[00:02:05] It’s infinite money. And I think for somebody from the outside that doesn’t understand AI, they look at that and they’re saying intuitively, they’re saying there’s no way anybody’s going to be able to compete with them because of how much they’re spending on training and the argument or the case for that goes on and on and on.

[00:02:22] But a guy like you and others that deeply understand AI are saying, Oh, that’s not how this is going to work at all. And so explain what you’ve built. Explain why that logic of we’re going to throw a hundred billion dollars at training, and therefore we’re going to have the better model is a false assumption.

[00:02:39] And then give a handoff to this thing that you’re building. Cause I think it’s absolutely fascinating and just kind of help educate us in the way that only NVK can educate us in that you make things so easily accessible. And even though they’re super technical.

[00:02:53] NVK: Yeah. I mean, well, thanks for the intro there. That’s going to be a hard follow up.

[00:02:57] So training models and sort of like inventing the hard science of this large models, right? There’s large language models cost a lot of money. I mean, that part, it does cost a lot. You have this very, very large neural nets that you have to like have a lot of horsepower to train on.

[00:03:16] You need a lot of data to put it through. You need to layer a lot of scientists. A lot of mathematicians, a lot of statisticians, like all the people who normally don’t work at a startup, but that’s to build a model, right? Like think about the models as more like a car engine, right? Think Toyota. So Toyota has this V6 engine that like they stick on almost every car they make.

[00:03:37] Okay. Like from trucks to sports cars, to off road vehicles, it’s the same V6 and then they will add a few other things to it and make it, make it beat. So today, so with this large language models, you have mixed role. You have a llama from Facebook, you have GPT from open AI. There is a bunch more. So with this engines, you can create the appropriate machine, right?

[00:03:59] It always does is like, Hey, and I’m like, I think this letter comes after this letter to make this work and this things have like an incredible accuracy to make it happen. So that’s sort of like basically how this language models work. Now, they’re not very smart. It’s just an engine, right? Like it doesn’t have wheels.

[00:04:15] It doesn’t have a chassis. It doesn’t have a purpose, right? Like you can rev an engine as much as you want in a little booth, engine test booth makes a lot of noise. Great. So what happens is you need to build all the tooling that comes around and that’s the stuff that makes it look like magic. And that’s a lot of human made stuff, often in Python.

[00:04:33] And this tooling includes stuff like Leng Chan that helps you essentially you got to say that the AI doesn’t understand English. Yeah. Okay. None of this model is understanding English, right? These are just vector maps where, you know, it just understands that statistically this other point is here.

[00:04:48] That’s it. So when you create this model that now understands like human topics, say a translation, right? So like you want to transfer from this language to this language, the AI goes there and create, it has this statistical map of like, this word essentially is going to be. Very close to this other word in this other language.

[00:05:06] And then with a lot of points, millions and billions and billions of points, he figures out the right neuropath to sort of like put out what he wants to, to put out. So anyway, so that’s cool. But then you go like, okay, can you please tell me what like Preston had for breakfast yesterday? It’s like, it doesn’t know, it doesn’t know, Preston, it doesn’t know like how to figure out like what breakfast or, or where, or what.

[00:05:32] So what do we do? We go and we build something like, for example, Grok, where we teach it how to access this database of tweets by Preston. And that’s just like a lot of code that we let the agent, the AI agent access and run. As a query on a database. So then it gets like all this sort of tweets by press and talking about breakfast.

[00:05:56] Right. And then it’s, it vectorizes it. What that means is that it transforms all this stuff into points. So that’s the language that it speaks. And then it goes like, okay, well, I have some context now. That’s called the context window. And he goes like, mm, breakfast, Preston, English, it’s sort of like with a lot of woobly goobly there, it comes off of like, he probably had bagel today because he talks about bagel all the time. So that’s the value that the people who are not building the models themselves, the engines, right. We’re starting to build all this other stuff and, and this other stuff is like, how do you embed all this context into the AI model window, the context window, right? So for example, every time you open a new, ChatGPT window, right.

[00:06:47] A new chat, it clears the old context. Right. And it’s kind of like a shame. But as a limitation of the technology, because there’s only so much context in width in bytes, right? That he can stick it into the model in run time. So it has a limit. It’s similar to like a person, right? You learn a new hobby, but you kind of forget other things.

[00:07:07] And there’s only so much you can have in memory at a time. You know, our context window is absolutely ginormous. The machines are not there yet, but they’re, they’re there yet for many other things. So they can remember, like they can have the whole Wikipedia accessible, right? And the models are trained in a snapshot in time.

[00:07:25] So what that means is that when you run that training and you essentially like massage it and teach this thing to think it is a snapshot of data in time. That’s why AI is a terrible at trivia pre being able to search the internet for things. If something happened the day after the data set was used for training, the AI doesn’t know.

[00:07:45] So you just assumed stuff. So what we do now is we have all this tooling that goes and sort of like, you let the AI search the internet, find the context and vectorize it, inputs it into the system. You know what I mean? In that context window, and then it helps you answer questions. Right?

[00:08:00] So what I like to say is like, you have the AI galaxy brain people, right? Building the models. And then you have the left curve apes like us building businesses and sort of like building the tooling around it to sort of feed into the Borg.

[00:08:13] Preston Pysh: You use this term context window to basically have like specialized or updated. You were using me and my breakfast preference as an example, what you’re building is that, would you categorize that as enhanced context windows for individuals? Is that kind of how you would preface what it is that you’re building to explain to people what you are building?

