Speaker 1Evan, welcome to the show. Boy, am I excited to do this since we met in Houston. And it's good to have you. -
Speaker 2Yeah, it's great to be here. I mean, I'll see if I can match your energy. You're ready, you know? - Did I fire it up? - I got my mod set, I'm ready to go. -
Speaker 3Here we go. - Beautiful. - Well, Evan, welcome to the show. It's a pleasure to have you. We're excited about the store of value, privacy, and this thesis. -
Speaker 1Especially in the week, you know, I want to talk Pearl Rob, but nobody knows what Evan's been doing for the last five years. Like, I don't know that I know, you know, Big East Guy, East Podcast, you know, Anthony Susano, Evan, the East Cabal, the guy has more East than he knows what to do with. What have you been doing in the last five years, Evan? Like, what has your life been? You found Pearl Rob, you know, I didn't mean to interrupt, but like, what have you been doing? -
Speaker 2Oh, yeah, well, I worked still five years ago. I was still in leadership at the Ethereum Foundation. I left out a couple of years ago. I had a little venture fund in there. Maybe three years ago, I left EF. I had a venture fund in there that, you know, it's okay. And I guess, you know, I was sort of like looking for the next big thing. And I was looking around, waiting, and you know, maybe 18 months ago now. I found Pearl and, you know, it was, love it for a site for me. To say exactly what I've been waiting for. I think it's the biggest thing to happen since Bitcoin. I think it's bigger than Bitcoin. I think we're gonna find that out. And, you know, I am, yeah, I've been obsessed with Pearl for, you know, over a year now. So I'm excited to talk about it. -
Speaker 3Yeah. - So, maybe you could just tell us just the concrete transition. Like, obviously we've seen Ethereum Foundation, you know, in all of its glory or not. But maybe before we get real deep into Pearl and near intense, and this, you know, this thesis, like give us the rundown on what should we think about the ETH Foundation or, you know, ETH Labs, or just the state of Ethereum these days? -
Speaker 2Yeah, that's a great question. I'm not sure I'm the best person to answer it because my head is 100% into Pearl. I think there's been some changes. I think they're mostly bullish. I think, you know, there's gonna be a lawsuit filed around stuff that happened in the last year that's coming public in the next couple of days. And that's gonna be kind of cheesy. But, like, or maybe not, maybe nobody cares. But yeah, I mean, I don't know. I'm not the guy to ask anymore. Let me put it that way. -
Speaker 1Yeah, makes sense. - Okay, well Evan, you are the guy to ask about Pearl. I didn't mean to pry there. I was just, you know, genuinely curious. I know we talked about it a bit, but, you know, folks know you as the notable Ethereum bull, the early Ethereum bull, the guy that is early to the things that matter. And, well, you told me about Pearl when we met. I started buying on Safe Trade, Near Intense. Launches is our AI Supercycle show here. Near Intense launched and bottom the market. Classic Near Intense, markets of markets. Those guys are killing, shut up to the sponsor of today's show. And 145, we're at 180 now. This, honestly, this price action is irrelevant. It's like the earliest of network adoption price action. Like, it's, you know, in five years we'll look back and we'll be like, those ticks were like very small in the broader scale of things. So maybe just take us all the way back and give us the story. Like, how did you find Pearl? Who did you meet? What headspace were you in? Give us the story here.
