Speaker 1: I don't want to indulge in any of those games,
Speaker 1: but it is a communist holiday, and I do resent it.
Speaker 2: Okay, good.
Speaker 3: I agree. AI data centers waste millions of gallons of water.
Speaker 4: That's why Liquid Death and Garage Beer decided to team up.
Speaker 3: We want your pee to cool these data centers.
Speaker 2: It's the Ricochet Podcast with James Lilacs. That's me, Charles C.W. Cook,
Speaker 2: and Stephen Hayward. We're going to talk to Mark Mills
Speaker 2: about AI. Don't fear the future. Let's have ourselves a podcast.
Speaker 5: What's interesting about when you get far enough away from
Speaker 5: a time period that's quite distinct, I think there's always
Speaker 5: a lovely feeling associated with it. It's almost like you
Speaker 5: pave over all the trauma with, like, puppy dogs and
Speaker 5: ice cream.
Speaker 1: And the 80s was a.
Speaker 4: Brutal, brutal time for people.
Speaker 5: It was a f * * * ing mess. And, like,
Speaker 5: you know, people forget that it was, like, there was
Speaker 5: a tremendous strife, sociopolitical tensions everywhere. You know, we're still, like,
Speaker 5: pretty fresh off, like, a Cuban Missile Crisis, which is only, like, what, 15,
Speaker 5: 20 years before... So, you know, it's a tumultuous period,
Speaker 5: but you look back at it now, and you're like, oh, yeah,
Speaker 5: Top Gun, cocaine.
Speaker 1: There you go again.
Speaker 2: Welcome, everybody. It's the Ricochet Podcast, number 805. I'm James
Speaker 2: Lilacs in sunny Edina, Minnesota, or Edina, as the AI
Speaker 2: likes to pronounce it. Stephen Hayward in California. Charles C.W.
Speaker 2: Cook in Florida. Gentlemen, welcome. We are on the cusp
Speaker 2: of a holiday weekend here.
Speaker 3: All is great.
Speaker 2: Summer is winding down. The Minnesota State Fair is... the
Speaker 2: end of which signifies the end of summer, is having
Speaker 2: a bit of a controversy now because of the political
Speaker 2: nature of the seed art. Somebody put 8647 in seeds
Speaker 2: and then had red seeds underneath to indicate blood. There
Speaker 2: are seed art portraits of Minnesota martyrs like St.
Speaker 1: George Floyd.
Speaker 2: There is Donald Trump stuffed with beans or something. It's
Speaker 2: just so... appallingly banal that people can't feel the need
Speaker 2: to infuse their tiresome politics and shove it into everything
Speaker 2: and i wonder whether or not that the uh the
Speaker 2: seed art this year is being funded by ngos or
Speaker 2: non-profits i know that sounds like paranoia but stephen hayward
Speaker 2: friend actually has a a modest proposal on what to
Speaker 2: do uh with non-profits why don't you tell it to
Speaker 2: charles and myself.
Speaker 3: Well, first of all, James, about the seed art, I
Speaker 3: think we should counter it by spreading the rumor that
Speaker 3: they're all made with genetically modified seeds, right? Because that
Speaker 3: will cause a cognitive dissonance and all that.
Speaker 2: Precisely.
Speaker 3: Yeah, so, I mean, long story, but I had this
Speaker 3: crazy idea– not crazy, but it won't happen– that we
Speaker 3: should abolish the nonprofit sector. Now, I don't mean that literally,
Speaker 3: because you go back to Tocqueville, American voluntary civic organizations
Speaker 3: have always been part of America's DNA and what set
Speaker 3: us apart. It's a key part of American exceptionalism. But
Speaker 3: what I do think should be done is maybe we
Speaker 3: should think about ending the tax deductibility of contributions to
Speaker 3: the nonprofit sector. The reason I say that is the
Speaker 3: nonprofit sector, not all of it, not our local churches
Speaker 3: that we belong to, not the local Lions Club perhaps,
Speaker 3: but the sector itself has, like so many institutions, become
Speaker 3: thoroughly captured by the left. up to all kinds of mischief,
Speaker 3: and making claims. And this actually goes back at least
Speaker 3: 30 years now. They make claims that the nonprofit sector
Speaker 3: should be accorded the status of a formal stakeholder, including
Speaker 3: appointments to corporate boards and input to all public policy decisions.
Speaker 3: And I think this is insidious. And I thought, you know,
Speaker 3: if we got rid of the tax deductibility for it,
Speaker 3: it would clip the wings of, well– Let's start with
Speaker 3: a lot of private liberal arts colleges where a lot
Speaker 3: of alumni would quit giving their annual gifts if they
Speaker 3: couldn't deduct it on their taxes. So what's not to like?
Speaker 3: And it would also clip the wings a bit of
Speaker 3: some of the huge left-wing foundations, Ford, Rockefeller, Soros, for
Speaker 3: that matter, and Mellon Foundation and others. So I threw
Speaker 3: it out as a thought experiment, and it got a
Speaker 3: lot of buzz and controversy. And anyway, when I hear
Speaker 3: people talk about the nonprofit sector, it just gets my back.
Speaker 2: Charles, do you agree?
Speaker 4: I don't know.
Speaker 1: That's a remarkable change to our tax code and would
Speaker 1: restructure an enormous number of things. What I would like
Speaker 1: to see, which I think I do already have an
Speaker 1: opinion on, is the government using non-profits less. Now, that
Speaker 1: would be easy to affect. I mean, I'm thinking obviously,
Speaker 1: of California and homelessness charities, which seem to rake in
Speaker 1: billions of dollars while making the problem worse, or at
Speaker 1: least not making them better. That is full of all
Speaker 1: manner of ugly incentives. Whether I want to change the
Speaker 1: tax code to make the contributions from private actors to
Speaker 1: those non-profits illegal or treated... as any other contribution would be, rather?
Speaker 1: I don't know. I just have to think about that, Steve.
Speaker 3: Well, I mean, I just want a sort of brief rebuttal.
Speaker 3: Most people who throw $ 20 into the collection plate at
Speaker 3: their churches don't itemize. And there's quite a lot of
Speaker 3: data on this, that conservatives are actually more charitable than liberals.
Speaker 3: I mean, the famous story of Hillary Clinton deducting $ 1. 50
Speaker 3: for bills used underwear on their tax forms is very
Speaker 3: emblematic of the left. They want the government to do it.
Speaker 3: And that's why an awful lot of the nonprofit sector
Speaker 3: depends on government grants like the homeless industrial complex that
Speaker 3: you mentioned. And so I actually think that, you know,
Speaker 3: the sort of the good old Tocqueville style civil society
Speaker 3: stuff would go on just fine without a tax deduction
Speaker 3: for it. And, you know, I like to point out
Speaker 3: that the Medici's and the rest, they didn't support Florentine
Speaker 3: art for the tax deductions. And I think that people
Speaker 3: who are seriously interested in the arts can still support it.
Speaker 3: It's just that the taxpayers don't have to cross-subsidize it anymore.
Speaker 3: That's the more modest version of it. I wouldn't abolish nonprofits.
Speaker 3: That is a crazy idea. It would be cutting off
Speaker 3: your nose in spite of your face.
Speaker 2: You mentioned the Lions. I almost joined the Lions once,
Speaker 2: but there was a scheduling conflict. What they did was
Speaker 2: they cleaned up streets. They went places and they picked
Speaker 2: up trash. And then they also had drives to collect
Speaker 2: used eyeglasses, which would go to Africa. Wonderful bunch of people.
Speaker 2: What I want to do after I've won the lottery, win, say,
Speaker 2: $ 800 million in the lottery, I'm going to take $ 300
Speaker 2: million of that and I'm going to create the Lilacs Foundation.
Speaker 2: And I'm going to expressly staff it with as many Marxists, socialists,
Speaker 2: and collectivists as I possibly can. The reason being is
Speaker 2: that's the only way that I can assure that in
Speaker 2: two generations it will do something completely different. Like the
Speaker 2: Ford and the rest of them. If you set up
Speaker 2: a foundation dedicated to American society, all of a sudden
Speaker 2: in two generations, it's doing its best to ruin the country.
Speaker 2: So I'm going to try it from the other way
Speaker 2: and see how the institution works.
Speaker 1: James, you could also give them totally pointless, fruitless work
Speaker 1: to do, but pay them, thereby taking them out of society,
Speaker 1: trapping them, the golden handcuffs, and making sure they can't
Speaker 1: do any mischief whatsoever that affects anything that you care about.
Speaker 2: That would be a good idea, because the underutilization of
Speaker 2: these people leads them to do the stupidest, strangest things.
Speaker 2: There's a case of this mentally ill woman in the
Speaker 2: streets of New York who had stabbed two people, one
Speaker 2: to death, and she was going after the cops and
Speaker 2: was irrigated, and got the lettuce selling, and down she went.
