Latest / TFTC: A Bitcoin Podcast / #773: Open Source AI Is Non-Negotiable with Conner Brown

Transcript

#773: Open Source AI Is Non-Negotiable with Conner Brown · TFTC: A Bitcoin Podcast

• 0:00
  You've had a dynamic where money has become freer than free.
• 0:10
  We talk about a Fed just gone nuts.
• 0:13
  All the central banks going nuts.
• 0:16
  So it's all acting like safe haven.
• 0:18
  I believe that in a world where central bankers are tripping over themselves to devalue their currency, Bitcoin wins.
• 0:25
  In the world of fiat currencies, Bitcoin is the victor.
• 0:28
  I mean, that's part of the bull case for Bitcoin.
• 0:31
  If you're not paying attention, you probably should be.
• 0:36
  DC, it's easy to get to from Philadelphia.
• 0:38
  I think I want to be here a lot more.
• 0:40
  We need you here, Marty.
• 0:41
  Do you?
• 0:41
  We need you here in the trenches.
• 0:42
  Yeah, we've got PubKey now.
• 0:44
  We've got the office set up.
• 0:46
  We need more Marty Bent.
• 0:47
  We need rips all the time in DC.
• 0:49
  I prefer them in person, as you know.
• 0:52
  Yeah.
• 0:52
  We've only ever recorded in person.
• 0:53
  Yes.
• 0:54
  This is the third time now.
• 0:55
  As is tradition.
• 0:55
  We didn't wait, what was it, seven, eight years between the second and third, like we did with the first and second.
• 1:01
  Right.
• 1:01
  We're going to keep these recurring basis.
• 1:03
  A lot's going to be happening in D.C.
• 1:05
  D.C. is going to be, you know, the new up and coming important city, I think.
• 1:09
  Yeah.
• 1:09
  Everyone likes to talk about Austin and Miami.
• 1:12
  But this is where a lot of stuff is going to happen over the next five, ten years with all the technology changes.
• 1:18
  Like D.C. is going to be the true city to be in, I think, in the coming years.
• 1:23
  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.
• 1:31
  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.
• 1:37
  And then but just with the way things are headed. Yeah, I do unfortunately think it's important that we're here.
• 1:45
  Yes. A couple of things on the agenda today. We're going to talk about AI, not only the policy implications around AI,
• 1:52
  but actually implementing it in our businesses, particularly at BPI.
• 1:57
  And what you guys have been up to.
• 1:58
  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.
• 2:06
  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.
• 2:18
  Yeah, gosh, so much stuff going on.
• 2:21
  But I think at the corner of it, it's just this technology continues to improve, whether it be both with Bitcoin and AI.
• 2:32
  And that is just speeding up the pace of change.
• 2:36
  We're seeing it in our organization.
• 2:38
  We're seeing it in what we're being tasked with in different meetings and stuff.
• 2:43
  And so it's really it's been a lot.
• 2:47
  So yesterday we released what we did over just the past three months.
• 2:49
  and it's crazy. I was reading through it and I just couldn't believe how much we got accomplished
• 2:55
  in three months. And, um, you know, people say like AI is going to like replace all our jobs
• 3:00
  and stuff. And like everyone I know is working harder than they ever have before, because suddenly
• 3:04
  all of these sort of stray ideas that you were like, Oh, I don't have the people or time to do
• 3:08
  that. You can actually just roll up your sleeves and do it with like an afternoon. Um, and so,
• 3:14
  yeah, it has been sort of overwhelming. We've been doing a lot of new international work. We've been
• 3:18
  doing lots of new research that we were able to build out much deeper than we had been previously.
• 3:24
  So yeah, it's been a whirlwind really since I joined. I mean, we last spoke when I first joined
• 3:30
  BPI and just the change in the organization since then has been crazy, crazy. And we're really
• 3:39
  excited for what it means for the next five years of what we'd be able to build here in DC.
• 3:44
  Yeah. Well, let's start internationally. Yeah. Taiwan. How did that happen?
• 3:49
  So Taiwan, this is a perfect example. We had an idea for a research paper. One of our fellow,
• 3:54
  we said, hey, Jake, you have a background in DOD. Would you be interested in doing a paper on
• 4:00
  Taiwan's cash reserve? Why diversifying into Bitcoin would make sense for them?
• 4:06
  And he was excited for it. Taiwan has a really interesting history. I didn't know this,
• 4:12
  but Taiwan exists entirely because they use their gold as a strategic resource to like flee the country, basically.
• 4:20
  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.
• 4:29
  And so we thought, oh, that'd be interesting. We have the research expertise.
• 4:34
  We'll just do a paper sort of thought experiment.
• 4:36
  And then we get an email like two weeks after we released it with photos from Taiwan's legislature.
• 4:45
  And they're like, your paper was amazing.
• 4:48
  It is from a member of Congress, Legislator Ka.
• 4:51
  He emails us photos of him delivering our paper to the premier of the legislative Yuan, the head of the central bank.
• 4:58
  And we were just like, oh, my gosh, this is crazy.
• 5:03
  and then a few weeks after that we got invited to go and brief them for a week so
• 5:08
  um another thing has been keeping us busy is lots of international travel so what can you share about
• 5:14
  what was shared in the briefing or the information that was exchanged i can say that taiwan every
• 5:23
  person we talk to is really really cognizant of this the geopolitical situation they're in
• 5:30
  it feels like the weight of the world is on them and they're bringing it up all the time of they know that
• 5:37
  they've always been in this tenuous position between the United States and China
• 5:42
  and that every day they feel like the stakes are higher because the strategic importance of Taiwan
• 5:49
  goes up every day as the compute build out accelerates and there's more and more value on
• 5:55
  the island and it just leaves them in this like strange psychological position where everyone is
• 6:03
  thinking about it constantly like what does this mean for us what does it mean for the people of
• 6:08
  Taiwan for a long time we had this principle of the silicon shield that America would defend
• 6:14
  Taiwan's national interest it would defend them in a military escalation because of how valuable
• 6:20
  their chips are in many ways that's an even stronger case today than it was 20 years ago
• 6:25
  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.
• 6:43
  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.
• 6:53
  And that just came through across every conversation we had.
• 6:58
  We met with people from both the different parties there.
• 7:02
  The DPP and the KMT are the two ruling political parties there.
• 7:06
  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.
• 7:26
  And it's it's just really, really interesting political dynamic.
• 7:29
  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.
• 7:39
  That's what I was going to ask.
• 7:39
  Like, how is the partisan polarity over there?
• 7:43
  It's it's it's very, very strong, but it's just on this issue of reconciliation.
• 7:50
  What side do we end up?
• 7:51
  What side do we lean towards?
• 7:54
  And I think that both of them are just coming to grips with it.
• 7:58
  It's like what everything else we do.
• 8:00
  It's so hard to predict the future right now
• 8:03
  because of AI, the strategic questions wrapped up in that.
• 8:08
  And Taiwan feels it probably stronger
• 8:10
  than anywhere else on earth.
• 8:11
  I mean, it's just in the daily conversation all the time.
• 8:15
  So what I can share is we met at length
• 8:20
  with their head regulator
• 8:23
  for their financial services commission
• 8:26
  and the Central Bank of Taiwan.
• 8:29
  And it was my first time meeting people from a foreign central bank.
• 8:34
  Super interesting.
• 8:36
  I went over there not really knowing what to expect.
• 8:39
  So, you know, you write a paper on Bitcoin.
• 8:43
  I've met many central bankers, you know, over the years working in policy.
• 8:48
  And I think everyone has always been extremely skeptical of Bitcoin, you know, arm's length.
• 8:54
  Oh, yeah, nice to meet you.
• 8:55
  Pleasantries.
• 8:56
  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.
• 9:14
  without going into too much detail.
• 9:17
  I was surprised at their hospitality,
• 9:21
  their level of understanding,
• 9:24
  the quality of their questions.
• 9:26
  It was just a fantastic experience.
• 9:28
  We want to go back.
• 9:30
  And yeah, so hopefully more updates on that soon.
• 9:33
  But yeah, I think that this is something
• 9:37
  that is easy to forget about is what a signal
• 9:41
  that the American administration has sent to the world.
• 9:46
  You know, no one is ever excited with the pace of change in D.C.
• 9:49
  or how, you know, fast or slow things go.
• 9:53
  But things like the executive order for the SBR,
• 9:57
  like that is still being digested actively.
• 10:01
  And everyone around the world is trying to figure out what it means,
• 10:04
  you know, what to do with that.
• 10:06
  So it was a really, really cool experience.
• 10:09
  And it was my first time being there.
• 10:11
  So it was just all around just fantastic.
• 10:13
  Yeah.
• 10:14
  SBR, they're fighting over who actually gets control over the reserve right now, right?
• 10:18
  It's between commerce and treasury.
• 10:21
  I mean, it was something that we kind of scratched our heads at a little bit when the EO first came out,
• 10:26
  which was they've jointly delegated authority between treasury and commerce to execute the SBR executive order.
• 10:34
  And I think they're just still trying to figure out exactly how do they do this?
