M
MazingerDUDE
It wasn't a prototype of FSR4, training for FSR4 would have been done at FP32 full precision or FP16 ironically on Nvidia hardware most likely, you train a model and that produces the models weights, but to do that you have to compute gradients, tiny incrementral adjustments over millions of iterations via back propogation.
Once your model is trained you can then freeze the weights and you can then quantize them down to FP8 or INT8, you're no longer computing those gradients you're just doing forward passes of them, you lose a bit of quality but gain a huge amount in terms of speed and efficiency.
When Cerny says it's the same neural network, he means it's the same, the quant is different, for RDNA4 on PC it will be FP8 because you have the 3rd Generation Matrix Acceleration Engine on the GPU's they can do FP8 and BF8 and on PS5 Pro you have INT8 support because it's more efficient per watt and uses less die space, but will have trouble running larger models as each weight and activation has to snap to a specific value say 43, it couldn't be 42.7.
The reason it's notr releasing on RDNA2/3 cards is the lack of ML Compute available on them, even the 7900XTX only has 123TOPS of ML Compute, the PS5 Pro has 303TOPS, so it will complete inference quicker and fit in the frametime budget.