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We had to figure out an abstraction on the whole concept of building a digital commodity market in the first place.
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So what was Bitcoin in its core?
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Let s take that core, let s write a language to write digital commodity systems and then supply it.
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And so we did that and then we launched that language to people to build digital commodity systems to help us.
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create this open source artificial intelligence with inside BitTensor.
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And that was what you mentioned before subnets, right?
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It was like, it s our smart contract platform effectively.
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It s becoming an L2 and saying, hey, now you can come in and program this computer to create massive scale computational digital commodities, right?
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Hi everybody, welcome back to the Builder podcast.
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My name is Matthew Sabataro, I m your host and also the founder of Builder Capital, a Web3 native venture capital firm that invests in early projects and founders building in crypto, blockchain, AI, and other areas of technology as well.
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Today I m super excited to have Const, Constable as he goes by on Discord, who is one of the founders of BitTensor.
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I discovered BitTensor early 2022 when I was lurking on Twitter, lurking for alpha as us VCs do, and I came across
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This account, BitTensor underscore, what they were saying was a hybrid proof of work, proof of stake, layer one built on Substrate that enabled miners to use their compute and GPUs to essentially train AI and ML models.
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And they created this very unique ecosystem around miners, validators, and subnets.
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So now they just recently introduced subnets that are use case specific for AI and ML.
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We go into a few examples in this podcast around different AI and ML use cases for BitTensor subnets and a few examples that Constable would like to see implemented as a potential subnet.
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But moreover, we go into kind of his approach to building out the ecosystem, a lot of discussion around aligning incentives and
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how he, within the past couple of years, is able to get BitTensor to where it is now at a $1 billion FDV.
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So it s pretty interesting.
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A project I ve been following closely for a long time.
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So with that being said, we ll get into it.
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Appreciate you coming on the Call of Constance.
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I ve heard a lot about you and I remember the early days when I stumbled across it through Scouting Alpha on Twitter and I came across this profile called BitTensor and I m like,
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I m like, Oh, what is this?
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This is interesting.
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And then we, yeah, we started looking into as a team.
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And yeah, obviously, from the VC capacity, we re always looking to like, is this something we can invest in early on?
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And then I m like, okay, interesting Bitcoin South economics, there s no like private sale.
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So that like, piqued my attention.
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Yeah, I looked into it more.
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I m like, okay, cool.
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This is actually like actual utility for miners that are applied to AI and machine learning and brought me full circle to, you know, sort of
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building a liquid position within the fund and then just kind of diving in ever since you guys released subnets and all this fun stuff.
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So really excited to have you on here and dive into it.
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SPEAKER_00
Thank you.
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SPEAKER_01
That s amazing.
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SPEAKER_01
I didn t know that bad.
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SPEAKER_01
I didn t know you ve been in here for so long.
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There s so many people.
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It s like an iceberg.
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There s the people that are kind of
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visible in the community that are out there.
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They re very talkative.
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They re on Twitter.
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And then there s like the deep community, which the people that I d never really interact with, but they re there and they re like, they re lending us, you know, spiritual energy.
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We seem to have a really, really strong foundation of people that are like holders that love what we re building.
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SPEAKER_01
So it s awesome to meet one.
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SPEAKER_01
And when exactly, when was this, 21, 22?
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SPEAKER_00
Early 2022.
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SPEAKER_00
Yeah.
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Okay.
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So super early when I discovered it, there were not much of a presence online.
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SPEAKER_00
I was like early in the discord and I was talking with a few, a couple of members.
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SPEAKER_00
Uh, the one I kept going back and forth with, I ve never met, never met this person in real life, but floppy fish.
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Maybe, you know, I know they do a lot of yeah.
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Yeah.
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He s contentious character.
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Yeah, and Floppy helped answer a lot of questions around sort of how to get started.
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So that was super cool.
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It s been amazing to follow so far and really excited to sort of unpack this for the audience so they can discover what Midtensor is, how they can get involved.
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how you guys are sort of tackling decentralized AI machine learning, which I think is already incredibly important, but it s going to become even more important in the coming months and years.
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And I think crypto is probably the best technology to be able to solve that.
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So we ve seen a lot of different approaches.
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I think BitTensor stands out drastically from the others.
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SPEAKER_00
But yeah, maybe you can kind of do a more formal intro on how you got started and start with BitTensor.
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Yeah, so we simply
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wrote a language that allowed us to take advantage of Bitcoin s flip technology, which was creation of massive incentivized computing networks.
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So that, you know, people like who Matt mentioned, Whoopi Fish, who s an engineer, can plug themselves in and solve problems underneath an incentive mechanism.
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and that we can use the outputs of the problems they solve collectively and bring them into the collective network, which is BitTensor, and use that value add to solve problems in artificial intelligence.
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One of the biggest ones in artificial intelligence is just computational power.
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How can we go and collect all of these resources around the world and stitch them together and use them to solve gargantuan technical and computational problems
0
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The genius of using digital markets to collect those resources is that rather than define exactly the computers that you want to use, you let the market decide.
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So your computational substrate is adaptive and also can attract resources which other people can never attract, like some
0
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Dark cloud data center in China next to Three Gorges Dam is an example I use, which is something that happened on BitTensor.
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There s a data center there with 30,000 GPUs that was being used to mine BitTensor at one particular time.
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No company in the world has access to that.
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So the question is, how can we bring all that together?
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SPEAKER_01
And people have had this idea for a really long time, right?
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SPEAKER_01
It s not a new idea.
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SPEAKER_01
Like the peer-to-peer technology is all about this.
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How can we, how can we stitch resources together?
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How can we get, you know, something from over here to over there using this new, like the super highway, which is the internet?
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And you had folding at home, you had altruistic computation systems where people would donate their compute power.
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And for brief periods of time, they were massive supercomputers that rivaled even, you know, centralized organizations.
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And then with the advent of Bitcoin, we invented a language for stitching those resources together, but then also validating the resources that are added and paying for them.
0
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And then that was like the killer app or the
0
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you know, the zero-to-one technology innovation, because once we could integrate monetization into the process of basically crowdfunding digital commodities, we could build these massive systems, systems that any government marvels at, right?
0
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Bitcoin is a great example, the biggest supercomputer in the world.
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So we were like, okay, let s write a language to do that for AI.
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And massive computational challenge.
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It s probably the most important computational challenge we have today.
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Everyone is fascinated by it.
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Everyone s scared shitless of it.
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And everyone knows that it s really, really friggin  expensive.
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And people wish that it wasn t friggin  expensive because it s the reason why it s becoming so centralized.
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It s the reason why it s being soaked up by Silicon Valley elite circles and Wall Street funded corporations because it s so expensive.
