Any motor going out is based on a reason where to do it, how to do it, ex. go
to workshop and try making smaller disc cluster bits addresses. Try randomly
here. So you have a reason how to do your random motor out. You have egg. Then
data in feedback is seen/told to it. All we need do is let it think, OK, and if
it wants data from certain experiments its SUREof then we will return it
results. How many times does somewhere go build tools by trying fully random
crap? They have egg/plan first. The feedback is actually just more data, but
related data as well, very precise and may only answer their question ex. what
happens if you put carbon bits near too many clusters when inventing HDD? So in
a sense it can just eat data and not even try stuff! But it can ask for us to
return it specific facts. And it can learn where to eat internet source from.
The big data will advance it. When someone goes and invents a tool, like HDD,
nanobot replicator, speaker, monitor, phone, knife, hammer, car, glass,
shelter, they have internal goals on big data and they have a idea already, so
if we tweak the idea and return data results it can progress to next phase. We
just grab data from certain idea/area. Anyway big diverse data especially nano
engineering should punk the shit right out of its understanding of things.
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Artificial General Intelligence List: AGI
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