TL;DR:

While cultural intelligence has indeed evolved rapidly, the genetic architecture supporting it operates through complex stochastic development and co-evolutionary dynamics that simple statistical models miss. The most promising genetic enhancements likely target meta-parameters governing learning capabilities rather than direct IQ-associated variants.

Longer:

You make a good point about human intelligence potentially being out of evolutionary equilibrium. The rapid advancement of human capabilities certainly suggests beneficial genetic variants might still be working their way through the population. 

I'd also suggest this creates an even more interesting picture when combined with developmental stochasticity - the inherent randomness in how neural systems form even with identical genetic inputs (see other comment response to Yair for more detail).  This stochasticity means genetic variants don't deterministically produce intelligence outcomes but rather influence probabilistic developmental processes.

What complicates the picture further is that intelligence emerges through co-evolution between our genes and our cultural tools. Following Heyes' cognitive gadgets theory, genetic factors don't directly produce intelligence but rather interact with cultural infrastructure to shape learning processes. This suggests the most valuable genetic variants might not directly enhance raw processing power but instead improve how effectively our brains interface with cultural tools - essentially helping our brains better leverage the extraordinary cultural inheritance (language among other things) we already possess.

Rather than simply accumulating variants statistically associated with IQ, effective enhancement might target meta-parameters governing learning capabilities - the mechanisms that allow our brains to adapt to and leverage our rapidly evolving cultural environment. This isn't an argument against genetic enhancement, but for more sophisticated approaches that respect how intelligence actually emerges.

(Workshopped this with my different AI tools a bit and I now have a paper outline saved on this if you want more of the specific modelling frame lol)

The book Innate actually goes into detail about a bunch of IQ studies and relating it to neuroscience which is why I really liked reading it! 

and it seems most of this variation is genetic

This to me seems like the crux here, in the book innate he states the belief that around 60% of it is genetic and 20% is developmental randomness (since brain development is essentially a stochastic process), 20% being nurture based on twin studies. 

I do find this a difficult thing to think about though since intelligence can be seen as the speed of the larger highways and how well (differentially) coupled different cortical areas are. There are deep foundational reasons to believe that our cognition is concepts stacked on top of other concepts such as described in the Active Inference literature. A more accessible and practical way of seeing this is in the book How Emotions Are Made by Lisa Feldman Barett. 

Also if you combine this with studies done by Robert Sapolvsky described in the book Why Zebra's Don't Get Ulcers where traumatic events in childhood leads to less IQ down the line we can see how wrong beliefs that stick lead to your stochastic process of development worsening. This is because at timestep T-1 you had a belief or experience that shaped your learning to be way off and at timestep T you're using this to learn. Yes the parameters are set genetically yet from a mechanistic perspective it very much interfaces with your learning. 

Twin studies also have a general bias in that they're often made in societies affected by globalisation and that have been connected for a long time. If you believe something like cultural evolution or cognitive gadgets theory what is seen as genetically influenced might actually be genetically influenced given that the society you're in share the same cognitive gadgets. (This is essentially one of the main critiques of twin studies)

So there's some degree that (IQ|Cogntiive Gadgets) could be decomposed genetically but if you don't decompose it given cultural tools it doesn't make sense? There's no fully general intelligence, there's an intelligence that given the right infrastructure then becomes general?

I felt too stupid when it comes to biology to interact with the original superbabies post but this speaks more my language (data science) so I would also just want to bring up a point I had with the original post that I'm still confused about related to what you've mentioned here.

The idea I've heard about this is that intelligence has been under strong selective pressure for millions of years, which should apriori make us believe that IQ is a significant challenge for genetic enhancement. As Kevin Mitchell explains in "Innate," most remaining genetic variants affecting intelligence are likely:

1. Slightly deleterious mutations in mutation-selection balance
2. Variants with fitness tradeoffs preventing fixation
3. Variants that function only in specific genetic backgrounds

Unlike traits that haven't been heavily optimized (like resistance to modern diseases), the "low-hanging fruit" for cognitive enhancement has likely already been picked by natural selection. This means that the genetic landscape for intelligence might not be a simple upward slope waiting to be climbed, but a complex terrain where most interventions may disrupt finely-tuned systems.

