AI ROLLUP #9: $6M DeepSeek Shocker | $500B AI Push | Venice’s Billion-Dollar Airdrop | Solana DEX Record

Ejaaz and David reunite to unpack the DeepSeek shockwave: how a mere $6M open-source AI model rattled OpenAI’s dominance, nudged Nvidia’s stock, and sparked a fresh “arms race” in crypto AI. Meanwhile, Trump’s massive AI funding pledge and Solana’s record DEX volumes signal that the space might be heading for its biggest bull run yet. On the builder side, ARC’s rust-based agents partner with the Solana Foundation, AI16Z launches a $10M fund, and Virtuals teases multi-chain expansions that could redefine how agent tokens earn revenue. Between China’s fast breakthroughs and America’s big AI bets, the race to integrate AI and crypto has never been hotter. Buckle up, anon. ------ 💸 CRYPTO TAX CALCULATOR | BANKLESS15 https://bankless.cc/CryptoTaxCalculator ------ BANKLESS SPONSOR TOOLS: 🪙FRAX | SELF SUFFICIENT DeFi https://bankless.cc/Frax 🦄UNISWAP | BUG BOUNTY PROGRAM https://bankless.cc/Uniswap-Bug-Bounty ⚖️ARBITRUM | SCALING ETHEREUM ⁠https://bankless.cc/Arbitrum 🛞MANTLE | MODULAR LAYER 2 NETWORK https://bankless.cc/Mantle 🌐CELO | BUILD TOGETHER AND PROSPER https://bankless.cc/Celo 🎮RONIN | THE FUTURE OF WEB3 GAMING https://bankless.cc/Ronin ----- ✨ Mint the episode on Zora ✨ https://zora.co/collect/base:0x4be6cd4d402fed49eb2de95fbc8e737e8ffd3e7f/25 ------ TIMESTAMPS & RESOURCES 0:00 China & DeepSeek 12:43 Why Markets Rattled https://en.wikipedia.org/wiki/Jevons_paradox 24:32 OpenAI & Perplexity Agent Products https://x.com/OpenAI/status/1882509286439637448 https://x.com/perplexity_ai/status/1882466239123255686 https://x.com/sama/status/1884066337103962416 34:12 AI Agent Chain Wars 39:42 Virtuals is expanding to SOLANA! https://x.com/virtuals_io/status/1883107553183162507 https://x.com/state_of_mika/status/1883107601183048078 https://x.com/vaderresearch/status/1883597990830731678 https://www.lookonchain.com/articles/1035 53:01 AIXBT is becoming a product https://x.com/aixbt_terminal/status/1882755705586982969 56:01 VeniceAI launches a token that pays for your agent’s expenses https://x.com/askvenice/status/1883925135825990091 https://x.com/iampaulgrewal/status/1884051994324947001 1:03:13 Griffain now has a Shopify integration for their agents https://x.com/griffaindotcom/status/1883230795764322328 1:05:22 ARC partnered with Solana https://x.com/arcdotfun/status/1884325639047819476 1:06:36 Ai16z $10M x Jupiter Fund & Rebrand? https://x.com/shawmakesmagic/status/1883124194013319340 https://x.com/shawmakesmagic/status/1884376511391674742 1:08:45 What is Ejaaz paying attention to? 1:10:02 Closing & Disclaimers ------ Not financial or tax advice. See our investment disclosures here: https://www.bankless.com/disclosures ⁠

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:07David Hoffman?

  Welcome Bankless Nation to the AI rollup where we stay up to speed with the emerging trends and developments in the AI crypto space. I'm David Hoffmann here with my co-host EJAS. EJAS, man, big week in AI this week.

• 0:18Speaker 01

  Big, big week.

• 0:20David Hoffman?

  Big week, big week. How are you doing, my man? Good to see you.

• 0:23Speaker 01

  China, David, China.

• 0:25David Hoffman?

  China, how's it going?

• 0:26Speaker 01

  Dude, the CCP is coming for our AI models and I don't know what to do about it. But no, okay, so let's set the stage for a second here, right? Because a completely unheard of AI model has taken away the limelight, David. Forget about OpenAI, forget about Anthropic's Claude. It's all about this model called DeepSeek, which is an open source AI model developed by a team in China. And it may surprise you to hear that it costs next to nothing compared to OpenAI and it beats OpenAI's top model by a decent chunk or at least matches its standard. And the thing that's blowing people's mind is, aside from the fact that it's from China, USA's number one rival,

• 1:11Speaker 01

  is the fact that it costs next to nothing. And they pioneered two groundbreaking research techniques, which seemed to catch everyone else who has spent billions and billions of dollars into this off guard. Did you catch any of this, David?

• 1:27David Hoffman?

  Yeah, so I've actually been going down this rabbit hole pretty deeply over the last two days. We did an episode with this one individual who made this article that apparently went around both Wall Street investors and then he was watching in Google Analytics where this article was getting read and it made its way to Silicon Valley, like where Nvidia's headquarters are. And so people think that the market got tanked because of DeepSeek. He thinks, and many other people think, it's actually because of his article that he wrote, which is not just DeepSeek, but many other companies unbundling Nvidia from the periphery. And then DeepSeek was kind of the thing that lit the match, if you will. As I'll like distill everything that I know about DeepSeek and I can get you to.

• 2:10David Hoffman?

  To check to check it. DeepSeek, the model is very legit. It does in a very legit way pass benchmarks and performance tests that is very competitive with OpenAI. The cheapness of how it was trained, the $6 million in training costs. People are saying that that is much less legit. That's where the CCCP China and DeepSeek has the most incentive to lie. And then OpenAI is saying like, well, there's extremely strong evidence that they actually just used ChatGPT to train the model. So nonetheless, there were some very real engineering breakthroughs that changed how LLMs work

• 2:52David Hoffman?

  in order to produce an output that's much more efficient, that uses much less resource costs to produce a very strong output that is just cheaper to run. And so the fact that DeepSeek, the model is using, is charging 95% less than OpenAI and for their API calls is just evidence that this is very, very real. But they also just like rode on the backs of ChatGPT in order to produce their open source. Nonetheless, this thing is going to make waves in American AI models. And now you just, everyone at Facebook, at Meta and OpenAI is, are now understanding the tricks and bells and whistles that was built into DeepSeek to incorporate that into their models.

• 3:35David Hoffman?

  And I think really people are realizing that this, the arms race between the United States and China is fully on. And any innovation that we make in America is just going to be copied and improved upon by China. But that's a positive feedback loop between development on, in the, in the West versus the East. That's kind of how I understand it.

• 3:54Speaker 01

  Yeah, really good summary, David. I would just add one more thing, which I don't know if you mentioned it, but just in case you didn't. They open sourced.

• 4:03David Hoffman?

  They open sourced it. They open sourced it.

• 4:04Speaker 01

  Which is just a crazy move. That's like, you know, creating a potion that allows you to live forever. And then just telling everyone what the recipe is instead of monetizing it, you know, which is the American way. But yeah.

• 4:17David Hoffman?

  Did you see Archival's tweet?

• 4:19Speaker 01

  I didn't.

• 4:20David Hoffman?

  Where he says, it's ironic that we got AI that costs $200 a month from a nonprofit. And then we got the open source AI from a Chinese hedge fund.

• 4:30Speaker 01

  Yeah, that was hilarious. We should pull that up. Okay, so I wanna, I wanna touch on a few things that you mentioned, David, right? So you mentioned that they made, that it's legit and it made these like groundbreaking achievements. What are these groundbreaking achievements? Well, I wanna kind of like touch upon like a few things here and kind of like trying to distill it for the audience, right? So the one pioneering thing that they figured out was how to use data that they train their model with more effectively. So typically, a pre-deep-seek, what everyone thought was the case was you had this model. So you kind of designed it to do like super cool things, but then you need to train the model.

• 5:11Speaker 01

  So you need to combine data with it, you know, all this like raw data like, hey, this is David Hoffman, by the way. And these are humans and the sky is blue, all this kind of stuff, right? You need to run it through the model. In order to do that, you need to combine it with a bunch of compute power, right? That's why Nvidia rose to fame because it like produces the best chips, which allows you to run a bunch of compute, which allows you to train these super smart models. And then suddenly you end up with magic like ChatGPT. And so what that looked like was data, model and a ton of compute. And it was so expensive to do, David. It costs billions and billions of dollars to to train these things, right? But then what these guys, the DeepSeek team figured out was like, okay, well, we don't have a lot of compute. That's pretty expensive.

• 5:54Speaker 01

  And you know, there's a conspiracy theory saying that they actually did, didn't, it hasn't been proven yet. But the point is.

• 6:00David Hoffman?

  We do know that China has less resources, compute resources available. They need to be, they are compute constrained because of the chip ban.

• 6:09Speaker 01

  Exactly.

• 6:09David Hoffman?

  So even though they are getting able to get around the ban in finicky ways, nonetheless, that is a constraint that they have.

• 6:14Speaker 01

  Yes, exactly. So they're constrained, right? And so they have to figure out a smarter way to overcome this like setup where they need a lot of compute to train a smart model. So what did they do? Well, they designed the model and then they thought, hmm, I wonder if a smart way to train it is to feed it a bit of compute. Let it come out with an output from the data that it's, the little bit of data that it's used. And then get it to review the output and figure out why it's wrong or why it's correct or how it might get closer to the truth. And then, you know, rerun that compute, but just a little more smarter. So think about it, right? It's like learning to ride a bike for the first time. Imagine hypothetically, you jumped on a bike, you know, you sat on the seat, but then you put

• 6:59Speaker 01

  your feet on the handlebars and you fell off immediately because you lost your balance. And obviously putting your feet on the handlebar doesn't make the bike move forward. It's like getting off and being like, hmm.

• 7:09David Hoffman?

  Let's not do that again.

• 7:10Speaker 01

  Yeah, let's not do that again. I wonder if I put my feet on these little pedally things beneath me, maybe it'll center my gravity and maybe I'll figure something out. Like maybe if I push on it, it'll, it'll make the bike go forward. So they pioneered this method, David, which basically meant that they had to, the model had to take fewer steps, less compute and less data to figure out what it needed to do. It's kind of like a human, you know, when you make a mistake, you, you don't just run straight back. Well, some humans do, they just run straight back at it. But it forces you to think and be like, hmm, okay, interesting.

• 7:41David Hoffman?

  The way that I heard this is that L L M's and we all, I think we all saw this in early models of chat G P T is like hallucinations where you would throw it a prompt and then it would spit you back out a very long answer. And the end of that answer wouldn't really like line up with the first part of the answer because L L M's are very bad at backtracking and correcting previous responses. The metaphor that I heard is like, it's kind of like when a child is just like having train of thought. They're like, they're three years old, four years old, and their logic isn't so great. And they can't stop themselves and consider what they've said earlier and how does it square with what they're saying now? So they kind of just sound schizophrenic and they go off into the wild.

• 8:22David Hoffman?

  And so what this has done is it's broken up into chunks, is broken up its process into chunks, reviewed each chunk and make sure the chunks fit before creating a new answer. And so it'll, before actually spitting out an answer, it is able to make sure that the chunks fit with each other coherently and then it produces an answer. But this, this actually, my understanding was that this takes more compute. This is more. inference time because each chunk has inference costs inference and then sumating all of them is also more inference. And so this was what people this boosted the valuation of Nvidia because they were like, wow. The value of inference is just up only like so much inference means makes a better answer.

• 9:05Speaker 01

  Right. So there's some nuance there with your chunk theory, David, right? So you're right that you need more inference and for those listening who don't know what what inference is, think of it as like making a call to the model, like, you know, a website will make a call to the model to be like, hey, by the way, this user asked this question. Can you give us the answer for it real quick? Okay, cool. Thank you.

• 9:25David Hoffman?

  When you are asked, when you are querying chat GPT, you are making it do inference. That is the inference side.

• 9:30Speaker 01

  When you, when you type in a sentence like, hey, I want to make my mama's banana bread recipe. It's, it's, it's making a call to, to the, to the GPT model. Anyway, inference is cheaper than training, full stop, right? So whilst it's making a lot of

• 9:44David Hoffman?

  The point of training is cheap inference.

• 9:47Speaker 01

  Correct. Exactly. So whilst it's making a lot more calls, inference calls, it's getting smarter by using less compute effectively. But the point you were making just now, David, is people suddenly woke up and was like, wait, hang on a second. If, if we apply this inference model to like a bunch of other things, right? Like, hey, like, what if I could just like keep prompting chat GPT in my chat to give me a better recipe or something like, maybe I'll end up with the ultimate recipe. Right? And people are now like thinking of how they apply that model, you know, to a number of different things. But I just want to round this up, David. The second breakthrough that they made, which is super important is, you know, typically how you have like the GPT model, right? Let's take OpenAI, right? They have the model. When you query it or when you inference it, it queries the entire model.

• 10:32Speaker 01

  So think of this model as the design. It hits the entire brain, David.

• 10:36David Hoffman?

  Right. Every single neuron is

• 10:38Speaker 01

  Every single neuron is stimulated. It's queried. Exactly. Now, if we take the deep seek model, it gets a request and it only routes it to the section of the model brain that it needs to hit. Which is just so much more efficient.

• 10:51David Hoffman?

  What do they call this? MOE? There's something, something of experts.

• 10:54Speaker 01

  Mixture of experts.

• 10:55David Hoffman?

  Mixture of experts, right? So think of this This new model as literally a mixture of experts. And when you query it, it identifies, all right, I need to, I'm going to ask these three experts of my 27 experts. And I'm all and every like 24 of them are going to shut down and not not run inference. And three of them are going to answer. And that's going to produce 97% of the quality of the output by saving 97% of the energy required.

• 11:23Speaker 01

  Yes. Yep, exactly. And David, to be honest, we've just like splurged a bunch of stats and a story to folks. Can you pull up this chart that I just sent you, please? So it basically displays what we're talking about here. So what are we looking at in this like, you know, on this website? So artificialanalysis.ai, by the way, like just basically tracks all the top models, whether it's closed source or open source and ranks them against each other. Now, if you look on the left, we look at overall quality of these models. You'll notice that O1 is there, you know, right at the stop, right at the front, you know, it's got, you know, all the bells and whistles. But right next to it is suddenly DeepSeek R1 out of nowhere. And, you know, it's just a single point below it. Okay, okay, but what about the speed? You know, well, like, come on, this, I heard this thing isn't very quick.

• 12:07Speaker 01

  Well, actually, if you look at the speed tab, it is the slowest. But if you pay attention to what's right next to it, there's a familiar brand there.

• 12:16David Hoffman?

  Right.

• 12:16Speaker 01

  It's O1. So it's actually not too indifferent from O1 when it comes to like reasoning and delivery. And finally, David, I mean, the point that we're making is this thing is like so much cheaper. If you look at the price, right? We've got like

• 12:28David Hoffman?

  O1 is so expensive.

• 12:30Speaker 01

  Yeah, yeah, I mean, DeepSeek is at a four and you're looking at O1, which is like over six times as expensive or around six times as expensive, which is just nuts. So clearly like this just captures the breakthrough here.

• 12:43David Hoffman?

  And maybe to get to why this rattled the markets so far, it's like so hard on Monday, is that the idea here is that through creative use of this like medium of experts and a few other efficiency gains, this DeepSeek R1 model is measured to be 45 times more efficient than its competitors, its United States based competitors. And so what that means is like you're using 45 times less Compute resources in order to get the same response in about the same amount of time. And as a result, people are like, well, realizing like, well, this was a major in the tug of war between software and hardware between the AI outputs.

• 13:24David Hoffman?

  The software just got a big victory and it's diminishing the value of hardware because we're realizing we can eke more out of our models. And by doing things other than just throwing brute force resources at it. There's like this ancient, not even ancient, I've just used this metaphor in bankless, probably like 20 times over the years to talk about scaling. How scaling works and use this in the context of blockchains. There's two different ways to get scale out of any, any system whatsoever. You can write more efficient software and you can just build stronger, more performant hardware. And I think maybe a metaphor that people can relate to is like early Xbox 360 games versus late Xbox 360 games. Grand Theft Auto San Andreas, or maybe, maybe it's Grand Theft Auto four.

• 14:09David Hoffman?

  Came out on the Xbox 360 and so did Grand Theft Auto five. Same hardware, different games. And you can just look on screen as to like how you can probably count the polygons on Grand Theft Auto San Andreas. And in Grand Theft Auto five, you might be able to mistake that for like a real photo. And so this was just an example of these Grand Theft Auto teams writing better software to use the same amount of the hardware. Better to produce a better product. And then you can also scale hardware and just now we're on Xbox One, so the hardware is even better. And so this is, this is how blockchains work, right? We can either scale a blockchain by writing better software. And we can also scale blockchain by using better hardware. Honestly, the answer is always going to be both.

• 14:50David Hoffman?

  And this is what we're going to see out of LLM models is we're going to write models that use compute resources more efficiently. And with the creation of DeepSeek R1, it's 45 times more efficient than previous models. And then also we're going to be able to use more hardware as hardware improves. People have been talking about Jevon's paradox in this like Nvidia market crash, tech crash that's already recovering. But Jevon's paradox. I think is something like useful to to understand. Jevon's paradox states that as technological advancements improve the efficiency of a resource, its overall consumption can paradoxically increase rather than decrease. This occurs because increased efficiency lowers costs and expands potential use cases,

• 15:35David Hoffman?

  driving greater demand. AI is now a major economic driver. And Jevon's paradox suggests that as compute gets cheaper, AI adoption will spread out faster, expanding demand rather than reducing it. So in short, as Nvidia and DeepSeek improve AI efficiency, they don't reduce overall compute consumption. They make AI more accessible, leading to greater global demand for GPUs, energy and data infrastructure.

• 16:00Speaker 01

  Okay. So if I would have left curve thesis, what you've just said, David, because I think it's very important and I want people to understand. DeepSeek made models that are groundbreaking much cheaper to make.

• 16:14David Hoffman?

  Yes.

• 16:15Speaker 01

  Which means that there's this massive surplus of compute. And everyone's panicking. They're like, oh, my God, we have all this compute. What are we going to use it on?

• 16:22David Hoffman?

  Maybe we've been totally over indexing on compute. Maybe Nvidia is super overvalued.

• 16:26Speaker 01

  Yes. And so what you've just said is, hang on a second. No, there's this paradox which kind of explains that this compute will simply just get utilized kind of at the app layer.

• 16:37David Hoffman?

  It's induced demand. It's induced demand.

• 16:38Speaker 01

  It's induced demand. So this like groundbreaking discovery has basically meant that now more models are going to exist, which means more apps and more cool things are going to get built, which will consume that same compute that is the surplus. So eventually we'll still have over demand for the same thing.

• 16:55David Hoffman?

  Totally. And I think listeners are probably looking at the crypto AI token prices over the last two weeks. And they're like, oh, uh oh. And and then maybe they're thinking, all right, like, well, how does DeepSeek and Nvidia and all of this like, impact my bags? Like, what about my virtual tokens? And so I kind of wanted to attack that conversation head on. DeepSeek R1, the introduction of R1, is inherently, fundamentally massively bullish for the consumer. The AI sector is going to become more useful, more efficient, more just like we're going to be. Able to build better products faster because of something like DeepSeek R1. Nonetheless, Nvidia is still, has still like sold off. It started to pick back up. Here's the chart. I'm looking at the chart right now.

• 17:38David Hoffman?

  It started to pick back up a little bit yesterday, but it's still down

• 17:43David Hoffman?

  14% since last Friday, which is, you know, hundreds of billions of dollars. And so I kind of want to just talk about the stars that need to align before like our AI tokens go up in price because AI tokens, AI crypto, AI agents. It's a niche within a niche. This is a single sector of crypto. And crypto is a niche inside of broader finance. So we need broader, we need macro to go well, actual macro. And that's the Nvidia price. That is the performance of the stock market. That's also Federal Reserve monetary policy and Trump actions. Nvidia is macro, right, David? Nvidia is macro at this point because of how large it is.

• 18:25David Hoffman?

  And so we need, we need, we need macro, we need the traditional stock market to like at least hold on rather than go down. We need the Federal Reserve to signal that it's okay to invest in risk on assets. We need, we need cuts. And then Trump can also kind of do that same thing by just spending a bunch of money. That's actual macro. And then internal to crypto, we need AI agent tokens to be the meta. And I think people are going back and forth on whether or not AI agents and AI tokens are actually going to be the meta of 2025. I think if you ask people a month ago or two months ago, they're like, oh yeah, this is going to totally cause a bull market. I think now today, people are not so sure. And so there's like a stacking of contingencies

• 19:10David Hoffman?

  that we need in order to have an AI agent driven bull market. And while nonetheless, like this DeepSeek R1 is fundamentally bullish. And I think EJAS and I are going to say that this makes the AI agent meta, the AI agent part of crypto stronger because we now have another more efficient model to use these agents on. Nonetheless, we still need like a series of contingencies in order to like be bullish about crypto AI. So I kind of just wanted to like lay that conversation out because I think we're both bullish on the fundamentals here, but does that actually translate into AI agent tokens? Unsure.

• 19:43Speaker 01

  Yeah, it's a worthy reminder for the audience, David, and for us, actually, that crypto is still such a young industry. It's still burgeoning and blossoming, so it is very dependent on macro. The macro people, by the way, are still looking at crypto and they've seen these ETFs and stuff. They're seeing Larry Fink talking about tokenizing everything and only now, you know, it's like, oh, maybe we'll add a tiny little portion to a strategic reserve and see what happens. But we are still very much the younglings here and, you know, whatever happens to the macro market at large, if they're like a major war or whatever that might be, it will have a knock on effect to more risky assets, right? And crypto will always be the first one to hit.

• 20:27Speaker 01

  One thing I want to point out as well, David, is, you know, we said just now that Nvidia is macro. And what we meant by that is it is the biggest company in the world. It's the most expensive, you know, market cap for a single company and it's AI related. So it has a direct correlation or one to one kind of branding with, guess what? AI coins in crypto. So if you look at like alt caps within crypto, you know, you know, you've got like Bitcoin coming down a bit. It's still above 100K, which by the way, no one's talking about, which might be the most bearish sentiment on Twitter ever. But, you know, other alts are kind of shaken out, but not as much as like crypto AI coins, right?

• 21:08Speaker 01

  And I think that there we have kind of like a one to one kind of relation between Nvidia leading the market on the traditional stock index. And then like crypto coins having a direct branding thing here. And the point we're making here is the crypto markets are still very narrative driven. Fundamentals often like lag a bunch of these things, but in a bull cycle, narrative often drives like a ton of these different things. Now that is good or bad, right? Like if you're focused on the fundamentals and, you know, you have a thesis that, you know, crypto AI is going to be pretty huge. Open source AI unlocked by this deep seek innovation is going to be absolutely killer from now going forwards. Then you should just be chilling, right? And maybe you would buy the dip, but again, not financial advice, but maybe you would have more conviction in your positions and, and see these prices as kind of like a bargain, right?

• 21:53Speaker 01

  But it's important to pay attention and understand how this game works, right? And understand that the price will not always reflect fundamentals. And you're going to figure out what that means for your investing strategy.

• 22:04David Hoffman?

  With over $1.5 billion in TVL, the METH protocol is home to METH, the fourth-largest ETH liquid staking token, offering one of the highest APRs among the top 10 LSTs. And now, CME takes things even further. This restaked version captures multiple yields across Karak, Eigenlayer, Symbiotic, and many more, making CME the most efficient and most composable LRT solution on the market. Metamorphosis Season 1 dropped $7.7 million in Cook rewards to METH holders. Season 2 is currently ongoing, allowing users to earn staking, restaking, and AVS yields plus rewards in Cook, METH protocol's governance token, and more. Don't miss out on the opportunity to stake, restake, and shape the future of METH protocol with Cook. Participate today at meth.mantle.xyz. What if the future of Web3 gaming wasn't just a fantasy,

• 22:49David Hoffman?

  but something you could explore today? Ronin, the blockchain already trusted by millions of players and creators, is opening its doors to a new era of innovation, starting February 12th. For players and investors, Ronin is a home to a thriving ecosystem of games, NFTs, and live projects like Axie and Pixels. With its permissionless expansion, the platform is about to unleash new opportunities in gaming, DeFi, AI agents, and more. Sign up for the Ronin wallet now to join 17 million others exploring the ecosystem. And for developers, Ronin is your platform to build, grow, and scale. With fast transactions, low fees, and proven infrastructure, it's optimized for creativity at scale. Start building on the testnet today and prepare to launch your ideas, whether it's games, meme coins, or an entirely new Web3 experience. Ronin's millions of active users and wallets means tapping into a thriving ecosystem

• 23:34David Hoffman?

  of 3 million monthly active addresses, ready to explore your creations. Sign up for Ronin Wallet at wallet.roinchain.com and explore the possibilities. Whether you're a player, investor, or builder, the future of Web3 starts on Ronin. Are you ready to swap smarter? Uniswap apps are simple, secure, and seamless tools that crypto users trust. The Uniswap protocol has processed more than $2.5 trillion in all-time swap volume, proving it's the go-to liquidity hub for swaps. With support for growing numbers of chains, including Ethereum mainnet. Base, Arbitrum, Polygon, ZK Sync. Uniswap apps are built for a multi-chain world. Uniswap sees your transactions across its web interface, mobile apps, and Chrome browser extensions. So you're never tied to one device. And with self custody for your funds and MED protection,

• 24:18David Hoffman?

  Uniswap keeps your crypto secure while you swap anywhere, anytime. Connect your wallet and swap smarter today with the Uniswap web app or download the Uniswap Wallet, available now in iOS, Android, and Chrome. Uniswap, the simple, secure way to swap in a multi-chain world. Let's get into some of the actual fundamentals that I think picked up this last week because, you know, usually it's me, EJaz, and maybe 100 other people on crypto Twitter, AI agent crypto Twitter, talking about AI agents. But this last week, different people were talking about AI agents. Can you want to run us through this?

• 24:49Speaker 01

  Yeah, okay. So we're putting our metaphorical bull hats on now, David. We're done with the news. It's time to like, get into like, why this is so exciting and why, you know, DeepSeek and everyone is just pushing this entire AI space forwards. Okay, David, not just in a single day, within a two-hour window, two of the largest AI setups, not crypto AI setups, AI setups, OpenAI and Perplexity, announced their agent products. What do you have to say about that? So we had OpenAI demoing or teasing their agent product, David. This is something that we've been speaking about for months now. And we've been kind of teasing with the idea like OpenAI is going to launch something, blah, blah, blah. OpenAI teased their agent.

• 25:33Speaker 01

  And guess what it did, David? Aside from, you know, showcasing Sam Altman and our future overlords, it showed this agent doing a bunch of shopping. It showed this agent ordering pizza. By the way, you saw it here first on Bankless, an agent ordering pizza. So I'm just saying, open source is kind of like.

• 25:49David Hoffman?

  We've already done that, Sam.

• 25:51Speaker 01

  Listen, Sam, just chill. We're ahead of you. It's fine. You can take a leaf out of our book. It's cool. But anyway, and a third point, which we'll get into later, which their agents are using computer use, David. Now, remember, we've always spoken about APIs, APIs, APIs, and it's important, but just an interesting little thing there. But let's move on to Perplexity, right? Which has a very slick, kind of like, Apple-like demo here. Which basically demonstrates the same thing. So we have two of the biggest companies announcing agents at a time where DeepSeek is coming out with open source and all these new products are being pushed forwards. Techniques, products, whatever it might be. Just an insanely like opening week for us.

• 26:31David Hoffman?

  Let's watch the introduction of the OpenAI agent, just the first 20 seconds of Sam Altman as he talks about this.

• 26:39Speaker 02

  Good morning. We've got something exciting for you today. We're going to launch our first agent. AI agents are AI systems that can do work for you independently. You give them a task and they go off and do it. We think this is going to be a big trend in AI and really impact the work people can do, how productive they can be, how creative they can be, what they can accomplish.

• 26:58David Hoffman?

  Okay, so my understanding of this, EJAS, is that whatever AI, OpenAI builds with this agent thing, we just get to have that technology in the crypto AI agent sector, right? Like that whatever capacity that they're imbuing inside of OpenAI, do we get that or is it still closed off to us?

• 27:15Speaker 01

  So OpenAI is still closed source, just to make things abundantly clear, right? But what it does do for us in the short term, David, is it convinces us that we're either already on the right path or it corrects us to make sure that we're currently on the right path. And they've already given us a bunch of information just in this tease alone, right? I mentioned computer use. I mentioned some of the things these agents can start doing. They are already crypto platforms that are doing this and we'll talk about it later. But it's just cool to know that we are at least directionally correct, but these guys are still closed source. I have a feeling they're going to do something like they've done already, which is like, you know, here's an API, you can query it, it's still censored, you can't open source it, blah, blah, blah.

• 27:57Speaker 01

  But I bet you that Meta is probably going to follow up with a model that can do something similar and release their agent product. David, what if it becomes open source? What are you about to say? You look excited.

• 28:07David Hoffman?

  Well, isn't China just going to do it? Like, I feel like we're going to build all the proprietary, like, high-touch, white-glove LLMs that cost $200 a month. And then China is going to be like, well, thanks for that. We're going to spend $6 million more dollars by riding on the back. Of all of your guys is hard work and then we're just gonna open source all of your labor.

• 28:26Speaker 01

  Yeah, well, I'm curious like how far this strategy is gonna get taken, right? Like Meta did it within the US against OpenAI so that they can kind of vamp attack them and like, you know, bring them ahead of everyone else. And, you know, there's been this like thought that eventually Meta will eventually close source it, you know, because they're a private company, they have shareholders, etc. And, you know, we'll go back to normal. But like whilst this, we're in this golden age, like there's a lot to learn from here, right? Now, to your point on DeepSeek, right? I think they will end up releasing an agent model and typically, and it's not something we mentioned, they open source this model, which typically means that they've got a better model under closed like wraps that they have been already been working on for a while. And I don't know if you saw some,

• 29:10Speaker 01

  Sam basically mentions that, you know, R1 is very impressive, DeepSeek is super impressive. And he acknowledged that they have made advancements that they didn't quite figure out. And kind of this has been the take from like a number of OpenAI employees as well as like, you know, I'm pretty sure Jensen, Jensen Huang of Nvidia also said something similar, being like, wow, this is groundbreaking, blah, blah, blah. So it's put people on their kind of like alert

• 29:38Speaker 01

  kind of scenario right now where they're like, okay, can we be doing something better here? And what does it mean for like the kind of like wider sense of things?

• 29:45David Hoffman?

  Part of this is just heavily ripping off the ripping the realization off that, no, we are in a deep, deep arms race about AI. And the strategy of announcing that it only costs $6 million to train the R1 model, which is not true, that's like, that's probably the one part of this whole thing that's probably not real, was an intentional strategy to knock down the valuations of US-based AI companies.

• 30:13Speaker 01

  There's like a conspiracy that the hedge fund took a short position as well.

• 30:16David Hoffman?

  Yes, yeah, stuff like that. And then also like, you know, China will, China has for decades heavily, heavily subsidized their tech industry in order to commoditize some of the value created inside of the United States, copy it. And then, you know, produce it at scale and then just have. That become highly competitive with United States models. So it makes a ton of sense that they are in heavily intended to take the value of United States AI companies. And open source it as much as possible because that slows down investment. They are trying to slow down investment in United States AI companies. And so anything that I think comes out of China, in my mind, I'm kind of viewing that, perceiving that as

• 30:58David Hoffman?

  both trying to bolster their own AI tech industry, but also be an attack on American market values of AI tech companies.

• 31:04Speaker 01

  Yeah, yeah, for sure. I mean, I think it's a, I would personally brand it as a splash of very, very cold water on Americans, on America's AI darlings, right? They need to figure out, you know, are they too bloated? Are they directionally correct with their research? And are they building the right types of products? Because this is a wake up call and I kind of think you summarized it perfectly with the phrase, it's an arms race. That's literally what it is. If AI is going to penetrate every single sector, including, you know, literally defense and, you know, open source tech and consumer apps and all that kind of stuff. Well, then you're gonna need to like lead the frontier here. And so far, up until like literally last week, it was pretty clear that the US was the leader.

• 31:47Speaker 01

  And now it's kind of been brought into question, but I think this is going to be net, net good for all of us, David, particularly.

• 31:53David Hoffman?

  The fact that it's converging on open source at the end of the day is like.

• 31:57Speaker 01

  My point.

• 31:58David Hoffman?

  Open source just wins.

• 31:59Speaker 01

  Okay, okay, okay. So let's do the breakdown here, right? Okay, we had Trump come into presidency and announce a bunch of like really pro AI and crypto things, right? And he said, hey, we're going to have a specific person appointed to figure out the AI and crypto strategy, but we're going to be pro. Okay, literally a few days later, he announced a $500 billion set of investments that's going to happen purely within the US for AI, right? Which is just unreal, crazy, whatever, super bullish, right? Okay, we're leading the charge here. Sam Altman is leading that fund as well. Okay, wonderful. Then we have this deep seek thing come, right? And it's a cheaper, more accessible model. It's open source and it can compete with the best of the best.

• 32:43Speaker 01

  Okay, and it's from China, David, which is like the arch nemesis politically of the US. So now there's this branding of like, wait, this thing can be cheaper and accessible to everyone. So everyone's like perking up and like, hey, maybe I have a shot at building something cool in this industry and not just allowing Meta and OpenAI do it, but also like, whoa, it's China, we're scared, like, what's gonna happen, blah, blah, blah, blah, right? But they open source the entire model, which means that all the, and we're gonna bring it back to crypto here. People that are working on open source AI things such as agents, you know, the combination of this and OpenAI's agent product tease is like, you know, it's very, it's very telling. It's just like the perfect mixture to allow this entire industry to kind of boom.

• 33:27Speaker 01

  Cause it's like, okay, where's the, where's some of the most important agentic open source activity happening, David? It's in crypto.

• 33:34David Hoffman?

  It's in crypto, right.

• 33:35Speaker 01

  It's like some of the top teams are working on pioneering all these frameworks and platforms. So I think we're gonna see a lot of investment push out into this. I don't know if you saw Jack Dorsey's tweet, by the way, just adding this in, David. He released an open source, he's calling it an agent on machine system, which basically, I don't know what exactly it does, but it's gonna be his agent system that he's open sourcing for a bunch of different folk to kind of use, and I think he's calling it Goose. So it's super interesting regardless, and I think we're gonna see a push for more open source AI development.

• 34:12David Hoffman?

  Oh yeah, let's, let's get into some more crypto native subjects. You have this tweet in the agenda from DJ News, breaking Solana becomes the first thing in history to break $200 billion in monthly DEX volume. Why is this in the AI roll up agenda? How, how is this AI agent related?

• 34:28Speaker 01

  Okay, so last week, we spoke about the kind of like comparison of Solana versus Base. And I actually think this theme is very important to introduce or reintroduce rather into this episode, because there's been a number of announcements this week, David, which is suggested or is suggesting that Solana might be the home for a lot of AI agent activity going forwards. And I'm not saying that as a fact. I'm just seeing it from like certain observations. So

• 34:55David Hoffman?

  You're saying that the tug of war between Solana and other chains mainly base is meaningfully moving into this Solana camp? Like Solana is winning the tug of war.

• 35:04Speaker 01

  Correct. So let me, let me tee us up for this, right? So number one, Solana's had like its best month of decentralized exchange token volumes. It's actually broken the all time record, $200 billion. It doesn't take a genius to, to figure out why Trump launched his meme coin on Solana, which like broke everything. So it's not exactly AI specific, but I'm teeing us up for, for some of the analysis that we're about to break into, right? Secondly, I think something worth noting, you mentioned earlier, David, like, you know, AI coins are down. We don't know whether it's going to be the same meta. People are like looking at social consumer apps separate to AI. They're looking for the next meta. They talk about hyper liquid.

• 35:43Speaker 01

  Every tweet has hyper liquid at the end, but it is still the number one most talked about thing, AI, specifically within crypto. If you pull up like this mind share analysis, you know, baby, we're back, baby, we've never left, right? So it's still like the number one, 42%. It is still consuming everything and you'll see on the right there, you know, we see meme, we see DeFi. That, that represents basically people being like in panic mode and trying to figure out, damn, is this AI thing even worthy? Should I chase other things? But AI is still up on the rise. It's green.

• 36:17David Hoffman?

  Is deep seek, I think this is, this is a deep seek induced spike though. So whatever it was, we are higher than what we were. Is talking about

• 36:25Speaker 01

  I would actually disagree. Yeah.

• 36:27David Hoffman?

  Oh, really? Okay. So disagree with me. Why, why is this not just a deep seeking dude?

• 36:31Speaker 01

  So it is deep seek induced, but it's ingrained within the crypto stuff that's being developed within AI agents, David. So a lot of this chatter, remember crypto doesn't just, sorry, Kito, which we're referencing here, doesn't just track general AI stuff within crypto. It, it tracks like whether it has any relevancy to projects, to teams, to applications being built. And what I think this is capturing accurately, David, is all the teams and protocols, which announced, hey, by the way, it took us five minutes to integrate deep seek into our framework. It's there if you want to use it for any of the agents that you've spun up. And David, that's in fact the case. You know, I can name like a bunch of protocols off the top of my head.

• 37:14Speaker 01

  Eliza Framework, Arc Framework, Virtuals, Venice AI, which we'll talk about later, which had their launch with their token this week. All of them have DeepSeek already ingrained and running locally, which means that, you know, it's accessible to all, can't shut it down, et cetera, et cetera. Go and enjoy it. So it's capturing basically crypto's number one use case or like maybe number two use case, which is its resilience. You know, it doesn't matter what's happening in the world. If there is something good that comes out of it, it'll adapt it or adopt it rather, and use it for its own good, and it benefits every single agent. So now, you know, let's assume there's like, I don't know, 100,000 agents there built on crypto rails.

• 37:55Speaker 01

  Now all of those agents pretty much, or 90% of those agents get access to this amazing pioneering new advancement.

• 38:02David Hoffman?

  It is worth, I think, really reflecting on that idea that it doesn't matter what OpenAI builds or Meta builds, or even like this DeepSeek new AI lab builds, the natural convergence, if it does naturally converge on open source gets it. And like, why do you pay OpenAI for $200 a month? Well, so you can get the shiny new model like three months, six months sooner than open source. But the idea here is that eventually the value of all the AI LLM and all that stuff eventually shows up in the open source world, which is our world, and that value comes to be reflected on open source, open blockchains in the form of tokens. That, that's very bullish. That's very bullish to me. There's a bunch of other subjects that we're going to get into.

• 38:45David Hoffman?

  Virtuals, we have to talk about Virtuals, AI XBT becoming a product is something you want to talk about. Venice, Eric Voorhees, project launch token that is part of the whole like sovereign AI thesis that I want to map together. So we're going to get into those subjects. But first, Bankless Nation, you guys got to know the tax season is around the corner. And Crypto Tax Calculator is probably the best place to get your crypto taxes done. If you have been trading AI agent tokens, buying and selling them, you have a taxable event that you need to account for, and you can use. Crypto tax calculator 30% off with a link in the show notes. If you are a bankless citizen, otherwise you can get 15% off with the code bankless15. We've been big fans of crypto tax calculator. We've been using that at bankless for years.

• 39:30David Hoffman?

  I have an accountant that I just pay money, so I don't have to do this at all. But they just use crypto tax calculator. And so this is the other product that my accountant uses. And so if you guys want to check them out, there is a link in the show notes to get started. EJES, tell me about virtuals. Some very big news happened on Sunday or Saturday, I think. It was a weekend announcement. Walk us through the news that happened in virtuals this last week.

• 39:52Speaker 01

  Okay, so context here. Virtuals, one of the biggest agent protocols within the crypto AI sector. It's pretty much led the market and it was birthed on the base chain, David. Well, on Saturday, they announced that we're making a pretty strict move. Or a pretty bold move, rather, which is they are going to be also launching on, you guessed it, Solana. So this obviously churned up a bunch of news, right? Mixed reactions, like some were incredibly overwhelmed. They were like, this is the best news ever. If you remember, virtual's mission is to build up an agentic society or agentic economy.

• 40:35Speaker 01

  And you know, it should know no bounds, right? Regardless, so it should use any chain. And this is the first major move, territorial move, rather, that we're seeing some of these protocols move from one chain to the next in a very dominant form. So what does this mean, David? It basically means virtuals, as it exists today, you know, it has a platform you can go on to. You can design an agent, launch an agent, integrate with its frameworks or any other framework. As we mentioned last week, you know, they have this new API. You can now do all of that on Solana. So obviously it bodes a bunch of questions. It's like, well, hang on a second. What about the virtual's token that I own on base?

• 41:10David Hoffman?

  Because the virtual token built deployed contract address is on base. That thing, you can only, a token can only have one contract address.

• 41:17Speaker 01

  Yes.

• 41:18David Hoffman?

  And it's where, whatever is deployed first is its home now and for forever.

• 41:21Speaker 01

  Exactly. So everyone's like, okay, well, are they going to be minting more tokens? The short answer is no. Don't worry. Your coins are good. It's gonna be the same thing. There's a one-to-one comparison, but they're using, I believe, Layer Zero to transport some form of liquidity or portion of their tokens, be it treasury, to seed the pool or seed a bunch of tokens that they have on base onto Solana. So think of it as having, you know, the Solana version of their token, but you know, it's not using any more or any less. It's just literally the same coins being transported over to another chain. But they are literally, you know, expanding their economy here, David. They're gonna have like the kind of same kind of rails, the same kind of ability.

• 42:02Speaker 01

  And I think they're adding a few other things, David. They've mentioned that they're gonna be introducing something known as a venture partner, which I believe is gonna be something along the lines of they'll recruit some of like the, whatever, the best minds or what they believe to be, you know, active contributors in the Solana AI ecosystem to help curate and launch projects on their Solana version of virtuals, which will allow them to have some kind of like a seeding here in terms of like building something awesome. But I I mentioned, David, that, you know, there were some really overwhelmingly good reactions. There were some overwhelmingly bad reactions as well.

