The only way to transmit information from one generation to the next is through evolution changing genomic traits, because death wipes out the within lifetime learning of each generation.
This is clearly false. GPT4, can you explain? :
While genes play a significant role in transmitting information from one generation to the next, there are other ways in which animals can pass on information to their offspring. Some of these ways include:
Epigenetics: Epigenetic modifications involve changes in gene expression that do not alter the underlying DNA sequence. These changes can be influenced by environmental factors and can sometimes be passed on to the next generation.
Parental behavior: Parental care, such as feeding, grooming, and teaching, can transmit information to offspring. For example, some bird species teach their young how to find food and avoid predators, while mammals may pass on social behaviors or migration patterns.
Cultural transmission: Social learning and imitation can allow for the transfer of learned behaviors and knowledge from one generation to the next. This is particularly common in species with complex social structures, such as primates, cetaceans, and some bird species.
Vertical transmission of symbionts: Some animals maintain symbiotic relationships with microorganisms that help them adapt to their environment. These microorganisms can be passed from parent to offspring, providing the next generation with information about the environment.
Prenatal environment: The conditions experienced by a pregnant female can influence the development of her offspring, providing them with information about the environment. For example, if a mother experiences stress or nutritional deficiencies during pregnancy, her offspring may be born with adaptations that help them cope with similar conditions.
Hormonal and chemical signaling: Hormones or chemical signals released by parents can influence offspring development and behavior. For example, maternal stress hormones can be transmitted to offspring during development, which may affect their behavior and ability to cope with stress in their environment.
Ecological inheritance: This refers to the transmission of environmental resources or modifications created by previous generations, which can shape the conditions experienced by future generations. Examples include beaver dams, bird nests, or termite mounds, which provide shelter and resources for offspring.
(/GPT)
Actually, transmitting some of the data gathered during the lifetime of the animal to next generation by some other means is so obviously useful that is it highly convergent. Given the fact it is highly convergent, the unprecedented thing which happened with humans can’t be the thing proposed (evolution suddenly discovered how not to sacrifice all whats learned during the lifetime).
Evolution’s sharp left turn happened because evolution spent compute in a shockingly inefficient manner for increasing capabilities, leaving vast amounts of free energy on the table for any self-improving process that could work around the evolutionary bottleneck. Once you condition on this specific failure mode of evolution, you can easily predict that humans would undergo a sharp left turn at the point where we could pass significant knowledge across generations. I don’t think there’s anything else to explain here, and no reason to suppose some general tendency towards extreme sharpness in inner capability gains.
If the above is not enough to see why this is false… This hypothesis would also predict civilizations built by every other species which transmits a lot of data e.g. by learning from parental behaviour—once evolution discovers the vast amounts of free energy on the table this positive feedback loop would just explode.
This isn’t the case ⇒ the whole argument does not hold.
Also this argument not working does not imply evolution provides strong evidence for sharp left turn.
What’s going on?
In fact in my view we do not actually understand what exactly happened with humans. Yes, it likely has something to do with culture, and brains, and there being more humans around. But what’s the causality?
Some of the candidates for “what’s the actually fundamental differentiating factor and not a correlate”
- One notable thing about humans is, it’s likely the second time in history a new type of replicator with R>1 emerged: memes. From replicator-centric perspective on the history of the universe, this is the fundamental event, starting a different general evolutionary computation operating at much shorter timescale.
- Machiavellian intelligence hypothesis suggests that what happened was humans entered a basin of attraction where selection pressure on “modelling and manipulation of other humans” leads to explosion in brain sizes. The fundamental thing suggested here is you soon hit diminishing return for scaling up energy-hungry predictive processing engines modelling fixed-complexity environment—soon you would do better by e.g. growing bigger claws. Unless… you hit the Machiavellian basin, where sexual selection forces you to model other minds modelling your mind … and this creates a race, in a an environment of unbounded complexity.
- Social brain hypothesis is similar, but the runaway complexity of the environment is just because of the large and social groups.
- Self-domestication hypothesis: this is particularly interesting and intriguing. The idea is humans self-induced something like domestication selection, selecting for pro-social behaviours and reduction in aggression. From an abstract perspective, I would say this allows emergence of super-agents composed of individual humans, more powerful than individual humans. (once such entities exist, they can create further selection pressure for pro-sociality)
or, a combination of the above, or something even weirder
The main reason why it’s hard to draw insights from evolution of humans to AI isn’t because there is nothing to learn, but because we don’t know why what happened happened.
