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

Episode Date: January 30, 2025

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 ⁠ 

Welcome Bankless Nation to the AI roll-up where we say up to speed with the emerging trends in developments in the AI CryptoSpace. I'm David Hoffman here with my co-host, E-Jazz. E-Jaz, man, big week in AI this week. Big week. Big week. How are you doing, man? Good to see you. China, David.

China's how it's going? 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 Open AI, forget about Anthropics 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 Open AI, and it beats Open AI'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, you know, from China, USA's number one rival, is the fact that it costs next to nothing. And they pioneered two groundbreaking research techniques, which seemed to catch everyone else who spent billions and billions of dollars into this off guard. Did you catch any of this, David? 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 check to check it. Deep Seek 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, well, there's extremely strong evidence that they actually just used ChatGBTGT to train the model. So nonetheless, there were some very real engineering breakthroughs that changed how LLMs work 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 charging 95% less than OpenAI for their API calls. It's just evidence that this is very, very real. But they also just rode on the backs of ChatGBT BT in order to produce their open source. Nonetheless, this thing is going to make waves in American AI models. And now everyone at Facebook at Meta and OpenAI are now understanding the tricks and bells and whistles.

that was built into Deepseek to incorporate that into their models. And I think really people are realizing that 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 in the West versus the East. That's kind of how I understand it. 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 the whole thing.

They open sourced it. They open sourced it. 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. Did you see Archival's tweet? I didn't. 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. Yeah. That was hilarious. We should pull that up. Okay. So I want to 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 want to 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, pre-deepseek, 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. 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 chat GPT. And so what that looked like was data

model and a ton of compute and it was so expensive to do it. It costs billions and billions of dollars to train these things right. But then what these guys, the deep seek team figured out was like okay well we don't have a lot of compute. That's pretty expensive 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, we do know that China has less resources, compute resources available. They are constrained, correct. They are compute constrained because of the chip ban. So even though they are getting able to get around the ban in finicky ways, nonetheless, that is a constraint that they have. 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 a 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 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. Let's not do that again. Yeah, let's not do that again. I wonder if I put my feet on these little peddly 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 make the thing. the bike go forward. So they pioneered this method, David, which basically meant that 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 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. The way that I heard this is that LLMs, and we all, I think we all saw this in early models of chat GBT 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 LLMs 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 for a while. 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 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 actually, my understanding was that this takes more compute. this is more inference time because each chunk has inference, costs inference, and then summating 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 makes a better answer.

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 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 asks this question, can you give us the answer for it real quick? Okay, cool.

Thank you. When you are asking, when you are querying chat chitb-t, you are making it do inference. That is the inference side. When you type in a sentence like, hey, I want to make my mama's banana bread recipe, it's making a call to the GPT model. Anyway, inference is cheaper than training. Full stop, right? So, whilst it's making a lot of-

training is cheap inference. 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 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 Open AI, right? They have the model. When you query it or when you

inference it, it queries the entire model. So think of this model as the design. It hits the entire brain, David. Every single neuron is stimulated. It's queried. Exactly. Now, if we take the deep seek model, it gets a request. And it. It only routes it to the section of the model brain that it needs to hit, which is just so much more efficient. M-O-E. There's something of experts. Mixure of experts, right? So think of 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 every, like, 24 of them are going to shut down and 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 a saving 97% of the energy required. Yes. Yeah, 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 artificial analysis. com, by the way, like just basically tracks all the top models, whether it's closed source or open source. ranks them against each other.

Now, if you look on the left, we look at overall quality of these models. You'll notice that O-1 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, we're like, come on, this, I heard this thing isn't very quick. 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. It's O-1. So it's actually not too indifferent from O-1 when it comes to 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...

