Hacker News new | past | comments | ask | show | jobs | submit login

The issue isn't number of designs but architectural stability. NVIDIA's chips have been general purpose for a long time. They get faster and more powerful but CUDA has always been able to run any kind of neural network. TPUs used to be over-specialised to specific NN types and couldn't handle even quite small evolutions in algorithm design whereas NVIDIA cards could. Google has used a lot of GPU hardware too, as a consequence.



At the same time if the TPU didn't exist NVIDIA would pretty much have a complete monopoly on the market.

While Nv does have an unlimited money printer at the moment, the fact that at least some potential future competition exists does represent a threat to that.




Join us for AI Startup School this June 16-17 in San Francisco!

Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: