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Nvidia is developing networking technology that allows non-Nvidia AI chips to work together. This strategic move ensures customers remain within Nvidia's ecosystem, even if they don't buy Nvidia's GPUs, by capturing them at the crucial interconnect layer.

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By funding and backstopping CoreWeave, which exclusively uses its GPUs, NVIDIA establishes its hardware as the default for the AI cloud. This gives NVIDIA leverage over major customers like Microsoft and Amazon, who are developing their own chips. It makes switching to proprietary silicon more difficult, creating a competitive moat based on market structure, not just technology.

Nvidia's partnership with Thinking Machines Lab for its unreleased Verirubin chip is a strategic move. It secures a high-profile "neo lab" as an early customer, helping smooth out initial chip issues while locking them into the Nvidia architecture. It's a win-win, providing the startup with compute and validation.

NVIDIA is moving "up the stack" from chips to an AI agent software platform to diversify its business and create a new moat beyond its CUDA system. By courting enterprise partners, NVIDIA aims to maintain infrastructure dominance even if AI labs succeed with their own custom silicon, reducing reliance on NVIDIA GPUs.

Seemingly strange deals, like NVIDIA investing in companies that then buy its GPUs, serve a deep strategic purpose. It's not just financial engineering; it's a way to forge co-dependent alliances, secure its central role in the ecosystem, and effectively anoint winners in the AI arms race.

Large tech companies are actively diversifying their AI chip supply to avoid lock-in with NVIDIA. However, the true challenge isn't just hardware performance. NVIDIA's powerful moat is its extensive software and developer ecosystem, which competitors must also build to truly break free from its market dominance.

NVIDIA is strategically repositioning itself beyond just hardware. Through collaborations like the one with Groq for inference-specific chips and partnerships with cloud providers, the company is building a comprehensive AI platform that covers the entire AI lifecycle, from training and inference to agent orchestration, signaling a major strategic shift.

The exponential growth in AI required moving beyond single GPUs. Mellanox's interconnect technology was critical for scaling to thousands of GPUs, effectively turning the entire data center into a single, high-performance computer and solving the post-Moore's Law scaling challenge.

NVIDIA's vendor financing isn't a sign of bubble dynamics but a calculated strategy to build a controlled ecosystem, similar to Standard Oil. By funding partners who use its chips, NVIDIA prevents them from becoming competitors and counters the full-stack ambitions of rivals like Google, ensuring its central role in the AI supply chain.

NVIDIA investing in startups that then buy its chips isn't a sign of a bubble but a rational competitive strategy. With Google bundling its TPUs with labs like Anthropic, NVIDIA must fund its own customer ecosystem to prevent being locked out of key accounts.

NVIDIA's additional $2B into CoreWeave is more than a customer investment; it's a strategic play to participate in every layer of the AI ecosystem. By funding infrastructure build-out, NVIDIA ensures sustained demand for its chips and solidifies its central role in the industry.