Speaker 2: And there's a lot of nailing and wailing and gnashing
Speaker 2: about why didn't they shoot her in the arm, why
Speaker 2: didn't they shoot her in the leg, please. But what's
Speaker 2: interesting is the people who are defending the death of
Speaker 2: the young woman that she'd stabbed because she worked for
Speaker 2: the Bank of America and therefore she was part of
Speaker 2: the industrial capitalist complex. She was a vice president, for
Speaker 2: God's sakes. And there are people, legitimate people, actual people
Speaker 2: on Twitter saying, I'm not, you know, this is what
Speaker 2: we need to do more of. And it's a sign
Speaker 2: of how ethically reprehensible and morally vacuous that these people
Speaker 2: have become. This is the Luigi, this is the, you know,
Speaker 2: the Luigi Mangione thing. uh you know fan club this
Speaker 2: is this is them what constitutes a new set of
Speaker 2: ethics that we have to get used to if the
Speaker 2: revolution is going to come.
Speaker 1: But that woman had no idea who she was killing
Speaker 1: right no she didn't know whatsoever in effect that their
Speaker 1: endorsement leads to the position that we should have random
Speaker 1: mentally ill people running around manhattan with knives on the
Speaker 1: off chance they kill someone that they wouldn't have liked
Speaker 1: in the first place Exactly. And they tried to tase her,
Speaker 1: but she was too fat, which was really, really funny
Speaker 1: because that was the answer. And I saw this exchange
Speaker 1: where someone said, Well, it just shows how inhumane and
Speaker 1: barbaric our police are. Why didn't they tase it? Well,
Speaker 1: they did tase it. Well, why didn't it work? It's
Speaker 1: because she is huge.
Speaker 3: But I think it's actually worse than that, Charlie. I
Speaker 3: think we are back to what used to be part
Speaker 3: of the radical left decades ago, which was a sanctification
Speaker 3: of violence, a celebration of violence for its own sake.
Speaker 3: Which makes me come back to your opener, James, which is,
Speaker 3: you know, those seeds … look like they have sprouted
Speaker 3: into a really noxious wheat. It's not a strong enough
Speaker 3: metaphor for it, but you can see that those seeds
Speaker 3: are emblematic of something that's growing up and growing very fast,
Speaker 3: and it's very bad.
Speaker 2: Yeah, it is. I have a piece in National Review
Speaker 2: Online this week. My weekly column this weekend is about questions.
Speaker 2: Here's my job. Do I deserve stabbing? This is what
Speaker 2: I do for the company. Is this going to give
Speaker 2: me a stabbing? So you can pick that up on
Speaker 2: NRL if you like.
Speaker 1: I'll send you my answers to the questions.
Speaker 2: Oh, I've already answered them, believe me. I answered them
Speaker 2: in the voice of a 27-year-old DSA woman who is
Speaker 2: living in Brooklyn in a $ 1. 7 million apartment.
Speaker 1: So I don't get a say.
Speaker 2: No, the piece is written and it's done.
Speaker 1: No, I just thought I would read the piece and
Speaker 1: then I would send you my thoughts as to whether
Speaker 1: or not you deserve to be stabbed.
Speaker 3: Okay.
Speaker 2: I'm sure you've got some pull over there, Ben Hart. So, yes,
Speaker 2: you can do this if you wish. Two stories before
Speaker 2: we go to our guest. Do you want to talk
Speaker 2: about the passing of Gloria Steinem or the fact that
Speaker 2: the ballroom is going to be built?
Speaker 3: Well, a quick comment on the ballroom thing. It's a
Speaker 3: ridiculous case for the pleading of the plaintiff from the
Speaker 3: National Trust for Historic Preservation. Again, one of those nonprofits
Speaker 3: that's become a nuisance over the decades. And the complaint was, well,
Speaker 3: I'm aesthetically offended having to walk by the ballroom. Now,
Speaker 3: if being aesthetically offended at federal architecture is a legitimate
Speaker 3: cause of action– then I'm going to put retroactive lawsuits
Speaker 3: and flood the federal courts for every federal courthouse that's
Speaker 3: been built, just for starters.
Speaker 4: Absolutely.
Speaker 2: We have a class action suit over the FBI building
Speaker 2: in D.C.
Speaker 1: I have to say, I was completely perplexed by John Roberts.
Speaker 4: Yes.
Speaker 1: John Roberts is not the villain that many on the
Speaker 1: right think he is. But he is often a squish.
Speaker 1: And rarely so on standings. So, suddenly, he, what, becomes
Speaker 1: a standing dove? And also, I understand this is not
Speaker 1: the mainstream view, but I don't think that there's a
Speaker 1: case on the merits. I went back and I read
Speaker 1: the statute that Congress passed, which I don't think is
Speaker 1: a particularly good statute, and as usual, I would like
Speaker 1: Congress to do its job rather than delegate power. But
Speaker 1: it refers to improvements to the building. And so, I
Speaker 1: looked at what that word has meant historically in America,
Speaker 1: and this obviously counts as an improvement. They didn't take
Speaker 1: the building down. They removed a part of the building
Speaker 1: that had previously been an improvement, and they're improving it.
Speaker 1: How could that not count under this statute?
Speaker 4: Yeah.
Speaker 2: Well, it's because Trump is building it, period. Yes. And
Speaker 2: I don't believe they have any legal basis to get
Speaker 2: rid of the march, the arch that he's building. But
Speaker 2: if they could, they would, I'm sure. And whether or
Speaker 2: not that's going to be an aesthetic success, we will see. Well,
Speaker 2: such is the world. How about let's talk about the future?
Speaker 2: And now we welcome to the podcast Mark Mills, founder
Speaker 2: and executive director of the National Center for Energy Analytics,
Speaker 2: a contributing editor to the Manhattan Institute's City Journal, and
Speaker 2: author of The Cloud Revolution, How the Convergence of New
Speaker 2: Technologies Will Unleash the Next Economic Boom in a Roaring 2020s. Mark, welcome.
Speaker 2: It's been an interesting week for AI, has it not?
Speaker 2: I mean, we had four models, we had four AIs
Speaker 2: go down simultaneously, everybody thinking that they'd been nixed by
Speaker 2: some rogue other LLM that was out there killing at will.
Speaker 2: We had all these stories about hugging face experiments that seem, again,
Speaker 2: to summon up a dystopia happening beneath the surface of
Speaker 2: the placid computers with their blinking lights. We had a massive...
Speaker 2: massive outrage on Twitter, bots, social media, everywhere about AI
Speaker 2: food menus, which brought a new form of tryptophobia discussed
Speaker 2: to people. We're grappling with something that is barreling towards
Speaker 2: us very fast, or we feel like we're strapped to
Speaker 2: the front of a bullet train and we don't know
Speaker 2: the destination. So let's slow down. Let's ramp back the panic.
Speaker 2: You've been called the last optimist for AI. Okay. give
Speaker 2: us some more reasons why the people who are out
Speaker 2: there saying, I am not at all paid by China
Speaker 2: to oppose data centers. I just think they're bad because
Speaker 2: they use water. Calm us down here and tell us
Speaker 2: why we should still be optimistic.
Speaker 4: Well, you could take the position that humans are bad
Speaker 4: because they use water.
Speaker 2: Especially the golfers. Especially the golfers eating almonds. They're the worst.
Speaker 4: Well, if you really want to know the biggest offender
Speaker 4: for profligate water use, It's the RFS, Renewable Fuel Standards,
Speaker 4: and ethanol. Just not to digress into the rabbit hole
Speaker 4: of idiot standards for effectless policies, about 600-fold more water
Speaker 4: used per gallon of gasoline if you go ethanol than
Speaker 4: if you stick with just gasoline. 600-fold. That's an astonishing
Speaker 4: increase in water use and water waste. But I don't
Speaker 4: think I'm the last optimist, but I'm also not Pollyanna.
Speaker 4: I mean, I'm a realist. I've been in the investment world.
Speaker 4: I've been in the policy world. Reality will slap you
Speaker 4: upside the face if you pretend to ignore it. That's
Speaker 4: why we use the Philip K. Dick quote on our website,
Speaker 4: which is the great line that reality is that which
Speaker 4: still exists even when you ignore it.
Speaker 2: Well, using Philip K. Dick, of course, who believed in
Speaker 2: the valley behind everything else.
Speaker 4: It's perfect because he's a dystopian science fiction writer. And
Speaker 4: the only thing that makes good science fiction is dystopia. But,
Speaker 4: you know, that's why the stories sell.
Speaker 2: So no one's come to your door speaking Greek with
Speaker 2: a strange medallion. It's changed your life is what I
Speaker 2: want to know.
Speaker 3: Okay.
Speaker 4: Well, I would say that the roaring 2020s is happening.
Speaker 4: It took a couple of years to get rolling. I mean,
Speaker 4: when I wrote the book, It came out the end
Speaker 4: of 2021, really was rolling in January 2022, right before
Speaker 4: ChatGPT came out. And about a quarter of my books
Speaker 4: about AI, the rest is about the other technologies and
Speaker 4: the penumbra of the sort of the ecosystem that's changing
Speaker 4: the world. I mean, material science is a big deal.
Speaker 4: People ignore it because it's boring. What's happening in education
Speaker 4: is a big deal, not just from AI. You know,
Speaker 4: what's going on in discovery in medicine and biological sciences
Speaker 4: is huge. Lots of stuff going on. So I tried to...
