[HarHarVeryFunny]

The compute edge belongs to those like Google (TPU) and Amazon/Anthropic (Trainium) building their own accelerators and not paying NVIDIAs 1000% cost markups. Microsoft just announced experimenting with Cerebras wafer scale chips for LLM inference which are also a cost savings.

Microsoft is in process of building optical links between existing datacenters to create meta-clusters, and I'd expect that others like Amazon and Meta may be doing the same.

Of course for Musk this is an irrational ego-driven pursuit, so he can throw as much money at it as he has available, but trying to sell AI when you're paying 10x the competition for FLOPs seems problematic, even you you are capable of building a competitive product.

[Tycho]

Timing matters. A long term strategy for superior hardware might bear fruit too late.

[HarHarVeryFunny]

I'm not sure about that - I expect AI is going to become a commodity market, so it doesn't matter how late you are if you've got a cheaper price.

In terms of who's got a lead on cheap (non-NVIDIA) hardware, I guess you have to give it to Google who are on their 6th generation TPU.

[vardump]

I wonder how Tesla's training computer Dojo is doing. Although I guess there's a reason for buying so much Nvidia hardware...

[theckel]

Curious where you saw the Microsoft/Cerebras experimentation noted online? That's very interesting.

[HarHarVeryFunny]

It was mentioned in Anthropic Jack Clark's "Import AI" newsletter.

https://jack-clark.net/2025/02/17/import-ai-400-distillation...