I think OP is correct about cultural learning being the most important factor in explaining the large difference in intelligence between homo sapiens and other animals.
In early chapters of Secrets of Our Success, the book examines studies comparing performance of young humans and young chimps on various congnitive tasks. The book argues that across a broad array of cognitive tests, 4 year old humans do not perform singificantly better than 4 year old chimps on average, except in cases where the task can be solved by immitating others (human children crushed the chimps when this was the case).
The book makes a very compelling argument that our species is uniquely prone to immitating others (even in the absense of causal models about why the behaviour we’re immitating is useful), and even very young humnans have inate instincts for picking up on signals of prestige/compotence in others and preferentially immitating those high prestige poeple. Imo the arguments put forward in this book make cultral learning look like a very strong theory better in comparison to Machieavellian intelligence hypothesis, (although what actually happend at a lower level abstraction probably includes aspects of both).
Note that this isn’t exactly the hypothesis proposed in the OP and would point in a different direction.
OP states there is a categorical difference between animals and humans, in the ability of humans to transfer data to future generation. This is not the case, because animals do this as well.
What your paraphrase of Secrets of Our Success is suggesting is this existing capacity for transfer of data across generations is present in many animals, but there is some threshold of ‘social learning’ which was crossed by humans—and when crossed, lead to cultural explosion.
I think this is actually mostly captured by …. One notable thing about humans is, it’s likely the second time in history a new type of replicator with R>1 emerged: memes. From replicator-centric perspective on the history of the universe, this is the fundamental event, starting a different general evolutionary computation operating at much shorter timescale.
Also … I’ve skimmed few chapters of the book and the evidence it gives of the type ‘chimps vs humans’ is mostly for current humans being substantially shaped by cultural evolution, and also our biology being quite influenced by cultural evolution. This is clearly to be expected after the evolutions run for some time, but does not explain causality that much.
(The mentioned new replicator dynamic is actually one of the mechanisms which can lead to discontinuous jumps based on small changes in underlying parameter. Changing the reproduction number of a virus from just below one to above one causes an epidemic.)
OP states there is a categorical difference between animals and humans, in the ability of humans to transfer data to future generation. This is not the case, because animals do this as well.
There doesn’t need to be a categorical difference, just a real difference that is strong enough to explain humanities sharp left turn by something other than increased brain size. I do believe that’s plausible—humans are much much better than other animals at communicating abstractions and ideas accross generations. Can’t speak about the book, but X4vier’s example would seem to support that argument.
Jan, your comment here got a lot of disagree votes, but I have strongly agreed with it. I think the discussion of cultural transmission as source of the ‘sharp left turn’ of human evolution is missing a key piece.
Cultural transmission is not the first causal mechanism. I would argue that it is necessary for the development of modern human society, but not sufficient.
The question of “How did we come to be?” is something I’ve been interested in my entire adult life. I’ve spent a lot of time in college courses studying neuroscience, and some studying anthropology. My understanding as I would summarize it here:
Around 2.5 million years ago—first evidence of hominids making and using stone tools
Around 1.5 million years ago—first evidence of hominids making fires
Around 300,000 years ago (15000 − 20000 generations), Homo sapiens arises as a new subspecies in Africa. Still occasionally interbreeds with other subspecies (and presumably thus occasionally communicates with and trades with). Early on, homo sapiens didn’t have an impressive jump in technology. There was a step up in their ability to compete with other hominids, but it wasn’t totally overwhelming. After outcompeting the other hominids in the area, homo sapiens didn’t sustain massively larger populations. They were still hunter/gatherers with similar tech, constrained to similar calorie acquisition limits.
They gradually grow in numbers and out-compete other subspecies. Their tools get gradually better.
Around 55,000 years ago (2700 − 3600 generations), Homo sapiens spreads out of Africa. Gradually colonizes the rest of the world, continuing to interbreed (and communicate and trade) with other subspecies somewhat, but being clearly dominant.
Around 12,000 years ago, homo sapiens began developing agriculture and cities.
Around 6,000 years ago, homo sapiens began using writing.
From wikipedia article on human population:
Here’s a nice summary quote from a Smithsonian magazine article:
For most of our history on this planet, Homo sapiens have not been the only humans. We coexisted, and as our genes make clear frequently interbred with various hominin species, including some we haven’t yet identified. But they dropped off, one by one, leaving our own species to represent all humanity. On an evolutionary timescale, some of these species vanished only recently.
