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The Surprising Mathematics Linking Brains and Galaxies · The Last Observer: Science and Beyond

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  Speaker 1: So to start off today, I want you to just
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  Speaker 1: imagine two completely different things.
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  Speaker 2: Okay, I'm with you.
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  Speaker 1: First, think about the human brain just resting right there
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  Speaker 1: inside your skull.
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  Speaker 2: Right weighing what about maybe one point four kilogram.
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  Speaker 1: Yeah, exactly, a little localized biological organ sitting completely in
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  Speaker 1: the dark. Now hold that thought and try to imagine
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  Speaker 1: the observable universe.
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  Speaker 2: That's quite a pivot.
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  Speaker 1: I know, right, But seriously, the universe hundreds of billions
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  Speaker 1: of galaxies stretching across billions of light years. It's almost
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  Speaker 1: entirely empty cold space.
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  Speaker 2: And we were talking about a size difference that is
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  Speaker 2: frankly absurd.
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  Speaker 1: It really is. It's a difference of twenty seven orders
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  Speaker 1: of magnitude. Your brain physically can't even model that kind
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  Speaker 1: of scale difference.
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  Speaker 2: No, it's mathematically beyond human intuition.
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  Speaker 1: But and this is our mission for today. This is
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  Speaker 1: what we're going to unpack. When you actually map out
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  Speaker 1: the large scale structure of the universe and you place
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  Speaker 1: it right next to a microscopic map of the brain's.
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  Speaker 2: Neurons, the resemblance is uncanny.
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  Speaker 1: It's beyond uncanny. The patterns of dense clusters connected by
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  Speaker 1: these long branching filaments. They are structurally identical.
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  Speaker 2: Yeah, and the immediate reaction is usually, you know, extreme skepticism,
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  Speaker 2: which makes sense, it does. I mean, comparing biological tissue
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  Speaker 2: to gravitational superstructures sounds a lot like.
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  Speaker 1: Apafenia, wait aia, like seeing faces in.
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  Speaker 2: Clouds exactly, the human tendency to just project meaningful patterns
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  Speaker 2: onto totally random noise.
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  Speaker 1: Right, because we want things to make sense.
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  Speaker 2: Yeah, but researchers didn't just look at pictures and say, hey,
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  Speaker 2: these look similar. They stripped everything down to the raw
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  Speaker 2: mathematical architecture.
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  Speaker 1: And that's what we're diving into today. Are we looking
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  Speaker 1: at a cosmic coincidence or is there some universal underlying
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  Speaker 1: rule governing how complexity emerges in nature?
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  Speaker 2: Well, to really get into that, we have to establish
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  Speaker 2: what's actually happening at both of these extremes.
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  Speaker 1: Let's start small. Let's start with a microscale. The human brain.
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  Speaker 2: It's arguably the most complex object we've ever income.
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  Speaker 1: Right, We're talking about roughly eighty six billion neurons.
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  Speaker 2: But the sheer number of neurons is almost well a distraction.
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  Speaker 2: How so, because the real magic, the actual processing architecture,
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  Speaker 2: is all in the connections, the synaptic junctions.
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  Speaker 1: Ah right, how they talk to each other.
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  Speaker 2: Exactly. You're looking at hundreds of trillions of connections, and
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  Speaker 2: they are absolutely not just randomly wired together, because if
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  Speaker 2: they were random, it would be chaos, right, it would
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  Speaker 2: be incredibly inefficient. The brain is housed in a very
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  Speaker 2: strict physical space, the cranium.
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  Speaker 1: Not a lot of room to expand in there.
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  Speaker 2: No, and it's relentlessly constrained by metabolism. Like we said earlier,
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  Speaker 2: it runs on just twenty watts of power.
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  Speaker 1: Which is literally the power of a dim refrigerator light bulb.
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  Speaker 1: It's crazy.
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  Speaker 2: It is so because biological tissue is really expensive to
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  Speaker 2: build and maintain. The brain can't just wire every single
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  Speaker 2: neuron to every other neuron.
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  Speaker 1: Right, Your head would have to be the size of
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  Speaker 1: hot air balloon.
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  Speaker 2: And you'd have to eat that thousands and thousands of
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  Speaker 2: calories every hour just to keep it running.
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  Speaker 1: So evolution has to force a compromise.
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  Speaker 2: Exactly, It forces what neuroscientists call a small world network.
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  Speaker 1: Okay, let's unpack that. What makes it a small world network?
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  Speaker 2: Well, you have these dense, hyper local hubs. Imagine tiny
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  Speaker 2: neighborhoods of neurons that are massively interconnected with their immediate neighbors, so.
