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You've had a dynamic where money has become freer than free.

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We talk about a Fed just gone nuts.

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All the central banks going nuts.

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So it's all acting like safe haven.

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I believe that in a world where central bankers are tripping over themselves to devalue their currency, Bitcoin wins.

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In the world of fiat currencies, Bitcoin is the victor.

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I mean, that's part of the bull case for Bitcoin.

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If you're not paying attention, you probably should be.

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DC, it's easy to get to from Philadelphia.

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I think I want to be here a lot more.

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We need you here, Marty.

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Do you?

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We need you here in the trenches.

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Yeah, we've got PubKey now.

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We've got the office set up.

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We need more Marty Bent.

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We need rips all the time in DC.

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I prefer them in person, as you know.

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Yeah.

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We've only ever recorded in person.

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Yes.

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This is the third time now.

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As is tradition.

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We didn't wait, what was it, seven, eight years between the second and third, like we did with the first and second.

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Right.

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We're going to keep these recurring basis.

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A lot's going to be happening in D.C.

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D.C. is going to be, you know, the new up and coming important city, I think.

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Yeah.

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Everyone likes to talk about Austin and Miami.

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But this is where a lot of stuff is going to happen over the next five, ten years with all the technology changes.

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Like D.C. is going to be the true city to be in, I think, in the coming years.

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That's why I told you this last time I was here, I've been to the city more times in the last six months than I was in the first 34 years of my life.

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Yeah. I mean, I'm not saying it's a great thing. I would prefer it not be the place that the magic is happening.

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And then but just with the way things are headed. Yeah, I do unfortunately think it's important that we're here.

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Yes. A couple of things on the agenda today. We're going to talk about AI, not only the policy implications around AI,

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but actually implementing it in our businesses, particularly at BPI.

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And what you guys have been up to.

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I think it's very fitting that we're meeting today because you guys launched the Q2 report of what BPI has been up to this year.

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So I think starting there and going through all the policy efforts that you guys have been pushing forward and the wins and maybe losses or neutral victories you guys may have.

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Yeah, gosh, so much stuff going on.

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But I think at the corner of it, it's just this technology continues to improve, whether it be both with Bitcoin and AI.

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And that is just speeding up the pace of change.

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We're seeing it in our organization.

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We're seeing it in what we're being tasked with in different meetings and stuff.

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And so it's really it's been a lot.

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So yesterday we released what we did over just the past three months.

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and it's crazy. I was reading through it and I just couldn't believe how much we got accomplished

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in three months. And, um, you know, people say like AI is going to like replace all our jobs

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and stuff. And like everyone I know is working harder than they ever have before, because suddenly

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all of these sort of stray ideas that you were like, Oh, I don't have the people or time to do

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that. You can actually just roll up your sleeves and do it with like an afternoon. Um, and so,

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yeah, it has been sort of overwhelming. We've been doing a lot of new international work. We've been

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doing lots of new research that we were able to build out much deeper than we had been previously.

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So yeah, it's been a whirlwind really since I joined. I mean, we last spoke when I first joined

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BPI and just the change in the organization since then has been crazy, crazy. And we're really

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excited for what it means for the next five years of what we'd be able to build here in DC.

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Yeah. Well, let's start internationally. Yeah. Taiwan. How did that happen?

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So Taiwan, this is a perfect example. We had an idea for a research paper. One of our fellow,

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we said, hey, Jake, you have a background in DOD. Would you be interested in doing a paper on

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Taiwan's cash reserve? Why diversifying into Bitcoin would make sense for them?

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And he was excited for it. Taiwan has a really interesting history. I didn't know this,

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but Taiwan exists entirely because they use their gold as a strategic resource to like flee the country, basically.

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So the only reason Taiwan exists is because they airlifted all their gold outside of mainland China and were able to fund a government exile.

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And so we thought, oh, that'd be interesting. We have the research expertise.

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We'll just do a paper sort of thought experiment.

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And then we get an email like two weeks after we released it with photos from Taiwan's legislature.

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And they're like, your paper was amazing.

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It is from a member of Congress, Legislator Ka.

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He emails us photos of him delivering our paper to the premier of the legislative Yuan, the head of the central bank.

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And we were just like, oh, my gosh, this is crazy.

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and then a few weeks after that we got invited to go and brief them for a week so

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um another thing has been keeping us busy is lots of international travel so what can you share about

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what was shared in the briefing or the information that was exchanged i can say that taiwan every

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person we talk to is really really cognizant of this the geopolitical situation they're in

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it feels like the weight of the world is on them and they're bringing it up all the time of they know that

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they've always been in this tenuous position between the United States and China

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and that every day they feel like the stakes are higher because the strategic importance of Taiwan

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goes up every day as the compute build out accelerates and there's more and more value on

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the island and it just leaves them in this like strange psychological position where everyone is

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thinking about it constantly like what does this mean for us what does it mean for the people of

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Taiwan for a long time we had this principle of the silicon shield that America would defend

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Taiwan's national interest it would defend them in a military escalation because of how valuable

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their chips are in many ways that's an even stronger case today than it was 20 years ago

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But at the same time, it can also be seen as a reason that China is even more likely to intervene because they're now not just have this historical rift, but they have a strategic element here of, you know, China is trying to figure out what it means.

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Could they actually pull off a blockade? All that. And everyone in Taiwan knows that people on both sides are trying to figure out what their plan is.

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And that just came through across every conversation we had.

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We met with people from both the different parties there.

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The DPP and the KMT are the two ruling political parties there.

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The DPP currently has the majority and the KMT as an opposition party is leaning more towards some form of reconciliation or, you know, some sort of lessening of sort of hostilities with China.

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And it's it's just really, really interesting political dynamic.

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If you look at all the other policy issues for the parties, they pretty much agree on, I don't know, 90 percent of policy issues.

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That's what I was going to ask.

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Like, how is the partisan polarity over there?

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It's it's it's very, very strong, but it's just on this issue of reconciliation.

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What side do we end up?

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What side do we lean towards?

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And I think that both of them are just coming to grips with it.

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It's like what everything else we do.

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It's so hard to predict the future right now

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because of AI, the strategic questions wrapped up in that.

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And Taiwan feels it probably stronger

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than anywhere else on earth.

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I mean, it's just in the daily conversation all the time.

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So what I can share is we met at length

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with their head regulator

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for their financial services commission

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and the Central Bank of Taiwan.

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And it was my first time meeting people from a foreign central bank.

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Super interesting.

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I went over there not really knowing what to expect.

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So, you know, you write a paper on Bitcoin.

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I've met many central bankers, you know, over the years working in policy.

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And I think everyone has always been extremely skeptical of Bitcoin, you know, arm's length.

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Oh, yeah, nice to meet you.

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Pleasantries.

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This was the first time I walked into a briefing. They had read our report cover to cover. All the different members of the Taiwanese Central Bank had taken extensive notes and had really, really good questions, actually, about the reasoning, the practicalities.

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without going into too much detail.

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I was surprised at their hospitality,

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their level of understanding,

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the quality of their questions.

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It was just a fantastic experience.

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We want to go back.

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And yeah, so hopefully more updates on that soon.

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But yeah, I think that this is something

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that is easy to forget about is what a signal

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that the American administration has sent to the world.

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You know, no one is ever excited with the pace of change in D.C.

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or how, you know, fast or slow things go.

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But things like the executive order for the SBR,

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like that is still being digested actively.

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And everyone around the world is trying to figure out what it means,

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you know, what to do with that.

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So it was a really, really cool experience.

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And it was my first time being there.

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So it was just all around just fantastic.

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Yeah.

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SBR, they're fighting over who actually gets control over the reserve right now, right?

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It's between commerce and treasury.

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I mean, it was something that we kind of scratched our heads at a little bit when the EO first came out,

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which was they've jointly delegated authority between treasury and commerce to execute the SBR executive order.

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And I think they're just still trying to figure out exactly how do they do this?

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How do they build up the capacity?

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I mean, it's been sort of embarrassing

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for the administration a bit.

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You know, they had that scandal

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where they gave custody of the Marshalls funds

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to, you know, a contractor with shady origins

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whose son then ran off with some of the money.

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I mean, it's just like a-

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Comical.

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It really is just like a circus.

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So in true government fashion,

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it's always slower than you would expect.

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but i do i mean what we've heard is um you know there are lots of things happening um

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that people are trying to get things stood up and there's just like an endless series of

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bureaucratic hurdles um but they say expect something soon so two weeks tm we know that

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well here yeah two weeks two weeks two weeks to flatten the curve two weeks to execute the sbr yo

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I don't know. Bring it back internationally. UK. UK. Yeah. Another thing we went over there.

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And I guess what we're seeing is what happened in D.C. and with the new administration has just

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want all of these other governments are wanting to get the inside scoop from the people that work

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through the process of what how is the U.S. thinking about this and how can they be a fast

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follow. That was the, we went over to the UK and heard that term like a hundred times. The UK wants

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to be a fast follow. And, um, it was honestly pretty surprising. So I went over there just sort

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of expecting that they would like throw me in jail if I was looking at Twitter and instead,

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like surprisingly positive. Um, you know, they had just announced a cap on stable coin balances.

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and then the week we went over there,

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they actually rescinded that.

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And they're still, like many other governments,

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trying to wrap their head around what all of this means.

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But again, surprised by the level of openness,

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we met with people and we did a briefing

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in the House of Lords.

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It's a ton of fun, first time being in there.

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It was in the Parliament building,

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so it felt like A lot of pageantry involved Lots of pageantry They have statues in there from like 1600s I tried to take a photo I got accosted by some security guard

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looked like the Hogwarts like cafeteria,

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but yeah, surprisingly optimistic there too.

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You know, afterwards the head of their,

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is like a head of innovation at their FCA,

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put out a thing about the importance of Bitcoin policy.

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I mean, we have to remember, like these people, they don't even understand the difference between Bitcoin and shitcoin.

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They don't understand how Bitcoin is different from the parade of horribles they hear about.

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And they are very interested in the story we have to tell.

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So I think the lessons learned is you have to tell the story in a way that relates to their history.

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You know, when we go over there, we talk about, hey, you know, Newton set you guys up on the gold standard and that paved the way for 200 years of British Empire.

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So those are the types of stakes that are at play here.

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And I think explaining in those broader historical terms, same with Taiwan.

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You know, we talked a lot about their historical use of gold as funding government and exile.

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So relating to those longer term historical narratives

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for a country, same here in America,

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is the key to getting people to understand

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the policy implications.

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Yeah, it's incredible work.

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It's exhausting.

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Thank you.

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I mean, we got a lot more to do.

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There's no shortage of work.

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Well, I mean, you guys are the hot chick on the block,

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not because of Bitcoin, because of AI.

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I mean, bringing this back to Taiwan.

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Yeah.

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You guys, I think Sam spearheaded the report,

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basically unearthing that China has been influencing

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conversations around AI data centers

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here in the United States.

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Yeah, that started as, like we were saying with AI,

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you can just do so much more.

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So it started as sort of like, I don't know, a side bit.

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People had mentioned to us, Bitcoin miners mentioned to us,

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they've been seeing just unprecedented local opposition

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and that they've been doing this for years.

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And they're used to some local concerns,

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obviously with any major infrastructure project,

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people are gonna have questions.

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But a few months ago they said,

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you know, we're seeing the same local people

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that have concerns, typical stuff.

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But we're also seeing this new thing,

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which is people from out of town that,

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while the local people will ask a reasonable question like,

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okay, where is this gonna be located?

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Is this gonna create noise?

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Is this gonna impact me in XYZ way?

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There would be these people from out of town

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that would really aggressively say,

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this is gonna give everyone an aneurysm, right?

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Or this is going to destroy all the bees in the area.

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I heard that no bees could ever exist

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within 50 miles of a data center, is that true?

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Just like ludicrous things.

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And they were like, we've never seen this before.

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Can you guys see if there's anything going on?

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He said, yeah, we'll take a look at it.

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And we just got Sam Lyman that joined.

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So he came over from Treasury

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and Sam has experience dealing with this stuff.

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So he used to work-

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He was at Riot, right?

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He used to work at Riot.

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He's done the rounds in local communities in Texas,

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working on this stuff.

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And he just kind of started pulling the thread.

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And you start going through these different layers

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of nonprofits and all the different activist groups

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that are on the ground and mobilizing.

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And it just kind of shocked all of us.

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And then it just all sort of worked out

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in the virality of it,

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because everyone's talking about data centers now,

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and we were really the first to sort of

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put all the pieces together and say,

253
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well, actually, if you look at all these different projects,

254
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we're seeing a common element,

255
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which is the party for socialism and liberation

256
00:17:07,448 --> 00:17:11,628
are functioning as at least important organizers

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in a lot of these debates.

258
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And they have sort of a dubious history.

259
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So yeah, it's been a whirlwind past couple of months

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as that story broke.

261
00:17:21,888 --> 00:17:23,748
And who's the individual behind all of it?

262
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Who's very vocally anti?

263
00:17:25,708 --> 00:17:27,408
We don't know who is like,

264
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there's a lot of questions about the organization.