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And the open source community is trying to find a way of competing with the closed source
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companies which are well-funded.
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And we have, there s so much innovation out there, so many intelligent people, but there s also this monetization problem.
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How are you going to pay all of these people to work together?
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How are you going to pay, how are you going to organize them?
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And how are you going to get them resources they can use to solve this problem and do something admirable with it?
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which is we want it to be given back, right?
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SPEAKER_01
That s the E slash ACK, you know, the accelerationists, they want to develop AI in the open source world and give it back to humanity and allow us all to have our own GPUs, you know, running our own machine learning models.
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SPEAKER_01
And that s very, very, very gallant.
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Endeavor because they re up against really well organized corporations.
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We are trying to bring that level of organization among.
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monetization to the open source world for the pursuit of artificial intelligence so that we can liberate this technology back to humanity.
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And the way we re going to do that is by building a super open ownership, open contribution, open source, open access, decentralized, non-monopolistic version of artificial intelligence research and production.
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SPEAKER_00
So that s like the goal and that s what we ve been working on for a really long time.
1
SPEAKER_00
And it s a really difficult problem.
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And I ll tell you why.
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Because Bitcoin built a supercomputer, but it s validating hashes.
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SPEAKER_00
And hashes are really easy to validate because they re either true or false.
1
SPEAKER_00
But evaluating whether or not a gradient added to a machine learning model to improve the performance is good or not involves validating that gradient on the model against the validation.
1
SPEAKER_00
And that s a difficult and computationally expensive problem in the first place.
1
SPEAKER_00
And it s also not only is it computationally expensive, not just like a millisecond validation process, it s
1
SPEAKER_00
it s probabilistic and hyper-dimensional.
1
SPEAKER_00
We had to figure out an abstraction on the whole concept of building a digital commodity market in the first place.
1
SPEAKER_00
So what was Bitcoin in its core?
1
SPEAKER_00
Let s take that core, let s write a language to write digital commodity systems, and then let s apply it.
1
SPEAKER_00
And so we did that.
1
SPEAKER_00
And then, you know, just a couple weeks ago, we launched that language to people to build digital commodity systems to help us
1
SPEAKER_00
create this open source artificial intelligence with inside BitTensor.
1
SPEAKER_00
And that was what you mentioned before subnets, right?
1
SPEAKER_00
It was like, it s our smart contract platform effectively.
1
SPEAKER_00
It s becoming an L2 and saying, hey, now you can come in and program this computer to create massive scale computational digital commodities, right?
1
SPEAKER_00
So, and we know that we can do it.
1
SPEAKER_00
We haven t been, and I ll be honest, like I got a caveat when we say like not to get too ahead of ourselves because, you know, we have to be scientists here.
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SPEAKER_00
Um, we, we re not as good as the closed source AI, right?
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So we, we created subnet one and subnet one was intended to inference machine learning models and then get the results to an API.
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And then people could use the API like chat GPT.
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And was it powerful, really powerful.
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So we, we were able to get it.
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We were getting 44 million queries per day on that network.
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We were inferencing 44 million language models.
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And that was in terms of inference.
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capability, the same amount as say open AI, except we re running a much smaller model, but we re doing it with less money because our miners are really, really competitive and very, very good at lowering the costs on doing things because that s their bottom line.
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And that s what makes the people like floppy successful.
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So was it better than GPT?
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SPEAKER_00
No, it wasn t because, you know, there s an art to working with, with incentive mechanisms because they re adversarial, right?
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SPEAKER_00
That the miners don t do exactly what you sell them to do.
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They do what they want to do.
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And that s both a feature and a bug in these systems.
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It s out of their adversarial.
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SPEAKER_00
So, so we got it to work fairly well and it s kind of a continual process, but the, the, you know, the win was, was really showcasing how much resource we could collect.
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SPEAKER_00
Okay.
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We could collect it.
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We didn t quite align it, but we collected it and it validated that premise.
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And now we re, we re, we re doing is we, by expanding out BitTensor and allowing people to run multiple experiments, this is what we re really excited about is, is like to see what we can do by actually nesting the pursuit of the incentive mechanism underneath the market itself.
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and having just way more exploration.
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So what we re hitting right now is research teams.
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We re going to the open source contributors.
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We re going to these PhD students.
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We re saying, hey, come on, you can go do your research on our platform at scale.
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We re giving you access to our data center effectively.
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It would be like if a researcher from McGill could go and access Borg at Google.
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And if they could do something with that compute in an effective way, then Google would pay you.
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SPEAKER_00
As long as it comes into our network, right?
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SPEAKER_00
And so, you know, many people have asked me like, okay, well, is there even a market?
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SPEAKER_00
Is there even excess GPUs?
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SPEAKER_00
Everyone s just buying up all the GPUs, right?
1
SPEAKER_00
Like, what like spare GPU are you talking about?
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SPEAKER_00
Because they re all being monetized.
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SPEAKER_00
And it s like, it s not so much about whether or not they re being used.
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SPEAKER_00
They re all being used.
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It s whether or not they re being allocated properly.
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SPEAKER_00
Because even that that s the problem that these these corporations have is that they have this many spent a hundred billion dollars on GPUs and Then they got to get the researchers to come and use it
1
SPEAKER_00
Right.
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Like how are they going to like, because there s so much waste.
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SPEAKER_00
Right.
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And we have the ability to nest all these problems under market mechanisms and say, select, we re going to select you.
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If you can do good research, we re going to select you for building something that has value and the market is efficient.
1
SPEAKER_00
And that s, that s the beauty of digital currency systems, right?
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SPEAKER_00
Like the whole, the beauty of, of digital currency is that we have this additional liquidity and the ability to create markets where hitherto things were locked up.
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We let the energy flow.
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Right.
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So BitTensor is really just that computer.
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It s the computer that allows us to build digital commodity markets in the pursuit of artificial intelligence.
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And, you know, I ve been on it for years and I will be on it for years going forward.
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It s my love.
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SPEAKER_01
Very cool.
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SPEAKER_01
No, that s amazing.
1
SPEAKER_01
So many questions from that.
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SPEAKER_01
I guess maybe starting off.
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SPEAKER_01
So obviously what I found interesting initially was this hybrid proof of work and then also smart contract functionality.
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SPEAKER_01
Uh, you guys are built on top of substrate.
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SPEAKER_01
And so I guess like one of my questions is why did you feel that proof of work was necessary from inception to, to have that basis there as opposed to just building like another, like proof of stake L1 or L2?
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SPEAKER_00
Well, because it, it takes work to create intelligence.
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So that s what we re validating.
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SPEAKER_00
If it was proof of stake, we wouldn t be producing anything.
