Now it should be noted that DLSS has to be trained per-game; it isn’t a one-size-fits all solution. This is done in order to apply a unique neutral network that’s appropriate for the game at-hand. In this case the neural networks are trained using 64x SSAA images, giving the networks a very high quality baseline to work against.
None the less, of NVIDIA’s two major gaming use cases for the tensor cores, DLSS is by far the more easily implemented. Developers need only to do some basic work to add NVIDIA’s NGX API calls to a game – essentially adding DLSS as a post-processing stage – and NVIDIA will do the rest as far as neural network training is concerned. So DLSS support will be coming out of the gate very quickly, while raytracing (and especially meaningful raytracing) utilization will take much longer.