Lessons could also be passed from AI to AI (e.g. fro Google to Ford) by sending the input [training data] and a output [reasonable response to that data] for the other AI to ponder.
And the weird thing is, I've got this niggling suspicion that this handicap is actually a profound strength. That evolution didn't produce so many species of organisms separated by walls of flesh and bone, detached from one another and capable of wandering far apart, then incapable of even expressing fundamentally novel concepts (I mean novel novel, such that your language has no word for it and such that any metaphor would be more misleading than enlightening). We could have evolved such that when holding hands, a flow of specially produced chemicals seep from ones hand to the other, travelling to the brain and making the changes necessary to convey concepts exactly. Bacteria communicate in this way. They change each other. Directly. We could to. But... we don't. And there is maybe a reason for that.
There's a rather good argument that as a species, we're the stupidest thing nature could get away with that could still develop writing and science. So the reason may very well be that nature didn't bother.
I was referencing the superiority of AI minds to biological minds. Humanity not a thing which possesses a mind.
Neurons do not possess a mind, yet a collection does.
Humans do possess minds, and a collection of them does not.
You can't use the first statement to support the opposite of the second statement because the premise is dissimilar.
By the Bekenstein bound; they would eventually run out of states to be in, so the total length of their experiences (if they have any) would be finite.
Humanity cannot conquer death.
Of course, the number of possible states is very very large, so, extremely long lived, sure.
But not immortal, unless expanding without end.
So for other things, it might be relevant that it continues to exist and repeats states, and it might even be worthwhile for it to make decisions while keeping in mind the fact that its decision might be at many different times (due to repeated states). But the length of its life internally viewed would still be finite, just with parts of it possibly having expression in infinitely many times of the external world.
As an absurd thought experiment, suppose that an entity arrives from the future, over the course of a year, builds a time machine, and then uses it to go back in time to become when it originally arrived. (as a bootstrap paradox sort of thing.) Would you say that the extent of the entities life is ~1 year, or infinite? There isn't any point in the cycle where it ends, but one wouldn't say that circles are infinitely long line segments, just because they don't have an end.
Humanity cannot conquer death, but this does not take away the immortality of living beings that already exist in our world.
Take a look at this 80,000 year old trees[3]. It's one living being in multiple trees with a single root system connecting all the trees into one being.
[1]https://en.wikipedia.org/wiki/Turritopsis_dohrnii [2]https://en.wikipedia.org/wiki/List_of_longest-living_organis... [3]https://en.wikipedia.org/wiki/Pando_(tree)
But things like long-term planning and goal formation aren't in this quick-reflex domain. (Though humans are arguably pretty bad at these sorts of activity too, on average.)
We're also generally training neural nets to succeed at well-defined, bounded tasks, which don't really require long term planning so much. The video-game playing work at Deep Mind is actually a pretty important step forward, though; they're doing impressive stuff with domain-transfer (learning multiple games with a single network), and as one goes further with games, we might start seeing longer-term planning and concept formation. (eg, if we start seeing awesome StarCraft players...)
There's a case to be made, though, that we humans just trained on a big, broad objective function - survive, thrive, and multiply - with training applied across millions of years. And a good deal of intense local training over the first ten years of life, using a massively parallel computer that far outstrips any data center.
The question for strong AI seems to rest heavily on how much extraneous work there is done in biology, and whether we end up with a system so complex that it requires eighteen years of training time. If creating a single strong AI actually requires that much effort, we don't have to worry too much about skynet, methinks.
But we certainly don't have to worry about them spontaneously arising when we train with simple objective functions.