AMD currently has a process lead over Nvidia (and this is rumoured to be set to continue for a little while longer - apparently the first consumer Ampere chips are being fabbed on Samsung's inferior 8nm process due to lack of capacity at TSMC for the next few months)
Nvidia has clearly had an architecture advantage, although RDNA2 may close this gap, depending on how Ampere performs.
While Nvidia has had a much stronger showing in the GPGPU space, with CUDA helping it be the clear current winner, this also appears to have driven architecture decisions at Nvidia with the focus on tensor cores.
In gaming, Nvidia has put a lot of work into utilising these tensor cores for Deep Learning Super Sampling (DLSS). The idea being that you render at a lower resolution and then use deep learning to upscale in real-time to higher resolutions. DLSS 2.0 made some leaps in quality and DLSS 3.0 is on the horizon. It will be interesting to see:
a) How well they can get this working b) Is AMD working on its own version of this? c) If so, how well will the RDNA architecture be suited to this approach?
Will be interesting to watch how this plays out!