So, the hidden mental model that the OP is expressing and failed to elucidate on is that llm’s can be thought of as compressing related concepts into approximately orthogonal subspaces of the vector space that is upper bounded by the superposition of all of their weights. Since training has the effect of compressing knowledge into subspaces, a necessary corollary of that fact is that there are now regions within the vector space that contain nothing very much. Those are the valleys that need to be tunneled through, ie the model needs to activate disparate regions of its knowledge manifold simultaneously, which, seems like it might be difficult to do. I’m not sure if this is a good way of looking at things though, because inference isn’t topology and I’m not sure that abstract reasoning can be reduced down to finding ways to connect concepts that have been learned in isolation.
Not the OP, but my interpretation here is that if you model the replies as some point in a vector space, assuming points from a given domain cluster close to each other, replies that span two domains need to "tunnel" between these two spaces.
So, the hidden mental model that the OP is expressing and failed to elucidate on is that llm’s can be thought of as compressing related concepts into approximately orthogonal subspaces of the vector space that is upper bounded by the superposition of all of their weights. Since training has the effect of compressing knowledge into subspaces, a necessary corollary of that fact is that there are now regions within the vector space that contain nothing very much. Those are the valleys that need to be tunneled through, ie the model needs to activate disparate regions of its knowledge manifold simultaneously, which, seems like it might be difficult to do. I’m not sure if this is a good way of looking at things though, because inference isn’t topology and I’m not sure that abstract reasoning can be reduced down to finding ways to connect concepts that have been learned in isolation.
A hallmark of intelligence is the ability to find connections between the seemingly disparate.
Not the OP, but my interpretation here is that if you model the replies as some point in a vector space, assuming points from a given domain cluster close to each other, replies that span two domains need to "tunnel" between these two spaces.