Earth Growing an AI Brain? Planetary Computation Explained with Ben Bratton [Ep. 486]

As a member of the Into the Impossible family, you get a special 20% discount on a subscription to The Economist. Visit their website at https://www.economist.com/Keating to get started. Pique is offering 20% off for life AND a free Starter Kit with your purchase—that's a rechargeable frother and glass beaker to make the perfect cup every time. Just go to http://piquelife.com/impossible Please join my mailing list here 👉 https://briankeating.com/list to win a meteorite 💥 What is planetary computation, and why does it matter? Are humans and AI truly separate, or are we actually co-evolving? And how did we end up building a megastructure that’s quietly reshaping governance, knowledge, and power on a planetary scale? Here to shed light on our evolving technological reality is Ben Bratton, philosopher of technology and professor at UCSD. Ben is the Director of Antikythera, a research program at the Berggruen Institute focused on the future of planetary computation. The program explores five core areas: planetary computation, synthetic intelligence, recursive simulations, hemispherical stacks, and planetary sapience. He is also the author of The Stack, a groundbreaking book that introduced the term “planetary computation” and mapped its political, social, and philosophical implications. In our wide-ranging conversation, Ben explains how computation has evolved far beyond servers and algorithms to become an organizing force of the planet itself. We also dive into the future of AGI, the ethics of machine valence, terraforming Earth as a philosophical imperative, non-biological life, and how speculative design and planetary sapience might reframe humanity’s role in the cosmos. — Key Takeaways: 00:00 Intro 01:02 Antikythera and planetary computation 07:50 AI and the limits of computation 18:04 Terraforming and the future of humanity 19:55 The role of language in AI 31:01 Planetary data centers and future energy needs 34:00 Techno signatures 39:10 Science and philosophy 41:09 The Stack: On Software and Sovereignty 45:52 Outro — Additional resources: ➡️ Learn more about Ben Bratton: 💻 Website: https://bratton.info/ 📸 Instagram: https://www.instagram.com/benjaminbratton ✖️ X: https://x.com/bratton 📚 The Stack: https://amzn.eu/d/j80ENZW ➡️ Follow me on your fav platforms: ✖️ Twitter: https://twitter.com/DrBrianKeating 🔔 YouTube: https://www.youtube.com/DrBrianKeating?sub_confirmation=1 📝 Join my mailing list: https://briankeating.com/list ✍️ Check out my blog: https://briankeating.com/cosmic-musings/ 🎙️ Follow my podcast: https://briankeating.com/podcast — Into the Impossible with Brian Keating is a podcast dedicated to all those who want to explore the universe within and beyond the known. Make sure to follow so you never miss an episode! Learn more about your ad choices. Visit megaphone.fm/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  Now, more than ever, we need someone on our side. But Rob Whitman? Whitman's votes drove up costs, cut Medicaid, and risked 350,000 Virginians' health care to pay for tax breaks for himself and his donors. He's not on our side. Shannon Taylor will fight corruption, cut taxes, and bring down costs. This November, vote for Shannon Taylor. She's for us. Paid for by HMP, the HouseMajorityPac.com. Not authorized by any candidate or candidate's committee.

• 0:29Brian Keating?

  Today, we're exploring whether the Earth itself is developing intelligence through us. Soon, you'll discover why the world's first computer wasn't built to crunch numbers, but to map our place in the cosmos. My guest today is Ben Bratton, a professor, a visionary philosopher of technology, and a man whose work has redefined intelligence at planetary scales. He's the perfect person to explore this mind-bending concept. Ben argues that AI isn't just another tool. It's the planet evolving a nervous system. But here's the twist. Are we training artificial intelligence? Or terrifyingly, is AI training us?

• 1:14Brian Keating?

  First, we'll unpack computation as a natural force of the universe. Then, we'll ask, is Earth itself becoming conscious? Join us as we reimagine humanity's role in the greatest evolutionary leap since life began. One of the best parts about doing a podcast is that you get to invite your friends and people that you are so inspired by, and that's no exception for you. I want to start with this new project that dovetails so beautifully with what I do, which is, you know, possibly the existence of planetary-scale computing and so forth. And I thought we could start there with this concept that I'm trying to learn how to pronounce Antikythera? Antikythera. Antikythera. So what is Antikythera? And why should we care about this?

• 1:58Brian Keating?

  As astronomers, speaking to the most brilliant minds in the multiverse, a lot of them are astronomers. I should say, first of all, that, you know, I call myself a philosopher of technology, right?

• 2:08Speaker 02

  Come from the humanities side of the house.

• 2:09Brian Keating?

  Visual arts, right?

• 2:10Speaker 02

  That's your in the department of visual arts, your E C C, right? But I'm a little bit unusual in this regard. That is, I take a very intense and sincere interest in what science is doing. And the way in which emerging technologies not only allow us to do new things, but to know new things. The relationship between philosophy and science has been one that has been, you know, variously contentious, but also one that had a very tight genealogical relationship sometime, right? And so you may have people like, I don't know, Lawrence Krauss, who sort of see them as strongly opposed to one another. Whereas others like myself may recognize that all the sciences that we recognize today, one way or another, began as philosophies. And so like you were saying, like, when philosophy learns to ask the right questions, a new science is born.

• 2:56Speaker 02

  But when, so where do new philosophies come from? They might actually say when when tech new technologies force us to realize that the languages and concepts that we've been using to understand the world are inadequate or anachronistic. Moments like these, when philosophy, I think, becomes most useful in a creative and generative sense. Right? So it's less about how do I take these these concepts and apply them to new things? What would Hegel think about driverless cars? What would what would Kant say about this telescope? But rather, how do we generate the concepts to allow to bring something new? So Antikythera. Antikythera is named after the, what is probably apocryphally the first known computer was from 200 B C.

• 3:40Speaker 02

  It was discovered off the island of Antikythera in Greece in the beginning of the 20th century. And it took a really long time to figure out what it was. Because it was this intricate, complex geared mechanism that in the course of technological evolution. And I should say, I actually believe that technology evolves in a literal sense. It was completely anomalous. There wasn't a, you know, a sort of.

• 4:01Brian Keating?

  Predator technology.

• 4:02Speaker 02

  Yes, a predator sensor species before or after it went where.

• 4:05Brian Keating?

  iPhone version one, you know?