Speaker 2Yeah, I mean, I look, I think I got involved in Ethereum really early because I saw all of the problems with Bitcoin like from an early, early point. And I wanted to fix them. Like, I've never been a Bitcoin believer. I think it like ossified way too soon. I think it has some serious security budget issues. And I mean, obviously like whenever something comes up technologically that needs to happen like quantum, like, I mean, like the fixes are simple, right? I mean, they certainly can do them. They know how to do them. I'm just not sure that the community accepts them. We'll see. I mean, I could be wrong. I tend to be kind of bearish on their ability to fix it. But yeah, I've been, you know, looking for the thing that will flip it going, I guess, for a long time. I found Pearl because I think I tweeted something and I ended up talking to Yoni Simpolinski, the founder of Casbah. And, you know, he was talking to me about possibly doing something in Casbah. It didn't really make sense, I think, for either of us probably. And he mentioned, and I told him, like, I'm not a believer in like proof of work as it exists right now. And he said, well, you know, that's not a big deal. There's this paper published, you know, a month ago or something. It was probably a little bit two or three months at that point that is, you know, I know the guys and they're, you know, super like rock star academics. And if it works, like, then, you know, maybe I'll try to do it. So like, that shouldn't deter you long term. And we kept talking a little bit, but like, I honestly, I really just wanted to meet the Pearl team. And as soon as he said that, like, I, yeah, I mean, there was just like, from me, every, every, every moment from the moment I heard that there was useful proof of work was I just wanted to talk to Pearl. I guess I can, I can say why, right? Which is that, so you know, I think it was 92 that her name was Cynthia Dwork published a combating via processing of junk mail. If something like that was the title of the paper. So proof of work, you know, it's been around. And they didn't even call it spam back then, right? And then five years later, Adam Bash, Adam Back did hash cash, which was like the implementation of that idea. And, and, you know, I remember hearing about this and like reading one of the Bill Gates books back in the, like in the mid 90s about, you know, like, we were, we were gonna fix this spam problem, right? And like he, we had this proof of work idea. He probably didn't say that because actually proof of work didn't become a term until Ari Jules coined it in 99. But I mean, for decades, we have been like, everybody knew that like proof of work was wasteful. And that, you know, it would be so much better if it was actually, actually useful. And so, you know, for what does that mean, Evan?
Speaker 1Sorry to cut you off. What is making proof of work useful me? Because like from our, you know, Bitcoin's useful, right? You turn electricity into Bitcoin and, you know, you get the reward for it and it's at currency and it's got network effects. What is, what is useful proof of work mean?
Speaker 2Yeah, sure. I mean, it's, it's useful for Bitcoin, right? And it's not useful for anything else. So I think a, you know, you can come up with your arbitrary definition of what useful is. I think for most of the people along the way, useful was some sort of societally beneficial purpose. Okay. And so, you know, instead of going to like just, you know, otherwise nonsense computations to solve spam, right? Like that's what it was. So the every, every email you had to do a little bit of computation so that it would make spam unfeasible to send for low value emails. So, you know, for decades, people were trying to solve this and it was conjectured impossible. In fact, I don't think they will mind me saying it, but the team behind Pearl, it's now called Pearl Research Labs. But originally it was called impossible labs. Impossible labs. Because everyone thought that making useful proof of work was just not possible. And it, you know, people said that like people, I mean, academics really for decades have been trying to make this happen. And then Omri Weinstein decided that he was going to tackle the impossible. And then he, you know, he started talking about it with some folks at Nvidia. And then he found Elon and they published a paper and it's gone from there. And the, I think what's, you know, it's not only that it's useful, but I think the really amazing thing is that it's not just that they did useful work, but the actual usefulness is the most important fundamental computation of the rest of our lives, right? It's major multiplication, right? So Pearl is mining via arbitrary matrix multiplication, which is what every AI model, every LLM, every machine learning is like the fundamental computation is matrix multiplication. Both in training a model and in serving queries of interest. -
Speaker 1Is that just like solving hard problems in it? Like, I'm sorry, that Robbie got that one over my head. -
Speaker 2Yeah, yeah, yeah. - Matrix multiplication is also called linear algebra. It's basically you just are sticking a, you know, it's a way you're putting a crop ton of numbers in a matrix and then you are multiplying and multiplying them together. -
Speaker 3And Evan, like with these LLMs, you know, there's kind of like an input, which is the prompt. And then that goes into this big old matrix. Like when we think billion and trillion pyramids. models, right? Those are kind of like the rows and the columns in the matrix. This is very, very rough explanation. But like, the prompt goes into this trillion, you know, this matrix made up of billions of rows and columns. And then, you know, it does a ton of, you know, number crunching, and it spits out the output, right? So input tokens go into the matrix, output tokens come out, and the matrix multiplication is like the probabilistic guesswork that the LLM does to try to predict the right output, you know, give you the right output tokens based on your input. And, and, you know, the other training data, right? So, so you're saying that, you know, the matrix multiplication, the way that it's doing the multiplication is more efficient than the way that it was done before.