On the Indonesian island of Flores, fossils evidence a curious and diminutive early human species nicknamed “hobbit.” Homo floresiensis appear to have been living until perhaps 50,000 years ago, but what happened to them is a mystery. They don’t appear to have any close relation to modern humans including the Rampasasa pygmy group, which lives in the same region today.
Neanderthals once stretched across Eurasia from Portugal and the British Isles to Siberia. As Homo sapiens became more prevalent across these areas the Neanderthals faded in their turn, being generally consigned to history by some 40,000 years ago. Some evidence suggests that a few die-hards might have held on in enclaves, like Gibraltar, until perhaps 29,000 years ago. Even today traces of them remain because modern humans carry Neanderthal DNA in their genome.
And from the wikipedia article on prehistoric technology:
There are some key defining characteristics. The introduction of agriculture resulted in a shift from nomadic to more sedentary lifestyles,[35] and the use of agricultural tools such as the plough, digging stick and hoe made agricultural labor more efficient.[citation needed] Animals were domesticated, including dogs.[34][35] Another defining characteristic of the period was the emergence of pottery,[35] and, in the late Neolithic period, the wheel was introduced for making pottery.[36]
So what am I getting at here? I’m saying that this idea of a homo sapiens sharp left turn doesn’t look much like a sharp left turn. It was a moderate increase in capabilities over other hominids.
I would say that the Neolithic Revolution is a better candidate for a sharp left turn. I think you can trace a clear line of ‘something fundamentally different started happening’ from the Neolithic Revolution up to the Industrial Revolution when the really obvious ‘sharp left turn’ in human population began.
So here’s the really interesting mystery. Why did the Neolithic Revolution occur independently in six separate locations?!
Here’s my current best hypothesis. Homo sapiens originally was only somewhat smarter than the other hominids. Like maybe, ~6-year-old intelligences amongst the ~4-year-old intelligences. And if you took a homo sapiens individual from that time period and gave them a modern education… they’d seem significantly mentally handicapped by today’s standards even with a good education. But importantly, their brains were bigger. But a lot of that potential brain area was poorly utilized. But now evolution had a big new canvas to work with, and the Machiavellian-brain-hypothesis motivation of why a strong evolutionary pressure would push for this new larger brain to improve its organization. Homo sapiens was competing with each other and with other hominids from 300,000 to 50,000 years ago! Most of their existence so far! And they didn’t start clearly rapidly dominating and conquering the world until the more recent end of that. So 250,000 years of evolution figuring out how to organize this new larger brain capacity to good effect. To go from ‘weak general learner with low max capability cap’ to ‘strong general learner with high max capability cap’. A lot of important things happened in the brain in this time, but it’s hard to see any evidence of this in the fossil record, because the bone changes happened 300,000 years ago and the bones then stayed more or less the same. If this hypothesis is true, then we are a more different species from the original Homo sapiens than those original Homo sapiens were from the other hominids they had as neighbors. A crazy fast time period from an evolutionary time point, but with that big new canvas to work with, and a strong evolutionary pressure rewarding every tiny gain, it can happen. It took fewer generations to go from a bloodhound-type-dog to a modern dachshund.
There are some important differences between our modern Homo sapiens neurons and other great apes. And between great apes vs other mammals.
The fundamental learning algorithm of the cortex didn’t change, what did change were some of the ‘hyperparameters’ and the ‘architectural wiring’ within the cortex.
For an example of a ‘hyperparameter’ change, human cortical pyramidal cells (especially those in our prefrontal cortex) form a lot more synaptic connections with other neurons. I think this is pretty clearly a quantitative change rather than a qualitative one, so I think it nicely fits the analogy of a ‘hyperparameter’ change. I highlight this one, because this difference was traced to a difference in a single gene. And in experiments where this gene was expressed in a transgenic mouse line, the resulting mice were measurably better at solving puzzles.
