Comments on: AGI from AI

By: Bruce LaDuke

Bruce LaDuke — Fri, 08 Feb 2008 12:58:31 +0000

What is missing is an understanding of how knowledge is worked within the individual, in groups, and how these interact with each other and the social knowledge base. Until this entire knowledge working process is fully understood, no algorithm can enhance it or accurately represent it.

So neither AI or AGI are correct approaches. When knowledge working processes are appropriately understood, knowledge creation will finally be accurately differentiated from intelligence and we’ll no longer be trying to create any kind of artificial ‘intelligence’ (it already exists), but will understand that the real problem, and opportunity, on the table is artificial ‘knowledge creation.’

By: Jeffrey Herrlich

Jeffrey Herrlich — Mon, 07 Jan 2008 20:21:45 +0000

Based on my (currently very elementary) understanding of Novamente’s structure, I think that it may be a sufficiently ideal platform for directly implementing a version of Friendliness. Implemented as repeated throughput. It has the structure to incorporate (learned) abstract concepts, (eg. “what is compassion”) and “common sense”. Now if we can just get some large investments into Novamente R&D.

By: Jeffrey Herrlich

Jeffrey Herrlich — Sun, 06 Jan 2008 21:21:10 +0000

Eh… scratch that. I think a better description would be an internal model (algorithmic knowledge matrix) of “how things relate”. I think that understanding a concept is being able to relate it to other things/concepts. “How things work” and “how things relate” are probably roughly synonymous, but “how things relate” I think is a better description. By “perceived” in the above, I meant: calculated. The diverse throughputs are always perceived (ie. calculated) in-relation-to the internal model. As a simple example: The procedure is “add 2″. When the input is 3, the output is 5. But when the input is 6, the output is 8. However, in both cases the output/throughput is always calculated “in-relation-to” the algorithmic procedure.

By: Jeffrey Herrlich

Jeffrey Herrlich — Wed, 02 Jan 2008 22:40:49 +0000

“Iâm on-and-off thinking about a potential PhD project in knowledge representation, and computing power is the last thing on my mind; I think that getting the right ideas is much more important.”

I agree; algorithmic knowledge representation is probably the proverbial “vital essence” of AGI (in a way not terribly dissimilar from how humans learn about their environment). I think that general intelligence is the possession of a (variably useful) internal model (algorithmic knowledge matrix) of “how the environment works”. The relevant forms of throughput are “filtered” through this model. Or put another way, the diverse throughputs are always perceived in-relation-to (or by-reference-to) this algorithmic knowledge matrix. That’s why our human intelligence is flexible – diverse forms of throughput are always filtered through our internal model of “how things work”.

By: Emily Alders

Emily Alders — Mon, 17 Dec 2007 07:31:20 +0000

If someone wins it , we are likely to have AGI. But there is also a chance that the Turing Test could be one by “fooling” the judges with human-like responses: Something like ELIZA but much better.

Also, we may achieve AGI without the Turing Test. What if someone creates an intelligence that can figure things out, be tricky and clever, but is fundamentally alien to the human way of thinking. Human thought is very specific — an AGI need not follow its model at all.

By: name

name — Sun, 16 Dec 2007 21:41:18 +0000

There’s a competition every year to see if somebody can write a program to pass the Turing Test. Once somebody wins that contest, we’ll have AGI.

By: Roko

Roko — Sat, 01 Dec 2007 12:47:43 +0000

I’d have to agree with Jeff. QC is not the cure for all ills, and besides, there are no usefully large quantum computers around. Also, why is everyone so excited about getting more computing power? I’m on-and-off thinking about a potential PhD project in knowledge representation, and computing power is the last thing on my mind; I think that getting the right ideas is much more important. Well, perhaps I’ll be singing a different tune when I’m actually getting down to writing some programs and then trying to run them ;-0

By: Jeffrey Herrlich

Jeffrey Herrlich — Sun, 18 Nov 2007 21:42:33 +0000

It’s true that you can’t create an intelligent algorithm with unlimited (or infinite) generality. Even the most “general” modules of the human brain still require that the environment be learned (ie. “specialized” by the environment) – before any significant intelligence can be deployed. But the human brain *is* an existence proof that “general” intelligence can exist *at least* up to the human level. And I think that there is good evidence that the human level can be well exceeded.

By: Jeffrey Herrlich

Jeffrey Herrlich — Sun, 18 Nov 2007 21:30:56 +0000

“Two. What impact will quantum computing have on AGI research and theories? D-Wave aside, researchers *are* making advances in this area.”

I expect, not much direct impact. Quantum computing is fit only for highly specialized processing. Eg. Decryption and Factoring large numbers. QC isn’t fit for programming “stable/rigid” algorithms that will be necessary for an AGI. AFAIUI, in QC, until the algorithms “decohere”, the algorithms can basically be considered to be random. (ie. not useful for constructing an AGI). QC might indirectly have a modest impact by furthering our understanding of science or engineering in a different domain. But, I’m no QC expert.

By: Otto Valtakoski

Otto Valtakoski — Sun, 18 Nov 2007 20:53:31 +0000

I, too, have longed for a distributed computing – type of thing for AGI research projects, but have been frustrated that none exists. I’m quite convinced that protein folding projects like Folding@Home (nearly 1.5 PetaFLOPS!) and Rosetta@Home have benefitted tremendously from such computing power, even if computer simulations are (always) approximations.

If AGI (or even narrow AI) research projects would benefit from some kind of distributed computing, I would gladly donate CPU time.