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The work was required.
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That s the thing we want.
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We want to incentivize the work.
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SPEAKER_01
You could have built on a number of different technologies, right?
1
SPEAKER_01
So I guess you could have done Tendermint, Cosmos.
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SPEAKER_01
I guess you guys chose Substrate for a few specific reasons.
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SPEAKER_01
Subnets probably being related to that in some capacity.
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SPEAKER_01
What was your thinking there and how did you stumble upon?
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SPEAKER_01
Because we re also pretty involved in the AlephZero ecosystem.
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They built on Substrate.
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SPEAKER_01
Yeah, yeah, exactly.
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SPEAKER_01
So I think it s pretty interesting seeing the quality of projects being built over there.
1
SPEAKER_01
And yeah, I m curious, like, how did you guys stumble upon that and think through polka dot substrate?
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SPEAKER_00
Well, we needed something that was performant and we needed something that was easy to write and that was going to be error free.
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SPEAKER_00
Rust is a great language for that.
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SPEAKER_00
It s very performant.
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Rust is becoming the language for machine learning along with Python.
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So we thought it made sense for us to do our chain in Rust.
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That was a technical reason.
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And then, you know, I built a prototype for BitTensor on EOS actually, because EOS was promising like free transactions or something like that.
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It was a stupid idea.
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because the amount of data that we generate, it would be impossible to build it on any L2.
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SPEAKER_00
We looked at Tendermint, we looked at Cosmos.
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SPEAKER_01
Solana, Avalanche maybe?
1
SPEAKER_00
Oh yeah, Avalanche, right.
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SPEAKER_00
Avalanche as well.
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SPEAKER_00
Avalanche was great because it was going to provide us more easy access to markets.
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But one thing that I ve learned is that it s actually good to have an organic growth of the market.
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SPEAKER_00
If you just go and you put it on a deck somewhere, like day one, right?
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SPEAKER_00
You get a price.
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SPEAKER_00
You re sort of like bringing the flame to the fire prematurely.
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SPEAKER_00
And if you, you know, we had this great behavior from our community where we just built and we didn t focus on marketing.
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We didn t focus on trying to go and get on exchanges.
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And we let the community do that and gave them
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something to do that was very productive.
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It also happened organically.
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SPEAKER_00
They made their markets for themselves and then they opened those markets up and that was great and we didn t need to touch that.
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SPEAKER_00
That organic growth was fantastic.
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SPEAKER_00
It s funny, if you sell too much, you are removing the proof of work.
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SPEAKER_00
You need the proof of work because the proof of work is the filter of the sell, which is the crypto state.
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SPEAKER_00
And if you just let everything in without a little bit of push, you get a bunch of people that don t give a f**k. Excuse my language.
1
SPEAKER_00
The proof of work is simultaneously there so that people produce value, but also so that they re forced to learn and not just come into the store, get the cheap thing, rounded corners.
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SPEAKER_00
It s easy to understand.
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SPEAKER_00
If you do that, you also lose a lot of the depth of what you re doing.
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SPEAKER_00
You sell yourself out.
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SPEAKER_01
When you say produce value, what do you mean by that?
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SPEAKER_00
Well, when people came and mined for us, for instance, that was the only way to get the token at the beginning.
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SPEAKER_00
We distributed our token to people that really cared, right?
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SPEAKER_00
And they were really cared.
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SPEAKER_00
They were really technical.
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SPEAKER_00
Either they were really technical or they really cared.
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SPEAKER_00
Because they were like, I need this and I m like a mailman and I have like an iPhone 4 and I ve never heard of a terminal before and you re asking me to download software and install it and then run a miner with a server and like port my router with a UPNPC so we get like NAT port.
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SPEAKER_00
Those people, bless their hearts, are like the bread and butter of your society, because they re the people that really care.
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SPEAKER_00
They take the time to know, and then they become, they really become the technology.
2
SPEAKER_00
Like the whole idea with crypto is that it s not controlled by you, right?
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SPEAKER_00
It s not about you.
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SPEAKER_00
It s about the people you give it to.
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SPEAKER_00
It s about the fact that it s being co-created.
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SPEAKER_00
If it s not being co-created, then you re defeating the whole purpose of creating something that has this decentralized meaning, that it s well-nested into a whole bunch of people.
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SPEAKER_00
So we got this amazing group of people that have defined what BitTensor is, and it s still open to that, right?
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SPEAKER_00
We still want to always be breaking down barriers for people to get a piece of this and to put their work in and learn and become part of our ecosystem and our culture, right?
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SPEAKER_00
Coming to the United States, good example.
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SPEAKER_00
Everyone was welcome in the United States, but you had to come across an ocean.
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SPEAKER_00
And that maiden journey for them is part of the ethos.
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SPEAKER_00
And that s proof of work from another side.
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SPEAKER_01
Awesome.
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SPEAKER_01
No, I love that.
2
SPEAKER_01
I think it s super cool seeing how that developed in the earlier days of BitTensor when people were just OTCing the token in the Discord.
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SPEAKER_01
And I think that s still happening quite a bit as well.
2
SPEAKER_01
I guess like beyond the time and resources investments from like the early community members to be able to mine the token, I think that s like incredibly important as well, as you mentioned, from a community building perspective.
2
SPEAKER_01
But I guess from
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SPEAKER_01
I guess the compute and the mining resources are there.
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SPEAKER_01
What broader role does that play in the network of BitTensor?
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SPEAKER_01
So you have all these people who are mining, setting up as miners and validators.
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SPEAKER_01
Aside from the early alpha and the proof of work sexiness of the whole ecosystem, which I really liked, I really was interested in the fact that
2
SPEAKER_01
Whereas like Bitcoin, you re kind of using your compute resources to just mine the token.
2
SPEAKER_01
But like that, I guess like that energy is not really used for something greater, right?
2
SPEAKER_01
Whereas like this, you re actually, you know, using those resources towards like AI and ML.
2
SPEAKER_01
So yeah, maybe you can kind of go into how you sort of came up with that and what that plays into the ecosystem.
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SPEAKER_00
I ll say though, before I get into the fact that we use proof of work for good, that Bitcoin s work is not actually wasted, right?
2
SPEAKER_00
Because it secures the network.
2
SPEAKER_00
Yeah.
2
SPEAKER_00
This is a glorious day, right?
2
SPEAKER_00
The market is up, everyone s happy because King Daddy Bitcoin is on the rise, right?
2
SPEAKER_00
And we all know that we re all floating on this ship.
2
SPEAKER_00
And to deny that is, I think, you know, sacrilege.
2
SPEAKER_01
Yeah, it is.