[00:08:34] NVK: Yeah. So, okay. So I’m building Unleashed.chat, right? That was born because I wanted to, to do data analysis, right? So use a model to analyze my source code, my company’s business data. And I’m not willing to give away that data to, open AI for free, right? Like, I mean, they, they’re going to just take your data in terms of services. The data is mine now. So, and I want privacy too, right?

[00:09:00] So Bitcoin company, coinkite. com, right? Like we do a lot of stuff that we don’t want to just give away to the board. And so I went down the rabbit hole of like, how can you run those models privately? And a lot of people do this, you end up running on your own laptop, but like your computers are very limited in GPU memory, right?

[00:09:19] Like that’s the difference between like having a million dollar’s worth of GPUs in a farm, right. That were specialized, create for AI stuff, right. Versus like even the most expensive laptop you can buy. That context window is one of the first things that suffer. And you want the biggest context window as possible.

[00:09:37] Yeah. So that’s why like most phones, they’re going to have AI and things like that. They’re going to have a local sort of like a on device, a little chip that helps accelerate things. But for most things, it’s going to have to go to the cloud, go do the thing there in big space of servers and then come back.

[00:09:54] So on Unleashed.chat, what we did is like, how can I make it so it is as private as possible for myself versus the people working on it? Inside the company and also we saw other people wanted to use it. So like, okay, great. So how can we make this sort of like multi-tenant? So like more people can be on it privately and it’s not perfect, but we’ve done a decent amount of work into making sure that we can’t see what people are doing.

[00:10:18] And, and there’s other things we want to do in the future, but so your contacts is store on your local browser. We don’t have it in our servers and that helps a lot. And anyways, so, so the cool thing is things that I wanted to analyze are for example, time series data. We’re still working on that part.

[00:10:36] Very hard to do time series data with AI, by the way, if anybody’s listening and is an expert on that, please hit me. I love to talk to you.

[00:10:44] Preston Pysh: Explain what you mean by time series data for people who might not understand what you’re saying.

[00:10:48] NVK: So time series data is essentially like, imagine rows on an Excel, right. And you have like a date or time, and then you say like stock prices today, this, and then tomorrow is that, and then tomorrow, the day after is that right. And, and like business data, 99 percent of the data is time series data, right? So that, that is to me, in my opinion, and somebody obsessed with time series data, the most interesting data that there is.

[00:11:11] And so, but that’s surprisingly hard, to build tooling for it. And we’re working on it. And then there was, I wanted to very quickly look at code, right? So analyze our code. So we built this thing where you can just put your GitHub repo and you press a button and inputs, it takes the data in and like, boom, it’s like ready to go.

[00:11:30] And you can do analysis on that. And then I was looking at Nostr. Right. You’re familiar with Nostr. You had, you had a few Nostr folks to talk about it before. It’s just this sort of like decentralized communication network that is great for many things like social media or markets, all kinds of communication is very cool.

[00:11:48] Broadcast system. Anyway, so. I was like, okay, great. So Elon has Grok on Twitter and, but I can’t access it. Right. That data is fully closed and that sucks. So I was looking at Nostr and it’s like, Oh, the social graph and the data is open. So let’s see if we can build Grok for that. And surprisingly enough, like, I mean, it’s totally possible.

[00:12:07] We did it. So we index as much of Nostr that we can see, and then we vectorize everything and you have like live access to Nostr on that. And that’s super cool. I mean, as, as things. Start moving further into Nostr, right? Like Nostrizing everything. It’s a super powerful thing. Not just for like, what did Preston have for breakfast?

[00:12:27] I know that’s very cool topic, but which by the way, Eggs Benedict is my favorite breakfast. No, no, no. I’m going to keep it to bagel. I’m going to keep it to bagel. You know how AIs get everything wrong. Eggs Benedict. Okay. That’s a tasty one. And so with the Nostr part is like, imagine when you have. Like people using for bids and asks, right.

[00:12:45] On a public market or they have, you know, like advertising programs in the air or whatever people are going to end up doing with it. It’s just really cool to be able to query that live and have the social graph with it. I think social graphs, that kind of graph and large language models, they seem to really have interesting interactions. You can discover a lot with that. So we’re playing with that at the, at this time.

[00:13:09] Preston Pysh: So, NVK, you said that you had built Grok for Nostr. If a person is using Nostr, let’s say you’re on Primal and they want to interact with this, I’m assuming that Millian, if he wanted to incorporate access directly to the Unleashed.chat and what you guys have done as far as indexing and vectorizing all of this. That’s something that he could just add as a button in there. It would almost look like Grok on Twitter and all of that from a payment standpoint. So you are pinging a server that’s then taking your model that you’ve developed and it’s, you’re providing that input and then it’s pumping out an output, but that cost energy to basically run it through that model.

[00:13:49] I’m assuming you’re paying with sats or the person that would be accessing this has a micro payment of a hundred sats to basically ping the server and utilize those resources is, am I describing this correctly? And is the vision, I guess, that I’m describing something that you think is going to play out for some of these clients that are hosting Nostr clients.

[00:14:11] NVK: Yeah. So like, it’s nice that you brought that up. So the way we monetize Unleashed was like, how can we have honest sort of pricing? Right. So we just do token time sats. So that all that that means is that like, whatever we’re paying for computation, even though we have the GPUs allocated to ourselves, we try to do that as if it wasn’t, we just charging sats, like it just deducts from your account.

[00:14:35] However, because of Nostr, you can connect your account. Yep. And if you want, you can use DVMs. These are digital vending machines, so you can go through the UI route, right? Like on maybe a million ads to, to Primo, and then you press a button. But what’s really cool is using digital vending machines. This is a very early work in Nostr.

[00:14:54] And what that means is like native to the protocol of Nostr. You can post an event saying, can anybody translate this for me? And it’s a special kind of event. And if the Unleash. chat digital vending machine sees that it makes an offer, like I can do that, this is my cost. Or you can do it sort of like you can do it and say, it costs this for you to see the result.

[00:15:17] So. You can now imagine how, instead of having APIs that you need permission to use and all this stuff, it’s just when we press translate and all of a sudden you don’t care who did it, you create some logic that says like, give me the best price and I don’t like this, this, this one because they never did a good job. And I imagine that for any kind of competition, this gets super interesting.

[00:15:39] Preston Pysh: And what’s interesting to the user is the privacy that they’re also getting from this, as opposed to, Hey, Elon Musk now knows the last 10 questions I asked Grok, and he has a very good idea as to what it is I’m interested in and what it is I’m going to be doing tomorrow, potentially, or whatever.

[00:15:55] So that’s interesting. Okay. So let’s say I was going to use Unleashed.chat for not for like the AI grok use that we just described. But let’s say I wanted to take the last 10 years of my emails. I wanted to train it on how I draft, respond the style. So I take all of 10 year’s worth of email data of the back and forth inside of my account.

[00:16:20] And I want to upload it into this Unleashed.chat. I want to basically train a model on Preston’s email habits or whatever. And then any inbound traffic that I have on email, I now have a model that’s giving me a really accurate. A response that I don’t have to spend a lot of time doing. Is this something that is capable with what you’re building or help walk us through like what some of the capabilities are for people that want to train it on their data or, and then have possession of the model and nobody else has access to all of that information.

[00:16:53] Talk us through that.

[00:16:54] NVK: So we do have APIs, right? So if you want to build a tool that integrates that with your email, it’s like that could be done. I can’t remember right now off the top of my head, the size of the context window. So 10 years of email might be a little pushing, but there is no reason why that can’t be done.

[00:17:12] Preston Pysh: What would something like that cost for me to train it on that much data? And you know, I got a lot of emails over 10 years. Would, would that be pretty expensive? Would it be hundreds of dollars? What would it be?

[00:17:21] NVK: Surprisingly enough, probably like between a hundred and a thousand dollars kind of thing. Maybe a hundred and a thousand. Yeah. I’d have to put it through.

[00:17:29] Preston Pysh: I thought you were going to say a hundred thousand dollars.

[00:17:31] NVK: No, so this is the thing, right? Like if you go to open AI and you want to train a model on, on your staff, they will, I think it’s about a million bucks and they’ll do it for you.

[00:17:39] The thing is that the result will be very similar to just having enough context window. so essentially with the context windows, it’s essentially non-permanent, right? So if you just reboot the GPU or get the context out of the system, which we do after each run, but you keep it locally, that’s it.

[00:17:57] You can’t, you can’t update it with the next. It’s a very similar result. So right now what we’re doing is we’re using Mixtral, which is a really, really good model for many things. I don’t think the context window will be enough, 10 years of emails. I mean, I’d say like, I probably have like a couple of gigabytes worth of emails.

[00:18:14] The point is like, these are all things that like are like reasonably easy to engineer.

[00:18:19] Preston Pysh: Yeah.

[00:18:20] NVK: If there is a market for something like that, I mean, it shouldn’t be hard to just put together something that, that does that. But I think more than the inputting of the emails is having the ability of creating sort of like a, like a hard prompts, essentially, like you’re helping the prompts. So one thing you can do is in the instructions, like that’s a custom instructions. You can say like, whenever I say this, I mean that, or whenever you think I like bagels for breakfast, I actually like this other thing for breakfast, right?

[00:18:49] So you can essentially massage the prompt. Yeah, to have an inclination towards things. So, for example, we had that dream covered like you asked the models about the safety of some medication that like it doesn’t use the data. It just outputs what the government asked them to say. So that’s another interesting aspects of this whole thing is that.

[00:19:16] When you are using the big models in those big websites, they have to follow government guidelines in a bunch of stuff, right? Like if they want that funding, it’s biased. Yeah. Oh yeah. I know. It’s insanely biased, right? Like, I mean, what was it a Google that like made the ratio look of somebody who was not supposed to be anyways, it’s really bad.

[00:19:37] Yeah. And when this big companies release this models, what people try to do is a bit of a lobotomy on them. Yeah. Hmm. They try to de educate them from all this communist stuff and put them as in censored models. Right. It is not perfect. And so people should know that there’s a lot of companies out there to try to pretend they’re like, their models are super based or whatever.

[00:19:57] Right. But you know, it’s all they did is they go there and they type if somebody asks about COVID just answer this, right. And then they look good on demos. But realistically speaking, there’s limits because the, the actual fundamental part of the model was taught in a certain way. So. Even though the models can be uncensored, they’re still not quite there.

[00:20:15] And it’s okay. I mean, you can be productive or you can look for outrage and you pick your path. But anyways, so the models are improving and, we want to have Yammer 3 soon added to the system. We support different models. Different models are kind of better for different things. And there is a lot still that can be done to make all this more productive.

