[0:00]So if I'm right, there is no theory of everything. We tend to operate on the sonorous promise that the world is understandable. Plato called it the logos. Newton built his mechanics on it. Even I, Curt Jaimungal, with this channel, explicate theories of everything which assumes this intellibility. Stuart Kauffman, one of the founders of complexity theory, says this assumption is egregiously incorrect. Kauffman actually finds a parallel to ancient Chinese philosophy. The Dao that can be expressed is not the eternal Dao. The biosphere that can be described is not the biosphere that will become. Toward the end of this conversation, Stuart Kauffman outlines some speculation on quantum gravity. He believes non-locality rules out string theory, loop quantum gravity, and even the holographic principle. He maps von Neumann entropy to spatial distance, deriving de Sitter space from entanglement. Don't worry, all of these technicalities are explained in the podcast itself. Now, whether this whole topic admits requires independent verification. But the biology, that's been 63 years in the making. I'm excited to bring you one of the only ever recorded podcasts with someone who helped build complexity theory from scratch, invented random Boolean networks at 23. And helped found the Santa Fe Institute. Stuart Kauffman. What's the largest unsolved problem in complexity science? Getting beyond its utter dependence upon mathematics. Now, how's that for a strange response? Let me let me tell you about complexity theory. I know it well. I was, you know, I started doing it when I was 23. I'm 86, so that's 63 years ago. Let me tell you what the problem was then. We didn't know why different cells expressed different genes. And at that time, Jacob and Monod showed that one gene can make a protein that turns another gene off. Then they published a paper two years later, 63, showing, imagine you've got two genes, gene one represses gene two, gene two represses gene one, so it can have two states, one on, two off, one off, two on. So they solved a fundamental problem and got the Nobel Prize for it. So I took one of the early steps, Kurt, in inventing what became complexity theory. I wondered, no, it was obvious if there's, we thought 100,000 genes at the time. And I thought, well, what if there's 100,000 genes and they're turning one another on and off. And I asked the funny question. I asked, is there a class of networks and dynamics that would generically give rise to the order we see in ontogeny. That's an odd question. To ask it, you have to invent a class of networks. I invented random Boolean nets. So there's N binary variables, N genes. Each one receives inputs drawn at random from K genes. And each one realizes an arbitrary Boolean function on its K inputs. There's two to the two to the K Boolean functions. And then I studied the generic behavior of that ensemble of systems. It's really interesting, it turns out they're ordered, critical or chaotic. And critically behavior predicts lots of the behaviors of actual cells in differentiation. So that was one of the early birthings of complexity theory, published in 1969. "Temporary AI audio (original corrupted)" "Temporary AI audio (original corrupted)" "Temporary AI audio (original corrupted)"
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[4:51]So if affordances are truly indefinite, then how does natural selection find them without searching? Well, it's wonderful. Um,
