This Week in Startups - Bittensor creator Const on Affine, dTAO, "mining reasoning," and more | E2326

Episode Date: August 17, 2026

This Week In Startups is made possible by: Northwest Registered Agent https://northwestregisteredagent.com/twist DigitalOcean https://do.co/twist Odoo https://Odoo.com/twist Today's show: We've been going deep on Bittensor and how it works all year on TWiST, meeting with the creators of some of our favorite subnets, and exploring how the system decentralizes inference, compute, and storage. Now, on this very special episode, Jason and Lon welcome Bittensor co-founder Jason Steeves (aka "Const") to the show. He gives us a quick tour of the project's first principles, before diving into how subnets incentivize miners to contribute, how dTAO turned the creation of subnets into its own competition, how Const says he employs "the internal machinery of capitalism" to rank subnects, and his latest project, Subnet 120 (aka Affine). Find out what the OpenTensor Foundation actually does, go inside the Templar controversy, and learn why Const is trying to make himself increasingly irrelevant. Guest Jacob Steeves on X: https://x.com/const_reborn Bittensor: https://www.bittensor.com/ Affine: https://affine.io/ Relevant Links Original Bittensor whitepaper: https://bittensor.com/whitepaper Bittensor governance and documentation: https://www.bittensor.com/docs Beginner's Guide to Dynamic TAO: https://www.tao.media/the-complete-beginners-guide-to-dynamic-tao-dtao/ Prime Intellect: TOPLOC: https://www.primeintellect.ai/blog/toploc Engy (SN53): https://engy.ai/ Lium (SN51): https://www.lium.io Targon (SN4): https://targon.com/ Templar (SN3): https://www.tplr.ai/ Hippius (SN75): https://hippius.com/ MakerDAO: https://makerdao.com/ Stillcore Capital: https://stillcorecapital.com/ Timestamps: 0:00 The origin of Bittensor (and the name Const) 10:48 Northwest Registered Agent - Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at https://northwestregisteredagent.com/twist 13:55 From Bitcoin mining to mining intelligence 19:33 DigitalOcean - Head to https://do.co/twist to start building on DigitalOcean's AI-Native Cloud today — and cut your AI workload costs by up to 50%. 30:17 Odoo - The all-in-one business platform. Get started for free at https://Odoo.com/twist 32:37 What is a subnet? 33:35 Forcing honest inference from bad actors 37:14 Building a subnet is harder than it looks 40:42 Understanding dTAO 51:57 Where the registration TAO actually goes 1:02:57 All about the Conviction "rug pull" 1:15:19 How Const is making himself irrelevant 1:17:33 The "Buy One TAO" philosophy Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp   Follow Lon: X: https://x.com/lons   Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis   Check out all our partner offers: https://partners.launch.co/   Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland   Check out Jason's suite of newsletters: https://substack.com/@calacanis   Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com

I've been looking for a crypto project that would solve problems in the real world. Instead of just saying, here are all the tokens, have added, everybody starts speculating it's a store of value. You have to make them by solving this mathematical equation. It's not an understatement to say that we are up against nation states because this is truly like China-hurst the United States. Order for the rest of us to take on Open AI, we need to come up with a way that we can work together. For some people, mining the tensor is like the most fun game. they've ever played ever. I predict I'm going to make tens of millions.

That's my goal. This week in startups is brought to you by Northwest Registered Agent. Got a new business idea? Northwest Registered Agent helps you bring it to life. Get a free domain, email, phone number, and more with no purchase required. Learn more at www.w.w.northwestregisteredagent.com slash twist domain. Digital Ocean. Want to see what building on a true AI native platform looks like?

Head to DO.com slash twist to start building on digital ocean. AI Native Cloud today and cut your AI workload costs by up to 50% and Odu. The all in one business platform. Your first app is free. Get started today at ODO.com slash twist. All right, everybody. Welcome back to this week in startups twist. Man, do we have something special for you today?

I have been tau-pilled. Yeah, I think that's fair. Your tau maxing. Bit tensor maxing. There you go, yeah. All of that. Because I, all of that, I have been looking for a crippled. project that would solve problems in the real world, mom.

Yes. And I felt like we got it on Bitcoin. I made some purchases when it was under 100 bucks. I got hacked. I lost it all. My wife bought a bunch under 100 and 200. We made millions. Fentastick.

If you put my Hall of Fame investments on a leaderboard, your Uber's, your calls, are in the top seven. Wow. Look at Jade. Top five. Well, dollar amounts and also in a percentage of terms. So when is Jade raising her first fund?

I think that's the question. She's got half of this one. She's doing okay. Oh, all right. Well, they go. Yeah. And rightfully so, having to deal with me for 23 years. But the second bet I made was on BitTensor.

Why did I make it on BitTensor? I just saw these subnets actually solving problems in the world, and I said, this is what I've been waiting for. Yes. And there's a guy named Const, and he's here with us today to talk about BitTensor. We've been talking about it on this program all year long. It's one of our themes long. I've learned a whole lot about it this year.

Let me tell you. Now let's get into it. Let's bring on Jacob, Steve's. He is also known as cons, C-O-N-S-T, const. We'll find out why. I have a guess. I'm curious. I'm curious as to your guess.

Do we call you const, sir-Const? I'm not calling him Sir-Const. That's not happening. Jacob. Just Jake. It's fun. Jake, it is. Is cons because you're constantly shipping?

Or the protocol is constantly changing and annoying people. Okay, there's that. That too. Actually, it comes from Constantine, the emperor. Sure. Got it. Makes sense. You are the emperor of BitTensor.

Let's start off with why did you create BitTensor? What's the history here? And then I want to get into all the subnet and the economic model, which I find so fascinating. And we're going to break this down if you're a neophyte to crypto or you think crypto is a scam. I really want you to pay attention to this one because there's two times in the history of crypto, I said definitely not a scam, definitely something going on here. It was Bitcoin. I made millions. And it's Tao. I predict I'm going to make tens of millions. That's my goal. So, Kans tell us, where did this all come from, BitTens are in town?

Well, I think there's a project you're probably missing there, which is Ethereum. And, and, and, and, and, and, A lot of people have said that themselves. And Ethereum took from Bitcoin the ability to write these immutable contracts. And they were like, oh, wow, let's abstract that quality of Bitcoin where you can do a transaction. But why don't we make the programming language that allows you to make any type of complicated transaction? Let's build MakerDy, which is a very complicated system of, you know, collateralized lending pools and stable coins. that's all because of the abstraction of the contractual nature of Bitcoin. Hey, let's go beyond transactions, basically.

And that's what people refer to as smart contracts. Yeah, that's the general category. Smart contracts. So, Vitalik saw that and went, there you go. You have Solana and you have Ethereum and all the other L2s and L1s of the world that builds smart contracts. And we do that on BitTencer as well, right? So we also have smart country platform.

But Bitcoin was, I think, two very incredible innovations. One was this contractual layer that Ethereum spun out. And then the other side would be proof of work mining or the computational side of Bitcoin, which goes, hey, we can aggregate all of these contributors if we're across the globe together to solve this one very difficult competition problem, which is to just stuff the blockchain full of shot 56s. and bury the transactions in this immutable time chain so that it can never be taken out by the American government or nobody can do a revision. But the consequence was of being able to build this market for a digital commodity.

I would say it's like the first digital commodity, something that you could mine. It's digital. And it was Bitcoin. It's you mine it for producing hashes. They created this computational network called Bitcoin, which turned out to be incredibly large. like insanely large. And this is a key innovation. Instead of just saying, here are all the tokens, have added, everybody starts speculating,

it's a store of value. They said you have to make them, and you have to make them by solving this mathematical equation, which requires invi-cars Nvidia cards and a computer, a server on the network, or just a desktop computer even. And that meant there was a cost to participate. The cost was compute and electricity. Am I correct in that framing of the innovation? Yeah, exactly.

And what makes it digital is the way which is defined, it's computationally defined commodity, right? Oil is not computationally defined. It's physically defined. But a Bitcoin hash is actually computationally defined. It's whether or not you have solved the Shopify-D6 algorithm with the inputs. And how many you can solve is hashing power. And that's actually something that you can now trade by.

the way. You can trade Bitcoin hacking power. You can sell it. People buy it, which is quite incredible. And so Bitcoin birthed the contractual basis and then also the creation of the first digital commodity. And digital commodities are very interesting because when very well-defined mathematical computational primitives that you can create anywhere in the world by combining things like hardware and electricity together, you build these hyper-competitive markets. Bitcoin is probably the most efficient market we've ever seen in history. Anybody anywhere can buy and sell it. Anybody can contribute to it from any place on Earth by plugging something into the wall.

And those are Bitcoin's, that's what Bitcoin miners machines are. And as a consequence of having this permissionless hyper-competitive market, the efficiency of producing this digital commodity has just gone exponential. Bitcoin's chart is like this, but the power, the proof of work power of Bitcoin is just purely exponential. It just never goes down. So the price is variable because of speculation, regulation, a different market like Korea embraces it, bans it, and then reembraces it. There's so many outside factors that determine it.

But the amount of hashing, the amount of computers and energy in the network has just gone straight up. And this is important because there's another term of art we should define here, which is permissionless and, you know, peer to peer. Something is peer to peer and permissionless. Explain that in plain English and why that's so important in the history of Bitcoin and then, you know, how that impacts BitTensor as we get there. And I want to really take our time on this because there's so many people who think they understand Bitcoin because they understand the price and they may own some of it, but maybe don't understand these core fundamental principles. Well, there's two concepts there. So there's permissionlessness and peer to peer. And so peer to peer is, I can send directly to you without an intermediary. That's actually what Bitcoin wanted to solve.

They were like, let's make a monetary system. It's the first sentence of the white paper, right? You know, sending, I developed a mechanism where I can send a transaction for me to you without an intermediary without the need for a bank, right? Like that's the whole purpose. Because we need intermediaries, then the intermediaries can censor us. Which leads us to the second point, which is, permissionlessness. So peer-to-peer is the thing he wanted. Permissionlessness was a quality that

needed to get to that. And so permissionless means that anybody can contribute, it doesn't matter from where or who they are. Think of it like the ultimate form of non-bias. People are always trying to build these organizations. We don't care about race and gender, et cetera, et cetera. A permissionless market is purely blind. you can contribute it anonymously from anywhere in the world. And it doesn't matter if you are a bad actor or a good actor. It's purely a meritocracy. We don't care if you're in a communist country.

We don't care if you're in a democracy. We don't care if you're 12 years old or 72 years old. We don't care what computer you're using as long as you've got compute. You could be taking solar energy and converting it into Bitcoin. You could be at some nuclear power plant and you have a, closet and you put a couple of computers in there, which people did. Or, you know, you got some city street lamp and ran it to your tent and put a, you know, that was when I knew this thing was truly permissionless when people started hijacking like New York City public lights and

run a cable into their apartment to make Bitcoin. This is what permissionless means. It doesn't mean necessarily breaking the law, but it is a fundamental breakthrough in how the world works. Yeah. Totally. Regular listeners already know that if you've got a great idea for a new business, our friends at Northwest Registered Agent want to help you bring it to life. They're going to be the most amazing partner you've ever had. Even if you're not ready to form an LLC, you still need to take care of some basics. So Northwest Registered Agent is now offering free identity services.

That means a free domain name, open source website hosting, a business email, and a phone number, and everything else that's going to make your new startup look and feel like a professional company, all with no purchase required. And you know you can rely on Northwest because they've been helping people like you start businesses for nearly 30 years. If you have an idea, you can't get out of your head. Or even if you're already building something amazing, you already got started. Northwest Registered Agent is the best way to establish your new company. Learn more at Northwest registeredagent.com slash twist domain. And it means that we just measure the output. And when you just measure the output, it means you opt to you can optimize the output.

And there's nothing hindering our ability to get the maximum amount of that output because they don't have these boundaries. And there's no permission. There's no entrance gate. And it's very difficult to make permission to systems because anybody anywhere can try to cheat. And we don't classically do that. It's actually very difficult to build a permissionless system because up until really Bitcoin, everything was managed. manually done by humans and humans have biases. So there's going to be permission involved with any system that's, you know, even like, let's say an immigration policy will try to be permissionaless in some sense. So like it will be, you know, blind to certain invariable qualities of humans like

their race, et cetera, et cetera. But it's still very difficult because there's a human in the loop and the humans are going to be, you know, have their biases. Bitcoin is permissionless still to this day. And as a consequence of building this pure market, pure permissionless market, you have people contributing hatching power and computing power from all across the globe. And they couldn't have done it unless there was, you know, there and now in the outer rims, which, you know, really says something about the fact that, like,

there's excess qualities out there that these permissionless markets can take advantage of. And so anyways, Bitcoin invented that first example. And it still is growing day to day. And where Bitensor started from was understanding that, hey, well, a really powerful computer should be applied to the most important computational problem of the 21st century, which is artificial intelligence. That's where the idea actually started. I began as a Bitcoiner.

So I was highly interested in Bitcoin, and I was also studying artificial intelligence. and thought, well, okay, how do we connect these two things? How do we connect the most powerful computer in the world to the most important computational problem in the world? And that's the founding raison d'et. I'll jump in. We got Mark Jeffrey here in the comments. He says, Bitcoin showed us a new way to do a company

instead of hiring. You pose a coin reward. Miners compete to get the reward. Miners join, minors leave. Anyone anywhere can compete. Is that part of your vision for where you see this going, that this is going to be eventually a engine for starting a company without, you know, doing all of the build out a small business rigmarole that we think of?

Well, let's, let's, you know, pull a thread between these two concepts. So there was a first, okay, Big Point Mining. All right, let's see if we can build the same type of computational primitive for artificial intelligence. What we needed to invent in order to do that was a very, I use this word a lot, abstract consensus of me, which is that we needed a way, Bitcoin measure something very, very

in sense it's easy to measure. A hash is just binary. It's just true or false. You don't really need to have any complexity there in a consensus mechanism. But in order to measure something like artificial intelligence, which is very high dimensional, it's like, let's say you're measuring

the informational significance of a 124-dimensional vector. Right. Okay, how useful is that to a machine-running model? And that's not as simple as checking a hash. And so we... So Bitcoin, just to summarize that just concisely, Bitcoin had to solve one problem.

Therefore, they just wrote it into the protocol. Like, did you solve the hash? BitTensor has a much bigger mandate, which we'll get into now. And the one criticism of Bitcoin was, hey, beyond speculation and money store transfer, which are valid things in the world, this is a giant energy-sucking machine that doesn't provide any other value. So what is the point of all this compute?

And it was during a time of excess compute. Bitcoin was formed in a time when there was plenty of compute available. In fact, people were trying to figure out ways to get people to consume more. And they were just desperate for you to fire up something new on AWS or Google Cloud or whatever it happens to be, Rackspace, all these great cloud providers, digital ocean, et cetera. But you did get into this, like, is this really worth it? We'll put that debate aside. Now we are in a compute-contrained environment. And BitTencer is kind of having its moment.

So let's go to that origin of BitTensor and how it paralleled and what you built on top of it. Yeah. Yeah, so building this way of creating a proof of work network for anything was originally, the original intention was to train machine learning models, which we do. But it turned out that also there was a lot of different things that we could apply that primitive to that was not just training machine learning models. We could inference machine learning models, as example, which is, you know, when you call them and you get the outputs.

And so there's a couple of subduces on bit tenser. I think you've talked about this recently, the NG subnet, where you can talk to the miners, the miners contribute to compute and they run the outputs of the model. So, you know, that's a broadening of the scope of this primitive. You know, just like how when they abstracted the contracts from Bitcoin, you know, MakerDai, it took a couple of years for people to invent MakerDi. At first, it was just decentralized autonomous organizations, and they all failed. And then we actually got really good at decentralized organizations, and we have everything from Athena, et cetera, and on to the future.

