[WrtCdEvrydy]

I did a lot of my learning on a GTX 1060 about 2 years ago with 16gb of RAM and an i5-6400.

The issue with machine learning is that you need enough GPU VRAM to load your dataset and then have to wait for a result being trying something else.

If you have too little VRAM, you get nothing done, but if your GPU is slow (GTX 1070 is about 2x faster than a GTX 1060) you will have to wait before learning something after trying something. The feedback loop for learning is better if you're able to iterate quickly. This is why you sometimes see GPU rigs with up to 4 GPUs that are not being used on the same task (so you can do more than 1 thing at a time)