Nvidia selling more GPU's at the cost of it's datacenter business is pretty close to Kodak selling digital cameras at the cost of film.
The data center side is so bloated anything that eats into it is a huge negative. Their data center business brings in 20x the gpu market. Local open weight models will be what pops the bubble and China will do anything in it's power to enable that pop.
> Nvidia selling more GPU's at the cost of it's datacenter business is pretty close to Kodak selling digital cameras at the cost of film.
This assumes a) AI is a zero-sum game, and b) we're actually talking about on-prem AI will replace cloud-based AI. I think neither statements are true.
AI is like compute: we'll need all sorts of it, in various sizes, everywhere. I'm sure Nvidia whats to own all the workloads.
On the other hand, I do think open weight, like open source, will win in general.
> Nvidia selling more GPU's at the cost of it's datacenter business is pretty close to Kodak selling digital cameras at the cost of film.
You mean they resisted the idea trying to protect their legacy business, and it ended up all but killing them?
Hmm this sounds like an incumbent missing a paradigm shift because they didn't want it to disrupt their core (usually enterprise) business, although riding the shift would have ultimately delivered an order magnitude larger business.
Classical example is Microsoft actively undermining mobile because it threatened selling Windows or enterprise licenses.
Or Yahoo fighting Google's model because the latter model's didn't depend on taking enterprise deals to rank results.
Could you explain what you mean by this? I thought all of their insane profitability and returns are from crazy margins on their GPUs. I know they started/partnered/invested in some data center businesses, but I thought they were fledgling
Their data center business is selling gpus. They wrap them in a complete platform, but that's what they are selling.
They do report it separately from consumer and business sales of gpus used in PCs.
Could you put that in units of HP Printers and Toner please?
You need 64 H200 super-node for inference for kimi k3. You will not do inference locally. What might pop the western hardware bubble is Chinese GPU, memory, networking companies. But even in China, these AI centric hardware is not cheap.
I wonder what the thinking inside NVIDIA is at the moment. They have countless examples to learn from here, about the danger of not being willing to cannibalize your high end products. But, of course, there’s a reason that there are lots of examples of this sort of failure.
There’s plenty of competition that would be happy to attack them from below, though…