At first, we tried to do information mining, which was cool, but not enough to push AGI. And then we got really good at some of the base primitive stuff, like doing inferences and aggregating compute. But also, and this is one of the points that I know Mark Jeffrey has made in the way that he frames is very interesting. you know, okay, we can buy building these permissionless markets that anybody can contribute to or anything can contribute into it. Any type of computer contribute, you can get storage into it. You can also get latent talent. And perhaps, you know, that's something else that needed to be mined permissionlessly, that hitherto was not, we weren't able to do that. And when you have something simple like Bitcoin mining, you just plug it in the wall, it's done.

But for these higher order commodities, I like to describe them like higher order because they require like hardware to software and then ingenuity. They actually require somebody going on and solving a problem. I'd say that you're creating an algorithm that runs inside of software that runs on top of hardware. And okay, the hardware is commoditized. The software is becoming commoditized because through artificial intelligence. And then you have the innovation and the algorithm and the intuition and the, and the creativity.

The application, in a way, the network layer, and that requires essentially on BitTensor, creating a subnet with a new application. It's almost like BitTensor is, I'm not sure how many subnets there are. I know that's been a, we'll talk about that. But this is where, I mean, I think maybe explaining what the subnets are

and what problems they solve, because you're essentially creating what I've called the Y Combinator, the TechStars, the accelerator of AI, services built on an open platform. Precisely. The truth is, most of the big popular models can handle your AI workloads. Now, your performance, not to mention your cost, that really comes down to your infrastructure,

not your prompts. That's why I want to tell you about DigitalOceans Inference Engine, the best way to serve your outputs fast while keeping things affordable, which is super important, right? DigitalOcean is offering you three ways to run your workloads from a single connection. point. First, serverless for real-time chatbots and agents. Second, batch for big jobs you're running in the background. And third, dedicated for those heavy, always-on workloads where you need more control. It's all running on chips tuned specifically for these kinds of jobs and comes with built-in monitoring so you can always keep a close eye on performance. If you want to understand what building

on a true AI-native platform looks like, go to do.do.co slash twist. Start building on the digital ocean an AI native cloud today and cut your AI workload costs by up to 50%. That's DO.co slash TWIST. Ethereum is a blockchain where you can create lots of smart contracts. Betenzer is a blockchain where you can produce a different type of mining network. Think of it like a contract, but it mines a particular commodity. It produces something of value from storage to inference to training machine-liny models, to scraping the web to stealing API keys and selling them like GM

or pulling innovation from people across the globe. So BitTensor is a platform for building these contracts, like Ethereum is for maybe more classic, it's more contracts that people understand these mining networks. And then into that platform, we actually, actually have those projects mine. They all have their own token. There's some standardization in the way that they're built.

And they compete against each other to attract investment from other other holders in the network from people to hold TOW. And to those projects that perform well, we actually mint the inflation of TOW. So Tau has a 21 million cap. It's just like Bitcoin. There's only 21 million coins ever. there's one produced every 12 seconds. Actually, well, it's less nets.

Half is produced every 12 seconds because we've gone through our first halving event. And that token, that newly minted token gets distributed to these projects as basically additionally acquitted to you know. So each subnet has a reward system built in. Instead of getting a Bitcoin for mining the hash and building out the Bitcoin network, in Tao, you could work on one of 128 different different. subnets. You have to stake. You have to put up some TOW to make one of these. And then you can earn Tau, more or less. So explain the subnet concept and maybe highlight the top two or three in terms of

actual usage and engagement and what problem they solve. Because that really helps people take this from being an abstraction and a philosophy to being, you know, a startup providing a service. Well, if you don't mind, let me try to just explain how, core subnet works in the first place. Because BitTencer is now a meta subnet. It's actually an abstraction on top of itself. So you need to understand the primitive before you can go to a higher level. So a subnet is basically an open network that you can join.

And by join, you burn a little bit of a token to prove that you're willing to play the game. and think of it like paying your entrance fee or, you know, competing with other people to join this day, to buy a lottery ticket. But it's not a lottery ticket because inside this network, your computer that you registered with is going to do some sort of work. Now, a good example of that type of work is that you're going to get, your computer is going to get queried by clients like yourself, Jason, who's using Claude Code, and wants to talk to a machine learning model. and you're going to be running a machine-winning model on your machine, and it's going to answer those requests, and it's going to respond with, yeah, the capital of Texas is Austin, and the next step in this agentic thing is to, you know,

LS into your folders and pull this file. Like all of that is basically talking to an L-LM, and it's competition- inexpensive. And so you can join this network by paying this little fee and running this software on your computer, which is a machine-lending model, and people will talk to it. And inside of this network,

you're going to have another set of participants, what we call valid. that are going to check to see if the computer that you would add it to the network is doing the job faithfully, right? But not just faithfully. Perhaps we're also going to check to see if you're doing it fast and faster than the last guy. And what happens in all of these networks is that people joining, is a continuous role of people joining into the network. And they're measured based on what the network is measuring in this particular design. An example would be I just described what's called inference speed.

right, how fast you can inference a machine money model. It's measuring how quickly you can answer these questions from the clients. And it's paying you more and more based on how quickly you can answer these questions and if you're meeting some sort of bar, right? So think of it like a very well-defined written to code description of how we're going to check to see if the computer that you added to the network is faithfully following the rules and doing the thing and an axis along which you can perform better, right? So perhaps you can combine and and add more computers to your cluster or you can speed them up or you can improve the software yourself and make it faster at serving these inferences. And if you can do that, you can serve a request and over time you can make more money in this network.

And so each of these networks are usually the way that we visualize them is like a curve. And so along the x-axis are all of the different participants. Usually it's about 256 of them. There's 256 computers, which is often more than enough and I'll explain it. why if you're interested later. And then there's the amount that they're getting paid, which tends to go up, well, it goes up to the top. And then there's the ones that are being cycled out at the bottom. And think of it like a league, like the Premier is a good example. I love it. So each of the networks on BitTensor has that this relegation system, this Premier League,

of the thing that the miners, that contributors to the network is contributing. So some of them may be inference. A good example. like a subsample of those projects would be you bring GPUs to the network that people can use. You provide computing power that you inference machine-lony models. So when people are talking to your endpoint that you respond. Or it's an example where you actually train a machine-leaning model. You produce an AI and contribute the AI itself to the network and get paid if your AI is better than the other AIs in the network. That's what we would call in model competition.

So that's a little subset. That would be like Liam, NG, and Affi with some of the top subnetts on BitTencer. That's what they do. The whole premise of one of these projects is that they're able to use this permissionless hyper-competitive market to produce this digital commodity, inference, compute, or models, faster and better than anyone else in the world because we're using the power of Bitcoin. And if that's not their premise, it doesn't make much sense to build on BitTensor. And there, then, that network has its own token.

So it's a think of it like a sub-token to tell, which is like a derivative token. We call a staking token. The name we use is an alpha token, which is a secondary cryptocurrency, which also has 21 million cap that only exists within side of that network that we just described. You need to pay it to enter. you get paid in that by doing well, and if you sell it, you sell it into TAL. That is what a subnet looks like.

And that commodity, we call it alpha token, that token that represents that network, it only has value if at the end of the day people are going to want to buy that token to get access to the computers in those network. So everyone is evaluating these submits based on whether or not they actually have some sort of long-term potential for producing value.

If it's just, oh, it's a network where you can just join and if you just break random numbers, no one's going to buy your token because there's no way to thread any, like a relationship between that thing having value and startup speak. For me, that would be a product with product market fit. So for me, using energy or ENGY, for me, that was, wait a second, these tokens for Quinn, Kimmy and GLM-5-2 are half the price of other places. And it's like, well, wait, how come those are half the price?

And now I'm looking at it, you know, using open router, Claude, Fable, and, hey, maybe I just plug in my API key for energy, and I use that in my ERM as agent. Right. Right. And, you know, and behind that product is this liquid swarm of anybody in the world that can enter and try to reduce that price over time. So right now it's half the price, But it doesn't necessarily need to stop there because whenever this excess compute, that person can plug themselves into this permissionless network and it becomes quite liquid, right? So, hey, I was, I'm not using these computers anymore. Well, I just run the software and I just sell the inference to NG. And as a consequence, you know, we can dramatically reduce the cost of that commodity.