[00:20:36] Preston Pysh: For people that, you know, want to check this out Unleashed.chat. This is what NVK is building on the AI side, super interesting stuff. If you have, what is it? Time chain data experience, and you want to hit them up in DMs. I’m sure he’d love to talk to you more on that. I have a question here on Nostr, but I’m going to push that till later on, because I really want to get into Bitcoin.

[00:20:58] It appears that we might be on the cusp of a big bull run. And for people that, that don’t know who you are, you have the best, literally the best hardware wallet on the entire planet. when it comes to Bitcoin for people that are looking at the video, you can see some of them behind NVK there.

[00:21:13] This is the question I want to ask you. What is the most frustrating security advice that you hear people sharing.

[00:21:21] NVK: Oh, Jesus. The list is long and prosperous.

[00:21:24] Preston Pysh: What’s at the top of the list, though?

[00:21:25] NVK: Oh, man, I think, you know, using, for most people, using DIY devices is just a terrible idea. They’re going to end up screwing themselves.

[00:21:35] Keeping seeds at home? Terrible idea. Doing a 202 multi sig, also idiotic idea, using an old phone as a hydro wallet. Oh, that triggers me so hard. It’s one of those things that we’ve been building now, like, you know, Bitcoin security for, you know, over 15 years, right? Like not just me, like other companies too.

[00:21:56] We got to a point where the security is amazing. Like you buy a cold card for 150 bucks or like a transfer or ledger or whatever. You buy one of these devices and you have like Pentagon level security, like even more actually way more because there’s no back doors. So like it’s way more security than even the Pentagon has for private keys.

[00:22:17] Right. Like it is, it is mind boggling. And. I think as we become more accustomed to our security becoming so good, I think the conversation becomes more complacent because you just assume everybody knows, right? You assume that everybody that’s been around knows and that gives sort of like space to a lot of people.

[00:22:36] Who have not a lot of understanding of security to become like new security influencers. And that mud is the water big time, right? Because you know, the new people don’t know the difference, right? That there is all this like security being built. It’s not like they’re following the Bitcoin mailing list or reading the cold on their devices.

[00:22:52] So it’s a very frustrating thing to see like bad advice being put out because people will get wrecked. Right? Like people get racked and people get racked and then they go tell everybody that Bitcoin self-custody is not safe. And then you have a bunch of people holding ETFs and not real Bitcoin. As a Bitcoin bag holder, it is in your interest to have as many people as possible being self custodying their coins safely, right?

[00:23:14] You don’t want them to lose it on a personal side, but it’s also how Bitcoin remains secure and independent from government central banks.

[00:23:23] Preston Pysh: I suspect that this is only going to get worse moving forward. Oh, absolutely. Yeah. So if, let’s say somebody’s from one of the big banks or, you know, they’re one of these people who’s like, Oh yeah, I’m just going to buy the ETF.

[00:23:36] What’s your message to that person who’s, who has that opinion? And they’re just looking at it like, I’ve been, I’ve had a trading account with you name it for the last 25 years. I’ve never had a concern or issue with. My Apple stock, not being there, I’m going to buy iBit or I’m going to buy FBTC. And you know, it’s just going to be like all the other stuff. And I don’t ever have to worry about it. What do you say to a person like that?

[00:23:59] NVK: It depends on my mood. And normally I’ll just go have fun staying poor, but I always say this. Okay. Like Bitcoin has two propositions, right? It has the debasement proposition where, you know, if you hold. Any kind of Bitcoin, even paper Bitcoin, theoretically, you are protected against debasement, right?

[00:24:17] Your Bitcoin is protected from government inflation. And then there is the sovereignty part of Bitcoin, right? The sovereignty part of Bitcoin makes sure that Bitcoin anti debasement doesn’t happen, but that’s a different conversation. But what happens when the government says, you know what, like, we’re going to tax Bitcoin differently.

[00:24:33] And let’s say you, you really eat into the ETF and you have like, you know, 90 percent of your portfolio in Bitcoin ETF. Now you have a conundrum there. Like that’s a problem, right? They can just take it. What if the trading desk, I imagine most people don’t have a trading desk, but like, let’s say like a big broker goes under and then there is some issues and like who owns what and some issues on those coupons.

[00:24:55] So it’s not ideal. And then there is the fact that you’re simply not. You’re not adding security to Bitcoin. If you’re holding that Bitcoin on an ETF, they are trading that Bitcoin. They might be leveraging that Bitcoin and you’re actually making that Bitcoin go down in price too. I know it sounds crazy, but if you are lending your Bitcoin out, right.

[00:25:15] Or if you were holding a Bitcoin that is owned by somebody else, like a big TradFi entity, I guarantee you that they’re leveraging it or they’re making it available in some other ways to other people to trade against you really. Cause that’s the only time somebody needs your asset is to trade against you.

[00:25:30] Right. So if you take the Bitcoin custody, you’re essentially removing from the system and you’re making sure that nobody can sell or lend out that BTC. Yeah. Right. And you’re essentially making the supply smaller and you’re making the price go up. So you want the price to go up if you’re a Bitcoin person, right? So take the custody.

[00:25:49] Preston Pysh: Yeah. You are one of the few people that I know in the space that’s literally manufacturing hardware and doing it in a successful, profitable way. I think for people that have never run a production line or dealt with supply chains, they don’t understand how hard this is to do and do it well and to do it profitable and do it for a very long extended period of time like you have.