Speaker 2No, I'm not saying that it's more efficient. Actually, I mean, there is, right, because you're adding a, a noising process. It is a little bit more inefficient, although there's more to talk about in that front too. But it is, the, the pearl mining, the pearl software is a, first of all, it's a VLLM plugin. So, which is, you know, every, every inference, every LLM query goes, going to go basically through VLLM, right? So, anybody that's serving query, inference can just like add pearl as a sidecar. And the mining will be done on top of their serving inference in a very seamless, light, almost zero overhead way. That depends on the model. There's like, I mean, you know, everybody's BS detectors goes off. And rightly so, when you say something like zero overhead, but it's an engineering challenge to get the overhead as little as possible. There are some models in which they've literally found that the end to end overhead is zero, which is kind of crazy. So, like, okay, so you have
Speaker 1this, sorry, you have this data center, you have these GPUs running inference for AI. You attack on this proof of useful work, verifiable work, algorithm on, so you run a software on that GPU, you are able to mine pearl with very little additional compute usage on top of what you're already doing. And you're able to get paid for that by providing that compute to the network.
Speaker 3Exactly. Yeah. And so, can you go to this, can you go to the part of the story here where these guys go to Elon and Nvidia and they put out this paper? Can you just help us, you know, let's start there.
Speaker 2So, Elon, Elon is the co-founder, not Elon Musk. Elon is an ILAN, not ELAN. Sorry, I had to, what's the question?
Speaker 3So, okay. So, these guys, if
Speaker 2Elon co-founded this coin, we would already be, you know, the opportunity would be over.
Speaker 3Stop out hyperliquity. Who knows? Who knows? And so, the relationship with Nvidia maybe, like, maybe you can just pick up, you know, what was, like, the breakthrough that was made with Matrix multiplication? How is that? Like, let's start there and kind of tell the rest of the story here.
Speaker 2Yeah. I mean, basically, from a really high level, I would say that their technique is they add a bunch of noise to your Matrix. And then they, like, and then the proof that you run, which is the mining condition, like the lottery ticket, like it isn't Bitcoin, is just, you know, hashing functions in Perl. It's not hashing, it's useful work, right? So, sorry, I got a little deep rail there. No, no, no.
Speaker 1No, I think you've explained it already. And I think it's, I think the question is really it's, and I don't think we need to get into technicals about, like, why is it not too good to be true? But I think, like, the next step here is, okay, we understand that the mining is done by GPUs running this software that are used for AI inference. So, we have this kind of, like, near infinite hash rate to be accrued to this network if the thesis plays out. So, that's kind of like where I'm getting to, it was like, the thesis then is that people will use their hardware to mine Perl thus strengthening the network and creating a truly AI backed, if you will, like, form of digital currency.
Speaker 2Yeah, 100%. And, in fact, in some ways, you could think about Nvidia is an ASIC for Perl mining, right? Because Nvidia already, I mean, their whole point of their company is to optimize for Matrix multiplication, right? Now, that's a little bit overstated in that it's possible to mine that you could create an ASIC that would multiply zeros in the current protocol. Then there will be some improvements, like, you will get a little bit more lottery tickets from the mining if you just multiply zeros. And that's one of the big fun cases. And, I mean, we can talk about that if that's, that's where we're going to take it out.
Speaker 3I mean, an example of non-useful work.
Speaker 2Right, yeah. So, right now, I mean, there's a paper out there from early in the network days that's like, you know, the Perl is a scam. Like, everything on the network is useless. And they are like, I mean, 100% correct. Like, I would guess that right now, like, the actual useful work is basis points. Like, it's definitely under 1%. And the reason for that is that the, as I described, like, the high level, like, the noisy and denoising of the, of the matrix, matrices. And then you, there's a snark proof that attached to that. Right now, Perl had to invent its own quantization format. So, every, I mean, I, we're getting a little in the weeds of AI here. But every, every model that served is quantized into some sort of format, right? And these frontier labs, when they release models, they release them in like the least quantized. And that's why the, the results are great. And then people start complaining that it's hallucinating or like, the, it got nuked or whatever. And the reason why I mean, I assume is that they quantize them a little bit more aggressively, because it makes them cheaper to run. Anyway, the whole point is there's a few different ways to, to quantize these models. And that's basically just means it's like to, to shorten up the, the matrix multiplication. So instead of, you know, billions of billions, it'll be a little bit less, right? Like, instead of 80 billion, it'll be 40 billion, something like that. I mean, that's roughly speaking. And then
Speaker 1with that in mind, Evan, with regards to these models, they're going to get better, right? They're going to be just constantly getting better. We're, we're seeing more of the compute build out here, kind of pulling us out from the weeds of the intricate network design. What's the bold thesis here? Like, what has to go right for you to be right? Like, what is the thesis? What's your validations in validations? How big are we talking? Kind of just get us back here on more like put your investor hat on here.