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  Speaker 1: They handle very specific, specialized local tasks.
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  Speaker 2: Yes, but local processing isn't enough. Your visual cortex need
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  Speaker 2: to be able to talk to your motor cortex instantly.
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  Speaker 1: Right, if you see a baseball flying at your face,
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  Speaker 1: you need to move your hand to catch it precisely.
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  Speaker 2: So to bridge those gaps, the brain uses these thick
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  Speaker 2: bundles of nerve fibers, mylinated axons acting as long haul
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  Speaker 2: super highways.
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  Speaker 1: It totally reminds me of how we design airline route maps. Oh,
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  Speaker 1: that's a perfect analogy, right, Because Delta doesn't fly direct
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  Speaker 1: jet from a tiny dirt runway in rural Montana to
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  Speaker 1: a tiny town in France.
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  Speaker 2: The fuel costs alone would bankrupt them, exactly.
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  Speaker 1: They build a Hubb and s Bogue model. You take
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  Speaker 1: a short regional flight to a massive local hub like Atlanta,
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  Speaker 1: and from Atlanta you take a massive, efficient long haul
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  Speaker 1: flight to another megahub like Paris, and then disperse locally again.
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  Speaker 2: Yeah, that architecture minimizes wiring or in your analogy, fuel
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  Speaker 2: and planes while maximizing communication speed. At any note, is
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  Speaker 2: just a few hops away.
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  Speaker 1: Okay, so that makes perfect sense for biology. It's the
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  Speaker 1: pinnacle of biological efficiency, it is. But then we jump
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  Speaker 1: to the macro scale, the entire universe.
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  Speaker 2: And biological evolution means absolutely nothing at this scale.
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  Speaker 1: Right, completely irrelevant. We have to rewind to the Big.
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  Speaker 2: Bank and the inflationary epoch immediately following it. The universe
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  Speaker 2: was just this ridiculously hot, dense plasma.
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  Speaker 1: But it wasn't perfectly smooth, was it.
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  Speaker 2: No, it had these tiny microscopic quantum fluctuations, little variations
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  Speaker 2: and energy density, and.
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  Speaker 1: Over billions of years, gravity basically took those tiny ripples
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  Speaker 1: and amplified them exactly.
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  Speaker 2: As the universe expanded and cooled, gravity which is a
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  Speaker 2: relentlessly attractive force, started pulling matter toward the slightly denser areas.
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  Speaker 1: Which eventually created the cosmic web.
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  Speaker 2: Yes, it's not a random scatter of stars and galaxies.
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  Speaker 2: Almost everything in the universe lies along these gigantic branching filaments.
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  Speaker 1: Filaments that span hundreds of millions.
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  Speaker 2: Of light years, connecting massive galaxy clusters and leaving behind
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  Speaker 2: these vast empty cosmic voids.
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  Speaker 1: But there's a huge catch here. Most of this structure
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  Speaker 1: isn't even made of regular matter.
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  Speaker 2: No, about eighty five percent of it is invisible dark matter.
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  Speaker 1: And this is where I always get stuck. If dark
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  Speaker 1: matter doesn't interact with light, if it's literally invisible scaffolding,
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  Speaker 1: how do we know it actually forms this web.
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  Speaker 2: It's a great question. We can't see it, but we
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  Speaker 2: can see its gravity.
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  Speaker 1: So we measure the pole.
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  Speaker 2: Yeah, we use weak gravitational lensing. Dark matter is incredibly massive,
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  Speaker 2: so it actually bends the fabric of space time around.
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  Speaker 1: It like a bowling ball on a trampoline exactly.
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  Speaker 2: And when light from distant galaxies passes through those bend areas,
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  Speaker 2: the image we see on Earth is slightly distorted.
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  Speaker 1: So by looking at millions of these warped images, we
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  Speaker 1: can reverse engineer where the invisible mass has to be.
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  Speaker 2: You've got it. That combined with massive supercomputer simulations, ah.
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  Speaker 1: Right, simulating thirteen point eight billion years of gravity.
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  Speaker 2: We program in the laws of physics, start with the
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  Speaker 2: early universe and let it run. The resulting structure perfectly
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  Speaker 2: matches the observations.
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  Speaker 1: Okay, So we have this simulated universe on one hand
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  Speaker 1: and a brain scan on the.
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  Speaker 2: Other, and if you scale them so they're the same size.
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  Speaker 1: The visual match is just wild. But we established earlier
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  Speaker 1: that looking similar isn't enough to prove anything, right, We.
