How is it improving, that would require rearranging its weights and biases which it cannot do easily or quickly.

Self improvement during training, and AI self training are already happening. Easily/quickly are seemingly a factor of how much power/hardware you want to use at once.

With the level of compute they have they aren't stuck with frozen models like you are.

Is easily and quickly a requirement? Isn't it enough that over time it improves itself even if the process is complex and slow?

Do we know it's actually improving itself? Perhaps it's just opaquely sorting all ones and zeros for better lookup efficiency.