[00:26:16] And I guess the question I have for you is, and the saying goes, hardware is hard, which is pretty generic, but very true. What is it that you would like to tell the audience about hardware manufacturing? And maybe something that you learned that you didn’t know before you got into this line of business that’s just interesting or something that is rarely discussed, because I find the topic to be really interesting.

[00:26:40] NVK: Yeah. I mean hardware is really cool. So there was a saying, I can’t remember who said that might have been Paul Allen. if you’re serious about your software, you make your own hardware, right?

[00:26:49] Preston Pysh: That’s interesting cause that’s a Microsoft quote, right?

[00:26:52] NVK: Oh, there you go.

[00:26:53] Preston Pysh: Right. That’s really interesting because it was more Apple that you would have thought would have said something like this, but this is Paul.

[00:26:59] NVK: It might have been them. I don’t know. I can’t remember.

[00:27:01] Preston Pysh: Okay. We’ll search it.

[00:27:03] NVK: But anyways, the thing is very few things you have to be as serious about, right?

[00:27:07] Like the hardware, right? Like when you have a private key on a device, anything goes wrong. Money gone. Yeah. Yeah. And there is no, there’s no mulligans, right? It’s not like a bank. You can just rewind and you can use general purpose computers. Right. So when you want to do something, you want more features.

[00:27:26] You want to make it prettier, but the more abstractions and the more features, the more things you add, the more complexity you add, and there’s more cold there that could have a bug. You could have a backdoor, you could have issues, right? So what we do in embedded hardware is we try to make it as simple as possible.

[00:27:42] So we pick the actual chips we want to use. And then we developed the actual code. Like there is on a cold card, like every single op code that we’re running on that chip is ours. Like we wrote everything from very scratch. Yeah. And then we pick the other secure elements we want to use. We do the same with them.

[00:27:58] And everything goes in this very sort of like simple. Very bare bones package and building hardware outside of Bitcoin. It’s like, you can take some liberty into like how you want to design it and things. But on Bitcoin, it’s, it’s this crazy universe where we have to be insanely paranoid, right? And so we’re thinking of what if an evil maid swapped the devices?

[00:28:19] How do you protect against it? What if a delivery man opens the package? What if we get compromised, right? Like how can we protect the users against it? So there is protections for every little bit of this things and they’re serious, right? Because we don’t want to be compromised. We don’t want anybody to be compromised.

[00:28:35] So like, how can we de risk every aspect of the operation, right? And that’s not very normal for a hardware company. Yeah. Yeah. Normally they can fix things with a software update or whatever. Right. So we, we go into this like extra crazy level of security to do this things. And just because of the nature of Bitcoin, we were able to do this, if this was some system that needed a server or something else, we would never be able to do this.

[00:29:00] So Bitcoin created this asymmetry of security where you with a design like ours can have this insane security for the price that you can get. It really is remarkable. And when it comes to how our companies, I mean, you learn that like, there is like essentially two things that matter, right? Like it’s logistics.

[00:29:17] And how close down, how, how much can you get to the bottom of the chip? How close can you get to silicon in terms to write your firmware, right? Because if you control the whole stack, it sucks that you’re now stuck with that chip. You have to rewrite everything in order to move to another one, but you control everything.

[00:29:35] Every aspect of it. And then you use your logistics, new knowledge, which we learned through time to make sure you have that specific chip in stock.

[00:29:45] Preston Pysh: Do you consider lifetime buys? I mean, you don’t really have to pay for replacements. Typically people would buy another device, right? So you don’t have to worry about that, I guess. So interesting.

[00:29:54] NVK: So what we do is we have like just very good relationships with the manufacturers and we pick families day. If we did chip families. That if we needed to move, we could, it’s just, it’s a lot of work, but it could be done. So, and we, we have like good knowledge that unfortunately under NDA and stuff about like, you know, end of life of parts, it’s very serious, right?

[00:30:14] Like when you’re talking to chip manufacturers, like. For real, like one on one, not buying off DJ key kind of thing. There is assurances. They can’t just change stuff. Imagine if they changed a chip and then like BMW can’t make a new car because they have to change the whole firmware, right? Like this was true during COVID.

[00:30:32] It was insane. The amount of car makers that shipped their cars, missing chips, it’s just like, sorry, you can’t have this functionality for the next year. We’ll add the chip later. Yeah. But, yeah, it’s pretty cool. It is a, it’s a lot of fun.

[00:30:47] Preston Pysh: It really did show you the dependency on chips. There’s a fantastic book. I’ve mentioned this a couple of times on the show called Chip Wars. It just shows you the dependencies on Taiwan, the lithography process, like all of it. It’s just, and I think because it’s such a specialized piece of manufacturing to create these chips. And how expensive some of these lithography machines are, I want to say some of them are like a hundred billion dollars just for one machine.

[00:31:14] And there’s only one manufacturer, I think it’s somewhere over here in Holland that makes these things. There’s just, it’s such a critical path to production and it’s so vulnerable to disruption. And when you understand all this and you see. The U S is interest in Taiwan and China’s interest in Taiwan.

