My intuition is that the cellular machinery and prenatal environment are required much more for meeting the biochemical needs of a human embryo than as providers of extra information. The hard part where you need to have a huge digital data string mostly exactly right is in the DNA, while the growth environment is more of a warm soup that has an intricate mixture of stuff but is far too noisy to actually carry anything close to the amount of actionable information the genome does.
Standard notions are also selling short the massive amount of very clever work the newborn baby's brain is already doing when it starts to learn things that lets it bootstrap itself to full intelligence. It manages to do this from other people who mostly just give it food every now and then and make random attempts to engage it in conversation instead of doing the sort of massively intricate and laborous cognitive engineering they'd have to pull off if the newborn baby's brain would actually need the similar sort of hard complexity a programmable general-purpose computer or a ovarian cell without a DNA does before it can have a go at turning into an intelligent entity.
I think you're underselling the developmental power of a culture. Bits of your brain literally don't grow properly if you're not raised in a human culture. Ignore a baby at the wrong points in its development and it'll fail to ever be able to learn any language, feel certain emotions or comprehend some social constraints. Etc.
That is, the hardware grows to meet the software and data, because (as usual) the data/software/hardware divides in the brain are very fuzzy indeed.
(This suggests Kurzweil was plausibly approximately correct about the genome having th...
For no reason in particular I'm wondering about the size of the smallest program that would constitute a starting point of a recursively self-improving AI.
The analysis of FOOM as a self-amplifying process would seem to indicate that in principle one could get it started from a relatively modest starting point -- perhaps just a few bytes of the right code could begin the process. Or could it? I wonder whether any other considerations give tighter lower-bounds.
One consideration is that FOOM hasn't already happened -- at least not here on Earth. If the smallest FOOM seed were very small (like a few hundred bytes) then we would expect evolution to have already bumped into it at some point. Although evolution is under no specific pressure to produce a FOOM, it has probably produced over the last few billion years all the interesting computations up to some minor level of complexity, and if there were a FOOM seed among those then we would see the results about us.
Then there is the more speculative analysis of what minimal expertise the algorithm constituting the FOOM seed would actually need.
Then there is the fact that any algorithm that naively enumerates some space of algorithms qualifies in some sense as a FOOM seed as it will eventually hit on some recursively self-improving AI. But that could take gigayears so is really not FOOM in the usual sense.
I wonder also whether the fact that mainstream AI hasn't yet produced FOOM could lower-bound the complexity of doing so.
Note that here I'm referring to recursively self-improving AI in general -- I'd be interested if the answers to these questions change substantially for the special case of friendly AIs.
Anyway, just idle thoughts, do add yours.