265
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What we know is that someone named Neville Roy Singham

266
00:17:38,548 --> 00:17:43,548
is a very wealthy philanthropist that lives

267
00:17:44,168 --> 00:17:47,588
at least part of the time in Shanghai,

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has said a lot of positive things

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that sort of align his views with those of China.

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And he is at least funding some nonprofits

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that are doing anti-data center stuff.

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It is, there's a lot of dark money involved.

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A lot of it is sort of unclear

274
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and we're trying to piece it all together

275
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and understand exactly what's happening.

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But yeah, I'd encourage anyone that's interested in this,

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read our reports.

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We have two different foreign influence reports

279
00:18:21,948 --> 00:18:25,368
and the case for American AI that sort of go over

280
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exactly what this nonprofit structure looks like,

281
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sort of all the different elements of foreign influence

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we've identified.

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And we've sort of detailed case studies

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of what we're seeing on the ground.

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And the one thing I do wanna say is,

286
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this is not to say in any way, shape or form

287
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that Americans themselves don't have legitimate concerns

288
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about this massive multi multi-billion dollar,

289
00:18:51,068 --> 00:18:52,728
trillion dollar build out of compute.

290
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Multi-trillion at this point.

291
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Yeah, I mean, it's like huge in its implications.

292
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These projects are larger than anything

293
00:18:59,948 --> 00:19:02,548
we've ever built before and are going to continue

294
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to just scale up over time.

295
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People have many legitimate questions about that.

296
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How is that gonna change their way of life?

297
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I don't think that the narratives that Anthropik

298
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or some of these effective altruist groups are putting out

299
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are compelling to the everyday American.

300
00:19:20,848 --> 00:19:22,948
And that is manifesting in a lot of concerns

301
00:19:22,948 --> 00:19:24,588
about this build out.

302
00:19:24,588 --> 00:19:31,708
So all of that, I think there are legitimate concerns and fears about AI and these data centers, their impact.

303
00:19:32,428 --> 00:19:38,508
But a proper accounting of this means you need to also think, OK, is there a foreign influence?

304
00:19:39,488 --> 00:19:42,588
What does that look like? Because there are strategic questions at play.

305
00:19:43,328 --> 00:19:49,108
And we know that our adversaries are savvy. They understand how social media works.

306
00:19:49,108 --> 00:19:58,228
They understand that in modern global great power competition, you're usually not fighting with boots on the ground.

307
00:19:58,588 --> 00:19:59,828
Fifth generation warfare.

308
00:20:00,108 --> 00:20:00,348
Yeah.

309
00:20:00,428 --> 00:20:02,608
The podcast I recorded this morning, we talked all about it.

310
00:20:02,788 --> 00:20:03,148
Yeah, yeah.

311
00:20:03,208 --> 00:20:06,868
I mean, it's just, it is the modern battlefield is on Twitter and Instagram.

312
00:20:07,488 --> 00:20:12,548
And they are, I think that we're just seeing like the latest in.

313
00:20:12,888 --> 00:20:16,568
Well, that's why we should all be thankful that BPI exists.

314
00:20:16,568 --> 00:20:20,688
We try to do our part at TFTC, but you have to engage in fifth generation warfare.

315
00:20:20,808 --> 00:20:25,088
And that means going, pulling on the threads, writing the reports, getting it out there.

316
00:20:25,168 --> 00:20:27,848
And I mean, was that the most viral thing you guys have ever done?

317
00:20:27,928 --> 00:20:29,028
Funnily not related to Bitcoin.

318
00:20:30,088 --> 00:20:31,328
Yeah, it was probably the most viral.

319
00:20:31,528 --> 00:20:33,388
I mean, we're on the front page of New York Times last week.

320
00:20:34,008 --> 00:20:37,748
So, but, you know, just the beginning, just the beginning.

321
00:20:37,928 --> 00:20:40,328
I think there might have been, I don't know.

322
00:20:40,388 --> 00:20:42,068
I mean, the numbers on it have just been insane.

323
00:20:42,308 --> 00:20:45,648
You know, it's one of those things that you hit at the right time and get circulated by the right people.

324
00:20:45,648 --> 00:20:50,828
mark andreason tells all his followers to read it and then the internet explodes you know yeah i mean

325
00:20:50,828 --> 00:20:55,608
that's why we're that's why i'm in town today is for the event tonight which is talking about energy

326
00:20:55,608 --> 00:21:01,828
policy data centers uh the intersection and how we should think about these things approach them

327
00:21:01,828 --> 00:21:07,408
and i had a conversation last night if you listen to the previous episode you're getting this again

328
00:21:07,408 --> 00:21:11,688
but i think it's important to reiterate to connor i i was sitting down with somebody who was

329
00:21:11,688 --> 00:21:16,668
involved in one of the largest utility companies in the United States.

330
00:21:16,668 --> 00:21:19,448
And we were just talking shop about like, all right, how do you,

331
00:21:19,528 --> 00:21:20,908
how do you educate the masses about this?

332
00:21:20,908 --> 00:21:23,588
Cause that's, I think one of the biggest uphill battles we have,

333
00:21:23,728 --> 00:21:29,148
and Bitcoiners I think know this more deeply than the AI data center people

334
00:21:29,148 --> 00:21:30,828
now, because we've been doing this for 10 years,

335
00:21:30,828 --> 00:21:35,628
but there is a lack of understanding of energy, the grid,

336
00:21:35,808 --> 00:21:40,348
how all of these things work, how data centers, Bitcoin mining operations,

337
00:21:40,348 --> 00:21:45,708
how they interact and how they affect your ability to access cheap electricity.

338
00:21:46,148 --> 00:21:51,668
And that's why I'm happy that American Bitcoin, PubKey and PubKey are starting this series,

339
00:21:51,888 --> 00:21:53,548
which would go for the next 10 months.

340
00:21:53,828 --> 00:21:55,908
But having conversations around these things.

341
00:21:56,488 --> 00:22:02,208
And I think to your point about social media, it's like packaging it and getting it out there in a way,

342
00:22:02,268 --> 00:22:03,688
which I think your report did very well.

343
00:22:04,048 --> 00:22:04,208
Yeah.

344
00:22:04,608 --> 00:22:06,388
I mean, it's so important to tell the story.

345
00:22:06,388 --> 00:22:16,728
And I do think it is critical to Bitcoin as well is people if we are going down a path where people are hostile to just energy production generally.

346
00:22:17,928 --> 00:22:20,568
That is not good for anyone.

347
00:22:21,208 --> 00:22:22,808
But but really.

348
00:22:24,188 --> 00:22:29,048
It's not surprising what we're seeing either, because what we're seeing is.

349
00:22:29,048 --> 00:22:37,828
a big tech executive gets up and says, well, AI is probably going to be as dangerous as pandemics

350
00:22:37,828 --> 00:22:43,708
and nuclear weapons combined. And it in the process is also going to take your job and the

351
00:22:43,708 --> 00:22:51,708
jobs of everyone, you know, and yeah, we're going to keep building it. Okay. How is this going to be

352
00:22:51,708 --> 00:22:57,748
compelled? Like this is not compelling for anyone. And I think it's just such a break from the

353
00:22:57,748 --> 00:23:04,028
American tradition of leaning into innovation and entrepreneurship and the optimism of building

354
00:23:04,028 --> 00:23:09,928
great things. That is what has made people inspired and want to come to America and want to build here.

355
00:23:10,268 --> 00:23:17,368
And what causes people to get up every day and build great companies is human achievement and

356
00:23:17,368 --> 00:23:23,108
greatness and energy is at the bottom of all of that. And, you know, I'm really excited. There's

357
00:23:23,108 --> 00:23:27,648
a lot of really, really great startups now that are getting into, I'm really glad to see there

358
00:23:27,648 --> 00:23:36,168
are startups that are doing real hard tech, um, energy production, breakthroughs and stuff like

359
00:23:36,168 --> 00:23:41,408
Valor Atomics or whatever. Um, you know, I saw that on Twitter, it's been all over my feed. Um,

360
00:23:41,948 --> 00:23:49,048
but if we're not telling a compelling story about how technology benefits us with either Bitcoin

361
00:23:49,048 --> 00:23:56,968
or open source AI or, you know, biotechnology, if we're not telling that compelling story,

362
00:23:56,968 --> 00:24:03,048
then it's going to manifest in hostility in a million different ways, all the way from the

363
00:24:03,048 --> 00:24:10,308
hyper local level of not letting any of this stuff get built all the way to federal licensing

364
00:24:10,308 --> 00:24:16,348
regimes, KYC for compute and surveillance of all your chat logs. It gets like very,

365
00:24:16,348 --> 00:24:23,208
very dystopian very quickly when you start convincing everyone that this is this crazy

366
00:24:23,208 --> 00:24:27,048
danger that we have no precedent for how to handle. It's just not true. It's not how

367
00:24:27,048 --> 00:24:34,168
our society was built. We're a society that trusts people with dangerous things. We let people have

368
00:24:34,168 --> 00:24:41,028
guns. I mean, in theory, America itself was founded on the idea that the people themselves

369
00:24:41,028 --> 00:24:46,088
can be trusted with dangerous tools, with self-government. I mean, this is like the core

370
00:24:46,088 --> 00:24:52,228
what we believe is that the people can be trusted with things. And if they break that trust, they

371
00:24:52,228 --> 00:24:59,288
will be prosecuted accordingly. Yeah, exactly. Exactly. It's it's it's we've dealt with dangerous

372
00:24:59,288 --> 00:25:04,448
things in the past. So freaks, this episode is brought to you by blocks Bitcoin ecosystem. You

373
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probably know cash app, you probably know square, you definitely know, Becky, if you've been listening

374
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custody without turning self-custody into a weekend engineering product. Square helps merchants run

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kind of ecosystem Bitcoin needs. We've been talking about this on the show for a while.

380
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We know that we need the different parts to line up to make Bitcoin everyday money,

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Block is doing just that.

382
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Check the episode description for the current Cash App, BitKey, and Square Links.

383
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All right, freaks, you know me.

384
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396
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397
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400
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401
00:26:56,196 --> 00:27:01,776
slash Bitcoin. Check it out. I think I'm back to the AI narrative. And it's one thing we've been

402
00:27:01,776 --> 00:27:07,736
working on at TFTC too, because we've been leaning in and maybe we can spitball some ideas, compare

403
00:27:07,736 --> 00:27:11,936
notes to how we've been implementing this stuff. But I think I've been trying to do this more and

404
00:27:11,936 --> 00:27:20,816
it's not an attempt to brag, but I think people, the broader public has an outside looking in view

405
00:27:20,816 --> 00:27:26,556
of AI and most of them haven't like really dove deeper than downloading chat gpt and

406
00:27:26,556 --> 00:27:34,956
interacting with the chat bot and I was actually relieved to see secretary percent do an interview

407
00:27:34,956 --> 00:27:38,336
this morning we were clipping it at tftc but talking about this exact problem where the

408
00:27:38,336 --> 00:27:43,636
interview was asking him dario modi is telling us it's going to take all of our jobs and you have

409
00:27:43,636 --> 00:27:49,356
this secretary treasury has to be like well like he's wrong about his business like if you actually

410
00:27:49,356 --> 00:27:54,356
you look into the data, I believe that AI proliferating,

411
00:27:55,916 --> 00:27:57,756
people learning how to use it is actually going to lead

412
00:27:57,756 --> 00:28:02,756
to thousands of flowers of individual small businesses

413
00:28:03,476 --> 00:28:04,316
springing up.

414
00:28:04,316 --> 00:28:08,196
You can do the job of 10 men, 100 men with one now.

415
00:28:08,196 --> 00:28:11,776
And if you're implementing this tech at your company,

416
00:28:11,776 --> 00:28:14,876
which we both are, it is very obvious that that is true.

417
00:28:14,876 --> 00:28:16,856
Like you said, I've never worked harder in my life

418
00:28:16,856 --> 00:28:19,576
because I can do more, but just diving into

419
00:28:19,576 --> 00:28:23,676
and really bringing like a real world example

420
00:28:23,676 --> 00:28:27,356
of how AI is not taking any of the jobs at BPI.

421
00:28:27,356 --> 00:28:29,956
It's extending your ability to do more jobs.

422
00:28:29,956 --> 00:28:30,796
Yeah.

423
00:28:30,796 --> 00:28:32,236
How are you guys implementing it?

424
00:28:32,236 --> 00:28:36,076
Yeah, so when Claude Code came out

425
00:28:36,076 --> 00:28:40,616
and then Claude Co-Work, it just completely blew our minds.

426
00:28:41,716 --> 00:28:43,536
We had been using these tools a lot.

427
00:28:43,536 --> 00:28:45,996
I was already, I guess, like a power user of this

428
00:28:45,996 --> 00:28:50,716
in many ways, but the transition to agentic models

429
00:28:50,716 --> 00:28:55,556
that can actually do full workflows is just crazy.

430
00:28:55,556 --> 00:28:59,976
And so we just sat down early in January

431
00:28:59,976 --> 00:29:02,996
and had an all staff call where we said,

432
00:29:02,996 --> 00:29:03,916
here's what we're doing.