[00:31:31] You quickly understand why that’s such a heated conversation is because of all these dependencies on these ships and COVID truly illustrated like how scary some of this can get. If that supply chain is disrupted for you in your manufacturing of cold card, is that something that ever got? Pretty scary as far as like receiving chips or is it something that you think about in the lots that you’re buying in order to prevent that volatility or future volatility with things?

[00:31:58] NVK: I mean, it’s a little sort of, it’s always like a little scary, but at the same time we have the scheduling and the parts and inventory and stuff. Well, you’re harder than normally playing a year or two out. Yeah. So, so it’s not the end of the world. for example, there was a typhoon in Asia, right? Like I don’t know, 70 percent of that batch got moved.

[00:32:16] Like it went on an airplane to the wrong country. Then they have to wait out there. So you get used to this things and you prepare for this things. Most of the time it’s just like, really like just a CapEx problem, right? Like, it’s like, can you stock more parts? When you were talking about the Taiwan thing is interesting, right?

[00:32:31] Because. Do you know how people say like humans don’t build beautiful buildings anymore? I mean, it’s just that we got bored of the buildings. Now we’re building like this insane cathedrals. Exactly. Like it is the pinnacle of human technology. It’s not putting rockets in space. It’s like making a two nanometer doped silicon little transistor, right?

[00:32:50] Like it’s insane. I highly recommend people go on YouTube or something and learn how this dies are made. Like it really is mind boggling. But now the most insane part of all this is that. There’s maybe 10 dudes out there that know the pro like the reason why TSMC is TSMC is because of those guys.

[00:33:08] And it really is just one guy. So I don’t know if people notice this, but like a few years ago, Samsung, right? Like, Oh, look, we have this amazing fab. Now we are competitive. And then TSMC goes like, Hmm, hang on a second. The guy who invented the whole like. A manufacturing process, because like having the tech and the papers, one thing, like having that stuff yield in a factory floor is a whole different ballgame.

[00:33:35] And that’s, and it’s normally like, you know, a couple of people know nobody else can do it. So the main guy that came up with the whole thing for three nanometers in for TSMC, they had a fallout and he moved to Korea to teach at the Korea electronics. Thanks. Biggest university there and somehow within three years, Samsung, the lawsuits are amazing.

[00:34:03] Like there is a lot covered on YouTube. I can’t remember if I remember the name of the channel. There’s a really good channel about this stuff. I think it’s like Asian electronics or something like that. There’s this guy, man, like he dives and it’s just so good. This market is wild. You know, in hardware, in like hardcore electronics, there’s often just a few people that do the things.

[00:34:23] Facebook used to have five guys that merged the code for 10, 000 engineers. SQLite has three guys and is the most used piece of open source software out there. FreeBSD, very few people as well. It really is remarkable, like how much human technology depends on like one gray beard.

[00:34:39] Preston Pysh: When you go from, and I’m just ignorant on this. If you would go from like a six nanometer chip down to a three nanometer chip, is it basically twice as fast? Does the math make it?

[00:34:49] NVK: No, it’s not quite like that. The speed is, it gets very complicated on like how to calculate the speed, but it’s going to be a lot faster and a lot better and also more efficient cause we moved from making super big, super fast chips to making way more efficient chips. Arm did a lot of that work.

[00:35:08] Preston Pysh: It might be a little bulkier, but it’s still using the same energy, which is really kind of the main variable that people are concerned with cause that’s the cost to run the machine.

[00:35:18] NVK: Just, just think about like your iPhone. I mean, like it’s insane. Like these things are some of the most modern machines that exist and the power lasts more than a day, like more than all day now.

[00:35:29] Preston Pysh: Yeah. . I gotcha. It’s a big deal.

[00:35:31] Hey, let’s go to this Nostr question. So I’m going to frame this in a, maybe a strange way, but bear with me. So you recently wrote an opinionated guide to Saunas and put it in a long form on Primal. And here’s what I find so fascinating. This is just as elegant and just as useful as medium. And now we’re doing it on Nostr and Primal has just rolled out kudos to Millian and his team, because they rolled this out for people to make long form posts.

[00:36:03] You don’t even have to have like a medium account and like get the publication. I don’t really know what the publication process is for medium, but now you can just do it on the Oster. Anybody can do this. And so I’m reading this article. Let me just read the start of this article, because this is hilarious.

[00:36:20] And this is NVK talking about his opinionated guide, dishonest. One of my fondest memories from this time was the Scottish bath, which involves standing against the sauna wall, execution style, so that somebody can spray you with freezing water from a high pressure hose. I’ve never heard of this outside of South America and can attest to whether it has any real Scottish origin.

[00:36:42] This is just the start of this brilliant article that you posted on, Nostr. The reason I’m bringing this up. Is it appears that Nostr just isn’t a Twitter clone. It appears that it’s becoming something way bigger than that. I’ve talked about this with some previous guests. I mean, we have like decentralized GitHub via Nostr.

[00:37:04] We have now long form posts like medium. We have AI agents. Like we were just talking about that haven’t been fully integrated into clients, but I’m sure it’s coming soon. We have spaces level. It seems almost like the Nostr protocol is this skeleton and all of these other functions that exist today. And I even heard of some other protocol that’s going to try to mimic YouTube.

[00:37:29] Now that’s going to be like almost pointed to from Nostr. Explain to the audience in your opinion, what is Nostr? Because it seems like it might be something way bigger or more than just replacement to Twitter, I guess.

[00:37:43] NVK: Okay, so I’m going to have to show the Nostr Rising miniseries that we’re doing. Okay.