• 10:39
  How do they build up the capacity?
• 10:42
  I mean, it's been sort of embarrassing
• 10:44
  for the administration a bit.
• 10:47
  You know, they had that scandal
• 10:48
  where they gave custody of the Marshalls funds
• 10:53
  to, you know, a contractor with shady origins
• 10:57
  whose son then ran off with some of the money.
• 11:00
  I mean, it's just like a-
• 11:01
  Comical.
• 11:02
  It really is just like a circus.
• 11:05
  So in true government fashion,
• 11:07
  it's always slower than you would expect.
• 11:09
  but i do i mean what we've heard is um you know there are lots of things happening um
• 11:18
  that people are trying to get things stood up and there's just like an endless series of
• 11:23
  bureaucratic hurdles um but they say expect something soon so two weeks tm we know that
• 11:31
  well here yeah two weeks two weeks two weeks to flatten the curve two weeks to execute the sbr yo
• 11:37
  I don't know. Bring it back internationally. UK. UK. Yeah. Another thing we went over there.
• 11:43
  And I guess what we're seeing is what happened in D.C. and with the new administration has just
• 11:51
  want all of these other governments are wanting to get the inside scoop from the people that work
• 11:57
  through the process of what how is the U.S. thinking about this and how can they be a fast
• 12:04
  follow. That was the, we went over to the UK and heard that term like a hundred times. The UK wants
• 12:11
  to be a fast follow. And, um, it was honestly pretty surprising. So I went over there just sort
• 12:17
  of expecting that they would like throw me in jail if I was looking at Twitter and instead,
• 12:22
  like surprisingly positive. Um, you know, they had just announced a cap on stable coin balances.
• 12:30
  and then the week we went over there,
• 12:33
  they actually rescinded that.
• 12:35
  And they're still, like many other governments,
• 12:39
  trying to wrap their head around what all of this means.
• 12:43
  But again, surprised by the level of openness,
• 12:46
  we met with people and we did a briefing
• 12:49
  in the House of Lords.
• 12:51
  It's a ton of fun, first time being in there.
• 12:53
  It was in the Parliament building,
• 12:55
  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
• 13:07
  looked like the Hogwarts like cafeteria,
• 13:11
  but yeah, surprisingly optimistic there too.
• 13:15
  You know, afterwards the head of their,
• 13:19
  is like a head of innovation at their FCA,
• 13:21
  put out a thing about the importance of Bitcoin policy.
• 13:23
  I mean, we have to remember, like these people, they don't even understand the difference between Bitcoin and shitcoin.
• 13:30
  They don't understand how Bitcoin is different from the parade of horribles they hear about.
• 13:37
  And they are very interested in the story we have to tell.
• 13:42
  So I think the lessons learned is you have to tell the story in a way that relates to their history.
• 13:49
  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.
• 13:59
  So those are the types of stakes that are at play here.
• 14:02
  And I think explaining in those broader historical terms, same with Taiwan.
• 14:07
  You know, we talked a lot about their historical use of gold as funding government and exile.
• 14:12
  So relating to those longer term historical narratives
• 14:16
  for a country, same here in America,
• 14:20
  is the key to getting people to understand
• 14:23
  the policy implications.
• 14:24
  Yeah, it's incredible work.
• 14:27
  It's exhausting.
• 14:29
  Thank you.
• 14:30
  I mean, we got a lot more to do.
• 14:31
  There's no shortage of work.
• 14:33
  Well, I mean, you guys are the hot chick on the block,
• 14:36
  not because of Bitcoin, because of AI.
• 14:38
  I mean, bringing this back to Taiwan.
• 14:40
  Yeah.
• 14:42
  You guys, I think Sam spearheaded the report,
• 14:45
  basically unearthing that China has been influencing
• 14:50
  conversations around AI data centers
• 14:51
  here in the United States.
• 14:52
  Yeah, that started as, like we were saying with AI,
• 14:57
  you can just do so much more.
• 14:58
  So it started as sort of like, I don't know, a side bit.
• 15:04
  People had mentioned to us, Bitcoin miners mentioned to us,
• 15:08
  they've been seeing just unprecedented local opposition
• 15:12
  and that they've been doing this for years.
• 15:15
  And they're used to some local concerns,
• 15:18
  obviously with any major infrastructure project,
• 15:20
  people are gonna have questions.
• 15:22
  But a few months ago they said,
• 15:24
  you know, we're seeing the same local people
• 15:26
  that have concerns, typical stuff.
• 15:28
  But we're also seeing this new thing,
• 15:30
  which is people from out of town that,
• 15:34
  while the local people will ask a reasonable question like,
• 15:37
  okay, where is this gonna be located?
• 15:40
  Is this gonna create noise?
• 15:42
  Is this gonna impact me in XYZ way?
• 15:45
  There would be these people from out of town
• 15:47
  that would really aggressively say,
• 15:50
  this is gonna give everyone an aneurysm, right?
• 15:53
  Or this is going to destroy all the bees in the area.
• 15:56
  I heard that no bees could ever exist
• 15:58
  within 50 miles of a data center, is that true?
• 16:00
  Just like ludicrous things.
• 16:03
  And they were like, we've never seen this before.
• 16:06
  Can you guys see if there's anything going on?
• 16:09
  He said, yeah, we'll take a look at it.
• 16:11
  And we just got Sam Lyman that joined.
• 16:14
  So he came over from Treasury
• 16:17
  and Sam has experience dealing with this stuff.
• 16:20
  So he used to work-
• 16:21
  He was at Riot, right?
• 16:22
  He used to work at Riot.
• 16:22
  He's done the rounds in local communities in Texas,
• 16:26
  working on this stuff.
• 16:28
  And he just kind of started pulling the thread.
• 16:31
  And you start going through these different layers
• 16:34
  of nonprofits and all the different activist groups
• 16:38
  that are on the ground and mobilizing.
• 16:41
  And it just kind of shocked all of us.
• 16:46
  And then it just all sort of worked out
• 16:49
  in the virality of it,
• 16:51
  because everyone's talking about data centers now,
• 16:54
  and we were really the first to sort of
• 16:56
  put all the pieces together and say,
• 16:58
  well, actually, if you look at all these different projects,
• 17:01
  we're seeing a common element,
• 17:02
  which is the party for socialism and liberation
• 17:07
  are functioning as at least important organizers
• 17:11
  in a lot of these debates.
• 17:13
  And they have sort of a dubious history.
• 17:17
  So yeah, it's been a whirlwind past couple of months
• 17:20
  as that story broke.
• 17:21
  And who's the individual behind all of it?
• 17:23
  Who's very vocally anti?
• 17:25
  We don't know who is like,
• 17:28
  there's a lot of questions about the organization.
• 17:30
  What we know is that someone named Neville Roy Singham
• 17:38
  is a very wealthy philanthropist that lives
• 17:44
  at least part of the time in Shanghai,
• 17:47
  has said a lot of positive things
• 17:49
  that sort of align his views with those of China.
• 17:55
  And he is at least funding some nonprofits
• 17:59
  that are doing anti-data center stuff.
• 18:04
  It is, there's a lot of dark money involved.
• 18:06
  A lot of it is sort of unclear
• 18:08
  and we're trying to piece it all together
• 18:11
  and understand exactly what's happening.
• 18:15
  But yeah, I'd encourage anyone that's interested in this,
• 18:18
  read our reports.
• 18:19
  We have two different foreign influence reports
• 18:21
  and the case for American AI that sort of go over
• 18:25
  exactly what this nonprofit structure looks like,
• 18:29
  sort of all the different elements of foreign influence
• 18:30
  we've identified.
• 18:33
  And we've sort of detailed case studies
• 18:36
  of what we're seeing on the ground.
• 18:37
  And the one thing I do wanna say is,
• 18:40
  this is not to say in any way, shape or form
• 18:44
  that Americans themselves don't have legitimate concerns
• 18:47
  about this massive multi multi-billion dollar,
• 18:51
  trillion dollar build out of compute.
• 18:52
  Multi-trillion at this point.
• 18:54
  Yeah, I mean, it's like huge in its implications.
• 18:57
  These projects are larger than anything
• 18:59
  we've ever built before and are going to continue
• 19:02
  to just scale up over time.
• 19:05
  People have many legitimate questions about that.
• 19:08
  How is that gonna change their way of life?
• 19:10
  I don't think that the narratives that Anthropik
• 19:15
  or some of these effective altruist groups are putting out
• 19:18
  are compelling to the everyday American.
• 19:20
  And that is manifesting in a lot of concerns
• 19:22
  about this build out.
• 19:24
  So all of that, I think there are legitimate concerns and fears about AI and these data centers, their impact.
• 19:32
  But a proper accounting of this means you need to also think, OK, is there a foreign influence?
• 19:39
  What does that look like? Because there are strategic questions at play.
• 19:43
  And we know that our adversaries are savvy. They understand how social media works.
• 19:49
  They understand that in modern global great power competition, you're usually not fighting with boots on the ground.
• 19:58
  Fifth generation warfare.
• 20:00
  Yeah.
• 20:00
  The podcast I recorded this morning, we talked all about it.
