I don't know why people really dislike the idea of innate knowledge so much, it's obvious other animals have tons of it, why would we be any different.
So the existence of a sensorimotor feedback loop for a basic behavior is innate (e.g. moving forward to seek food), but the fine-tuning for reliabily executing this behavior while adapting to changing conditions (e.g. moving over difficult terrain with an injured limb after spotting a tasty plant) needs to be learned through interacting with the environment. (Stumbling around eating random stuff to find out what is edible.)
That's not the only way to one could encode innate knowledge. Besides, we have demonstrated that animals have innate knowledge experimentally many times, the only reason we can't do this to humans is that it would be horrifically unethical.
>Stumbling around eating random stuff to find out what is edible
Plenty of animals have innate knowledge about what is and isn't edible: it's why, for example, tasty things generally speaking smell good and why things that are bad (rotting meat) smell horrific.
I'm saying that there are limits to how much knowledge can be inherited. I.e. the question isn't "Where could innate knowledge be encoded other than in synapses?" but "Considering the extremely large number of synapses involved in complex behavior far exceeds genetic storage capacity, how are their weights determined?" And since we know that in addition to having innate behaviors, animals are also capable of learning (e.g. responding to artificial stimuli not found in nature), it stands to reason that most synapse weights must be set by a dynamic learning process.
Maybe sections could be read from DNA and broadcast as action potentials?
There's already ribosomes that go over RNA. You'd need a variant which instead of making amino acids, would read out the base pairs and make something that causes action potentials to happen based on the contents.
Some people just believe there is no innate knowledge or we dont need it if we just scale/learn better (in the direction of Bitter Lesson)
(ML) Academia is also heavily biased against it due to mainly two reasons: - Its harder to publish, since if you learn Task X with innate Knowledge, its not as general, so reviewer can claims its just (feature) engineering - Which hurts acceptance, so people always try to frame their work as general as possible - Historical reasons due to the conflict the symbolic community (which rely heavily on innate knowledge)