433
00:29:03,916 --> 00:29:05,136
We're gonna really lean into this.

434
00:29:05,136 --> 00:29:07,656
We're gonna become the best people in DC

435
00:29:07,656 --> 00:29:09,236
to know how to use these tools.

436
00:29:10,396 --> 00:29:13,696
And each of us spent, I don't know,

437
00:29:13,696 --> 00:29:16,056
I don't know how many hours, right?

438
00:29:16,056 --> 00:29:17,796
Each of us just started playing with the tools, right?

439
00:29:17,796 --> 00:29:20,636
We said, everyone, think about these tools.

440
00:29:20,636 --> 00:29:22,136
Here's a brief overview.

441
00:29:22,136 --> 00:29:24,456
We did a presentation for like two hours with the team and said,

442
00:29:24,456 --> 00:29:26,456
here's generally what they can do.

443
00:29:26,456 --> 00:29:30,456
We want everyone on the team to spend a lot of time using these.

444
00:29:30,456 --> 00:29:32,696
Think about your existing workflows.

445
00:29:32,696 --> 00:29:35,236
Everyone has some sort of recurring tasks.

446
00:29:35,236 --> 00:29:39,996
They do think about how you can build these into recurring workflows.

447
00:29:39,996 --> 00:29:45,636
And then we want you to present to the team how you're going to use this.

448
00:29:46,016 --> 00:29:50,496
And the great thing about it is you can then encode those workflows into skills.

449
00:29:51,756 --> 00:30:02,796
And so that was a major unlock for the org because suddenly we just had our team's skill set just started populating.

450
00:30:03,516 --> 00:30:09,236
And we had a new thing in Slack of announcer skills here and people can know how to use them.

451
00:30:09,236 --> 00:30:21,056
And so it became this force multiplier where if you needed a specific skill to be called, obviously you would if you needed something for research, you talk to the head of research.

452
00:30:21,356 --> 00:30:27,876
But if you're doing something that needs some research, you can call the research skill and sort of like slot that in.

453
00:30:28,616 --> 00:30:36,036
And it was just like it was an incredible process to see it happen because now we're six months past that.

454
00:30:36,036 --> 00:30:43,716
and I would say our work product is better quality than ever before. We're getting a lot

455
00:30:43,716 --> 00:30:50,036
more traction on social media. It's just very clear to me that there are going to be two types

456
00:30:50,036 --> 00:30:56,936
of organizations, and we're going to see the K-shaped divergence of the firm. There are going

457
00:30:56,936 --> 00:31:04,516
to be firms that start to punch well above their weight because they have leaned into gaining the

458
00:31:04,516 --> 00:31:12,096
expertise in these tools. And the best thing about the tools is if your team really understands

459
00:31:12,096 --> 00:31:17,656
not only how to use them, but how to improve them over time, give really good feedback to them,

460
00:31:17,836 --> 00:31:22,816
make sure that the agents themselves are taking notes on your feedback, you can get it so that

461
00:31:22,816 --> 00:31:29,336
every error they present to you, you never see it again. And so now we're at a point where

462
00:31:29,336 --> 00:31:33,396
not only are we doing the things that we were doing six months ago better,

463
00:31:33,396 --> 00:31:35,896
but we're doing things that we could have never done before.

464
00:31:36,256 --> 00:31:39,716
You know, like our AI research on Bitcoins preferring AI,

465
00:31:40,496 --> 00:31:42,576
sorry, AI agents preferring Bitcoin.

466
00:31:44,176 --> 00:31:46,176
That was hugely viral.

467
00:31:46,316 --> 00:31:48,196
We were able to build out an entire website,

468
00:31:48,416 --> 00:31:51,036
much more interactive, much more multimedia stuff.

469
00:31:51,336 --> 00:31:55,236
We were able to do the scale of the research

470
00:31:55,236 --> 00:31:56,516
that wouldn't have been possible before.

471
00:31:57,216 --> 00:32:01,616
So I think that there are obviously growing pains.

472
00:32:03,396 --> 00:32:08,156
we are dealing with reducing slop all the time.

473
00:32:08,156 --> 00:32:12,496
It has become this constant sort of thorn in our side

474
00:32:12,496 --> 00:32:14,656
of like, how do we make sure there's no slop

475
00:32:14,656 --> 00:32:15,856
in the organization?

476
00:32:15,856 --> 00:32:18,976
Because, you know, there are some,

477
00:32:19,856 --> 00:32:22,156
some like, you know, stumbling blocks to it

478
00:32:22,156 --> 00:32:25,976
or things you have to learn how to manage, but.

479
00:32:25,976 --> 00:32:26,996
We deal with this too.

480
00:32:26,996 --> 00:32:30,896
Yeah, it's, yeah, but like the long view is like,

481
00:32:30,896 --> 00:32:34,036
It's just so obvious that you're just going to have

482
00:32:34,036 --> 00:32:37,056
the adopters and the people that don't take the time.

483
00:32:37,056 --> 00:32:38,056
Yeah.

484
00:32:38,056 --> 00:32:39,956
Does BPI have a company brain?

485
00:32:39,956 --> 00:32:41,136
A company brain?

486
00:32:42,356 --> 00:32:44,556
What do you consider a company brain?

487
00:32:44,556 --> 00:32:48,036
It's a persistent memory system attached to a knowledge graph.

488
00:32:48,036 --> 00:32:52,396
So we have a company brain, a TFTC, it's three layered.

489
00:32:52,396 --> 00:32:57,076
So we've leaned into harnesses.

490
00:32:57,076 --> 00:33:00,836
We used OpenClaw for six months.

491
00:33:00,836 --> 00:33:03,896
And then a month ago, after hearing about Hermes so much,

492
00:33:03,896 --> 00:33:05,696
like watching it from afar, I was like,

493
00:33:05,696 --> 00:33:06,576
all right, let me try Hermes.

494
00:33:06,576 --> 00:33:09,476
So we have our main agent that we use

495
00:33:09,476 --> 00:33:13,396
for a lot of tasks at TFTCs and a VPS that I control.

496
00:33:13,396 --> 00:33:14,816
He, we're anthropomorphic,

497
00:33:14,816 --> 00:33:18,836
we're anthropomorphizing these machines.

498
00:33:18,836 --> 00:33:23,396
The clanker is in the VPS and that's where everything sits.

499
00:33:23,396 --> 00:33:25,216
So we had the OpenClaw.

500
00:33:25,216 --> 00:33:30,536
And I basically just went to the OpenClaw agent that was running on Clawed 4.6.

501
00:33:30,936 --> 00:33:32,876
And I said, hey, I want to try out Hermes.

502
00:33:32,976 --> 00:33:35,336
Can you spin up a Hermes harness for me in your server?

503
00:33:35,696 --> 00:33:38,516
And just let me know when that's set up.

504
00:33:38,516 --> 00:33:43,916
And then tell me how to create a Telegram chat with that agent.

505
00:33:44,536 --> 00:33:46,156
And I'm going to go from there.

506
00:33:46,236 --> 00:33:47,056
So, like, set it up.

507
00:33:47,256 --> 00:33:47,436
Yeah.

508
00:33:47,636 --> 00:33:49,416
And then connected it.

509
00:33:49,416 --> 00:33:55,316
I wanted to AB test four, six, Opus four, six versus GPT five, five at the time.

510
00:33:55,476 --> 00:33:55,676
Yeah.

511
00:33:57,336 --> 00:34:03,756
And so I had the Hermes harness set up, connected it to five, five as the brain and played with it for a day.

512
00:34:04,096 --> 00:34:06,276
And almost immediately I was like, oh, this is better than what we've done.

513
00:34:06,336 --> 00:34:09,376
So I'm just going to like start using this as my daily driver.

514
00:34:09,556 --> 00:34:13,816
But because we had the company brain, so in that same server, we have like a three layered memory system.

515
00:34:13,816 --> 00:34:15,336
It's like flat notes.

516
00:34:15,456 --> 00:34:19,116
It's like the sole MD, the agent.md, the skill.md files, daily notes.

517
00:34:19,416 --> 00:34:27,936
wiki llm so there's like flat markdown files then we have a qmd semantic search vector database

518
00:34:27,936 --> 00:34:32,936
which like so if i give a prompt and it has keywords in it it'll it'll query that database

519
00:34:32,936 --> 00:34:37,636
that lives on the server without wasting any tokens and it'll find context of us dealing with

520
00:34:37,636 --> 00:34:43,836
that term in the past and then we have cogni cogne which is like an obsidian vault but it's

521
00:34:43,836 --> 00:34:51,396
agent first. And so that's the third layer, which is more expressive. So you have basically terms and

522
00:34:52,296 --> 00:34:59,016
vaults of particular subjects. And QMD will like query like every time we talked about it,

523
00:34:59,056 --> 00:35:03,336
then it'll go to Cogni like, okay, we've talked about this in the past, like, how is it

524
00:35:03,336 --> 00:35:07,656
interrelational to every other thing that may relate to this topic. And so like, it gets like

525
00:35:07,656 --> 00:35:12,136
a full context of how we've dealt with these certain terms. And it has temporal context to

526
00:35:12,136 --> 00:35:13,756
so it knows when we've talked about them.

527
00:35:14,176 --> 00:35:14,636
That is amazing.

528
00:35:14,636 --> 00:35:17,676
And then it'll go to the LLM.

529
00:35:17,836 --> 00:35:19,536
Like, okay, based off all this context,

530
00:35:19,636 --> 00:35:20,356
how we frame things.

531
00:35:20,436 --> 00:35:21,436
So it has all of our transcripts,

532
00:35:21,516 --> 00:35:23,076
all of our newsletters.

533
00:35:23,216 --> 00:35:24,576
So it now knows how we frame things.

534
00:35:24,796 --> 00:35:29,696
And that has been the most ROI that we've gotten

535
00:35:29,696 --> 00:35:31,496
in terms of investing the time

536
00:35:31,496 --> 00:35:33,176
to build out a particular part of the stack

537
00:35:33,176 --> 00:35:34,076
is that brain.

538
00:35:34,616 --> 00:35:35,276
It's really interesting.

539
00:35:35,456 --> 00:35:37,776
So that sounds like you're really trying

540
00:35:37,776 --> 00:35:39,016
to get as close as possible

541
00:35:39,016 --> 00:35:40,996
to an employee who has been with the org

542
00:35:40,996 --> 00:35:42,096
since its inception.

543
00:35:42,136 --> 00:35:43,776
has seen everything

544
00:35:43,776 --> 00:35:45,376
because that's what we're doing every day

545
00:35:45,376 --> 00:35:46,136
when we're working there

546
00:35:46,136 --> 00:35:47,636
is like you're building institutional knowledge.

547
00:35:48,716 --> 00:35:49,636
That's very cool.

548
00:35:50,016 --> 00:35:51,636
We're a little bit more simplistic.

549
00:35:52,416 --> 00:35:55,176
We use just the standard

550
00:35:55,176 --> 00:35:57,456
like Claude Enterprise subscription,

551
00:35:57,456 --> 00:36:00,576
but we do have something similar

552
00:36:00,576 --> 00:36:04,436
to a brain in a sense

553
00:36:04,436 --> 00:36:07,796
that we have like a shared set of context files.

554
00:36:08,176 --> 00:36:12,116
So we've sort of curated a project file

555
00:36:12,116 --> 00:36:16,856
that then has subfolders for every different arm in the organization.

556
00:36:17,416 --> 00:36:24,836
And we have at the top a ClaudeMD file that gives a basic overview of what we are

557
00:36:24,836 --> 00:36:28,216
and sort of all of context and all the different files within it,

558
00:36:28,376 --> 00:36:32,216
and then explain how it can search through those files and understand what we're doing.

559
00:36:32,676 --> 00:36:35,856
And then each one of the arms of the organization will have its own subfolder

560
00:36:35,856 --> 00:36:38,796
for comms or design or research or whatever.

561
00:36:38,796 --> 00:36:56,476
And in each of those, we have the, you know, sub-clawed MD files for each of those subfolders, sort of example workflows, example prior precedent, and then cross-references of, all right, here is our research workflow.

562
00:36:56,476 --> 00:37:00,596
We expect you to do this 20-step process for doing a research report.

563
00:37:01,376 --> 00:37:08,876
And then once you get the user's approval or feedback, we sort of have encoded the entire life cycle of the product.

564
00:37:09,436 --> 00:37:15,176
So we'll start with, all right, if you kick off the research skill, it'll start with ideation.

565
00:37:15,876 --> 00:37:19,316
And then we have specific gates where the user provides feedback.

566
00:37:19,916 --> 00:37:24,476
And then it'll continue working up the product and then give you another user feedback gate.

567
00:37:24,476 --> 00:37:26,256
And it'll continue working up the product.

568
00:37:26,476 --> 00:37:36,296
And then once it finalizes the research portion, they'll then hand off to the comms portion or it'll hand off the design and then comms.

569
00:37:36,556 --> 00:37:42,656
And so we have it just as a sort of intricate folder and subfolder system with Claude MD files throughout.

570
00:37:43,136 --> 00:37:45,096
And it seems like an assembly line.