O-1 is so expensive. Yeah. Yeah, I mean, Deep Seek is out of four, and you're looking at O-1, 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. 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 deep seek R1 model is measured to be 45 times more efficient than its competitors. It's 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, 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 by doing things other than just throwing brute force resources at it. There's like this ancient, not even ancient. use this metaphor on bank list probably like 20 times over the years to talk about scaling, how scaling works and I use this in the context of blockchains. There's two different ways to get scale out of 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 it's Grand Theft Auto 4. came out on the Xbox 360, and so did Grand Theft Auto 5. 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 5, 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 1, so the hardware is even better. And so this is how blockchains work, right? We can either scale a blockchain by writing better software, and we can also scale a blockchain by using better hardware.

Honestly, the answer is always going to be both. 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 Jevin's paradox in this like Nvidia market crash tech crash that's already recovering. But Jevin's paradox, I think, is something useful to understand. Jevin'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 driving greater demand. AI is now a major economic driver, and Jevin'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. So if I were a left-curve thesis, what you've just said, David, because I think it's very important

and I want people to understand. Deep Seek made models that are groundbreaking much cheaper to make. 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?

Maybe we've been totally over-indexing on compute. Maybe Nvidia is super overvalued. 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 player. It's induced demand.

It's induced demand. So this 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 overdemand for the same thing. 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 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's tokens? And so I kind of want to just 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, soul.

off. It started to pick back up. Here's the chart. I'm looking at the chart right now. It started to pick back up a little bit yesterday, but it's still down 14% since last Friday, which is 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 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. And so we need macro, we need the traditional stock market to like, at least. 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 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 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 EJazz 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 contingent. 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. 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. 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'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? 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. 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 see these prices as kind of like a bargain, right? 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. With over $1.5 billion in TVL, the M-Eath protocol is home to M-Eath, the fourth largest ETH liquid staking token, offering one of the highest APRs among the top 10 LFTs.

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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 usually it's me, E. Jazz, and maybe 100 other people on crypto-twit, AI agent and crypto-twit talking about AI agents. But this last week, different people were talking about AI agents. Can you want to run us through this? Yeah, okay. So we're putting metaphorical bullhats on now, David.

done with the news. It's time to get into why this is so exciting and why, you know, deep seek 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, Open AI and perplexity announced their agent products. What do you have to say about that? So we had Open AI 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 Open AI is going to launch something, blah, blah, blah. Open AI teased their agent.

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 kind of like meets the way. We've already done that, Sam. 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, 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 forward. Techniques, products, whatever it might be.

Just an insanely like opening week for us. Let's watch the introduction of the Open AI agent, just the first 20 seconds of Sam Altman as he talks about this. Good morning. We've got to be an 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. Okay, so my understanding of this, EJez, is that whatever AI, Open AI 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 imbueing inside of Open AIA, do we get that, or is it still closed off to us? So Open AI is still close. 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 close 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. But I bet you that META's 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. Well, isn't China just going to do it? 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 your guys as hard work. And then we're just going to open source all of your labor. Yeah. Well, I'm curious, like, how far this strategy is going to get taken, right? Like, META did it within the U.S. against Open AI 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, et cetera. and 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, it's not something we mentioned, they open source this model, which typically means that they've got a better model underclosed, like, wraps that they have been already been working on for a while.

And I don't know if you saw some, Sam basically mentions that, you know, R1 is very impressive. Deep Seek 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 open AI employees

as well as like, you know, I'm pretty sure Jensen, Jensen Huang of Vennvideo also said something similar being like, wow, this is groundbreaking, blah, blah, blah. So it's put people on their kind of like alert kind of scenario right now. What 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 thing? 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. Yes. And the strategy of announcing that it only cost $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 U.S.-based AI companies. There's like a conspiracy that the hedge fund took a short. position as well. Yes.

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 produce it at scale,

and then just have that become highly competitive with the United States models. So it makes a ton of sense that they are 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 both trying to bolster their own AI tech industry, but also be an attack on American market values of AI tech companies. 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 America's AI darling. 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 going to need to, like, lead the frontier here. And so far up until like literally last week, it was pretty clear that the U.S. was the leader.

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. The fact that it's converging on open source at the end of the day is like, open source just wins. 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 income, right? And it's a cheaper, more accessible model. It's open source, and it can compete with the best of the best.

