AI image upscaleing isn’t something I would associate with being energy efficient or fast. I wonder how that’s supposed to work?
It seems like it would be extremely fast to me. Take a 50x50 block of pixels and expand those across a 100x100 pixel grid leaving blank pixels were you have missing data. If a blank pixel is surrounded by blue pixels, the probability of the missing pixel being blue is fairly high, I would assume.
That is a problem that is perfect for AI, actually. There is an actual algorithm that can be used for upscaling, but at its core, its likely boiled down to a single function and AI’s are excellent for replicating the output of basic functions. It’s not a perfect result, but it’s tolerable.
If this example is correct or not for FSR, I have no clue. However, having AI shit out data based on a probability is mostly what they do.
I’m very much not an expert, but I’d imagine it’s similar to how AES-NI works: the task is CPU/GPU-intensive until specific instructions are designed to do whatever blackmagicfuckery level math is required, and once it’s in hardware it’s more both power efficient and faster.