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SPEAKER_00
Anyways, but so we wanted to stitch together these resources.
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SPEAKER_00
And so like, I guess your question may be like, how does that work?
2
SPEAKER_00
Like, you said why, like the why is so that we can combine them
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SPEAKER_00
and apply them.
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SPEAKER_00
to create value for people and distribute the other side, the flip side of that valuation, the value back into a decentralized network of people.
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SPEAKER_00
So it s not just controlled by a single entity.
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SPEAKER_00
And then, you know, you can take a piece and other people can take a piece and you can contribute, you can own, you can use.
2
SPEAKER_00
It s unclosable.
2
SPEAKER_00
That s the nice thing about the way we built it.
2
SPEAKER_00
You know, it s not just open AI in name only.
2
SPEAKER_00
It s unclosable by design.
2
SPEAKER_00
So that s really cool.
2
SPEAKER_00
But anyways, what are they doing?
2
SPEAKER_00
And you know, there s a lot of different answers to that question, because the language we use to write these commodity systems is fairly abstract.
2
SPEAKER_00
So you could write all sorts of stuff.
2
SPEAKER_00
The contribution can be something akin to NumerAI, where someone s predicting the stock market of Bitcoin in whatever way, and maybe that s a competition challenge, or maybe that s information extraction or procurement challenge, or maybe that s a
2
SPEAKER_00
porting to other APIs and combining APIs problem, but whatever it is, it can be measured and then it can be mastered by the Myers or like in subnet five right now, which is getting a lot of attention with the image net.
2
SPEAKER_00
It can be just generating images on the fly based on queries.
2
SPEAKER_00
Right.
2
SPEAKER_00
And that s just an inference problem.
2
SPEAKER_00
So we can create an endpoint that s high performance, right?
2
SPEAKER_00
It s like it s 256 miners that are forced to be high performance inference service servers that can service all sorts of different applications across the internet and generate images.
2
SPEAKER_00
And we can reduce the price down incredibly low of all the while distributing the value out to the people that are really doing viscerally the work, right.
2
SPEAKER_00
Of inferencing the machine learning models.
2
SPEAKER_00
So that s another example.
2
SPEAKER_00
And so that s our proof of work.
2
SPEAKER_00
Proof of work is really different than you might imagine it is.
2
SPEAKER_01
Interesting.
2
SPEAKER_01
So how can somebody set up a subnet?
2
SPEAKER_00
They just need to do btclee subnet create.
2
SPEAKER_00
It s actually pretty cheap.
2
SPEAKER_00
It s like a, it s like a hundred tau, which is not really, and you get that back.
2
SPEAKER_00
So it s just a lock.
2
SPEAKER_00
And then you re able to create a subnet and there s a developer toolkit that allows you and explains to you how that s done.
2
SPEAKER_00
And you know, right now the foundation is going through a lot of work right now, producing documentation for the general community so that developers can really come in and build value using this.
2
SPEAKER_00
And so it s, it s pretty simple.
2
SPEAKER_00
Like it s like a 10 step process really.
2
SPEAKER_00
Where the difficulty comes in is mastering the language of incentive.
2
SPEAKER_00
Because incentive systems are, you re trying to wield like a fusion reaction with your hands.
2
SPEAKER_00
It s popping off and trying to explode at you in all these different ways.
2
SPEAKER_00
It s like a plasma ball of energy.
2
SPEAKER_00
I would describe incentive mechanism computation
2
SPEAKER_00
Like it s like the fusion, the fusion power of computation.
2
SPEAKER_00
It s like insane, right?
2
SPEAKER_00
Like we can only really do it if we re super geniuses and you need like AI.
2
SPEAKER_00
And, and that s the tricky part.
2
SPEAKER_00
Actually building a subnet great and creating the subnet.
2
SPEAKER_00
It s like 20 lines of code or something.
2
SPEAKER_00
It s less four commands on your Klee.
2
SPEAKER_00
And then you ve got a subnet.
2
SPEAKER_00
And the question is, can you wield it?
2
SPEAKER_01
And so what does that involve in terms of, so I guess like aligning incentives for the validators and miners to, to get involved and obviously creating like a, like a novel use case, privacy AI and ML could be quite an interesting use case for a potential subnet.
2
SPEAKER_00
Yeah.
2
SPEAKER_00
Like one of the things that we re doing is, you know, we, we built the base API, but.
2
SPEAKER_00
things always get abstracted.
2
SPEAKER_00
So we have these, what I m building right now is like a cookie cutter subnet that you can just launch on BitTensor and it trains a machine learning model for you.
2
SPEAKER_00
As the technology becomes more sophisticated, what we can do with these subnets is we can port them and fork them and
2
SPEAKER_00
and create versions of the same thing, but for different problems.
2
SPEAKER_00
And specifically, we re going to come up with the rubrics, the, like the language, you know, the best practices for doing this.
2
SPEAKER_00
So you might want to create a subnet because you re, you re, you re trying to extract it to a commodity, or you want to go to the subnet marketplace and be like, okay, I want to, I want to run this subnet.
2
SPEAKER_00
This is going to, how much it s going to cost for the lock costs, like a hundred thousand.
2
SPEAKER_00
I go run it on the network, the network.
2
SPEAKER_00
goes and runs it for you, injects emission through it.
2
SPEAKER_00
And we, you know, collectively make value as a community because of your innovation that you ve taken a bit of a cut.
2
SPEAKER_01
Interesting.
2
SPEAKER_01
Now, that s super cool.
2
SPEAKER_01
I m excited to see all the new use cases that pop up through these different subnets.
2
SPEAKER_01
And how many are there right now?
2
SPEAKER_00
Twelve.
2
SPEAKER_01
Twelve.
2
SPEAKER_01
Okay.
2
SPEAKER_01
And you said there s another...
2
SPEAKER_01
Maximum.
2
SPEAKER_01
Oh, there is.
2
SPEAKER_01
Okay.
2
SPEAKER_01
Why, why, why the cap out of curiosity?
2
SPEAKER_00
Well, I mean, it s really about managing chaos.
2
SPEAKER_00
When we get to 32, we kick the subnet that is the worst.
2
SPEAKER_00
That process creates this selection criteria for the subnets themselves.
2
SPEAKER_00
So we add competition into the subnets and the 32 cap is what we have right now.
2
SPEAKER_00
It was basically managing chaos, like to limit the expansion so that we can see what s happening, fix problems as they come along.
2
SPEAKER_00
And then we ll likely go up to 128.
2
SPEAKER_01
And so forth 1024 2048 4096 So the idea is to like over the long term continue to expand Expanding this into like that more highly curated subnets just to make sure it s not just like I guess like the system
3
SPEAKER_00
not being abused.
