Alan,

You make the same traditional mistake that many make. You offer a
substantial scientific contribution obtained by humans using their human
intelligence, but never explain the process in their brains that made it
possible for them to do all that. Jeff Hawkins (On Intelligence) does the
same. His entire book revolves around certain "invariant representations"
but he never explains where those come from. Your proposal is the usual
mixture of man-made intelligence and promises. It does not contribute to
artificial intelligence. 

The keywords are "association" and "emerge." You write:

"The next challenge is that you need to break channel dependence and
introduce associations between patterns ie with faces and the various
representations of the word "face". I suspect that once channel dependence
is fixed, then, at some high level in the network, these associations will
emerge on their own. " 

"Introduce associations" means, in your mind, that you or some other human
will be using their human intelligence, not artificial intelligence, to find
those associations and introduce them in the program. "Emerge" indicates you
realize that something is still missing and blame something else that you
can't explain. You are not alone. 


Sergio


-----Original Message-----
From: Alan Grimes [mailto:[email protected]] 
Sent: Friday, June 29, 2012 8:20 AM
To: AGI
Subject: Re: [agi] Building high-level features using large scale
unsupervised learning

Ben Goertzel wrote:
> How exactly do you suggest to bridge the functionality gap between 
> visual pattern recognition and all the other things human beings do?

=)

Setting aside problems noted as still being unsolved, here's a crude sketch
of how the system can be organized. For the sake of brevity, only the
cortical-thalamic-cortical system will be considered.

The first thing to note is that this is an unsupervised pattern learner.
That should be pretty amazing all by itself. The second thing to note is
that all it deals with are vectors of numbers. There is no reason on earth
that it can't be made to work with any conceivable stimulus that can be
encoded as a vector of numbers. There are some serious channel dependence
problems, previously noted, but the basic process is present.

The third thing to note is that they could run their matrix stack in reverse
and "imagine" what a face looks like. This is critical, especially for motor
control! =P

This is your basic algorithm. The next challenge is that you need to break
channel dependence and introduce associations between patterns ie with faces
and the various representations of the word "face". I suspect that once
channel dependence is fixed, then, at some high level in the network, these
associations will emerge on their own.

The next issue is topology. You could organize the topology like the human
brain and, in theory, it should be human equivalent. Motor control is
implemented just like perception. It builds up complex sequences of actions
from simple sequences of actions exactly as complex perceptions are built up
from simple perceptions. To do something, you just run the stack in reverse,
as mentioned above. Combined with channel dependence and free association,
you obtain arbitrary sequences of planned actions.
Actions that are fully learned become habitual (simply initiate the top
level abstraction). Other actions require an iterative system-wide process
for planning, but most of the mechanisms are already present.

You obtain episodic memory by having a pipeline that associates concurrent
perceptions, which appears to be what the hypocampus does.

To obtain super-human intelligence, you need to make the topology of the
system adaptive, or even accessible to the system itself. Ideally, you want
a highly redundant, highly distributed, highly parallel and highly efficient
architecture. This architecture does have a second class of scalability
issues, each matrix, at each level of abstraction is of fixed size, There
needs to be a process that simplifies and consolidates knowledge to a more
ideal representation. At that point you're off the edge of the
(metaphorical) napkin I sketched this all out on. =P

About 80% of everything else you need is already available off the shelf,
the other 20% might have some important, perhaps even difficult, challenges
but then we're talking about emotions and motivation instead of
intelligence.

--
E T F
N H E
D E D

Powers are not rights.





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