[4gotunameagain]

Because intelligence is so much more than stochastically repeating stuff you've been trained on.

It needs to learn new information, create novel connections, be creative.. We are utterly clueless as to how the brain works and how intelligence is created.

We just took one cell, a neuron, made the simplest possible model of it, made some copies of it and you think it will suddenly spark into life by throwing GPUs at it ?

[atleastoptimal]

>It needs to learn new information, create novel connections, be creative.

LLM's can do all those things

[4gotunameagain]

Nope. Can't learn anything after the training data, only within the very narrow context window.

Any novel connections are through randomness, hence hallucinations instead of useful connections with background knowledge of involved systems or concepts.

About creativity, see my previous point. If I spit out words that go next to eachother, it won't be creativity. Creativity implies a goal, a purpose, or sometimes by chance, but utilising systematic thinking with understanding of the world.

[atleastoptimal]

I was considering refuting this point by point, but it seems your mind is already made up.

I feel that many people who deny the current utility and abilities of large-language models will continue to do so far after they've exceeded human intelligence, because the perception that they are fundamentally limited, regardless of whether they actually are or if their criticisms make any sense, is necessary for some load-bearing part of their sanity.

[4gotunameagain]

I never denied the utility or abilities of LLMs. I use them almost daily, and they can be very useful.

I am denying that they are intelligent, or that by scaling them / upgrading them they will suddenly spring to life and become AGI.