NVIDIA's new Blackwell GPUs command a hefty price tag, reportedly double that of Google and Amazon's custom silicon. Yet, Morgan Stanley argues the performance justifies the spend, though alternative metrics cast a shadow.
Altos Computing is making a play for South Korea's discerning AI server market. They're bringing Nvidia's shiny new Blackwell architecture and their own software to the party.
NVIDIA's Blackwell chips guzzle 15-18 times more ABF substrate than older GPUs. The catch? A Japanese food seasoning company holds the keys—and it's running dry.
Deep in Argonne's labs, 100,000 Nvidia Blackwell GPUs hum to life. This isn't sci-fi; it's Uncle Sam's bid to own AI's future — nukes, climate, and all.
The US Department of Energy just greenlit seven massive AI supercomputers from Nvidia and Oracle, headlined by Argonne's 100,000-Blackwell-GPU Solstice. It's the government's boldest AI infrastructure play yet, but will 'agentic scientists' actually crack real discoveries?
Picture this: 72 Blackwell GPUs humming in one rack, primed for your trillion-parameter AI model. One bad schedule across cliques, though, and it's slower than a single H100.
NVIDIA's platform just swept MLPerf Inference v6.0, claiming the lowest token costs ever. But after 20 years watching Valley hype, I'm asking: who's actually banking the profits here?
Data scientists drown in terabytes while CPUs choke. NVIDIA's RTX PRO 6000 Blackwell Workstation Edition claims to fix that with data-center muscle at desk level — but supply woes and real-world fit raise questions.
1,000,000x. That's how much NVIDIA claims its chips have boosted inference throughput per megawatt across six generations. Impressive—if it holds up outside the demo reels.
Forget centralized clouds—telcos are wiring their networks into AI grids with NVIDIA's help. It's the edge computing tsunami we've been waiting for.