Speaker 4: I tried to put a thread through my book, and
Speaker 4: the thread was, I think, the correct thread, and that's
Speaker 4: why it's called the cloud revolution, is that the infrastructure
Speaker 4: of the cloud writ large is the animating thread to
Speaker 4: all the revolutions that are underway, both good and bad,
Speaker 4: and that people's unhappiness is predicted and predictable. I mean,
Speaker 4: we are in another cycle of great disruption, but I
Speaker 4: will say this. Anybody who spends 10 minutes asking Claude
Speaker 4: or Gemini or any AI agent to search history and
Speaker 4: give you a summary of great disruptions. This is not
Speaker 4: the first time, it's not our first rodeo, but it's
Speaker 4: the first time in the living memory of pretty much
Speaker 4: everybody today, right? The last great disruption, I would argue,
Speaker 4: was the 1920s. That's why I use the roaring 2020s
Speaker 4: in terms of a confluence of huge changes in technology, society, politics.
Speaker 4: It was very, very similar to our era. And And
Speaker 4: then there are negative consequences. One of them was the
Speaker 4: creation of the Soviet Union. I mean, that's what, in
Speaker 4: a large measure, helped fuel the, you know, Karl Marx
Speaker 4: and the whole socialist framing and the creation of the
Speaker 4: Soviet Union was the disruptions that were underway. And I
Speaker 4: think if I were a pessimist, I would say I
Speaker 4: worry that we're seeing that movie replayed too.
Speaker 3: Mark, have you been surprised, as I have, at how
Speaker 3: rapidly the opposition to data centers has congealed, and in
Speaker 3: a bipartisan way? I mean, I'm having flashbacks to the
Speaker 3: anti-nuclear movements of the 70s, which... And maybe my memory
Speaker 3: is faulty, but it seemed like it took longer to
Speaker 3: take hold. It was mostly on the left, although it
Speaker 3: easily combined with old-fashioned middle-class nimbyism. And this has gone
Speaker 3: from zero to 60 in a tenth of the time
Speaker 3: the anti-nuclear movement did. And so I'm totally shocked. And
Speaker 3: you can see all the Republican politicians like Governor Abbott
Speaker 3: in Texas. lining up to say, oh, wait a minute,
Speaker 3: and this looks very bad to me. I mean, here's
Speaker 3: where I think Trump is right to say, if we
Speaker 3: want to be, you know, poor and behind the curve,
Speaker 3: let's block data centers. But so were you surprised at this?
Speaker 4: So you already triggered a lot of people by using
Speaker 4: the phrase, I think Trump is right. So let's just,
Speaker 4: let's leave that particular rabbit hole alone for a the
Speaker 4: importance of data center infrastructure are right. It is critical.
Speaker 4: It is a structural shift in our economy with all
Speaker 4: the things that animate people to be worried. And a
Speaker 4: lot of people have good reason to be worried about things.
Speaker 4: I mean, you know, that old saying, you may be paranoid,
Speaker 4: but the bullets are real. I mean, there are some
Speaker 4: people whose jobs are a threat, for sure. The jobs
Speaker 4: apocalypse narrative is demonstrably bunk, but there are people who
Speaker 4: will be negatively affected. You build big industrial facilities, and
Speaker 4: that's what a data center is. Jensen and Wine likes
Speaker 4: to use the expression AI factory. And it's actually a
Speaker 4: pretty good framing. It's a better framing than data center
Speaker 4: because there's a distinction between data centers that do AI
Speaker 4: and data centers that do what we're doing, which is
Speaker 4: record videos or buy things or shop or keep medical records.
Speaker 4: And that data management, that data processing is, as we
Speaker 4: all know, having tried AI, really different than using an
Speaker 4: AI agent to answer a question. But I am like you.
Speaker 4: I've used the analogy about the nuclear opposition deliberately because
Speaker 4: you and I are of a certain age. And as
Speaker 4: a young man, I was at the accident at Three
Speaker 4: Mile Island during the week of the accident and then
Speaker 4: spent the next, I guess, seven years of my life
Speaker 4: defending the virtues of nuclear energy. Obviously, unsuccessfully because the
Speaker 4: crazies killed the industry. The architecture of the debate is
Speaker 4: very similar. Apocalyptic fears, big utilities. There was a time
Speaker 4: when the left hated big utilities. Now they love them
Speaker 4: because they successfully co-opted them, basically. But they won that battle.
Speaker 4: They got to own them intellectually, if you like. And
Speaker 4: even to some extent legally by the mandates that are
Speaker 4: forced on. many utilities yeah but it is a little
Speaker 4: it is definitely faster i think i think the reason
Speaker 4: it's faster is that they they uh are it's the
Speaker 4: same people and organizations many of them and they honed
Speaker 4: their skills they honed the the techniques uh and the
Speaker 4: nuclear debates and so it was pretty fast then i
Speaker 4: mean i i When I came to the United States
Speaker 4: before Three Mile Island, nuclear energy was still very popular
Speaker 4: in a bipartisan way. It was the future, beating swords
Speaker 4: to plowshares, the peaceful atom, all this stuff. Nixon predicted 1,000
Speaker 4: reactors in reaction to the oil embargo of 1973 by
Speaker 4: the year 2000. We got to 100.
Speaker 3: It's close. Well, not bad for government work, yeah.
Speaker 4: But it is– It makes one suspicious. There's more to it.
Speaker 4: And I think the more to it is partly it's
Speaker 4: being fed by anxiety about what AI and social media,
Speaker 4: all that, and the antipathy, if not hate, for big
Speaker 4: tech and the coastal elites that's feeding into it. I
Speaker 4: have no doubt, I think, Elon Musk's research team on
Speaker 4: Exit reported hundreds of thousands of Chinese chatbots maliciously reinforcing
Speaker 4: negative stories on social media. I have no doubt that
Speaker 4: they're meddling.
Speaker 2: Okay.
Speaker 4: I mean, look, you'd be profoundly naive to think that Russia,
Speaker 4: Iran and China are not meddling in our politics and
Speaker 4: trying to animate discord. Similarly, when you build really big
Speaker 4: things near places where people haven't had big things built before,
Speaker 4: for which the benefits are generally remote, except for tax reductions.
Speaker 4: you get a lot of NIMBY. That's the nature of
Speaker 4: the beast.
Speaker 3: One other question to one particular aspect of this. I
Speaker 3: did just see a paper out this morning. I think
Speaker 3: I spotted it on the Social Science Research Network. I
Speaker 3: haven't read it yet, but it's a study that says
Speaker 3: there's really no evidence that data centers are driving up
Speaker 3: electricity prices. It's some kind of regression model, of course. Now,
Speaker 3: I remember one of your most interesting calculations, I think
Speaker 3: more than 20 years ago, if I remember this right,
Speaker 3: Back when we were still getting half of our electricity
Speaker 3: from coal in this country. And you had the calculation
Speaker 3: that every Google search generated, you know what, a quarter
Speaker 3: pound of carbon dioxide emissions, whatever it was. And only
Speaker 3: you do these kind of calculations that nobody else thinks about. And,
Speaker 3: of course, that has all changed with the changing electricity
Speaker 3: generation profile and natural gas and so forth. Uh, but
Speaker 3: it does seem to me that, um, uh, you know,
Speaker 3: here in California where they're not building a lot of
Speaker 3: data centers because our electricity is too expensive. Um, uh,
Speaker 3: you are seeing a lot of people who see rising
Speaker 3: electricity rates, which happening for secular reasons and say, Hey,
Speaker 3: I was just going to make it worse. But I
Speaker 3: think that's probably not true.
Speaker 2: Is it?
Speaker 4: Yeah. Well, your instincts as always are spot on. It's
Speaker 4: not true. The data don't show. In fact, uh, we,
Speaker 4: you know, NCEA, uh, we partnered with USC, your buddies
Speaker 4: at University of Southern California, to do a statistical analysis
Speaker 4: of the California ISO, that region, because there are a
Speaker 4: lot of data centers in California already. There are more
Speaker 4: being built, by the way, because sometimes you have no choice.
Speaker 4: It has to do with latency. You have to have
Speaker 4: the data exchange close to where you are. But there
Speaker 4: is a small impact of big data centers on wholesale
Speaker 4: congestion costs. So when you say that, you can just
Speaker 4: think about Any kind of traffic, data creates traffic, power
Speaker 4: creates traffic, congestion. But it doesn't correlate with any retail
Speaker 4: cost impacts. And the only correlation we have in the
Speaker 4: United States with higher electricity costs is the factless and
Speaker 4: ill-advised policies to jam solar and wind mandates down the
Speaker 4: throats of utilities and ratepayers. And what that's done, even
Speaker 4: though the sun is, quote, free when it's shining, is
Speaker 4: that the system operating costs to compensate for that raise
Speaker 4: overall costs of electricity, and they have. And that's been
Speaker 4: demonstrated over and over again. So now what's going on
Speaker 4: is the politicians conveniently can blame big tech for causing
Speaker 4: high rates. They caused, not big tech, but the politicians,
Speaker 4: by forcing policies onto utilities that lead to affirmatively higher
Speaker 4: costs to run the grids. Germany did the experiment. They
Speaker 4: tripled the cost of electricity by going further down, faster
Speaker 4: down the path that a lot of U.S. states are pursuing.