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 of building something cool in this industry and not just allowing meta and open AI do it

but also like whoa it's China we're scared like what's going to happen blah blah blah blah right but they open source the entire model which means that all the and we're going to bring it back to crypto here people that are working on open source AI things such as agents, you know, the combination of this in Open AI's agent productees is like, you know, it's very, it's very telling is just like the perfect mixture to allow this entire industry to kind of boom. Because it's like, okay, where's the, where's some of the most

important agentic open source activity happening, David? It's in crypto. It's in crypto. It's in crypto, right. It's like some of the top teams are working on pioneering all these frameworks and platforms. So I think we're going to 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 going to 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 going to see a push for more open source AI development. Oh yeah, let's get into some more crypto-native subjects. You have this tweet in the agenda from D-Gen News. Breaking Solana becomes the first train in history to break $200 billion in monthly Dex volume. Why is this in the AI roll-up agenda? How is this AI agent-related? 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 saying it from like certain observations. So the tug of war between Solana and other chains, mainly base, is meaningfully moving into this Salana camp.

Like, Solana's winning the tug of war. Correct. So 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 old-time record. $200 billion. It doesn't take a genius to figure out why Trump launched his Minko. Yeah, right, right, right. On Solana, which like broke everything. So it's not exactly AI-specific, but I'm teeing us up 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 method. They talk about hyperliquid. Every tweet has hyperliquid 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 that, you know, we see meme, we see defy. 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. Is DeepSeek, I think this is a deep seek induced spike, though. So whatever it was, we are higher than what we were. Yeah. Is talking about deep seek. I would actually disagree.

Yeah. Oh, really. Okay. So disagree with me. Why is this not just a deep seek induced attention, mind sure? 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 Twitter doesn't just, sorry, Kaito, which we're referencing here, doesn't just track general AI stuff within crypto. 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 Deepseek 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. 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 it's resilience. You know, it's, you know, just. 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. Now all of those agents pretty much, or 90% of those agents get access to this amazing pioneering new advancement. 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 deep seek. a new AI lab builds, the natural convergence, if it does naturally converge on open source gets it and like why do you pay open AI 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's very bullish. That's very bullish to me. There's a bunch of other subjects that we're going to get into. Virtuals.

We have to talk about virtuals. AIXBT becoming a product. It's something you want to talk about. Venice, Eric Voorhe's project launched a 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.

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And so if you guys want to check them out there, is a link in the show notes to get started. EJS, tell me about virtual. Some very big news happened on Sunday or Saturday, I think. It was a weekend announcement. Walk us through the news that happened in virtual since last week. Okay, so context here. Virtual's 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 they were making a pretty strict move, or a pretty bold move, rather, which is they are going to be also launching on, you guessed it, Salana. 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. 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 onto. 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 it. questions. It's like, hang on a second. What about the virtual's token that I own? Right. On base. Because the virtual token built, deployed contract address is on base. On base. You can only, a token can only have one contract address. Yes, correct. Whatever is deployed first, is it home now and for forever. 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 going to 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 Salana 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 going to have like the kind of same kind of rails, the same kind of ability. And I think they're adding a few other things, David. They've mentioned that they're going to be introducing something known as a venture partner, which I believe

is going to be something along the lines of they'll recruit someone like the, whatever, the best minds or what they believe to be, you know, active contributors in the Salana 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 mentioned, David, that, you know, there was some really overwhelmingly good reactions. There were some overwhelmingly bad reactions as well. 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 going to 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. 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 Salana or on base will get fed back into these same agent tokens, whether they're on base or whether they're on Salana. So everyone technically or theoretically should win.

Every agent on virtuals technically should win. I think if you are a chain maxi, you're just 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 virtual's agent and its token on Solana, and that be a Salana native token address, token contract address. And then also agents, agent tokens that are on base can use layer zero to become, have liquidity on Salana, access liquidity on Salana. So that last part, I'm not entirely confirmed that it's live yet.

