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How to build a thinking AI

aithought.com

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Re: How to build a thinking AI

#41

Post by hathawsh »

zaking17 wrote: post #27

I like the process that goes into these "imagine the architecture of AGI" articles. It's all hypothetical, but it's really fun. But it's a missed opportunity if you don't embed LLMs in some of the core modules -- and highlight where they excel. LLMs aren't identical to any part of the human brain, but they do a remarkable job of emulating elements of human cognition: language, obviously, but also many types of reason…

I like to think we could quickly create a next-level AI (maybe AGI?) if we simply model it on the Pixar movie "Inside Out". The little characters inside the girl's brain are different LLMs with different biases. They follow a kind of script that adapts to the current environment. They converse with each other and suggest to the girl what she should do or say.

I'd try the idea myself, but I have a job. :-)

Re: How to build a thinking AI

#43

Post by jameshart »

dachworker wrote: post #7

Many such thinking architectures are probably possible. The hard part is learning a good representation of the world and all its constituents, without which none of these thinking architectures are possible. What's exciting about LLMs is that they are approaching this learned representation. There are already people attempting to build AGI (or less ambitiously, task automation) on top of LLMs with projects like BabyA…

If you insist on being able to boot the thing up and immediately be self aware, yes, you need to figure out how to construct it so that all the training of 'how to be this particular self aware intelligence' is intrinsic to it, which is a bootstrapping problem.

Human intelligence solves this a different way. It instantiates the architecture without any of the weights pretrained, in the form of a 'baby'. The training starts from there.

Re: How to build a thinking AI

#44

Post by alchemist1e9 »

It’s a bit buried but eventually there are references to SOAR and ACT-R which in my crude attempt to broach cognitive architectures were the two I had understood as being the leading models with tangible applied results and working code.

If anybody with an understanding of that field knows some good open source frameworks or libraries I suspect many beyond myself would be interested.

It’s not considered cognitive framework but in applied learning I’ve developed a fascination with MuZero algorithm and also been trying to better understand factor graphs as used in another less know cognitive architecture called Sigma. It feels like some mashup of LLMs, RAG and vector search, cognitive architectures (SOAR, ACT-R, Sigma), ReACT/OPA/VOYAGER, with proven algorithms like MuZero might be on the verge of producing the next leap forward.

Re: How to build a thinking AI

#45

Post by ilaksh »

zaking17 wrote: post #27

I like the process that goes into these "imagine the architecture of AGI" articles. It's all hypothetical, but it's really fun. But it's a missed opportunity if you don't embed LLMs in some of the core modules -- and highlight where they excel. LLMs aren't identical to any part of the human brain, but they do a remarkable job of emulating elements of human cognition: language, obviously, but also many types of reason…

I think LLMs did not exist or barely existed at the time he wrote this.

Re: How to build a thinking AI

#47

Post by gremlinsinc »

yagizdegirmenci wrote: post #32
jmac01 wrote: post #29

Earlier quoted context omitted.

I'm the best musician on earth but I can't play any instruments but I can imagine a really amazing song, you'll just never hear it because it would take 1000s of hours of me practicing to actually learn to play so that I could prove it. So you'll just have to make do with my words and believe me when I say I'm the best musician alive. Here's an article I wrote describing the song but without actually writing any of t…

You can go into studio with a producer and turn your ideas into a beat and then to a song. The same thing does not applies to engineering. This is like comparing apple with an orange.

well, you could hire a team of developers and neuroscientists to build a prototype of the idea and concept and do physical research, whether you yourself have the chops to do it yourself is irrelevant at that point.

Re: How to build a thinking AI

#48

Post by gremlinsinc »

ryanklee wrote: post #21

> simulate human-like thought processes It ought to be clear to a cognitive scientist (which the author is) that we do not know how human thought processes work except at a very course level. The idea that we have an understanding refined enough to take the next step and "simulate" these processes is just pure crackpot bunk.

If we only get it partially figured out, we can still get a vastly more intelligent artificial intelligence system, and then IT will figure out what we missed, especially if it is self-improving.

Re: How to build a thinking AI

#49

Post by gremlinsinc »

zaking17 wrote: post #27

I like the process that goes into these "imagine the architecture of AGI" articles. It's all hypothetical, but it's really fun. But it's a missed opportunity if you don't embed LLMs in some of the core modules -- and highlight where they excel. LLMs aren't identical to any part of the human brain, but they do a remarkable job of emulating elements of human cognition: language, obviously, but also many types of reason…

one important thing you left out - the ability to reproduce and thus "evolve" naturally, and at scale, to essentially keep improving its own brain to the point it outpaces current human researchers in self-improvement. If not reproduce, maybe reincarnate itself in version 2.0, 3.0, etc...
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