Enterprise grade workstations and servers can be configured with 1TB of ram though, so it's not completely inconceivable that you could have a dedicated GPU workstation with 1TB of graphics ram. I mean the Tesla A100 cards have 40GB of VRam each so you'd only need 26 of them to have 1TB of VRAM in a single machine. While I have no idea if such a machine exists, it certainly could exist, 26 GPUs wouldn't fill even half of a server cabinet.

Edit: actually Quattro A6000 cards ship with 48GB vram each, so you only need 22 of those to have 1TB total.

I'm not super knowledgeable in machine learning but given that system RAM (not VRAM) in the TB range is really not that rare these days for high end workstations I assumed that the poster meant that you'd have 1TB of working RAM per GPU for the learning job (which would be paged in and out of VRAM as necessary).

I guess the lesson to be learned here is that if you want to use an implausibly huge amount of RAM to make a point, a TB is not safe anymore. Go for Exabytes instead, that should be unambiguous for a couple of years.