• 4:07Speaker 02

  Exactly, exactly. So what eventually was figured out that it was in fact a computational device. But in addition to being a device that allowed you to do basic mathematics, it also was an astronomical device. It allowed you to map your position in relationship to the stars and planets, not only in the present, but also in the past and future. So it was a kind of, you know, a temporal mapping device as well. Interesting. And so for us, thinking about how do we, what should be the foundation for a 21st century philosophy of computation? The idea that computation really begins, or artificial computation, I'll also make the argument that we discovered computation as much as we invented it. The foundational idea for computation that it orients intelligence in relationship to its planetary condition.

• 4:53Speaker 02

  As a starting point for what, not only what computation is, but ultimately what it's for, it was sort of the inspiration for this. And so the, I can talk a bit about the research program that we're, that we're sort of developing there, but to your question about what do we mean by planetary computation? More recently, I mean, zooming out from 200 B.C. to the, to the present time, the way in which we look at it is that we need to think about computation not only in terms of algorithms and mathematics and forms of calculation and inference, inference structures and so forth. And not only in terms of thinking of computation, in terms of what we recognize as computers, the kind of relatively energy inefficient appliances that we have managed to construct.

• 5:35Speaker 02

  But one, to think of, understand computation as a natural force in the universe, that informational system that the universe computes. And that we essentially have learned how to discover and tap into this. But a computer is no more computation than a light bulb is electricity. But to the planetary computation, over the last 50 years, arguably, you know, really beginning in the 1960s, artificial computation, artificial computational infrastructure has wrapped the globe. From subterranean data centers to oceanic, oceanic fiber optic cable, to the, the, you know, miraculous glowing glass rectangles that we all carry around in our pockets and still call phones, for some reason, to the satellites overhead.

• 6:20Speaker 02

  You could think of it this way. You know, the, the famous blue marble image, right? I just was speaking with Stuart Brandt a few, a few weeks ago. Imagine the blue marble image, not as a still image, but rather as a kind of super fast forward movie that sort of begin showing the whole several billion years of the evolution of Earth. What you'd see is this sort of goes from red to green to blue, the oxygenated life, appearance of atmosphere, Pangaea, all the rest. And in the very last few seconds, you would see something kind of remarkable, that this glowing blue orb would sprout

• 6:54Brian Keating?

  Start shooting them off.

• 6:55Speaker 02

  It would sprout this sort of

• 6:56Brian Keating?

  This extra

• 6:57Speaker 02

  Spraying into being Sensory exoskeleton. The way we see this is that's not only something that humans did very recently, ultimately, we need to see it as something that the planet done, that we have one planet, at least that we know of, that has evolved a mineral-based sensory organ that exists not only on its surface, but in its low Earth orbit, and that it uses to know things really fundamental about itself. So, for example, I would argue that when we ask the question, what contribution can planetary computation make to the mitigation of climate change, which is a perfectly reasonable question, we have to understand that the very idea of climate change as a scientific concept is an epistemological accomplishment of planetary computation in the first place.

• 7:41Brian Keating?

  The very entities that can comprehend and contribute to it.

• 7:43Speaker 02

  That's right.

• 7:44Brian Keating?

  It's symbiotic.

• 7:45Speaker 02

  That's, that's right. And so planetary computation, as we see it, is both something that allows intelligent life, in both, you know, human and non-human, arguably, in terms of AI, to do things that it wouldn't have been able to do, but it also allows us to know things that we wouldn't have known before. So for us, that's, that's the stakes. That's the stakes of this. And just as astronomy is arguably like the way in which the planet has folded itself into the shape of astronomers in order to know things about itself, it's all part of a similar kind of process of the emergence of what we may think of as a kind of planetary sapiens.

• 8:19Brian Keating?

  This just stimulates the seven podcasts worth of ideas in my mind. But you know, one of them that I love to tweet out every couple of months is, you know, kind of aping Einstein by saying, I don't know what with what, you know, what hardware, you know, ChatGPT five will run on, but ChatGPT six will run on an abacus, you know, basically, or an ATK, you know, whatever, I can't pronounce it. But the point being, you know, when we think about what AI is capable of, it seems to me there's almost this AI of the gaps, like whatever we think that AI or computation or planetary scale things can do, it can do everything that we don't understand. And that's kind of paradoxical because we don't actually fully understand the limits

• 9:01Brian Keating?

  of this technology, of the computational limits, except via physics. And the first guest on the podcast was Freeman Dyson, and you know, you're sitting in the seat basically that he was in. And the point that I'm, you know, kind of getting at is that are there ultimate limits, you know, to things like the singularity, to things like the simulation hypothesis, to global, not just planetary scale, but universal scale, or at least galaxy scale? Are there limitations that we can actually set right now on the probability, or the, let me, let me say, on the idea that this is an evolving system and that we're just one, one genus, you know, on the way to, you know, who knows where we're going to evolve to. But, but is it, is it not true that we may be, you know, both the creator of this tool

• 9:46Brian Keating?

  and its last users of it effectively?

• 9:48Speaker 02

  The first one, let me talk about the AI of the gaps. And I think there is a way in which the AI, trying to determine the status of AI, is it intelligent, is it not intelligent, does mirror the kind of god of the gaps, I'll give it. Think back to Turing's famous 1950 experiment. What Turing sets up is a highly functional definition of intelligence.

• 10:08Brian Keating?

  Right.

• 10:08Speaker 02

  But he also sets up one in which he asks, you cannot tell whether player A is a person or a computer, or actually says if it's a woman, which has an interesting valence in terms of his own biography. But then we have to grant that there's something going on, right? And so what he's positing is a sufficient condition of intelligence. Unfortunately, I think a lot of the ways in which Turing test has been incorporated at a culture level is more of as a necessary condition. That is, unless the AI can perform thinking the way that we think that we think, then it's disqualified.

• 10:39Brian Keating?

  It's a mirror of where we are.

• 10:41Speaker 02

  And so what that means is that there is a way in which the question is framed in a kind of either or opposition, that it's either human or AI, that the relationship between humans and AI is one of a boundary condition, that is, what humans are is what AIs are not, what AIs are is what humans are not. And so what you're beginning to see is first a kind of receding border, that more and more of the things that we may have said AI will never be able to do, it does, right? And so, you know, and, you know, people keep moving the goalposts as fast as they can possibly run to keep this, keep this going. But it also means that what it means to be human is defined in relationship to what we think AI is.

