labs today, you know, Chinese labs and meta have historically been the companies that have produced the most openweight models. Yeah, >> you're starting to see a trend where yes, we have a bunch of openweight models, but they're starting to close source kind of like the training setups and they're starting to close source like the really really good models

because these models cost tens and hundreds of millions of dollars to train, but then once they're out, nobody's like paying Meta for that. Nobody's paying the Chinese labs for that. So, they do need a business model around that. Now, in the decentralized training world, you've had these processes that have produced open models that are like hard to monetize. One of our one of the companies in our portfolio called Plurales has an answer to the question of like how do you monetize these things and in their algorithm what happens is the model gets broken up among different uh you know GPU providers in the network and so there's no individual or company or government sound familiar?

>> Yeah. >> That owns the entire weight set of the model and so the model ends up living kind of in the network. the network like if you want to use it, you have to pay the network to do an inference. And so the answer to your question is with this type of monetizable decentralized AI, if we can win like 10% of training, we also win the inference associated with that training. >> And that looks to be, you know, something like a 50 to$undred billion dollar market over 5 years.

>> Yeah. There's only one company in the world today that has enough technology uh to to implement a model like I just said. >> And when it comes to the weight being o like open weights, right? Like why is it important that why is it important that there's not one entity that controls the weights behind a model? Like could you just unpack what that means a bit more? >> Yes, of course. Because if if there's if if someone has the full weight set then they can like do with the neural network whatever they want. They can optimize it. They can quantize it. They can run it you know on their MacBook >> and just inference it for free. If you don't have a s single entity that has

the entire weight set, it means that um the collective of people who do can charge a fee to inference the model because the network will require them to put up their weights for the model to be inferenced, right? And so the difference between an open model and an anthropic model is like here the the weights are totally open. Here the weights are totally closed. What I'm talking about is a model whose weights are closed which gives it a business model, >> right?

>> But it's publicly owned. We can be we can be a a token holder and we can receive the revenue from each inference >> from the inference. Yeah. >> And and Okay. So if we get the training, if we chip away at the decentralized training part of the market, that then guarantees that we also get the revenue from the inference. >> Yes. Because if the model is trained in the decentralized network, then the customer has to pay the network to get the output. So like Akos, render, bit tensor all these kind of existing decentralized training networks their mo is to grow their adoption of their training because then the revenue from

the inference that will be you know can come back to them in some in some fashion like for example this macrocosm company that they mentioned doing 100 billion parameters sets for some of their models. Their goal was to get as much adoption of this of this of their training network to get the inference revenue. >> Yeah. I think I think like the the general MMO of decentralized training networks is we want to scale these processes to at the very least commercial viability. You know, I mean that can happen like as low as I would say like 50 billion to 70 billion parameters. But if you want like a really smart model, you know, you can go to a couple hundred billion. And like

kind of the the the ultimate goal is to get to the quoteunquote trill, right? Um and so yes, the I think the long-term game here is for these networks to source enough compute from from the world that they can actually start to be truly commercially competitive with things that Anthropic is doing, that OpenAI is doing. And we see that today like if you look at you know the the average commercial application of AI like you're some kind of you know consumer application you're a language tutor which has an AI backend like chances are most of your inference is running on open models that's because they're customizable they're 90% cheaper than the frontier models and they're

like 99% as good on the benchmarks. And so the goal is for uh these decentralized models to get to that point but be a little bit more expensive because they're actually providing like a better, you know, a better model overall, a lower cost model, etc. >> Uh kind of a bit of a tangent here. Have you seen the the goaround for this new AI kind of blockchain company called Pearl? >> Yes. >> Okay. Could you explain what Pearl is to us? >> Yeah. So, Pearl is sort of what I alluded to previously, which is like a clever like uh useful proof of work, proof of useful work, excuse me, blockchain, which enables merge mining of, you know, AI computations. And so,

it's it allows the cryptocurrency mining aspect and the fact that cryptocurrency is valuable to subsidize the AI computation. Yeah. >> And actually make uh the like for example decentralized inference cheaper for the customer. >> Okay, got it. >> Yeah. So, you know, we we were speaking about that earlier that, you know, that thing's getting, you know, sent around. I think there's like an OTC for it right now. It's it's pretty illquid, but, you know, people have been asking me about that quite a bit. >> So, so like the the um this this thread of like can decentralized things be cheaper is actually like a really important and nuanced one and I wanted to [clears throat] so this is like a great story like with decentralized training. So like initially as I said

people like decentralized training is impossible then you had a bunch of companies kind of come to market and say well it's possible because here it is we did it we used like a Google algorithm to do it and then we created new ones and we're now published this is now a a field which is being published in you know the biggest machine learning conferences in the world like Nurips and then people said okay you know what fine it's possible but you know what it's way too expensive because it's on these like dinky devices. And actually the reality of that is the opposite.

