Machine learning is a subset of artificial intelligence, along with things like machine perception, reasoning, and planning. Like I said in a different thread, ai is a really, really broad term. It doesn’t need to actually be Jarvis to be AI. You’re thinking of general ai
I know enough about how LLMs work to gauge how intelligent they are. The reason I have a different opinion than you is not because you or I lack understanding of how LLMs or diffusion models work, its simply that my definition of AI is more “lenient” than yours.
EDIT: Arguing about which definition is more correct is pointless because it’s totally subjective. However I think that a more lenient definition of AI is more useful in this case, because with more strict definitions we probably never will have something that could be considered AI.
It’s not completely subjective. Think about it from an information theory perspective. We want a word that maximizes the amount of information conveyed, and there are many situations where you need a word that distinguishes AGI, LLMs, deep learning, reinforcement learning, pathfinding, decision trees and the like from the outputs of other computer science subfields. “AI” has historically been that word, so redefining it without a replacement means we don’t have a word for this thing we want to talk about anymore.
I refuse to replace a single commonly used word in my vocabulary with a full sentence. If anyone wants to see this changed, then offer an alternative.
No we haven’t. We have an appearance of a AI. Large language models and diffusion models are just machine learning. Algorithm statistic engines.
Nothing thinks, creates, cares, or knows the difference between something correct or wrong.
Machine learning is a subset of artificial intelligence, along with things like machine perception, reasoning, and planning. Like I said in a different thread, ai is a really, really broad term. It doesn’t need to actually be Jarvis to be AI. You’re thinking of general ai
I know enough about how LLMs work to gauge how intelligent they are. The reason I have a different opinion than you is not because you or I lack understanding of how LLMs or diffusion models work, its simply that my definition of AI is more “lenient” than yours.
EDIT: Arguing about which definition is more correct is pointless because it’s totally subjective. However I think that a more lenient definition of AI is more useful in this case, because with more strict definitions we probably never will have something that could be considered AI.
It’s not completely subjective. Think about it from an information theory perspective. We want a word that maximizes the amount of information conveyed, and there are many situations where you need a word that distinguishes AGI, LLMs, deep learning, reinforcement learning, pathfinding, decision trees and the like from the outputs of other computer science subfields. “AI” has historically been that word, so redefining it without a replacement means we don’t have a word for this thing we want to talk about anymore.
I refuse to replace a single commonly used word in my vocabulary with a full sentence. If anyone wants to see this changed, then offer an alternative.
your definition of intelligence sounds an awful lot like a human, stop being entityist