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0 pointsthfuran2y ago0 comments

It depends what exactly you mean by "LLM". But an ANN is effectively a function approximator. If you made one big enough to very closely approximate the entire quantum state of a person interacting with an environment, would you still declare that nothing it could do is "thinking"?

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10 comments · 3 top-level

Alchemista2y ago· 4 in thread

This is silly, that's like talking about building a fusion reactor modeled after the sun. It is easy to propose something like that, but we always seem to be 10 years away from realizing it. In fact it could be easier to solve the fusion problem than trying to build a machine/software that closely approximates a human brain as you suggest.

Yes it would be wonderful if sci-fi was real, but we need to deal in what is possible in reality.

thfuranOP2y ago

Yes, that was obviously an extreme example. But we know that it is possible in reality to implement a physical system that does what we call thinking. There is, I think, no particular reason to suppose that it's physically impossible re-implement the functionality with much less meat. Supposing that you've done this, you then just need to more clearly define "thinking" and "LLM" to determine whether changing that re-implementation to be closer to an LLM results in it losing the ability to think before it gets there.

daveguy2y ago

I think you underestimate the efficiency of meat.

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genman2y ago

Perhaps the question was not fully understood. A function is simply a mapping from one state into another. In principle we can define it over what ever state. As such we can consider a human thinking as kind of a function.

ANN are function effectively approximators.

The question was - if an ANN would very closely approximate the "human thinking" function then can we still say that it is not thinking?

daveguy2y ago

In order to train an ANN to approximate the "human thinking" function, we would have to know that function well enough to give it examples and counterexamples. Currently we are only training LLMs to approximate the "human blabbing" function.

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Jensson2y ago· 2 in thread

To approximate a function with a loop you would need a close to infinitely large neural net. Humans do have loops in their thinking, we need a new architecture for LLMs to be able to think in loops.

thfuranOP2y ago

I don't think anyone would say that being an RNN disqualifies an architecture from being considered an LLM.

Jensson2y ago

But we don't know how to train those to be good yet. It would require some novel step there, and it is unclear if it would still be anything like current LLMs after that.

Verdex2y ago· 1 in thread

I don't know. This feels like an unfair question to ask. You've proposed a basically impossible engineering problem and then declared that the outcome will obviously be the outcome that you want it to be.

What if I answer, "No because humans have supernatural souls."

You can easily answer, "Souls don't exist, therefore I'm still right."

But then we actually build your machine and it turns out that Penrose's non-computable microtubules really exist and the machine is useless.

We can't know the result of such an ambitious endeavor before we go through with it. So it doesn't make much sense to me to use such a thought experiment as evidence for something much lesser that is currently contested.

thfuranOP2y ago

You think it's unfair to ask whether a simulation of a person can think in a discussion on whether some particular class of algorithm can think? Lacking a clear definition of what exactly an LLM is and what thinking is, I can't think of a single more germane question (aside from what those definitions are, I suppose).

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10 comments · 3 top-level

Alchemista2y ago· 4 in thread

Yes it would be wonderful if sci-fi was real, but we need to deal in what is possible in reality.

thfuranOP2y ago

daveguy2y ago

I think you underestimate the efficiency of meat.

1 more reply

genman2y ago

ANN are function effectively approximators.

The question was - if an ANN would very closely approximate the "human thinking" function then can we still say that it is not thinking?

daveguy2y ago

1 more reply

Jensson2y ago· 2 in thread

To approximate a function with a loop you would need a close to infinitely large neural net. Humans do have loops in their thinking, we need a new architecture for LLMs to be able to think in loops.

thfuranOP2y ago

I don't think anyone would say that being an RNN disqualifies an architecture from being considered an LLM.

Jensson2y ago

But we don't know how to train those to be good yet. It would require some novel step there, and it is unclear if it would still be anything like current LLMs after that.

Verdex2y ago· 1 in thread

What if I answer, "No because humans have supernatural souls."

You can easily answer, "Souls don't exist, therefore I'm still right."

But then we actually build your machine and it turns out that Penrose's non-computable microtubules really exist and the machine is useless.

thfuranOP2y ago

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