Evidence receipt / prediction
Published · transcript-backedKeith Duggar: prediction
10 Sept 2025 Machine Learning Street Talk Karl Friston - Why Intelligence Can't Get Too Large (Goldilocks principle)
“At which point, I think you would you would find it very difficult to find something that was intelligent in the sense we're talking about because we have to have this recurrence, this solenoidal aspect in order to revisit the states.”
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- Speaker
- Keith Duggar
- Attribution
- Verified speaker
- Claim type
- prediction
- Recorded
- 10 Sept 2025
- Publisher
- Machine Learning Street Talk
Transcript context
…So I think we're coming back now to the number of inner screens and the counterfactual depth and the definition of agency in the sense of strange things that we're talking about for this particular scale. So if we just read the scale as, if you like, the size of the mark off blanket. If within at this scale for this kind of thing there is a sufficient degree of complexity read specifically though in this instance as the counterfactual depth and breadth of your world model about the consequences of your action, that particular part of of of your implicit generative model. And that would happily accommodate the fact that when you get something, you know, something of the size or the scale of a virus, there just isn't the machinery of the space to entertain that in any nontrivial Right. In a nontrivial way. 1 could also argue, and I got a sense that you were arguing yourselves towards this, if you go too big, you also lose that. So, you know, this you know, coming back to this wonderful question, we have 8,000,000,000 intelligent, really intelligent sound like Trump there, didn't I? Entities constituting our biosphere. But is the biosphere, from the point of view of saying the hypothesis, is the biosphere in and of itself intelligent? And I would say no. Not because it's simply because at that scale the elemental, all the complexity of the constituent elements disappears at that scale. So, you know, it'd be a little bit like saying, well, let's just take it to the limit. Let's just take it to the astronomical limit of the motion of heavenly bodies. Now the motion of heavenly bodies is completely described by the position of the planets and the moon and the position of the earth. So at that scale you've averaged away the fact that the earth contains a biosphere and the biosphere contains human beings and human beings contain cells and the cells may or may not contain viruses depending upon who you've been exposed to. So there will be no intelligence at that level. So it's perfectly possible to have intelligence at a particular scale that disappears when you get too big and when you get too small. Another way of looking at that is going right back to things like brigadine and dissipative structures. You you're talking about complexity if you just think about how have people tried to understand complex systems and self organizing systems that are open. So we're not talking about twentieth century physics and equilibrium physics, we're talking about the physics of non equilibria and things that are in open exchange with each other. And of course you get to the notion of dissipative structures. What does that tell you mathematically? Well, what's not dissipative? That's a schoolboy question. Can you remember? You've probably forgotten. So what is not dissipative is conservative. Yeah. So I'm I'm sure I'm teasing it. So another gift of Helmholtz, of course, is that any dynamics can be partitioned into a dissipative part and a conservative part. not dissipative is conservative. Yeah. So I'm I'm sure I'm teasing it. So another gift of Helmholtz, of course, is that any dynamics can be partitioned into a dissipative part and a conservative part. And the dissipative part is that which rests upon very fast random complicated fluctuations of the kind you might find in say quantum mechanics or thermodynamics. Whereas the conservative part does not rely upon that and just goes round in circles basically. It's, you know, Literally it's called solenoidal flow, well conservative flow. So that basically means that dissipative structures have to have an admixture of this circular aspect, this conservative classical life cycles, reproduction, oscillations, plus random dissipative part that you'll find in things like thermodynamics and quantum mechanics, and that is definitional of dissipative structures. As you go too small, then everything becomes quantum and random. It all becomes probabilistic. There is no conservative stuff other than a scrotting of potential. At which point, I think you would you would find it very difficult to find something that was intelligent in the sense we're talking about because we have to have this recurrence, this solenoidal aspect in order to revisit the states. So you know a virus is a virus in order for there to be a non equilibrium steady state distribution as a solution to that. But as you get bigger and bigger and bigger, get to viruses and you're still not quite they're still not quite sort of complex enough to be intelligent in the way that we mean. And then you get to our size and that's perfect because we're both have both this dissipative. We deal with a random world, with an itinerant world and yet we keep revisiting states of being. So we have this sort of conservative bimimetic kind of self organization. But then you get bigger and bigger and bigger. You get to the level of the biosphere or size of the moon or the sun. And of course, by averaging all the random fluctuations go away. So you're just left with the solenoidal part. You're just left with the solenoidal motion, the Newtonian motion of classical mechanics. So 1 thing that really fascinates me about this is, however, it is possible for us when we do construct large scale things that are intelligent like a corporation. You know, a corporation is seen as like a super intelligence, but we're only able to do that by putting in structure. Right? That maintains this balance of of the dissipative and and conservative flow. Right? Like, we have to put in organizational structure so that it continue to function at these larger scales. Right? Like, isn't that pretty pretty interesting? I mean, it's it's again this yin and yang thing that we run into all the time. Right? Where it's the balance between 2 2 forces. Like, between, say, complete order and complete noise or between dissipation and conservation. And you have to be almost on the edge of chaos, and it has to have a certain causal structure in order for it to to be intelligent. No, I…
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