>> Really? >> Yeah. If you're a customer who wants to train a model, like a big one, right? And by the way, we just had a news item that Kirkland and Ellis big law firm is devoting $500 million to train their own proprietary model. Not to use Harvey or some other solution in the market, but to train their own model on their own proprietary data. So, you know, what we actually see is that a customer like that either has to build their own data center or go rent one. But the difference between a data center and a swarm of consumer commodity GPUs is that about half the cost of the data center is facilities, maintenance, cooling.

Yep. >> And capex and things like that. And when you go to the swarm, you don't have facilities, you don't have cooling. You basically like forego a bunch of costs. And what is the difference there? How is that possible? Well, it's just because we have innovated on the training algorithm itself. It now works in this context. And if you could if it can work in this context, then the costs are lower. So what we're actually seeing is that the cost of swarm training at least for the size of model that's possible right now is actually cheaper than if you were to do it in a data center.

>> Yeah. >> So first it was impossible, then it was like too expensive. >> Yeah. Then the next uh objection is like it won't scale, you know. So that's where we are. >> It won't scale to like the actual highest of quality of models. Like right now we're at like the 70 there's 100 billion or 100 billion parameter one input tensor but we get to 250 billion 500 billion where which is where these frontier models are going and this and this it'll be too expensive. It'll be not you you'll need more compute. Is that the thesis? Well, so another objection is like, okay, when you try to scale it, it'll just get too slow. But like all the practical data and all the practical results from these trading

runs suggests that actually um it tracks the loss curves of you know normal training processes like sometimes it's a little bit slower but there's like a lot of optimization to do. We have you know this is I'm talking about pre-training right now but there's also many other kinds of trainings that you could do. There's a company called gradient network that put out a paper that says when you're doing post training like reinforcement learning on these models you actually get a lot of parallelization and when you make this work on consumer devices and you can paralyze a lot you can actually 10 times lower the cost of this and 13 times the speed you know in a decentralization context really >> so there's a lot of research that like San Francisco like AI people are just

not doing because it's not like their focus right that actually makes this stuff in a decentralized uh context very very very competitive. And so if you look at the curve, if you plot the curve of like the number of parameters of models that have been trained in decentralized networks, it's kind of starting to go exponential. It was like 10, >> 40, 72 from Templar just a few months ago, big headline. Then 100 from macrocosmos. Then there's some early experience that are between 100 and 200 that have been posted on Twitter, but it's not quite a full model yet, right?

So you can imagine that we are going to go up that curve. What we're missing is qualified tech talent, AI talent coming into the space and you know doing more work. We're missing capital. We're missing more companies doing this. This is like one of the most exciting opportunities for web 3 because it has a hundred billion dollar market. >> Yeah. And so macrocosmos is the leader right now in this space. >> I would say macrocosmos currently has the the headline number 100 billion parameters trained on >> uh you know a certain strategy. Our company Plurales is the only company that has what's known as model parallel training which is the one that breaks up

the model into pieces. Yeah. >> And they're currently in an 8 billion training run which will start to ramp up in parameters over time. That's a much harder problem to solve. Um, and then there's other people, uh, you know, Jensen AI has done reinforcement learning, gradient network has done reinforcement learning, um, and NES research has done a little bit in like pre-training, but not sure if that's like a key focus area for them right now. >> Yeah. Yeah. Uh, have you used the the, you know, a tangent here, have have you used the Hermes agent much? >> Yes, I have. I'm I'm an open claw user and a Hermes user. Yes.