• 11:23Brian Keating?

  AI might be training us as much as we're training it, right?

• 11:26Speaker 02

  I don't think we've ever been in charge of our technologies. I think, you know, we've co-evolved with them from the very beginning.

• 11:31Brian Keating?

  Right.

• 11:31Speaker 02

  Now, to the other question, is there limits of, you know, limits of this as a larger computational thing? I don't know. It's a sort of a question, it's like, is there, is there a limit to how large and complex an informational structure can possibly become? Is there a limit to how much of a kind of, you know, intensive energy event you can, you know, artificially produce? And then you get back to, you know, Dyson Swarm kinds of questions, right? And you begin to scale things out to a galactic, a solar or even galactic scale, and you're asking, you know, what is Kardashev 2? How far are we from Kardashev 1? Kardashev 2, so forth and so on. I want to connect this with the, the gap and opposition problem. I don't see it as opposition. I don't see humans and technologies opposed. I see them deeply, the evolution of both is deeply intertwined.

• 12:15Speaker 02

  And so when I think about this, I don't know if you've read James Lovelock's last book, Nova Scene? Where Lovelock, of course, you know, posits the, you know, the Richard Guy hypothesis by which the emergence of simple life transform, terraform the planet to make the conditions for complex life, and that this is, this is this terraforming is an ongoing process. He concludes the book that like, with, you know, looking at the emerging and accelerating evolution of machine intelligence and says, this is a similar kind of phenomenon. And it's going to terraform the image in its own, you know, the Earth in its own image. But, you know, the, the book doesn't end on a pessimistic note. And it's not one of, well, we've had a good run, you know, we might as well, you know, drink the hemlock and, and be done with it.

• 12:57Speaker 02

  I think humans will survive really long, you'll continue to survive longer, but they won't, they won't necessarily be what we imagine them to be today. You know, I just think of it, all biological systems become, you know, I know you've had Sarah Walker on the show many times.

• 13:09Brian Keating?

  Yeah.

• 13:09Speaker 02

  All forms of, you know, complex biological systems become components in yet more complex systems.

• 13:14Brian Keating?

  That's right.

• 13:14Speaker 02

  Humans will persist. They've always been part of systems larger themselves, and they will continue to persist in systems larger themselves, some of which of their own making.

• 13:22Brian Keating?

  So one thing I've brought up in the past is that there's sort of this fallacy of iteration that, you know, there will come upon us AGI, and then it will do things that will be detrimental to humans. I'm just painting my very, very broad brush. And I think this fear is sort of misplaced. First of all, if it's as smart as us, which it has to be for super intelligent, it has to be smarter than us, right? But it will know at least that fact that we're concerned about it, AI, replacing us, right? So then it will be afraid, it will know that it's not the final evolution of its own technological advancement, right? I mean, presumably chat GPT, you know, infinity could exist the same way iPhone 18 is sure enough to come down the horizon as, as, you know, as the earth will make another lap around the sun, we hope. But, but the point being, if it, if we're smart enough to conceive of this as a challenge,

• 14:06Brian Keating?

  surely AI would say, well, look, this can either be a threat to me as an AI, or it could be something so beneficial, in which case I have to let it be created. In which case it's not a threat to humans to begin with, right? Because otherwise the AI wouldn't allow it to be created. How do you react to the kind of this solipsistic definition where, you know, the infinite regress of iteration, where eventually there's a final iteration, right? I mean, I always say a computer chip wasn't created with a computer chip, right? Um, by definition, an operating system wasn't created. They are now. No, no, but the original one, the first one. So I'd say the first AGI will not be created with an AI. I mean, there'll be some, some boundary if we get there. I'm not convinced on it.

• 14:42Speaker 02

  This is, you know, I am, you know, good, good thesis back to the sixties that the AI, if we make the true AGI, it'll be the last technology we ever make. Again, I don't, I see this as, you know, if you zoom out far enough, I see this really as a kind of a process that is continuous, but one that it can be, is marked by forms of, you know, of threshold events in the Maynard Smith sort of sense, um, punctuated equilibrium. But there are step functions in which. Complex forms of biological technological convergence, you know, have these moments where they radically increase in their information processing capacity, which was Leonard Smith's sort of key argument. I think we're in the middle of one. I don't think we're caught up to it paradigmatically. I think we're in a kind of pre-paradigmatic moment where then terms and concepts we use to even describe this, to recognize technological evolution is something we're part of.

• 15:27Speaker 02

  I think we have to grow into that very, very quickly. I don't think there's a final event, right? I'm not an eschatologist.

• 15:33Brian Keating?

  Right.

• 15:33Speaker 02

  I, you know, I think the future is much more contingent than it is, you know, that we are, there's certain path dependencies that are built into forms of convergent evolution. But for the most part, you know, it can go a lot of different ways. I think in the short term, the emergence of AGI, you know, I think we're seeing a kind of slow take up of that over the last few years. Is one's to be highly disruptive, really disruptive in terms of how, what an economy is, what a society is, how we relate to agents, AI agents that are trained on us and our relationships with simulations of ourselves as a fundamental tool. This is going to be beyond future shock. It's going to be a Copernican existential trauma. And it's going to be a really bumpy ride for a while.

• 16:18Brian Keating?

  For, especially for certain populations, right?

• 16:20Speaker 02

  Yeah, yes, but as, as you zoom out, I really kind of think of this as, is, is part of a, part of a larger process that can be mapped, that we can see ourselves inside of, to sort of understand that we have a certain degree of, you know, as a sapient species, we have a certain degree of, of agency. I mean, with the discovery of the Anthropocene is which is that we actually have, we actually can terraform the planet in a relatively short period of time. And we need to do it again in a way for to keep things going. That would discover forms of agency we didn't know that we had, but we're going to take a long time for us to mature into those, the subjectivities that are needed to actually have some degree of control over those things. So I'm optimistic in the long run and buckling up in the short run. We need the answer to the question.

• 17:02Brian Keating?