3
SPEAKER_01
It s been our style since the beginning.
3
SPEAKER_01
We re like an organic, ever-adapting, improving system.
3
SPEAKER_01
From where we were in 2021 and 2022, it s really, really incredible.
3
SPEAKER_01
We ve crafted these ideas and this language and improved it incrementally over time.
3
SPEAKER_01
And I think that s one of our advantages is that we have such a good community that s behind us that lets us do that, that is willing to help us grow and mature through the different states of a civilization.
3
SPEAKER_01
Civilizations start off really basic and then they become massive and uncontrollable and fully decentralized.
3
SPEAKER_01
And we re going through that process at the cadence we think that makes sense for the project.
3
SPEAKER_00
And how are you handling governance of this along the way?
3
SPEAKER_01
Well, we already have a liquid democracy of some sort.
3
SPEAKER_01
We know we do because as a foundation, we already have challengers.
3
SPEAKER_01
And that s a really good sign.
3
SPEAKER_01
Like people are doing things better than us and we can become relevant.
3
SPEAKER_01
So that s fantastic news.
3
SPEAKER_01
I think that it s always good in crypto systems where you could put more of the system underneath of the market.
3
SPEAKER_01
If there s something, put it underneath the table.
3
SPEAKER_01
Put it underneath the market.
3
SPEAKER_01
Put it underneath Liquid Democracy.
3
SPEAKER_01
Make it be selected by the market.
3
SPEAKER_01
Make people speculate on the idea.
3
SPEAKER_01
So we just follow through with everything.
3
SPEAKER_01
So the foundation is underneath the table.
3
SPEAKER_01
And we have competitors and things like that.
3
SPEAKER_01
So there s a Liquid Democracy that happens with delegation of stake right now, where people select the validators that are performing properly.
3
SPEAKER_01
And there s Liquid Democracy on the subnets where people are
3
SPEAKER_01
staking to the subnets they think are valuable and voting with their feet, so to speak, or voting with their tau.
3
SPEAKER_01
And that s become very sophisticated, right?
3
SPEAKER_01
And so as we grow and become more mature as a community, we sort of open up new ways for the system to become decentralized.
3
SPEAKER_01
And right now there s centralization at the chain level, right?
3
SPEAKER_01
So we run the validators.
3
SPEAKER_01
And there s also centralization in updating the code on the chain.
3
SPEAKER_01
So we only have that privilege.
3
SPEAKER_01
And this is sort of our next couple years of development.
3
SPEAKER_01
This is something that we re going to be doing.
3
SPEAKER_01
But we want, because that s like the final piece, once we check that off and say we re not going to be able to update this anymore, it really, really is gone.
3
SPEAKER_01
It s left the house, right?
3
SPEAKER_01
And we re getting very close.
3
SPEAKER_01
But right now, what we re focusing on step by step to decentralize different aspects.
3
SPEAKER_01
So obviously, we decentralize the mining first, and then we centralize the validating, and then we decentralize the ability to aggregate stake, and we made things more democratic, and then we decentralized the creation of subnets.
3
SPEAKER_01
And then, you know, we re going to add speculation on that level.
3
SPEAKER_01
And then we re going to add voting mechanisms onto the pseudo key and things like this.
3
SPEAKER_01
It s a little baby, right?
3
SPEAKER_01
He s like 14, right?
3
SPEAKER_01
He s going to leave, or she s going to leave the home at 17.
3
SPEAKER_00
Okay.
3
SPEAKER_00
So you re approaching it very systematically in different stages.
3
SPEAKER_00
Okay.
3
SPEAKER_00
Let s say hypothetically, I m a PhD researcher in AIML.
3
SPEAKER_00
I have like this proprietary, you know, model that is useful for electronic music production for like DJs and stuff like that.
3
SPEAKER_00
How do I get involved?
3
SPEAKER_01
Well, one way is you could train it on BitTensor, and you have an interesting idea for a new type of model, and you could build a subnet that trains it.
3
SPEAKER_01
Like a gargantuan job, right?
3
SPEAKER_01
So that s not quite launched yet.
3
SPEAKER_01
That s coming in the next couple weeks.
3
SPEAKER_01
Alternatively, you could train this model and then you could have the network inference it at scale.
3
SPEAKER_01
So you could build an application where
3
SPEAKER_01
Everyone is running your model and maybe even improving your model slowly against your reward landscape and inferencing it to use you So now you ve you ve outsourced the the computational problem of inferencing your machine learning model to this massive incentivized optum self-optimizing computer Yeah, and now you can build application.
3
SPEAKER_01
You can also make it accessible to people people can use it that s something that people are doing and
3
SPEAKER_01
You can solve different problems that are required for training that model.
3
SPEAKER_01
Maybe you want to source all of the data that they would use to train that model, right?
3
SPEAKER_01
And there s no set for it.
3
SPEAKER_01
So maybe you can build a reward landscape where the miners are going to go out and get you songs, right?
3
SPEAKER_01
They re going to scrape the internet for all of the music in existence and bring it into decentralized storage.
3
SPEAKER_01
And then you re going to train your machine anymore.
3
SPEAKER_01
There s so many creative ways that people have been using it, and that s really exciting for us is seeing how people are doing it.
3
SPEAKER_01
And if you have an idea like that, you can also come to BitTensor.
3
SPEAKER_01
If you just have something you want to contribute, we can also help you build it.
3
SPEAKER_01
Because it s a collective of people that we re all aligned.
3
SPEAKER_01
We all share a common sense of value and we can make money with each other in different ways.
3
SPEAKER_01
And we also want people to raise the ranks in this system.
3
SPEAKER_01
It s proof of work.
3
SPEAKER_01
Come and participate and become a member, become a board of directors.
3
SPEAKER_01
on BitTensor.
3
SPEAKER_01
So there s that aspect.
3
SPEAKER_01
You can also come and work for us because it s open source, right?
3
SPEAKER_01
So we get that too, right?
3
SPEAKER_01
It s like open source technology.
3
SPEAKER_01
So come and write code for BitTensor.
3
SPEAKER_01
It s a cool project that you might want to contribute to.
3
SPEAKER_01
Those are things that I think set us apart from
3
SPEAKER_01
A closed source company, for sure.
3
SPEAKER_01
But even an open source project, the ownership side is not something you can contribute to.
3
SPEAKER_01
And then there s also these resources that you can get access to.
3
SPEAKER_01
You can get access to these resources through the system.
3
SPEAKER_01
And if you have a good idea, that can be something that s pulled up out of the community itself to enable you to do your research.
3
SPEAKER_00
Funny that you brought it up.