[00:37:50] Because that’s the, it’s an audio thing, NostrRising.com. Because I’m going to take a quote from Fiat Jeff from there. Okay. And the most, like the funniest and best way of describing Nostr is that Nostr is just a bunch of websites. Classic Fiat Jeff. Fiat Jeff, for the people that don’t know, is the inventor of Nostr, right?

[00:38:10] He’s our Satoshi. And what’s fascinating about this view, this sort of mental model is that Nostr is decentralized in the sense of that anyone can put a store and relay server, right? It’s called the relays. And what does this do is imagine, for example, if Twitter was a relay, Facebook was another relay, and I dunno, LinkedIn was another relay, right?

[00:38:30] Now imagine if you could see the replies between the two. So do you know how companies post in all the social medias at the same time, it is a pain in the ass to go look. Imagine if they’re all interconnected and one has maybe long form posts, right? Like because it’s their company blog on medium. And the other one is more like Twitter, right?

[00:38:49] Like on primal. And then imagine if, when you respond to a medium article, it shows up on your feed. Twitter feed. Yeah. On the public square. Yeah. Now imagine that when you have your post, your company post, you can now go and post on the public square and say, I have a new post about my company, right? And all these things are fully like native intertwined.

[00:39:13] Yeah. Fully interoperable. Exactly. You gain the social graph, right? You now own your identity because it’s a key pair, just like Bitcoin. So nobody can take that identity from you. Like if somebody turns off your mastodon, somebody turns off your Twitter, your identity is gone. Right? Like you’re building on somebody else’s land and on also, nobody can take that away from you.

[00:39:34] They can disconnect you from their server and say, I don’t want you on my server, but your identity is yours. And you probably have that content like relayed by other relays, right? So you can’t really be canceled. In the universe, you could be canceled in that specific server, which is also like they should be free to do that, right?

[00:39:55] I mean, you maybe don’t want to host some kinds of content, right? So it gives us this freedom where you have these relationships that are many to many, many to one, one to many, private to public, public to private. You can run a private relay, but then because it’s native. Protocol with the public one. You can, for example, say, let’s say you build some tooling for marketing, right?

[00:40:14] Like Hootsuite or something like that. You can have your whole company internally on a relay that posts internally and comments on public posts internally without the outside seeing it. Oh, yes. And you can have all these things intertwined, right? So for example, when you go highlighter. com and you highlight a quote from my sauna article, Which, I mean, I think the quote I pulled was pretty good.

[00:40:38] It was a great quote. And then, very true by the way, very painful. And you post that quote on the Twitter like use of Nostr on Primal. It’s the same protocol. And the data lives on both.

[00:40:51] Preston Pysh: So in short, you think this is a long game that’s just going to continue similar to Bitcoin, it’s just going to be this grind of adoption that 10 years from now, people are going to look back and be like, Oh yeah, well, it was inevitable, but in the moment, especially early in the moment, you’re kind of looking at it and be like, what is this?

[00:41:07] I don’t know if it’s going to catch on. And then just more, more people just kind of. Continue to trickle in and use it. And the, because it’s completely interoperable, the usefulness of it just is like slowly getting better and better and better. And I think anybody that was on Nostr a year ago to now can see that the performance is like night and day difference, and I can only imagine what another year to three years is going to look like as to what’s happening on there. Would you agree with that?

[00:41:33] NVK: Yeah. So like, I remember Bitcoin in the very early days. It’s like, what is this? And why does it fix everything? Yeah. It’s like, you sound like an insane person, right? You can only help people so far. Yeah. But imagine electricity in the early days.

[00:41:46] It’s like, Oh, and people are going to use this for everything. Technology doesn’t grow like that. Right? Like it takes time. It takes, it takes both education and also tooling and UX to improve and go side to side. And even the people who are in it at the beginning, don’t necessarily know how things are going to play out or like what is going to be used for.

[00:42:04] So like, it’s hard for the skeptics to hear that this thing sort of fixes all these things, right? Because they heard that 10 times already from other technologies that fail. And it’s hard for the people to step in it to understand that people are not going to understand it. Yeah, that’s the norm, right?

[00:42:19] And for the people who’ve been in the Bitcoin grind since the early days, like you’ve already been through this once. So like, it’s okay. We’re going to make it. And with the master stuff, you’re going to start seeing the light switches go on faster than with Bitcoin because it’s social, right? It’s a social graph.

[00:42:35] The way I like to think about it, it’s like for Bitcoin, it’s the medium of exchange, but you can’t do that if you can’t coordinate and communicate. Amen. Right? Like you have to discuss bid and ask. That’s right. And where does the government go? Not just the government, like every like monopoly trying to corner a market or whatever. They try to get in between the bid and an ask and try to take a cut or block completely.

[00:42:57] So when Nostr does to us, it’s like, it help us have like a freedom of communication sort of system where you can have the bid and ask if that is for the marketplace of ideas or if that’s for an actual like trade of a commodity or whatever.

[00:43:11] Right. So. When you’re doing this, when you have this Nostr thing going on, you have this, the switch is going on. And for example, fountain.fm, right? Like they were a 2. 0 thing where for the people that don’t know, it’s essentially like podcasting, but they embed a public key there so that you can now do payments.