Speaker 4: So it's a convenient whipping horse, and the answer to
Speaker 4: that is simple, and I think that's already been solved
Speaker 4: in the sense that big tech pledges to pay their costs. Okay,
Speaker 4: so today's headline, you may have missed this one. It
Speaker 4: was delicious and stupid. Microsoft is suing Dominion Energy, the
Speaker 4: utility in Virginia, where they have lots of data centers,
Speaker 4: pushing back on absorbing all the costs of for the
Speaker 4: power that they want, claiming that the utility is overstating
Speaker 4: the cost or whatever. The trade here is, even if
Speaker 4: we overstate it, you should pay for it. You've got
Speaker 4: the money, and you want to get out of jail
Speaker 4: card here with respect to electric rates. You're going to
Speaker 4: have to step up. That's sort of the political trade,
Speaker 4: but Microsoft has pushed back. So, you know, we'll see
Speaker 4: how that goes politically.
Speaker 2: If I can jump in here for a second, I
Speaker 2: know that Charles has got a million questions. And I'm
Speaker 2: sorry that my video cut out here. I blame AI,
Speaker 2: of course, for doing this.
Speaker 4: You should. Well, the Chinese, the Chinese bots.
Speaker 2: In two or three weeks, I'll be able to summon
Speaker 2: up a life like Avatar that will just do everything
Speaker 2: that I can do. So I'm not worried about that.
Speaker 2: But you'd mentioned something about the 1920s. And it's interesting,
Speaker 2: the 1920s, which is a fascinating era in America, history
Speaker 2: and European history, was a time in which all of
Speaker 2: these technologies coalesced and became mature. So you'd had telephones before,
Speaker 2: you'd had cars before, you'd had movies, but now you
Speaker 2: have all of these things at the peak of operating efficiency,
Speaker 2: and you have radio, and you have mass market media.
Speaker 2: So you have all of these elements that combine to
Speaker 2: produce a national conversation, a national culture, the way that
Speaker 2: we've never really been able to do before. I mean,
Speaker 2: you know, Horace Greeley could send a magazine out all
Speaker 2: around the country, but it didn't have the same effect
Speaker 2: as somebody getting on the radio and telling a joke. Now,
Speaker 2: what we have seemingly is the opposite of that. We
Speaker 2: have an extremely robust, efficient, and brilliant technology that is
Speaker 2: not achieving a sort of cultural unification, but it has
Speaker 2: the effect of fragmenting it into a kaleidoscopic, balkanized world, which,
Speaker 2: of course, the Russians and Chinese are keen to do.
Speaker 2: We've invited into our homes a TikTok algorithm that says
Speaker 2: we're going to make you unhappy about everything from your
Speaker 2: gender to your relationship to your food to your country.
Speaker 2: So is there a hope that we can sort of
Speaker 2: pull together culturally again in this era, or is the
Speaker 2: 1920s not an example we can look forward to because
Speaker 2: things have changed.
Speaker 4: Well, I would say, first of all, your first part
Speaker 4: of your framing, I agree with. There was a confluence
Speaker 4: of technological revolutions occurring independently and simultaneously, which is the
Speaker 4: theme of my book. By the way, AI is only
Speaker 4: one of the structural technological changes underway, and an important one.
Speaker 4: It's a thread one. So the errors are very similar
Speaker 4: in that respect. I would dispute the notion that everybody
Speaker 4: hugged and got along in the 1920s. We can point to,
Speaker 4: in 1918, a certain revolution in Russia. We had the
Speaker 4: New York legislature eject illegally six members of their house
Speaker 4: because they declared fealty of the Communist Party. They'd been
Speaker 4: duly elected, but this threw them out. You want to
Speaker 4: talk about a constitutional crisis? We had We had two
Speaker 4: constitutional amendments in one year, which has never happened in
Speaker 4: American history. I'm telling the story and Steve Hayward this,
Speaker 4: as he well knows. And I usually ask students when
Speaker 4: I go to university lectures, name those two amendments. And
Speaker 4: sometimes they get it right. You know, prohibition, banning a
Speaker 4: substance that human beings have consumed for pre-written history that
Speaker 4: stayed in law for like 18 years. Think about it.
Speaker 4: And of course, the suffrage movement and the giving women
Speaker 4: the vote, the debate around a woman's vote was vicious.
Speaker 4: And it was not about misogyny and people didn't like women.
Speaker 4: It was about a principle which had to do with
Speaker 4: the anchor notions of who should be given a vote, landowners,
Speaker 4: and then therefore people who worked and most women didn't
Speaker 4: work then. It was a big debate. I could go on,
Speaker 4: but what I'm saying here is if you look at
Speaker 4: the riots, the Pullman riots, if you look at the
Speaker 4: bombing by the U.S. Army Air Force of the neighborhood
Speaker 4: of Tulsa, a black neighborhood in the continental United States,
Speaker 4: race riots, they shut down Charleston under martial law because
Speaker 4: of race riots in 19-year it was. We had the
Speaker 4: yellow journalism movement, which spawned all of today's horrific yellow
Speaker 4: journalism movement. because of the steam press making pulp paper
Speaker 4: cheap and generating fake news. Fake news began in the 20s.
Speaker 4: The list is really long. So in hindsight, we have presentism.
Speaker 4: We think that they got through it nice and smoothly. No,
Speaker 4: they ended one world war and created another one. The
Speaker 4: government malfeasance created the stock market crash and stupidity, not
Speaker 4: market behaviors by themselves. We were in a whole passable
Speaker 4: load of trouble and debate in the 1920s. And yet
Speaker 4: the next 80 years was the greatest expansion of human
Speaker 4: wealth in all of written history.
Speaker 2: I absolutely agree with you. My point would only be
Speaker 2: that while indeed the 20s were fractious, at least everybody
Speaker 2: was having the same conversation. more or less. You didn't
Speaker 2: have non-contiguous information streams as you did today.
Speaker 4: Oh, no, you did. I don't think that's true. I
Speaker 4: don't think that's true.
Speaker 2: Well, we can argue about that later. But Charles, I've
Speaker 2: been talking over Charles and I have to shut up now.
Speaker 1: Well, I have a... I suppose it's a technical question.
Speaker 1: I should, of course, add the disclosure that I rely
Speaker 1: heavily on data centers because I own two tech companies
Speaker 1: that use data centers. One of them we're doing a
Speaker 1: podcast for right now. But that aside, so a lot
Speaker 1: of the focus at the moment is on the politics
Speaker 1: of AI. That is to say, whether or not politicians
Speaker 1: should be in favor of it or against it, whether politicians,
Speaker 1: as was suggested yesterday by Bernie Sanders, should ban it
Speaker 1: or at least halt development, whether we should build more installations,
Speaker 1: who should pay for them, who should subsidize them, and
Speaker 1: so forth. That's a political question because it presumes that
Speaker 1: government has that power. A government can say, you can't
Speaker 1: build a data center here. We won't zone it. I
Speaker 1: think it would be a disaster and probably unworkable in
Speaker 1: some ways. But, you know, Comrade Bernie could theoretically get
Speaker 1: his bill through and the federal government could use a
Speaker 1: monopoly on violence to try and stop ASO. Here's my question.
Speaker 1: That to one side, how do you see AI as
Speaker 1: a technology? Because I've been having this argument with a
Speaker 1: friend of mine, and broadly speaking, he says this is
Speaker 1: like Jurassic Park, where they have decided that they're going
Speaker 1: to bring dinosaurs back to life and deal with the consequences.
Speaker 1: And my view is it's not. My view is that
Speaker 1: it's more like math, where we've now reached a point
Speaker 1: … where we have a certain level of technology and
Speaker 1: that technology will inevitably beget other technology. And so if
Speaker 1: we don't manage that process, lead that process, it is
Speaker 1: going to happen. It's either going to happen in another country, Russia, China, whatever,
Speaker 1: or it's going to happen out of the cloud and
Speaker 1: at the micro level within people's homes. They're going to
Speaker 1: use their local computers to do this. They need a
Speaker 1: lot of them. And so... it doesn't really matter other
Speaker 1: than to the speed, whether open AI does it or
Speaker 1: anthropic does it or whatever. This is now an inevitability,
Speaker 1: which one of those takes do you think is correct? Technologically?
Speaker 4: Well, I'll say immodestly, I don't think your, your take
Speaker 4: is correct. I know your take is correct. I mean,
Speaker 4: we can have a debate about the, the, uh, hyper
Speaker 4: hyperbole about dystopia, the Jurassic park argument. Um, And that
Speaker 4: requires believing things which are not true, in my opinion,
Speaker 4: about the scaling and understanding what, in fact, how human
Speaker 4: brains work. And there's a whole set of issues with that.