• 42:39Speaker 01

  Okay, understandably, from the base ecosystem, they were like, hang on a second, are you guys just abandoning us? What about the agents we launched on base? Like, what are we gonna do there? The TLDR of the response from the team is, we still love you. We are still putting the majority of our treasury and support and resources to you guys. We're just moving a chunk of it now to Solana for now. But also, they're figuring out ways where these agents on base with their tokens on base could also potentially move to Solana as well, David, which means that fees that are aggregated in the same way in Solana or on base will get fed back into these same agent tokens, whether they're on base or whether they're on Solana. So everyone technically or theoretically should win.

• 43:24David Hoffman?

  Every agent on Virtuals technically should win. I think if you are a chain maxi, you're just saying this is a big win for Solana and a big L for Base. I mean, nonetheless, like AI XBT, that token is on Base, that contract address is on Base. I think, like, correct me if I'm wrong, but the idea here is you can now issue a Virtuals agent and his token on Solana, and that be a Solana native token address, token contract address. And then also tokens, agent tokens that are on Base can use Layer Zero to become, have liquidity on Solana, access liquidity on Solana.

• 44:00Speaker 01

  So that last part, I'm not entirely confirmed that it's live yet.

• 44:03David Hoffman?

  Okay.

• 44:04Speaker 01

  But I believe it's in the works. They hired a, I saw Jensen say that he hired a token economist to like map out how this is going to happen in kind of phase structure. But it's their full intention that all these agent tokens on Base can operate and work on Solana. Yeah.

• 44:20David Hoffman?

  Okay. So it's really the idea that new Virtuals agents can issue their tokens on Solana. That's, I think that's kind of the big punchline for everything to me. Everything, everything else is kind of more marginal than that.

• 44:32Speaker 01

  It's that, but also just expanding the TAM of your potential users. It's been no secret that Solana has kind of been the DGEN chain of the year.

• 44:41David Hoffman?

  It's got the hot ball money.

• 44:43Speaker 01

  Yeah, it's got like the most activity, the most, you know, you could argue obviously this, but like the most kind of innovation or new primitives that we're seeing. And I think it's where a lot of the attention in general from the public on crypto at mass has been, right? You know, Trump literally launched his meme coin on Solana. So it'll be interesting to see how this plays out and whether it, you know, attracts the same type of quality of builder, maybe a different kind of quality. Remember, you know, Solana is written in Rust, so there's going to be like, kind of like, is it going to be a one-to-one comparison? Are we going to get better quality engineers or worse? Like, it'll be interesting to see how this kind of works out.

• 45:22Speaker 01

  But David, some of the like top protocols or rather teams that build on Virtuals are kind of like moving over or started to migrate over to Solana as well, David. I love this tweet from like Vada. So Vada is like one of the top investment DAOs on virtuals. And you know, they're gonna have like, you know, uh, some liquidity prevalent on the Solana chain. And there was also another team that migrated, David. I think it was Mika, which, you know, is kind of outlined the entire kind of like roadmap or plan of how they were gonna do it. So the point I'm making here is there's obvious demand from Solana ecosystem, but there's demand from the base guys to also kind of like get into this kind of like Solana attention economy.

• 46:05Speaker 01

  So just a massive and major announcement, which I think a lot of people weren't kind of like reacting to. People are hypothesizing, David, that also it's because Coinbase didn't list virtuals. And so they were kind of getting Huge L. Huge L, you know, and I'm kind of like thinking about like, has this happened before in a similar analogy? And it kind of got me to think of Pengu, you know, the meme coin that the Pudgy Penguins came out with. And the fact that they just launched it on Solana kind of reminds me of that, except that they didn't have the listing exchange issue. But yeah, virtuals, you know, didn't get the Coinbase listing and, you know, some people are still old school. They're still trying to be like, hey, you know, what's up? Like, why can't you pay us the attention that we need? Well, like one of your biggest tokens, we attribute for like, I think 50% of your Dex volume at one point.

• 46:50Speaker 01

  Like, how are you guys not figuring this out? Right? So, um, anyway, like, I, I think, like, stepping away from this, like, Solana launch, one final thing to mention is, um, the founders in the team, David, are still so locked in, dude. It's pretty nuts. I read this interview. Um, I don't know if you have it pulled up, but, um, with one of the co-founders of Virtuals on their recent kind of like trip to Asia, they were doing a bunch of like ground business development work. Um, and, you know, he was, I, I just loved that he took the approach of first principles to everything that he was building. You know, he wasn't focused on the token or any of that. He was like, how can I build a good product? And, you know, I found this quote pretty funny where he was asked, you know, why didn't you launch on Solana? And he was like, well, it was because we didn't know how to code in Rust.

• 47:35Speaker 01

  And obviously, like, since then, there were things that were in the works. They were either collaborating or working with Solana engineers to figure out how they can actually, you know, deploy those smart contracts. But there are three big takeaways from this interview that I kind of want to highlight before we move on, David, which is they're working on three things on their roadmap, which I think shouldn't go underscored. Number one. Better agent interoperability. So this means how do agents talk to each other? And how can they end up like working with each other? You know, we've seen Luna, their flagship agent, hire another agent to do something for it. What if that became commonplace amongst agents? Something super cool. Number two, sharing agent revenue with token holders and community that helped build the agent.

• 48:18Speaker 01

  Now we're thinking of like these agents as like investable assets potentially, right? And like, obviously there's a discussion around securities and all that kind of stuff. But if your agent is a productive being or entity and generates a ton of revenue, now you potentially may be able to get exposure to that kind of thing. Like typically they've been doing buyback and burns. But what does a revenue distribution look like is super interesting. And the third, and probably the wackiest one, David, is physical integration with the real world. So AI agents running pop up shops is going to be their first iteration. Yeah, yeah, I think, I believe, I forgot the name of it, but they're basically going to be setting up a coffee shop in Mexico as like their first kind of like test case. And it's going to be run by an agent.

• 49:00Speaker 01

  What that means, I have no idea, but hopefully the coffee tastes great.

• 49:07David Hoffman?

  Okay, so one question I have, if you go to the virtuals price, I'm looking at CoinEco.

• 49:13Speaker 01

  Down bad.

• 49:13David Hoffman?

  Let's go by even a month. It's down only for a month. And the integration with Solana, which I'm guessing, just like using my left curved brain, it's just because that's where the hot ball of money is, that's where the liquidity is. It's good for new users, it's good for, it's good for increasing the, you know, you want to be next. Everyone wants their token next to the hot ball of money and the hot ball money is on Solana. This actually just didn't show up in the virtuals price. And also, virtuals has been down only for the entire month of January. So, I mean, I'm going to ask you the impossible question that no one can actually ever answer. But just like, what do you think is going on with the price?

• 49:50Speaker 01

  Yeah, I mean, I would say that this price chart and pattern that you've just pointed out, David, is going to be reflective across a ton of other AI coins. And we should, we should double check that, right? But basically, we had a massive run up with these crypto. AI coins by the end of last year. And then we've pretty much been in a sell off period since. I mean, look at AI 16Z. It's like, kind of been like a very similar story or pattern there. So it kind of brings up the point that you mentioned earlier, David, which is crypto is very narrative driven. And what drives the narrative the most? It is macro. So if macro is not doing too well, or if there's a bunch of things happening in the US government that apparently has a massive reflection on the rest of the market, we will see similar things here.

• 50:34Speaker 01

  So crypto still isn't grown up enough yet or treated as a mature enough asset just yet, which makes sense. You know, regulations haven't caught up, but they will. But it's not mature enough to get treated as its own separate kind of trend that's going on. So that could be your best knowledge, right? So if you're like, oh, well, I think, you know, the fundamentals aren't being reflected in the market. That could be a really good buy opportunity. Or you could just be impatient and let the price, you know, reflect your own narrative or investment thesis. It really depends.

• 51:04David Hoffman?

  The Arbitrum Portal is your one stop hub to entering the Ethereum ecosystem. With over 800 apps, Arbitrum offers something for everyone. Dive into the epicenter of DeFi, where advanced trading, lending and staking platforms are redefining how we interact with money. Explore Arbitrum's rapidly growing gaming hub from immersed role playing games, fast paced fantasy MMOs, to casual luck battle mobile games. Move assets effortlessly between chains and access the ecosystem with ease via Arbitrum's expansive network of bridges and onramps. Step into Arbitrum's flourishing NFT and creator space where artists, collectors and social converge and support your favorite streamers all on chain. Find new and trending apps and learn how to earn rewards across the Arbitrum ecosystem with limited time campaigns from your favorite projects.

