NVIDIA’s $20B strategic integration of Groq marks a structural inflection point in the AI economy. It’s not an acquisition in the conventional sense — it’s a strategic repositioning around the emerging bottleneck in AI economics: inference latency. This move signals a new equilibrium in compute strategy — where capital, physics, and infrastructure converge. It confirms that the next frontier of value in AI will not be determined by training capacity, but by real-time inferenc

Let’s start where everyone’s talking right now — the number. $20 billion. That’s the reported value of NVIDIA’s “not-quite-an-acquisition” of Groq — the little AI hardware company that built a chip so unorthodox, the industry laughed when they unveiled it in 2023. Now? NVIDIA’s folding their architecture, their engineers, and their design DNA into the future of its own inference stack. Except here’s the twist — NVIDIA didn’t buy Groq outright. They structured it as a non-excl

Let’s be clear: the cloud isn’t dying. But the age of unquestioned cloud supremacy  — that decade-long reign where every ounce of intelligence had to pass through someone else’s API — that’s beginning to crack. We’re entering the post-imperial  phase of compute. The Great Inversion For twenty years, the cloud has been the empire of cognition: centralized, industrial, and rented by the teraflop. It made sense. The economics of scale were brutal. Training frontier models requir

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