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  Speaker 2: Have to look at the underlying math, which brings.
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  Speaker 1: Us to modern network theory.
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  Speaker 2: Yes, the science of nodes and links.
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  Speaker 1: Let's map this out clearly. In the brain, the nodes
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  Speaker 1: are what the neurons.
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  Speaker 2: The neurons are the localized brain regions, yes, and the
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  Speaker 2: links are the synapses connecting them.
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  Speaker 1: Okay.
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  Speaker 2: And in the universe, the nodes are the massive galaxy
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  Speaker 2: clusters and the links are those cosmic filaments of dark
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  Speaker 2: matter and gas connecting them.
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  Speaker 1: Now, when researchers actually ran the statistics on both of
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  Speaker 1: these systems, they looked at specific mathematical metrics.
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  Speaker 2: They did things like degree distribution, clustering coefficients, and path links.
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  Speaker 1: Wait, let me translate those really quickly so we don't
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  Speaker 1: lose anyone. Degree distribution is basically just asking how many
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  Speaker 1: friends does this particular node have compared to the others.
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  Speaker 2: Yes, exactly how connected is it?
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  Speaker 1: And path length is just how many jumps does it
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  Speaker 1: take to get a message from one side of the
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  Speaker 1: network to.
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  Speaker 2: The other spot on, And they also looked at centrality
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  Speaker 2: and network efficiency, and.
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  Speaker 1: The overlap between the two systems.
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  Speaker 2: Was it was incredibly tight. Statistically, the similarities are undeniably real.
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  Speaker 1: Which is mind blowing. But I want to throw it
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  Speaker 1: in a massive caveat here, just so we are completely clear.
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  Speaker 1: Please do We are absolutely not saying that neurons are.
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  Speaker 2: Galaxies, Oh, definitely not. The physics are entirely different.
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  Speaker 1: Right, One is electrochemical biology, the other is cosmological gravity.
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  Speaker 2: The similarity is entirely in the mathematics of how networks
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  Speaker 2: organize themselves.
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  Speaker 1: But why why would totally different physical systems obey the
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  Speaker 1: exact same mathematical principles.
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  Speaker 2: It all comes down to how nature handles.
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  Speaker 1: Energy self organization.
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  Speaker 2: Precisely simple local interactions generating highly complex global patterns without
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  Speaker 2: any central boss telling them what to do.
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  Speaker 1: And we see this everywhere, don't we. It's not just
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  Speaker 1: brains and galaxies.
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  Speaker 2: Oh, it's ubiquitous river systems, lightning strikes, the way trees branch.
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  Speaker 1: Out, blood vessels in our bodies.
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  Speaker 2: Fungal networks in the soil, even human made things like
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  Speaker 2: transportation systems or the Internet.
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  Speaker 1: They all naturally evolve toward this same architecture.
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  Speaker 2: Because it is the optimal way to manage constraints.
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  Speaker 1: Right, let's talk about those constraints. The brains constraint is
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  Speaker 1: that twenty want limit.
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  Speaker 2: Yes, it has to minimize unnecessary biological wiring while maintaining
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  Speaker 2: trillion of operations a second.
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  Speaker 1: And the universe is constraint gravity.
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  Speaker 2: Gravity naturally channels matter along the shortest, most dynamically stable roots.
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  Speaker 2: It avoids keeping matter in a uniform.
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  Speaker 1: Even fog because an even fog of matter is inherently unstable.
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  Speaker 2: Exactly any tiny bump causes it to collapse, so it
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  Speaker 2: falls into these highly efficient pathways.
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  Speaker 1: I just love the beauty of this. Whether the rule
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  Speaker 1: is save biological energy or follow gravitational physics, nature eventually
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  Speaker 1: converges on the exact same geometry.
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  Speaker 2: It's the ultimate solution to the problem of efficiency.
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  Speaker 1: And the crazy thing is this mathematical convergence doesn't just
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  Speaker 1: happen at one specific size.
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  Speaker 2: No, it repeats itself across multiple scales.
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  Speaker 1: Which is the definition of a fractal.
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  Speaker 2: Yes, patterns that repeat similar structures no matter how close
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  Speaker 2: or far away you zoom it.
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  Speaker 1: Like snowflakes yeah, or the edge of a coastline.
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  Speaker 2: Or romanesquco broccoli. Those perfect repeating little spirals.
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  Speaker 1: Or how fern leaves have tiny leaves that look exactly
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  Speaker 1: like the big leaf exactly.
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  Speaker 2: Now we should clarify neither the brain nor the universe
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  Speaker 2: is a perfect infinite mathematical fractal.
