>No, that's exactly not how LLMs work. They are extremely good at predicting what sentences resemble the sentences in their training data and creating those. Th

>No, that's exactly not how LLMs work. They are extremely good at predicting what sentences resemble the sentences in their training data and creating those. That's all. It's a little hard to take this argument entirely at face value when you can ask it to produce things that aren't in its training data to begin with, but are synthesized from things that are in the training data. I remember being pretty impressed with reading the one where someone asked it to write a parable in the style of the King James bible about someone putting peanut butter toast in a VCR and it did a bang up job. I've asked it to explain all sorts of concepts to me through specific types of analogies/metaphors and it does a really good job at it. I think the semantics around whether it itself possesses or is displaying "intelligence" isn't the point. I treat it kind of like an emulator. It's able to emulate certain narrow slice of intelligent behavior. If a gameboy emulator still lets me play the game I want to play, then what does it matter that it's not a real gameboy?