>> Okay. And and is is is Hermes as good as they say? >> So Hermes I would say so I have an engineering background. I study math and computer science. Um and you know it's just like a much better designed sort of product. >> Um and I think it's really really interesting to own a harness in this day and age. >> And what does that mean? I've I've heard harness like what does that mean? >> Yeah. It it it's so you have like the foundation models underneath >> and the harness kind of like puts them into a problem set, right? Like are you an assistant that's helping me, >> you know, calendar and do my daily tasks? Are you a researcher? Are you a coder? Right. And so Claw Code, that's a harness aimed at coding.

>> Correct. >> Open Claw is a harness aimed at being an assistant. There's other harnesses that are aimed at like, you know, doing math problems and solving complicated like research problems. Um, I would say Hermes is kind of, you know, more like general assistant. Yeah. >> Um, but it's just a the way it's been architected, I think, is a lot more robust and clean. Um, much cleaner than than OpenClaw in my in my humble opinion. Don't get mad at me, OpenClaw guys. I know you >> put in a lot of work, but but still I think I think her Hermes is just better designed product. And I think why harnesses are important is because they collect user data. One of the most important types of user data in in agentic AI, right, is how your agent

traverses the world and the mistakes that it makes and the things that it does to correct its mistakes. Right? This is data that you cannot buy. This is data that you can only generate and it is data that is like nearly infinite because you know agents can traverse the world in all these in all these different ways. And so today I would I would think that like you know people like anthropic every time somebody uses an agent on top of the enthropic API enthropic gets this it's called the trace data from the agents. Once you have a big bank of this data, then you can do reinforcement learning on the model to make your agent basically make

less mistakes to become a better >> agent. And so reinforcement learning or training happens after experimentation with a given model. So that's like what you would call post training. >> Yes sir. >> Okay. And is that just is that as simple as like me responding to the outputs and like trying to guide it in a better direction or is that done at like a deeper like lower level mistake? >> No, no. It's it's it's almost I mean like to some extent the user could be interacting with the agent and correcting him but most of the time the agent is just kind of like out there and it's like oh I'm going to download you know this library and try that. Oops, that didn't work and here's the reason why I should really download should should have downloaded that one for this

problem. Right? >> It does it on its own. It does it on its own, but it's like it takes so much compute >> to generate this. Remember like a couple of years ago, there was this big question. It's like, >> well, we just already put in the internet's worth of data into these LLMs. We're we're out of data. We're not going to be able to progress intelligence. Now, it's becoming very abundantly clear that the data bank is actually like quite infinite and it's based on these like agentic traversals of the world. M so the data so the lack of data is not a problem. Yeah, that that doesn't make sense. There there's infinite content out there.

>> Correct. Right. >> And there will just continue to be more infinite content. >> But now to bring it back to you know web 3 and harnesses. So today Anthropic is like the premier company collecting all the traces. Right. >> Right. >> Um when you talk about open models in and of themselves they don't collect traces like they're just open weight sets. Right. And so who really collects traces? It's the interfaces to those models. It's the harnesses of those models. >> I see. >> And so in today's world, the open harnesses like Hermes, they create a very like segmented uh market that is not coordinating on collecting everybody's traces and competing with anthropic.

>> Right. Right. >> But anthropic is just running away with it. Right. Right. >> And so one of the reasons I'm super bullish on decentralized training and harnesses is that you can now create a system where like let's say you're running a personal agent like Hermes agent or OpenClaw, you can point it to a special model that you co-own, okay? >> That you own the tokens of that you own the inference revenue of. And then you feel really good about donating your traces to that model because you know you're benefiting yourself and not some corporation right?

>> And so this is a way that like if enough people kind of you know gather around one of these decentralized RL processes and start putting it in their agent and that becomes really big. this is actually a counterbalance to like you know Claude owning everything >> right and and that seems to be one of the things that is like keeps people circling back on the decentralized AI thesis is like there's a lot of like hoops that are being jumped through and like product disadvantages compared to doing it like in the centralized way and this is this goes for everything. This goes for like why is it easier to like press your brokerage account to do a trade than like go do it on a DEX and

like have to wait for the block to finalize. You know, it's the same kind of concept across different parts of the stack. But what you're saying is like we're now reaching the point across whether it's the trace data and the ability of coordination to happen there or on the on the training and the inference side to actually create better cheaper inference. We're we're like we're reaching the point where the ideological blockers are no longer embedded into like the techn like the like they're no longer as deep of technology blockers as they once were. >> Yes. And I would say look I've been you know in the web 3 space for like 11 years. I've seen a lot of networks historically trying to offer compute, trying to offer, you know, storage on decentralized networks and a lot of

