Earlier quoted context omitted.
On the surface, it's not debatable. Enterprises are going full steam ahead on AI. Building out an ecosystem to challenge Nvidia seems like a decade long battle, if it's even possible.
What is full steam ahead for enterprises? It's not like they're throwing autoregressive LLMs into production any time soon. In any case Nvidia is expecting to ship ~550k H100s in 2023, hardly enough to satisfy every user. Tesla decided to in-house. TPUv4 and Gaudi2 exceeded A100 performance, they just never hit scale or the market and then Hopper added optimization for transformers rendering these chips relatively ob…
It's not unassailable. But it's going to take a lot to make any difference to Nvidia's volume or pricing, let alone a meaningful difference. They already face serious competitors in google and aws with TPU and inferentia, but those competitors are at a pretty big disadvantage for now (and others too). The cuda ecosystem is a big advantage. Nvidia has a lot of leverage with semi manufacturers because of volume. They spend way more on chip R&D than their competitors in the space. They have brand recognition. You can buy and own Nvidia chips v tpu and inferentia. It's... a tough road ahead for competitors.