• 20:02
  Yeah, yeah.
• 20:03
  I mean, it's just, it is the modern battlefield is on Twitter and Instagram.
• 20:07
  And they are, I think that we're just seeing like the latest in.
• 20:12
  Well, that's why we should all be thankful that BPI exists.
• 20:16
  We try to do our part at TFTC, but you have to engage in fifth generation warfare.
• 20:20
  And that means going, pulling on the threads, writing the reports, getting it out there.
• 20:25
  And I mean, was that the most viral thing you guys have ever done?
• 20:27
  Funnily not related to Bitcoin.
• 20:30
  Yeah, it was probably the most viral.
• 20:31
  I mean, we're on the front page of New York Times last week.
• 20:34
  So, but, you know, just the beginning, just the beginning.
• 20:37
  I think there might have been, I don't know.
• 20:40
  I mean, the numbers on it have just been insane.
• 20:42
  You know, it's one of those things that you hit at the right time and get circulated by the right people.
• 20:45
  mark andreason tells all his followers to read it and then the internet explodes you know yeah i mean
• 20:50
  that's why we're that's why i'm in town today is for the event tonight which is talking about energy
• 20:55
  policy data centers uh the intersection and how we should think about these things approach them
• 21:01
  and i had a conversation last night if you listen to the previous episode you're getting this again
• 21:07
  but i think it's important to reiterate to connor i i was sitting down with somebody who was
• 21:11
  involved in one of the largest utility companies in the United States.
• 21:16
  And we were just talking shop about like, all right, how do you,
• 21:19
  how do you educate the masses about this?
• 21:20
  Cause that's, I think one of the biggest uphill battles we have,
• 21:23
  and Bitcoiners I think know this more deeply than the AI data center people
• 21:29
  now, because we've been doing this for 10 years,
• 21:30
  but there is a lack of understanding of energy, the grid,
• 21:35
  how all of these things work, how data centers, Bitcoin mining operations,
• 21:40
  how they interact and how they affect your ability to access cheap electricity.
• 21:46
  And that's why I'm happy that American Bitcoin, PubKey and PubKey are starting this series,
• 21:51
  which would go for the next 10 months.
• 21:53
  But having conversations around these things.
• 21:56
  And I think to your point about social media, it's like packaging it and getting it out there in a way,
• 22:02
  which I think your report did very well.
• 22:04
  Yeah.
• 22:04
  I mean, it's so important to tell the story.
• 22:06
  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.
• 22:17
  That is not good for anyone.
• 22:21
  But but really.
• 22:24
  It's not surprising what we're seeing either, because what we're seeing is.
• 22:29
  a big tech executive gets up and says, well, AI is probably going to be as dangerous as pandemics
• 22:37
  and nuclear weapons combined. And it in the process is also going to take your job and the
• 22:43
  jobs of everyone, you know, and yeah, we're going to keep building it. Okay. How is this going to be
• 22:51
  compelled? Like this is not compelling for anyone. And I think it's just such a break from the
• 22:57
  American tradition of leaning into innovation and entrepreneurship and the optimism of building
• 23:04
  great things. That is what has made people inspired and want to come to America and want to build here.
• 23:10
  And what causes people to get up every day and build great companies is human achievement and
• 23:17
  greatness and energy is at the bottom of all of that. And, you know, I'm really excited. There's
• 23:23
  a lot of really, really great startups now that are getting into, I'm really glad to see there
• 23:27
  are startups that are doing real hard tech, um, energy production, breakthroughs and stuff like
• 23:36
  Valor Atomics or whatever. Um, you know, I saw that on Twitter, it's been all over my feed. Um,
• 23:41
  but if we're not telling a compelling story about how technology benefits us with either Bitcoin
• 23:49
  or open source AI or, you know, biotechnology, if we're not telling that compelling story,
• 23:56
  then it's going to manifest in hostility in a million different ways, all the way from the
• 24:03
  hyper local level of not letting any of this stuff get built all the way to federal licensing
• 24:10
  regimes, KYC for compute and surveillance of all your chat logs. It gets like very,
• 24:16
  very dystopian very quickly when you start convincing everyone that this is this crazy
• 24:23
  danger that we have no precedent for how to handle. It's just not true. It's not how
• 24:27
  our society was built. We're a society that trusts people with dangerous things. We let people have
• 24:34
  guns. I mean, in theory, America itself was founded on the idea that the people themselves
• 24:41
  can be trusted with dangerous tools, with self-government. I mean, this is like the core
• 24:46
  what we believe is that the people can be trusted with things. And if they break that trust, they
• 24:52
  will be prosecuted accordingly. Yeah, exactly. Exactly. It's it's it's we've dealt with dangerous
• 24:59
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  the taxable event, this is worth a serious look. Go to aven.com slash Bitcoin. That's A-V-E-N.com
• 26:56
  slash Bitcoin. Check it out. I think I'm back to the AI narrative. And it's one thing we've been
• 27:01
  working on at TFTC too, because we've been leaning in and maybe we can spitball some ideas, compare
• 27:07
  notes to how we've been implementing this stuff. But I think I've been trying to do this more and
• 27:11
  it's not an attempt to brag, but I think people, the broader public has an outside looking in view
• 27:20
  of AI and most of them haven't like really dove deeper than downloading chat gpt and
• 27:26
  interacting with the chat bot and I was actually relieved to see secretary percent do an interview
• 27:34
  this morning we were clipping it at tftc but talking about this exact problem where the
• 27:38
  interview was asking him dario modi is telling us it's going to take all of our jobs and you have
• 27:43
  this secretary treasury has to be like well like he's wrong about his business like if you actually
• 27:49
  you look into the data, I believe that AI proliferating,
• 27:55
  people learning how to use it is actually going to lead
• 27:57
  to thousands of flowers of individual small businesses
• 28:03
  springing up.
• 28:04
  You can do the job of 10 men, 100 men with one now.
• 28:08
  And if you're implementing this tech at your company,
• 28:11
  which we both are, it is very obvious that that is true.
• 28:14
  Like you said, I've never worked harder in my life
• 28:16
  because I can do more, but just diving into
• 28:19
  and really bringing like a real world example
• 28:23
  of how AI is not taking any of the jobs at BPI.
• 28:27
  It's extending your ability to do more jobs.
• 28:29
  Yeah.
• 28:30
  How are you guys implementing it?
• 28:32
  Yeah, so when Claude Code came out
• 28:36
  and then Claude Co-Work, it just completely blew our minds.
• 28:41
  We had been using these tools a lot.
• 28:43
  I was already, I guess, like a power user of this
• 28:45
  in many ways, but the transition to agentic models
• 28:50
  that can actually do full workflows is just crazy.
• 28:55
  And so we just sat down early in January
• 28:59
  and had an all staff call where we said,
• 29:02
  here's what we're doing.
• 29:03
  We're gonna really lean into this.
• 29:05
  We're gonna become the best people in DC
• 29:07
  to know how to use these tools.
• 29:10
  And each of us spent, I don't know,
• 29:13
  I don't know how many hours, right?
• 29:16
  Each of us just started playing with the tools, right?
• 29:17
  We said, everyone, think about these tools.
• 29:20
  Here's a brief overview.
• 29:22
  We did a presentation for like two hours with the team and said,
• 29:24
  here's generally what they can do.
• 29:26
  We want everyone on the team to spend a lot of time using these.
• 29:30
  Think about your existing workflows.
• 29:32
  Everyone has some sort of recurring tasks.
• 29:35
  They do think about how you can build these into recurring workflows.
• 29:39
  And then we want you to present to the team how you're going to use this.
• 29:46
  And the great thing about it is you can then encode those workflows into skills.
• 29:51
  And so that was a major unlock for the org because suddenly we just had our team's skill set just started populating.
• 30:03
  And we had a new thing in Slack of announcer skills here and people can know how to use them.
• 30:09
  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.
• 30:21
  But if you're doing something that needs some research, you can call the research skill and sort of like slot that in.
• 30:28
  And it was just like it was an incredible process to see it happen because now we're six months past that.
• 30:36
  and I would say our work product is better quality than ever before. We're getting a lot
• 30:43
  more traction on social media. It's just very clear to me that there are going to be two types
• 30:50
  of organizations, and we're going to see the K-shaped divergence of the firm. There are going
• 30:56
  to be firms that start to punch well above their weight because they have leaned into gaining the
• 31:04
  expertise in these tools. And the best thing about the tools is if your team really understands
• 31:12
  not only how to use them, but how to improve them over time, give really good feedback to them,
• 31:17
  make sure that the agents themselves are taking notes on your feedback, you can get it so that
• 31:22
  every error they present to you, you never see it again. And so now we're at a point where
• 31:29
  not only are we doing the things that we were doing six months ago better,
• 31:33
  but we're doing things that we could have never done before.
• 31:36
  You know, like our AI research on Bitcoins preferring AI,
• 31:40
  sorry, AI agents preferring Bitcoin.
• 31:44
  That was hugely viral.
• 31:46
  We were able to build out an entire website,
• 31:48
  much more interactive, much more multimedia stuff.