An example of what I mean about ‘architectural wiring’ changes is that there has been a shift in the patterns of the Brodmann areas from non-human apes to humans. As in, what percentage of the cortex is devoted to specific functions. Language, abstract reasoning, social cognition all benefited relatively more compared to say, vision. These Brodmann areas are determined by the genetically determined wiring that occurs during fetal development and lasts for a lifetime, not determined by in-lifetime-learning like synaptic weights are. There are exceptions to this rule, but they are exceptions that prove the rule. Someone born blind can utilize their otherwise useless visual cortex a bit for helping with other cognitive tasks, but only to a limited extent. And this plastic period ends in early childhood. An adult who looses their eyes gains almost no cognitive benefits in other skills due to ‘reassigning’ visual cortex to other tasks. Their skill gains in non-visual tasks like navigation-by-hearing-and-mental-space-modeling come primarily from learning within the areas already devoted to those tasks driven by the necessity of the life change.
What bearing does this have on trying to predict the future of AI?
If my hypothesis is correct, there are potentially analogously important changes to be made in shaping the defining architecture and hyperparameters of deep neural nets. I have specific hypotheses about these changes drawing on my neuroscience background and the research I’ve been doing over the past couple years into analyzing the remaining algorithmic roadblocks to AGI. Mostly, I’ve been sharing this with only a few trusted AI safety researcher friends, since I think it’s a pretty key area of capabilities research if I’m right. If I’m wrong, then it’s irrelevant, except for flagging the area as a dead end.
For more details that I do feel ok sharing, see my talk here:
It seems to me that the key threshold has to do with the net impact of meme replication:
Transmitting a meme imposes some constraint on the behaviour of the transmitting system.
Transmitting a meme sometimes benefits the system (or descendants).
Where the constraint is very limiting, all but a small proportion of memes will be selected against. The [hunting technique of lions] meme is transferred between lions, because being constrained to hunt is not costly, while having offspring observe hunting technique is beneficial. This is still memetic transfer—just a rather uninteresting version.
Humans get to transmit a much wider variety of memes more broadly because the behavioural constraint isn’t so limiting (speaking, acting, writing...), so the upside needn’t meet a high bar.
The mechanism that led to hitting this threshold in the first place isn’t clear to me. The runaway behaviour after the threshold is hit seems unsurprising.
Still, I think [transmission became much cheaper] is more significant than [transmission became more beneficial].
I don’t think this objection matters for the argument I’m making. All the cross-generational information channels you highlight are at rough saturation, so they’re not able to contribute to the cross-generational accumulation of capabilities-promoting information. Thus, the enormous disparity between the brain’s with-lifetime learning versus evolution cannot lead to a multiple OOM faster accumulation of capabilities as compared to evolution.
When non-genetic cross-generational channels are at saturation, the plot of capabilities-related info versus generation count looks like this:
with non-genetic information channels only giving the “All info” line a ~constant advantage over “Genetic info”. Non-genetic channels might be faster than evolution, but because they’re saturated, they only give each generation a fixed advantage over where they’d be with only genetic info. In contrast, once the cultural channel allows for an ever-increasing volume of transmitted information, then the vastly faster rate of within-lifetime learning can start contributing to the slope of the “All info” line, and not just its height.
Have you tried comparing the cumulative amount of genetic info over 3.5B years?
Isn’t it a big coincidence that the time of brains that process info quickly / increase information rapidly, is also the time where those brains are much more powerful than all other products of evolution?
(The obvious explanation in my view is that brains are vastly better optimizers/searchers per computation step, but I’m trying to make sure I understand your view.)
This whole just does not hold.
This is clearly false. GPT4, can you explain? :
While genes play a significant role in transmitting information from one generation to the next, there are other ways in which animals can pass on information to their offspring. Some of these ways include:
Epigenetics: Epigenetic modifications involve changes in gene expression that do not alter the underlying DNA sequence. These changes can be influenced by environmental factors and can sometimes be passed on to the next generation.
Parental behavior: Parental care, such as feeding, grooming, and teaching, can transmit information to offspring. For example, some bird species teach their young how to find food and avoid predators, while mammals may pass on social behaviors or migration patterns.
Cultural transmission: Social learning and imitation can allow for the transfer of learned behaviors and knowledge from one generation to the next. This is particularly common in species with complex social structures, such as primates, cetaceans, and some bird species.
Vertical transmission of symbionts: Some animals maintain symbiotic relationships with microorganisms that help them adapt to their environment. These microorganisms can be passed from parent to offspring, providing the next generation with information about the environment.
Prenatal environment: The conditions experienced by a pregnant female can influence the development of her offspring, providing them with information about the environment. For example, if a mother experiences stress or nutritional deficiencies during pregnancy, her offspring may be born with adaptations that help them cope with similar conditions.
