As Herculano-Houzel called it, the human brain is a remarkable, yet not extraordinary, scaled-up primate brain. It seems that our main advantage in hardware is quantitative: more cortical columns to process more reference frames to predict more stuff.
And the primate brain is mostly the same as of other mammals (which shouldn’t be surprising, as the source code is mostly the same).
And the intelligence of mammals seems to be rather general. It allows them to solve a highly diverse set of cognitive tasks, including the task of learning to navigate at the Level 5 autonomy in novel environments (which is still too hard for the most general of our AIs).
One may ask: why aren’t elephants making rockets and computers yet?
But one may ask the same question about any uncontacted human tribe.
Thus, it seems to me that the “elephants are not GI” part of the argument is incorrect. Elephants (and also chimps, dolphins etc) seem to possess a rather general but computationally capped intelligence.
Somebody tries to measure the human brain using instruments that can only detect numbers of neurons and energy expenditure, but not detect any difference of how the fine circuitry is wired; and concludes the human brain is remarkable only in its size and not in its algorithms. You see the problem here? The failure of large dinosaurs to quickly scale is a measuring instrument that detects how their algorithms scaled with more compute (namely: poorly), while measuring the number of neurons in a human brain tells you nothing about that at all.
Jeff Hawkins provided a rather interesting argument on the topic:
The scaling of the human brain has happened too fast to implement any deep changes in how the circuitry works. The entire scaling process was mostly done by the favorite trick of biological evolution: copy and paste existing units (in this case—cortical columns).
Jeff argues that there is no change in the basic algorithm between earlier primates and humans. It’s the same reference-frames processing algo distributed across columns. The main difference is, humans have much more columns.
I’ve found his arguments convincing for two reasons:
his neurobiological arguments are surprisingly good (to the point of being surprisingly obvious in hindsight)
It’s the same “just add more layers” trick we reinvented in ML
The failure of large dinosaurs to quickly scale is a measuring instrument that detects how their algorithms scaled with more compute
Are we sure about the low intelligence of dinosaurs?
Judging by the living dinos (e.g. crows), they are able to pack a chimp-like intelligence into a 0.016 kg brain.
And some of the dinos have had x60 more of it (e.g. the brain of Tyrannosaurus rex weighted about1 kg, which is comparable to Homo erectus).
And some of the dinos have had a surprisingly large encephalization quotient, combined with bipedalism, gripping hands, forward-facing eyes, omnivorism, nest building, parental care, and living in groups (e.g. troodontids).
Maybe it was not an asteroid after all...
(Very unlikely, of course. But I find the idea rather amusing)
One may ask: why aren’t elephants making rockets and computers yet?
But one may ask the same question about any uncontacted human tribe.
Seems more surprising for elephants, by default: elephants have apparently had similarly large brains for about 20 million years, which is far more time than uncontacted human tribes have had to build rockets. (~100x as long as anatomically modern humans have existed at all, for example.)
I agree. Additionally, the life expectancy of elephants is significantly higher than of paleolithic humans (1, 2). Thus, individual elephants have much more time to learn stuff.
In humans, technological progress is not a given. Across different populations, it seems to be determined by the local culture, and not by neurobiological differences. For example, the ancestors of Wernher von Braun have left their technological local minimum thousands of years later than Egyptians or Chinese. And the ancestors of Sergei Korolev lived their primitive lives well into the 8th century C.E. If a Han dynasty scholar had visited the Germanic and Slavic tribes, he would’ve described them as hopeless barbarians, perhaps even as inherently predisposed to barbarism.
Maybe if we give elephants more time, they will overcome their biological limitations (limited speech, limited “hand”, fewer neurons in neocortex etc), and will escape the local minimum. But maybe not.
I think Herculano-Houzel would want to mention that humans have 3x (iirc) more neurons in their cerebral cortex than even the elephant species with the biggest brains. Those elephants have more total neurons because their cerebellar cortices have like 200 billion neurons. Humans have more cortical neurons than any animal, including blue whales, because neuron sizes scale differently for different Orders and primates specifically scale well.
Crucially, people have thought human brains were special among primates but she makes the point that it’s the other great apes that are special in having smaller brains according to primate brain scaling laws. This is because humans either had a unique incentive to keep up with the costs of scaling or because they had a unique ability to keep up with the costs (due to e.g. cooking).