3
SPEAKER_00
I want to actually talk about data sourcing, because I do think that s a pretty unique use case.
3
SPEAKER_00
Is that something that s being done or is currently in the, it is?
3
SPEAKER_00
Yeah.
3
SPEAKER_00
I mean, there s a subnet three.
3
SPEAKER_01
Subnet three is scraping the internet.
3
SPEAKER_00
Wow.
3
SPEAKER_01
His reward landscape rewards you for, for adding new tweets to the decentralized storage.
3
SPEAKER_01
So you, you send them into the decentralized storage.
3
SPEAKER_01
We check that they re unique and that they re, they re valid.
3
SPEAKER_01
Periodically so some of them we check to see if they re valid and if you can do that faster than everyone else You can do that cheaper than everyone else You re gonna you re gonna get the majority of that subnet and so what you get is people that they get really Freaking good at finding the cheapest way to get all the tweets So we so we scrape like a million tweets per day, right?
3
SPEAKER_01
And and then that s a commodity that s accessible to that subnet I mean, I think right now it s just open source.
3
SPEAKER_01
You can just go get it.
3
SPEAKER_01
That s really high quality data That s something only a centralized organization could pay to have
3
SPEAKER_01
If you re doing open source machine learning work and you want to get this massive data set, you don t have the funds to do it.
3
SPEAKER_01
Because there s no monetization for your open source AI company, but monetization is primary.
3
SPEAKER_01
That s just an example of something that can be created and is being created by people on top of BitTensor.
3
SPEAKER_01
It s very easy to understand how that digital commodity makes sense.
3
SPEAKER_01
People can imagine it, right?
3
SPEAKER_01
Like it s a concrete.
3
SPEAKER_01
commodity.
3
SPEAKER_01
Intelligence is more abstract.
3
SPEAKER_01
Nobody really understands what that is, but it can be measured also.
3
SPEAKER_01
And that s sort of the holy grail of BitTensor is creating a digital commodity, commoditizing intelligence.
3
SPEAKER_01
That s something that s live right now.
3
SPEAKER_01
And I think it s, you know, it s only about a week and a half old.
3
SPEAKER_01
Got an API where you can get access to the data that s being generated there.
3
SPEAKER_01
And someone else could do that.
3
SPEAKER_01
Someone could just copy and fork it.
3
SPEAKER_01
Who cares?
3
SPEAKER_00
Accessing this data, do people have to pay in Tau?
3
SPEAKER_00
the native token to access it, or how does it work?
3
SPEAKER_01
Right now, no.
3
SPEAKER_01
In the future, actually, so he s just doing this as an initial design where it s like, we re just creating, we re just running the computer to create value.
3
SPEAKER_01
The future goal for that is that he s going to actually save the data to decentralize storage on BitTensor itself.
3
SPEAKER_01
So BitTensor has a decentralized storage subnet as well that validators have access to.
3
SPEAKER_01
So the validators go and get the scrapers to create the data and then they store it on the decentralized storage, which is encrypted only for the validators.
3
SPEAKER_01
So the validators then are the ones who have access to it.
3
SPEAKER_01
So it s monetized by the validators.
3
SPEAKER_01
And they ll probably give it away for free anyways.
3
SPEAKER_01
Their interest right now is just adding value into the system.
3
SPEAKER_01
There s so much value to be created in AI that that s why AI companies give things away.
3
SPEAKER_01
Because it s like, just come and look at what we re doing.
3
SPEAKER_01
It s fantastic.
3
SPEAKER_01
But that s sort of like a utopian ideal.
3
SPEAKER_01
That s not it s not something that can last forever.
3
SPEAKER_01
It s like once you know, the rising tide isn t rising all ships and it s sinking and you re hitting the bottom of the ocean like the
4
SPEAKER_01
true incentive structure of the technology you build comes into play.
4
SPEAKER_01
So yes, BitTensor is monetized around TAO.
4
SPEAKER_01
If there s no monetization around TAO, then there s no reason for validators to do it.
4
SPEAKER_01
which means that you re going to need to pay them to get access to the thing.
4
SPEAKER_01
And that s, you know, when the rubber hits the road, so to speak, that s the way it works.
4
SPEAKER_01
Now that means there are entry points into the BitTensor because you have to be a validator in order to get all these resources or to run the subnets and et cetera, et cetera.
4
SPEAKER_01
You ve got to have Tau.
4
SPEAKER_01
And so this, it s not open, open, open, open, but what it is is decentralized and therefore not monopolistic.
4
SPEAKER_01
and competitive.
4
SPEAKER_01
The free market drives down the price and ensures that the resources that are being created are not simply being used in the interest of a small group of people, right?
4
SPEAKER_01
And that s what people are really afraid of with AI.
4
SPEAKER_01
They re afraid that there s going to be a hyper-monopolization.
4
SPEAKER_01
You know, antitrust laws are not going to work for something like open AI.
4
SPEAKER_01
The regulation is going to drive it to an extreme form of centralization of power.
4
SPEAKER_01
And you re not part of that.
4
SPEAKER_01
It s a big club and you re not part of it.
4
SPEAKER_01
And they re up in the sky in the amazing, futuristic, ringed halo and you re down on Elysium, Brazilified world.
4
SPEAKER_01
That s what we re trying to fight against here.
4
SPEAKER_01
It s important.
4
SPEAKER_01
to recognize that you can t just run everything off altruism.
4
SPEAKER_01
It was never, we never intended that.
4
SPEAKER_01
But right now we re just creating value.
4
SPEAKER_01
And so things are free, right?
4
SPEAKER_01
So you can use the network for free.
4
SPEAKER_01
Like we ve driven the price down on ImageNet.
4
SPEAKER_01
It s just like, you can just query right in.
4
SPEAKER_01
Like there s no problem.
4
SPEAKER_01
There s no limits.
4
SPEAKER_01
And that s really cool.
4
SPEAKER_01
In the future, the liquid democracy side will become so much more important.
4
SPEAKER_01
These validators have thousands of delegates.
4
SPEAKER_01
Those thousands of delegates are voting
4
SPEAKER_01
with their feet and forcing the system to be decentralized and democratic.
4
SPEAKER_01
So if you re a TAO holder, you re on the board of directors for BitTensor.
4
SPEAKER_01
You know, if you re just a GPT subscription holder, you re not on the board of directors for OpenAI.
4
SPEAKER_01
If you re a voter in the United States, potentially you re kind of on the board of directors if they regulate it.
4
SPEAKER_01
But from what we ve seen, the machine that is the global state of the United States doesn t do a very good job of representing people s votes when it comes to regulatory capture and governing organizations, especially large corporations.