[00:43:29] You can send messages to the host. It’s super cool. Right? Like it’s taking the podcast industry by storm kind of thing. It’s just not very common on the main bigger pods yet, but it’s huge. Our pod does that like, and it’s super cool to get those apps with zaps is how you send Bitcoin on Nostr. Yeah. And now fountain.

[00:43:46] fm went and integrated Nostr. So they essentially switched their walled garden content system for people to interact with the podcast to Nostr. And. All of a sudden, every single interaction that people have with my pot goes and shows up to the whole social graph. Like everything is now in the public square.

[00:44:04] Automagically. So like, I can just re quote automatically. So you can just re quote when somebody commented or asked a question and it shows on my social graph, right? It shows on the public square. Now imagine what that’s done to other things. Yeah. Right. Like Medium got kicked out of Twitter, Substack got kicked out of Twitter, right?

[00:44:24] So you can’t get kicked out of Nostr, right? So when people come over and they start doing those activities there, you’re going to have the same thing. So I’m looking forward to, you know, Medium or Substack to convert their system into Nostr and then boom, it’s open.

[00:44:36] Preston Pysh: Yeah. And then you got somebody that’s incentivized to run more clients, right?

[00:44:40] If you’re Medium and you come to Nostr, you want to run your own client. If Twitter comes to Nostr, talk us through this. When you think Twitter would have an incentive to take all their existing server racks, effectively turn them into relays, they’re hosting all that same data that they’ve already been hosting.

[00:44:56] And they’re basically using the Nostr protocol. And then it’s like, they’re looking at the government and they’re saying, Hey, you know, we’re just one of many running a relay. We can’t control their speech. We’re just backing up what’s being said publicly. I mean, it just really kind of shifts the whole dynamic of the company and the incentives and what their actual dependencies are for backing up, you know, communication.

[00:45:17] NVK: Think about it this way. So close social media or any type. It’s more like miles credit card miles useless. Yeah, like it’s cool. I know if you happen to be the person that can rack up a million miles, but like most people just see miles is completely useless.

[00:45:32] Why? Because it’s a closed system, right? Bitcoin. Why is Bitcoin so valuable? Because it’s an open system. Yeah. So Twitter is just miles right now. Now, if they open their system, those notes would go, say, say, Facebook does it too. Now those notes cross the barrier, right? And they can interact with each other in a way that creates a lot more value for everybody, grows the pie.

[00:45:55] And there is a lot of fear in growing the pie, right? Because it’s like, this is my data. This is my server, but that comes with a lot of risk and that comes with a lot of cost. Like I bet they could.

[00:46:07] Preston Pysh: Do you think it’s based on Grok and their AI training that they’re really hesitant to open that up because now Facebook can tap into all that data.

[00:46:14] NVK: I think so in the early days of social media, right? Like the way most of the social news sites hacked was like, Oh, you know, press here, import your contacts and we’re going to contact them. Remember Friendster, Oracut, all that stuff. And then like they would close it down. And then the previous company that had it open goes like, screw you.

[00:46:31] Like you’re just stealing my users. But this is the conceptual problem. Is that my users, we are theirs, like our data and our identity are owned by them. We need to move on from this to like, it is my identity. It is my content and information wants to be free. And you can’t stop this train as a Lyn Alden would put it.

[00:46:56] Preston Pysh: It’s just going to take the awakening of the user to reclaim their data and their security and all of these things.

[00:47:02] NVK: They can’t go back. Once you feel it, once you try it, it’s very difficult to go back. You know, it’s too early, right? There’s a lot to be built. There’s a lot more people to bring over, but he already has like this.

[00:47:14] The vibe is right. The technology is already better. You probably haven’t created a Twitter account in like many years, like me, right? I was trying to create a Twitter account for a product. And what do you mean you need a phone number to create it? And then I tried to put a phone number and then it’s like, Oh no, we already have that one for another account.

[00:47:28] It’s like, I literally cannot create an account on Twitter. This is insane. Like it feels like a bank. You have to go to the bank, show ID and do all that. Where on Bitcoin, you download an app and you’re ready to hold a billion dollars in it, right? The same is for Nostr. You just go in any client and you create your key pair.

[00:47:45] And boom, you’re a master. And if the client doesn’t like you or you don’t like the client anymore, you just take your private key and you put it in another client and boom, all your stuff is there again. You can’t compete with this kind of efficiency. It’s very difficult. And all we need now is time.

[00:47:58] Preston Pysh: Yeah. NVK, I could literally talk to you all day. I really appreciate your time. Anytime we have a chance to talk, I’d learn so much. You’re just so astute when it comes to the technical hardware, software, everything related to Bitcoin, all of it, all the above. If you want to give people a hand off, obviously the cold card, anything else that you want to, we were talking about Unleashed.chat earlier, anything else that you want to highlight.

[00:48:22] For people that don’t know you, you’re very active on Twitter. You’re very active on Nostr and you reply to people’s questions very graciously with your time, sometimes very ironically with your responses. But is there anything else you want to hand people off to?

[00:48:37] NVK: No, I mean, like, listen, just try Nostr. It’s happening and nobody stops that train. And then on the Bitcoin side, just get off the exchanges, get a harder wallet. Any harder wallet is better than no harder wallet. And get your coins off the exchanges and, let’s be free people.

[00:48:51] Preston Pysh: Yeah. Amen to that. All right. We’ll have links to all this in the show notes.

[00:48:54] NVK, thank you so much for your time. Always a pleasure having you.

[00:48:57] NVK: Thanks for having me, sir.

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