Comment by salawat
2 months ago
Their world model is completely a byproduct of language though, not experience. Furthermore, they by deliberate design do not maintain any form of self-recognition or narrative tracking, which is the necessary substrate for developing validating experience. The world model of an LLM is still a map. Not the territory. Even though ours has some of the same qualities arguably, the identity we carry with us and our self-narrative are incredibly powerful in terms of allowing us to maintain alignment with the world as she is without munging it up quite as badly as LLM's seem prone to.
How do you know ours is any different, that we are not in a simulation or a solipsistic scenario? The truth is that one cannot know, it's a philosophical quandary that's been debated for millennia.
It is absolutely obvious how different it is from interacting with any LLM about the ways that it is wrong.
Nope, appeal to obviousness is not a sound argument. There are many things people thought were obvious that were wrong.
2 replies →
Simple. I have two sets of data I can pull from to validate a claim an LLM makes. I have the linguistic corpora we produce (artificial memory, analogical to latent space built by an LLM). You are correct in that this modality is shared. I also, however, have internal self-narrative and experiential state that is non-linguistic, but sensory/perception driven. An LLM can try to convince me that a bunch of mathematicians would come up with a system that requires one to make many copies of the same bitwise representation of a block for loading by the execution framework due to munging of the latent space via quantization. However, I have recollections of my time amongst Mathematicians and theorists. I can replay my lived perceptions of those times, and analyze and extract new meaning from them as my neural hardware evolves. Therefore, when that claim is made, my validation of the world as she is comes to a screeching halt to the tune of a recollection of a calculus class where the entire point is to pound into you the utility of fungibility of mathematical representations (substitution), and a further connection to optimization (replace entire cluster of an equation with a letter to process other things first and deal with the internal details later). That synthesizes also to the principle Mathematicians are both lazy, and clever. Alias that bitch, and moving right along. LLM's don't have that without you deliberately injecting that mechanism into their context. They'll in fact just run off the rails.
Now, could an equivalent process be modelled at some point? Probably. It'd be a conscious decision to do so on our part, and given fears over the AI Alignment quandary, it seems a rather fraught direction to carelessly proceed.