(1) with enough high-quality training data, «AI» models should be able to output H265 / H266 / AV1 directly, can achieve simplicity and reduce artifacts by skipping an inferior compression step and leveraging temporal elements
(2) if AI video compression (as demoed by nvidia) becomes standard, the training data and generated data will become [more] «AI-native», boosting these efforts by miles
why would you want 1? having the raster frames is surely better for post production. I agree that models should take a stab at compression but I think it should be independent. At the end of the day you also don't want to be doing video compression on your GPU, using a dedicated chip for that is so much more efficient.
lastly, you don't want to compress the same all the time. FOr low latency we compress with no b-frames and a smallish GOP, with VOD we have a long GOP and b-frames are great for compression.
2. as long as we can again port the algo's to dedicated hardware, which are on mobiles a must for energy efficiency for both encode and decode
(1) with enough high-quality training data, «AI» models should be able to output H265 / H266 / AV1 directly, can achieve simplicity and reduce artifacts by skipping an inferior compression step and leveraging temporal elements
(2) if AI video compression (as demoed by nvidia) becomes standard, the training data and generated data will become [more] «AI-native», boosting these efforts by miles