• 31:51
  We were able to do the scale of the research
• 31:55
  that wouldn't have been possible before.
• 31:57
  So I think that there are obviously growing pains.
• 32:03
  we are dealing with reducing slop all the time.
• 32:08
  It has become this constant sort of thorn in our side
• 32:12
  of like, how do we make sure there's no slop
• 32:14
  in the organization?
• 32:15
  Because, you know, there are some,
• 32:19
  some like, you know, stumbling blocks to it
• 32:22
  or things you have to learn how to manage, but.
• 32:25
  We deal with this too.
• 32:26
  Yeah, it's, yeah, but like the long view is like,
• 32:30
  It's just so obvious that you're just going to have
• 32:34
  the adopters and the people that don't take the time.
• 32:37
  Yeah.
• 32:38
  Does BPI have a company brain?
• 32:39
  A company brain?
• 32:42
  What do you consider a company brain?
• 32:44
  It's a persistent memory system attached to a knowledge graph.
• 32:48
  So we have a company brain, a TFTC, it's three layered.
• 32:52
  So we've leaned into harnesses.
• 32:57
  We used OpenClaw for six months.
• 33:00
  And then a month ago, after hearing about Hermes so much,
• 33:03
  like watching it from afar, I was like,
• 33:05
  all right, let me try Hermes.
• 33:06
  So we have our main agent that we use
• 33:09
  for a lot of tasks at TFTCs and a VPS that I control.
• 33:13
  He, we're anthropomorphic,
• 33:14
  we're anthropomorphizing these machines.
• 33:18
  The clanker is in the VPS and that's where everything sits.
• 33:23
  So we had the OpenClaw.
• 33:25
  And I basically just went to the OpenClaw agent that was running on Clawed 4.6.
• 33:30
  And I said, hey, I want to try out Hermes.
• 33:32
  Can you spin up a Hermes harness for me in your server?
• 33:35
  And just let me know when that's set up.
• 33:38
  And then tell me how to create a Telegram chat with that agent.
• 33:44
  And I'm going to go from there.
• 33:46
  So, like, set it up.
• 33:47
  Yeah.
• 33:47
  And then connected it.
• 33:49
  I wanted to AB test four, six, Opus four, six versus GPT five, five at the time.
• 33:55
  Yeah.
• 33:57
  And so I had the Hermes harness set up, connected it to five, five as the brain and played with it for a day.
• 34:04
  And almost immediately I was like, oh, this is better than what we've done.
• 34:06
  So I'm just going to like start using this as my daily driver.
• 34:09
  But because we had the company brain, so in that same server, we have like a three layered memory system.
• 34:13
  It's like flat notes.
• 34:15
  It's like the sole MD, the agent.md, the skill.md files, daily notes.
• 34:19
  wiki llm so there's like flat markdown files then we have a qmd semantic search vector database
• 34:27
  which like so if i give a prompt and it has keywords in it it'll it'll query that database
• 34:32
  that lives on the server without wasting any tokens and it'll find context of us dealing with
• 34:37
  that term in the past and then we have cogni cogne which is like an obsidian vault but it's
• 34:43
  agent first. And so that's the third layer, which is more expressive. So you have basically terms and
• 34:52
  vaults of particular subjects. And QMD will like query like every time we talked about it,
• 34:59
  then it'll go to Cogni like, okay, we've talked about this in the past, like, how is it
• 35:03
  interrelational to every other thing that may relate to this topic. And so like, it gets like
• 35:07
  a full context of how we've dealt with these certain terms. And it has temporal context to
• 35:12
  so it knows when we've talked about them.
• 35:14
  That is amazing.
• 35:14
  And then it'll go to the LLM.
• 35:17
  Like, okay, based off all this context,
• 35:19
  how we frame things.
• 35:20
  So it has all of our transcripts,
• 35:21
  all of our newsletters.
• 35:23
  So it now knows how we frame things.
• 35:24
  And that has been the most ROI that we've gotten
• 35:29
  in terms of investing the time
• 35:31
  to build out a particular part of the stack
• 35:33
  is that brain.
• 35:34
  It's really interesting.
• 35:35
  So that sounds like you're really trying
• 35:37
  to get as close as possible
• 35:39
  to an employee who has been with the org
• 35:40
  since its inception.
• 35:42
  has seen everything
• 35:43
  because that's what we're doing every day
• 35:45
  when we're working there
• 35:46
  is like you're building institutional knowledge.
• 35:48
  That's very cool.
• 35:50
  We're a little bit more simplistic.
• 35:52
  We use just the standard
• 35:55
  like Claude Enterprise subscription,
• 35:57
  but we do have something similar
• 36:00
  to a brain in a sense
• 36:04
  that we have like a shared set of context files.
• 36:08
  So we've sort of curated a project file
• 36:12
  that then has subfolders for every different arm in the organization.
• 36:17
  And we have at the top a ClaudeMD file that gives a basic overview of what we are
• 36:24
  and sort of all of context and all the different files within it,
• 36:28
  and then explain how it can search through those files and understand what we're doing.
• 36:32
  And then each one of the arms of the organization will have its own subfolder
• 36:35
  for comms or design or research or whatever.
• 36:38
  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.
• 36:56
  We expect you to do this 20-step process for doing a research report.
• 37:01
  And then once you get the user's approval or feedback, we sort of have encoded the entire life cycle of the product.
• 37:09
  So we'll start with, all right, if you kick off the research skill, it'll start with ideation.
• 37:15
  And then we have specific gates where the user provides feedback.
• 37:19
  And then it'll continue working up the product and then give you another user feedback gate.
• 37:24
  And it'll continue working up the product.
• 37:26
  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.
• 37:36
  And so we have it just as a sort of intricate folder and subfolder system with Claude MD files throughout.
• 37:43
  And it seems like an assembly line.
• 37:45
  Yeah.
• 37:45
  What do you think of it?
• 37:46
  Yeah, exactly.
• 37:47
  Yeah.
• 37:47
  Well, that's the thing.
• 37:48
  There's like a thousand ways it's going to get.
• 37:50
  It's like for your purposes.
• 37:51
  Like that probably makes a lot of sense for like our purposes.
• 37:54
  This makes it.
• 37:54
  And that's what's so fascinating
• 37:56
  is that the landscape is so wide right now.
• 38:00
  Everybody's still mapping the territory too.
• 38:02
  And so I just love hearing all the people saying this.
• 38:04
  And honestly, we could use both of these.
• 38:05
  We could probably use a database like that
• 38:08
  for just context about BPI and what are our positions
• 38:11
  and what are the papers we published.
• 38:14
  That would probably be a helpful thing
• 38:15
  to know how to plug in.
• 38:17
  What I have noticed though is you do have to be really careful
• 38:19
  because you can almost like accidentally context poison yourself where you'll notice it'll keep
• 38:27
  making an error. And then at some point you're like, oh, it's saying that because like at some
• 38:34
  point in my feedback to it, it like left a note for itself that it reads every single time it
• 38:40
  gives an output and it should not be reading that note. And like I've consistently found like
• 38:47
  whenever I'm having some sort of capability problem,
• 38:50
  it's either problems with my prompting itself
• 38:53
  or problems with the context that I'm giving it.
• 38:55
  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
• 39:11
  for every single prompt and yeah trying to like it's almost like pruning or something like bonsai
• 39:17
  tree you know you want it to like constantly be improved and you know every time you use it
• 39:22
  you're in some ways you could like accidentally poison the context for future conversations or
• 39:28
  improve the context for future conversations um and teaching the employees that too of
• 39:34
  using these systems your initial implication your initial uh i don't know impulse would be
• 39:44
  if it makes a small error okay i can just like fix that myself it'll be a small tweak
• 39:48
  but if you understand the right way to give it feedback you can provide feedback in a way that
• 39:55
  what might just be an easy fix for you now is fixed forever if you just explain hey this needs
• 40:02
  to be fixed and keep a note for yourself to never make this problem again make no mistakes make no
• 40:08
  mistakes forever going forward um but it is really great to see it's it's also just really fun yeah
• 40:15
  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
• 40:22
  text or are you typing stuff? I'm voice of course. Yes. Yeah. Whisper flow. I use super whisper. Oh my
• 40:28
  gosh. I know. I mean, we need to be better about this. Right. Um, but, uh, what, and I was just
• 40:35
  having this conversation with Thomas cause I co-write the newsletter now with my agent. Yeah.
• 40:42
  And basically what I'll do actually, does he have a name? Martin is a more sophisticated Marty.
• 40:47
  that's amazing okay so marina's he's trying to try to make somebody recognizing that i don't
• 40:55
  have the capacity to store files in my brain like right martin does on a server so he's more
• 41:00
  sophisticated he's going to be be better but i was just talking about this thomas to thomas like
• 41:04
  i was writing the newsletter here at pub key earlier and by writing the newsletter it's like
• 41:08
  hey basically my flow is i'll i was showing you yesterday i sent you a screenshot of the bpi q2
• 41:14
  report which we covered in the newsletter today and basically i yesterday when that came out i
• 41:19
  sent a note to our bitcoin brief uh topic in our telegram chat and said hey i want to talk about
• 41:25
  this tomorrow when we get to write the newsletter like this is one of the things we're gonna cover
• 41:29
  um so i'll do that and i'll do like anywhere from five to ten links and then morning morning of it's
• 41:35
  like okay pull up all the links all the emails i forwarded to you about stuff i want to cover
• 41:39
  and let's, I want you to, based off of the engagement
• 41:43
  that we've gotten in the newsletter in the past,
• 41:45
  you have access to that data on the back end of our CMS,
• 41:49
  like structure the newsletter in a way
• 41:51
  that we'll get the most engagement.
