Speaker unverified: belief

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…he other. And this means that an ecology of functions is building up through massively parallel computation that becomes, if you like, more and more intelligent with every 1 of these of these fusions. And since symbiogenesis makes the computation massively parallel, that implies that intelligence and life are very, closely connected, which is why, you know, I ended up with the book What is Life? As part of the book What is Intelligence? When you're not only using that intelligence to model yourself, but also to model your environment, which by the way includes others most importantly, then that's intelligence and that means that life was intelligent from the start. And the moment that that modeling of others begins, what we call in in larger, more complex animals, theory of mind becomes fundamental to the way intelligence develops. So, you know, these are really simple simulations that show how, you know, just persistence allows, you know, the modeling of of of of an environment to turn into learning chemotaxis in these fake bacteria. But of course, you know, in real life, you're not only learning about an environment that that exists in isolation like the like the sugar crystal, but actually all of your friends. Right? The moment you're reproducing, the greater part of your environment is is actually all of your all of the other things that that, you know, even your own reproduction is creating. Life is never a single player. Things like intelligence explosions in our lineage in the hominins and in cetaceans, and in bats and in a variety of other species are exactly this kind of runaway modeling of others resulting in, growth of brains and growth of of groups and and therefore that, you know, when we think about the growth of advanced intelligence, you know, in in in, you know, human societies or human brains, it's it's really that same sort of of symbiotic process happening at a much at a much higher level. Let's end there and and switch to, questions. I think there are, multiple different ways to represent the symbiotic. I think in the real biology, we maintain those hierarchical structures and that there are fundamental mathematical differences, how how you treat those embryos. And do you have any insight how we can implement that? Yes. In biology we often, sort of reify 1 particular level of detail and we say, you know, these are the life forms and, you know, maybe there's a symbiosis between, you know, let's say, you know, algae and a sea slug, but we still think of the algae and the sea slug as as separate and we think about population dynamics within that rather than modeling them separately, is there a reason to prefer 1 scale or another? You know, for me, 1 of the lessons, the reason that I spent so much time on the relationship between R and K is that you can always move something from 1 from from R to K and back. You know, Lin Margulis famously said we're just colonies of bacteria, you know, some of which live inside each other. And that's true. You know, you could describe us as just colonies of bacteria. But the reason that it's useful to to move up a level of detail is because, you know, humans also, you know, reproduce as a unit, you know, hence the METs, and and there are a lot of things that you can you can learn about when you study at that higher level, a lot of abstractions you can make from a computational perspective that are hard if you're only modelling at the lower level. So I don't think that there's any there's any 1 layered layer level that is true. And we have lots of boundary cases like lichen or like, colony insects, right, where you can model the entire colony or you can model the individuals. I don't think there's a right answer to those 2. So, you know, do you do you keep a block of rows and columns in R that are that are that are in, you know, that always end up or mostly end up getting copied together, or do you add a new row? You know, it's it's it's actually a a coarse graining choice and you can make either 1.…

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