those experiments have not kind of panned out and have become like global huge projects, right? Part of the reason is there's not a ton of demand. Like even though we have these great value propositions, like it's cheaper, it's more private, it's self- sovereign. Um, a lot of times like middle market companies are just kind of like, "Yeah, but we have Amazon AWS and it's like cheap enough." >> Of course, >> right? And so there's not like a ton, but I think like >> one thing that separates decentralized AI networks from those kinds of web 3 resource networks we've seen in the past is that there's just an insane demand >> for compute and it's just doesn't stop >> and for intelligence in general, right?

Like it's there's that's just not going to stop, right? this Filecoin or Arweave like decentralized storage like you know is it it was interesting but it was always that demand question right like who's really going to want to use this but it's very clear that all of us are using this technology in our day-to-day life and I think one of the other promises that kind of web 3 has made is like this idea of like monetizing your own data like I remember everything from like the early IPFS like YouTube in 2017 there was like this like IPFS thing that was gonna you know take over YouTube and then there was get paid for your data.

Um, you know, things like metering, inference, these types of things. Do you think that these decentralized AI like is part of the promise as part of the thesis kind of returning to some of that monetization of user data of your self-owned data like self-owned AI, userowned AI? Near's uh CEO Ilia always says userowned AI like things like metering inference or like you know let's say if you have uh extra usage on on your plan being able to share that like are these like sharable monetizable data usage inference is this also part of thesis? Yeah, I I think so. I mean, I think like um the the other aspect is like when people

are going to be able to put relatively inexpensive compute on their desk, they're going to go to sleep at night and their agent is going to autonomously go and provide that compute to different networks and create a return for them, right? Like I I really think that in the same way that we've seen in crypto, we've seen like airdrops and and yield farming and this kind of thing, >> you know, I think we'll see that um GPU compute is also a resource that you can then use to generate income, generate a return for yourself. So, >> but what about specifically on the data front? like on the data like being willing to uh uh sell my data like I'm

generating all this data anyway, right? like like using Venice for the first time was kind of like a mind because I was like whoa like I know none of this is being used to train these frontier models and wow like for you know maybe it doesn't have the best context window for me but at least for once I feel like I'm not just like a uh you know a pawn on the board being monetized for you know me me you know what they say if the product's free then your data is the product right you are the product I is the data front something that you think we'll be able to tackle on maybe centralized AI thesis. A >> absolutely absolutely I mean I think that like again if you lower the reliance on kind of centralized

corporations then you're sort of leaving your data either locally or inside of models that you co-own and feel feel good about. Also like what kind of data are we talking about? You know some there's obviously like a bunch of first what they call first party data. It's like information about me, what I like, you know, what I buy on Amazon, you know, what, you know, what's do I want an aisle seat or window seat on the plane? Like these kinds of preferences that a lot of um e-commerce companies want to know about you to give you like advertising and better products. There's another kind of data that you can potentially see coming online, which is that, you know, I'm asleep in my bed.

Yeah. >> My agent is doing research on my behalf. He's coming up with new knowledge. He's trying to solve a math problem. He's doing research on the GPU space. He's doing research on what tokens are good in in crypto. Like whatever it is, right? That might be an area that someone else didn't think about, >> but you did and your agent did. And now you have this kind of alpha or like proprietary data that is valuable because you've spent cycles, you know, researching it. >> You're going to be able to put that on some network and sell it to somebody, right? So again, I I think there's a huge set of financial opportunities and privacy opportunities um in data, the more like we use agents and the more those agents are

decentralized. >> Yeah. I guess Jake, just to kind of close us out here as we come to a wrap, can you just give us like a size of the TAM again? I know you've you've given us some numbers on the training side, on the infant side. Let's say we get this right. Pluralysis, macrocosmos, aos, bit sensor, near venice, ant seed, all these kind of really early stage but some more developed than others companies working in the space. How big are we talking of a market here? What is the what is the addressable market that we're really after?