  As a professor and a podcaster and a scientist exploring the boundaries of knowledge in the lab, I crave independent sources of knowledge and wisdom wherever I can find them. One of my go-to sources is The Economist. I've been reading. Yet literally for decades, The Economist consistently delivers independent journalism for independent thinkers like you and me. But the best part for me is that their science coverage is nothing short of extraordinary. Just this past week, I was captivated by their deep analysis of the recent claims of quantum computing breakthroughs that could revolutionize how we process information, exactly the kind of forward-thinking coverage that I discuss on the podcast and that I crave to expand my own intellectual horizons. The Economist's rigorous approach cuts through the noise and BS in a way that you can truly

• 17:47Brian Keating?

  trust. And what sets The Economist apart is their Simply Science Weekly Newsletter. It's a subscriber-only exclusive benefit. Each weekly edition delivers beautifully-written explorations of nature, technology, the cosmos, the human body, and all of this comes alongside stunning scientific photography selected and curated by their editors. I don't just do science. I love to explore complex ideas. The Economist analysis is a perfect complement. It provides the insight and clarity needed to navigate challenging intellectual terrain with confidence. And to get everything The Economist offers, The Economist is offering a special 20% discount just for viewers of the Into the Impossible podcast. To claim the special 20% discount, visit economist.com/keating. Your pursuit of knowledge shouldn't end when this podcast ends.

• 18:31Brian Keating?

  The Economist ensures that it doesn't have to. I think you've written terraforming in this way in the context that you've described it as sort of an imperative. What did you mean by that? What does that mean?

• 18:41Speaker 02

  Um, yeah, it's a book I wrote. It was really an essay that became a book that got translated very quickly. There's a longer version of this book that's going to be coming out with MIT Press next year called The Terraforming. And the argument, in a nutshell, is that we need to think of terraforming of the Earth, not terraforming not of Mars, or something to make those other planets habitable for Earth-like life, but the terraforming of Earth to ensure that Earth remains a viable host for Earth-like life.

• 19:08Brian Keating?

  Right.

• 19:09Speaker 02

  And so you could think of, really, there are three terraformings, I think, that are relevant here. One is Thinking about what Krutzen and others called the Anthropocene as a kind of planless, headless terraforming initiative that we fundamentally transformed the planet. Now, you know, now we call it Anthropocene event, it is supposed to an era, fire, but that it was a terraforming scale event and that you were born inside of it, that we were all born inside of a terraforming event and that's like, welcome.

• 19:36Brian Keating?

  And meteorites, right?

• 19:37Speaker 02

  The second terraforming is the one that's inevitably going to happen no matter what we do, that we could all go full Unabomber tomorrow and the ongoing effects in relationship to everything from oceans to land use to planetary geochemistry is going to, the momentum will outlast us. And the third one is potentially the more deliberate process by which open-ended, non-falsifiable questions like what kind of planet should we make? Where should the people go? How do you get, what should be the cycle?

• 20:09Brian Keating?

  Income, deep utopia?

• 20:11Speaker 02

  Deep utopia needs to be defined, but it needs to be designed and composed. And I think to your question, like, what is the role of machine intelligence within that? I think it's probably quite clear that there's a lot, but it also may be quite nonlinear. But anyway, that's what I mean by the terraforming.

• 20:24Brian Keating?

  How much is AI, at least these LLMs, I mean, the L, you know, for language? It seems to me that is incredibly powerful. Humans are language machines. It's how we, you know, establish dominance and how we preserve technology, science, the culture through language, but it's not all we do, right? You could say that you might be able to code mathematics and physics in terms of a language, but it's different from the types of language that these LLMs are trained on. For example, yes, they can be trained on my PhD thesis, but what I'm getting at is the type of science, say, just restricting it to a search for a so-called theory of everything.

• 21:02Speaker 02

  Yeah.

• 21:02Brian Keating?

  How AI is or is not going to be capable of that. For example, I don't think it's a matter of prompting. I don't think it's a matter of the corpus of training data that is precluding AI from right now, coming up with a theory of everything that Edward Witten and, you know, all of our friends that we know and love here and beyond have been unable to do. I don't think that relies on the same, you know, Space, you know, dot products and matrix manipulations that have been locked in effectively by the confluence of GPUs and, you know, matrix algebra and neural networks. In other words, there could be, I'm not saying there is, but what if there is a fundamental difference in the types of language, if you will, that we use to communicate and so forth, that these LNs are uniquely, you know,

• 21:46Brian Keating?

  well qualified, they're already IQ 100, 120 in every subject matter from law to medicine and so forth. But so far, you know, the stubbornness of, say, finding a theory of everything or discovering some missing matter, the constituents of missing matter, is that going to permanently evade at least LNs? And because we're so invested heavily into it, we're locked into LNs as far as the eye can see. I mean, there's almost no, you know, there are alternatives, but they're not at scale of $300 billion, you know, valuations, et cetera. And I just don't think that the thing preventing us from getting a theory of everything is the fact that the latest, greatest generation of Grok or whatever hasn't been trained on the Fast and the Furious, you know, 12.

• 22:30Brian Keating?

  In other words, is there something uniquely different about some types of what humans can do that may, will make us preserve what we do uniquely in perpetuity?

• 22:39Speaker 02

  To the last question for sure, to the last question for sure. Like, again, I don't think it is necessarily should be, there's a limit to thinking about this as a replacement dynamic, right? I think that in the long run, AI will teach us what thinking is as much as we will teach it how to think. That the demonstration of another substrate of intelligence, you know, like the planet Solaris was another substrate of intelligence, that we can compare ourselves to and understand where we fit within this larger spectrum, I think is part of the understanding that'll come to this. But in terms of the more specific questions you get there, like, you're right. I think there's, there's good reasons why it turned out language was the path. You know, Hasseba said bet on games because he was a chess prodigy. And so for him, games was going to be the path.

• 23:22Speaker 02

  And it turned out, actually, language is a repository of all different kinds of intelligences. It's something that evolves over time and something that speaks its users more than the users speak it. That you producing a kind of a model that is able to think and to respond to the world generatively using language was a shortcut that shouldn't really be that surprising in hindsight. First of all, the L L M's are evolving very, very quickly, right? I mean, just there were no real, the kind of reasoning models that we see today just didn't exist a while ago. And so I think L L M's will evolve into other things that would be unrecognizable to what they are today. But you're right, language isn't the only thing. I think in a way, you know, the model, whether models can be trained, I mean, anything can be tokenized, right?

• 24:05Speaker 02

  Now, what models are constructed on like that which can be tokenized, which could be anything, principle, right? And that is made into something, a kind of language in a way. And so I think the movement, you know, Fei Fei Lee's new startup is about spatial intelligence. Yann Le Cun at Meta is focusing on spatial intelligence and

• 24:23Brian Keating?

