
OpenAI's Jalapeño Chip Is About Control, Not Just Nvidia
OpenAI's first custom inference chip makes more sense as a strategy for controlling latency, energy costs, and the product experience than as a simple attempt to replace Nvidia.
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OpenAI's first custom inference chip makes more sense as a strategy for controlling latency, energy costs, and the product experience than as a simple attempt to replace Nvidia.
Nvidia designs the accelerators driving AI, but its chips depend on manufacturing tools, advanced foundries and packaging that it does not own. ASML illustrates where the real bottlenecks sit.

AMD's trillion-dollar milestone is not simply a bet on one faster GPU. It is a bet that the company can become a credible second full-stack supplier for the AI data center.

The deal is not just about models. NVIDIA is buying a position inside the workflow where millions of developers discover, evaluate, customize, and deploy open AI — while promising not to close that workflow around its own hardware.