As an update for anyone else who finds this thread, I found a list of currently supported CUDA Compute Capabilities in the NetTrain TargetDevice documentation section (kinda an obvious spot to look, sorry I missed it!)

Now we just have to wait for 2060s to go back to normal < $1000 prices... :(

The Wolfram language internally uses Apache MXNet, so we are at the mercy of their GPU requirements for ML training.

According to this Nvidia website regarding MXNet, "You will also need an NVIDIA GPU supporting compute capability 3.0 or higher."

The compute capability has to do with the computational instructions available in the graphics chip (in your case a GT 710 chip).

Edit: Actually, the GT 710 is not on the list because there are two versions of the GT 710. One version had a compute capability of 2.0 and the other 3.0.

Because Neural Network training worked for you in the past, your GT 710 probably has a compute capability of 3.0. Mathematica 12.2 seems to be compatible with CUDA version 11. According to the Nvidia forum, CUDA 11 requires a compute capability of 3.5, so your card is probably not compatible with CUDA 11. Maybe the upgraded version from the wolfram research server needs CUDA 11 features that your GPU is not compatible with.

I am not sure if the Wolfram plans to support older cuda versions, but some newer networks probably need operations that only higher compute capability GPUs can perform efficiently.