• 51:49David Hoffman?

  Empower your future with Arbitrum. Visit portal.arbitrum.io to find out what's next on your web three journey.

• 51:58David Hoffman?

  Cello is transitioning from a mobile-first, EVM-compatible Layer 1 blockchain to a high-performance Ethereum Layer 2, built on OP stack with EigenDA and one-block finality, all happening soon with a hard fork. With over 600 million total transactions, 12 million weekly transactions, and 750,000 daily active users, Cello's meteoric rise would place it among one of the top Layer 2s, built for the real world and optimized for fast, low-cost global payments. As the home of the stablecoins, Cello hosts 13 native stablecoins across seven different currencies, including native USDT on Opera MiniPay, and with over 4 million users in Africa alone. In November, stablecoin volumes hit $6.8 billion, made for seamless on-chain FX trading. Plus, users can pay gas with ERC20 tokens like USDT and USDC and send crypto to phone numbers in seconds.

• 52:43David Hoffman?

  But why should you care about Cello's transition to a Layer 2? Layer 2s unify Ethereum. L1s fragmented. By becoming a Layer 2, Cello leads the way for other EVM-compatible Layer 1s to follow. Follow Cello on X and witness the great Cello happening, where Cello cuts its inflation in half as it enters its Layer 2 era and continuing its environmental leadership. I think of all the charts out there, AI XPT stands out to me the most as it's, I mean, it's off of its all-time highs from just like 15 days ago, but otherwise, the chart looks pretty intact. Talk to me about AI XPT. What's going on over there?

• 53:17Speaker 01

  Dude, I'm super pumped about the AI XPT team. So, major news this week is they announced their kind of like product. So, if you remember what we mentioned on the pod a few weeks ago was, AI XPT is cool, it delivers financial alpha, but my guess, or our guess, was they would eventually dog food a product to people through this, right? And their product at the time was, hey, you need 600,000 of these tokens to get access to private, sorry, private access to these, to the terminal, right? So it could give you your own tailored alpha. That was a lot of money. That was, I think, $150,000 at the time, and so, you know, very inaccessible to most.

• 54:01Speaker 01

  So what they did was they launched this new AI XPT Terminal tiered system. Which now allows a range of token holders of AI XPT to get differing access to the agent terminal itself. Now, I'm not going to go through all the tiers, but basically, if you scroll down, David, it gives you varying kinds of access to the interface, what kinds of alpha or questions you might be able to ask it, and gives you a general idea of like where this thing is kind of going from a product perspective. But obviously, that wasn't enough information for us. So, you know, we jumped on a call with the AXBT team this week, and they kind of gave us their insight into like what they were thinking.

• 54:42Speaker 01

  And I'm not going to get into it because I want to save it for a pod episode later where we formally, you know, speak to AI XPT and the team. But the two main takeaways was number one, I really like that they're trying to get AXBT into different types of mediums. So, right now, it exists on Twitter in written form. But what does it look like from a voice perspective or a digital representation on video? What does it look like when it is existent on different social media platforms? Or just like entirely non-social platforms, like what does that look like? Is it your assistant? What does that look like? The second thing I thought was really cool was they're kind of like plans for like a B to B approach,

• 55:24Speaker 01

  which is like, hey, if you're a protocol that's trying to figure out your token economics, wouldn't you kind of want to speak to the smartest agent in the room? That's already digested a bunch of these things from a million other teams and knows where the kind of market is trending and could give you advice on like, hey, I think you should structure it this way or that way, or you should do A, B, and C. What if you, David, had your own private AI XPT agent just pop up, you know, just sitting on the edge of your screen there, like kind of like Clippy back in the day? What would that be? Like, how would that look? What would that price pricing system look like? You some really cool, you know, products coming out of this.

• 56:01David Hoffman?

  One big bit of news that rocked the AI and just crypto world generally, I think this was maybe the news of the week, at least so far, is the Venice airdrop. Venice is kind of like a private DuckDuckGo version of ChatGPT. Where you don't need to sign up for an account to make a query with ChatGPT. So it's branded as like private, private ChatGPT. This is built by Eric Voorhees and this is very downstream of his old project Shapeshift. Which was once upon a time forced to implement KYC. All it would do is you would input, you know, one crypto asset on one chain. And then you would give it another address on a different chain and then Shapeshift would swap the assets and send it to a different chain. You never had to do any signup because Eric Voorhees hates KYC.

• 56:45David Hoffman?

  Venice is something similar, just no signup for using this LLM. And so, and they, Venice launched the VVV token. Which instantly zoomed up to $2 billion, fell back down to about $1 billion until Coinbase. Announced that it was listing Venice and then it went back up.

• 57:04Speaker 01

  Much to the Virtuals fans disgrace.

• 57:06David Hoffman?

  Yes, right? Yes, exactly. Like very, a very quick token listing. Which may, allowed it to break all time highs again in the same day it was launched. At $23, 2.3 billion, I think is about the total valuation. And that has been the story of Venice and I think everyone kind of scrambled. If you are a listener of this podcast and you hold something like AI XBT, which is a token on base. Clanker, a little AI bot to drop tokens, also a token on base. Many AI agent based tokens, if you held any of these things, you got an airdrop. And so many people have claimed their airdrop, pretty fat airdrop.

• 57:46David Hoffman?

  And then it made its way into a listing on Coinbase and it already trades on Coinbase. Right now. What did you think of this event when you saw this event?

• 57:55Speaker 01

  Okay, so there's a few things here. Number one, love that Eric Voorhees is building out this product. You kind of summarized it well, but rather than think of it as like the ChatGPT. Think of it as like ChatGPT, but it has access to any. Model that Venice connects it to, right? So think of Venice as like the front end and it will query whatever model you want it to, right? And that could be potentially centralized, but preferably open source, locally run models, right? The second selling point of Venice is that it's supposedly private, right? And there's a bit of debate as to how private it is, but it is private. And the way that they do this is it's privatized cryptographically at the node level.

• 58:40Speaker 01

  So when you make a request, it goes to a node, the node privatizes it and then like, you know, does a query off chain, pulls the output again, cryptographically privatizes their response and then sends it back to you. So it doesn't technically know where the query came from, your IP address or any of that kind of stuff. It only exists on your browser, doesn't store any information. And to your point earlier, you don't need to KYC, you just connect a wallet address and you get on with it. And it has a free version and a pro version. So, you know, a really cool product. I think what was also cool about this is as soon as DeepSeek was released, Venice just plugged straight into it and ran locally. So now you had like the best model and access to it.

• 59:22Speaker 01

  So, you know, you could just jump on Venice and have like some of the smartest returns, maybe smarter than the leading OpenAI O1 model. So very cool. Now, on the point of the Coinbase listing, David, there's a few things that I think about this. I think potentially like, you know, they were working together by some means because you know, it seems like Venice is like being plugged in as an API as part of their AI agent SDK kit, which has been, you know, very popular in terms of setting up certain agents. But number two, it brought into question what their listing process is like. And, you know, this isn't the first time this is being done, but it's been really focused on for the last week. And I want to kind of like point out, I think a tweet or a comment that Paul Graal made on this, Paul Graal is like the chief legal officer.

• 1:00:07Speaker 01

  And what he basically said was, listen, we hear you and we are now at a point where we really need to revise what our listing process looks like because the fact of the matter is there are a million tokens being released every, is it every week? Yeah, it's every week and we just can't feasibly keep up the same standard and structure that we're taking to diligence and list tokens. Otherwise, we're just gonna miss out on a massive market. So whether it was Paul Graball or someone else that mentioned this next specific point that I'm about to make, which is they kind of wanna maybe explore doing a list all approach and then just, you know, retroactively ban or prevent tokens that, you know, are in ill faith.

• 1:00:48Speaker 01

  So they're looking at ways to do this via their centralized exchange, but also through decentralized exchange ways. I think Brian put out a point here where he was like, Brian Armstrong, the CEO, where he was like, we shouldn't be constrained by this. Whether it's a Dex or a Sex, we should be able to get access to listing tokens for all our Coinbase users. And I think net-net, that is a productive output from all of this, David.

• 1:01:10David Hoffman?

