Ah, we're getting into more concrete considerations now. I think that's better. (I mean, if you choose to use "mean" in a way that implies certain details in t

Ah, we're getting into more concrete considerations now. I think that's better. (I mean, if you choose to use "mean" in a way that implies certain details in the causal history that I think aren't needed, and choose not to care about what AI systems do but only about that causal history, then all that's something you have the right to choose, and there's limited value in arguing about it. But if you have concrete predictions for what AI systems will be able to do, and what would need to change for them to be able to do more, then to me that's more interesting and more worth arguing about.) So, I think we're agreed now that the kind of question that really matters, for determining how much understanding some entity has of the words it's taking in and spitting out, is: how does its linguistic behaviour depend on the actual world, and how would it vary if the world were different, and how will it vary as the world changes? And I think we're agreed that today's LLMs learn about the world largely through their training process, which means that they have rather limited capacity once trained to adapt to the world, which puts real limits on what they can do. (I think you would also say that it means they don't really understand anything, because they can't adapt in real time as those things change, but again I think that goes too far, firstly because there are plenty of things we consider ourselves to understand even though they lie far in the past and aren't going to change, and secondly because LLMs _do_ have some ability to learn in the short term: if you say "All snorfles are porfles and my dog is a snorfle" and ask it a few sentences later whether you have a porfle, it will probably be able to say yes and explain why.) I am curious whether you think that, say, Helen Keller was dramatically less able to mean and understand things than most people, on account of being both deaf and blind and therefore dramatically less able to get new information about the world in real time other than "textually" (via Braille and the like). I think the available evidence strongly suggests that Keller was in fact able to understand the world and to mean things in pretty much the exact same way as the rest of us, which in turn strongly suggests that being connected to the physical world only through language isn't necessarily an obstacle to meaning and understanding things. (Keller did have other links to the physical world; for instance, her tactile sense was perfectly OK. This is actually how she first managed to grasp the idea that the words Anne Sullivan was tracing out on her hands meant something. However, it doesn't seem credible to me that this rather "narrow" channel of information-flow was responsible for Keller's understanding of most of the things she understood.) Suppose someone builds something like today's multimodal LLMs, but with constant real-time video input, and suppose it's trained on video as well as text. (It's not obvious to me how all that would work technically, but it seems to me that there are things worth trying, and I bet there are people trying them at OpenAI, Google, etc.) Would your objections then disappear?