Okay. 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 the kind of phase structure. But it's their full intention that all these agent tokens on base can operate and work on Solana. Yeah. Okay. So it's really the idea that new virtual agents can issue their tokens on Solana. That's, I think that's kind of the big punchline for everything to me.

everything else is kind of more marginal than that. 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. It's got the hop-ball money. 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 beam coin on Salana. 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's 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. But David, some of the like top protocols or rather teams that built on virtuals, are kind of like moving over or started to migrate over to Salonor as well, David. If you pull up this tweet from like Vader, so Vader is like one of the top investment dows on virtuals.

You know, they're going to have like, you know, some liquidity prevalent on the salon chain. And there was also another team that migrated, David. I think it was Mika, which, you know, has kind of outlined the entire kind of like roadmap or plan of how they were going to 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. 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. 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, the, the means. 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 didn't get the Coinbase listing and 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 are attribute for like, I think 50% of your Dex volume at one point. Like, how are you guys not figuring this out, right? So anyway, like, I think like stepping away from this like Salon launch. One final thing to mention is the founders in the team, David, are still so locked in dude. It's pretty nuts. I read this interview. I don't know if you have it pulled up, but

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. And, you know, he was, 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. 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. 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 that 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. What that means, I have no idea, but hopefully the coffee tastes great.

Wow. Okay, so one question I have, if you go to the virtual's price, I'm looking at Coin Gecko, down bad. 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 curve brain, it's just because that's where the hop ball of money is. That's where the liquidity is.

It's good for new users. It's good for increasing the, you know, you want to be next. Everyone wants their token next to the hotball of money and that hotball money is on Solana. This actually just didn't show up in the virtual's 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? Yeah, I mean, I would say that this price chart and patent that you've just pointed out, David,

is going to be reflective across a ton of other AI coins. And 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-16-Z. It's 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 U.S. government that apparently has a massive reflection on the rest of the market, we will see similar things here. 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 fundamental.

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pumped about the AIXBT team. So major news this week as they announced, their kind of like product. So if you remember what we mentioned on the pod a few weeks ago was AXPT 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 tailor.

Alpha. That was a lot of money. That was, I think, $150,000 at the time. And so, you know, very inaccessible to most. So what they did was they launched this new AIXBT terminal tiered system, which now allows a range of token holders of AIXBT 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 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. 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 AIXBT and the team. But the two main takeaways was number one, I really like that they're trying to get AIXPT 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 kind of like plans for like a B2B approach, 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,

XBT agent just pop up, you know, just sitting on the edge of your screen there, like kind of like clipy back in the day. What would that be? Like how would that look? What would that pricing system look like? Some really cool, you know, products coming out of this. One big bit of news that I 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 Duck, Duck Go version of Chat, GPD, where you don't need to sign up for an account. to make a query with chat GBT. So it's branded as like private, private chat GBT. 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 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 sign up because Eric Voorhees hates KYC. Venice is something similar. Just no sign up for using this LLM. And so, and Venice launched the VVVT token, which instantly zoomed up to $2 billion, fell back down to about a billion dollars until Coinbase announced that it was listing Venice. And then it went back up. Much to the virtual fans disgrace.

Yes, right? Yes, exactly. Like a very quick token listing, which 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 AIXBT, which is a token on base, Clanker, a little AI bought 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, and then it made its way into listing on Coinbase and it already trades on Coinbase right now. What did you think of this event when you saw this event? Okay, so there's a few things here.

Number one, love that Eric Voorhe's is building out this product. You kind of summarized it well, but rather than think of it as like the chat GPT, think of it as like chat GPT, 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. 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 the 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. It doesn't store any information. And to your point earlier, you don't need to KIC. 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 Deep Seek was released, Venice just plugged straight into it and ran locally. So now you had like the best model and access to it. So, you know, you could just jump on Venice and have like some of the smartest returns, maybe smarter than the leading Open AIO1 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 being 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 Gravall made on this. Paul Gravall is like the chief legal officer. 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 going to miss out on a massive market. So whether it was Paul Grabahl or someone else that mentioned this next specific point that I'm about to make, which is they kind of want to maybe explore doing a list all. approach and then just, you know, retroactively ban or prevent tokens that, you know, are in ill faith.