571
00:37:45,476 --> 00:37:45,716
Yeah.

572
00:37:45,916 --> 00:37:46,456
What do you think of it?

573
00:37:46,496 --> 00:37:47,136
Yeah, exactly.

574
00:37:47,476 --> 00:37:47,636
Yeah.

575
00:37:47,976 --> 00:37:48,856
Well, that's the thing.

576
00:37:48,916 --> 00:37:50,276
There's like a thousand ways it's going to get.

577
00:37:50,376 --> 00:37:51,496
It's like for your purposes.

578
00:37:51,496 --> 00:37:54,376
Like that probably makes a lot of sense for like our purposes.

579
00:37:54,556 --> 00:37:54,916
This makes it.

580
00:37:54,916 --> 00:37:56,916
And that's what's so fascinating

581
00:37:56,916 --> 00:38:00,216
is that the landscape is so wide right now.

582
00:38:00,216 --> 00:38:02,176
Everybody's still mapping the territory too.

583
00:38:02,316 --> 00:38:04,016
And so I just love hearing all the people saying this.

584
00:38:04,016 --> 00:38:05,476
And honestly, we could use both of these.

585
00:38:05,696 --> 00:38:08,296
We could probably use a database like that

586
00:38:08,296 --> 00:38:11,656
for just context about BPI and what are our positions

587
00:38:11,656 --> 00:38:13,316
and what are the papers we published.

588
00:38:14,416 --> 00:38:15,836
That would probably be a helpful thing

589
00:38:15,836 --> 00:38:16,796
to know how to plug in.

590
00:38:17,156 --> 00:38:19,776
What I have noticed though is you do have to be really careful

591
00:38:19,776 --> 00:38:27,336
because you can almost like accidentally context poison yourself where you'll notice it'll keep

592
00:38:27,336 --> 00:38:34,876
making an error. And then at some point you're like, oh, it's saying that because like at some

593
00:38:34,876 --> 00:38:40,856
point in my feedback to it, it like left a note for itself that it reads every single time it

594
00:38:40,856 --> 00:38:47,616
gives an output and it should not be reading that note. And like I've consistently found like

595
00:38:47,616 --> 00:38:50,176
whenever I'm having some sort of capability problem,

596
00:38:50,176 --> 00:38:53,076
it's either problems with my prompting itself

597
00:38:53,076 --> 00:38:55,256
or problems with the context that I'm giving it.

598
00:38:55,256 --> 00:39:11,184
Like I giving it bad examples of prior work product or something that aren up to the standard we need and it drawing on them for design inspiration or something and so you know always like thinking about what is the context

599
00:39:11,184 --> 00:39:17,264
for every single prompt and yeah trying to like it's almost like pruning or something like bonsai

600
00:39:17,264 --> 00:39:22,704
tree you know you want it to like constantly be improved and you know every time you use it

601
00:39:22,704 --> 00:39:28,504
you're in some ways you could like accidentally poison the context for future conversations or

602
00:39:28,504 --> 00:39:34,084
improve the context for future conversations um and teaching the employees that too of

603
00:39:34,084 --> 00:39:44,444
using these systems your initial implication your initial uh i don't know impulse would be

604
00:39:44,444 --> 00:39:48,604
if it makes a small error okay i can just like fix that myself it'll be a small tweak

605
00:39:48,604 --> 00:39:55,444
but if you understand the right way to give it feedback you can provide feedback in a way that

606
00:39:55,444 --> 00:40:02,824
what might just be an easy fix for you now is fixed forever if you just explain hey this needs

607
00:40:02,824 --> 00:40:08,584
to be fixed and keep a note for yourself to never make this problem again make no mistakes make no

608
00:40:08,584 --> 00:40:15,864
mistakes forever going forward um but it is really great to see it's it's also just really fun yeah

609
00:40:15,864 --> 00:40:22,304
i find it to be like a much more fun way of working i do too it's uh i've are you voice to

610
00:40:22,304 --> 00:40:28,804
text or are you typing stuff? I'm voice of course. Yes. Yeah. Whisper flow. I use super whisper. Oh my

611
00:40:28,804 --> 00:40:35,724
gosh. I know. I mean, we need to be better about this. Right. Um, but, uh, what, and I was just

612
00:40:35,724 --> 00:40:42,724
having this conversation with Thomas cause I co-write the newsletter now with my agent. Yeah.

613
00:40:42,724 --> 00:40:47,384
And basically what I'll do actually, does he have a name? Martin is a more sophisticated Marty.

614
00:40:47,384 --> 00:40:55,024
that's amazing okay so marina's he's trying to try to make somebody recognizing that i don't

615
00:40:55,024 --> 00:41:00,724
have the capacity to store files in my brain like right martin does on a server so he's more

616
00:41:00,724 --> 00:41:04,484
sophisticated he's going to be be better but i was just talking about this thomas to thomas like

617
00:41:04,484 --> 00:41:08,384
i was writing the newsletter here at pub key earlier and by writing the newsletter it's like

618
00:41:08,384 --> 00:41:14,184
hey basically my flow is i'll i was showing you yesterday i sent you a screenshot of the bpi q2

619
00:41:14,184 --> 00:41:19,784
report which we covered in the newsletter today and basically i yesterday when that came out i

620
00:41:19,784 --> 00:41:25,224
sent a note to our bitcoin brief uh topic in our telegram chat and said hey i want to talk about

621
00:41:25,224 --> 00:41:28,584
this tomorrow when we get to write the newsletter like this is one of the things we're gonna cover

622
00:41:29,224 --> 00:41:35,784
um so i'll do that and i'll do like anywhere from five to ten links and then morning morning of it's

623
00:41:35,784 --> 00:41:39,224
like okay pull up all the links all the emails i forwarded to you about stuff i want to cover

624
00:41:39,224 --> 00:41:43,584
and let's, I want you to, based off of the engagement

625
00:41:43,584 --> 00:41:45,224
that we've gotten in the newsletter in the past,

626
00:41:45,284 --> 00:41:49,204
you have access to that data on the back end of our CMS,

627
00:41:49,704 --> 00:41:51,384
like structure the newsletter in a way

628
00:41:51,384 --> 00:41:52,604
that we'll get the most engagement.

629
00:41:53,984 --> 00:41:55,164
But like, so we're filtering,

630
00:41:55,464 --> 00:41:57,044
I'm definitely covering these topics.

631
00:41:58,644 --> 00:42:01,844
Machine, you know, based off the topics

632
00:42:01,844 --> 00:42:02,664
we want to talk about,

633
00:42:02,744 --> 00:42:05,464
which is going to resonate the most with the audience

634
00:42:05,464 --> 00:42:07,124
and what they may deem most important.

635
00:42:07,244 --> 00:42:08,984
So like we have a lead story and then signal stories.

636
00:42:09,224 --> 00:42:11,224
So then it comes back to me, it's like,

637
00:42:11,224 --> 00:42:13,064
I think this should be the lead today,

638
00:42:13,064 --> 00:42:14,304
and these should be the signal stories,

639
00:42:14,304 --> 00:42:15,704
and here's all I'm thinking about framing it.

640
00:42:15,704 --> 00:42:17,504
And then I'll be like, okay,

641
00:42:17,504 --> 00:42:18,724
I understand why you're framing it this way,

642
00:42:18,724 --> 00:42:19,884
but let's tweak this, that.

643
00:42:19,884 --> 00:42:22,024
And I talk for like 10 minutes, like, okay,

644
00:42:22,024 --> 00:42:23,624
here's what I wanna cover frame.

645
00:42:23,624 --> 00:42:26,524
And then it's like, okay, I think we're at a good spot.

646
00:42:26,524 --> 00:42:27,904
I like the lead, I like the signal stories,

647
00:42:27,904 --> 00:42:29,544
like, let's go right.

648
00:42:29,544 --> 00:42:31,044
And so that puts together a draft,

649
00:42:31,044 --> 00:42:32,504
gets in the back end of our ghost CMS,

650
00:42:32,504 --> 00:42:35,284
and I read it twice, and then get final edits,

651
00:42:35,284 --> 00:42:36,924
like, okay, you messed up here.

652
00:42:36,924 --> 00:42:38,264
And then we hit send.

653
00:42:38,264 --> 00:42:39,904
And everybody's like, oh, you're not writing anymore.

654
00:42:39,944 --> 00:42:40,984
You're going to lose that skill.

655
00:42:42,124 --> 00:42:44,044
And I thought that for the longest time.

656
00:42:44,164 --> 00:42:48,244
I actually shied away from using Claude for writing for a while.

657
00:42:48,304 --> 00:42:51,844
But now I feel more comfortable for two reasons, one of which is the company brain is there.

658
00:42:51,844 --> 00:43:04,604
So it has that institutional knowledge of how we frame things, even how our opinions have evolved over time and how the voice and the positions that we have on certain topics.

659
00:43:04,604 --> 00:43:09,244
and it's able to inject that based off of stuff that we've talked about on the show and written

660
00:43:09,244 --> 00:43:12,384
when I was still manually writing in years past.

661
00:43:13,244 --> 00:43:17,244
The second thing is I had a conversation with somebody you know,

662
00:43:17,324 --> 00:43:18,424
we're not going to dox him on the show.

663
00:43:19,444 --> 00:43:21,464
And he completely changed my mind because people were worried,

664
00:43:21,544 --> 00:43:23,024
like, we're going to use the art of writing.

665
00:43:23,124 --> 00:43:25,044
I do still, I do write, I do type.

666
00:43:25,224 --> 00:43:26,684
I tell people, like, I don't type in there.

667
00:43:26,724 --> 00:43:27,304
I do sometimes.

668
00:43:27,864 --> 00:43:29,124
I do still write handwritten notes.

669
00:43:29,204 --> 00:43:29,984
I like that art.

670
00:43:30,624 --> 00:43:32,144
It's an art form that should never die.

671
00:43:32,984 --> 00:43:34,164
But he described it to me.

672
00:43:34,164 --> 00:43:37,464
He's like, we're basically just returning to the era of the scribe.

673
00:43:38,064 --> 00:43:56,844
And he changed the way I prompt because the way he describes me is like, when you're talking to these things, since it's an LLM with like a matrixy vector database in the back with like points of association, like you need to give it as much context as possible so you can eliminate points of association in that matrixy to give you more narrow output.

674
00:43:57,444 --> 00:44:00,684
And so what you do is you pretend like you're Napoleon Bonaparte.

675
00:44:01,044 --> 00:44:01,384
Oh, my God.

676
00:44:01,524 --> 00:44:03,044
You took it out of my mind.

677
00:44:03,044 --> 00:44:04,464
I was just about to say this.

678
00:44:04,464 --> 00:44:04,704
Right.

679
00:44:04,904 --> 00:44:05,264
So like,

680
00:44:05,384 --> 00:44:06,624
it's like after a day of battle,

681
00:44:06,624 --> 00:44:09,224
you get back to your war tent and you have like 10 scribes,

682
00:44:09,304 --> 00:44:10,924
one for munitions,

683
00:44:11,084 --> 00:44:11,804
replenishments,

684
00:44:11,864 --> 00:44:12,984
one for like war philosophy,

685
00:44:13,124 --> 00:44:13,264
like,

686
00:44:13,344 --> 00:44:13,544
ah,

687
00:44:13,804 --> 00:44:14,624
one for strategy.

688
00:44:14,624 --> 00:44:14,924
Like,

689
00:44:14,924 --> 00:44:16,004
here's where we messed up today.

690
00:44:16,624 --> 00:44:18,364
And you just talk to,

691
00:44:18,524 --> 00:44:24,364
you spin up a bunch of sessions and each session is an individual scribe that you give a bunch of context to.

692
00:44:24,504 --> 00:44:24,664
Yep.

693
00:44:24,784 --> 00:44:28,964
And it forces you to think from first principles and really articulate what you're trying to get out there.

694
00:44:29,084 --> 00:44:29,864
That's so funny.

695
00:44:30,304 --> 00:44:30,704
Bitcoiners,

696
00:44:30,784 --> 00:44:32,544
we all just like come to the same conclusions independently.

697
00:44:33,044 --> 00:44:39,384
Have you read Napoleon's biography? No. Oh, my gosh. OK. Andrew Roberts, Napoleon, a life.

698
00:44:39,864 --> 00:44:49,384
Best book I've read in a long time. Just incredible. I think about this all the time.