  He, I should say, is quite pessimistic about, you know,

• 24:25Speaker 02

  He is.

• 24:25Brian Keating?

  The organization.

• 24:26Speaker 02

  He is. I'm just focusing particularly on the spatial dynamic of the question, which suggests that all these implications of spatial intelligence models for robotics. And, you know, Hubert Dreyfus's old critique of A I is that it can't really, we're going to work, because it's not embodied, it doesn't have embodied phenomenological experience. Well, like, that's no longer the case. The physicalization of A I, where you've got spatial models and linguistic models that are together interacting with the world and ultimately, in the long run, through forms of active inference, that where their experience is retraining the model almost in real time, then you have a kind of, a different kind of takeoff that may take this in a really different direction.

• 25:02Brian Keating?

  Yeah.

• 25:03Speaker 02

  The second, but the second, but the limit.

• 25:04Brian Keating?

  Yeah.

• 25:05Speaker 02

  While you were speaking, I was reminded of a, I should say, Anticathira also has a journal that we edit with M I T Press in a book series. First book in the series is a book called What is Intelligence by Blaise Aquari Arcas, from who I work with also at Google Research, at Google, fantastic book. Another piece that we're publishing in the journal later this year is a piece by the, who you may know, Risa Weschler at Stanford.

• 25:26Brian Keating?

  That's a good name.

• 25:27Speaker 02

  Yeah.

• 25:27Brian Keating?

  She's on the Simon's Observatory in Columbia.

• 25:29Speaker 02

  That's right. And so Risa's doing a piece for us on the role of computational simulations in her work and then the simulations as a kind of epistemic technology. And I don't want to like, you know, oversimplify the point, and I'm sure I will. But I mean, Risa would say that one of the reasons that we, you know, can't figure out exactly what dark matter, dark energy is, is we don't have the compute. That if you think about, if you think about all the available computation on Earth at this moment, like you network everything together into one giant machine, let's call that one unit of planetary compute as of 2025. How many units of planetary compute would be necessary to produce a simulation at a granular resolution sufficient enough to make, you know, important conclusions about the nature of the earth?

• 26:11Brian Keating?

  People say the same thing about the weather, you know, simulating climate.

• 26:14Speaker 02

  But yeah, so Risa would say like, no, there actually is like, like a brute, there is a, like a brute force scale to scientific ontology. The more compute, the more you know.

• 26:24Brian Keating?

  Right.

• 26:25Speaker 02

  That would be one answer to your question. Like, is, is there a way in which, are there things that we can't know, even if we had a lot of compute? Probably.

• 26:32Brian Keating?

  Yeah.

• 26:33Speaker 02

  Are there things that we don't know, that if we had orders of magnitude and more compute, we could know for sure?

• 26:38Brian Keating?

  Yeah. One thing that is, you know, sort of, you know, fascinating to me, and you did bring it up, and I brought it up many times, is, you know, this, the famous statement by Einstein that an observer in free fall would experience no gravitational force.

• 26:51Speaker 02

  Such a lovely thought.

• 26:52Brian Keating?

  It is, and he called it his happiest thought. He called it the thought that titillated him more than any other thought he ever had. But that brings up, you know, the exact, you know, topic that, that you hinted at before, which is embodiment. To what extent can a computer have happy thoughts? You know? And to what extent can it experience this early or no? Even robotics with a, you know, with a gyroscopic sensor and attitude indicators and inertial reference, you know, laser gyro, even such a device, can it visualize what you're, you know, my toddler can visualize is going on a roller coaster, driving over a bump, and that feeling in the pit of your stomach? And was that not, you know, the sine qua non that allowed Einstein to have the happiest thought, as he called it? So these two things. Can they have happy thoughts? If so, can they have painful thoughts?

• 27:36Brian Keating?

  Do we have ethical requirements and imposition on us as their programmers? And then when they exceed us? And then, second of all, can they do it truly without embodiment? Are there things that, that are, you know, to use? Get the gentleman that you mentioned, but this is something I've thought about a lot. Do we need this?

• 27:51Speaker 02

  Was a philosopher.

• 27:53Brian Keating?

  I think Chomsky had a similar.

• 27:54Speaker 02

  Berkeley in the seventies. Yeah.

• 27:56Brian Keating?

  Yeah.

• 27:56Speaker 02

  He wrote a famous book called What Computers Can't Do, which was a really important critique of sort of Simon era good old fashioned AI. And and kind of laid the philosophical foundations for what Brooks picked up later as a kind of bottom up model. So your question about is there can a sufficiently advanced form of machine intelligence have?

• 28:15Brian Keating?

  Yeah, enough.

• 28:15Speaker 02

  Valence.

• 28:16Brian Keating?

  Mm hmm. Yeah.

• 28:17Speaker 02

  Can it feel bad or good for something to happen to it?

• 28:20Brian Keating?

  Qualia that we experience, right?

• 28:22Speaker 02

  I wouldn't say qualia. I you said valence. Okay. Yeah, I'm more on the Dennett side than the the Chomsky side of that one.

• 28:27Brian Keating?

  Dennett was again, his final interview. Yeah. It's almost a year ago.

• 28:31Speaker 02

  His his biography, his latest autobiography. It's like fantastic. But they had it can't can it have valence? I think is an interesting question. I I think it would be a mistake to presume too quickly that it can't. And I just the lesson, I think, to learn there is how badly Western philosophy underestimated the the the complexity of animal intelligence. You know, as early as 20th century, you have people saying animals can't feel pain.

• 28:54Brian Keating?

  Pain, right. Bentham.

• 28:56Speaker 02

  Even before today, we would think is insane, right? And so I get now you have this, you know, just in the 20th century, you had this very interesting convergence of neuroscience, human neuroscience and AI, where they're sort of bouncing back between each other and even neuroscience and flow, you know, the churchlands here, for example, where this this feedback loop between AI models and and the way we should thought about this was was very important. I think now you've got one between studies in animal cognition and studies in machine cognition, where it's a kind of comparative non-human mind studies. That's very, very interesting. So you've got people like Peter Godfrey Smith, who are looking at, you know, cephalopod intelligence. I think you have to think this is a kind of parallel discourse with what how would we know? How would we test? Like, this is a real question.