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  Speaker 1: Right, because eventually you zoom in so far you hit
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  Speaker 1: an atom, you run out of physical space.
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  Speaker 2: But they both exhibit what we call scale invariant characteristics
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  Speaker 2: over a really significant range of sizes.
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  Speaker 1: Meaning, if you zune in on a cluster of galaxies,
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  Speaker 1: the smaller groups inside it look statistically similar to the
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  Speaker 1: supercluster as a whole.
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  Speaker 2: Yes, And the reason nature allies on factals is that
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  Speaker 2: it is the ultimate hack for maximizing coverage.
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  Speaker 1: Right, You get the most bang for your buck.
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  Speaker 2: You maximize the area you can reach while minimizing the
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  Speaker 2: material you have to use.
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  Speaker 1: Okay, So, if the whole point of this structure is
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  Speaker 1: to be hyper efficient, what exactly is moving through these networks?
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  Speaker 2: Well, this is where the systems diverge significantly.
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  Speaker 1: Because in the brain, it's electrical signals.
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  Speaker 2: Yes, action potentials constantly traveling through circuits real time communication.
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  Speaker 1: But in the cosmic web, galaxies aren't sending electrochemical signals
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  Speaker 1: to each other.
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  Speaker 2: Now in the cosmos, it's the flow of physical matter
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  Speaker 2: and thermal energy gas, dark matter, magnetic fields, cosmic rays.
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  Speaker 2: They are preferentially funneled along the dark matter filaments flowing
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  Speaker 2: into the galaxy clusters.
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  Speaker 1: Okay, but I read that researchers actually use information theory
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  Speaker 1: to describe both systems.
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  Speaker 2: They do.
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  Speaker 1: Okay, Wait, let's pause right here, because if information theory
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  Speaker 1: applies to both and they look identical, are we implying
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  Speaker 1: that the universe is like thinking?
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  Speaker 2: Ah, and there is the trap.
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  Speaker 1: It's a massive philosophical trap.
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  Speaker 2: It really is. It's so easy to jump to the
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  Speaker 2: conclusion that the universe is conscious or that it's functioning
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  Speaker 2: as some giant cosmic computer.
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  Speaker 1: It sounds like sci fi, but I can see why
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  Speaker 1: people go there.
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  Speaker 2: I get it too. But we have to firmly state
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  Speaker 2: there is absolutely zero scientific evidence that the universe possesses consciousness.
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  Speaker 1: Right. No experiment has ever shown that a galaxy cluster
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  Speaker 1: has memory or intentions none.
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  Speaker 2: The issue is that human evolve to be exceptional pattern recognizers.
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  Speaker 1: It's how we surviveed spotting the tiger of.
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  Speaker 2: The bushes exactly. But it also means our brains are
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  Speaker 2: highly prone to seeing meaningful intent where there is none.
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  Speaker 1: So when researchers say they are measuring information in the universe,
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  Speaker 1: what do they actually mean?
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  Speaker 2: They mean thermodynamic information. Information theory can quantify how physical
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  Speaker 2: states change regardless of biology.
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  Speaker 1: Oh like the exact position and velocity of gas particles.
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  Speaker 2: Right when gas falls down a filament and heats up,
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  Speaker 2: its physical state changes. That can be mathematically modeled as
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  Speaker 2: information processing.
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  Speaker 1: But doesn't mean it's having a thought exactly.
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  Speaker 2: While the similarities in the network geometry are mathematically genuine,
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  Speaker 2: similarity of architecture does not imply identity of function.
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  Speaker 1: Going back to the river analogy, a branching river basin
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  Speaker 1: and the blood vessels in my arm look totally identical.
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  Speaker 2: They use the same fractal math.
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  Speaker 1: Yes, and they both distribute fluids. But a river isn't
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  Speaker 1: pumping blood to a giant geological heart.
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  Speaker 2: That's the perfect way to look at it. Similarity is optimization,
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  Speaker 2: not identity.
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  Speaker 1: So to really appreciate this we have to look at
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  Speaker 1: the fundamental differences. Let's talk about time scales.
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  Speaker 2: The time scales completely shatter any idea of a cosmic mind.
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  Speaker 1: How fast does the brain work milliseconds.
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  Speaker 2: For consciousness to emerge, you need ultrafast dynamic feedback loops.
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  Speaker 2: The system has to constantly adapt.
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  Speaker 1: But the universe is bound by the speed of light.
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  Speaker 2: Right. If an event happens at one end of a
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  Speaker 2: cosmic filament, the gravitational ripple takes hundreds of millions of
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  Speaker 2: years just to reach the next note.