699
00:44:49,484 --> 00:44:55,464
Napoleon was like the most incredible human I've ever read about. He would do this. He would go

700
00:44:55,464 --> 00:45:00,804
back. He would triple dictate. He would be able to dictate faster than his scribes could write

701
00:45:00,804 --> 00:45:07,384
things down. And so he was one of the only people in recorded history that had this ability where he

702
00:45:07,384 --> 00:45:13,324
could do exactly what you said. He could dictate, tend to, it's similar to a grandmaster chess

703
00:45:13,324 --> 00:45:18,104
player who goes and plays 20 different games simultaneously and comes back and he can remember

704
00:45:18,104 --> 00:45:23,884
the context for the moves he's planning. Napoleon would do the same thing with writing these really

705
00:45:23,884 --> 00:45:30,484
just incredibly detailed and important letters to all the different world leaders, all of his

706
00:45:30,484 --> 00:45:36,124
different troops. It's crazy the breadth of what he was able to cover. But yeah, he would go back

707
00:45:36,124 --> 00:45:42,464
to the tent. And after a day of the most intense fighting in documented history, he would then go

708
00:45:42,464 --> 00:45:47,664
and dictate a letter on the importance of building a local bridge in a rural municipality in France,

709
00:45:47,664 --> 00:45:53,304
and then follow that up with a letter on the need for a girls education academy, because there

710
00:45:53,304 --> 00:45:58,944
really isn't one in this certain area of Paris. And then he'd go on to another one and dictate

711
00:45:58,944 --> 00:46:04,124
something about, you know, preparing his army for invasions in Russia. I mean, it was just

712
00:46:04,124 --> 00:46:10,324
incredible how he's able to do this. And I do think that that is what these agents allow us to do

713
00:46:10,324 --> 00:46:16,324
is multiply human agency. And that is the good timeline. The good timeline is that the best

714
00:46:16,324 --> 00:46:25,424
aspects of human greatness, achievement, and will and vitality are multiplied. And I feel that

715
00:46:25,424 --> 00:46:26,984
happening when I use this.

716
00:46:28,064 --> 00:46:31,244
But I do think it is something to be really cognizant

717
00:46:31,244 --> 00:46:32,944
of how you're using the tools.

718
00:46:32,944 --> 00:46:36,244
Like if you're using it in this dictation sense

719
00:46:36,244 --> 00:46:38,664
where you are able, when I'm using it,

720
00:46:40,204 --> 00:46:42,264
you know, and dictating to it,

721
00:46:42,264 --> 00:46:45,924
I can say so much more than I could possibly type.

722
00:46:45,924 --> 00:46:47,224
Because I can just talk forever.

723
00:46:47,224 --> 00:46:49,104
All of us can yap.

724
00:46:49,104 --> 00:46:51,264
Typing can be exhausting.

725
00:46:51,264 --> 00:46:52,644
And I do-

726
00:46:52,644 --> 00:46:54,264
It's slow, I type slower than I think.

727
00:46:54,264 --> 00:47:22,604
Yeah, exactly. So you actually like I feel like I lose some fidelity of my thoughts to commands when I write. Now, there are certainly many things that you have to really carefully phrase and write correctly. And, you know, that is in publications and things like that, that I do. I think you should spend more time thinking about exactly what you're saying, phrasing it, refining it like a sculpture or something.

728
00:47:22,604 --> 00:47:30,924
but for just raw output and ability to impact the world the vacation model is just incredible

729
00:47:30,924 --> 00:47:35,784
it's awesome yeah yeah so freaks when you take bitcoin seriously you start with custody you want

730
00:47:35,784 --> 00:47:39,524
to control your keys avoid single points of failure and make sure your savings cannot disappear

731
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because you or someone else screwed up that is what unchained has been focused on since 2016

732
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733
00:47:47,604 --> 00:47:52,024
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734
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That means about one out of every 200 Bitcoin sits inside an Unchained vault.

735
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Their model is simple.

736
00:47:56,904 --> 00:47:58,404
You hold two keys, they hold one key.

737
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And it always takes two keys to move Bitcoin, meaning their single key can't access your Bitcoin on its own.

738
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739
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740
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741
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742
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743
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744
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745
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746
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747
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And that is because I'm a CrowdHealth member. My family and I have been CrowdHealth members for

748
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five years now, literally this month. Five years ago, we joined CrowdHealth. We've had two babies.

749
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We've had multiple health events, and we're never going back to health insurance.

750
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CrowdHealth is crowdfunded healthcare. So you sign up for CrowdHealth, you pay a monthly fee,

751
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you help out with other people's bills. And it's significantly cheaper than health insurance. We

752
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were on COBRA as a family of three. When I left my last job before I went full-time with TFTC,

753
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went on the crowd health. Now as a family of five, we pay, I believe $700 a month. It's

754
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755
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negotiated healthcare prices as much as 50, 60, 80%. In many cases, they help out with babies.

756
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757
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762
00:50:02,664 --> 00:50:07,664
What's the rate of adoption of AI tools outside of BPI in the city? Is it big or is it?

763
00:50:07,664 --> 00:50:10,824
I expected it would be a lot higher than it is.

764
00:50:11,564 --> 00:50:15,164
Well, I have this theory that Bitcoiners are just like early adopters to all this stuff.

765
00:50:15,744 --> 00:50:16,724
This is what I was just thinking.

766
00:50:16,904 --> 00:50:21,424
Every time I talk to a Bitcoiner about this stuff, they have some crazy workflow.

767
00:50:22,064 --> 00:50:24,204
Because we just lean into new technology.

768
00:50:25,004 --> 00:50:30,704
And I mean, I've talked about this with like Thorn and Galaxy and Skyler on the design stuff.

769
00:50:30,824 --> 00:50:37,124
Like every Bitcoiner I know at all these different places in the industry or different types of jobs or skill sets.

770
00:50:37,664 --> 00:50:42,584
Like all of us have independently come up with crazy interesting ways to use this stuff.

771
00:50:43,904 --> 00:50:49,084
When I talk to people at traditional think tanks, like they're not, this isn't even on their radar.

772
00:50:49,524 --> 00:50:55,744
You know, there's just like an institutional inertia for a lot of these more legacy institutions.

773
00:50:55,984 --> 00:50:56,744
I think this is true.

774
00:50:57,324 --> 00:51:00,684
You know, Zach Shapiro, our head of policy, he's finding this at the law firm level.

775
00:51:00,964 --> 00:51:01,444
You know, he's.

776
00:51:03,324 --> 00:51:04,304
He's beating the drum.

777
00:51:04,304 --> 00:51:06,364
I mean, he's going out on the BPI policy hour,

778
00:51:06,364 --> 00:51:08,224
I feel like has been like, Zach, like,

779
00:51:08,224 --> 00:51:10,844
like lawyers, you better start vibe coding.

780
00:51:10,844 --> 00:51:11,904
You better start using this.

781
00:51:11,904 --> 00:51:13,544
Well, he wrote an article that went viral.

782
00:51:13,544 --> 00:51:16,944
And then like, he, from that had so many attorneys

783
00:51:16,944 --> 00:51:21,284
reach out to him that are, you know, at major law firms.

784
00:51:21,284 --> 00:51:24,304
And they're just so frustrated.

785
00:51:24,304 --> 00:51:25,864
I dealt with this.

786
00:51:25,864 --> 00:51:29,564
It was frustrating for me in 2022, 2023,

787
00:51:29,564 --> 00:51:33,244
when I was working at a firm here in DC,

788
00:51:33,244 --> 00:51:37,644
of just how hard it was to use any of the tools

789
00:51:37,644 --> 00:51:39,944
in the way that they're meant to be used.

790
00:51:39,944 --> 00:51:43,484
And that was when the tools weren't even that capable.

791
00:51:43,484 --> 00:51:46,264
You know, like we couldn't even access it on our laptop.

792
00:51:46,264 --> 00:51:49,084
Now they have some mediocre tools,

793
00:51:49,084 --> 00:51:51,364
but it's all sort of like baked in stuff,

794
00:51:52,804 --> 00:51:55,244
like Westlaw AI and stuff like that.

795
00:51:55,244 --> 00:51:57,944
And Zach has done a great job of just saying,

796
00:51:57,944 --> 00:52:01,184
no, you need to just integrate it top to bottom

797
00:52:01,184 --> 00:52:04,944
and you will be able to provide professional services

798
00:52:04,992 --> 00:52:07,892
You know, one-tenth the cost and twice the quality.

799
00:52:08,892 --> 00:52:13,592
And I think that has really surprised people at what he's been able to pull off.

800
00:52:13,712 --> 00:52:17,272
And then from that, I've met lots of other...

801
00:52:17,272 --> 00:52:25,432
It seems like what's happening is there's lots of senior associates or young partners that are breaking off from law firms.

802
00:52:25,472 --> 00:52:34,532
And I'm sure this is happening in other fields, too, where they're realizing, hey, as a solo shop, I can do what a team of 20 would do and do it at better quality.

803
00:52:34,532 --> 00:52:41,112
and keep all the money and keep all the money yeah um so well this is cool to see i mean this

804
00:52:41,112 --> 00:52:46,272
dovetails into an important point that we definitely should discuss which is like policy

805
00:52:46,272 --> 00:52:53,192
around ai like as we're describing it is incredibly powerful and i think it's incredibly

806
00:52:53,192 --> 00:52:58,472
important to make sure that we're able to utilize these tools in the way that

807
00:52:58,472 --> 00:53:00,872
we know we can moving forward.

808
00:53:01,272 --> 00:53:03,032
And so like policy around AI,

809
00:53:03,952 --> 00:53:06,732
whether it pertains to the models you can access

810
00:53:06,732 --> 00:53:12,092
and the energy debate around how those models are being trained

811
00:53:12,092 --> 00:53:15,652
and how the inference is being delivered is extremely important.

812
00:53:15,652 --> 00:53:17,872
And it seems pretty chaotic right now.

813
00:53:18,432 --> 00:53:19,432
It's very chaotic.

814
00:53:19,912 --> 00:53:24,612
I constantly think about what we did with nuclear energy, right?

815
00:53:24,732 --> 00:53:27,212
We invented basically unlimited energy.

816
00:53:28,472 --> 00:53:32,572
And then we banned it and built enough weapons to blow up the world many times over.

817
00:53:33,152 --> 00:53:37,732
I mean, we basically did the absolute worst thing possible with that technology.

818
00:53:38,492 --> 00:53:41,972
And I'm really, really concerned we're going to do the same thing.

819
00:53:42,132 --> 00:53:46,412
It took us about 50 years to get back to a semblance of sanity and nuclear policy.

820
00:53:46,652 --> 00:53:46,912
Yeah.

821
00:53:47,032 --> 00:53:48,772
And honestly, we're really far from it.

822
00:53:48,772 --> 00:53:55,492
The NRC has done an unbelievable amount of damage on the nuclear energy, on the nuclear industry.

823
00:53:55,492 --> 00:54:06,852
And what's so funny is if you go back and you actually read the announcement of the NRC, all the different major nuclear industry heads were like, this is a great new day for America.

824
00:54:06,852 --> 00:54:12,672
I can't wait for America to build out nuclear under this new leadership of a nuclear regulatory committee.

825
00:54:12,772 --> 00:54:15,312
I mean, people were just like patting themselves on the back.

826
00:54:15,392 --> 00:54:17,092
The people in Congress are super happy with it.

827
00:54:17,112 --> 00:54:18,152
The industry loved it.

828
00:54:18,492 --> 00:54:20,752
And it killed all the progress.

829
00:54:21,612 --> 00:54:24,832
It just became filled with people.

830
00:54:24,832 --> 00:54:34,072
Like if you listen to the guy who is the head of the NRC under Obama, he will openly get on stage and brag about how nuclear is the worst technology.

831
00:54:34,452 --> 00:54:36,312
We stopped it in every way we could.

832
00:54:36,432 --> 00:54:37,692
It's not going to save anyone.

833
00:54:39,772 --> 00:54:40,732
It's very funny.

834
00:54:41,072 --> 00:54:46,872
So point being, I'm really concerned that we're going to go to the same place with AI.

835
00:54:46,872 --> 00:54:55,892
the government just the nature of the institution struggles so hard with understanding exponentials

836
00:54:55,892 --> 00:55:05,632
or understanding just reasoning about existential risk I feel like is this way to just like one

837
00:55:05,632 --> 00:55:12,572
shot the government you know you have someone like in during COVID lockdowns right you have

838
00:55:12,572 --> 00:55:20,412
someone like Trump, who in theory is pro-freedom, pro-innovation, pro-small businesses,

839
00:55:20,412 --> 00:55:28,332
et cetera. They said, okay, there's a risk here that this could be some sort of major catastrophe.

840
00:55:28,692 --> 00:55:33,032
We're just going to shut everything down indefinitely. Print a bunch of money.

841
00:55:33,432 --> 00:55:39,152
Print infinite money. They just can't reason about when someone says, oh, this is existential.

842
00:55:39,152 --> 00:55:44,912
like just logic goes out the window we saw it with nuclear we saw it with the pandemic we saw it

843
00:55:44,912 --> 00:55:51,252
we're potentially seeing it now with ai i do think that the administration the current administration

844
00:55:51,252 --> 00:56:01,492
is somewhat inoculated to restricting ai but it is we're still at the very early innings

845
00:56:01,492 --> 00:56:08,892
how many people have died from ai like we haven't had a major catastrophe i think that inevitably

846
00:56:08,892 --> 00:56:14,012
like any technology, you know, you invent ships, there's going to be shipwrecks, you invent AI,

847
00:56:14,372 --> 00:56:20,992
some people will use it as a tool for bad things or accidentally use it to cause some sort of harm.

848
00:56:22,332 --> 00:56:29,812
I guess my point is, we are seeing pretty strong calls for heavy regulation of this technology

849
00:56:29,812 --> 00:56:38,212
before we've even seen any of those, you know, misuses or harms manifest.