Hormonal and chemical signaling: Hormones or chemical signals released by parents can influence offspring development and behavior. For example, maternal stress hormones can be transmitted to offspring during development, which may affect their behavior and ability to cope with stress in their environment.
Ecological inheritance: This refers to the transmission of environmental resources or modifications created by previous generations, which can shape the conditions experienced by future generations. Examples include beaver dams, bird nests, or termite mounds, which provide shelter and resources for offspring.
(/GPT)
Actually, transmitting some of the data gathered during the lifetime of the animal to next generation by some other means is so obviously useful that is it highly convergent. Given the fact it is highly convergent, the unprecedented thing which happened with humans can’t be the thing proposed (evolution suddenly discovered how not to sacrifice all whats learned during the lifetime).
If the above is not enough to see why this is false… This hypothesis would also predict civilizations built by every other species which transmits a lot of data e.g. by learning from parental behaviour—once evolution discovers the vast amounts of free energy on the table this positive feedback loop would just explode.
This isn’t the case ⇒ the whole argument does not hold.
Also this argument not working does not imply evolution provides strong evidence for sharp left turn.
What’s going on?
In fact in my view we do not actually understand what exactly happened with humans. Yes, it likely has something to do with culture, and brains, and there being more humans around. But what’s the causality?
Some of the candidates for “what’s the actually fundamental differentiating factor and not a correlate”
- One notable thing about humans is, it’s likely the second time in history a new type of replicator with R>1 emerged: memes. From replicator-centric perspective on the history of the universe, this is the fundamental event, starting a different general evolutionary computation operating at much shorter timescale.
- Machiavellian intelligence hypothesis suggests that what happened was humans entered a basin of attraction where selection pressure on “modelling and manipulation of other humans” leads to explosion in brain sizes. The fundamental thing suggested here is you soon hit diminishing return for scaling up energy-hungry predictive processing engines modelling fixed-complexity environment—soon you would do better by e.g. growing bigger claws. Unless… you hit the Machiavellian basin, where sexual selection forces you to model other minds modelling your mind … and this creates a race, in a an environment of unbounded complexity.
- Social brain hypothesis is similar, but the runaway complexity of the environment is just because of the large and social groups.
- Self-domestication hypothesis: this is particularly interesting and intriguing. The idea is humans self-induced something like domestication selection, selecting for pro-social behaviours and reduction in aggression. From an abstract perspective, I would say this allows emergence of super-agents composed of individual humans, more powerful than individual humans. (once such entities exist, they can create further selection pressure for pro-sociality)
or, a combination of the above, or something even weirder
The main reason why it’s hard to draw insights from evolution of humans to AI isn’t because there is nothing to learn, but because we don’t know why what happened happened.
I think OP is correct about cultural learning being the most important factor in explaining the large difference in intelligence between homo sapiens and other animals.
In early chapters of Secrets of Our Success, the book examines studies comparing performance of young humans and young chimps on various congnitive tasks. The book argues that across a broad array of cognitive tests, 4 year old humans do not perform singificantly better than 4 year old chimps on average, except in cases where the task can be solved by immitating others (human children crushed the chimps when this was the case).
The book makes a very compelling argument that our species is uniquely prone to immitating others (even in the absense of causal models about why the behaviour we’re immitating is useful), and even very young humnans have inate instincts for picking up on signals of prestige/compotence in others and preferentially immitating those high prestige poeple. Imo the arguments put forward in this book make cultral learning look like a very strong theory better in comparison to Machieavellian intelligence hypothesis, (although what actually happend at a lower level abstraction probably includes aspects of both).
Note that this isn’t exactly the hypothesis proposed in the OP and would point in a different direction.
OP states there is a categorical difference between animals and humans, in the ability of humans to transfer data to future generation. This is not the case, because animals do this as well.
What your paraphrase of Secrets of Our Success is suggesting is this existing capacity for transfer of data across generations is present in many animals, but there is some threshold of ‘social learning’ which was crossed by humans—and when crossed, lead to cultural explosion.
I think this is actually mostly captured by …. One notable thing about humans is, it’s likely the second time in history a new type of replicator with R>1 emerged: memes. From replicator-centric perspective on the history of the universe, this is the fundamental event, starting a different general evolutionary computation operating at much shorter timescale.
Also … I’ve skimmed few chapters of the book and the evidence it gives of the type ‘chimps vs humans’ is mostly for current humans being substantially shaped by cultural evolution, and also our biology being quite influenced by cultural evolution. This is clearly to be expected after the evolutions run for some time, but does not explain causality that much.
