That’s leaving out vital information however. Certain types of brains (e.g. mammal brains) can derive abstract understanding of relationships from reinforcement learning. A LLM that is trained on “letting go of a stone makes it fall to the ground” will not be able to predict what “letting go of a stick” will result in. Unless it is trained on thousands of other non-stick objects also falling to the ground, in which case it will also tell you that letting go of a gas balloon will make it fall to the ground.
Well that seems like a pretty easy hypothesis to test. Why don’t you log on to chatgpt and ask it what will happen if you let go of a helium balloon? Your hypothesis is it’ll say the balloon falls, so prove it.
That’s leaving out vital information however. Certain types of brains (e.g. mammal brains) can derive abstract understanding of relationships from reinforcement learning. A LLM that is trained on “letting go of a stone makes it fall to the ground” will not be able to predict what “letting go of a stick” will result in. Unless it is trained on thousands of other non-stick objects also falling to the ground, in which case it will also tell you that letting go of a gas balloon will make it fall to the ground.
Well that seems like a pretty easy hypothesis to test. Why don’t you log on to chatgpt and ask it what will happen if you let go of a helium balloon? Your hypothesis is it’ll say the balloon falls, so prove it.