So we have to buy new processors.
Software encoder/decoder implementations will also be a thing in the interim, until the hardware is ready.
Even if AV1 and VP9 share structurally similar components, no VP9 decoder is going to work out of the box. It may mean that people who produce AV1-capable encoding/decoding hardware have a better starting point, though (provided they had VP9 hardware, beforehand)
Sadly Netflix doesn't see it that way and demands that I update my perfectly functional i7-2500 system to a newer one to play back their 4k content.
(Sorry, slightly OT rant).
First, the reprogrammability of FPGAs means lots of unused gates and less density, or wasted space. with flash technology nowadays, it doesn't waste as much power, but the footprint is just so large it's not worth it.
Second, a lot of the things that make custom silicon fast can be found in GPUs, such as ALU, MAC, FFT, FIR, SIMD and other DSP slices. Sure, there is a whole additional layer of optimization that can be done with custom silicon, but the computational powerhouses already exist. It's mostly (not all) a matter of reprogramming the memory movements from block to block, delegating certain operations to the CPU and general optimization. Most new codec algorithms can probably done pretty well with GPUs on phones these days.
And unfortunately, cell phone companies aren't interested in keeping older HW relevant :( Other industries might, though. My friend said lots of military radar projects he worked on used FPGAs.
Dedicated, fixed silicon will outperform FPGA's in performance and energy use practically every time.
For rare/uncommon use cases, having an FPGA you can adapt to your algorithm is fantastic, but for a use case as common and day-to-day as decoding video, a dedicated chip is far more ideal.
>PureVideo occupies a considerable amount of a GPU's die area
Intel implemented VP9/h265 decoding in its processors just recently.