• 29:36Brian Keating?

  Right.

• 29:37Speaker 02

  There's a couple, you know, a couple of people that I have collaborated with, Winnie Street, who was part of the Antichrist Program, her colleague in this group, Paradigms of Intelligence, where I'm a visiting faculty researcher at Google, another Jeff Keating philosopher. All their work is on, how would we know exactly the answer to this question?

• 29:52Brian Keating?

  Right.

• 29:53Speaker 02

  And if we don't know, what are the, what are the rules by which we, you know, may have learned from animal welfare, uh, sort of standards by which we might apply this as well? It's an open question, but I think it's one that will become increasingly, increasingly relevant. But I think it's a different question to the real justice. It's, I, first of all, I think AI is embodied. It's just embodied not in a test or fetal body plan. It doesn't have a stomach, so it doesn't have a pit in its stomach. But I, I think there's a limit to anthropomorphization in that, like, to the extent to which we cannot, we are frustrated in our attempts to fully anthropomorphize it. That's not the same thing as suggesting that, you know, across this different substrate it may have other kinds of things. Like, there may be forms of pain and pleasure that it can perceive that we cannot perceive, and vice versa, and that's fine.

• 30:38Brian Keating?

  That sensation may, you know, may not be the critical, you know, quantity. It may just be one.

• 30:43Speaker 02

  It's a different, right. Yeah, I think it's important.

• 30:44Brian Keating?

  And many other scientists don't have any sort of physical and, you know, uh, embodiment of it. That's what I'm saying. Yeah, yeah. I mean, some of the, uh, you know, theories of mine before we go on to, you know, think about, do artificial intelligence feel pain or whatever? We have to look at our own colleagues and understand, you know.

• 31:00Speaker 02

  How do they feel?

• 31:01Brian Keating?

  Yeah, now, I mean, what is painful about not getting, you know, failing in an experiment or not getting some data or predicting something that's small.

• 31:07Speaker 02

  If I, you know, you, you know, I, very simply, you know, more simply, you know, Demosio's work on the importance of emotion and these kinds of things and, you know, constructions of other fortunes. I, I think what we call, I think the distinction between emotional and rational intelligence is probably overblown.

• 31:20Brian Keating?

  Mm-hmm.

• 31:21Speaker 02

  Um, and don't see any reason why we wouldn't, the forms of valence would not be able to operate across different kinds of substrate, even beyond just simple knee-jerk reward systems.

• 31:30Speaker 00

  Now, more than ever, we need someone on our side. But Rob Whitman? Whitman's votes drove up costs, cut Medicaid, and risked 350,000 Virginians' healthcare to pay for tax breaks for himself and his donors. He's not on our side. Shannon Taylor will fight corruption, cut taxes, and bring down costs. This November, vote for Shannon Taylor. She's for us. Paid for by HMP, the HouseMajorityPact.com. Not authorized by any candidate or candidate's committee.

• 32:01Brian Keating?

  So you you mentioned, just in some conversations we had before this, we were talking about planetary, you know, data centers and computation, some work you're doing with Google. Can you explain a little bit more for the audience? What does that involve? And what interests does Google have in other planets?

• 32:15Speaker 02

  I mean, there's some of it, I can't, you know, there's some things that are being worked on, I probably can't talk too much, I can't talk too much about. But I I would say that, like, you think about the idea, what I suggested before, that has to do with, if you think about all of the aggregate computation that exists on the planet now, versus how much exists on the planet 10 years ago, versus how much exists on the planet 50 years ago. Clearly, we're in a kind of, you know, exponential spike, uh, in terms of the amount of, you know, the complexity of, you know, the amount of capacity for artificial information processing, which is something that, you know, we turns out very good at, you know. As I say, like, the fire apes have figured out how to make the rocks think.

• 32:53Brian Keating?

  You say bark rocks, right?

• 32:54Speaker 02

  We take bits of rocks and minerals, and we electrocute them just so, and the the other rocks can do things that only primates could do, which is, you know, big news.

• 33:01Brian Keating?

  Yeah.

• 33:02Speaker 02

  But if you begin to think about, you know, where this goes in the long run, you know, what is 10x planetary compute, 100x planetary compute, 1000x planetary compute, which are all kinds of things that we may see in our lifetime.

• 33:14Speaker 02

  You probably will see orders of magnitude increases in efficiency, you in terms of, you know, from neuromorphic chips to to other kind of algorithms that make, you know, the amount of energy that goes in for a certain unit of compute dramatically, a certain of it. But you also see, you know, all of the platforms buying up every available electricity contract they can find, starting up Three Mile Island. And so it turns out AI may be the economic solution to nuclear energy. So you think like, okay, AI is what's driving the economy of nuclear energy. GPUs is what's driving the economy of AI, and Fortnite was driving GPUs. And so if I, it transfers Fortnite is saving.

• 33:47Brian Keating?

  It's saving the world.

• 33:50Brian Keating?

  But a Minecraft, it could even be.

• 33:51Speaker 02

  From Minecraft, yes. But if you really get to like, okay, now we're beginning to, we're not quite Carters have won, but we're we're getting, we we're we're closer, it becomes a relevant question. Of like, what, how would a planet make functional use of the available energy that it has?

• 34:09Brian Keating?

  And not only minerals and so forth. So it brings up a chance for me to give you your gift of appearing in person on the podcast. This is a genuine meteorite. So this is a fragment on the early solar system, about 4.3 billion years old, older than the Earth. I give them out on my website, briankeating.com/yt or slash list. But you're guaranteed to win one if you have a .edu email address like you do. And you're guaranteed to win one because you are such a gracious intellect in front.

• 34:37Speaker 02

  If you're a platform that operates at the scale of a state, which is what Google does, and you're thinking 50 years out, 100 years out about what, how you would in fact, power a thousand X or, you know, or is it 10,000 X version of the sort of thing? You begin to have crazy ideas about where you get the energy from, and I'll leave it at that.

• 34:58Brian Keating?

