natural selection produced systems with an extremely general intelligence (the learning algorithm of the human brain)
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evolution selects strongly for extremely general-purpose algorithms
Natural selection mostly produces rather narrow intelligences, and in this sense, the brains of humans (and other smart animals) are an outlier. Although I vaguely expect even bacterial cell biology to involve some computation-like stuff that would be difficult to train modern NNs to emulate veridically, especially when it comes to robustness of processes against various sorts of perturbations. A separate thing is the generality of evolution itself, if you frame it as an algorithm.
In general, I think I agree with your framing, but I would emphasize the component of slack / exploration lack of premature optimization.
@cdt, I don’t understand what it is that you don’t understand.
For the first 2 billion years of life’s existence on Earth, the planet was covered by unicellular slime. It took another ~billion for animals to emerge and a few more hundreds of millions for complex brains capable of more flexible, general behavior, within-lifetime learning, and so on.[1] It seems likely that had Chicxulub not killed off the non-avian dinosaurs (or substitute some other major catastrophic event), human-par general intelligence would not have evolved.
Thank you for taking the time to explain further. I had originally interpreted “narrow intelligence” strictly, but based on your lowest bar this would include the majority of animal biomass and the vast majority of its species.
I am not sure the extent to which contemporary species provide evidence for or against the algorithmic properties of evolved behaviour. I am also not sure how much ecological opportunity enables or prevents this. It’s a good question and one I have not read in the literature before.
What do you mean by “algorithmic properties of evolved behaviour”?
I am also not sure how much ecological opportunity enables or prevents this.
I think a lot. Given how long it took for humans to evolve and how this seems to have been enabled by a bunch of “random” events, like an asteroid wiping out the dinosaurs.[1]
“Reasonably impressively smart” animals are common and “easy to evolve”: cephalopods, corvids, parrots, elephants, primates, raccoons, cetaceans, elephantfish, etc. It seems to me that the three main things you need are (1) the/a right sort of body plan[2]; (2) a nearby niche that benefits from intelligence; (3) time to evolve intelligence (“niche stability”?). For something like humans to emerge, a greater number of unlikely factors have to align.
Although it’s possible that the Cretaceous extinction (and maybe some other major or minor extinctions too) was a type of event that is, in general, very likely to happen. Something like: you have “dumb”, more environmentally rigid macrofauna and “smart”, more environmentally flexible microfauna. At some point, you’re going to have a major ecological disruption, so the former mostly dies off, and the latter can fill in its niche. This seems like a plausibly common pattern. But I’m speculating.
It is hard to describe evolution as “fast” or “slow” without a yard-stick. Often slow relative to ecological time, perhaps, but I don’t understand the idea that 3 billion years to find learning is “slow”.
What do you mean by “algorithmic properties of evolved behaviour”?
It is not clear to me that the behavioural properties of contemporary species provide much information as to the capabilities of evolution or how fast it can reach certain behavioural adaptations. Strong evidence of possibility, weak evidence of speed, almost-no evidence of impossibility. Similarly, the stretch of time it took to make humanity and the events it took to reach there are not really evidence of any of the difficulty of human adaptations.
I can agree that it looks like certain adaptations appear together re: body plan, but “appearance of nearby niches” and “environmental(?) stability” are controlled mostly by ecological factors like distribution and dispersal. So perhaps ecological opportunity controls this more than I anticipated. One thing that struck me while reading your reply was that general learning seems energy-intensive, so it would be dependent on available resource flux from the ecosystem, and this would push the evolution of learning later in time. But again, this is more a claim about ecological factors, and it’s not clear to me what that says about “what natural selection produces” or “natural selection vs gradient descent”. Thanks for the interesting thoughts.
It is hard to describe evolution as “fast” or “slow” without a yard-stick. Often slow relative to ecological time, perhaps, but I don’t understand the idea that 3 billion years to find learning is “slow”.
Clock time is a perfectly valid yardstick. An adaptation that takes evolution a few thousand/million years to find can be found much more quickly by a competent team of human biologists.
Another valid yardstick would be something like computational efficiency or even more generally efficient use of resources (other than time, which I just covered). Natural selection proceeds via blind generate-and-test.[1] With something like AlphaFold, you can do better.
I can agree that it looks like certain adaptations appear together re: body plan
It sounds to me like you misinterpreted what I was saying about the body plan. I meant (/ I should have taken time to clarify) that you need some sort of basic pre-adaptation (vaguely analogous to pre-training an LLM) to make use of such an opportunity, and one such pre-adaptation is having a body that is generally agile/adaptive and can evolve into even more adaptive forms capable of exploiting new niches. Compare arthropods vs earthworms.
but “appearance of nearby niches” and “environmental(?) stability” are controlled mostly by ecological factors like distribution and dispersal. So perhaps ecological opportunity controls this more than I anticipated.
Yep.
One thing that struck me while reading your reply was that general learning seems energy-intensive, so it would be dependent on available resource flux from the ecosystem, and this would push the evolution of learning later in time.
Yeah, that (or more generally, intelligence being expensive) is why you sometimes see lineages “reverting” to less intelligent/brainy forms, e.g., proto-molluscs into mussels. I think also sea squirts.
But again, this is more a claim about ecological factors, and it’s not clear to me what that says about “what natural selection produces” or “natural selection vs gradient descent”.
Yeah, so the claim can be refined to: It’s unusual for ecological factors to produce conditions favorable for high intelligence, especially given that it’s not even one specific condition, but rather a series of ecological conditions[2] that hand-holdably lead a lineage into a form at which it starts being capable of reshaping its environment into a stable form favorable to its survival.