Speaker 2Yeah, yeah. My, my did all the CFA exams hat back on. Yeah. I think it is still technical. It's, it's getting everything that is, is, that is, that is useless work to be useful work, right? I think once that happens, like, that, that is the key thing. And there is a hard fork coming up. The code is already out there. It's under audit that has one of these quantization formats. It's called FP8 or floating point eight. So eight, eight bits of a floating point. And that will enable the network to become useful, right? So you, any, any model that is quantized in floating point eight, FP8 will then be able to be served on Pearl. And right now, like, just the front, the good models are not, are not in their quantization format right now. So, FP8, like, all of a sudden, you can serve a lot of really great models with Pearl. So, I mean, for me, like, the thing that has to happen is the useful work. I, I 100% believe that it hasn't happened yet. I think that there is, like, that is sort of the correct mid-curve fun around, like, around Pearl is that, you know, like, it is not useful yet, right? So, and I personally think that was great, right? It was a good way to bootstrap the network to get it started, you know, and to have this, and to show that it worked with a different quantization format and, yeah, FP8 changes everything.
Speaker 3When you, when you said, so the useful work, right, there's the sidecar that is run along with these models, and you can serve the models, and you can mine Pearl. Yep. And so the usefulness is, is, to the extent that Pearl is useful, right? In the same, like, like, there's the model, and then the thing that you're doing on top of the model is the, is the mining of Pearl. And so the useful work is only so, so useful as in, as so far as Pearl is useful, right?
Speaker 2Work is the matrix multiplication, right? It's the serving, the serving the model serving the proof, right? Like, the proof of useful work is the fact that you are proving that you served the inference, the LLM query.
Speaker 3And so what is the argument for why someone who owns a data center is gonna run, you know, Pearl, Algo, FP8 versus Run, you know, a typical, like we're gonna sort of inference, you know, Opus 55 or something. -
Speaker 2Yeah, I mean, well, this is a very competitive space and you're already like yesterday, I think it was. We saw an early Bitcoin equity miner sold a billion and a half of Bitcoin and is shifting into being a GPU farm, right, for AI. You know, every, like, every edge you need to, like, you need to extract because this is a difficult thing. So I think from a, like, a game theory perspective, if you have one provider, which is, like, you know, which is mining Pearl on top of it, then they will be able to serve queries cheaper than anybody else. - Okay. - And then that's like a flywheel, right? Like, if one guy starts doing it, then everybody else has to start doing it. And then you can ask yourself, well, how many of these guys are going to hold? How many of you these guys are going to dump? And like, obviously, like, some of them are going to dump. Some of them are gonna hold. Some of them will do both. I think one interesting thing that I found is that when I talk to AI people, they actually get Pearl more than, like, crypto people. -
Speaker 1Yeah, I bet they do. Well, because it sounds like a no-brainer. It's, it's, you have fixed cost of your rent, of your facility, of your exit. You know, it's just, here's your spreadsheet, add a line on the green side for your Pearl tokens, dump them if you want them, keep them if you, you know. -
Speaker 3There's some really simple math, though, that has to make sense in order for this to work, right? Which is the inefficiency that's added from the noise of the matrix multiplication is gonna, you know, increase your overhead slightly. And the green in your balance sheet, right? The Pearl line item has to offset and compensate for that. -
Speaker 1And so like analogous to Bitcoin price has to be worth the cost of doing it almost, right? - Similarly, it's different, but is there a price that Pearl needs to get to? I think that's kind of where Rob's getting to. Is there a market, like, similar to like, the cost of, to mine a Bitcoin and the price, is there like a, the cost of the noise that generates you a worst response versus the price of Pearl to be worth it? Like, is there an analysis that's been done on that? -
