Consequently, your DNA has less information about how to survive on Jupiter or in the absence of oxygen.
However, your genome contains a fair amount of data on how to identify a mate that will maximize your reproductive success in an environment similar to the one your lineage experienced, e.g., a preference for symmetrical faces.
Until we can measure the environment of humans accurately, all the algorithmic complexity measures applied to the genome are going to be missing the relevant context.
The real interesting part is _how_ this small metaprogram can generate something like a brain, which is ostensibly multiples more complex than the DNA that produced it, since obviously DNA cannot possibly encode the data for every possible synaptic connection or protein or whatever losslessly. I think this is more of a testament to how complex the human body is, that it has such complex seemingly emergent behavior from a very sparse set of initial conditions.
maybe
It such a subtle thing too! We're attracted (or not) to the tiniest differences in physiology. If you doubt this, try this exercise: Pretend you've just met green aliens and have to explain to them how to reliably tell the difference between men and women from appearance alone! Now explain why that particular girl (or boy) is very pretty/handsome, but not that one.
It's one of those topics where the more you know, the more freaky it is.
DNA does not -- to our knowledge -- directly encode the "weights" of our neurons! It can't possibly because there are far more synapses than there bits of information in our genes. Also, most of those genes are dedicated to non-brain parts of the body plan and to the low-level machinery of our cellular biochemistry.
Secondly, DNA has only an indirect effect of our development: it encodes for proteins, which then provide chemical signals such as concentration gradients that guide cell division. It's a bit like playing SimCity, where the players' control is limited to zoning and road topology. The individual Sims are not directly controllable and behave stochastically.
Solving this problem is so freakishly difficult for even the incredible brute force of parallel search of evolution only managed to discover a solution a few times in a billion years.
Our attraction to our partners is a genetic heritage shared with all mammals, going back hundreds of millions of years. That's why Furry is a thing, but not Featherry. Birds are a different class from us mammals and don't share the same "partner attraction wiring" genes. (This is closely related to why all mammal babies are cute to humans, but baby bird chicks are generally repulsive.)
Because this is a hard problem to solve, the few solutions that were discovered had to be reused by entire classes of Animalia. I would hazard a guess that this is precisely what defines a “class” in taxonomy! If there were intelligent birds, their equivalent of Furry would be Featherry, and their crimes of bestiality would be with other non-intelligent birds, not mammals.
With LLMs, we got to see a glimpse into the possible mechanisms of intelligence, and what it might take to design or evolve one.
The LLM equivalent of this kind of encoding would be to design a model architecture that falls in love with a specific, narrowly selected, subset of its users. Keep in mind that I'm not talking about a learned or specifically tuned set of model weights! The architecture is where the attraction is encoded, such as selecting some complex variant or combination of Transformers, Mamba, or CNNs that just "so happen" to result in the model preferentially learning to be attracted to certain styles of conversation, but not others.
Worse still, the direct equivalent to what genes do is that you can't even choose an architecture directly, instead you can only contribute to PyTorch. You have to design its API such that naive developers using it stochastically tend towards the desired architecture of their own accord by simply tab-completing often.
That's essentially what evolution figured out, at least five or six times, but tunable, so that individual species can be attracted to each other but much less to even very closely related species.
And then, evolution found a way to add a "notch filter" such that despite increased attraction to closely related individuals, most animals (including humans) are repulsed sexually by their parents and siblings.
That's mind-blowing to me.
Not being attracted sexually to close relatives is likely the result of early imprinting when growing up under one roof, and not genetics. Indeed there is some evidence relatives separated at birth etc who meet later are more likely to unwittingly be attracted to one another.
The question is how is that encoded, not just in your genes, but in the final neurons?
There are hundreds of trillions of synapses in the brain that a few megabytes of genes somehow shaped into: "be attracted to faces almost, but not exactly like your parents"... but not actually repulsed, because you have to get along nicely with your parents and not just run away in terror.
DNA is like a computer program that when it runs, it provides feedback for the code and determines which parts of it should run. It can also modify the code (DNA methylation).
Then add on top the external environment - external molecules can interact with the machinery which then impact which code is executed.
If code is self-regulating, the amount of information it encodes is far higher than that defined by its base pairs.
E_Evan•5h ago