And this dovetails with your previous statement about permissionless and anybody can join to make a little bit of extra tau or whatever. the subnet's token is. So if I'm sitting there and I was, I don't know, providing servers to startups and other folks, and I happen to have, you know, a rack that I haven't provisioned yet. And it's going to be provisioned, you know, in a hundred days. I have a client who's coming online in a hundred days. What do I do with that for a hundred days? Well, I could give it to NG without asking anybody permission and start making money from it. So the downtime would turn into productive time would turn into revenue generation time. Precisely.

If you've got a company, you probably have a tool for invoicing and one for running your website. And then finally, you got one for your CRM, of course. And somehow, even with all these time savers, you're still moving data around by yourself at 10 p.m? That's why, here at Twist, we recommend O-D-O-D-O-O, the all-in-one management software that's already serving 16 million users across more than 170,000 companies. Think about that. They're bringing everything you need into one platform.

That means your CRM, your sales tools, accounting, manufacturing, your website, inventory, and of course your point of sale, if you have a point of sale, all right where you need them. And they're all in constant communication with each other. No more logging every change order or new sale across three different apps. And the dreaded spreadsheet as a database. No, you make a sale and your invoice gets created instantly while your inventory gets quickly updated. So if you're still cobbling together, your back office across five different tools and apps, get started today at odoo.com slash twist.

and your first app is free. That's O-D-O-O-O-com slash twist. It took quite a long time. It's important to put an asterisk here. It took quite a long time for us to figure out how to build these mechanisms. Just like how, you know, the first smart contracts on Ethereum, like the Dow didn't work, right? And you had crypto kitties, and that was cute. But now you have production level stuff and all of these side chains.

How long has Tau been around and how long did it take you to get to what I'll call? Yeah. People have been building mechanisms on BitTencer for two years. So the second year that it's been open for people to build mechanisms on BitTensor, but actually we're 2021. So the network launched with us learning the art of what we call incentive mechanisms. We call subnets the core design, the structure of what a subnet is, which I can talk about at length. It's actually quite an interesting field of the study, the economic study of how do you build a permission, adversarial game where even the worst person in the world,

if Hitler and the devil were to have a child, and then that child were to mine on your subnet, they would just produce value. You know, so you can take away intent, but you need to have some validator that says, hey, this Hitler, Idi Amin, putting servers on here, is not doing so to kill people or to do harm in the world for being a little bit, you know, dramatic.

Cheeky here. Yeah, but they are being judged on a specific criteria, which is, does this server provide inference and provide Kimmy or GLM-5-2? And there's something there with these validators that do this, yeah? In the subnets? Yeah, so we built a mechanism that would allow a distributed set of computers

that could take any code that you wrote Jason for describing whether or not the computer that joined the network is actually, you know, if Hitler and Satan's, you know, a love child was actually doing inference properly, you wrote code that would check that. And these computers, which we call validators, you can elicit them to all run the code at the same time. And if they do so, they will reach consensus if more than 50% of them are running the right code. It's very similar to the way in which Bitcoin works, right? If more than 50% of the network is running the correct code of Bitcoin,

then it doesn't matter if 49% of them are cheating. It's irrelevant. The person, the majority, the honest majority will determine the direction of the incentives in the network. So the core mechanism of BitTensor is that. We can build mechanisms like this so that, yes, we can build a network to this permission list and verifiable and auditable, right? if you know that this distributed set is all running this code, and it's going to take more than 50%

of them, and the decentralization of that set, which is measured in proof of state, it's not like Bitcoin. Bitcoin is proof of warp, which means that the weight of a node is based on how much compute they provide in Ethereum, it's proof of state, which means that the weight of a node in consensus is based on how much economic value they have. It's the same thing in the Tenswer. In this case, if you were, you know, NGO, I'll go to that one because I actually use it. if somebody got on the network and said, yeah, I'm providing GLM 52, you know, this open source model from XAI in China, but they were actually using like some old Deepseek 3 and they were passing it off as GLM 52 to use less compute and they were giving wrong inference.

The validator would say, uh, uh, uh, uh, we're checking that you're actually using the right GLM 52 code, not 51, not 4O, not some other half. Not quantized, yeah. Yeah, and we are going to make sure in a way that there's an SLA, a service level agreement here, which you might have with Google or Amazon WebServes. In a way, you've smart contracted or built into the system, an SLA. The service level is mechanically and architecturally built into the system. Am I understanding correctly in layman's terms?

Yeah, and instead of a contractual, SLA. It's a programmatic SLA, right? So you define the way in which you can check to see if they're doing the right thing.

So for an inference subnet, it's actually very difficult, but the technology is there. The way you do it is you query the endpoint, the endpoint gets a result. And they have to pair that result with a very cheap what's called a ZK proof.

In case of NG53, it's Topaloc, which is an algorithm breeded by Prime Intellect, which is basically hash is the hidden states of the model. Hidden states is like halfway through the machine winning model. They take those basically intermediate representation, and then they project them onto a different mathematical space, and then you don't need to know too much more about it. But anyways, that's basically proving it is what you say it is, It's a way to say it.

Yeah, I'm planning. Precisely. And on BitTensor, these things get, like, it's one thing to write a paper. It's a completely other dimension to write an on BitTensor because we have the smartest people in the world and we have the smartest hackers in the world and they're just right next to each other and they're going to break your system. And if you can build a system that on launch doesn't break, you know, it's like, oh, my God. It's unbelievable because.

So this is. critically important const. If it's permissionless, you can have bad actors, and then the bad actors can be forced to act well and be good actors by the architecture. But you're constantly being stressed tested. You're constantly being attacked because it's permissionless and global. You have attackers who say, hey, there's something at stake here. I can get tokens that are worth something. So there's a value in hacking the system. Therefore, the system must be architected properly. And that's a big part of your job and the BitTenzer Foundation's job is to make sure the rules and the architecture. In a way, you're the police officers or something. You're the,

you're the Jedi Knights of this system, making sure there's peace and that it's being done properly. This is the role that we play reluctantly while it's still required. You know, as all southern owners do themselves. So at the level of the individual subnet, they build a mechanism and it breaks and then they fix it. And then it breaks and then it breaks and then it fix it. And then they get it right and then it starts working and then they make a million bucks. And but in that time, it often requires a lot of ensodging and realignment, you know, to fight against effectively, you know, nation-state militias. You know, there's a level of the people that are trying to destroy your project. And for a lot of people starting a subna on BitTencer, they don't really understand that

that's what they're up against, which is, I think, kind of cute. I often have these phone calls with people. They're like, I want to start a subnet. And I'm like, oh, that's so nice. But you're really not coming at it with the right level of intensity because your adversaries on this network are very serious. And so they could literally be a nation state. It could be North Korea, which, like, North Korea is so desperate for revenue, Lon. I don't know if you remember this story, which we covered. North Korea was placing developers as remote developers in companies, not because they were hacking the companies. They wanted the six-figure jobs.

Yeah, yeah. No, we talked to. They wanted the salaries. We talked about this. How those companies had to develop, like, whole protocols to identify when a North Korean was applying for a job, pretending to be a different kind of remote worker. Yeah, I remember.

Right. Crazy. Building that is difficult, but we have now, I would say, like, the top 10 to 20, some, some pitches, which are premier and they're experts at this, and they can do things like, you know, Subat 51 figured a GPU attestation, you know, trusted execution, without trusted execution, which is quite incredible.

They don't even have TEEs, which is what, you know, Intel does. They built the algorithms that could go in, SSAG into the GPU and checked everything in the world to make sure that that person has that computer and is not cheating. And they built economic derivatives to make that make sense. And so, you know, now those churn. But it took a while for just to build those things. And so this is all just one level. That's just a level of the mechanisms on BitTensor.