Speaker 2Yeah, there's been, I mean, I, the, the Pearl team has done a bunch of analysis on that. The, there's also a mining pool, like, Perrin, P-E-R-Y-N, A-I, that I've talked to in the past week that they are waiting for this fork to go live so that they can go live. And, you know, some of the engineering that they've done is around, like, balancing useful work as it comes in with useless work to be fair. But that kind of makes sense, right? Because it's, it's hard to have, you know, like, 24/7 exactly steady inference, right? So, you know, they're going to mix the, the, the, multiplying zero matrices with the useful work. And they are, I mean, they already have, you know, it, the number, the profitability improvement being 50% on a, on a GPU. -
Speaker 1And real quick, on this Perrin thing, can I just put money up to get access to GPUs to mining or do I have to actually have GPUs? Like, there's a GPU cloud, right? -
Speaker 2Yeah, there's, there's marketplaces out there that you can go, read, read. -
Speaker 1Would you recommend that? Like, I mean, not funding to advice. I own Pearl, like, should I mine it? See, we should just buy more. -
Speaker 3Sounds really similar to early Bitcoin days. - Yeah. - When you had mining, you had mining. - You had mining. -
Speaker 2There are mining pools out there. We actually had the, the, it should have been the first. But unfortunately, it was the second mining pool. It already went, went defunct. But, yeah, just like in Bitcoin, I would say you should never mine it. You should just buy it. Like, unless you have some unfair advantage around electricity or hardware, like, it's always going to be better for you to just buy the asset than it is to mine it. -
Speaker 3So, okay, that makes sense. And I think the most timely piece here is the midterms coming yesterday, you know, earlier this week, potential data center moratoriums. This blue wave is frightening the AI trade in the traditional markets. People are thinking that these data centers, what's already committed to might get built out, but they're not going to do too much more than that is the fear right now. And so we're slowing down build out. And I can start to wrap my head around how this could lead to a bullish pearl thesis because to your point around competition, if they're not allowed to scale, they're going to fight tooth and nail for margin. And this is going to increase margin. -
Speaker 2100%. I mean, I think that the, it's hard to come up with all the effects of like exactly whether, you know, less AI data centers in the US is going to be, you know, bullish or bearish for this. But I mean, absolutely, my thesis is that in the long run, and again, there will need to be more forks that have all of the other quantization formats as well. But in my thesis is in the long run, every LLN query, every AI query, so to speak, will mind pearl. So yeah, I think we're going to move on. -
Speaker 3Are they on, with FP8, you know, they'll kind of unlock useful work for floating point eight operations. And then like you said, they'll do, you know, more hard forks for more quantization of, you know, more models, which will unlock even more, you know, call them asset classes, right, or, you know, the potential facets of useful work will expand. Are they also going to negate or, you know, deprecate the non-useful work part of this? Or is that always going to be an effect and more efficient than running this usefully? -
Speaker 2I think that there will always be, you will always be able to get more lottery tickets, right? For the, for the mining, I'm calling it lottery tickets. Like the lottery ticket race by multiplying zeros or ones or whatever it is. I definitely think that is possible. It just won't be economic, because if you have useful work, it will be much more profitable to do the useful, like to serve the AI in-friends and get the pearl on top of it, even if you would get a little bit more pearl by multiplying the
Speaker 3useful work out ways, the extra lottery tickets that you got. Yeah, yeah, exactly, that's the idea. -
Speaker 1Yeah, I mean, look, this is just a similar question from the chat, I mean, maybe you just answered this. Just with the data center, debt issues, circular financing, how do you guys see this affecting the thesis? I mean, my quick take, Evan, and I think Robbie just kind of asked this, and I'm curious, your take. Pearl's so small, like it doesn't matter the data center buildout stops, you know. This thing has, this thing is in like, I don't know, I would guess less than 1,000, if not less than 100 of the major data centers in the US. So like, the thing for Pearl is like, it's not even about the market increasing from here, it's just about getting into the market. Is that right? Or how would you answer that question? -
Speaker 2Yeah, I don't think so. There has been, like the Frontier Labs are aware of this. In some form, there was, we had an event a few months ago in San Francisco, technically north of San Francisco, where we had people from the Frontier Labs. You know, obviously, I'm really used to work in Nvidia. I mean, they are, I mean, Pearl, the entity, the research labs is actually in the Nvidia Startup Accelerator Program, which they don't take crypto companies, right? Because to them, it's not a crypto thing. It's an AI, it's an AI thing. -
