There's so little liquidity post-merge that it's only worth mining as a way to launder stolen electricity.
The bitcoin people still waste raw materials, and prices are relatively sticky with so few suppliers and a backlog of demand, but we've already seen prices drop heavily since then.
AMD really needs to pick up the pace and make a solid competitive offering in deep learning. They’re slowly getting there but they are at least 2 generations out.
On desktops, only the 7000 series is kinda competitive for AI in particular, and you have to go out of your way to get it running quick in PyTorch. The 6000 and 5000 series just weren't designed for AI.
The existing ecosystems (cuda, pytorch etc) are all pretty garbage anyway -- aside from the massive number of tutorials it doesn't seem like it would actually be hard to build a vertically integrated competitor ecosystem ... it feels a little like the rise of rails to me -- is a million articles about how to build a blog engine really that deep a moat ..?
First of all you need hardware with cutting-edge chips. Chips which can only be supplied by TSMC and Samsung.
Then you need the software ranging all the way from the firmware and driver over something analogous to CUDA with libraries like cuDNN, cuBLAS and many others to integrations into pytorch and tensorflow.
And none of that will come for free, like it came to Nvidia. Nvidia built CUDA and people built their DL frameworks around it in the last decade, but nobody will invest their time into doing the same for a competitor, when they could just do their research on Nvidia hardware instead.
Realistically it's up to AMD or Intel.
https://www.cerebras.net/ Has innovative technology, has actual customers, and is gaining a foothold in software-system stacks by integrating their platform into the OpenXLA GPU compiler.