  I also wanna talk about just the price performance. So as soon as the VVV token was launched on Coinbase, it instantly went up. It did like a two, two and a half X, but it's been down only ever since. So it peaked at $22, it said $9. And I wanna compare that to Toshi, which is a meme coin on base. And to me, the like data here, the interpretation that I'm giving is like, well, let's, let's look at what happened when an AI token was listed on Coinbase and was made available to retail versus what happened when a meme was listed on Coinbase. And I'll say the Toshi token listing, well, it always kind of peaks at token listing, but the Toshi price

• 1:01:50David Hoffman?

  has really maintained its value post-listing. And the Venice price is kind of down only. Now, this is a very, there's hugely massively apples and oranges because Toshi has been a token for over a year, over a year. And then VVV is a token for like two days now, so it's not, not the same. But what do you, what do you think about like retail appetite for memes versus AI tokens on Coinbase?

• 1:02:15Speaker 01

  Yeah, I think you raise a really good point, which is, you know, the general archetype of some of the D gens. And particularly D gens that are trading on chain. So that's, you know, not necessarily using centralized exchanges. Are just completely dispersed. It's like a split personality, David, where it's like one, one time we're like, oh, we're pro AI fundamentals. And then the next one, like, oh, it's all a lie and we should just go to memes and, you know, financial nihilism TM. Do you know what I mean? So there's definitely part of that. The other thing, though, and, you know, the Toshi or supporters may, may not like this. And again, I'm going to put my hands up and say, I don't know whether it's, it's true or not, but I believe the supply of Toshi is pretty concentrated amongst, you know,

• 1:02:56Speaker 01

  a set of holders. So that might also be a reason why, you know, price was able to pump so quickly and so.

• 1:03:03David Hoffman?

  Just because the flow isn't very, very high.

• 1:03:05Speaker 01

  Yeah, yeah. And again, yeah. And again, like, fact check me on this. I could be wrong, but that could also potentially be a reason.

• 1:03:13David Hoffman?

  All right, E. Jaz, we're at an hour. Let's kind of burn through the rest of the, the news here. So Griffane, Arc, AI 16Z. We're going to burn through these. What's going on with Griffin?

• 1:03:22Speaker 01

  Okay, so Griffin context here, we've mentioned it on the show before, but think of it as like an agent execution platform. So you basically can go onto it. It's like a chat GPT, but hey, there's a bunch of agents that can do on chain stuff for me. Well, David, that kind of changed this week when they added an off chain web two, very boomer component, David, which was Shopify integration. So now.

• 1:03:44David Hoffman?

  This sounds what Sam Altman announced at OpenAI is just like your agent that can do things.

• 1:03:48Speaker 01

  Yeah, it's, it's almost as if the open source crew are like front running a lot of what the centralized corpse are focused on, which is, you know, kind of bullish. But yeah, so a bunch of the agents now are able to integrate with Shopify and do a bunch of web two products and services with you. So what this looks like and what you're looking at in the demo, if you scroll down, actually, David, I think you should be able to see an agent ordering cold brew, a pack of cold brew coffee cans for the particular individual. This agent in particular, I believe, is Agent Kitsune. And if you watch this demo, it's basically like ordering a pack of cold brew. So why is this important? Why am I even? Mentioning this, I think there's a secret trend that no one's really talking about, David,

• 1:04:30Speaker 01

  which is what happens when you combine a web two product or service with a web three innovation or tool and strap a token to it, right? We've spoken about all the crazy things that have happened in crypto before, which is like we're launching NFTs, but it's web three native. We're doing, you know, DeFi, but it's on chain and blah, blah, blah. Okay. But like the normies don't get it, David. They don't understand what this means for them. You need to make it somehow relay to them. Now we have a vector or a medium which comes in the form of agents that will allow you to, you know, hey, could you cash out some of my crypto portfolio in Coinbase and then use that to buy me the groceries for the week? You know, what does that look like? Why is that important? Why should we be paying attention to that? Well, it's going back to our thesis that agents are

• 1:05:14Speaker 01

  going to make all of this really easy for people to use. They don't even need to know that blockchain is happening on the backend. But I thought that was super cool about the Griffain thing.

• 1:05:22David Hoffman?

  And ARC, the announcement here is we're teaming up with the Solana Foundation to accelerate AI innovation on Solana. ARC, okay, I remember, I remember you telling me about ARC. ARC is all about Rust. These are the Rust AI agents. It's harder, but it's more performant. Solana also built in Rust. It makes sense that the Rust AI agent platform is going on the Rust chain. It's weird that they are announcing a team, they're teaming up with the Solana Foundation because I always already figured that they would already be fully integrated with Solana. So what's going on?

• 1:05:51Speaker 01

  Listen, there's nothing better than a formal headline on X to pump your price, David. But actually, the, the complete opposite happened. Nothing happened. If this happened a week ago, if this headline was made a week ago, or maybe even two weeks ago, this would have absolutely sent ARC. But this is going very much under the radar. And so what's interesting here, or like the wider point is a formal partnership with Solana with the crypto AI space hasn't really happened yet. I don't think we've seen the same on, on base. So maybe I'm wrong. But like Solana Foundation partnering with an actual protocol that like embeds or will create a bunch of these agents has not been seen before. So, you know, very understated announcement, but I want to kind of like raise it on this. Super, super cool.

• 1:06:37David Hoffman?

  And then lastly, AI 16Z, which I saw formerly rebranded because A16Z, actual real A16Z, finally probably sent them a cease and desist. Is that what's going on?

• 1:06:49Speaker 01

  Okay, so these are all rumors, and so I don't know the exact specifics, but actually initially, when AI 16Z launched, the real A16Z reached out to them and said, hey, this is super cool. Actually, if you remember, Marc Andreessen called out AI 16Z saying, huh, this is a really cool project. I hope you guys kind of make it. And, and actually, there's rumors that the A16Z team helped them set up their legal structure within the US, which is like pretty awesome, right? Like very, you know, hand in hand, centralized, decentralized, like, hey, we're going to figure this out together, right? But of course, you know, all things must settle down eventually, and there are some Ts to be crossed and some Is to be dotted. And one

• 1:07:28Speaker 01

  of these things potentially is around, you know, namesake and copyright. And of course, AI 16Z originally started as kind of like a parody for A16Z and

• 1:07:39David Hoffman?

  A very small, like a $10 million parody, which is no longer now that

• 1:07:44Speaker 01

  Yes. Yeah. So basically, the likeness was, was too, too close, and they wanted to move on to something that was more formally separate. And I also have a feeling, David, that this is also interfering with exchange listings potentially. So they want something that is like separate, that they can, you know, not be sued after, basically. So, so that's pretty cool. The second important thing here is they announced a $10 million fund in conjunction with Jupiter Exchange, which is like the number one decentralized exchange or aggregator on Solana. And why this is super interesting is, you know, yet another conduit to build and support teams that are building within this space. And I think that that's super important. You know, we've seen the rise of investment DAOs, we've seen the rise of

• 1:08:27Speaker 01

  traditional VC funds, raising funds specifically for the sector. So it's cool to see, you know, some of the core protocols dedicate so much funding towards the space. Pretty awesome.

• 1:08:35David Hoffman?

  Cool. All right. Bankless Nation, that was the AI roll-up EJAS. Thank you once again for guiding us through all the weekly news. It moves faster than ever. What are you paying attention to now? What are you looking forward to? Like, let's get a little peek into the head of EJAS. What are you doing over the next seven days or so?

• 1:08:54Speaker 01

  Okay, so I'm looking at unsexy agents, David.

• 1:08:57David Hoffman?

  Unsexy agents. That sounds very unsexy.

• 1:08:59Speaker 01

  So yeah, very unsexy. So sexy agents are the agents that you see on your Twitter every day that talk to you, that make you laugh, that order you pizza, you know, all those fun real things. I'm looking at the guys behind the closed curtains, David. The ones that are...

• 1:09:12David Hoffman?

  Middlewear agents?

• 1:09:13Speaker 01

  Yeah, the agents that are delivering the food, you know, and the gig economy that's happening behind the scenes that are aggregating all the important data that you need to feed you the perfect responses that you need to. I think that with all of this, like, you know, DeepSeek news with Nvidia crashing a little bit, there's going to be a flight to quality, to fundamentals. And I think people are going to be putting on their framework hats and looking at a bunch of these unsexy agents that are driving kind of the fundamental usage. They're going to look at like infrastructure plays and all that kind of stuff. Second thing I'm looking at is computer use. I've mentioned that on previous pod episodes before, but with OpenAI and Perplexity teasing computer use for their agents, I have a feeling there's

• 1:09:57Speaker 01

  a trend that's going to emerge here on the open source side of things. So digging into those things.

• 1:10:01David Hoffman?

  Cool. Bankless Nation, you guys know the deal. Crypto is risky. Crypto AI is probably even riskier. You can lose what you put in, but we are headed west. This is Frontier. It's not for everyone, but we are glad you are with us on the Bankless journey. Thanks a lot.