• 41:53
  But like, so we're filtering,
• 41:55
  I'm definitely covering these topics.
• 41:58
  Machine, you know, based off the topics
• 42:01
  we want to talk about,
• 42:02
  which is going to resonate the most with the audience
• 42:05
  and what they may deem most important.
• 42:07
  So like we have a lead story and then signal stories.
• 42:09
  So then it comes back to me, it's like,
• 42:11
  I think this should be the lead today,
• 42:13
  and these should be the signal stories,
• 42:14
  and here's all I'm thinking about framing it.
• 42:15
  And then I'll be like, okay,
• 42:17
  I understand why you're framing it this way,
• 42:18
  but let's tweak this, that.
• 42:19
  And I talk for like 10 minutes, like, okay,
• 42:22
  here's what I wanna cover frame.
• 42:23
  And then it's like, okay, I think we're at a good spot.
• 42:26
  I like the lead, I like the signal stories,
• 42:27
  like, let's go right.
• 42:29
  And so that puts together a draft,
• 42:31
  gets in the back end of our ghost CMS,
• 42:32
  and I read it twice, and then get final edits,
• 42:35
  like, okay, you messed up here.
• 42:36
  And then we hit send.
• 42:38
  And everybody's like, oh, you're not writing anymore.
• 42:39
  You're going to lose that skill.
• 42:42
  And I thought that for the longest time.
• 42:44
  I actually shied away from using Claude for writing for a while.
• 42:48
  But now I feel more comfortable for two reasons, one of which is the company brain is there.
• 42:51
  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.
• 43:04
  and it's able to inject that based off of stuff that we've talked about on the show and written
• 43:09
  when I was still manually writing in years past.
• 43:13
  The second thing is I had a conversation with somebody you know,
• 43:17
  we're not going to dox him on the show.
• 43:19
  And he completely changed my mind because people were worried,
• 43:21
  like, we're going to use the art of writing.
• 43:23
  I do still, I do write, I do type.
• 43:25
  I tell people, like, I don't type in there.
• 43:26
  I do sometimes.
• 43:27
  I do still write handwritten notes.
• 43:29
  I like that art.
• 43:30
  It's an art form that should never die.
• 43:32
  But he described it to me.
• 43:34
  He's like, we're basically just returning to the era of the scribe.
• 43:38
  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.
• 43:57
  And so what you do is you pretend like you're Napoleon Bonaparte.
• 44:01
  Oh, my God.
• 44:01
  You took it out of my mind.
• 44:03
  I was just about to say this.
• 44:04
  Right.
• 44:04
  So like,
• 44:05
  it's like after a day of battle,
• 44:06
  you get back to your war tent and you have like 10 scribes,
• 44:09
  one for munitions,
• 44:11
  replenishments,
• 44:11
  one for like war philosophy,
• 44:13
  like,
• 44:13
  ah,
• 44:13
  one for strategy.
• 44:14
  Like,
• 44:14
  here's where we messed up today.
• 44:16
  And you just talk to,
• 44:18
  you spin up a bunch of sessions and each session is an individual scribe that you give a bunch of context to.
• 44:24
  Yep.
• 44:24
  And it forces you to think from first principles and really articulate what you're trying to get out there.
• 44:29
  That's so funny.
• 44:30
  Bitcoiners,
• 44:30
  we all just like come to the same conclusions independently.
• 44:33
  Have you read Napoleon's biography? No. Oh, my gosh. OK. Andrew Roberts, Napoleon, a life.
• 44:39
  Best book I've read in a long time. Just incredible. I think about this all the time.
• 44:49
  Napoleon was like the most incredible human I've ever read about. He would do this. He would go
• 44:55
  back. He would triple dictate. He would be able to dictate faster than his scribes could write
• 45:00
  things down. And so he was one of the only people in recorded history that had this ability where he
• 45:07
  could do exactly what you said. He could dictate, tend to, it's similar to a grandmaster chess
• 45:13
  player who goes and plays 20 different games simultaneously and comes back and he can remember
• 45:18
  the context for the moves he's planning. Napoleon would do the same thing with writing these really
• 45:23
  just incredibly detailed and important letters to all the different world leaders, all of his
• 45:30
  different troops. It's crazy the breadth of what he was able to cover. But yeah, he would go back
• 45:36
  to the tent. And after a day of the most intense fighting in documented history, he would then go
• 45:42
  and dictate a letter on the importance of building a local bridge in a rural municipality in France,
• 45:47
  and then follow that up with a letter on the need for a girls education academy, because there
• 45:53
  really isn't one in this certain area of Paris. And then he'd go on to another one and dictate
• 45:58
  something about, you know, preparing his army for invasions in Russia. I mean, it was just
• 46:04
  incredible how he's able to do this. And I do think that that is what these agents allow us to do
• 46:10
  is multiply human agency. And that is the good timeline. The good timeline is that the best
• 46:16
  aspects of human greatness, achievement, and will and vitality are multiplied. And I feel that
• 46:25
  happening when I use this.
• 46:28
  But I do think it is something to be really cognizant
• 46:31
  of how you're using the tools.
• 46:32
  Like if you're using it in this dictation sense
• 46:36
  where you are able, when I'm using it,
• 46:40
  you know, and dictating to it,
• 46:42
  I can say so much more than I could possibly type.
• 46:45
  Because I can just talk forever.
• 46:47
  All of us can yap.
• 46:49
  Typing can be exhausting.
• 46:51
  And I do-
• 46:52
  It's slow, I type slower than I think.
• 46:54
  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.
• 47:22
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• 47:30
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• 47:35
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• 48:48
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• 49:05
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• 49:22
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• 50:02
  What's the rate of adoption of AI tools outside of BPI in the city? Is it big or is it?
• 50:07
  I expected it would be a lot higher than it is.
• 50:11
  Well, I have this theory that Bitcoiners are just like early adopters to all this stuff.
• 50:15
  This is what I was just thinking.
• 50:16
  Every time I talk to a Bitcoiner about this stuff, they have some crazy workflow.
• 50:22
  Because we just lean into new technology.
• 50:25
  And I mean, I've talked about this with like Thorn and Galaxy and Skyler on the design stuff.
• 50:30
  Like every Bitcoiner I know at all these different places in the industry or different types of jobs or skill sets.
• 50:37
  Like all of us have independently come up with crazy interesting ways to use this stuff.
• 50:43
  When I talk to people at traditional think tanks, like they're not, this isn't even on their radar.
• 50:49
  You know, there's just like an institutional inertia for a lot of these more legacy institutions.
• 50:55
  I think this is true.
• 50:57
  You know, Zach Shapiro, our head of policy, he's finding this at the law firm level.
• 51:00
  You know, he's.
• 51:03
  He's beating the drum.
• 51:04
  I mean, he's going out on the BPI policy hour,
• 51:06
  I feel like has been like, Zach, like,
• 51:08
  like lawyers, you better start vibe coding.
• 51:10
  You better start using this.
• 51:11
  Well, he wrote an article that went viral.
• 51:13
  And then like, he, from that had so many attorneys
• 51:16
  reach out to him that are, you know, at major law firms.
• 51:21
  And they're just so frustrated.
• 51:24
  I dealt with this.
• 51:25
  It was frustrating for me in 2022, 2023,
• 51:29
  when I was working at a firm here in DC,
• 51:33
  of just how hard it was to use any of the tools
• 51:37
  in the way that they're meant to be used.
• 51:39
  And that was when the tools weren't even that capable.
• 51:43
  You know, like we couldn't even access it on our laptop.
• 51:46
  Now they have some mediocre tools,
• 51:49
  but it's all sort of like baked in stuff,
• 51:52
  like Westlaw AI and stuff like that.
• 51:55
  And Zach has done a great job of just saying,
• 51:57
  no, you need to just integrate it top to bottom
• 52:01
  and you will be able to provide professional services
• 52:04
  You know, one-tenth the cost and twice the quality.
• 52:08
  And I think that has really surprised people at what he's been able to pull off.
• 52:13
  And then from that, I've met lots of other...
• 52:17
  It seems like what's happening is there's lots of senior associates or young partners that are breaking off from law firms.
• 52:25
  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.
• 52:34
  and keep all the money and keep all the money yeah um so well this is cool to see i mean this
• 52:41
  dovetails into an important point that we definitely should discuss which is like policy
• 52:46
  around ai like as we're describing it is incredibly powerful and i think it's incredibly
• 52:53
  important to make sure that we're able to utilize these tools in the way that
• 52:58
  we know we can moving forward.
