1 link tagged with all of: hardware + hyperscalers + ai-arms-race + open-source + full-stack
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The article tracks how AI competition has expanded from model performance to controlling hardware, data centers, models, and applications. It shows how major players—model-first labs, application startups, cloud providers, chip makers, and Google—are moving up and down the stack to protect margins and capture value.
- Every layer of the AI stack—chips, data centers, models, apps—is getting squeezed on margins, pushing companies to vertically integrate both up and down the chain instead of specializing.
- Nvidia is open-sourcing its Nemotron 3 models specifically to lock buyers into its GPUs, turning model generosity into a hardware sales strategy.
- Cursor's Composer 2.5, trained on data from millions of coding sessions routed through GPT/Claude, shows how application-layer UX data can become its own competitive moat—reinforced by SpaceX's $60 billion acquisition of Cursor's maker Anysphere.
- Google is the only company operating at all four layers simultaneously (TPUs, data centers, DeepMind/Gemini models, and embedded apps across Search/Workspace/Android), giving it a structural advantage no competitor matches.
ai-arms-race
full-stack
hardware
hyperscalers
open-source