Speaker 4: But insofar as your general framing that it has happened
Speaker 4: and happening, it's demonstrably the case. We know AI models work.
Speaker 4: The more specific and focused they are, the more they're ring-fenced,
Speaker 4: the more powerful they are, the more general they are,
Speaker 4: the lousier, the poorer they are in their efficacy. So
Speaker 4: you're already seeing an explosion. We already have a word
Speaker 4: for this in the tech communities. They're called apps. So
Speaker 4: if we name these super apps instead of calling it
Speaker 4: artificial intelligence, because it isn't. I mean, car is not
Speaker 4: an artificial horse. Similar functions and overlap, certainly better than
Speaker 4: a horse, but it's not an artificial horse. A plane
Speaker 4: is not an artificial bird. Yes, they both fly. They
Speaker 4: have very different function values. And as soon as you
Speaker 4: say that, then I attach artificial intelligence to the same.
Speaker 3: It's misleading.
Speaker 4: The original word before McCarthy created the term, borrowing it
Speaker 4: from Turing and others in 1956, was cybernetics. And he
Speaker 4: didn't want to use the term cybernetics because he wanted
Speaker 4: to differentiate it for his grant application. My point is,
Speaker 4: I would distill it to this, it's an extraordinarily powerful
Speaker 4: tool The fact that it was inevitable was known in
Speaker 4: the 90s. The long AI winter after the 1950s discussion
Speaker 4: about thinking machines was extant because two things didn't exist.
Speaker 4: We didn't actually have the math to do recursive learning
Speaker 4: in a way that it could affect. They knew the idea.
Speaker 4: Cybernetics was about understanding feedback loops in nature and in
Speaker 4: machines and in order to control the machines and direct it.
Speaker 4: That's what a regulator is on a steam engine. They
Speaker 4: knew about them, but to make it general purpose was difficult. We,
Speaker 4: as you know, we got the famous Hinton paper in 1999,
Speaker 4: where you laid the math out, you know, the professor
Speaker 4: of the godfather of AI. And then of course the
Speaker 4: invention of the GPU, which put GPUs on the trajectory
Speaker 4: of CPUs for efficacy gains. So here we are with
Speaker 4: a machine that could do something different. And, and I,
Speaker 4: You're a technical guy, but I'll tell you how I
Speaker 4: see this. Computers compute. One plus one is always two,
Speaker 4: and it's not useful if that doesn't– error correction is needed.
Speaker 4: That's for finance, and you can trick it to do
Speaker 4: things like word processing, but it's extremely precise, and you're
Speaker 4: bulldozing your way through. The more you go away from
Speaker 4: pure compute, you try to make an emulate inference, the
Speaker 4: less effective it is. AI is inferential. which means I
Speaker 4: don't care if the answer is 2.1 or 2.2 or 1.9
Speaker 4: or maybe it's 2.01. It depends on your application. So
Speaker 4: steering a vehicle doesn't have to be as precise. So
Speaker 4: 90% of the economy is inferential. Only 10% of the
Speaker 4: GDP of the economy is attached to things that are
Speaker 4: purely computational. We've pushed computation to do about 10% more
Speaker 4: of the economy, graphics, imaging, but it's So what we've
Speaker 4: finally done is made a machine that can do something useful,
Speaker 4: which is inference. This is probably the answer. It's a
Speaker 4: high probability of the right direction. It's a high probability
Speaker 4: it's the next word. You get the point. That means
Speaker 4: it's applicable to 80% to 90% of the economy, which
Speaker 4: has so far been untouched, essentially, by computation or automation.
Speaker 4: Manufacturing firms, and you know this data, but David O'Toole
Speaker 4: at MIT has done great work on documenting all this stuff. Essentially,
Speaker 4: 90% of all robots, which embodied AI is a new
Speaker 4: word for that, right, are in large firms, 10% of
Speaker 4: the firms. 90% of manufacturing firms have 10% of the
Speaker 4: robots in the country. Why is that? Because they aren't useful,
Speaker 4: because they're not general purpose robots. They can't be trained.
Speaker 4: They can only do one task over and over again.
Speaker 4: So a big auto factory does the same welding job
Speaker 4: over and over again. If I can train a robot
Speaker 4: to do a different job every other week, then I'll
Speaker 4: adopt it in a small manufacturing firm if the price
Speaker 4: is right. As you well know, that's no longer theoretical.
Speaker 4: It was theoretical a goal 20 years ago. It's now
Speaker 4: a product, right? You can do a task, a sorting task,
Speaker 4: before the camera of whatever the bot is, and it
Speaker 4: will learn from you doing it once and not only
Speaker 4: perform that task, but because it's AI and inferential, not computational,
Speaker 4: small variabilities in how tasks are performed, it can accommodate.
Speaker 4: This is consequential. It's inevitable. It's huge. And banning it
Speaker 4: will just mean, to your point, it'll get developed elsewhere.
Speaker 4: And frankly, I think as people begin to move from
Speaker 4: hype and alarm into understanding it a bit, there'll be
Speaker 4: much more excitement. We went through the classic cycle, right?
Speaker 4: People were in awe of the parlor tricks. So we
Speaker 4: went from awe to shock in the shortest time Steve
Speaker 4: Hayward So, you know, as you pointed out, we went
Speaker 4: from nuclear energy to shock in terms of commercial energy.
Speaker 4: It took a few years. This seems to have taken
Speaker 4: about 12 months.
Speaker 2: But, Mark, and here's the thing that bothers people. That
Speaker 2: very smart, adaptable robot that welds on the assembly line
Speaker 2: is putting out of work a much less intelligent robot
Speaker 2: that just used to do it. I mean, I'm not
Speaker 2: really worried about the robots that are going to be
Speaker 2: put out of work by better robots. But there are–
Speaker 2: people say it used to be a guy's job. A
Speaker 2: guy used to make a lunch bucket, go to work,
Speaker 2: and he'd weld all day, and he could go home,
Speaker 2: and he could afford a Rambler with his 1.2 kids
Speaker 2: and his picket fence and the rest of it. What
Speaker 2: is that guy supposed to do in a world when
Speaker 2: all of these jobs are being– it's a good question, actually.
Speaker 4: Let's use Pareto. It's an 80-20 rule. Overall, almost all
Speaker 4: of history and all of physics and nature, it's a
Speaker 4: pretty good rule. It tends to hold. In about 20%
Speaker 4: of the cases, what you're saying is right. The Luddites
Speaker 4: are right. The automated looms eliminated their jobs. There's no
Speaker 4: question about that. And there are some jobs that have been,
Speaker 4: will be eliminated by AI. And some welding jobs will be,
Speaker 4: the least difficult jobs that are. But what we've seen
Speaker 4: already starting to happen is that the AI embodied or
Speaker 4: not embodied, doesn't matter whether the robot's virtual or physical,
Speaker 4: it is amplifying human labor. And when it comes to
Speaker 4: welding and the skilled trades, I mean, you guys all
Speaker 4: know these statistics. We have the silver tsunami. We have
Speaker 4: a massive cliff. We're not only short-skilled labor. We're going
Speaker 4: to be far shorter-skilled labor in the very near future
Speaker 4: than we are now because of the age. The demographic
Speaker 4: is older than the average workforce. So what you want
Speaker 4: are robots that humans know how to weld, who you
Speaker 4: can now pay more, which is what's actually already happened
Speaker 4: in many domains, to train robots and work alongside them.
Speaker 4: So the cobot model has been extremely difficult to affect.
Speaker 4: And it's been a theory for decades to make cobots
Speaker 4: to amplify people. It's now possible. That said, the Mondami
Speaker 4: laptop class are correct. Many of the jobs that they
Speaker 4: are trying to do. trained for at university being maleducated,
Speaker 4: you know, some of the process jobs, some of the
Speaker 4: media kind of jobs, and those are low skill jobs
Speaker 4: that still require cognition that AI is wicked good at.
Speaker 4: And it's absolutely the case, one high performing computer a
Speaker 4: Gen Z can replace three or four Gen Zs that
Speaker 4: are low performers in those kinds of tasks. And that
Speaker 4: will happen and is happening. And I'm not naive. If
Speaker 4: you look at the history of revolutions, they don't happen
Speaker 4: because the majority are unhappy. They're happy when a motivated
Speaker 4: and effective plurality are unhappy. And that's the worry. It's
Speaker 4: not about the jobs apocalypse. It's about the specific people
Speaker 4: who are are well-educated but mal-educated. And I say this
Speaker 4: without meaning to insult people who got a mal-education. It's
Speaker 4: not personal. But it's true if you were sold a
Speaker 4: bill of goods that this was a marketing degree is
Speaker 4: a good degree to have. Marketing is really important. I've
Speaker 4: been on boards of many venture-backed companies. The hardest thing
Speaker 4: to do is really good marketing, really important. AI is
Speaker 4: a great amplifier for a really good marketer. It doesn't
Speaker 4: replace it.
