Exactly. Nvidia's current dominance is based on the notion that leading AI related libraries and tools depend on Cuda and run well on that. But that's not somet

Exactly. Nvidia's current dominance is based on the notion that leading AI related libraries and tools depend on Cuda and run well on that. But that's not something that will last. Many parties are working on making these libraries work against alternative architectures and untangling them from Nvidia specifics. Apple's laptops for example are pretty popular with people into LLMs. Why? They are good laptops with decent enough hardware and lots of people have them. The key point with that is that there's no nvidia hardware on Apple's platform and that a lot of work seems to be going into making sure Apple silicon is supported well in all relevant libraries and tools. And they are of course not the only ones. A lot of the bigger AI companies are using their own chips and platforms. Tesla, Google, Microsoft, Amazon, etc. And then there are Intel and AMD that are equally eager to grab more of the AI market. Add to that the emerging open source ecosystem around LLMs and you have a nice recipe for vendor neutral libraries used by world+dog and users simply cherry picking the market for the best hardware that can run those libraries. Nvidia has enjoyed a nice software moat for the last years but it won't last. Everyone is trying to engineer around them currently.