4
SPEAKER_01
Here, your vote is visceral.
4
SPEAKER_01
It s liquid.
4
SPEAKER_01
It s direct.
4
SPEAKER_01
You can see how the mechanism works.
4
SPEAKER_01
It s fully transparent.
4
SPEAKER_01
I think these are, you know, values that we have.
4
SPEAKER_00
So right now, you said the foundation is managing most, if not all of the validators.
4
SPEAKER_00
Is that correct?
4
SPEAKER_01
No, no, no, no, no, no, no, no, not at all.
4
SPEAKER_01
Our validator is the largest, but we don t have the TAO.
4
SPEAKER_01
The TAO is delegated to us.
4
SPEAKER_01
We are at the mercy, so to speak, of the people that are donating TAO.
4
SPEAKER_01
We re the largest, but we re only about 20% larger than the second largest.
4
SPEAKER_01
and 30% larger than the third and 40% larger than the fourth and so on and so on.
4
SPEAKER_01
So there s a fair amount of decentralization at that level.
4
SPEAKER_01
There s multiple parties, you could say.
4
SPEAKER_01
There s political parties.
4
SPEAKER_01
They have a lot of power.
4
SPEAKER_01
There s deep conspiracies in BitTensor that the OpenTensor Foundation doesn t even have any power anymore at all.
4
SPEAKER_01
And the deep iceberg titanic
4
SPEAKER_01
is really run by the discord and the multiple discords upon discords upon discords where people that have been contributing value for a really long time have risen to the surface as being the right people that run the system you know what i mean like mog machine in the discord and for he runs taostats
4
SPEAKER_01
people love him, you know.
4
SPEAKER_01
And he got there not by having tons of tau, he got there by being an amazing contributor to the project.
4
SPEAKER_01
So contributing value.
4
SPEAKER_01
I like to see that meritocracy.
4
SPEAKER_00
Do you see any opportunity for somebody to build or contribute liquid staking infrastructure to help validate a validated deployment on subnets in the future?
4
SPEAKER_01
Do you mean like wrapping stakes TAO and is that kind of the idea?
4
SPEAKER_01
Like building like smart contract functionality and allowing people to do more fancy financial instruments?
4
SPEAKER_01
Yes.
4
SPEAKER_01
People have been talking about that for a really long time.
4
SPEAKER_01
It s not our highest priority.
4
SPEAKER_01
We have a lot of development work.
4
SPEAKER_01
I think it comes first.
4
SPEAKER_01
But yes, you know, as the calls for it increases, something that we will certainly implement.
4
SPEAKER_00
Which new subnets are you excited to release soon or hoping that people will build soon that aren t there yet?
4
SPEAKER_01
A fork of scale AI would be really great.
4
SPEAKER_01
We want to collect human responses to queries, not just AI responses.
4
SPEAKER_01
The ability to kind of have a human in the loop on one of the subnets would be something that I will build hopefully after I finish my current work.
4
SPEAKER_01
So that s an exciting one where it s like, you know, you don t just mine with a computer, but you can mine with yourself.
4
SPEAKER_01
And we can plug ourselves into the system and work for BitTensor in a different way.
4
SPEAKER_01
answering questions, doing RLHF, collecting datasets for RLHF, labeling datasets.
4
SPEAKER_01
Training and the variety of different mechanisms for training over a decentralized network, I think that that s a really, really interesting problem.
4
SPEAKER_01
There s so many different approaches to it, and I want to stimulate my own ideas, but also other people s for coming across how can we do that really fast.
4
SPEAKER_01
And that s like a gargantuan challenge.
4
SPEAKER_01
It s a really difficult one.
4
SPEAKER_01
It s very technical.
4
SPEAKER_01
Very, very technical.
4
SPEAKER_01
But cracking that egg is something that s, you know, personally, that I m personally working on.
4
SPEAKER_00
As a subnet concept?
4
SPEAKER_01
Yeah, well, monetizing... Is that right?
4
SPEAKER_01
Yeah, yeah, yeah.
4
SPEAKER_01
Well, monetizing the improvement of a machine learning model directly at the level of the weights would be the basis for a trading mechanism.
4
SPEAKER_01
There are a variety of ways of doing it.
4
SPEAKER_01
Now that you could have a network where the miners are rewarded for producing gradients on your machine learning model that improve it against a loss.
4
SPEAKER_01
So you could have these like long term Kaggle competition, like situations where people are out there, they take the model state, they try to come up with an adaption to that model that improves it against a very large data set.
4
SPEAKER_01
And we have like this collective Kaggle collaborative machine learning training process that happens.
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SPEAKER_01
And I think that that could really change the field by allowing researchers to come and train with the large scale models and open us up to be the producers of best in class systems in a completely unique way.
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SPEAKER_01
That s really exciting for me.
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SPEAKER_00
It s moving pretty quickly, but also in a very strategic and controlled manner, which is exciting to see.
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SPEAKER_00
And so is the main objective moving forward just to get more subnets deployed, more high quality subnets?
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SPEAKER_00
Are you looking for more technical people in the ecosystem to run miners and validators?
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SPEAKER_00
Or what s next on the horizon for the next six to 12 months?
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SPEAKER_00
And who are you looking for primarily to join the ecosystem?
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SPEAKER_01
We re on a push to 10x the number of developers.
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SPEAKER_01
And that s our main goal.
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SPEAKER_01
The focus from the foundation, building high quality content, tutorials, templates, showcasing how that can be done, incentivizing, injecting TAO into people that are contributing and adding things and writing code and doing fantastic work.
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SPEAKER_01
And I think this process is really about us.
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SPEAKER_01
de-centering ourselves from the development work and letting the project go.
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SPEAKER_01
So that s kind of our main push, that s my main push.
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SPEAKER_01
And that s what we ve seen happen.
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SPEAKER_01
It s really cool to see people come out of the woodwork and build a fantastic technology on top of a tensor already.
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SPEAKER_01
To have that go 100x in the next year, it would be fantastic.
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SPEAKER_00
And so, yeah, I guess like your more controlled approach, I guess it makes sense from, you know, trying to make sure that quality subnets are being deployed, but I guess from keeping it like, you know, as opposed to just opening it to whoever wants to build and like the market decide, I guess you would, you probably end up with like a lot more subnets, but maybe not as many quality ones.
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SPEAKER_01
It s an interesting question that we come across often.
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SPEAKER_01
When you re trying to create quality, do you select for diversity?
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SPEAKER_01
Do you allow for a lot of different things?
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SPEAKER_01
Or do you focus on having high quality?
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SPEAKER_01
And it turns out that that s kind of an infinitely difficult problem to solve.