(The mentioned new replicator dynamic is actually one of the mechanisms which can lead to discontinuous jumps based on small changes in underlying parameter. Changing the reproduction number of a virus from just below one to above one causes an epidemic.)
There doesn’t need to be a categorical difference, just a real difference that is strong enough to explain humanities sharp left turn by something other than increased brain size. I do believe that’s plausible—humans are much much better than other animals at communicating abstractions and ideas accross generations. Can’t speak about the book, but X4vier’s example would seem to support that argument.
Jan, your comment here got a lot of disagree votes, but I have strongly agreed with it. I think the discussion of cultural transmission as source of the ‘sharp left turn’ of human evolution is missing a key piece.
Cultural transmission is not the first causal mechanism. I would argue that it is necessary for the development of modern human society, but not sufficient.
The question of “How did we come to be?” is something I’ve been interested in my entire adult life. I’ve spent a lot of time in college courses studying neuroscience, and some studying anthropology. My understanding as I would summarize it here:
Around 2.5 million years ago—first evidence of hominids making and using stone tools
Around 1.5 million years ago—first evidence of hominids making fires
https://en.wikipedia.org/wiki/Prehistoric_technology
Around 300,000 years ago (15000 − 20000 generations), Homo sapiens arises as a new subspecies in Africa. Still occasionally interbreeds with other subspecies (and presumably thus occasionally communicates with and trades with). Early on, homo sapiens didn’t have an impressive jump in technology. There was a step up in their ability to compete with other hominids, but it wasn’t totally overwhelming. After outcompeting the other hominids in the area, homo sapiens didn’t sustain massively larger populations. They were still hunter/gatherers with similar tech, constrained to similar calorie acquisition limits.
They gradually grow in numbers and out-compete other subspecies. Their tools get gradually better.
Around 55,000 years ago (2700 − 3600 generations), Homo sapiens spreads out of Africa. Gradually colonizes the rest of the world, continuing to interbreed (and communicate and trade) with other subspecies somewhat, but being clearly dominant.
Around 12,000 years ago, homo sapiens began developing agriculture and cities.
Around 6,000 years ago, homo sapiens began using writing.
From wikipedia article on human population:
Here’s a nice summary quote from a Smithsonian magazine article:
And from the wikipedia article on prehistoric technology:
So what am I getting at here? I’m saying that this idea of a homo sapiens sharp left turn doesn’t look much like a sharp left turn. It was a moderate increase in capabilities over other hominids.
I would say that the Neolithic Revolution is a better candidate for a sharp left turn. I think you can trace a clear line of ‘something fundamentally different started happening’ from the Neolithic Revolution up to the Industrial Revolution when the really obvious ‘sharp left turn’ in human population began.
So here’s the really interesting mystery. Why did the Neolithic Revolution occur independently in six separate locations?!
Here’s my current best hypothesis. Homo sapiens originally was only somewhat smarter than the other hominids. Like maybe, ~6-year-old intelligences amongst the ~4-year-old intelligences. And if you took a homo sapiens individual from that time period and gave them a modern education… they’d seem significantly mentally handicapped by today’s standards even with a good education. But importantly, their brains were bigger. But a lot of that potential brain area was poorly utilized. But now evolution had a big new canvas to work with, and the Machiavellian-brain-hypothesis motivation of why a strong evolutionary pressure would push for this new larger brain to improve its organization. Homo sapiens was competing with each other and with other hominids from 300,000 to 50,000 years ago! Most of their existence so far! And they didn’t start clearly rapidly dominating and conquering the world until the more recent end of that. So 250,000 years of evolution figuring out how to organize this new larger brain capacity to good effect. To go from ‘weak general learner with low max capability cap’ to ‘strong general learner with high max capability cap’. A lot of important things happened in the brain in this time, but it’s hard to see any evidence of this in the fossil record, because the bone changes happened 300,000 years ago and the bones then stayed more or less the same. If this hypothesis is true, then we are a more different species from the original Homo sapiens than those original Homo sapiens were from the other hominids they had as neighbors. A crazy fast time period from an evolutionary time point, but with that big new canvas to work with, and a strong evolutionary pressure rewarding every tiny gain, it can happen. It took fewer generations to go from a bloodhound-type-dog to a modern dachshund.
There are some important differences between our modern Homo sapiens neurons and other great apes. And between great apes vs other mammals.