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  Speaker 1: So a single signal back and forth one feedback loop
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  Speaker 1: could take half.
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  Speaker 2: A billion years, and the universe is only thirteen point
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  Speaker 2: eight billion years old. There literally hasn't been enough time
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  Speaker 2: for the macro network to think a single thought.
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  Speaker 1: Plus the whole dark matter aspect.
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  Speaker 2: Right, eighty five percent of the cosmic scaffolding relies on
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  Speaker 2: a particle that the biological brain entirely lacks, and.
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  Speaker 1: Neural networks evolve through genetics and natural selection to survey.
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  Speaker 2: I have in a hostile environment, while the cosmic web
• 14:03
  Speaker 2: is just gravity blindly acting on initial quantum conditions, no environment,
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  Speaker 2: no survival pressure.
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  Speaker 1: Okay, so they are physically wildly different. But even with
• 14:13
  Speaker 1: all those differences, this mathematical overlap is turning out to
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  Speaker 1: be incredibly useful, isn't it.
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  Speaker 2: Oh, it's driving major breakthroughs understanding efficient biological networks has
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  Speaker 2: already transformed technology.
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  Speaker 1: Like artificial intelligence.
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  Speaker 2: Yes, artificial neural networks were directly inspired by the human brain.
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  Speaker 2: We copied the microscale blueprint to build machine learning.
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  Speaker 1: But now we're using supercomputers to simulate both the brain
• 14:38
  Speaker 1: and the cosmos.
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  Speaker 2: And researchers across entirely different fields neuroscientists, astrophysicists, computer scientists
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  Speaker 2: are collaborating, which.
• 14:45
  Speaker 1: Is so rare. Usually those fields never talk to each.
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  Speaker 2: Other, but now they share the same statistical tools, and
• 14:51
  Speaker 2: they're asking could the principles of the cosmic web inspire
• 14:54
  Speaker 2: new types of computers?
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  Speaker 1: Because AI is incredibly energy hungry right now, extremely so
• 15:00
  Speaker 1: if we can design computational architectures based on how dark
• 15:04
  Speaker 1: matter efficiently routes energy across the cosmos, we might solve
• 15:08
  Speaker 1: our own energy bottlenecks. It is amazing to me that
• 15:12
  Speaker 1: studying the billions of light years of empty space might
• 15:15
  Speaker 1: actually help us build a better, greener computer chip right
• 15:19
  Speaker 1: here on Earth.
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  Speaker 2: It's a beautiful synergy.
• 15:22
  Speaker 1: So as we wrap up this exploration, what's the grand takeaway?
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  Speaker 2: The profound realization isn't that your brain is some miniature universe?
• 15:30
  Speaker 1: Right We firmly debunk that.
• 15:31
  Speaker 2: The takeaway is that nature repeatedly discovers elegant, mathematically identical
• 15:36
  Speaker 2: solutions to the problem of organizing complexity.
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  Speaker 1: It doesn't matter if you are wiring together neurons, clustering
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  Speaker 1: together galaxies, or growing a fungal network under the soil.
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  Speaker 2: Complexity itself obeys universal rules that transcends scale entirely.
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  Speaker 1: Mathematics really is nature's universal language.
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  Speaker 2: It's the underlying bedrock of reality.
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  Speaker 1: And that leads to a really provocative final thought for
• 15:58
  Speaker 1: everyone listening.
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  Speaker 2: Where are we going with this?
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  Speaker 1: Well, think about what we as humans are building right now.
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  Speaker 2: The global digital infrastructure exactly, the Internet, satellite networks, global
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  Speaker 2: financial markets.
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  Speaker 1: We are aggressively building this massive, chaotic network of billions
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  Speaker 1: of nodes.
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  Speaker 2: All trying to optimize the flow of data and energy.
• 16:19
  Speaker 1: Without any central architect It's self organizing. So if nature
• 16:24
  Speaker 1: universally relies on these specific network structures to optimize flow across.
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  Speaker 2: All scales, it's mathematically inevitable.
• 16:31
  Speaker 1: Right will our global digital infrastructure, or even the structure
• 16:34
  Speaker 1: of human society itself inevitably evolve to mirror the exact
• 16:37
  Speaker 1: same architecture of the cosmos In the human mind.
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  Speaker 2: It's a staggering thought. The topology might be inescapable.
• 16:43
  Speaker 1: Keep questioning the patterns you see in the world around you,
• 16:46
  Speaker 1: because the rules governing the stars are the exact same
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  Speaker 1: rules firing in your head right now