>> I again I think that's a on a five-year time scale based on my research. I think that's a 500 billion to1 trillion dollar you know revenue market um based on inference and I think that decentralized AI uh to the extent that it creates desirable scaled commercially viable um you foundation models can capture like I mean even you know 1% of a trillion dollar market like it's still you know still a lot of money right um so I think that's kind on the, you know, on the training side and then the on the inference side and then we didn't even start talking about agentic commerce

which we could spend probably a whole other episode on and you have multiple times, >> right? But basically, you know, just to give you some numbers there. Um even today when agentic commerce is definitely like not widespread and and there's like very few agents in the world the number of ma ma of AI assistants is something like 2.4 4 billion people, MAU, monthly active users. >> Um, and the number of like personal agents like Open Claw, you know, um, uh, Hermes agent, this is more like an enthusiast crowd. It's very small. It's it's my estimate is like 20 million or something like that,

>> right? >> But the 2.4 billion number is poised to grow is poised to double in in five years. And this personal agent number 20 million is poised to grow like over 100% kagger over the next you know 5 years. So I think there's like this huge huge opportunity there and how the value gets captured in that market in that agentic commerce market I think is very up in the air. Is it Visa? Is it payment rails? Is it the discovery layer? Is it the people who decide how your agents decisions are made? Is it like SEO? You know, there's a lot of issues there, but everyone agrees. It's very consensus that that's going to be a huge market as well.

>> Ladies and gentlemen, Jake, the CEO of Coin Fund in the tokenization tower. Sometimes tokenization means real world assets, sometimes it means actual AI tokens. Jake, thanks for your time, man. Cheers to have you. >> Thank you. Thanks for having me, >> guys. What an episode. We're going to recap it here in just a minute. We're going to let Jake go. It's a busy week here at ETHCOM. We'll be back in just a second. keep the show rolling. As always, guys, thanks for rocking with us. Thank you for all you guys in the chat as well. Great questions, great comments. Um, and we'll see you in just a second. [music] [music]

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>> We get [music] we get we get >> yo yo yo yo yo yo Oh yo yo, that was great. That was so bullish. Uh that was like the the best decentralized AI kind of like thesis wrap-up that I think we've had in a while. I mean Jake is extremely knowledgeable extremely knowledgeable about uh decentralized AI about openweight models about training about inference about the revenue profitability the uh scale of this industry. And I wanted to play this clip

from uh Ral Pal talking about um kind of like it's a general idea. It's kind of like in the same realm of like this is all happening right now. Like the TAM is 500 billion to a trillion. So let's just play this video. We're not going to listen to it all, but I think this is a nice little sentiment reminder. And the in the state of things as they are now, I think we might need a little reminder as to how early we actually are still. you know, the obviously there's a lot of stuff going on in the world and you know, the price action isn't doing what people want. People are so impatient as a society. It's not doing what we want.

So, I just want to, you know, kind of leave you with the last word about, you know, kind of this opportunity in this era that we're in right now. >> It's all so obvious. I mean, it literally is obvious when you've got here. We're at consensus as well right now and every bank is here, every asset management firm is here. They're all building on blockchain rails. We've got everywhere AI people building agents, building payment system, building wallets. >> We've got liquidity flowing. The liquidity um the everything code is in full flow right now. We've got the passing of the Clarity Act coming.

>> We've got the stable coin bill finally clearing and and being put into into play. >> Yep. We've got potentially the end of the entire Iran situation in perpetuity. I think is up for grabs, which I've been talking about for a while is, you know, that's what Trump's alluding to. I think that's what they want. >> If you could just stay in and do nothing for 10 years, you make all the money. >> And that it's very, very difficult to trade around the cycle. And if you don't need to, don't. But take lifestyle chips off as and when you can. Sometimes you can't.

But all wealth compounds over time and everybody desperate to trade it, it's going to it up. >> Yeah. >> It's just it's the biggest opportunity we've ever been given. >> We can infrastructure >> the substrate for all economic >> like I I hear you new type on track record and sooie and whatever else. Trust me, I know he's been getting destroyed. Um but I think he's right. I I think it's it's just it's hard to it's hard to trade these things. I mean, we're at the precipice of AI, of infrastructure, of of blockchain platforms like Hyperlquid, like Lighter, like Ethereum, like like Bitcoin. It's

guys, I mean, on the days like today when it's just kind of red out there, what hype's under 59, Bitcoin's just bouncing at the 61 level. I mean, it it just it just requires you to go to whatever iteration of the chart you're looking at and just zoom it way out. And just zoom it way out. And so that's what we're going to do. That's what we're going to do. I'm going to pull up the ecosystem dashboard because I believe there's a new uh there's a new um uh tool here on and this is from I believe it is from the uh circle yield tool. So let me try to find it real

quick. So this is MLM mode. So you can actually track some of the largest traders. For example, you can track L Oracle, his longs, his shorts on chain. It's pretty cool. You can track uh Garrett Bullish on his address. You can track his positions. He has no positions open. You can track Seleni, their positions. You can track Manifold. You can track all these funds. It's pretty cool.