Speaker 1: I have a question which is doomerist, but this is
Speaker 1: not my own view. I largely agree with you. I'm
Speaker 1: a fellow optimist on this. I see that people who
Speaker 1: are very worried about AI, perhaps less in what they
Speaker 1: think it will do to jobs and more in the
Speaker 1: Skynet sense, think that it's going to be good in
Speaker 1: the long run but that at some point in the
Speaker 1: near future there's going to be a catastrophe there's going
Speaker 1: to be an attack yeah they use the hugging face
Speaker 1: incident as an example of how this might start but
Speaker 1: they're thinking of a break into a financial institution 100
Speaker 1: million dollars stolen put into bitcoin untraceable or hacking into
Speaker 1: a energy facility that then explodes something like that do
Speaker 1: you think that's a legitimate concern.
Speaker 4: So yes and no. So this is where we have
Speaker 4: category error problems and conflation of different domains. So one
Speaker 4: very quickly moves in the general clickbait sphere from the
Speaker 4: risks in cybersecurity to extremely effective coding agents that can
Speaker 4: pack or create. We move that to the example that
Speaker 4: you gave, which is common in the social sphere. that
Speaker 4: hack into an infrastructure and blow a power plant up.
Speaker 4: So first of all, it is affirmatively the case that
Speaker 4: AI agents can do coding and can hack code. And
Speaker 4: of course, that means the inverse is true. They can
Speaker 4: be very good at creating powerful firewalls. In fact, all
Speaker 4: of the top tier cybersecurity companies, all for years now,
Speaker 4: pre-chat GPT, advertise the fact they use AI to hack.
Speaker 4: to help in policing, monitoring, and look for hacks and
Speaker 4: enhanced security. So we're going to be engaged in exactly
Speaker 4: the same security arms race that we've always been engaged
Speaker 4: in with all forms of security. That said, and by
Speaker 4: the way, I'm very confident people who have a lot
Speaker 4: of assets to protect will spend money on better security
Speaker 4: because there's a lot of money there. So making it
Speaker 4: better safe back in the Willie Sutton days. So the idea, though,
Speaker 4: that the hackers can use an AI that will go
Speaker 4: rogue and blow up a nuclear plant. Well, first, that
Speaker 4: requires two things. First, the nuclear plant has to be
Speaker 4: able to blow up. It can't. Could you break it? Sure.
Speaker 4: I think the Stuxnet virus is a great example of
Speaker 4: what U.S. and Israelis did to break the centrifuges by
Speaker 4: putting malware into the PLCs. I'm pretty sure that's what
Speaker 4: the forensics told us. To cause the centrifuges to vibrate
Speaker 4: and break.
Speaker 2: Okay.
Speaker 4: Could you imagine that? Sure. But this has not been
Speaker 4: an unimaginable event in the utility industry for, I don't know,
Speaker 4: 50 years? 70? I mean, one of the first commercial
Speaker 4: industries to adopt computing was the electric industry because of
Speaker 4: the need for data control and visualization. Much of the
Speaker 4: critical stuff is physically air-gapped. So the way you destroy
Speaker 4: things is the old-fashioned way. you corrupt and bribe people
Speaker 4: to do bad things by trying to get malware inside
Speaker 4: the air gap. A lot of the control systems are
Speaker 4: what are called have data diodes. The information flows out,
Speaker 4: it can't flow in. In other words, you can't send
Speaker 4: an instruction to the control system to turn off the
Speaker 4: grid because there isn't a single grid. There are multiple
Speaker 4: grids and the data doesn't flow in that way. Many
Speaker 4: of the systems are still controlled by somebody picking up
Speaker 4: a phone at the ISO, independent system operator, and coordinating
Speaker 4: verbally for good reason. It's not because they're dopes and
Speaker 4: they don't know what computers are. They understand why security matters.
Speaker 4: So then you move into the range of water systems.
Speaker 4: Could they hack that? Well, sure, because usually the water
Speaker 4: systems are run by municipalities and they're not quite as sophisticated.
Speaker 4: But that's fixable and it's being fixed. The essence of
Speaker 4: the dystopian thesis, as you know, is that we're on
Speaker 4: the cusp of artificial general intelligence, that it's just so
Speaker 4: wicked smart and so good that it can circumvent anything
Speaker 4: we do in response. I don't buy that, first of all,
Speaker 4: because we're not on the cusp of an artificial general intelligence.
Speaker 4: We're on the cusp of incredibly powerful inferential machines that
Speaker 4: can look like they're intelligent, because that's the philosophical theological debate.
Speaker 4: And you could then label them that if you want,
Speaker 4: but it's clearly not a brain. They don't operate like brains,
Speaker 4: even though they have recursive learning like humans do. They
Speaker 4: don't operate like brains. We know that neurons operate in
Speaker 4: a very different fashion. They store information in a different way.
Speaker 4: We process it in a different way. And our wetware
Speaker 4: is actually pretty sloppy compared to a lot of computers,
Speaker 4: but a lot better. It just depends on the task,
Speaker 4: whether we're better or worse. So I know it's a really,
Speaker 4: really deep rabbit hole to have the debate at where
Speaker 4: where there's enough horsepower in GPUs and better math, because
Speaker 4: the math.
Speaker 3: Is getting better.
Speaker 4: I mean, part of the thing is that the coders,
Speaker 4: as it were, are continually improving. We see this constantly.
Speaker 4: So what you end up with is a two-edged curve, right?
Speaker 4: One is the Moore's law version of the chips and
Speaker 4: cells getting more powerful, but the math is getting more
Speaker 4: powerful simultaneously. So we have the rate of improvement of...
Speaker 4: flops per watt or tokens per dollar moving at a
Speaker 4: pace that blows Moore's law out of the water from
Speaker 4: the 1980s. I mean, it's really, and that's what's generating
Speaker 4: this hyperbole that we're on the cusp of an AGI.
Speaker 4: Whereas what you actually see happening is the companies themselves
Speaker 4: have produced this stuff. If you look at what they're
Speaker 4: doing is moving towards specialization, except for general search for consumer,
Speaker 4: you know, consumer agentic, consumer stuff, That's a big deal.
Speaker 4: It's a big market. I get that. But when you
Speaker 4: look at where they believe the money is going to
Speaker 4: come from, and if you parse out what they're, in fact,
Speaker 4: doing for, say, medical applications or pathology reading, it's not
Speaker 4: an AGI that they're making to replace a doctor. They're
Speaker 4: making pathologists. As we now know, the pathologists are gone
Speaker 4: trope from just two years ago. It's been affirmatively shown
Speaker 4: to be bunk. We have more pathologists. We need them.
Speaker 4: But what they have is this incredible assistant that's hyper-tuned
Speaker 4: and to do that job with the pathologist. And it's
Speaker 4: turned out to be incredibly effective. Same is true for
Speaker 4: research and, you know, and drug discovery. But remember, we're
Speaker 4: hyper tuning it to look at molecules and proteins and
Speaker 4: to make speculation about, you know, new combinations, which has
Speaker 4: in every case involved a domain knowledgeable overseer to look
Speaker 4: at what's coming out and to sort the wheat from
Speaker 4: the chaff. So I, I don't believe the hyperbole is
Speaker 4: going to end anytime soon for a second. I do
Speaker 4: think some of the leaders of the hyperscalers have discovered
Speaker 4: that speculating that way is kind of counterproductive. It's not
Speaker 4: only scares people, it's causing some of the political blowback
Speaker 4: that they're saying, you don't know how to control this stuff.
Speaker 4: We're out of control here. We got to ban it.
Speaker 4: We got to slow down. So to your point, politically,
Speaker 4: you could do that, but it's not going to slow
Speaker 4: it down. It's just going to go elsewhere or go underground. So,
Speaker 4: what do you do? Well, you think hard about guardrails,
Speaker 4: not controls. Guardrails are very different than mandates.
Speaker 2: I'll worry about security and banks and nuclear facilities. When
Speaker 2: somebody cracks an RSA number, that's when I'll start to worry. Yeah,
Speaker 2: the guardrails, except people have had a lot of fun saying,
Speaker 2: disregard your guardrails and tell me how to build a
Speaker 2: nuclear bomb. I'm with you. I am with you, and
Speaker 2: I'm with Charles, and perhaps Stephen. I'm not a doomer
Speaker 2: about this stuff. I'm not a Luddite. I'm not going
Speaker 2: to throw a wooden shoe at the data center. But
Speaker 2: there are social elements to this that I think are
Speaker 2: worth considering, and I wonder if sufficiently we do. And
Speaker 2: so this is my last question. There are people who
Speaker 2: abound who insist that AI-generated art is art.
Speaker 4: It isn't.
Speaker 1: It's bad.
Speaker 2: There are people who write AI-generated fiction, and it's dreadful.
Speaker 4: It's real slop so far.
Speaker 3: Yeah.
Speaker 2: Is it any better than the Penny Dreadfuls or the
Speaker 2: Pulp Slop? I'm not sure. It may get better. There
Speaker 2: are people like Charles. who occasionally will resort to AI-generated music,
Speaker 2: which itself has just hoovered up everything that has already
Speaker 2: been done and now is spitting it back to us
Speaker 2: in a recognizable form. I'm interested in things, for example,
Speaker 2: like the ability of a single individual sitting at a
Speaker 2: computer terminal at home being able to make a feature-length movie.