The fundamental learning algorithm of the cortex didn’t change, what did change were some of the ‘hyperparameters’ and the ‘architectural wiring’ within the cortex.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3103088/
For an example of a ‘hyperparameter’ change, human cortical pyramidal cells (especially those in our prefrontal cortex) form a lot more synaptic connections with other neurons. I think this is pretty clearly a quantitative change rather than a qualitative one, so I think it nicely fits the analogy of a ‘hyperparameter’ change. I highlight this one, because this difference was traced to a difference in a single gene. And in experiments where this gene was expressed in a transgenic mouse line, the resulting mice were measurably better at solving puzzles.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10064077/
An example of what I mean about ‘architectural wiring’ changes is that there has been a shift in the patterns of the Brodmann areas from non-human apes to humans. As in, what percentage of the cortex is devoted to specific functions. Language, abstract reasoning, social cognition all benefited relatively more compared to say, vision. These Brodmann areas are determined by the genetically determined wiring that occurs during fetal development and lasts for a lifetime, not determined by in-lifetime-learning like synaptic weights are. There are exceptions to this rule, but they are exceptions that prove the rule. Someone born blind can utilize their otherwise useless visual cortex a bit for helping with other cognitive tasks, but only to a limited extent. And this plastic period ends in early childhood. An adult who looses their eyes gains almost no cognitive benefits in other skills due to ‘reassigning’ visual cortex to other tasks. Their skill gains in non-visual tasks like navigation-by-hearing-and-mental-space-modeling come primarily from learning within the areas already devoted to those tasks driven by the necessity of the life change.
https://www.science.org/content/blog-post/chimp-study-offers-new-clues-language
What bearing does this have on trying to predict the future of AI?
If my hypothesis is correct, there are potentially analogously important changes to be made in shaping the defining architecture and hyperparameters of deep neural nets. I have specific hypotheses about these changes drawing on my neuroscience background and the research I’ve been doing over the past couple years into analyzing the remaining algorithmic roadblocks to AGI. Mostly, I’ve been sharing this with only a few trusted AI safety researcher friends, since I think it’s a pretty key area of capabilities research if I’m right. If I’m wrong, then it’s irrelevant, except for flagging the area as a dead end.
For more details that I do feel ok sharing, see my talk here:
It seems to me that the key threshold has to do with the net impact of meme replication:
Transmitting a meme imposes some constraint on the behaviour of the transmitting system.
Transmitting a meme sometimes benefits the system (or descendants).
Where the constraint is very limiting, all but a small proportion of memes will be selected against. The [hunting technique of lions] meme is transferred between lions, because being constrained to hunt is not costly, while having offspring observe hunting technique is beneficial.
This is still memetic transfer—just a rather uninteresting version.
Humans get to transmit a much wider variety of memes more broadly because the behavioural constraint isn’t so limiting (speaking, acting, writing...), so the upside needn’t meet a high bar.
The mechanism that led to hitting this threshold in the first place isn’t clear to me. The runaway behaviour after the threshold is hit seems unsurprising.
Still, I think [transmission became much cheaper] is more significant than [transmission became more beneficial].
I don’t think this objection matters for the argument I’m making. All the cross-generational information channels you highlight are at rough saturation, so they’re not able to contribute to the cross-generational accumulation of capabilities-promoting information. Thus, the enormous disparity between the brain’s with-lifetime learning versus evolution cannot lead to a multiple OOM faster accumulation of capabilities as compared to evolution.
When non-genetic cross-generational channels are at saturation, the plot of capabilities-related info versus generation count looks like this:
with non-genetic information channels only giving the “All info” line a ~constant advantage over “Genetic info”. Non-genetic channels might be faster than evolution, but because they’re saturated, they only give each generation a fixed advantage over where they’d be with only genetic info. In contrast, once the cultural channel allows for an ever-increasing volume of transmitted information, then the vastly faster rate of within-lifetime learning can start contributing to the slope of the “All info” line, and not just its height.
Thus, humanity’s sharp left turn.
Hey Quintin thanks for the diagram.
Have you tried comparing the cumulative amount of genetic info over 3.5B years?
Isn’t it a big coincidence that the time of brains that process info quickly / increase information rapidly, is also the time where those brains are much more powerful than all other products of evolution?
(The obvious explanation in my view is that brains are vastly better optimizers/searchers per computation step, but I’m trying to make sure I understand your view.)