Nvidia’s $20 billion strategic licensing deal with Groq represents one of the first clear moves in a four-front fight over the future AI stack. 2026 is when that fight becomes obvious to enterprise builders.For the technical decision-makers we talk to every day — the people building the AI applications and the data pipelines that drive them — this deal is a signal that the era of the one-size-fits-all GPU as the default AI inference answer is ending.We are entering the age of the Disaggregated Inference Architecture, where the silicon itself is being split into two different types to accommodate a world that demands both massive context and instantaneous reasoning.Why inference is breaking the GPU architecture in twoTo understand why Nvidia CEO Jensen Huang dropped one-third of his r [...]
From miles away across the desert, the Great Pyramid looks like a perfect, smooth geometry — a sleek triangle pointing to the stars. Stand at the base, however, and the illusion of smoothness van [...]
Jensen Huang walked onto the GTC stage Monday wearing his trademark leather jacket and carrying, as it turned out, the blueprints for a new kind of monopoly.The Nvidia CEO unveiled the Agent Toolkit, [...]
Nvidia on Monday took the wraps off Vera Rubin, a sweeping new computing platform built from seven chips now in full production — and backed by an extraordinary lineup of customers that includes Ant [...]
Baseten, the AI infrastructure company recently valued at $2.15 billion, is making its most significant product pivot yet: a full-scale push into model training that could reshape how enterprises wean [...]
Lowering the cost of inference is typically a combination of hardware and software. A new analysis released Thursday by Nvidia details how four leading inference providers are reporting 4x to 10x redu [...]
Enterprises expanding AI deployments are hitting an invisible performance wall. The culprit? Static speculators that can't keep up with shifting workloads.Speculators are smaller AI models that w [...]
Nvidia on Monday unveiled a deskside supercomputer powerful enough to run AI models with up to one trillion parameters — roughly the scale of GPT-4 — without touching the cloud. The machine, calle [...]
Every GPU cluster has dead time. Training jobs finish, workloads shift and hardware sits dark while power and cooling costs keep running. For neocloud operators, those empty cycles are lost margin.The [...]
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