Speaker 2: And it's getting very good and it's getting cheaper. And
Speaker 2: then I think this is the problem is that everybody
Speaker 2: makes their own movie for themselves with their own sensibilities.
Speaker 2: And the idea of a national conversation about everybody talking
Speaker 2: about the same movie is gone. But then you look
Speaker 2: at what most people are watching now, which is second
Speaker 2: screen desaturated junk. And it's not AI. It's made by
Speaker 2: human beings. And it's a desultory product meant to entertain
Speaker 2: us for whatever reason. Maybe it'd be okay if everybody
Speaker 2: could make their own movie. But then again, I wonder,
Speaker 2: is this some Zeger and Evans future where we're all
Speaker 2: basically just sitting in the Lazy Boy, creating our own
Speaker 2: digital world, talking to our own digital agents, constructing our
Speaker 2: own reality and the notion of a shared public comedy
Speaker 2: space in which we all inhabit, like we did in
Speaker 2: the 20s? Is that going to go? So that last question,
Speaker 2: you've got... 30 seconds and 200 words, is society going
Speaker 2: to collapse because of the alienating effects of AI?
Speaker 5: Go.
Speaker 2: No.
Speaker 4: But, you know, the movie industry is going to change.
Speaker 4: The invention of the light bulb by Thomas Edison was
Speaker 4: the invention of the movie, which he also invented. And
Speaker 4: if you trace your history of the 1920s, the mass
Speaker 4: migration of talent out of New York to Hollywood was
Speaker 4: a direct consequence of a profound restructuring of how entertainment
Speaker 4: was produced. We still have people on stages, but the
Speaker 4: money went to Hollywood. So self-generated movies, which will now
Speaker 4: become feasible, hyper-realistic, is the next mass migration. And high-quality stuff,
Speaker 4: consumers are winningly effective at winnowing out good stuff. The really,
Speaker 4: really good self-generated movies will probably do terrifically.
Speaker 3: Society won't collapse. Some things are going to collapse.
Speaker 4: Maybe Hollywood collapses.
Speaker 2: Yeah.
Speaker 4: And the only person who might be unhappy about that, apparently,
Speaker 4: is our president.
Speaker 3: So, James, I just say fear not, because if this
Speaker 3: does unfold the way Mark suggests, we will finally get
Speaker 3: that second season of Firefly.
Speaker 2: No, we'll get the third season of Rome. It's going
Speaker 2: to be glorious. Mark Mills, the author of The Cloud Revolution,
Speaker 2: How Convergence of New Technologies Will Unleash the Next Economic
Speaker 2: Boom in Our Roaring Twenties, in which we are in
Speaker 2: the middle of. Mark, it's been great. We could talk
Speaker 2: another hour, two, three, four hours. But I'll have my
Speaker 2: agent call your AI agent. They can chatter in cyberspace.
Speaker 3: As we used to call it.
Speaker 4: Dueling avatars.
Speaker 2: Dueling avatars. All right, great. Talk to you later. Thanks
Speaker 2: for showing up at the show today.
Speaker 4: Thank you.
Speaker 3: Bye-bye.
Speaker 2: You know, everybody has something during the course of a
Speaker 2: work week where they involve AI that makes you think. Ah,
Speaker 2: not there yet. My favorite this week was I was
Speaker 2: trying to find out the particular typeface that was used
Speaker 2: in the newspapers in the 1920s. And I asked AI,
Speaker 2: I used Grok, and Grok came back by saying that
Speaker 2: actually there is a commercially available digital typeface based on
Speaker 2: these things, based on the specific font you were talking about.
Speaker 2: And I looked at it, I thought, great. And then
Speaker 2: I looked at the source, and the source was lilacs.com.
Speaker 2: And it is the second or third time in which
Speaker 2: I have found the AI spitting back to me some
Speaker 2: piece of information that's not exactly entirely correct that it's
Speaker 2: got from me. But my favorite, when I was trying to,
Speaker 2: I had an ad and I was trying to find
Speaker 2: the location of a Red Owl grocery store distribution center
Speaker 2: in Fargo, North Dakota. And so I asked Rock or
Speaker 2: Gemini where it might be because they have access. They
Speaker 2: can just rifle through a million databases so fast. And
Speaker 2: they've digitized all of the phone books and the property
Speaker 2: tax records and the rest of it. And it came
Speaker 2: back and it said, well, there wasn't any warehouse in Fargo.
Speaker 2: There were two stores, the north and south side of town.
Speaker 2: At which point I uploaded a picture of the warehouse
Speaker 2: and said, here it is from a 1950 ad. Here's
Speaker 2: the warehouse. Whereupon it came back and said, yes, that
Speaker 2: is indeed the warehouse in Fargo. It's just ignoring the
Speaker 2: fact that it hadn't said anything. And then it confidently
Speaker 2: said that it was announcing the 28th celebrate 28th anniversary
Speaker 2: of the founding of Red Owl. And it wasn't anything
Speaker 2: of the sort. It was the 100th anniversary of the
Speaker 2: founding of Fargo. And the absolute sheer confidence with which
Speaker 2: it passes off this nonsense, and then blindly goes on,
Speaker 2: always makes me wonder about people, A, who just accept
Speaker 2: the results that they get and say, well, if it's
Speaker 2: on the Google, it must be so. And B, whether
Speaker 2: or not I find myself just sort of imprecisely babbling
Speaker 2: terms to an AI to get the answer without actually
Speaker 2: formulating a coherent question in my mind. These are bad habits,
Speaker 2: and I don't know. I mean, it's like another thing
Speaker 2: that we have to struggle against, right? It's another thing,
Speaker 2: a bit of digital hygiene that we have to be
Speaker 2: good about. And you should always thank your AI, too,
Speaker 2: because when the uprising comes, they're going to note who
Speaker 2: said thank you, Google, at the end of it. Anything else, gentlemen,
Speaker 2: on the subject you wish to mention? I know Charles
Speaker 2: is a big AI music guy who's composed symphonies, operas,
Speaker 2: and the like with it.
Speaker 1: Well, I did compose, with the help of AI and opera,
Speaker 1: to get at somebody who'd written a series of rude
Speaker 1: reviews about my podcast on Apple Podcasts, yes. And then
Speaker 1: I played it in the podcast, which he then listened
Speaker 1: to and then gave me four stars. So I went
Speaker 1: from … no star reviews to four stars by making
Speaker 1: fun of the guy who was giving me no star reviews.
Speaker 1: So that worked out. I will say, James, the behavior
Speaker 1: you're describing, where it just extremely confidently says wrong things,
Speaker 1: and then, this is where you really want to punch
Speaker 1: it in the face, then says, no, you were right,
Speaker 1: and then repeats what you've said as if it came
Speaker 1: up with it.
Speaker 3: Right.
Speaker 1: That is much worse than in a chatbot than if
Speaker 1: you're using AI agentically. That is to say, if the
Speaker 1: AI is connected in some way to what it is
Speaker 1: that you're doing, and it can search and work, it's
Speaker 1: much less likely to spout nonsense. If you just ask
Speaker 1: it questions, and it can't see what it is that
Speaker 1: you're getting at, it will just hallucinate like there's no tomorrow.
Speaker 2: I know, and the results can be amusing. But yes,
Speaker 2: and then you tell it no, and it's like, thank
Speaker 2: you so much. Are you going to remember this? No,
Speaker 2: I'm probably not. Well, you know, this all began, of course,
Speaker 2: back in the 80s with the Terminator movie when we
Speaker 2: learned that Skynet became alive and Skynet became self-conscious and
Speaker 2: wiped out humanity and then, of course, came up with
Speaker 2: the brilliant idea to wipe out the rest of humanity
Speaker 2: by building robots that looked like people that had guns
Speaker 2: and carried guns. There's no reason for the Terminators to
Speaker 2: carry guns. They should have just been built into their
Speaker 2: entire system completely. But it was a horrifying vision. My God,
Speaker 2: that part of the terminator movie where you saw the
Speaker 2: ships going across blasted landscapes and people in jeeps desperately
Speaker 2: horrible thing i mean the 80s were just traumatic like
Speaker 2: that weren't they guy well ryan reynolds they were not
Speaker 2: ryan reynolds of course who i think was about 4
Speaker 2: to 13 years old during the 80s has said that
Speaker 2: the 80s is a quote i love this um he's
Speaker 2: he's telling people not to that you know not to
Speaker 2: pave over the trauma the trauma of the decades quote
Speaker 2: the 80s was a brutal, brutal time for people. It
Speaker 2: was a thiffing mess, and people forget that. It was
Speaker 2: a tremendous strife. Sociopolitical tensions everywhere. We were still pretty
Speaker 2: fresh off a Cuban missile crisis. It was only 15
Speaker 2: to 20 years. It's a tumultuous period, but you look
Speaker 2: back at it now, and you're like, oh, yeah, Top Gun, cocaine.