When we combine multiple supposedly beneficial variants, we risk creating novel interactions that disrupt the intricate balance of neural development that supports intelligence. The evolutionary "valleys" for cognitive traits may be deeper precisely because selection has already pushed us toward local optima.

This doesn't make enhancement impossible, but suggests the challenge may be greater than statistical models indicate, and might require understanding developmental pathways at a deeper level than just identifying associated variants.

Also if we look at things like horizontal gene transfer & shifting balance theory we can see these as general ways to discover hidden genetic variants in optimisation and this just feels highly non-trivial to me? Like competing against evolution for optimal information encoding just seems really difficult apriori? (Not a geneticist so I might be completely wrong here!)

I'm very happy to be convinced that these arguments are wrong and I would love to hear why!

Do you believe it effects most of it or just individual instances, the example you're pointing at there isn't load bearing and there are other people who have written similar things but with more nuance on cultural evolution such as cecilia hayes with cognitive gadgets?

Like I'm not sure how much to throw out based on that?

Just wanted to drop these two books here if you're interested in the cultural evolution side more:

https://www.goodreads.com/book/show/17707599-moral-tribes

https://www.goodreads.com/book/show/25761655-the-secret-of-our-success

A random thought that I just has from more mainstream theoretical CS ML or Geometric Deep Learning is about inductive biases from the perspective of different geodesics. 

Like they talk about using structural invariants to design the inductive biases of different ML models and so if we're talking abiut general abstraction learning my question is if it even makes sense without taking the underlying inductive biases you have into account?

Like maybe the model of Natural Abstractions always has to filter through one inductive bias or another and there are different optimal choices for different domains? Some might be convergent but you gotta use the filter or something?

As stated, a random thought but felt I should share. Here's a quick overarching link on GDL if you wanna check it out more: https://geometricdeeplearning.com

I really like the latest posts you've dropped on meditation, they help me with some of my own reflections.

Is there an effect here? Maybe for some people. For me, at least, the positive effect to working memory isn't super cumulative nor important. Does a little meditation before work help me concentrate? Sure, but so does weightlifting, taking a shower, and going for a walk.

Wanting to point out a situation where this really showed up for me, I get the point that it is stupid compared to what lies deeper in meditation but it is still instrumentally useful. 

So, I didn't meditate (samadhi) that much over the past two weeks, realized that I didn't and spent like 6 hours meditating the last 3 days. My co-founder noticed directly and was like "last week it was like your ideas where in a narrow domain and carried a lot of uncertainty but now they're broad and weird but at the same time pointing at the same thing, it is nice to have creative you back"

For me it is almost crucial for optimal work performance to have an hour of focused meditation a day. ¯\_(ツ)_/¯

I like to think of learning and all of these things as self-contained smaller self-contained knowledge trees. Building knowledge trees that are cached, almost like creatin zip files and systems where I store a bunch of zip files similar to what Elizier talks about in The Sequences. 

Like when you mention the thing about Nielsen on linear algebra it opens up the entire though tree there. I might just get the association to something like PCA and then I think huh, how to ptimise this and then it goes to QR-algorithms and things like a householder matrix and some specific symmetric properties of linear spaces...

If I have enough of these in an area then I might go back to my anki for that specific area. Like if you think from the perspective of schedulling and storage algorithms similar to what is explored in algorithms to live by you quickly understand that the magic is in information compression and working at different meta-levels. Zipped zip files with algorithms to expand them if need be. Dunno if that makes sense, agree with the exobrain creep that exists though.

This is the quickest link i found on this but the 2nd exercise in the first category and doing them 8-12 reps for 3 sets with weighted cables so that you can progressive overload it.

https://e3rehab.com/rotator-cuff-exercises/

Essentially, if you're doing bench press, shoulder press or anything involving the shoulders or chest, the most likely way to injure your self is through not doing this in a stable way. The rotator cuffs are in short there to stabilize these sorts of movements and deal with torque. If you don't have strong rotator cuffs this will lead to shoulder injuries a lot more often which is one of the main ways you can fuck up your training.