executing the same basic algorithm (genetic differences are tiny compared to size of genome).
This seems moderately misleading. People start out nearly the same, but apply their algorithm to somewhat different domains. Running a year of human-level compute on different data should be expected to produce much more divergent results than is captured by the genetic differences.
Specialization on different topics likely explains much more than algorithmic tweaks explain.
I had in mind an earlier and somewhat more subtle type of specialization, along the lines of what Henrich discusses in WEIRDest People.
An example is that people who learn to read at an early age tend to have poorer facial recognition, and more of the abstract cognitive skills that are measured by IQ test. This kind of difference likely alters a nontrivial amount of learning over a period of 15 or so years before people start thinking about specializations within higher math.
It’s certainly plausible that something like this pumps in quite a bit of variation on top of the genetics, but I don’t think it detracts much from the core argument: if you push just a little harder on a general optimizer, you get a lot more capabilities out.
This seems moderately misleading. People start out nearly the same, but apply their algorithm to somewhat different domains. Running a year of human-level compute on different data should be expected to produce much more divergent results than is captured by the genetic differences.
Specialization on different topics likely explains much more than algorithmic tweaks explain.
That the very best mathematicians are generally less specialized than their more average peers suggests otherwise.
I had in mind an earlier and somewhat more subtle type of specialization, along the lines of what Henrich discusses in WEIRDest People.
An example is that people who learn to read at an early age tend to have poorer facial recognition, and more of the abstract cognitive skills that are measured by IQ test. This kind of difference likely alters a nontrivial amount of learning over a period of 15 or so years before people start thinking about specializations within higher math.
It’s certainly plausible that something like this pumps in quite a bit of variation on top of the genetics, but I don’t think it detracts much from the core argument: if you push just a little harder on a general optimizer, you get a lot more capabilities out.