> Phase 3: Emergence Layer
I see. So the author rejects the hypothesis of emergent behavior in LLM, but somehow thinks it will magically appear if the "engineering" is correct.
Self contradictory.
AGI is an engineering problem, not a model training problem
201–210 of 442 posts
Re: AGI is an engineering problem, not a model training problem
#202Earlier quoted context omitted.
I think Metzinger nailed it, we aren't conscious at all. We confuse the map for the territory in thinking the model we build to predict our other models is us. We are a collection of models a few of which create the illusion of consciousness. Someone is going to connect a handful of already existing models in a way that gives an AI the same illusion sooner rather than later. That will be an interesting day.
I don't see how your explanation leads to consciousness not being a thing. Consciousness is whatever process/mechanisms there are that as a whole produce our subjective experience and all its sensations, including but not limited to touch, vision, smell, taste, pain, etc.
You've missed our consciousness of our inner experiences. They are more varied than just perception at the footlights of our consciousness (cf Hurlburt):
Imagination, inner voice, emotion, unsymbolized conceptual thinking as well as (our reconstructed view of our) perception.
Re: AGI is an engineering problem, not a model training problem
#203Earlier quoted context omitted.
> AGI, by definition, in its name Artificial General Intelligence implies / directly states that this type of AI is not some dumb AI that requires training for all its knowledge, a general intelligence merely needs to be taught how to count, the basic rules of logic, and the basic rules of a single human language. From those basics all derivable logical human sciences will be rediscovered by that AGI That's not how n…
Are you sure? Do you require dozens, to hundreds, to thousands of examples before you understand a concept? I expect no. That is because you have comprehension that can generalize a situation to basic concepts which you apply to other situations without effort. You comprehend. AI cannot do that: get the idea from a few, under a half dozen examples if necessary. Often a human needs 1-3 examples before they can general…
Any human old enough to talk has already experienced thousands of related examples of most everyday concepts.
For concepts that are not close to human experience, yes humans need a comically large number of examples. Modern physics is a third-year university class.
Re: AGI is an engineering problem, not a model training problem
#204LLMs are semantic memory. Good job. Now build the other parts of cognitive systems.
Re: AGI is an engineering problem, not a model training problem
#205We don't know if AGI is even possible outside of a biological construct yet. This is key. Can we land on AGI without some clear indication of possibility (aka Chappie style)? Possibly, but the likelihood is low. Quite low. It's essentially groping in the dark. A good contrast is quantum computing. We know that's possible, even feasible, and now are trying to overcome the engineering hurdles. And people still think th…
> We don't know if AGI is even possible outside of a biological construct yet
Of course it is. A brain is just a machine like any other.
Re: AGI is an engineering problem, not a model training problem
#206Earlier quoted context omitted.
> there is missing philosophy I doubt it. Human intelligence evolved from organisms much less intelligent than LLMs and no philosophy was needed. Just trial and error and competition.
The magical thinking around LLMs is getting bizarre now. LLMs are not “intelligent” in any meaningful biological sense. Watch a spider modify its web to adapt to changing conditions and you’ll realize just how far we have to go. LLMs sometimes echo our own reasoning back at us in a way that sounds intelligent and is often useful, but don’t mistake this for “intelligence”
The idea that biological intelligence is impossible to replicate by other means would seem to imply that there’s something magical about biology.
Re: AGI is an engineering problem, not a model training problem
#207We don't know if AGI is even possible outside of a biological construct yet. This is key. Can we land on AGI without some clear indication of possibility (aka Chappie style)? Possibly, but the likelihood is low. Quite low. It's essentially groping in the dark. A good contrast is quantum computing. We know that's possible, even feasible, and now are trying to overcome the engineering hurdles. And people still think th…
> We don't know if AGI is even possible outside of a biological construct yet. This is key. A discovery that AGI is impossible in principle to implement in an electronic computer would require a major fundamental discovery in physics that answers the question “what is the brain doing in order to implement general intelligence?”
That question is not a physics question
Re: AGI is an engineering problem, not a model training problem
#208Earlier quoted context omitted.
Intelligence (solving problems) does not require consciousness.
Please elaborate.
Re: AGI is an engineering problem, not a model training problem
#209There is a reason why LLM's are architected the way they are and why thinking is bolted on. The architecture has to allow for gradient descent to be a viable training strategy, this means no branching (routing is bolted on). And the training data has to exist, you can't find millions of pages depicting every thought a person went through before writing something. And such data can't exist because most thoughts aren't…
You didn't mention it, but LLMs and co don't have loops. Whereas a brain, even a simple one is nothing but loops. Brains don't halt, they keep spinning while new inputs come in and output whenever they feel like it. LLMs however do halt, you give them an input, it gets transformed across the layers, then gets output.
While you say reinforcement learning isn't a good answer, I think its the only answer.
Re: AGI is an engineering problem, not a model training problem
#210If you believe the bitter lesson, all the handwavy "engineering" is better done with more data. Someone likely would have written the same thing as this 8 years ago about what it would take to get current LLM performance. So I don't buy the engineering angle, I also don't think LLMs will scale up to AGI as imagined by Asimov or any of the usual sci-fi tropes. There is something more fundamental missing, as in missing…
The counter argument is that we were working with thermodynamics before knowing the theory. Famously the steam engine came before the first law of thermodynamics. Sometimes engineering is like that. Using something that you don’t understand exactly how it works.