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SPEAKER_01
It harkens to the exploration-exploitation problem in machine learning.
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SPEAKER_01
Do you do new things, or do you do the things you know how to do?
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SPEAKER_01
That s DAO, right?
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SPEAKER_01
That s the play between order and chaos, that the only way to manage it
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SPEAKER_01
is to continue to abstract the process, the selection of the process underneath markets and then iterate quickly, right?
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SPEAKER_01
That s why we ve been organic and moving this problem higher and higher up the stack.
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SPEAKER_01
I ll come back to the beginning.
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SPEAKER_01
Do we have 15,000 miners?
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SPEAKER_01
Or do we have 10,000 miners?
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SPEAKER_01
Or do we have 1,000 miners?
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SPEAKER_01
Or do we have 50 miners?
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SPEAKER_01
And do we give the best miner all of the reward and the others none?
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SPEAKER_01
Well, that s not great because that means that all of them don t get incentive and then there s no landscape, there s no gradient for them to improve.
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SPEAKER_01
So you need to have a little bit of a communist mindset, right?
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SPEAKER_01
Where you re like, no, no, we re going to have a social welfare system.
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SPEAKER_01
But if you re too social welfare, then what happens is that people don t, they don t care about being good anymore.
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SPEAKER_01
They just care about being big.
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SPEAKER_01
They just care about taking more slots.
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SPEAKER_01
There s always this interplay between those two dynamics.
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SPEAKER_01
And you could say it s like the interplay that society is continuously trying to navigate, right?
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SPEAKER_01
Should we have limits on wealth generation?
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SPEAKER_01
Should we have a social democracy, one where we have welfare state?
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SPEAKER_01
Should we have no welfare state or should we have total welfare state and somewhere in between?
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SPEAKER_01
And we need a way of,
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SPEAKER_01
Bridging this this this problem and we need a mechanism for finding the solution.
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SPEAKER_01
It s really about the mechanism So when that kind of question is asked to me, I always you know, like to ponder that it s like so what?
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SPEAKER_01
Given that this is an infinitely difficult problem.
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SPEAKER_01
I can t tell you for sure whether or not
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SPEAKER_01
One is better than the other, because it s not true.
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SPEAKER_01
They re both important, but we have to find that middle point, the DAO, the boundary between order and chaos, or whatever you would call it.
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SPEAKER_01
And that s why we re really into these ideas.
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SPEAKER_01
The way to do that is to use a market, is to allow the system to die when it s not doing it right, and allow the system to learn when things are going right.
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SPEAKER_01
And that is all about feedback.
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SPEAKER_01
And that s what we do at a lower level in machine learning.
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SPEAKER_01
It s all just feedback.
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SPEAKER_01
It s like, is this good?
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SPEAKER_01
Make it then good.
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SPEAKER_01
And if it s bad, then it s bad.
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SPEAKER_01
And then we do that a trillion times.
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SPEAKER_01
And then eventually we learn stuff.
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SPEAKER_01
And that s like the interconnection between BitTensor and nature, because that s the power.
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SPEAKER_01
That s what nature does.
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SPEAKER_01
It s just trial and error, right?
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SPEAKER_01
So the more, you know, the subnets launched for us was a huge thing because it was the first time that we took that question that I just described to you with, you know, do we have many or less, or do we have,
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SPEAKER_01
Is it going to be, you know, hypercapitalist or hyper socialist?
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SPEAKER_01
We made that question answerable by a variety of people and then nested the solution underneath the market.
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SPEAKER_01
So we were selecting for the thing itself and that sort of fractal we could talk about forever.
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SPEAKER_01
But that s, you know, a core philosophy of what we re building.
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SPEAKER_00
Yeah, that s fascinating.
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SPEAKER_00
It s one of the reasons why I love crypto and blockchain so much is you re literally constructing these digital societies using decentralized infrastructure and token incentives from scratch.
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SPEAKER_00
And it s funny, like, yeah, whenever I talk to friends and family here and they re like, Oh, yeah, you re still doing that Bitcoin stuff, right?
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SPEAKER_00
I m like,
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SPEAKER_00
It s so hard to like articulate how deep this stuff goes in terms of the formulation of new ecosystems and societies and like all the thought that goes into like governance and ecosystem growth and aligning incentives.
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SPEAKER_00
So it s really cool to hear you talk about that part.
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SPEAKER_01
The crypto ecosystem, I know we ve got to finish up, but I ll just say, maybe I ll end up on this point.
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SPEAKER_01
It s like crypto, the thing that fascinated me about it from the beginning is that we re not left or right wing, in my opinion.
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SPEAKER_01
Even though some people say that, like, obviously, like, libertarian, I guess you might say.
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SPEAKER_01
Right.
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SPEAKER_01
But actually, crypto is just a more precise and more expressive, more complete language for describing these political problems.
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SPEAKER_01
of human organization.
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SPEAKER_01
And it doesn t say that this is the, we re going to be left-wing or right-wing.
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SPEAKER_01
It s like, no, no, no, we just, if we can just be more efficient and more explicit and more comprehensive in the way that we talk about what it means to create a healthy political system, then we re going to naturally come up with a better one.
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SPEAKER_01
And that s what the Spencer is doing too.
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SPEAKER_01
We re like, okay, hey, let s nest
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SPEAKER_01
the pursuit of artificial intelligence underneath a mechanism that is more abstract in its ability to represent the problem and allows for there to be more exploration on behalf of the way the problem is solved so that we can find a better solution.
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SPEAKER_01
We re going to use this hyper-comprehensive language to write these hyper-powerful mechanisms.
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SPEAKER_01
For me, that s the blend.
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SPEAKER_01
That s what s always constantly interesting about this technology is what
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SPEAKER_01
you know, makes me sort of utopian and happy to be in this field.
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SPEAKER_01
And yes, like you, you re still in Bitcoin?
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SPEAKER_01
Yeah, I m still in Bitcoin.
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SPEAKER_01
I m still in crypto.
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SPEAKER_01
I ll never leave.
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SPEAKER_01
This is the future.
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SPEAKER_00
Yeah.
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SPEAKER_00
Agreed.
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SPEAKER_00
No, I love that.
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SPEAKER_00
I think that s a great point to end off.
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SPEAKER_00
I think that kind of summarizes everything that you re building and why we re involved in the space.
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SPEAKER_00
And yeah, it s been amazing to see the project tape form.
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SPEAKER_00
And yeah, Konst, thanks so much for coming on.
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SPEAKER_00
Appreciate it.
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SPEAKER_00
It s been an honor to be involved in the community and looking forward to
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SPEAKER_00
Yeah, doubling down in the coming months and years.
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SPEAKER_00
Thanks, man.