How would DLSS, which runs on GPU hardware — and specifically, as I understand it, GPU hardware that accelerates AI inference — eliminate the GPU?

And if a system is intended to be modular and upgradable, what would combining the GPU and CPU into a single module contribute to this goal?

Now an architecture that separates the memory controller from the CPU and gives pluggable CPUs and GPUs (and storage and network controllers, for that matter) equal access to a single pool of RAM in a secure and high-performance way, that would certainly be interesting, and not only or even primarily for gaming.

DLSS does not require any specific packaging configuration. There's no reason DLSS can't run on DGX Spark or GPU cores of the Apple's M-chips aside from specific Nvidia software optimizations that can surely be worked out if needed.

I imagine the PCs for the future would maybe have motherboard with two sockets: a normal CPU one and a GPU one, both having access to some high bandwidth unified memory that.

Right now the unified memory needs to be pretty much soldered super close to the chip to ensure the bandwidth and energy efficiency, but hopefully there will be some solution to circumvent this limitation in the future.

Putting CPU and GPU cores into the same physical die works for your average consumer machines, but hardcore professionals or enthusiasts would always strive for more custom configurations than existing packages can provide, like more GPU cores.