But it in and absolutely insane, but it turned out, well, decision by us. We decided to make the actual creation of the mechanisms themselves on the BitTenzer blockchain mechanism itself. So we went, okay, hey, let's apply ourselves to ourselves. We're really good at building this permissionless mechanism. Let's build a permissionless mechanism which selects permissionless mechanisms. And so that was what we launched just over a year ago, which we called Dynamit Tau, which is where all of these subnets got their own token, all those tokens got paired to the Tau, and all of them are trying to push the metric of success inside our ecosystem,

which is increasing their price while staying on, basically. And so our thesis at the highest level of BitTensor is that we want to, hey, this network is going to incentivize and try to optimize people for bringing inferences. Great. Well, we're going to optimize people bringing projects into this ecosystem that produce a lot of value, which we can measure with price, more or less. And, you know, with a couple knobs here. And obviously, it's complicated and we can get into it. But that is what we think will pull the most amount of innovation into the ecosystem and also drive the most amount of value into BitTensor, which I believe does work.

When you look at the way in which, like, the hand overhead crawling towards performing well in this ecosystem, the more competitive we make it, the more badass the teams have become. And it's quite impressive. Like it's truly, it's really reached a point now where the entrepreneurs in this chain are so much better than I am and many times smarter. And I listen to as many of them as I can because they all often are mentors and guides for us at the ecosystem. You know, how could we improve the core incentives of the BitTenzer blockchain? So this is a good pausing moment. again, we'll just stay on E-N-G-Y.A-I.

We've been talking about the person running that is a guy named N-I-N-G-R-E-N. This person came to BitTencer, how and why. Who are these people that come to you or to the BitTencer Foundation, and we should understand what that is and how that works? Who are these people who are attracted to creating these projects and what's their goal? Are they, like, freedom-loving individuals? Are they entrepreneurs? Are they hackers?

Are they some combination of these? A good number of them are scammers. And you kind of can't avoid that because, you know, you have the doors open. And that's part of what we're doing is where we're saying, we can, like, open our eyelids the most, and that's what is going to make us win. But, you know, we're staring right at the sun. So you're going to get a lot of stuff. And so there's a lot of bullshit.

But then there's also the best stuff and the highest quality and the most intelligent people that if they can get across the stigma, because there's a lot of stigma in crypto, well-earned, honestly. And if they can get through that stigma and they can look at the technology and they can see what they can build here. And they understand technically and philosophically, like, why this is such a powerful primitive. Yeah, those people that see it, they come. But you need a level of openness, for sure, because it's not the most treaded path, right? And but so someone like Ning, like he he was brought in by Algod, I believe, who built a team and said he knew this guy who worked at Google Brain where it also worked. And he didn't know about it, but he was told about it and he thought it was super interesting as it is.

And so he got a fascinated and obsessed with it. You know, so there's those people, those types of people that come in. And then, and then there's, and then there's people that have absolutely no academic experience, but they're just raw entrepreneurs that, that go, hey, wow, this is novel. This is the thing that will allow me to build something that can break down that glass ceiling, where, you know, can you really break past these Fiat-funded companies by just doing the thing that they're doing. And I think that the thing that compels a lot of entrepreneurs in our ecosystem, which compels me, is that we need to do something different and better and more

powerful than what they're doing. Otherwise, they'll just beat us with more cash, right? And so... So this is also mind-blowing. The fact that BitTensor exists, and it's relatively stable and providing functionality to the world that some number of consumers and enterprises are dependent on is extraordinary as a technical achievement, but it's also extraordinary, as you're pointing out, hey, there's frontier labs,

there's open source projects out there. There's a lot of competition. This is the highest degree, like what is the chess rating, ELO or something? Like, if this was chess, you're going and playing with the grandmasters, the grandmasters being you know, Elon Musk, you know, Claude, Sam Altman, Open AI. I mean, these, Gemini, Sergey Brin, and his team, like, these are the most elite.

And you have to beat them in the offering, if it was inference in this case. So it's an extraordinary achievement on so many levels right now. And yet, the largest supercomputer in the world is Bitcoin. So, like, this is the type of. that has the example of the only thing that's beat them in Siles. So, you know, there's something to be mined here. And, and like, it's, it takes time to build the future. And but now we're really starting to see, like, what's so exciting right now in BitTencer

is that these primitives just, they just make perfect sense now. So, you know, we just, we turned up the emissions for a lot of subments. We said, hey, you've got to turn up the amount that you're paying miners. And some of the mechanisms like 51, the revenue just scales with the more money you put in because it's permissionless. But companies don't act like that. Oh, here's a bunch of money. It's not necessarily that you can just distribute that immediately and scale efficiently. There's so much inefficiency when you have that.

You try to scale a billion dollars through a human organization. You have to hire people. We were talking at the beginning of the call. You have to fire people. You have to give the contracts. You have to get spaces. you have to find all these things, put them all together. It's not easy, but a mechanism that's just described by really just a code base

in a permissionless market, you just pump more money through it and it just scales. So, you know, because they've tripled the amount of money, they're paying liners, they've tripled their amount of compute in two months. And so, like, these things are really beginning to work and it's really excited to see how they are coming together and meshing together in an ecosystem. But our goal is not just to do more compute and more inference. That's fantastic. Our goal is actually to truly hit to head with the elite centralized labs at intelligence.

This is, I think, the pinnacle commodity that we can measure. Inference and compute and storage, these are sort of predicates. But this is where I think that, well, this is where we're going to go. And this is what we're trying to build right now. And it's much more difficult to measure intelligence. A computer is very difficult. An inference is extremely hard, but measuring intelligence is still possible. It's just very, very, very abstract and hard to get at.

So this is what my personal mission is. And I actually run a subnet on the tensor right now. It's Borla Call it is working on right now. It's called aphine. So we're building the code, the mechanism that can actually measure that pinnacle element. Like, what does it mean to actually grasping your hand intelligence as a commodity? So that's the thing that we're thinking about. And how would one measure that?

We do have, like, humanity's last test. We have all kinds of benchmarks from L-M Arena. Is it as simple as saying, here are intelligence tests? And I want to hear more about Afine. Affine. Affine. Affine. A-F-I-N?

A-F-F-I-N? A-F-F-I-E. A F-N. Okay. I-N-E, Jason. A-F-F-I-N-E. And that's subnet number? 120. There's 120. There's 120. There's 120. There's been talk about 256.

What does it take to start a subnet? How does that work? Do you go to a board of sub-nets? You go to the other ones and say, hey, I want to do this. How does it work? Well, if we had a board, then we wouldn't really be permissionless. you and so anyone can register one

and the way that you do that is exactly the same bractal-like design so it's the same way that you would register into a network of a subnet you basically burn

some token to pay an entrance fee into the league in this case the league is 128 in size a normal subject is 256

So we'll probably get to try to we'll try to get to do 256 at that level as well So you enter into the network and you start building your system and people show up and go hey with how many How many tow do you have to burn or contribute this is like buying a franchise right like buying a team In a Lee? Yeah, let's look it up. Oh, okay And how is that determined? Yeah, it changes every block on on the tensor and so what we we use is a, it's kind of like a Dutch auction. So the current rate is 600 and 8 tau. And we're trying to lower that. So it's, it's about, it costs about $121,000 to have one of these hundred, hundred and 228 slots, which is a lot of too much. And we want to lower that a lot because,

but it's a Dutch auction. So, so the price decreases until somebody's willing to pay for it. And then when someone, when a subnet registers, we double the price and then we lower it again. Well, I mean, it's essentially the cost of joining, uh, money you would get if you joined an accelerator. It's classically been 125K. So it's not, to my mind, like a crazy number, but it's certainly not nothing. So where does that tau go? It just gets burnt and it lowers the amount of Tao in the network or it gets into the foundation. Where does the Tao go? Goes to you? Who does it go to the other subnets? It actually goes to create liquidity in the initial pooling between Tao and, you.

what we call alpha token, so the subnet token. It creates liquidity. So all of these subnets in the tents are all 128 have a liquidity pool, a V3 automatic market maker. It's basically somewhere you can just buy the token through with a little bit of slippage. It's a smart contract itself. And so each one of them has a pairing with tau.