850
00:56:38,212 --> 00:56:41,412
Or on the other side, on the positive side, explore the full potential of it.

851
00:56:41,812 --> 00:56:43,852
Yeah, or explore the full potential of it.

852
00:56:43,952 --> 00:56:55,972
And so I'm just worried that without someone explaining in clear terms the optimistic case for human flourishing with AI,

853
00:56:55,972 --> 00:57:07,072
how this is a complement to human agency, greatness, achievement, and all of the sort of knock-on benefits it can bring to individuals, localities, states,

854
00:57:07,072 --> 00:57:10,832
that you're going to just, you know,

855
00:57:11,152 --> 00:57:15,052
go down a pretty dark path of you'll get surveilled,

856
00:57:15,592 --> 00:57:18,392
closed, permissioned, AI fiefdoms.

857
00:57:20,352 --> 00:57:23,032
You know, there are people in the administration

858
00:57:23,032 --> 00:57:25,612
that defend open source,

859
00:57:26,312 --> 00:57:28,852
but is that going to stand up over time

860
00:57:28,852 --> 00:57:31,892
if we have open source that's at the capability of Fable

861
00:57:31,892 --> 00:57:33,812
or five times better than Fable?

862
00:57:34,272 --> 00:57:35,292
I really hope so.

863
00:57:35,432 --> 00:57:36,692
It has to, in my mind,

864
00:57:36,692 --> 00:57:38,252
and for us to have a free society.

865
00:57:40,332 --> 00:57:43,352
But there's strange winds blowing in DC

866
00:57:43,352 --> 00:57:46,832
and I feel like there's a lot more money coming in

867
00:57:46,832 --> 00:57:48,092
on the restrict side.

868
00:57:48,092 --> 00:57:49,692
What's whispering in these winds?

869
00:57:49,692 --> 00:57:51,612
Yeah, I mean, just one example.

870
00:57:52,952 --> 00:57:57,952
Trump's, one of Trump's like ground game lieutenants,

871
00:57:59,452 --> 00:58:03,932
her name is escaping me now, I think it's Lisa Kremer.

872
00:58:03,932 --> 00:58:06,912
She used to, she ran like the Stop the Steal

873
00:58:06,912 --> 00:58:11,112
grassroots campaign for the 2020 election

874
00:58:11,112 --> 00:58:12,592
and the dispute over that.

875
00:58:14,132 --> 00:58:16,732
She is now being funded by effective altruists.

876
00:58:16,732 --> 00:58:17,972
Oh gosh.

877
00:58:17,972 --> 00:58:20,772
To run a new campaign called Humans First,

878
00:58:20,772 --> 00:58:25,772
which is like a MAGA aligned anti-AI.

879
00:58:25,772 --> 00:58:27,012
Populist anti-AI.

880
00:58:27,012 --> 00:58:28,212
Yeah, populist AI.

881
00:58:28,212 --> 00:58:31,052
So I will say that the doomers,

882
00:58:31,052 --> 00:58:42,292
The people that want to paint this pessimistic view of AI, they are very, very savvy about how to play in the conversation.

883
00:58:42,292 --> 00:58:44,092
The frontier model providers themselves.

884
00:58:44,492 --> 00:58:48,112
I mean, I think OpenAI is sort of backed away from it.

885
00:58:48,192 --> 00:58:50,632
It seems like Dario and Anthropic are leaning into it.

886
00:58:50,632 --> 00:58:57,852
And one has to wonder, view their marketing or how they're positioning things with a lens of skepticism,

887
00:58:57,852 --> 00:58:59,892
because it's an easy way for them to get a regulatory mode,

888
00:58:59,972 --> 00:59:03,332
which if you're following economic incentives

889
00:59:03,332 --> 00:59:05,352
is probably something they want at the end of the day.

890
00:59:05,612 --> 00:59:09,512
It's really difficult to actually figure out motives.

891
00:59:10,032 --> 00:59:14,132
And that is what's difficult about all of this.

892
00:59:14,292 --> 00:59:15,792
I do think there are some people

893
00:59:15,792 --> 00:59:17,772
that genuinely think AI is dangerous.

894
00:59:18,092 --> 00:59:18,732
Paperclip problems.

895
00:59:18,932 --> 00:59:20,452
And yeah, we're going to get paperclipped

896
00:59:20,452 --> 00:59:23,352
and that they are not doing this.

897
00:59:23,532 --> 00:59:25,452
Yudkowsky is not seeking regulatory capture.

898
00:59:25,452 --> 00:59:28,632
Gagowski genuinely from the bottom of his heart

899
00:59:28,632 --> 00:59:40,612
wants to blow all this stuff up And for whatever reason has just been like one by these doomer scenarios And then I think there like there just this whole spectrum of different people that

900
00:59:41,172 --> 00:59:47,332
are all, it is a really strange set of bedfellows of people that are pushing in the same direction.

901
00:59:48,612 --> 00:59:52,932
You know, you start to think through it, you have foreign influence, right? Strategic adversaries,

902
00:59:52,932 --> 00:59:57,812
of course, they want to undermine the use of the technology. You have, let's say, radical

903
00:59:57,812 --> 01:00:04,492
environmentalists, people that want to de-develop civilizations. Yeah, Malthusian. You have

904
01:00:04,492 --> 01:00:10,792
economic populists that have legitimate concerns about job displacement, and they're confused about

905
01:00:10,792 --> 01:00:18,552
where they're going to fit into all this. You have people that are just your classic run-of-the-mill

906
01:00:18,552 --> 01:00:23,632
socialist, you know, Marxist type people that generally believe that all this should be

907
01:00:23,632 --> 01:00:29,912
redistributed um you have the national security hawks that think only the government should have

908
01:00:29,912 --> 01:00:37,092
access to technology and we need to restrict it to just a few bureaucrats um then you have

909
01:00:37,092 --> 01:00:44,192
like the effective altruist you have the incumbents uh that are playing for the frontier regulatory

910
01:00:44,192 --> 01:00:50,712
capture game like all of these people are angling in a similar direction and sort of rowing in the

911
01:00:50,712 --> 01:00:55,312
same boat. I don't even think they're working together. But it is just this weird thing that

912
01:00:55,312 --> 01:01:02,752
we haven't really seen with any other. Typically, you have like, pretty strong set of voices on both

913
01:01:02,752 --> 01:01:08,832
sides. This is sort of a weird place where people that in no other scenario, would it be sort of

914
01:01:08,832 --> 01:01:16,332
rowing in the same direction, are all for one reason or another, lining up. And I'm genuinely,

915
01:01:16,332 --> 01:01:27,692
I'm deeply concerned that our ability to use open source models or use these things in a way that maintains our privacy is compromised because of that.

916
01:01:28,472 --> 01:01:38,452
You know, it was 2023 when Dario was testifying in the Senate that open source AI is headed down a very dangerous path.

917
01:01:38,632 --> 01:01:40,332
That was three years ago.

918
01:01:40,332 --> 01:01:50,872
um so i i just think at the end of the day it would be just terrible if we're the ones that

919
01:01:50,872 --> 01:01:56,952
are getting the short end of the stick again as a result of all of this um and that's why

920
01:01:56,952 --> 01:02:01,052
going back to the beginning of the conversation dc is going to be very very important for the next

921
01:02:01,052 --> 01:02:07,392
10 years i mean my ability to predict what's going to happen is just so low i just it's all

922
01:02:07,392 --> 01:02:14,052
bets are off on what's going to happen with the rate of progress but on the policy front there are

923
01:02:14,052 --> 01:02:22,812
dark winds blowing in dc so i got a comment and then a follow-up yeah comment is uh comparing uh

924
01:02:22,812 --> 01:02:26,792
open ai strategy to anthropic is actually pretty funny because sam was just like you want five

925
01:02:26,792 --> 01:02:32,292
percent of the company we'll just give you we're not gonna we're not gonna fear monger we'll just

926
01:02:32,292 --> 01:02:36,672
give you five percent give us yeah we'll just cut you give us the moat cut you in yeah interesting

927
01:02:36,672 --> 01:02:41,712
strategy. Yeah. Yeah. So that's the comment follow up. Give the optimistic view. I feel like

928
01:02:41,712 --> 01:02:47,512
a lot of the, a lot of the conversation is focused on the pessimistic view and defending against that

929
01:02:47,512 --> 01:02:53,592
pessimistic view and not enough is focused on what is the optimistic outcome? What is the optimistic

930
01:02:53,592 --> 01:02:59,352
path? What could potentially happen in the future that, that many people will look back on and be

931
01:02:59,352 --> 01:03:03,632
like, wow, that was actually massively beneficial for me as an individual in society at large.

932
01:03:03,632 --> 01:03:15,052
Yeah, I think that the optimistic view is a proliferation of this technology and our ability to achieve even greater heights of human achievement.

933
01:03:15,972 --> 01:03:19,872
And what that looks like is broad.

934
01:03:19,872 --> 01:03:25,792
It has so many different ways that I see this going, whether it be for health care or education.

935
01:03:25,792 --> 01:03:33,992
but I do think that America has this incredible tradition of saying, we're going to experiment.

936
01:03:33,992 --> 01:03:39,392
We are going to embrace a new technology before everyone else. And we're going to do it in a way

937
01:03:39,392 --> 01:03:44,992
that preserves freedom, preserves privacy, preserves autonomy. And what that looks like

938
01:03:44,992 --> 01:03:51,732
for AI is again, choosing to lead the world and a rising tide lifts all boats. I think that if

939
01:03:51,732 --> 01:03:58,872
it's done correctly, that the people that have been left out of the economy in rural America that

940
01:03:58,872 --> 01:04:05,452
have just been hit one thing after another with losing jobs overseas, just being left out,

941
01:04:05,792 --> 01:04:11,012
having brain drain to metropolitan areas, I think those people stand to benefit an incredible amount

942
01:04:11,012 --> 01:04:19,072
because of the benefits of energy production that we're going to need to build this stuff out.

943
01:04:19,072 --> 01:04:22,032
and there will be economic benefits for those people.

944
01:04:22,712 --> 01:04:26,712
But I think really the upside in my mind is

945
01:04:27,472 --> 01:04:31,512
it does allow for an unprecedented amount of human agency.

946
01:04:31,952 --> 01:04:35,632
And this is only if we have

947
01:04:35,912 --> 01:04:40,752
AI that is free in the sense of what advice it can give you.

948
01:04:41,352 --> 01:04:45,712
And is it going to genuinely do be an extension of your will?

949
01:04:45,712 --> 01:04:49,892
or is it going to restrict your ability to operate?

950
01:04:50,092 --> 01:04:54,912
So the Doomer case is we're going to surveil everything you say,

951
01:04:55,012 --> 01:04:57,412
everything you ask, and if you have a tough question,

952
01:04:57,512 --> 01:04:58,732
then we're going to tell you the party line.

953
01:04:59,312 --> 01:05:03,552
The optimistic scenario is we're going to give you an AI

954
01:05:03,552 --> 01:05:05,692
that is aligned with your interest,

955
01:05:05,692 --> 01:05:08,632
that wants you to maximize your human capability.

956
01:05:09,632 --> 01:05:14,332
And the possibilities for our species, I think,

957
01:05:14,332 --> 01:05:16,592
or even like still underexplored.

958
01:05:17,512 --> 01:05:20,452
Our education system is terrible, absolutely terrible.

959
01:05:20,452 --> 01:05:22,792
I went through a public education

960
01:05:22,792 --> 01:05:27,712
and I feel like I'm probably 10% developed

961
01:05:27,712 --> 01:05:29,112
to what I could have come out of.

962
01:05:30,192 --> 01:05:32,272
Like you look back to the education systems

963
01:05:32,272 --> 01:05:35,192
of like ancient Rome and Greece and the Trivium

964
01:05:35,192 --> 01:05:36,852
and like how rigorous they are

965
01:05:36,852 --> 01:05:40,972
and how the people that came out of those,

966
01:05:40,972 --> 01:05:45,772
I think that we can have access to like the true

967
01:05:45,772 --> 01:05:47,272
great heights of civilization.

968
01:05:47,272 --> 01:05:50,372
Like Socrates being your teacher, like Alexander the Great.

969
01:05:50,372 --> 01:05:54,092
Yeah, having like, you know, I mean,

970
01:05:54,092 --> 01:05:55,412
I think about this all the time,

971
01:05:55,412 --> 01:06:00,412
but I think that each human has so much

972
01:06:00,412 --> 01:06:05,412
under cultivated capability for creation.

973
01:06:05,412 --> 01:06:08,092
And I really see this as there's a distinction

974
01:06:08,092 --> 01:06:10,432
between consumption and creation.

975
01:06:10,432 --> 01:06:27,612
And that the bad path is that we are relegated to infinite consumers, that we're going to be fed a algorithm that we have no access to, and it will provide endlessly stimulating entertainment for us to consume.

976
01:06:28,152 --> 01:06:29,852
And that is a dark path.

977
01:06:29,852 --> 01:06:39,752
The good path is we are all empowered to self-create in ways that is, you know, difficult to imagine.