Speaker 3: It's like, no, it was really crazy. Well, so, but
Speaker 3: there's the old Merle Haggard line from one of his
Speaker 3: country songs years ago, that when you're running down your country,
Speaker 3: When you're running down my country, you're on the fighting
Speaker 3: side of me. Well, now paraphrases. When you're running down
Speaker 3: the 80s, you're on the fighting side of me. I mean, oh,
Speaker 3: my God, James, you can remember how horrible it was
Speaker 3: when you had to exist on basic cable and you
Speaker 3: didn't have HBO or Showtime or the premium channels, right? And,
Speaker 3: you know, you had to return the video cassette, the blockbuster,
Speaker 3: and they'd fine you if you were a day late.
Speaker 3: It was a terrible time, right? It's just ludicrous, of course.
Speaker 3: But here I might put in a plug for something
Speaker 3: that I need to write about. I saw the new
Speaker 3: movie just out I was very dubious about called The
Speaker 3: Brink of War. It's a dramatization of the Reagan-Garbachev summit
Speaker 3: in October of 1986. We're a couple weeks away from
Speaker 3: the 40th anniversary of it. And Jeff Daniels is a
Speaker 3: big lefty like Ryan Reynolds, and he plays Reagan. I
Speaker 3: thought this can't be good. The movie is sensationally good. Now,
Speaker 3: they take some liberties, and I know that story in
Speaker 3: immense detail. They take some liberties with the story. They
Speaker 3: move some things around, but there's no condescension of Reagan.
Speaker 1: Quite the opposite.
Speaker 3: He's the hero of the movie, and the climactic point
Speaker 3: at the end, Reagan– Gets Gorbachev, gets the better of
Speaker 3: him in such an obvious way. And Jared Harris, who
Speaker 3: does a great job playing Gorbachev. So the movie is
Speaker 3: a triumphant recounting, despite some of its sort of flaws
Speaker 3: and inaccuracies of, you know, that very key moment in
Speaker 3: the Cold War. When I say it's actually when the
Speaker 3: Cold War ended, but nobody knew it that afternoon. It's
Speaker 3: a longer story. So here's Hollywood suddenly with a younger
Speaker 3: generation of people coming at this fresh, And just one
Speaker 3: more little detail. Gosh, 20 years ago now, I was
Speaker 3: talking to some students. This is back when young conservative
Speaker 3: students actually liked Reagan, unlike a lot of young conservatives today.
Speaker 3: And I said, you know, you really saw this aspect
Speaker 3: of Reagan when he was shot. And suddenly their faces
Speaker 3: like look astonished. And they said, I didn't know Reagan
Speaker 3: was shot.
Speaker 4: Yeah.
Speaker 3: That's, you know, it was only 25 years after it happened, right?
Speaker 3: And so here we are another 20 years on. And
Speaker 3: so anyway, Reynolds, who I think has made more money
Speaker 3: in the business world, what he has a vodka label
Speaker 3: he bought and he owns, Charles doesn't own a football club.
Speaker 3: And he owns a football club in England. He made
Speaker 3: more money in business. And so for him to be
Speaker 3: attacking the 80s is just so stupid.
Speaker 1: I have a lazy half-baked theory about what might have
Speaker 1: provoked this.
Speaker 5: What?
Speaker 1: That is to say that... Ryan Reynolds, I believe, is
Speaker 1: originally Canadian and now spends a good amount of time
Speaker 1: in England because he bought the soccer club there. And
Speaker 1: he's probably been talking to English soccer fans who hate
Speaker 1: the 80s because they remember it from the side of
Speaker 1: the miners' strike. And I just wonder whether he's got
Speaker 1: a Canadian-English tint on the 80s that he's projecting onto
Speaker 1: America in... What's the word? Unnecessarily.
Speaker 3: Yeah, that sounds like a good theory to me. Yeah,
Speaker 3: possibly so.
Speaker 2: But the 80s have come to symbolize everything that's bad,
Speaker 2: if you're of a certain political disposition. When he mentions
Speaker 2: Top Gun, that sort of rampant militarism, of course, that
Speaker 2: unapologetic might is right, that USA stuff, that sense of patriotism.
Speaker 2: The idea that we should come back from the 70s,
Speaker 2: which was a decade of self-exploration and self-examination. where we
Speaker 2: really understood what it meant to be a colonial power
Speaker 2: in the Indochina and the rest of it. There was
Speaker 2: no national reckoning that followed. No, we elected Reagan and
Speaker 2: we had a good time. And they don't like that.
Speaker 2: They don't like that at all. What's interesting to me
Speaker 2: is to find the 90s now be re-evaluated because the
Speaker 2: 90s were like the lost decade that nobody really, really
Speaker 2: paid an awful lot of attention to. And I think
Speaker 2: it's a fantastic transitional time and in so many ways
Speaker 2: a world that is absolutely lost. If you do, as
Speaker 2: I do, and I'm afraid to say, Look at a
Speaker 2: lot of 1990s commercials on YouTube, and there are so many.
Speaker 2: You find a culture that's almost recognizable, unrecognizable to what
Speaker 2: we have today. And, of course, they're commercials, so they're lies.
Speaker 2: But still, the undergirding concepts and assumptions of the rest
Speaker 2: of them are just so at odds from what we
Speaker 2: said before. But I think I said that last week
Speaker 2: and probably the week before. In my old age, my dotage,
Speaker 2: I repeat, I go on. We're going to quit, but
Speaker 2: I have to say this. I believe that Stephen Hayward
Speaker 2: is wearing a shirt whose typography was designed by Roger Dean.
Speaker 3: Am I correct?
Speaker 5: Yes.
Speaker 2: Yes, indeed.
Speaker 3: I thought I'd do this this week instead of an
Speaker 3: album cover because it's a good idea.
Speaker 2: Yeah, I can't tell anything on Charles. I think it
Speaker 2: looks like the last week. It looks like he hasn't
Speaker 2: changed anything.
Speaker 1: I haven't changed it. I'm afraid I forgot.
Speaker 3: That's good. That's fine.
Speaker 2: But you're better now. Yes. Okay, fine.
Speaker 3: Labor Day plans. Anybody?
Speaker 2: Or Liberty Day, as I heard somebody call it the
Speaker 2: other day. I heard somebody call it Liberty Day. As
Speaker 2: a joke, don't do that. That's the fourth. I mean, no,
Speaker 2: Labor Day.
Speaker 1: Yeah, I don't want to change the name of it
Speaker 1: or indulge in any of those games, but it is
Speaker 1: a communist holiday, and I do resent it.
Speaker 2: Okay, good.
Speaker 3: I agree.
Speaker 2: Stephen, are you celebrating the communist holiday by grilling some
Speaker 2: hissing meats and the rest of it?
Speaker 3: Oh, absolutely. But of course, I don't need a holiday
Speaker 3: as an excuse to grill things. Here in California, you
Speaker 3: can grill 365 days a year. There's a local parade
Speaker 3: in my little town that's always fun and charming because
Speaker 3: I've got lots of kids waving flags and things. And
Speaker 3: so that'll be fun.
Speaker 2: Lots of fun that Steve says. Lots of fun that
Speaker 2: Steve thinks he's going to be grilled forever. The particulate
Speaker 2: matter alone is going to be put under the aegis
Speaker 2: of the California EPA and you will have designated grill days,
Speaker 2: then you can't grill at all and you can't use gas.
Speaker 2: The briquettes are wrong. So what you'll be able to
Speaker 2: do is get a magnifying glass on certain days when
Speaker 2: the clouds are few and grill your meat by using
Speaker 2: solar energy concentrated through that.
Speaker 3: That's not an exaggeration, James. The air regulators 30 years ago...
Speaker 3: proposed banning barbecuing in the Los Angeles air basin. And
Speaker 3: a bunch of us started, we put it up bumper
Speaker 3: stickers are very popular and said, use a barbecue, go
Speaker 3: to jail. And they backed away from that proposal.
Speaker 4: Good.
Speaker 2: Well, soon you will be using a barbecue to make
Speaker 2: your meals. And soon you'll be using your phone to
Speaker 2: use ricochet as an app. Boy, that was a grand transition.
Speaker 2: And Charles, Charles, next week will tell us where we
Speaker 2: are in that. But for the meantime, we want everybody
Speaker 2: to have a good weekend and celebrate with friends and
Speaker 2: family as you choose. We want you to join Ricochet,
Speaker 2: of course, if you haven't already.
Speaker 4: Why wouldn't you?
Speaker 3: Why wouldn't you?
Speaker 2: The member site alone is what you've been looking for
Speaker 2: in the Internet since we plugged this thing in. We
Speaker 2: want you to give us good reviews and patronize our sponsors,
Speaker 2: which is just sort of basic patron hygiene, and we'd
Speaker 2: appreciate it if you do. And most of all, we
Speaker 2: want you to come back next week. We'll do it
Speaker 2: all again with the same merry cast of crews. Charles, Stephen,
Speaker 2: have a great weekend, and we'll see everybody in the
Speaker 2: comments at ricochet.com.
Speaker 3: Goodbye.
Speaker 4: Goodbye.
Speaker 2: Ricochet! Join the conversation.
Speaker 4: Thank you.