And so you have to buy TOW or to buy those subnet tokens. And this is one of the ways in which we've demand for the underlying token, right? It's like the U.S. dollar, right? It has all of these amazing companies inside of the U.S. system and it has a massive network effect. So we're creating. Are people speculating and just buying five of them and sitting on them if I was like an investor and a speculator? Can I just buy four of them for $500,000 and sit on them? You'd be like I'm a speculator? You know, non-financial advice. Yes, you definitely could do that. And people do do that, right?

We had this question problem, which was, how are we built the platforms so people could build these systems. But we wanted to know how are we going to incentivize the teams? Okay, we still have, you know, 10 million tau to distribute. And, okay, what we're really good at is an optimization mechanism. So let's build an optimization mechanism that these teams can, compete in, right? Where they come in, they get relegated, or they go to the top. And so we came up to this idea of using the price of a paired token as the thing that we would measure. And, you know, that allowed us to build, allowed us to distribute the inflation of tau itself

into a network with people who are mining by creating submits. So people create subnets and they mine TA by creating the subnet. That's the, that's the meta system in BitTencer. And the idea is that as a whole, this network, if we optimize for all those projects to produce a value, which is measured by their price, we can actually elicit the internal machinery of capitalism, which is thousands of individuals from DGens to scientists and the like to long-term investors, we can elicit all of that swarm intelligence to properly order rank these projects. Hey, if you were to sit down right now, Jason, and go, hey, How can we order all of the companies in the United States?

And you didn't have the NASDAQ. How would you do that? It would be an impossible job. So what we do in society is we use markets to do that ranking order for us in some way. So we did the same thing inside the internal market of BitTen. So we elicited this market mechanism, this trading system to order the submits and push the cream to the top, which is what you see. So, you know, when you're entering into the BitTencer ecosystem, I often tell people, you know, be careful because there's some rotten milk and there's some cream and the cream is more expensive than there's raw milk.

And your job for playing this game is to actually help us contribute to the actual movement of this internal system, right? Like, you're actually governing BitTensor. In that way, BitTensor is highly decentralized. They're probably one of the most decentralized networks ever produced. It's not like 10 nodes. It's not 1,000 nodes. There's tens of thousands of nodes contributing and making informed bets on the truth. And so that's how we built.

Yeah, that's how we built it. And that's holistically, I think, what it looks like. It's a extraordinary. Lon, you had a question. Yeah, we got to talk more about A5 before we were on a full-on chat mutiny. They really, the folks want to hear about this. So I'm curious, this is the idea is you're building models? And if so, how are you setting up the competition or how are you setting up the landscape

to ensure that your miners are producing the next generation of models, like, of the kind of model that you want to train and design? Last year, we did produce a model that was better than Twenz's best model at the $35 billion range. And just before we launched it, they launched another $35 billion. model that was better than ours. It's a race. Everybody's in the race now. It's an unbelievable race. It's not an understatement to say that we are up against nation states

because this is truly like China or the United States and there's that level of funding. So it's in no ways easy, but we did produce a very good model, but it didn't take us to the level we wanted. I find's logo is mining reasoning. And reasoning is the way in which a model thinks to itself

so that it can answer a question properly. And so what we have the miners on the network do is we have them produce machine winning models that can produce reasoning, that they can reason, in a way that makes other machine learning models answer the right question. So it's sort of indirect. It's like imagine if I were like, you would think that I'm smart if whenever you talks to me,

you felt a lot smarter yourself. Right. Like I know you better, right? That's a really good sign. It's like it's actually reflective, right? It's like you feel, you're, you know that I'm smart if when you talk to me, like things make sense to yourself. And so right now, this is what we're honing in on as the core mechanism for that network.

Even if it doesn't necessarily produce models that are stylistically perfect, they can, at the very least, if this is successful, the adapters to other machine-winning models. So you could run GLM. and instead of GLM thinking, you would just talk to the smaller model and then be able to go like 30 times faster. Got it.

But that's not the end goal. Actually, the end goal is that we think that mining that latent space of thought is going to be the prerequisite for us training incredibly good models. And so that's what we're doing right now. If you go to Affine I.O., you can participate. For people on the call that are interested, like we're in this really interesting period of time where you don't need to be a machine engineer

and you don't necessarily need to even be a computer scientist to participate in these networks. Like you can literally just get your open call off and send him the website. And he will tell you or it will tell you, whatever you want, gender you want, they will tell you. They will tell you. They them, Zem. Gap is a he. I don't know what you guys are talking about. He's a he and he is my friend.

So he's a he. Okay, great. He will tell you what is needed to participate in these games. and if you can just basically send your AIs to participate in these networks, which is really, really interesting time to be allowed. And this is what I was talking about before the call started with Yilan, about how we work remotely. So I'm nowhere near the rest of my team right now.

But we can all work together through these games. We don't need to be in the same room. We just build these really well-defined. computational and innovation games and then anybody in the world can contribute almost without communicating by just sharing the best work they can they can and if you're not good if you don't come to work it doesn't matter because you're just going to get replaced um very quickly in these hyper-competitive systems so um yeah and the the call-out i've always said from the very beginning like i don't actually really sell tau the token i sell i sell that you can be part of this um and and you should because there's it's very

exciting and it's very fun. It's like for some people, mining the tensor is like the most fun game they've ever played ever. The most dynamic, most interesting, most in-verwarding thing they've done. Along those lines, one thing I'm really fascinated about, we've talked to other subnet or we've talked to subnet owners about this. Like when you're first setting up these competitions, how much are you sort of thinking about the 4D chess of it? Like I have to create a competition or a system that's so tight that no bad action. can come in and like game my system. Like how much a part of the project is that,

that sort of adversarial thinking about? I would say that that is the entirety of the project. Okay, fair enough. All the other stuff is fluffed in some sense. Because you have to think about your, you can start with all the marketing. You can start with the website, and that might help you. And people will maybe invest in your project because they're like, oh, this guy's got a good sense of sales.

But if you can't solve the adversarial problem in the network, then the network produces no value. Right. And so, you know, then it's just lipstick on a pig. And you're wasting your time, you're wasting my time, and everyone's time. And that's the most fun thing. And when you get down to how do you resist adversaries,

you often find that there's this very, like, compressed idea at the very core. a very simple compressed idea that you're truly build it that is like an elemental right okay oh interesting so inference verification is is actually information checking information pair of you're checking that the information produced by this thing is similar to this thing and so they're they're actually they're producing inferences but underneath the hood they're using information and they're trying to produce the information as fast as they can and and so that that is actually the commodity of an inference network where people don't talk about um so anyways that that's like the you know the inside baseball philosophy of the stuff but i i i love that the most there was a

there was an interesting moment when this uh language model got created uh we were on all in and chamoff brought it up with jensen you probably saw that clip where he was like this is is so impressive. Talk a little bit about not only that moment and like what you took away from it, but then the controversy with that subnet and it imploding from what we learned from that. The reason why Templar is called Templar is because when we were building this subnet, we talked about how one of the holy grails in the artificial intelligence, field in the psyche and Neuosphere, whatever you call it, is not decentralized inference or decentralized computing or even what I'm talking about with Affine, with the model training.

It's decentralized training, which is where you have a computer and I have a computer, Lon has a computer, and they are making the same machine-leaning model at the same time. because in order to train a trillion from our machine learning model, you need a hell of a lot of compute. So in order for the rest of us to organically, you know, self-organize and to take on Open AI, we need to come up with a way that we can work together because only together we will have enough compute

to compete with the big guys that have the billion dollars investments in infrastructure. So, you know, we need to figure out how we can train together. But in order to do that, we come up against some like fundamental limits of physics, which is that the way in which these machine learning models are trained is that they merge their weights every step, more or less. They merge them. So you do some work and I do some work and then we just merge them together. And if one of the parameters in your network is pointing this way and the other ones pointing this way and this one is pointing this way, we find this middle point, which would be where the model is the most intelligent,

because you've trade notes and some data and I've trade notes of data, right? It makes sense, right? But in order to move these models across the wire, it's like heavily expensive in terms of bandwidth. We're talking like a terabyte of data more, right? And if we want to do hundreds of thousands of steps, almost hundreds of thousands of terabytes that we need to communicate, which is more than any of us have at our home connections. and it's certainly not what an average person has at their home and not on their laptops. And so how do we aggregate together in the first place if we can't even do it with the internet connection we have?