978
01:06:40,572 --> 01:06:45,892
But each one of us has latent capabilities, I think.

979
01:06:46,052 --> 01:06:48,812
You know, I took up sort of as a side hobby.

980
01:06:48,852 --> 01:06:51,132
I took up painting a couple years ago.

981
01:06:51,132 --> 01:06:53,072
I got into art history.

982
01:06:53,492 --> 01:06:53,912
I like this.

983
01:06:53,952 --> 01:06:55,292
And then I started drawing.

984
01:06:55,692 --> 01:06:57,212
And then I said, drawing, come on.

985
01:06:57,292 --> 01:06:58,772
Like the real skill is painting.

986
01:06:58,772 --> 01:07:14,592
So I started doing painting started learning how to do like oil portraits and stuff And the possibilities I mean this is just like what the internet can do is the internet can connect you with the best teachers in the world right Like I was able

987
01:07:14,592 --> 01:07:22,372
to find a painting instructor, used to serve at the academy in Florence, and I took online lessons

988
01:07:22,372 --> 01:07:26,712
from him. He was fantastic. Steven Bauman, he's awesome. I highly recommend.

989
01:07:26,712 --> 01:07:33,792
um and then i think i need a connor brown original in my office yeah well i'm working maybe we can

990
01:07:33,792 --> 01:07:40,532
work on a side commission but um this is just like a microcosm right this was only possible

991
01:07:40,532 --> 01:07:47,632
because of the internet the ability to reduce the cost of incredible education now what does it look

992
01:07:47,632 --> 01:07:57,972
like when you multiply that to direct feedback from these agentic systems, right, that have the

993
01:07:57,972 --> 01:08:04,612
ability to provide customized feedback. One of the best things for improving my painting abilities

994
01:08:04,612 --> 01:08:13,952
has been I'll get an hour-long call with a guy who is a fantastic painter, and he'll review my work

995
01:08:13,952 --> 01:08:15,712
from the past month, provide some feedback,

996
01:08:15,712 --> 01:08:17,132
he'll draw on it.

997
01:08:17,132 --> 01:08:21,052
And that is, that hour of my month

998
01:08:21,052 --> 01:08:25,192
is probably responsible for 70% of my mental improvement.

999
01:08:25,192 --> 01:08:28,092
You know, learning a skill is partially

1000
01:08:28,092 --> 01:08:29,412
just like learning the motor skills,

1001
01:08:29,412 --> 01:08:30,372
but it's mostly-

1002
01:08:30,372 --> 01:08:31,892
Having an expert come correct you.

1003
01:08:31,892 --> 01:08:34,192
Yeah, and the mental heuristics, right?

1004
01:08:34,192 --> 01:08:36,032
Like this thing you didn't even know you were doing wrong.

1005
01:08:36,032 --> 01:08:37,532
And you have an expert like, oh,

1006
01:08:37,532 --> 01:08:39,692
looking over your shoulder like, do this,

1007
01:08:39,692 --> 01:08:41,932
don't do it that way, like shift this way, boom.

1008
01:08:41,932 --> 01:08:42,812
Yeah, yeah.

1009
01:08:43,132 --> 01:08:50,132
Pulls up, you know, Photoshop and paints over it and says like, oh, your your value structure here is wrong.

1010
01:08:50,132 --> 01:08:52,172
Like this area of the face is way too dark.

1011
01:08:52,432 --> 01:09:03,012
And you're not understanding that because the eye perceives like values in a near distance at a different, you know, level than than reality.

1012
01:09:03,012 --> 01:09:09,272
And you have to like step back, you know, he'll give you like advice that is very simple, but it actually completely changes how you paint.

1013
01:09:09,272 --> 01:09:12,632
You know, it's like, well, technically you're standing too close to paintings.

1014
01:09:12,732 --> 01:09:17,112
You have to walk away eight feet, take a couple of seconds and then walk back.

1015
01:09:17,192 --> 01:09:19,572
And then you sort of can your eye like adjust.

1016
01:09:19,952 --> 01:09:20,072
Yeah.

1017
01:09:20,592 --> 01:09:21,972
All these sort of small things.

1018
01:09:22,692 --> 01:09:25,692
Point being, that's one hour a month and it's expensive.

1019
01:09:25,692 --> 01:09:28,152
And even then, it's incredible to have that access.

1020
01:09:28,992 --> 01:09:38,452
This is just one way in which, you know, you can imagine a great AI teacher is available 24 seven to provide customized feedback.

1021
01:09:38,452 --> 01:09:40,532
and provide those insights constantly.

1022
01:09:41,552 --> 01:09:45,132
And so, again, you're unlocking these new heights

1023
01:09:45,132 --> 01:09:46,692
of human achievement and creation.

1024
01:09:46,872 --> 01:09:50,172
And I think what I struggle with

1025
01:09:50,172 --> 01:09:52,472
and what everyone is struggling with

1026
01:09:52,472 --> 01:09:56,952
is the algorithmic consumption complex

1027
01:09:56,952 --> 01:09:59,552
that just gets you in the doom scroll forever.

1028
01:10:00,152 --> 01:10:03,652
And the optimistic view is you have agents

1029
01:10:03,652 --> 01:10:05,032
that are acting in your own interests.

1030
01:10:05,032 --> 01:10:08,372
You have freedom on the technology.

1031
01:10:08,452 --> 01:10:10,972
you can select it for yourself and you can choose

1032
01:10:13,352 --> 01:10:15,912
to use the technology in a way that sort of makes you

1033
01:10:15,912 --> 01:10:17,312
the best version of yourself.

1034
01:10:18,952 --> 01:10:20,712
That's just one example, you know?

1035
01:10:20,712 --> 01:10:23,512
I see this across every sector.

1036
01:10:23,512 --> 01:10:28,192
And also filling in just like more time to self cultivate.

1037
01:10:28,192 --> 01:10:31,772
Like the great gentlemen scholars of yore,

1038
01:10:31,772 --> 01:10:32,912
you know, they were able to do that

1039
01:10:32,912 --> 01:10:35,352
because a lot of them had been gifted like massive estates

1040
01:10:35,352 --> 01:10:38,772
and had people that freed up their time

1041
01:10:38,772 --> 01:10:41,972
to pursue new creative endeavors and academic endeavors

1042
01:10:41,972 --> 01:10:43,432
and catalog every single insect

1043
01:10:43,432 --> 01:10:45,952
that had ever been found in their local area.

1044
01:10:45,952 --> 01:10:50,412
Like they were freed up with material wealth

1045
01:10:50,412 --> 01:10:53,112
to do those really cool human endeavors.

1046
01:10:53,952 --> 01:10:57,312
And I think that the optimistic scenario

1047
01:10:57,312 --> 01:10:59,552
is that we are gonna see the same thing.

1048
01:10:59,552 --> 01:11:01,152
We can see the same thing.

1049
01:11:01,152 --> 01:11:02,232
And then we can-

1050
01:11:02,232 --> 01:11:03,872
Come back to your war tent and-

1051
01:11:03,872 --> 01:11:04,932
Go back to your war tent.

1052
01:11:04,932 --> 01:11:05,992
orate to your scribes.

1053
01:11:06,072 --> 01:11:07,132
Like, here's what I learned out there.

1054
01:11:07,192 --> 01:11:08,192
Here's what I want to work on.

1055
01:11:08,372 --> 01:11:08,512
Yeah.

1056
01:11:08,592 --> 01:11:09,032
It's funny.

1057
01:11:09,112 --> 01:11:09,992
Like, I've taken up gardening.

1058
01:11:10,812 --> 01:11:11,612
Good for you.

1059
01:11:11,752 --> 01:11:12,952
I want to take up gardening.

1060
01:11:13,212 --> 01:11:14,532
I don't have a...

1061
01:11:14,532 --> 01:11:16,432
I'm in a pod dweller right now.

1062
01:11:16,452 --> 01:11:16,952
You're a pod dweller.

1063
01:11:16,992 --> 01:11:18,052
You got to get out of the pod, brother.

1064
01:11:18,312 --> 01:11:19,632
I was a pod dweller for a long time.

1065
01:11:20,032 --> 01:11:20,532
But it's good.

1066
01:11:20,592 --> 01:11:21,012
You like it?

1067
01:11:21,412 --> 01:11:22,552
I mean, I'm just getting...

1068
01:11:22,552 --> 01:11:24,072
Like, we moved into this new house.

1069
01:11:24,112 --> 01:11:27,232
It's a beautiful 112-year-old property.

1070
01:11:27,972 --> 01:11:30,032
So it's a nice stone old building.

1071
01:11:30,292 --> 01:11:30,952
Good for you.

1072
01:11:30,952 --> 01:11:33,132
Pre-Federal Reserve Act.

1073
01:11:33,132 --> 01:11:35,312
So we've got a nice English garden in the background.

1074
01:11:36,112 --> 01:11:39,372
We're the fifth family to ever live in this house.

1075
01:11:39,492 --> 01:11:42,312
And so I feel a duty to the property to treat it well.

1076
01:11:42,432 --> 01:11:46,712
And so I'm beginning to understand the nature of the landscaping.

1077
01:11:47,012 --> 01:11:47,372
You're a steward.

1078
01:11:47,592 --> 01:11:47,892
Yes.

1079
01:11:48,092 --> 01:11:49,092
We can all be stewards.

1080
01:11:49,312 --> 01:11:49,612
Yes.

1081
01:11:49,972 --> 01:11:50,312
Yes.

1082
01:11:50,572 --> 01:11:51,292
I'm a steward of the land.

1083
01:11:51,292 --> 01:11:52,372
It is our house.

1084
01:11:52,432 --> 01:11:52,852
We own it.

1085
01:11:53,152 --> 01:11:57,472
But it is a property that when our kids are up and they're out of the house, maybe they'll buy it.

1086
01:11:57,512 --> 01:12:01,172
Maybe there was one family that bequeathed it to their children.

1087
01:12:01,172 --> 01:12:05,492
so they got two generations in that house but who knows but for the time being a mistake you gotta

1088
01:12:05,492 --> 01:12:10,452
view this house is bigger than our family it's a it's a property that we have to steward is it a

1089
01:12:10,452 --> 01:12:15,652
lot of upkeep because of its historic nature i mean it's it's strong good bones okay good bones

1090
01:12:15,652 --> 01:12:21,732
yeah are you gonna get a physical clanker to walk around and help you i don't know and i imagine

1091
01:12:21,732 --> 01:12:29,412
eventually yes i don't think the physical clankers are uh dexterous dexterous dexterous enough or

1092
01:12:29,412 --> 01:12:31,712
I don't know. I've seen some crazy hand demos.

1093
01:12:31,812 --> 01:12:34,392
Yeah, but like getting up the steps and all that, I'm not sure if they're there yet.

1094
01:12:34,512 --> 01:12:35,352
Oh, they can get up steps.

1095
01:12:35,552 --> 01:12:35,712
Okay.

1096
01:12:36,152 --> 01:12:37,992
You think Optimus can't get up steps right now?

1097
01:12:38,892 --> 01:12:39,592
I don't know. I'm not sure.

1098
01:12:39,772 --> 01:12:39,912
Yeah.

1099
01:12:40,332 --> 01:12:42,732
But do you want to buy the first iteration or you want to wait like two generations?

1100
01:12:42,732 --> 01:12:52,232
This goes back to like, I would never in a million years have a closed source clanker in my house walking around going up my stairs.

1101
01:12:52,492 --> 01:12:52,672
Yeah.

1102
01:12:53,012 --> 01:12:53,372
Never.

1103
01:12:53,972 --> 01:12:54,332
Yeah.

1104
01:12:54,432 --> 01:12:56,892
Like I won't get a room to vacuum for that reason.

1105
01:12:56,892 --> 01:13:04,092
You know, if I get to like run my own, you know, if I get to choose what software goes on there, I might.

1106
01:13:04,332 --> 01:13:04,952
You get to build it.

1107
01:13:04,952 --> 01:13:05,092
I might.

1108
01:13:05,212 --> 01:13:07,852
You could use the models to build the software to go on there.

1109
01:13:07,952 --> 01:13:08,192
Yeah.

1110
01:13:08,292 --> 01:13:13,712
I mean, I would still have some like really weird concerns about it.

1111
01:13:13,712 --> 01:13:19,672
Just like the idea of having some robotic entity walking around my home.

1112
01:13:19,672 --> 01:13:31,292
But I would certainly never do that if it was a closed source surveillance tool that is phoning home all the time to, you know, Silicon Valley.

1113
01:13:32,632 --> 01:13:33,352
And the government.

1114
01:13:33,672 --> 01:13:34,292
And the government.

1115
01:13:34,632 --> 01:13:34,792
Yeah.

1116
01:13:34,972 --> 01:13:35,892
Yeah, exactly.

1117
01:13:38,532 --> 01:13:40,732
Yeah, it'd be like a hardware wallet or something, right?

1118
01:13:40,792 --> 01:13:42,692
I want to know the firmware.

1119
01:13:43,052 --> 01:13:46,332
I want to, like, feel really good about what I'm using.

1120
01:13:46,612 --> 01:13:46,792
Yeah.