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, that is a productive output from all of this, David. I also want to talk about just the price performance. So as soon as the VVVT 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 $23. It said $9. And I want to 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 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 has really maintained its value post-listing.

And the Venice price is kind of down only. Now these this is a very, there's a hugely massively apples and oranges because Toshi has been a token for over a year, over a year. And then VVVV is a token for like two days now. So it's not the same.

But what do you think about like retail appetite for memes versus AI tokens on Coinbase. Yeah, I think you raise a really good point, which is, you know, the general archetype of some of the DGens, and particularly DGens 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 time we're like, oh, 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 the toshi or supporters may not like this. And again, I'm going to put my hands up and say, I don't know whether it's true or not. But I believe the supply of toshi is pretty concentrated amongst, you know, a set of holders. So that might also be a reason why, you know, Price was able to pump so quickly and so just because the flow isn't very high.

Yeah. Yeah. And again, yeah. And again, like fact check. on this, I could be wrong, but that could also potentially be a reason. All right, you guys, we're at an hour. Let's kind of burn through the rest of the news here. So Griffin, Arc, AI16, Z.

We're going to burn through these. What's going on with Griffin? 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 sheet, 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. This sounds what Sam Altman announced at OpenAI. Is it just like your agent that can do things? Yeah, it's almost as if the open source crew are like front running a lot of what the centralized corps are focused on, which is, you know, kind of bullish.

But yeah, so a bunch of their 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, which is what happens when you combine a Web 2 product or service with a Web 3 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 Web3 native. We're doing, you know, defy, 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 relate 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 them? a 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 going to make all of this really easy for people to use. They don't even need to know that blockchain's happening on the backend. But I thought that was super cool about the graphane thing. And ARC, the announcement here is

we're teaming up with the Solana Foundation to accelerate AI innovation on Solana. Arc, okay, I remember you telling me about ARC. Arc is all about Rust. These are the Rust AI agents. It's harder, but is 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 that they're teaming up

at the Salana Foundation because I always already figured that they would already be fully integrated with Solana. So what's going on? Listen, there's nothing better than a formal headline on X to pump your price, David.

But actually 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 base, so maybe I'm wrong. Yeah. 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. And then lastly, AI16Z, which I saw formally rebranded because A16Z, actual real A16Z, finally probably sent them a cease and desist. Is that what's going on? Okay, so these are all rumors, and so I don't know the exact specifics, but actually initially, when AI16Z launched, the real A16Z reached out to them and said, hey, this is super cool. Actually, if you remember, Mark and Driesen called out AI16Z saying, this is a really cool project.

I hope you guys kind of make it. And actually there's rumors that the A16 and Z team help them set up their legal structure within the US, which is like pretty awesome, right? Like very hand in hand, centralized, decentralized, 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's some T's to be crossed and some eyes to be dotted. And one of these things potentially is around, you know, namesake and copyright.

Right. And of course, A16Z originally started as kind of like a parody for A16Z. A very small like a $10 million parody, which is no longer now that. Yeah. So basically the likeness was 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 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 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 dows. We've seen the rise of traditional VC funds raising funds specifically for the sector. So it's cool to see some of the core protocols dedicated. it's so much funding towards the space. Pretty awesome. Cool.

All right. Banklos 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? Let's get a little peek into the head of EJazz.

What are you doing over the next seven days or so? Okay. So I'm looking at unsexy agents, David. Unsexy agents. That sounds very unsexy. 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- Middleware agents? 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, deep seek news with Embedia 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 open AI and perplexity teasing computer use for their agents, I have a feeling there's a trend that's going to emerge here on the open source side of things. So digging into those things. 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 the frontier. It's not for everyone, but we are glad you are with us on the bankless journey. Thanks a lot.