And maybe we can do it, but it's going to take 10 years, right, which then is no longer important. And then on BitTenSert, to put it from another perspective, we have all of these compute aggregators like Liam and Targon and Cube, which people actually bring in, they plug in their GPUs. But these GPUs are all over the world. So for us to use them, we need to come up with a decentralized training mechanism. So in some sense, like training a trillion per our model is sort of beyond what BitTensor can do

until we can come up with an algorithm that stitches together all of the compute in a way that gets around this bandwidth problem. And it's also the holy grail because a lot of people are thinking about this problem, and people have thought about this problem for a very long time, including myself. So that's why it's called Templar, because the Templars were trying to find the Holy Braille, or they were protecting the Holy Grail.

And so we can't put that name, and we started working on the way in which to do that, which was to take advantage of some of the Tinsers primitives. Like we have hippiest bucket storage, so where all the computers can upload to single places and they download, which is kind of cool. as we built this out. And then we also built the algorithm where we could, what would we be measuring that the miners are doing in the first place? So as I talked to you about like the core of the problem is, okay, well, how do I know that you did the inference, right? So in this, it would be, how do we know that you did the training?

How did you, how do we know you trained on that particular subset of the data that we needed you to train on in order for you to merge with us? and how do we know that you don't just contribute bullshit that destroys our model while we're training? That's really difficult. And training machine minimal is a very fragile thing. If you have one person there that's talking around, specifically my language, it can destroy the whole thing.

This is why, like, when Yelon talks about, hey, the next version of Grox's coming out, he has Colossus, it's a some number of day training run. You throw some, you know, wrench into that machine. you got to start over. And so that's perfect. So what happened when Templar and the rug pull? I know this is like the one thing people use as an attack vector on BitTensor and the subnet

and the architecture. Just candidly, what happened? Does there somebody run off with essentially all the tau in their subnet and just tell everybody to fuck off? And, you know, it's just part of the system. I mean, effectively, you know, in any company, If somebody works in the company, the CEO starts a company, they can just leave. There's actually no contract.

You invest in me. You invest in my company and just be like, I don't want to do it. Right. This happens in early stage startup because some people look at what it's like to be an entrepreneur and they go, well, shit, that's a lot of work. Yeah, not for me. Yeah. And not only it's a lot of work, it's a lot of stress. stress and I just got some investment into my company and maybe I think I'm just going to take that.

So what this person did was they just sold their shares. More or less, they sold their shares. And while they also sold their shares, they wanted to cover up that they were leaving with a reason for leaving. Like it's not that I'm a bad guy. It's their bad. And so I look good. I'm going to cover my ass as I do something that's really shitty, which is.

take a bunch of people's investment and then just walk away, which is a pretty standard thing in crypto, right? Because it's, you know, one of the things about permissionless markets and us allowing for early stage startups from non-incredited investors and things like this is that basically

people get burned. And because most of the time, or like a lot of the time, this kind of stuff can happen, right? And so they wrote an article that basically said, hey, we're not bad for leaving. It's the mean network and cons for being an evil dictator because he sold some of our token,

and that was mean. And then what did they go do? They did another startup, or they want to be a good tent? No, the project fell apart immediately. And, I mean, of course it does, because you kind of like, you can't burn your reputation like that. You can't take money for people and make people to follow you. This is a reoccurring issue for whycom. where somebody goes to the Y Combinator program, if you get accepted, not only do they put that

125K in, they will give you a loan, $375,000 in an uncapped note. Then you get a bunch of people excited and you might get a bunch of people on demo data. Let's just theoretically say, put in another million. Well, I had, this is, I've had multiple people contact me to this. Hey, Jake, you know, you wrote the book, Angel, what should I do here? I'm not getting updates. The project's not active. They raise one. $1.5 million and they're just using it to live off of and we don't see any updates and they're not shipping any product. What do we do? And I say, that's the cost of going to the casino is you could have bad actors. Now you could file a lawsuit. You could do all these kind of things.

You put 50K in to file a lawsuit would be 250K to then pursue it would be a million dollars. And then the outcome is maybe you get back your 50. In the best case scenario. So talking about trust, the startup ecosystem is largely based on trust. We've literally had people take the money from their bank account when we give them these small checks and just yolo it and go crazy. And it's like you, it's kind of like credit card, bad credit cards. You know, you get like a 2% or 1% fraud.

And you're like, okay, whatever, 50 basis points of fraud is what it's going to be. I mean, this happens in every industry. You remember there was that Netflix sci-fi. show they were creating and the guy just took the budget that they gave him and just went and bought a bunch of mattresses. Did that really happen? That really happened. I think he's in jail now where he got, yeah, he got sentenced already.

I remember this. Yeah, he bought like watches and, yeah. Fraud can happen in Hollywood, startups, and on the BitTensor network, I think is the, but you did tighten up the tensor network a bit based on that. Related question from the chat room. Oh, sorry, go ahead. Well, I just want to make a point here, right? So it's a double-edged sword to allow anybody permissionlessly to have access to early-stage startups, right?

Like, this is one thing that crypto does, right? It's like, okay, you can be on the ground floor potentially where you can't for Open AI. And so, like, this is, but as a consequence, we've learned that there's a lot of issues. And so crypto has become a lot more prickly and has thorned. now because people have woken up to the realities of this network. Now, so it's devilage sword, but the benefit is that people get access, and I would say that overall in the business ecosystem, we've made people a lot more money than they've lost.

So that's, you know, I hold on to that. No, but the reason why it's particularly bad in crypto is because in early surge startups, you would invest in, they can't just go and sell their equity into a market automatically. Because there's no, there's no, there's no, there's no, there's no, like, order. There's no secondary market of startups, although people have tried, but even for the nascent ones, there would be no by-side. Exactly. And so, but we, we, in crypto, build those, the buy-side, and we let these things float. And as a consequence, it's part of our technology, right? I spoke about how, like, this internal market is how BitTensor works. It's actually a functioning aspect

of the machine is that we have individuals that govern the network through market dynamics. It's not something that we're not just creating alpha tokens for nothing. We're using them to move like a computer through space. So the reason why it's particularly pernicious in crypto in general is because anyone you can just go and sell on market, hence rug pulls, right? It doesn't exist in startups because you can't do that. There's not going to be a secondary market. And if you just go to your investors and go, hey, quickly, give you my $10 million, I'm out. They'll go, actually, I don't know if I want to buy that because you're selling. So what we built into the chain was basically the best that we could do is go,

hey, let's build sort of an ability for the subnet teams, not enforced, that allow them to express their conviction, we call it conviction by locking their tokens effectively. And in a way that if they want to go and sell them in one big sell, that's a public event. And anybody who invested before them could be like, you know what? I think I want to get out of here because you just did that. And so that's actually led to this. It's been very beautiful actually to see a lot of the teams, you know, go up to the plate and be like, yeah, you know what?

I'm locking this thing perpetually for years. and which by the way, we call that vesting in startups where you vest your shares over time and then you can't sell them and if you do want to sell them, there's a board decision, hey, we're going to do a secondary offering. Hey, as we wrap here,

tell us about the foundation and its role. We had a bunch of questions, Maria 123 asked as well. Not Maria 6, 7, 8. There's Maria 1, 2, 3. Lon. He's got to keep your Maria's distinct, Jay.

It's so separate here in the chat, but what's the role? of the foundation in all of this, and then what's your stake in all of this? Like, as the creator of this, do you have like a gazillion Tao? And how do you stay motivated to keep this holding gone? Because my gut tells me, it's, you know, Tao isn't at the point yet where it would keep going if Kants went away. So how far are you away from making yourself irrelevant in this equation? And then what does the foundation do? I think it would definitely continue if I went away. Most certainly.