  Okay. Yeah, fair enough. And, and those are some of the most exciting things from a physicist's perspective, right? I mean, we'd love to tie into the late, great Freeman Dyson's ideas. But, but it does bring up not only energy, but also minerals and so forth. So the average enrichment of this metal is 100%. You know, it's basically pure iron, nickel, cobalt, very, you know, rare, you know, in terms of the overall crustal, you know, the composition of the earth. But, but by no means unique. And, and so some of the questions I have, at least about the planetary scale, maybe, we'll have to do a part two eventually about this. But on the trajectory of Earth's evolution, you know, is, is the, is the, I mean, is the planetary sapian, so to speak, that you talk about, is that truly, you know, is that meant literally or is that more metaphor? I'm asking for the following reasons.

• 35:41Brian Keating?

  We have a very Earth-like planet in a very habitable zone planet called Mars. And it's very close to us. It's completely barren, sterile. It had water on it, had water on it when life existed on the earth. And there's a phenomenon called panspermia. Fred Hoyle popularized it where planets exchange material and

• 35:58Speaker 02

  And it was genetic. Biological, I mean, like planets are not close systems.

• 36:01Brian Keating?

  That's right. They're exchanging continuously. And yet we see pretty much everywhere we look, Doug, and, you know, we stuck probes. We violated Mars in basically every way we could possibly do it for an hour. And we see no life. Now, that's not proof that life never existed. It's not proof that life couldn't exist in the future.

• 36:16Speaker 02

  That we recognize as life.

• 36:18Brian Keating?

  As we recognize as life.

• 36:19Speaker 02

  Always correct me whenever.

• 36:21Brian Keating?

  Right, not as we know it. Exactly. Wonderful. They look. So my question is, what would you look for? My colleagues upstairs that use Keck telescope, thirty meter telescope coming out in the next two years, UC project. What what sorts of techno, what would we look for to see planetary compute? My friend Adam Franks been on many times. He talks about, yeah, he talks about global warming as a techno signature, right? Agriculture, at least, right? What would we look for? What sort of techno, give my young viewers out there, listeners, some inspirational, what would you look for to validate or falsify this notion of planetary sapiens? How could we do it?

• 36:54Speaker 02

  What are the pieces that we're also publishing? I think their journal is a new piece by Sarah and Lee Cronin, her glauquer on, kind of like what, it's sort of the technological version of the question of life, we don't know it, like, how would we, if we, how would we find forms of technology on a word that we don't recognize as being earth-like?

• 37:11Brian Keating?

  Or natural technology.

• 37:12Speaker 02

  Or first, okay. So let me, let me make a, a sort of wild conjecture here, sort of for the end here as well. Is that one of the things about the pre-paradigmatic moment that we find ourselves in is that functional, is that functional definitions of life, like the one that Sarah and Lee developed, which is a kind of, you know, you've got this increasing complexity, componentization, one thing and not done instead of this, and our contemporary definitions of technology, which are also kind of evolutionarily, you know, Brian Arthur and this sort of like complexity inside of further complex, all technologies are built to previous technologies, so forth. And our definition of intelligence of this sort of system that's able to, you know, both auto-poetically and allo-poetically transform the world in a certain goal-directed way are starting to converge.

• 37:58Speaker 02

  One way to think about, that is, what we define as life in the Aristotelian sense, and we define as technology, we define as intelligence, are looking more like each other than they did before. I'm not saying they're all exactly the same thing, but they may in some respects be different ways of describing a set of very similar phenomena. And that may be the way we, what we may arrive at. So the difference between a techno signature and a, I mean, bio-signature is one thing. Signature of life is something else, right? I think in many ways. Technology, I don't think life needs to be biological. And I think that the fluns of technological evolution around us, which are evolutionary, that do follow these paths, is exemplary of that. I don't mean hypothetically, life doesn't need to be biological. I think we're surrounded by non-biological life and always have, always

• 38:43Speaker 02

  have been. So the difference between finding a signature of life and finding a techno-signature may be academic, maybe, maybe academic, but.

• 38:50Brian Keating?

  What's an example of a non-biological way?

• 38:52Speaker 02

  AI.

• 38:53Brian Keating?

  Okay, so I don't, literally, okay.

• 38:54Speaker 02

  Yeah, no, literally.

• 38:55Brian Keating?

  So you would consider that biolike?

• 38:56Speaker 02

  I've not to be studied in the biotom is light, but not alive, right? And so, and I keep trying to come up with a, sir, but there was a piece that was published in Noamio called AI is Life, where she makes a similar kind of argument here as well. So what would we look for? Let me think, let me try to think of what we were trying to fight this as well. One answer to the question is you may, it may be a kind of sampling problem where you need, it's not looking for a thing or a category of matter. You would be looking for a process of transformation over a longer period of time, where there's a state, a certain kind of state change.

• 39:26Brian Keating?

  Telelog.

• 39:27Speaker 02

  Or one, from one thing, from one thing to another, that may be the thing you want to find. Well, there's something that demonstrates sort of like moments of, moments of increasing complexity that were not there before. And this intensification of localized complexity may be the sign that there's something going on there that may be technological, maybe life, maybe something, maybe another thing we don't, we don't quite recognize. But I don't think, and I think, you know, a lot of the discussions in astrobiology, both official and non-official, let's say, seem to sort of concluding that, you know, what we think of as life is, is again, not a, not what we recognize life to be, and nor is it a kind of matter, potentially something like quite alien. It's still the same table of elements, right? There are.

• 40:09Brian Keating?

  Right, there are, there are any dotted periodic, right, there could be a dark periodic table.

• 40:13Speaker 02

  But what the substrate might be, we don't, we don't really know. But this is, to me, like, what's really wonderful about, you know, things like. Fermi paradox as a philosophical problem because they force you to think about what is the possible boundaries, what are possible conditions of what a civilization might be, what communication might be, sort of this, to me, this is, this is where science is doing good philosophy and hopefully philosophy can contribute to the science in an interesting way, too.

• 40:36Brian Keating?

  Yeah, I mean, as Galileo, my hero, said, that's not Galileo, that's Einstein, Galileo said, you know, he was a natural philosopher. And so he said, with his telescope, which is technology, he didn't invent it, but he perfected it for that time. He said that he had, quote, and I quote, and let's see if I can remember, I thus made irrelevant the disputations that have for generations vexed philosophers by his, in other words, by observing that the Milky Way was comprised of individual stars rather than this discrete, you know, flowing plasma, whatever, and certainly with the moon's surface that he was able to reveal that it wasn't this idealized thing. He was then instantiating a new hypothesis, right? That's what philosophy does. Now, he was a philosopher himself, except they called physicists

• 41:18Brian Keating?

  natural philosophers. But, but his ultimate goal, as he said, was to, you measure what's measurable and make measurable what is not yet so. So, yeah, I mean, vision in the, in the future, how could we develop a Drake equation, you know, for, for these technological biosapiens and these technological sapiens? Where does that fit in and kind of in, in your research profile? I mean, we didn't even talk about visual arts and, and so forth and, and speculative designing.