• 53:01
  And so like policy around AI,
• 53:03
  whether it pertains to the models you can access
• 53:06
  and the energy debate around how those models are being trained
• 53:12
  and how the inference is being delivered is extremely important.
• 53:15
  And it seems pretty chaotic right now.
• 53:18
  It's very chaotic.
• 53:19
  I constantly think about what we did with nuclear energy, right?
• 53:24
  We invented basically unlimited energy.
• 53:28
  And then we banned it and built enough weapons to blow up the world many times over.
• 53:33
  I mean, we basically did the absolute worst thing possible with that technology.
• 53:38
  And I'm really, really concerned we're going to do the same thing.
• 53:42
  It took us about 50 years to get back to a semblance of sanity and nuclear policy.
• 53:46
  Yeah.
• 53:47
  And honestly, we're really far from it.
• 53:48
  The NRC has done an unbelievable amount of damage on the nuclear energy, on the nuclear industry.
• 53:55
  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.
• 54:06
  I can't wait for America to build out nuclear under this new leadership of a nuclear regulatory committee.
• 54:12
  I mean, people were just like patting themselves on the back.
• 54:15
  The people in Congress are super happy with it.
• 54:17
  The industry loved it.
• 54:18
  And it killed all the progress.
• 54:21
  It just became filled with people.
• 54:24
  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.
• 54:34
  We stopped it in every way we could.
• 54:36
  It's not going to save anyone.
• 54:39
  It's very funny.
• 54:41
  So point being, I'm really concerned that we're going to go to the same place with AI.
• 54:46
  the government just the nature of the institution struggles so hard with understanding exponentials
• 54:55
  or understanding just reasoning about existential risk I feel like is this way to just like one
• 55:05
  shot the government you know you have someone like in during COVID lockdowns right you have
• 55:12
  someone like Trump, who in theory is pro-freedom, pro-innovation, pro-small businesses,
• 55:20
  et cetera. They said, okay, there's a risk here that this could be some sort of major catastrophe.
• 55:28
  We're just going to shut everything down indefinitely. Print a bunch of money.
• 55:33
  Print infinite money. They just can't reason about when someone says, oh, this is existential.
• 55:39
  like just logic goes out the window we saw it with nuclear we saw it with the pandemic we saw it
• 55:44
  we're potentially seeing it now with ai i do think that the administration the current administration
• 55:51
  is somewhat inoculated to restricting ai but it is we're still at the very early innings
• 56:01
  how many people have died from ai like we haven't had a major catastrophe i think that inevitably
• 56:08
  like any technology, you know, you invent ships, there's going to be shipwrecks, you invent AI,
• 56:14
  some people will use it as a tool for bad things or accidentally use it to cause some sort of harm.
• 56:22
  I guess my point is, we are seeing pretty strong calls for heavy regulation of this technology
• 56:29
  before we've even seen any of those, you know, misuses or harms manifest.
• 56:38
  Or on the other side, on the positive side, explore the full potential of it.
• 56:41
  Yeah, or explore the full potential of it.
• 56:43
  And so I'm just worried that without someone explaining in clear terms the optimistic case for human flourishing with AI,
• 56:55
  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,
• 57:07
  that you're going to just, you know,
• 57:11
  go down a pretty dark path of you'll get surveilled,
• 57:15
  closed, permissioned, AI fiefdoms.
• 57:20
  You know, there are people in the administration
• 57:23
  that defend open source,
• 57:26
  but is that going to stand up over time
• 57:28
  if we have open source that's at the capability of Fable
• 57:31
  or five times better than Fable?
• 57:34
  I really hope so.
• 57:35
  It has to, in my mind,
• 57:36
  and for us to have a free society.
• 57:40
  But there's strange winds blowing in DC
• 57:43
  and I feel like there's a lot more money coming in
• 57:46
  on the restrict side.
• 57:48
  What's whispering in these winds?
• 57:49
  Yeah, I mean, just one example.
• 57:52
  Trump's, one of Trump's like ground game lieutenants,
• 57:59
  her name is escaping me now, I think it's Lisa Kremer.
• 58:03
  She used to, she ran like the Stop the Steal
• 58:06
  grassroots campaign for the 2020 election
• 58:11
  and the dispute over that.
• 58:14
  She is now being funded by effective altruists.
• 58:16
  Oh gosh.
• 58:17
  To run a new campaign called Humans First,
• 58:20
  which is like a MAGA aligned anti-AI.
• 58:25
  Populist anti-AI.
• 58:27
  Yeah, populist AI.
• 58:28
  So I will say that the doomers,
• 58:31
  The people that want to paint this pessimistic view of AI, they are very, very savvy about how to play in the conversation.
• 58:42
  The frontier model providers themselves.
• 58:44
  I mean, I think OpenAI is sort of backed away from it.
• 58:48
  It seems like Dario and Anthropic are leaning into it.
• 58:50
  And one has to wonder, view their marketing or how they're positioning things with a lens of skepticism,
• 58:57
  because it's an easy way for them to get a regulatory mode,
• 58:59
  which if you're following economic incentives
• 59:03
  is probably something they want at the end of the day.
• 59:05
  It's really difficult to actually figure out motives.
• 59:10
  And that is what's difficult about all of this.
• 59:14
  I do think there are some people
• 59:15
  that genuinely think AI is dangerous.
• 59:18
  Paperclip problems.
• 59:18
  And yeah, we're going to get paperclipped
• 59:20
  and that they are not doing this.
• 59:23
  Yudkowsky is not seeking regulatory capture.
• 59:25
  Gagowski genuinely from the bottom of his heart
• 59:28
  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
• 59:41
  are all, it is a really strange set of bedfellows of people that are pushing in the same direction.
• 59:48
  You know, you start to think through it, you have foreign influence, right? Strategic adversaries,
• 59:52
  of course, they want to undermine the use of the technology. You have, let's say, radical
• 59:57
  environmentalists, people that want to de-develop civilizations. Yeah, Malthusian. You have
• 1:00:04
  economic populists that have legitimate concerns about job displacement, and they're confused about
• 1:00:10
  where they're going to fit into all this. You have people that are just your classic run-of-the-mill
• 1:00:18
  socialist, you know, Marxist type people that generally believe that all this should be
• 1:00:23
  redistributed um you have the national security hawks that think only the government should have
• 1:00:29
  access to technology and we need to restrict it to just a few bureaucrats um then you have
• 1:00:37
  like the effective altruist you have the incumbents uh that are playing for the frontier regulatory
• 1:00:44
  capture game like all of these people are angling in a similar direction and sort of rowing in the
• 1:00:50
  same boat. I don't even think they're working together. But it is just this weird thing that
• 1:00:55
  we haven't really seen with any other. Typically, you have like, pretty strong set of voices on both
• 1:01:02
  sides. This is sort of a weird place where people that in no other scenario, would it be sort of
• 1:01:08
  rowing in the same direction, are all for one reason or another, lining up. And I'm genuinely,
• 1:01:16
  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.
• 1:01:28
  You know, it was 2023 when Dario was testifying in the Senate that open source AI is headed down a very dangerous path.
• 1:01:38
  That was three years ago.
• 1:01:40
  um so i i just think at the end of the day it would be just terrible if we're the ones that
• 1:01:50
  are getting the short end of the stick again as a result of all of this um and that's why
• 1:01:56
  going back to the beginning of the conversation dc is going to be very very important for the next
• 1:02:01
  10 years i mean my ability to predict what's going to happen is just so low i just it's all
• 1:02:07
  bets are off on what's going to happen with the rate of progress but on the policy front there are
• 1:02:14
  dark winds blowing in dc so i got a comment and then a follow-up yeah comment is uh comparing uh
• 1:02:22
  open ai strategy to anthropic is actually pretty funny because sam was just like you want five
• 1:02:26
  percent of the company we'll just give you we're not gonna we're not gonna fear monger we'll just
• 1:02:32
  give you five percent give us yeah we'll just cut you give us the moat cut you in yeah interesting
• 1:02:36
  strategy. Yeah. Yeah. So that's the comment follow up. Give the optimistic view. I feel like
• 1:02:41
  a lot of the, a lot of the conversation is focused on the pessimistic view and defending against that
• 1:02:47
  pessimistic view and not enough is focused on what is the optimistic outcome? What is the optimistic
• 1:02:53
  path? What could potentially happen in the future that, that many people will look back on and be
• 1:02:59
  like, wow, that was actually massively beneficial for me as an individual in society at large.
• 1:03:03
  Yeah, I think that the optimistic view is a proliferation of this technology and our ability to achieve even greater heights of human achievement.
• 1:03:15
  And what that looks like is broad.
• 1:03:19
  It has so many different ways that I see this going, whether it be for health care or education.
• 1:03:25
  but I do think that America has this incredible tradition of saying, we're going to experiment.