1121
01:13:47,492 --> 01:13:49,532
So, very important.

1122
01:13:49,672 --> 01:13:50,432
Very important stuff.

1123
01:13:50,972 --> 01:13:58,312
And on a positive note, we had an American-made open weight model released this week.

1124
01:13:58,952 --> 01:13:59,772
Yeah, Inkling.

1125
01:14:00,192 --> 01:14:00,732
Very interesting.

1126
01:14:00,852 --> 01:14:01,372
Have you used it?

1127
01:14:01,492 --> 01:14:02,052
Not yet, no.

1128
01:14:02,232 --> 01:14:03,192
It just came out yesterday.

1129
01:14:03,372 --> 01:14:03,612
Yeah.

1130
01:14:03,992 --> 01:14:04,432
Yeah.

1131
01:14:06,572 --> 01:14:07,832
I'm excited by that.

1132
01:14:09,112 --> 01:14:11,032
I hope that it keeps going in that direction.

1133
01:14:11,032 --> 01:14:18,112
You know, it seems like every company starts off and they say, oh, we're the open source company.

1134
01:14:18,292 --> 01:14:19,132
We're open AI.

1135
01:14:19,132 --> 01:14:21,232
Open source is at the core of what we do.

1136
01:14:21,232 --> 01:14:22,072
We're a nonprofit.

1137
01:14:22,072 --> 01:14:26,732
We're going to, you know, then Grok was open source.

1138
01:14:26,732 --> 01:14:38,852
They released something early on and there was talk about this Facebook fumbled it You know yeah same thing Facebook oh yeah open source That really what gonna be the future

1139
01:14:38,852 --> 01:14:41,872
You have Llama and now Spark is closed source.

1140
01:14:41,872 --> 01:14:45,412
Like I do hope that we have someone who is just willing

1141
01:14:45,412 --> 01:14:49,132
to put the frontier open source and publish it.

1142
01:14:52,392 --> 01:14:53,612
We'll see.

1143
01:14:53,612 --> 01:14:55,352
I don't really know what to expect from the company.

1144
01:14:55,352 --> 01:14:58,672
It looks like it's like a little bit behind the frontier.

1145
01:14:58,672 --> 01:15:01,232
So we can't live in the world,

1146
01:15:01,232 --> 01:15:02,652
the world where China decides

1147
01:15:02,652 --> 01:15:04,112
they're gonna be the open source leader

1148
01:15:04,112 --> 01:15:06,612
and all the American labs just sort of close up.

1149
01:15:06,612 --> 01:15:07,712
It seems insane to me.

1150
01:15:07,712 --> 01:15:12,712
Oh my God, such a strategic blunder for the US

1151
01:15:12,712 --> 01:15:17,712
if we end up restricting open source

1152
01:15:17,712 --> 01:15:19,552
and then the entire world just downloads

1153
01:15:19,552 --> 01:15:23,112
China's open source weights.

1154
01:15:23,992 --> 01:15:28,012
Like think of the strategic benefit you can give a country

1155
01:15:28,012 --> 01:15:31,292
if the entire world is building on your open source stack,

1156
01:15:31,292 --> 01:15:33,712
it is way deeper than,

1157
01:15:33,712 --> 01:15:35,552
oh, it's not gonna talk about Tiananmen Square.

1158
01:15:35,552 --> 01:15:38,592
Okay, that's not, that's just kind of like,

1159
01:15:38,592 --> 01:15:40,192
you know, a parlor trick or something.

1160
01:15:40,192 --> 01:15:43,292
What really is at stake is China creates

1161
01:15:43,292 --> 01:15:46,072
a best in class open source model.

1162
01:15:46,072 --> 01:15:48,272
It's better than anyone else can put out.

1163
01:15:48,272 --> 01:15:53,272
It's cheaper and it somehow is really, really good

1164
01:15:54,272 --> 01:15:56,412
at programming for Huawei Ascend chips

1165
01:15:56,412 --> 01:15:58,312
and terrible at using Nvidia chips.

1166
01:15:59,552 --> 01:16:01,532
You know, it's just like, it makes these little tweaks

1167
01:16:01,532 --> 01:16:04,552
that each one incrementally actually really helps

1168
01:16:04,552 --> 01:16:06,172
China's strategic position.

1169
01:16:06,172 --> 01:16:08,252
And of course they would do that.

1170
01:16:08,252 --> 01:16:10,212
I mean, the soft power you get

1171
01:16:10,212 --> 01:16:12,392
of leading the world's open source models

1172
01:16:12,392 --> 01:16:14,952
and having those just be slightly better

1173
01:16:14,952 --> 01:16:16,352
at doing things in your interest

1174
01:16:16,352 --> 01:16:18,472
and slightly shittier at doing things

1175
01:16:18,472 --> 01:16:23,472
that are against your interest, huge, huge.

1176
01:16:23,472 --> 01:16:30,092
huge um do you think anybody in the administration realizes this no i mean i don't i mean we're we're

1177
01:16:30,092 --> 01:16:35,812
still so early in the conversation but somebody clip it and send it to them yeah if someone could

1178
01:16:35,812 --> 01:16:42,252
clip that send it um i would say send it to sax he's not there anymore send it to lutnik lutnik

1179
01:16:42,252 --> 01:16:46,552
would be a good person primary sex partner craft you've been on this show get it to him get in his

1180
01:16:46,552 --> 01:16:52,312
hands i'll text you um bringing us back to bitcoin but combining the two i mean

1181
01:16:52,312 --> 01:16:58,912
been a thesis within Bitcoin for a while, the abundant future that's going to be unleashed by

1182
01:16:58,912 --> 01:17:07,392
AI is going to make the need for a sound digital distributed currency like Bitcoin even stronger.

1183
01:17:07,672 --> 01:17:13,272
Are you more or less convinced of that? Oh, absolutely more convinced. But it goes back to

1184
01:17:13,272 --> 01:17:19,332
what type of systems are we going to be allowed to have or do we have? Right. Because I do think

1185
01:17:19,332 --> 01:17:24,432
that capable open source systems that are trained in a neutral way are going to prefer Bitcoin.

1186
01:17:24,972 --> 01:17:31,412
Our research has shown that if you just query them as they get more capable, they generally

1187
01:17:31,412 --> 01:17:37,012
prefer this is across different models. They prefer Bitcoin and stable coins. So I think that

1188
01:17:37,012 --> 01:17:42,772
in a world where people aren't putting their thumb on the scale, then the possibilities for

1189
01:17:42,772 --> 01:17:46,012
Bitcoin, its use in agentic commerce are just,

1190
01:17:47,452 --> 01:17:52,452
it's hard to even imagine because agents are going to have

1191
01:17:52,492 --> 01:17:57,492
so many fewer barriers in using this as everyday payment

1192
01:17:57,672 --> 01:17:58,772
compared to humans.

1193
01:17:59,892 --> 01:18:01,852
They're digitally native, Bitcoin's digitally native.

1194
01:18:01,852 --> 01:18:05,192
It just is going to click for them.

1195
01:18:06,092 --> 01:18:08,352
Nick Szabo wrote about the mental transaction costs

1196
01:18:08,352 --> 01:18:09,652
and stuff, they don't have any of that stuff.

1197
01:18:09,652 --> 01:18:11,432
So it's gonna be huge for them.

1198
01:18:11,432 --> 01:18:16,672
And I think will be naturally adopted because how much Bitcoin content is in their training set?

1199
01:18:16,792 --> 01:18:23,072
Like every rip you've ever recorded is somewhere in, you know, the training sets of the frontier models.

1200
01:18:23,692 --> 01:18:28,952
Like GPT-3, one of the tokens was GMAX from Gregory Maxwell.

1201
01:18:28,952 --> 01:18:31,412
He was actually one of the GPT-3 tokens.

1202
01:18:31,632 --> 01:18:32,092
That's insane.

1203
01:18:32,272 --> 01:18:34,372
And there was only like a small number of tokens.

1204
01:18:34,452 --> 01:18:34,752
I forget.

1205
01:18:34,852 --> 01:18:37,432
They only had like 20,000 unique tokens or something.

1206
01:18:37,432 --> 01:18:41,632
So like Bitcoiners are prolific in our content output.

1207
01:18:41,772 --> 01:18:48,432
Our arguments are right and are good and are consistent and appeal to machines.

1208
01:18:49,272 --> 01:18:50,772
You know, it is a tech forward approach.

1209
01:18:51,832 --> 01:19:06,432
So if we have open, permissionless, free AI, then I think that the implications for Bitcoin and its adoption are massive.

1210
01:19:07,432 --> 01:19:15,452
but if we have a dystopian scenario where all we have are surveilled and controlled AI fiefdoms

1211
01:19:15,452 --> 01:19:22,072
then it would not surprise me at all if the players start putting their thumb on the scale

1212
01:19:22,072 --> 01:19:31,452
I almost I almost hesitated in releasing our AI research about how agents prefer Bitcoin

1213
01:19:31,452 --> 01:19:39,492
because I know that many of the people in the frontier labs are, you know, socialist leaning

1214
01:19:39,492 --> 01:19:46,272
or sort of anti-libertarian leaning. And one of them has his own shit coin. I would, I was, yeah,

1215
01:19:46,312 --> 01:19:52,152
exactly. I was worried that just by releasing that, they might be like, oh, we need to like

1216
01:19:52,152 --> 01:19:56,272
alter the training set because Claude likes Bitcoin. We can't have that going on.

1217
01:19:56,272 --> 01:20:09,712
But I think that like ultimately open source software will provide the counterweight and will be sort of the mechanism that Bitcoin is uptaken by these agents.

1218
01:20:09,712 --> 01:20:14,712
So, but if we are sort of in this like fiefdom endgame,

1219
01:20:14,792 --> 01:20:19,612
which is easier to happen than people want to admit, I think,

1220
01:20:19,612 --> 01:20:23,892
then they easily could say, great.

1221
01:20:23,892 --> 01:20:25,732
So as part of our frontier testing

1222
01:20:25,732 --> 01:20:27,292
for releasing a new model to public,

1223
01:20:27,292 --> 01:20:29,272
it has to really like CBDCs.

1224
01:20:30,352 --> 01:20:31,832
Or these preferred stable coins.

1225
01:20:31,832 --> 01:20:34,272
Or these preferred stable coins.

1226
01:20:34,272 --> 01:20:35,952
Running on the X402 protocol.

1227
01:20:35,952 --> 01:20:36,792
Yeah.

1228
01:20:36,792 --> 01:20:37,632
That's what you prefer.

1229
01:20:37,632 --> 01:20:38,752
Yeah, exactly.

1230
01:20:38,752 --> 01:20:45,312
So that's kind of where my mind is at, is we're going to have to make sure we get that scenario.

1231
01:20:46,072 --> 01:20:49,852
Well, I think we could keep going for hours, but I know you have to get somewhere.

1232
01:20:50,192 --> 01:20:51,232
I'm going to be back down here a lot.

1233
01:20:51,412 --> 01:20:52,272
We'll do this more frequently.

1234
01:20:52,672 --> 01:20:53,992
Yeah, I'm looking forward to it.

1235
01:20:54,072 --> 01:20:55,032
We're going to have plenty to talk about.

1236
01:20:55,352 --> 01:20:56,172
Yes, we are.

1237
01:20:56,172 --> 01:20:56,752
Ten years.

1238
01:20:56,832 --> 01:20:59,432
Ten years of very important things happening in the city.

1239
01:20:59,752 --> 01:20:59,952
Yeah.

1240
01:21:00,272 --> 01:21:00,592
All right.

1241
01:21:00,852 --> 01:21:01,472
Peace and love, freaks.

1242
01:21:01,612 --> 01:21:04,252
Thank you for listening to this episode of TFTC.

1243
01:21:04,752 --> 01:21:08,292
If you've made it this far, I imagine you got some value out of the episode.

1244
01:21:08,752 --> 01:21:12,652
If so, please share it far and wide with your friends and family.

1245
01:21:12,812 --> 01:21:14,092
We're looking to get the word out there.

1246
01:21:14,932 --> 01:21:18,932
Also, wherever you're listening, whether that's YouTube, Apple, Spotify,

1247
01:21:19,692 --> 01:21:22,212
make sure you like and subscribe to the show.

1248
01:21:22,612 --> 01:21:26,952
And if you can leave a rating on the podcasting platforms, that goes a long way.

1249
01:21:27,372 --> 01:21:31,932
Last but not least, if you want to get these episodes a day early and ad-free,

1250
01:21:32,232 --> 01:21:35,032
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1251
01:21:35,512 --> 01:21:37,772
You can go to fountain.fm to find that.

1252
01:21:37,772 --> 01:21:40,552
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1253
01:21:40,552 --> 01:21:42,272
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1254
01:21:42,832 --> 01:21:43,852
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1255
01:21:44,252 --> 01:21:45,372
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1256
01:21:46,392 --> 01:21:48,392
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1257
01:21:48,392 --> 01:21:49,592
via Fountain as well.

1258
01:21:50,172 --> 01:21:52,472
Thank you for your time, and until next time.

1259
01:21:53,092 --> 01:21:53,292
Okay!