Speaker 1Yeah. - Yeah. - $1.82 dollars, what's the FDV? And can we do some valuation math here and try to understand what we're buying right now? I think you have a probably a better question, but I like it, as well. -
Speaker 3It's related to what you're asking, which is market penetration, right? And the TAM here, and obviously that's related to FDV and market cap. So maybe you could just help us understand, very similar to the last question, right? Like, how many data centers are there out there that could run Pearl? And I'd imagine the market penetration to Andy's previous point, it's very, I mean, like you said, basis points, right? So, you know, literally
Speaker 2any major data center is running it right now. Like a lot of the old, like ETH miners have their, like they spun up their GPU farms that were just lying around or mob balls, or they had been running some, mining some random thing and they're mining Pearl. So it is, like I said, it's all useless right now. One thing to note, which is a like an astute, like a AI person might be saying, well, you're talking about open source models and that's only, you know, whatever percent of, although that percent is growing versus the frontier closed source models. And the important point there is that the frontier labs can prolify themselves without any input from anybody, right? Like they can choose to. I mean, I'm sure that the Pearl research labs will be happy to help them if they want to, to prolify their closed source models, but they absolutely can do that. I honestly like, look, if there's a moratorium on data centers in the U.S., like literally if Trump, you know, like wakes up and decides that that's the way he gets back on top, and so he does that by executive order, right? I just don't think it really matters. Like there's, you know, like the they will figure out how to put them in Canada, right, or somewhere else where it does want the economic growth. I mean, Elon's already gonna try to put them in space, right? I mean, he was already trying even before the midterm. So, yeah, I don't, you know, it's a short term turbulence. It is not important to whether it, you know, everything becomes useful on the network. Oh, and by the way, I actually meant to say this as well, and I sort of said it earlier, but the fact that you can multiply matrices, like zero matrices, I think it's actually in some ways a strong point because like I said, like inference isn't steady, right? Inference to meant isn't steady. And so the fact that you can still do like useless work like in keeping your GPU humming along, I think works out for the protocol quite well.
Speaker 1And actually, we're at $3.74 billion FDV. I think that's correct. Putting that at number 88 in the market, you're saying bigger than Bitcoin. Like you're smoking the shisha, you're drinking the cool laid, you're having a matcha, you're talking in Spanish, you're imagining your Patagonian mansion, if this comes true, like I'll be right next to Ordea. What's, what's going to happen for this thing to hit 10 billion, 50 billion, 100 billion? Is that possible? What's your time horizon? What's your valuation framework for this thing?
Speaker 2I mean, the obvious comparable is like Bitcoin. I think, you know, AI changes everything and it is, it is a bit, it is a BTCD fork, right? So like the, the innovation is not in like writing their own, you know, blockchain node or anything like that. It is the fact that they put AI into, into money, right? And I think that changes everything. And I think in the long term, you know, although the direct comparable is Bitcoin and it is going 100% after the, the, the store of value narrative. Yeah. Maybe it gets re-rated not as a crypto thing, but as an AI thing. And that's actually how, like, how everybody thinks of it. So, you know, time horizon, you know, a target. I mean, I know, come on.
Speaker 1I have long for price targeting.
Speaker 2I have long forever. And, you know, like, and so on.
Speaker 1You never want to sell it. That's the thing that got me in Houston. You're like, I've been mining it since the first day and I'm never selling.
Speaker 2Yeah, I mean, I'm definitely never selling until it's a least flip Bitcoin. I mean, I just don't see why I would unless they, I don't think that they will flip Bitcoin anymore. I mean, but I, I never selling it unless I sell. Well, yeah, yeah, right. I mean, I don't, I am, I still hold youth, right? So I mean, that's how, that's how long I'm going.