• 1:03:33
  We are going to embrace a new technology before everyone else. And we're going to do it in a way
• 1:03:39
  that preserves freedom, preserves privacy, preserves autonomy. And what that looks like
• 1:03:44
  for AI is again, choosing to lead the world and a rising tide lifts all boats. I think that if
• 1:03:51
  it's done correctly, that the people that have been left out of the economy in rural America that
• 1:03:58
  have just been hit one thing after another with losing jobs overseas, just being left out,
• 1:04:05
  having brain drain to metropolitan areas, I think those people stand to benefit an incredible amount
• 1:04:11
  because of the benefits of energy production that we're going to need to build this stuff out.
• 1:04:19
  and there will be economic benefits for those people.
• 1:04:22
  But I think really the upside in my mind is
• 1:04:27
  it does allow for an unprecedented amount of human agency.
• 1:04:31
  And this is only if we have
• 1:04:35
  AI that is free in the sense of what advice it can give you.
• 1:04:41
  And is it going to genuinely do be an extension of your will?
• 1:04:45
  or is it going to restrict your ability to operate?
• 1:04:50
  So the Doomer case is we're going to surveil everything you say,
• 1:04:55
  everything you ask, and if you have a tough question,
• 1:04:57
  then we're going to tell you the party line.
• 1:04:59
  The optimistic scenario is we're going to give you an AI
• 1:05:03
  that is aligned with your interest,
• 1:05:05
  that wants you to maximize your human capability.
• 1:05:09
  And the possibilities for our species, I think,
• 1:05:14
  or even like still underexplored.
• 1:05:17
  Our education system is terrible, absolutely terrible.
• 1:05:20
  I went through a public education
• 1:05:22
  and I feel like I'm probably 10% developed
• 1:05:27
  to what I could have come out of.
• 1:05:30
  Like you look back to the education systems
• 1:05:32
  of like ancient Rome and Greece and the Trivium
• 1:05:35
  and like how rigorous they are
• 1:05:36
  and how the people that came out of those,
• 1:05:40
  I think that we can have access to like the true
• 1:05:45
  great heights of civilization.
• 1:05:47
  Like Socrates being your teacher, like Alexander the Great.
• 1:05:50
  Yeah, having like, you know, I mean,
• 1:05:54
  I think about this all the time,
• 1:05:55
  but I think that each human has so much
• 1:06:00
  under cultivated capability for creation.
• 1:06:05
  And I really see this as there's a distinction
• 1:06:08
  between consumption and creation.
• 1:06:10
  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.
• 1:06:28
  And that is a dark path.
• 1:06:29
  The good path is we are all empowered to self-create in ways that is, you know, difficult to imagine.
• 1:06:40
  But each one of us has latent capabilities, I think.
• 1:06:46
  You know, I took up sort of as a side hobby.
• 1:06:48
  I took up painting a couple years ago.
• 1:06:51
  I got into art history.
• 1:06:53
  I like this.
• 1:06:53
  And then I started drawing.
• 1:06:55
  And then I said, drawing, come on.
• 1:06:57
  Like the real skill is painting.
• 1:06:58
  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
• 1:07:14
  to find a painting instructor, used to serve at the academy in Florence, and I took online lessons
• 1:07:22
  from him. He was fantastic. Steven Bauman, he's awesome. I highly recommend.
• 1:07:26
  um and then i think i need a connor brown original in my office yeah well i'm working maybe we can
• 1:07:33
  work on a side commission but um this is just like a microcosm right this was only possible
• 1:07:40
  because of the internet the ability to reduce the cost of incredible education now what does it look
• 1:07:47
  like when you multiply that to direct feedback from these agentic systems, right, that have the
• 1:07:57
  ability to provide customized feedback. One of the best things for improving my painting abilities
• 1:08:04
  has been I'll get an hour-long call with a guy who is a fantastic painter, and he'll review my work
• 1:08:13
  from the past month, provide some feedback,
• 1:08:15
  he'll draw on it.
• 1:08:17
  And that is, that hour of my month
• 1:08:21
  is probably responsible for 70% of my mental improvement.
• 1:08:25
  You know, learning a skill is partially
• 1:08:28
  just like learning the motor skills,
• 1:08:29
  but it's mostly-
• 1:08:30
  Having an expert come correct you.
• 1:08:31
  Yeah, and the mental heuristics, right?
• 1:08:34
  Like this thing you didn't even know you were doing wrong.
• 1:08:36
  And you have an expert like, oh,
• 1:08:37
  looking over your shoulder like, do this,
• 1:08:39
  don't do it that way, like shift this way, boom.
• 1:08:41
  Yeah, yeah.
• 1:08:43
  Pulls up, you know, Photoshop and paints over it and says like, oh, your your value structure here is wrong.
• 1:08:50
  Like this area of the face is way too dark.
• 1:08:52
  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.
• 1:09:03
  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.
• 1:09:09
  You know, it's like, well, technically you're standing too close to paintings.
• 1:09:12
  You have to walk away eight feet, take a couple of seconds and then walk back.
• 1:09:17
  And then you sort of can your eye like adjust.
• 1:09:19
  Yeah.
• 1:09:20
  All these sort of small things.
• 1:09:22
  Point being, that's one hour a month and it's expensive.
• 1:09:25
  And even then, it's incredible to have that access.
• 1:09:28
  This is just one way in which, you know, you can imagine a great AI teacher is available 24 seven to provide customized feedback.
• 1:09:38
  and provide those insights constantly.
• 1:09:41
  And so, again, you're unlocking these new heights
• 1:09:45
  of human achievement and creation.
• 1:09:46
  And I think what I struggle with
• 1:09:50
  and what everyone is struggling with
• 1:09:52
  is the algorithmic consumption complex
• 1:09:56
  that just gets you in the doom scroll forever.
• 1:10:00
  And the optimistic view is you have agents
• 1:10:03
  that are acting in your own interests.
• 1:10:05
  You have freedom on the technology.
• 1:10:08
  you can select it for yourself and you can choose
• 1:10:13
  to use the technology in a way that sort of makes you
• 1:10:15
  the best version of yourself.
• 1:10:18
  That's just one example, you know?
• 1:10:20
  I see this across every sector.
• 1:10:23
  And also filling in just like more time to self cultivate.
• 1:10:28
  Like the great gentlemen scholars of yore,
• 1:10:31
  you know, they were able to do that
• 1:10:32
  because a lot of them had been gifted like massive estates
• 1:10:35
  and had people that freed up their time
• 1:10:38
  to pursue new creative endeavors and academic endeavors
• 1:10:41
  and catalog every single insect
• 1:10:43
  that had ever been found in their local area.
• 1:10:45
  Like they were freed up with material wealth
• 1:10:50
  to do those really cool human endeavors.
• 1:10:53
  And I think that the optimistic scenario
• 1:10:57
  is that we are gonna see the same thing.
• 1:10:59
  We can see the same thing.
• 1:11:01
  And then we can-
• 1:11:02
  Come back to your war tent and-
• 1:11:03
  Go back to your war tent.
• 1:11:04
  orate to your scribes.
• 1:11:06
  Like, here's what I learned out there.
• 1:11:07
  Here's what I want to work on.
• 1:11:08
  Yeah.
• 1:11:08
  It's funny.
• 1:11:09
  Like, I've taken up gardening.
• 1:11:10
  Good for you.
• 1:11:11
  I want to take up gardening.
• 1:11:13
  I don't have a...
• 1:11:14
  I'm in a pod dweller right now.
• 1:11:16
  You're a pod dweller.
• 1:11:16
  You got to get out of the pod, brother.
• 1:11:18
  I was a pod dweller for a long time.
• 1:11:20
  But it's good.
• 1:11:20
  You like it?
• 1:11:21
  I mean, I'm just getting...
• 1:11:22
  Like, we moved into this new house.
• 1:11:24
  It's a beautiful 112-year-old property.
• 1:11:27
  So it's a nice stone old building.
• 1:11:30
  Good for you.
• 1:11:30
  Pre-Federal Reserve Act.
• 1:11:33
  So we've got a nice English garden in the background.
• 1:11:36
  We're the fifth family to ever live in this house.
• 1:11:39
  And so I feel a duty to the property to treat it well.
• 1:11:42
  And so I'm beginning to understand the nature of the landscaping.
• 1:11:47
  You're a steward.
• 1:11:47
  Yes.
• 1:11:48
  We can all be stewards.
• 1:11:49
  Yes.
• 1:11:49
  Yes.
• 1:11:50
  I'm a steward of the land.
• 1:11:51
  It is our house.
• 1:11:52
  We own it.
• 1:11:53
  But it is a property that when our kids are up and they're out of the house, maybe they'll buy it.
• 1:11:57
  Maybe there was one family that bequeathed it to their children.
• 1:12:01
  so they got two generations in that house but who knows but for the time being a mistake you gotta
• 1:12:05
  view this house is bigger than our family it's a it's a property that we have to steward is it a
• 1:12:10
  lot of upkeep because of its historic nature i mean it's it's strong good bones okay good bones
• 1:12:15
  yeah are you gonna get a physical clanker to walk around and help you i don't know and i imagine
• 1:12:21
  eventually yes i don't think the physical clankers are uh dexterous dexterous dexterous enough or
• 1:12:29
  I don't know. I've seen some crazy hand demos.
• 1:12:31
  Yeah, but like getting up the steps and all that, I'm not sure if they're there yet.
