On Thursday, December 31, 2020, at 8:40 PM, Colin Hales wrote:
> (i)                 Observation of a natural
context (empirical science).


> (ii)              Observation of artificial
versions of the natural context. Call this engineered or replicated nature a
‘scientifically-artificial’ version of nature (empirical science).


> (iii)            Creation of abstract models
predictive of the properties of the natural context observable in (i) and (ii)
(theoretical science).


Dude the brain doesn't depend on particles, atoms, cells, and a lot of other 
stuff. We can simulate bubbles without atoms. GPT-2 does not simulate / need 
atoms or other physics, the "atom" for GPT-2 or at least in my pre-AGI is 
"memories" of sequences like abcdef...

(i) and (iii) ok ... but (ii) IS already being done when we create things like 
GPT-2 and then observe GPT-2, because (ii) says "Observation of artificial 
versions" and GPT-2 IS an artificial "brain" that we then observe (my AI is not 
a black box or uses backpropagation like GPT-2 does yet will perform on par or 
better than GPT-2, and is much more natural just like a real human brain you'll 
see soon in a month).

Colin, if you have an AI (aka one you came up with, or not) that you want to 
run, you do it either of 2 ways, either run it on a computer simulated, or on a 
hardware chip/ etc "for real" or at least more realer than a computer at least. 
The neuromorphic chips are hardware that run specifically AI algorithms and 
therefore can run them faster, that's why they are called hardware 
accelerators. They are less general at computing, but faster for AI algorithms 
- that's the trade off. You said you can run your AI on a computer, so how does 
your AI work then!? Does it use backprop? How does it find Patterns in Data ex. 
'z' is the least common letter or eat usually follows dog. The only thing that 
exists in the universe is patterns, else all would be random and could not use 
any past experience memories to improve prediction decision making. And, if you 
want to run your AI on a real hardware accelerator to speed it up merely, why 
are you suggesting you can only make AI if run it on a accelerator? I thought, 
you said, you can run it on a computer? You say you want to observe it 
empirically on an accelerator chip but why - it will not behave different, it 
will only, ONLY, run faster. There's nothing to observe there then but speed. 
You can observe everything on a computer of your AI.

Lastly if you have full time to read this too, as said data in from random 
sources, desired data collection out to attain desired data from non random 
sources, it can do this in brain, ex. decide AGI is similar to food goal, so 
now it starts thinking about AGI not food as much hence collecting data from 
tests in its brain. You mentioned external lab world tests to prove theories 
simply as reinforcement, well, this is data collection from a specific domain 
still, a brain can do that in its head, it does not need a lab/world/ body to 
be a scientist, it just updates its hobby in its brain to change where it 
collects data from, repeat.
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Artificial General Intelligence List: AGI
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