Speaker 1You and Robbie are both doing that bucket together.
Speaker 2Yeah, yeah. I mean, I, I think, I think we should, like, I mean, as long as I see useful work, I mean, to be fair, right, I think that the range of outcomes is, is wide, right? Like, you could theoretically become the most decentralized money because every data center around the entire world is, is mining it. And, you know, I mean, for whatever reason, like, you know, the, the, the quote unquote cult of store value doesn't form. Maybe Bitcoin fixes itself, maybe it fixes it security budget issues. And, you know, it doesn't flip Bitcoin. Like, I, I do think there is a range between, you know, like, a lot bigger than right now, even as the most decentralized money in terms of, of miners and block production. And, you know, 10x Bitcoin, like, I think, you know, there is, you know, nobody knows. I think there is a lot of, like, religiosity around money that, I mean, Bitcoin has done really well at, at, at, at fomenting. And maybe Ethereum had done better in the past and maybe not so much lately, that, you know, that matters, right? I mean, do, yeah, I mean, even like, to some extent, like, politics, right? I mean, I think the people that are, that are like the AI people are less political, whereas crypto has become, you know, kind of like one side of the aisle, which I think is not true, but that's, you know, I mean, I talked to a lot of friends on the internet, that's what I think.
Speaker 3Have you, have you seen Arthur Hayes' thing, this flop? Because it almost feels as if, maybe it's a direct fork. Okay, so if it's a fork of my understanding is that he's trying to go like currency and Pearl is trying to go like store value from, like, very, you know, left curve way to look at this is like, you know, you got a big block or small blocker debate here. Satoshi, you know, Pearl's vision and Pearl, like, is that the way that this is going to play out?
Speaker 2So basically, it's Pearl's Arthur vision.
Speaker 3Pearl Arthur's vision. Yes, that's fantastic.
Speaker 2I think that's about right. I actually, I'm not familiar with it. I know, I think it is a direct fork. I do think it's like he added something around theoretical payments or whatever. I mean, there's some things you could obviously do to be more payments ask. You know, I mean, candidly, like, I pushed for things before the Pearl's blockchain launched and, I mean, you know, I was sort of maybe directionally effective in some of these things. Like, our block time is 194 seconds, so 3.14. We know that's got a cringe, whatever it is what it is. You know, I wanted it to be a little bit less than that. I mean, to be honest with you, but it was before I got involved, it was going to be higher than that too. So, you know, they can.
Speaker 1All right, boss, man.
Speaker 2They can go and make it more. more payments asking to have shorter block time, all that. I don't know if they're worried about flop or else.
Speaker 3Is there smart contracts on Pearl?
Speaker 2No, there's not.
Speaker 3No. And so, what is the. is the idea for the usefulness of Pearl then to be a store of value or to be used for payments or to be a currency or is there, like. 100%
Speaker 2oriented around store of value. A store of value.
Speaker 1Yeah. Okay. All right. Evan, we're going to let you go, man. All right. I would love to continue the conversation. Can we do a part two like next month?
Speaker 2Anytime. I'm here. I love to do this, like,
Speaker 1honestly, honestly, like, on a monthly basis because I'm going to keep buying. And I just, you know, if you're the guy that kids going to keep us up to date and be bullish and be excited and we can help you out, I'd love that. It was great to meet you and, yeah, any closing thoughts?
Speaker 2Yeah, you can buy it on your intents. It's got Lister this week. As Andy said, you know, it's a. I mean, if you haven't used your intents, like, it's a. maybe poorly named, but, like, amazing piece of software. Um, you know, it maybe only resonates to crypto people, but I like.
Speaker 1Near.com, now, it's near.com. Yeah, yeah, right. He's near.com. Throw up. Near.com. 20% off of your trading fees paid back to you in near tokens. Pearls listed bottom of the market. I bought it under $1.50. Ladies and gentlemen, this has been Evan Van Ness, the biggest, the world's largest pearl holder in the East and in the Americas. Wherever he is. I wish that were true.
Speaker 2Unfortunately, I know it not to be.
Speaker 1All right, Evan, thanks for your time. Yeah, look, this is fun. Cheers. Cheers, buddy. See you, Evan.
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