It would be, I think, I hope that people would miss me. But there's a vibrant community of people that want to really participate in this network and that they do. And there's an open source community and those people contribute. And there's 128 different teams that understand this technology really well and want the system to go along. And there's the foundation in Canada, which is no longer involved with development. And there's now another foundation, which is more shielded, which is purely about upgrading the chain. So we push a lot of changes to tweak and improve the mechanism. And that goes through our internal governance system on the chain, which we called the Triumbrate,

and which is this year going to be expanded. Basically, because we have a chain that we can build government systems directly into it, we intend to build all of that this year. So that's the two foundations you might call it. There's the OpenTense Foundation and there's the Rao Foundation, and they hold different sides. One's more marketing and outreach, et cetera, and one's more development and upgrading the chain.

I'm no longer involved with Open Tensor. I work just in the Rao Foundation, and I program. That's my language. Actually, this is very unfamiliar for me. Like, I am a programmer at heart. That's how I speak. Awesome. Well, listen, continue success with it. We're going to be monitoring all these subnets. As I told everybody, like, I think buying one tau, just buy one tau is what I've been telling

folks. Why? Because I think it is a ticket to watch something, a spectacular experiment occur. So if you think of it long, like going to see a basketball game, just your 200 bucks or whatever it's trading at. If it's the finals, you're $15,000. or whatever. Okay, sure. But who's counted? It's a front row seat to like bet and learn and it's not financial advice. But it's also like in my, in one way, a vote for me.

Like if you were giving a go fund me, like I don't see it like as a vote of confidence that maybe there could be a decentralized AI intelligence platform out there. And that's good for humanity. Yeah. Pardon me. So I see it as like. And then, oh, and there's a third. What if it is Bitcoin and what if it goes from 200 to?

Yeah, 60,000 or 120,000. Hey, that could be like a great bet. Don't sell too early. That's what I learned about Bitcoin. I had a few and then I sold it when it hit like a thousand. Like I didn't think it was going to go. Dummy. You're big dummy. You got to ride your winners. Anyway, how important is it to get people promoting this and getting involved in it or is that like actually a distraction? The fact that like people like me are speculating on it now and interested in it and I'm obviously a venture capitalist. It's a very passionate fan base. It's a very talkative, passionate ecosystem. Anytime we talk about T. Definitely on X. But yeah, the video goes crazy. How do you think about the pumping in crypto or,

you know, non-builders like myself saying, hey, I want to invest in this because I think there's something here. And I'm fascinated Biden. I like to make a return. And I think this is like risk adjusted for me, like a great, you know, hey, maybe this thing, you know, I look out and go, hey, maybe this thing can go 100 or 1,000 X. That's why I make the bet. it's like a real long shot kind of bet in my mind, but it's also fascinating. So how does speculators like me and then pumping and all that impact these projects on a practical basis, if at all? Well, I mean, I think that it's inevitable and we can't really avoid it.

It's the nature of markets. But it's not the goal. The reason why we have TOW in the first place is so that everyone can have some and that everyone can join and that it can be split up. And in the first place, they can be split up, it turned into a whole 21 million of these things. So, like, I love it that there's people that are excited and that's amazing. And the ones that are inauthentically promoting it, they come, they go. There's always people they're going to say shit on both sides. I can't stop them. I'm way more interested in people that are, that see it the same way that I see it the same way that I

see it, which is more as a really, really powerful technology and that are super excited about that, and the potential for us to build something that's novel and unique and, and competitive and the third path for what artificial intelligence can be born out of. So the, the, the, yeah, but the market dynamics were also really fun. I'm in all the price chats as well. All right. There you go. We got over an hour with the man himself, constantly shipping. You can follow him on Twitter. Kans. Thanks, Jason.

We're born. Great follow. And I think it's great that you're going out and talking. So I appreciate it. I know you've got to get back to coding. But I think it's important for people to understand it, like just from first principles. He did a great job of sharing that with our audience today. All right.

Let's drop. Yeah. Thanks so much for being here, Kats. That was great. Here's the thing along. You know, these projects are so, they have so much potential. And the intention is super important. And when you spend an hour talking to him, it reminds me of what I saw in the Bitcoin early

True Believers. I had somebody on, I think, in 2011. And I saw it then. I didn't make a big enough bet. And now I see this. And just all the signaling is going off. So I was like, let me put like, I don't know if I put like half a million or $750 into this, something like that.

Not a lot of money for me be the equivalent of like, you know, maybe somebody putting in I don't know, a couple of thousand dollars, right? Or I don't know, $10,000. Whatever. You know, it's a smaller bet for me. It's not out of my funds. It's just personal because I think there's something here that's notable. And my signaling goes off.

Just like I had the open-cloth signaling. You remember when that happened? I was like, guys, we got to like pay attention to this. I remember. This reminds me of the mobile cloud computing era when like local mobile GPS all started coming together. I got that signaling for Uber and Robin Hood. that, hey, what would mobile do to trading and getting a car in GPS and all that stuff?

And being early on a lot of this thing, same thing I saw when I bought the 16 Tesla. Now, that doesn't mean you're going to be right. Right. Yeah. But you do have to place the bet is what I've learned. Yeah, I mean, sometimes you are right, but it's just not the right bet at the right moment. I mean, there's no way to know, there's no way to know which bet is the correct one. But, you know, it keeps things interesting.

Yes. And, you know, like the interesting thing for Tesla was, you know, I bought the two cars for 300,000. I wish I just bought 300,000 in shares and just let it sit forever, you know. Yeah. And I always go, oh, you know, I did have shares and whatever, but I, and I did fine. So I'm not complaining. I mean, hindsight on this stuff is always 2020. Like if I could go back in time and tell myself not to sell my few Bitcoin when they were in the thousand.

I was like, I can't believe how much money I made. What a windfall. I'm going to go get myself, you know. And the mistake was you should, you could have sold 10%. or 20%, but you want to keep it, if something's accelerating, you have to ask yourself, is it going to stop accelerating? And so when I look at this, yeah, I think I might actually be down right now in my bit tenser bet, which I made this year.

And I like to be vocal and clear about this so that nobody thinks I have some nefarious reason. And that's why I told folks just by one. Because I realized people were starting to take my tweets online, Lon, and, you know, there's all these Pelosi tracker. Now there's a J-Cal tracker. So when I bought Figma or I said Uber was at a bottom last week when it was like 67, when people were panicking. They think you're Michael Salering.

They think you're- I'm not yolo. I'm not trying to influence anybody. I just like to be honest about it. And when I j-trade something, I just take a screenshot now. Like I bought Figma when it was at 20 because I was like, you know what? Dylan's like a beast. We should have him on the program. I was like Dylan's a beast, you know?

Like he's not going to sit here and lay it down. He understands designers better than anybody. He understands how to make a great tool. build a great brand, get people to pay for it, all that great stuff. I like to make a bet on him. It's now up to $25 a share, whatever, and now they're doing the same thing. They're retweeting it. J-Cal called the bottom on this. Jayco called the bottom on this. You know, my promise to you as the people who listen to this specific pocket is when I do it, I'm going to try to be transparent about it to the extent I can. I can't do that with private companies because it's not my choice to make the

funding announcement. Right. That's the founder and the board's choice. So sometimes I will make a private bet, I'm not at liberty to talk about that. But I try to be transparent with the public. Yeah, the J-trades. Only because the J-trading is all, I'm not day-trading. I'm J-trading. J-trading. J-trading.

That's the nature of J-trading. Now, you may want to quit a stock if you get new information, but I like to find stocks that I'm comfortable holding for a decade. That's my whole period I'm looking for. Sure. You got to wait. In tech, the strategy is always wait for there to be a bad news. cycle, the stock dips, you get it at a little discount, and then you just hold on to it forever.

That's the play. That's true this week in startups. We'll see you next time. Bye-bye. Bye-bye.