> They have no intelligence. These are very very very refined prediction engines.
"Very refined prediction engine" is not a bad working definition for intelligence. It is not the only component you need, but it might be the most important over-all capability.
If its making lots of errors, its not doing a very good job of predicting the outcome of its actions.
It's a terrible definition of intelligence. Intelligence is far more than just predicting things based on a massive set of similar things. We do do pattern recognition, but I don't need to have seen 10k dogs to be able to recognize a dog. And it's not a difference of degree, either. "Meaning" is something I am able to derive from my experiences, and it is not something an LLM does or will ever be able to do (nor is training data even analogous to having experiences in any way shape or form.)
I didn't say anything about training methods. I said an intelligence can predict things accurately, most particularly if it can predict the outcomes of possible actions it can take then it can do planning. Its especially important that it should be able to predict outcomes in cases that are not exactly the same as things it has seen before, but how it gets to that capability level is not important for understanding what the capability unlocks.
This is one of the most distinctive qualities of human intelligence compared to many animals - is our ability to adapt to new situations and make accurate predictions of the outcomes of our actions. Other animals can also do this but over very narrow time horizons and situations.
AI agents are better at it than any animal, and better at it than humans in some domains.
Is "meaning" inherent to intelligence? Is emotion and the ability to have a subjective experience inherent to meaning? Genuine questions that I'm not sure we have good answers for yet.
Your other point that humans need very few examples for learning vs. what LLMs need is an interesting one. A few researchers talked about this very thing on the most recent episode of Dwarkesh's podcast.
My own view is that it seems unfair to compare an LLM's training with just what a human gets over the course of a lifetime, because our brains have been trained by a billion years of evolution for pattern matching. I'm not at all confident that AI models won't catch up.
"Very refined prediction engine" is not a bad working definition for intelligence. It is not the only component you need, but it might be the most important over-all capability.
If its making lots of errors, its not doing a very good job of predicting the outcome of its actions.