Having better algorithms that could take advantage of scale fits with her views, I think.
As Herculano-Houzel called it, the human brain is a remarkable, yet not extraordinary, scaled-up primate brain. It seems that our main advantage in hardware is quantitative: more cortical columns to process more reference frames to predict more stuff.
And the primate brain is mostly the same as of other mammals (which shouldn’t be surprising, as the source code is mostly the same).
And the intelligence of mammals seems to be rather general. It allows them to solve a highly diverse set of cognitive tasks, including the task of learning to navigate at the Level 5 autonomy in novel environments (which is still too hard for the most general of our AIs).
One may ask: why aren’t elephants making rockets and computers yet?
But one may ask the same question about any uncontacted human tribe.
Thus, it seems to me that the “elephants are not GI” part of the argument is incorrect. Elephants (and also chimps, dolphins etc) seem to possess a rather general but computationally capped intelligence.
Somebody tries to measure the human brain using instruments that can only detect numbers of neurons and energy expenditure, but not detect any difference of how the fine circuitry is wired; and concludes the human brain is remarkable only in its size and not in its algorithms. You see the problem here? The failure of large dinosaurs to quickly scale is a measuring instrument that detects how their algorithms scaled with more compute (namely: poorly), while measuring the number of neurons in a human brain tells you nothing about that at all.
Jeff Hawkins provided a rather interesting argument on the topic:
The scaling of the human brain has happened too fast to implement any deep changes in how the circuitry works. The entire scaling process was mostly done by the favorite trick of biological evolution: copy and paste existing units (in this case—cortical columns).
Jeff argues that there is no change in the basic algorithm between earlier primates and humans. It’s the same reference-frames processing algo distributed across columns. The main difference is, humans have much more columns.
I’ve found his arguments convincing for two reasons:
his neurobiological arguments are surprisingly good (to the point of being surprisingly obvious in hindsight)
It’s the same “just add more layers” trick we reinvented in ML
Are we sure about the low intelligence of dinosaurs?
Judging by the living dinos (e.g. crows), they are able to pack a chimp-like intelligence into a 0.016 kg brain.
And some of the dinos have had x60 more of it (e.g. the brain of Tyrannosaurus rex weighted about 1 kg, which is comparable to Homo erectus).
And some of the dinos have had a surprisingly large encephalization quotient, combined with bipedalism, gripping hands, forward-facing eyes, omnivorism, nest building, parental care, and living in groups (e.g. troodontids).
Maybe it was not an asteroid after all...
(Very unlikely, of course. But I find the idea rather amusing)
Seems more surprising for elephants, by default: elephants have apparently had similarly large brains for about 20 million years, which is far more time than uncontacted human tribes have had to build rockets. (~100x as long as anatomically modern humans have existed at all, for example.)
I agree. Additionally, the life expectancy of elephants is significantly higher than of paleolithic humans (1, 2). Thus, individual elephants have much more time to learn stuff.
In humans, technological progress is not a given. Across different populations, it seems to be determined by the local culture, and not by neurobiological differences. For example, the ancestors of Wernher von Braun have left their technological local minimum thousands of years later than Egyptians or Chinese. And the ancestors of Sergei Korolev lived their primitive lives well into the 8th century C.E. If a Han dynasty scholar had visited the Germanic and Slavic tribes, he would’ve described them as hopeless barbarians, perhaps even as inherently predisposed to barbarism.
Maybe if we give elephants more time, they will overcome their biological limitations (limited speech, limited “hand”, fewer neurons in neocortex etc), and will escape the local minimum. But maybe not.
I think Herculano-Houzel would want to mention that humans have 3x (iirc) more neurons in their cerebral cortex than even the elephant species with the biggest brains. Those elephants have more total neurons because their cerebellar cortices have like 200 billion neurons. Humans have more cortical neurons than any animal, including blue whales, because neuron sizes scale differently for different Orders and primates specifically scale well.
Crucially, people have thought human brains were special among primates but she makes the point that it’s the other great apes that are special in having smaller brains according to primate brain scaling laws. This is because humans either had a unique incentive to keep up with the costs of scaling or because they had a unique ability to keep up with the costs (due to e.g. cooking).
Having better algorithms that could take advantage of scale fits with her views, I think.