Although what new genetic variants it can generate at any given point depends on the current genotype and genotypes may tend to get selected for being better at spawning potentially useful mutations (in the context of the rest of the genome being held constant), cf. https://en.wikipedia.org/wiki/Evolvability#Evolution_of_evolvability. So, it is “blind”, but, in a sense, it slowly refines its “priors” or “generative biases”.
Not necessarily a unique series of ecological conditions. It seems very unlikely that there’s only one rough ecological-evolutionary pathway to general intelligence.
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Natural selection mostly produces rather narrow intelligences, and in this sense, the brains of humans (and other smart animals) are an outlier. Although I vaguely expect even bacterial cell biology to involve some computation-like stuff that would be difficult to train modern NNs to emulate veridically, especially when it comes to robustness of processes against various sorts of perturbations. A separate thing is the generality of evolution itself, if you frame it as an algorithm.
In general, I think I agree with your framing, but I would emphasize the component of slack / exploration lack of premature optimization.
@cdt, I don’t understand what it is that you don’t understand.
For the first 2 billion years of life’s existence on Earth, the planet was covered by unicellular slime. It took another ~billion for animals to emerge and a few more hundreds of millions for complex brains capable of more flexible, general behavior, within-lifetime learning, and so on.[1] It seems likely that had Chicxulub not killed off the non-avian dinosaurs (or substitute some other major catastrophic event), human-par general intelligence would not have evolved.
cf. “complex active bodies”, i.e., arthropods, cephalopods, and vertebrates, as the lowest bar
Thank you for taking the time to explain further. I had originally interpreted “narrow intelligence” strictly, but based on your lowest bar this would include the majority of animal biomass and the vast majority of its species.
I am not sure the extent to which contemporary species provide evidence for or against the algorithmic properties of evolved behaviour. I am also not sure how much ecological opportunity enables or prevents this. It’s a good question and one I have not read in the literature before.
What do you mean by “algorithmic properties of evolved behaviour”?
I think a lot. Given how long it took for humans to evolve and how this seems to have been enabled by a bunch of “random” events, like an asteroid wiping out the dinosaurs.[1]
“Reasonably impressively smart” animals are common and “easy to evolve”: cephalopods, corvids, parrots, elephants, primates, raccoons, cetaceans, elephantfish, etc. It seems to me that the three main things you need are (1) the/a right sort of body plan[2]; (2) a nearby niche that benefits from intelligence; (3) time to evolve intelligence (“niche stability”?). For something like humans to emerge, a greater number of unlikely factors have to align.
Although it’s possible that the Cretaceous extinction (and maybe some other major or minor extinctions too) was a type of event that is, in general, very likely to happen. Something like: you have “dumb”, more environmentally rigid macrofauna and “smart”, more environmentally flexible microfauna. At some point, you’re going to have a major ecological disruption, so the former mostly dies off, and the latter can fill in its niche. This seems like a plausibly common pattern. But I’m speculating.
I mean “body plan” to include “brain plan”.
It is hard to describe evolution as “fast” or “slow” without a yard-stick. Often slow relative to ecological time, perhaps, but I don’t understand the idea that 3 billion years to find learning is “slow”.
It is not clear to me that the behavioural properties of contemporary species provide much information as to the capabilities of evolution or how fast it can reach certain behavioural adaptations. Strong evidence of possibility, weak evidence of speed, almost-no evidence of impossibility. Similarly, the stretch of time it took to make humanity and the events it took to reach there are not really evidence of any of the difficulty of human adaptations.
I can agree that it looks like certain adaptations appear together re: body plan, but “appearance of nearby niches” and “environmental(?) stability” are controlled mostly by ecological factors like distribution and dispersal. So perhaps ecological opportunity controls this more than I anticipated. One thing that struck me while reading your reply was that general learning seems energy-intensive, so it would be dependent on available resource flux from the ecosystem, and this would push the evolution of learning later in time. But again, this is more a claim about ecological factors, and it’s not clear to me what that says about “what natural selection produces” or “natural selection vs gradient descent”. Thanks for the interesting thoughts.
Clock time is a perfectly valid yardstick. An adaptation that takes evolution a few thousand/million years to find can be found much more quickly by a competent team of human biologists.
Another valid yardstick would be something like computational efficiency or even more generally efficient use of resources (other than time, which I just covered). Natural selection proceeds via blind generate-and-test.[1] With something like AlphaFold, you can do better.
It sounds to me like you misinterpreted what I was saying about the body plan. I meant (/ I should have taken time to clarify) that you need some sort of basic pre-adaptation (vaguely analogous to pre-training an LLM) to make use of such an opportunity, and one such pre-adaptation is having a body that is generally agile/adaptive and can evolve into even more adaptive forms capable of exploiting new niches. Compare arthropods vs earthworms.
Yep.
Yeah, that (or more generally, intelligence being expensive) is why you sometimes see lineages “reverting” to less intelligent/brainy forms, e.g., proto-molluscs into mussels. I think also sea squirts.
Yeah, so the claim can be refined to: It’s unusual for ecological factors to produce conditions favorable for high intelligence, especially given that it’s not even one specific condition, but rather a series of ecological conditions[2] that hand-holdably lead a lineage into a form at which it starts being capable of reshaping its environment into a stable form favorable to its survival.
Although what new genetic variants it can generate at any given point depends on the current genotype and genotypes may tend to get selected for being better at spawning potentially useful mutations (in the context of the rest of the genome being held constant), cf. https://en.wikipedia.org/wiki/Evolvability#Evolution_of_evolvability. So, it is “blind”, but, in a sense, it slowly refines its “priors” or “generative biases”.
Not necessarily a unique series of ecological conditions. It seems very unlikely that there’s only one rough ecological-evolutionary pathway to general intelligence.