Um, but there was a there was a new feature added, I believe, on the the actual site that was about the circle yield. Let me try to find that real quick. Where was that? So, I think something interesting for you guys. DeFi yields. No ecosystem. No, it was a there was a stable coin segment here. No, I'll find it, guys. Uh there was a tweet that went out about it. Uh let me just find it.

MLM mode, price to earnings, open interest. Yeah. Okay. So, either way, guys, I mean, again, we've been talking about this a lot. Uh, we want to see this HIPP3 share volume go up. We want to see um this OI bounce, which it is. Whoa, all the way back up. That's awesome to see. That is what we wanted to see, guys. So, we're happy to see that. Um, obviously price is down and market's down, so that's okay.

>> But this is like the key the key indicator that we wanted to see. Um, so that I'm glad to see that that's coming, you know, bouncing back up. And what also happened today, guys, was the Coinbase news where they actually turned on the uh they turned on the the buybacks. So for Coinbase now there is a actual um like there's about 200 million I think in buybacks coming 277. I saw the screenshot. Let me try to find it in my in my X here. That'll be what we want to

show. Maybe DJ News covered it. Wow. Alltime highs, open interest, new alltime highs. That's what I was just talking about. That's what we have on the screen is that we wanted to see that open interest go to alltime highs. So, this was part of it. um this th this post, but there was also, if you do the math on that, at 3.5 to 3.7% yield on that amount of capital, you're sitting at like I mean, you're sitting at you're sitting at like 200

150 to $200 million of additional revenue in buybacks on Hyperlquid as a result of that USDC on chain. So, pretty nuts. Pretty nuts. Markets a little slow though, guys. I mean, had a wild end of the week last week. I think I think most people are kind of a little bit skeptical right now about the broader macro, about Bitcoin, about kind of what's happening. So, not surprised. Also, you know, I would expect the traditional markets to have a nice re like I don't think the traditional markets are in any real trouble. I think people are kind of overblowing that. But yeah, I mean, we'll see. We'll see,

guys. It's big Eth week here in New York. Uh, tomorrow we have an amazing show again. Uh, we'll have Peter, we'll have Jacqueline, we'll have Chainlink teams in here. We're talking to some, we're talking to that Zcash digital asset treasury company tomorrow as well. Uh, Cippher Punk Technologies. So, that should be a good one. And yeah, guys, stay positive out there. It's been a bit of a shorter show today. Robbie's flying in. He should be landing in any minute. I think he should be at the office in about an hour. So, that'll be good. He'll be on the show tomorrow with me live here in the studio. But I think that pretty much wraps us up for today, guys. Thank you. Thank you for rocking with us as always. It's a beautiful day in New York. Uh we're going to have the Knicks win tomorrow. We'll be back up

3-1. Series will be on today, guys. It's one of those days where you just want to zoom out, relax, deep breaths here, understand we're at the precipice. You know, we're in the closing era of this bare market. I truly believe we are. You know, we've seen three of these before. We've seen quite a few iterations of crypto going through these periods of time. We're going to get through it. It's going to be all right. We'll be with you every day, rocking with it, no matter what the price is, no matter where we're at. And we're going to be with you when it goes up. And when we have a massive bullish move again, we're going to be right here with you the whole way. Guys, thanks for tuning in to the show today in the chat.

You guys have been amazing. Make the show so much more fun, so much more enjoyable. We'll see you guys back here 12:30 p.m. Eastern from the tokenization tower, the Nest live in the financial capital of the world. You're watching the rollup. It's been a great show. Thanks for being with us. Same place, same time. Much love y'all. Every single one of you watching. Love you guys. Thank you so much. See you soon. [music] [music] >> [music]