• 1:12:34
  Oh, they can get up steps.
• 1:12:35
  Okay.
• 1:12:36
  You think Optimus can't get up steps right now?
• 1:12:38
  I don't know. I'm not sure.
• 1:12:39
  Yeah.
• 1:12:40
  But do you want to buy the first iteration or you want to wait like two generations?
• 1:12:42
  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.
• 1:12:52
  Yeah.
• 1:12:53
  Never.
• 1:12:53
  Yeah.
• 1:12:54
  Like I won't get a room to vacuum for that reason.
• 1:12:56
  You know, if I get to like run my own, you know, if I get to choose what software goes on there, I might.
• 1:13:04
  You get to build it.
• 1:13:04
  I might.
• 1:13:05
  You could use the models to build the software to go on there.
• 1:13:07
  Yeah.
• 1:13:08
  I mean, I would still have some like really weird concerns about it.
• 1:13:13
  Just like the idea of having some robotic entity walking around my home.
• 1:13:19
  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.
• 1:13:32
  And the government.
• 1:13:33
  And the government.
• 1:13:34
  Yeah.
• 1:13:34
  Yeah, exactly.
• 1:13:38
  Yeah, it'd be like a hardware wallet or something, right?
• 1:13:40
  I want to know the firmware.
• 1:13:43
  I want to, like, feel really good about what I'm using.
• 1:13:46
  Yeah.
• 1:13:47
  So, very important.
• 1:13:49
  Very important stuff.
• 1:13:50
  And on a positive note, we had an American-made open weight model released this week.
• 1:13:58
  Yeah, Inkling.
• 1:14:00
  Very interesting.
• 1:14:00
  Have you used it?
• 1:14:01
  Not yet, no.
• 1:14:02
  It just came out yesterday.
• 1:14:03
  Yeah.
• 1:14:03
  Yeah.
• 1:14:06
  I'm excited by that.
• 1:14:09
  I hope that it keeps going in that direction.
• 1:14:11
  You know, it seems like every company starts off and they say, oh, we're the open source company.
• 1:14:18
  We're open AI.
• 1:14:19
  Open source is at the core of what we do.
• 1:14:21
  We're a nonprofit.
• 1:14:22
  We're going to, you know, then Grok was open source.
• 1:14:26
  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
• 1:14:38
  You have Llama and now Spark is closed source.
• 1:14:41
  Like I do hope that we have someone who is just willing
• 1:14:45
  to put the frontier open source and publish it.
• 1:14:52
  We'll see.
• 1:14:53
  I don't really know what to expect from the company.
• 1:14:55
  It looks like it's like a little bit behind the frontier.
• 1:14:58
  So we can't live in the world,
• 1:15:01
  the world where China decides
• 1:15:02
  they're gonna be the open source leader
• 1:15:04
  and all the American labs just sort of close up.
• 1:15:06
  It seems insane to me.
• 1:15:07
  Oh my God, such a strategic blunder for the US
• 1:15:12
  if we end up restricting open source
• 1:15:17
  and then the entire world just downloads
• 1:15:19
  China's open source weights.
• 1:15:23
  Like think of the strategic benefit you can give a country
• 1:15:28
  if the entire world is building on your open source stack,
• 1:15:31
  it is way deeper than,
• 1:15:33
  oh, it's not gonna talk about Tiananmen Square.
• 1:15:35
  Okay, that's not, that's just kind of like,
• 1:15:38
  you know, a parlor trick or something.
• 1:15:40
  What really is at stake is China creates
• 1:15:43
  a best in class open source model.
• 1:15:46
  It's better than anyone else can put out.
• 1:15:48
  It's cheaper and it somehow is really, really good
• 1:15:54
  at programming for Huawei Ascend chips
• 1:15:56
  and terrible at using Nvidia chips.
• 1:15:59
  You know, it's just like, it makes these little tweaks
• 1:16:01
  that each one incrementally actually really helps
• 1:16:04
  China's strategic position.
• 1:16:06
  And of course they would do that.
• 1:16:08
  I mean, the soft power you get
• 1:16:10
  of leading the world's open source models
• 1:16:12
  and having those just be slightly better
• 1:16:14
  at doing things in your interest
• 1:16:16
  and slightly shittier at doing things
• 1:16:18
  that are against your interest, huge, huge.
• 1:16:23
  huge um do you think anybody in the administration realizes this no i mean i don't i mean we're we're
• 1:16:30
  still so early in the conversation but somebody clip it and send it to them yeah if someone could
• 1:16:35
  clip that send it um i would say send it to sax he's not there anymore send it to lutnik lutnik
• 1:16:42
  would be a good person primary sex partner craft you've been on this show get it to him get in his
• 1:16:46
  hands i'll text you um bringing us back to bitcoin but combining the two i mean
• 1:16:52
  been a thesis within Bitcoin for a while, the abundant future that's going to be unleashed by
• 1:16:58
  AI is going to make the need for a sound digital distributed currency like Bitcoin even stronger.
• 1:17:07
  Are you more or less convinced of that? Oh, absolutely more convinced. But it goes back to
• 1:17:13
  what type of systems are we going to be allowed to have or do we have? Right. Because I do think
• 1:17:19
  that capable open source systems that are trained in a neutral way are going to prefer Bitcoin.
• 1:17:24
  Our research has shown that if you just query them as they get more capable, they generally
• 1:17:31
  prefer this is across different models. They prefer Bitcoin and stable coins. So I think that
• 1:17:37
  in a world where people aren't putting their thumb on the scale, then the possibilities for
• 1:17:42
  Bitcoin, its use in agentic commerce are just,
• 1:17:47
  it's hard to even imagine because agents are going to have
• 1:17:52
  so many fewer barriers in using this as everyday payment
• 1:17:57
  compared to humans.
• 1:17:59
  They're digitally native, Bitcoin's digitally native.
• 1:18:01
  It just is going to click for them.
• 1:18:06
  Nick Szabo wrote about the mental transaction costs
• 1:18:08
  and stuff, they don't have any of that stuff.
• 1:18:09
  So it's gonna be huge for them.
• 1:18:11
  And I think will be naturally adopted because how much Bitcoin content is in their training set?
• 1:18:16
  Like every rip you've ever recorded is somewhere in, you know, the training sets of the frontier models.
• 1:18:23
  Like GPT-3, one of the tokens was GMAX from Gregory Maxwell.
• 1:18:28
  He was actually one of the GPT-3 tokens.
• 1:18:31
  That's insane.
• 1:18:32
  And there was only like a small number of tokens.
• 1:18:34
  I forget.
• 1:18:34
  They only had like 20,000 unique tokens or something.
• 1:18:37
  So like Bitcoiners are prolific in our content output.
• 1:18:41
  Our arguments are right and are good and are consistent and appeal to machines.
• 1:18:49
  You know, it is a tech forward approach.
• 1:18:51
  So if we have open, permissionless, free AI, then I think that the implications for Bitcoin and its adoption are massive.
• 1:19:07
  but if we have a dystopian scenario where all we have are surveilled and controlled AI fiefdoms
• 1:19:15
  then it would not surprise me at all if the players start putting their thumb on the scale
• 1:19:22
  I almost I almost hesitated in releasing our AI research about how agents prefer Bitcoin
• 1:19:31
  because I know that many of the people in the frontier labs are, you know, socialist leaning
• 1:19:39
  or sort of anti-libertarian leaning. And one of them has his own shit coin. I would, I was, yeah,
• 1:19:46
  exactly. I was worried that just by releasing that, they might be like, oh, we need to like
• 1:19:52
  alter the training set because Claude likes Bitcoin. We can't have that going on.
• 1:19:56
  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.
• 1:20:09
  So, but if we are sort of in this like fiefdom endgame,
• 1:20:14
  which is easier to happen than people want to admit, I think,
• 1:20:19
  then they easily could say, great.
• 1:20:23
  So as part of our frontier testing
• 1:20:25
  for releasing a new model to public,
• 1:20:27
  it has to really like CBDCs.
• 1:20:30
  Or these preferred stable coins.
• 1:20:31
  Or these preferred stable coins.
• 1:20:34
  Running on the X402 protocol.
• 1:20:35
  Yeah.
• 1:20:36
  That's what you prefer.
• 1:20:37
  Yeah, exactly.
• 1:20:38
  So that's kind of where my mind is at, is we're going to have to make sure we get that scenario.
• 1:20:46
  Well, I think we could keep going for hours, but I know you have to get somewhere.
• 1:20:50
  I'm going to be back down here a lot.
• 1:20:51
  We'll do this more frequently.
• 1:20:52
  Yeah, I'm looking forward to it.
• 1:20:54
  We're going to have plenty to talk about.
• 1:20:55
  Yes, we are.
• 1:20:56
  Ten years.
• 1:20:56
  Ten years of very important things happening in the city.
• 1:20:59
  Yeah.
• 1:21:00
  All right.
• 1:21:00
  Peace and love, freaks.
• 1:21:01
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• 1:21:04
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• 1:21:08
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• 1:21:12
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• 1:21:19
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• 1:21:53
  Okay!