• 41:42Speaker 02

  He's seeing the alienated relationship.

• 41:44Brian Keating?

  That's fine. But that was originally, you know, what brought you here. And I think that there's, you know, your, your work on how, uh, the visual arts can influence philosophy and there could be the symbiosis between them in the past.

• 41:55Speaker 02

  Yeah, we started a new major here.

• 41:56Brian Keating?

  Yeah.

• 41:56Speaker 02

  Speculative design.

• 41:57Brian Keating?

  That's right.

• 41:58Speaker 02

  He's trying to bring together a kind of the creative, open-ended exploratory sort of approach of, of art studio, but starting with questions that are informed by what's going on in the labs around here.

• 42:09Brian Keating?

  Well, I'd be remiss if I didn't at least ask one question about the stack. You've got it there. You brought it. You're so kind to bring it. Tell me about the stack and the upcoming reprint or second edition.

• 42:17Speaker 02

  There's a newsletter up here.

• 42:18Brian Keating?

  Yeah.

• 42:19Speaker 02

  To the can. There you go, Marshall. There's a 10th anniversary of it coming out later. So this was a book that I wrote 20, here at UCSD. It was a book that I came here to write. It was published in 2016 originally. And then I was making, what was that? At that point, I was making was a kind of somewhat science fiction sort of argument. Was that what we recognize as planetary computation was transforming the entire structure, political geography in its image. That the emergence of planetary computation was transforming this relationship between technology and state, between the political and governance, and that the forms of geopolitical dynamics that we would see over the next coming years would be fought over the competition to produce large VAC systems, to model societies through these large VAC systems.

• 43:04Speaker 02

  And again, by then, this was a bit kind of trippy of unconscious. And now it's sort of taken for granted. I think that was just kind of obvious, from chimp wars to everything else. The other argument, though, is that we can see this thing called planetary computation not as a single, undifferentiated mega machine in the way in which Lewis Mumford might have thought of it, but rather as something that is literally like a stack. It is comprised of modular functionally defined layers, where the earth, cloud, city, address, interface, user, that each have their own dynamic, each have their own sort of process, each is replaceable by different kinds of technological systems, and becomes a kind

• 43:44Speaker 02

  of schema by which from energy sourcing to service provision to, you know, the images that we use to make sense of that system.

• 43:52Brian Keating?

  Waste, excruciating, to the interface that's right.

• 43:55Speaker 02

  That it becomes a kind of discontinuous, accidental megastructure. That's what we have produced. And so the book is the story of where that came from, how you build a society with it, what its integral accidents are, and indeed, more importantly, how we think about the stack to come. Because the great thing about stack systems is they're designed to be replaced. And that is, Theseus is infrastructure.

• 44:14Brian Keating?

  That's right.

• 44:14Speaker 02

  So that's what the book is all about.

• 44:17Brian Keating?

  I was thinking yesterday, it was good that, you know... Didn't burn the ships when it came to Thessus. But also, I can't, I can't think it was an accident that the vice president recently made a, made a mention of, of the stack or maybe not specifically of the book, but, but I think he's been

• 44:30Speaker 02

  AI stack.

• 44:31Brian Keating?

  AI stack, which is a component of what the book is.

• 44:34Speaker 02

  I'm not going to take any clue with it, but I, I, it, it's interesting to see how sometimes

• 44:38Brian Keating?

  Percolated to the zeitgeist.

• 44:40Speaker 02

  How it's helped circulate. That's right. And that's, I mean, that, you know, to me, I mean, so maybe I'll just put this, you know, make this last point. I think the relationship between philosophy and technology is traditionally, at least in the 20th century, be one that's like been quite hamstrung by different, you know, from, let's say, the Heideggerian school of thought, which always seen, saw technology as sort of the enemy of deep thinking. As the thing that, that withdrew us or alienated us from being. I think the Galileo example that you show is like, no, it's actually through the alienation of technology, of perception, to getting outside our, our whole century, this is like, through technology that we know who we are, where we are, when we are, any of these kinds of things. It's always this epistemic role of, of technology. Now our fundamental technologies are computational.

• 45:23Speaker 02

  Then we need to protect it all. We need to protect it at, at all, at all cost. One, I should say, we are also, there's also curating an exhibition at the Venice Architecture Biennale this May. One of the artifacts that we're presenting, well, two artifacts I'll mention are presenting there. One is an original copy of the Harmonia, Harmonia macrocosmica from 1662, that 17th century astronomical atlas. And another is an image from 1966 called the lunar orbiter image, which was the first picture of Earth taking a fall.

• 45:51Brian Keating?

  Orbiter, right?

• 45:52Speaker 02

  Which is kind of forgotten these days, but it was on the front page of every newspaper in 1966, but blue marble kind of right. Came, came, came and took the glory. This was also the, an image that was shown to the German philosopher Heidegger, who was sort of the, you know, a founding figure, 20th century philosophy and technology for, for mostly worse in my mind. And he looked at this image and said, in his typically hyperbolic fashion, we don't need nuclear weapons because this image has already destroyed the world. And what he means by this is that the world of a kind of intuitive understanding of the horizon is flat. That, you know, I am located in this sort of egocentric kind of like that. Everything operates according to a kind of a Trivian scale.

• 46:33Speaker 02

  The basis of a kind of phenomenological essentialism was now forever exploded. That innocence was gone.

• 46:39Brian Keating?

  Could not right unsee it, could not.

• 46:41Speaker 02

  So I agree with that. I just see this as more as like, um, the point, a feature, not a bug, let's say. Um, and so I would invite your viewers to come to Venice and see for themselves.

• 46:51Brian Keating?

  Don't need many excuses to go out and see the original Doge where the original Doges were hanging out. Uh, Ben Braden, so great to meet you, not to meet you, but to be with you in person again. And to, uh, hopefully be the first of many conversations.

• 47:04Speaker 02

  I will do that.

• 47:04Brian Keating?

  Thank you, man. Awesome.