Nvidia is moving beyond just selling GPUs to become a platform company. By proactively partnering with smaller rivals like D-Matrix, it ensures its own hardware remains central to complex AI systems. This "coopetition" strategy aims to maintain ecosystem dominance even as diverse chip architectures emerge, countering the narrative that Nvidia only seeks to eliminate competition.

Despite major tech companies developing their own AI chips, CoreWeave's clients exclusively demand Nvidia hardware. This is attributed to the mature CUDA software platform, which provides an efficient, scalable, and reliable ecosystem that competitors have been unable to replicate.

NVIDIA doesn't simply sell its scarce chips to the highest bidder. It strategically allocates them to cultivate a diverse ecosystem of cloud providers and customers. This prevents any single customer from becoming too powerful and ensures healthy competition among its buyers, which ultimately drives more demand for NVIDIA's hardware.

While known for its GPUs, Nvidia's real competitive advantage comes from years of hands-on work integrating its entire stack with companies across many industries. This deep partnership model makes it incredibly difficult for customers to switch to competitors.

NVIDIA's new business model involves guaranteeing it will rent back unused GPU capacity from smaller cloud providers. This acts as anchor demand, enabling these 'NeoClouds' to secure financing for massive GPU purchases. It's a strategic move for NVIDIA to build and control its own demand ecosystem, ensuring its chips continue to sell.

NVIDIA's DGX Cloud, intended to compete with major clouds by layering NeoCloud partners, ultimately shifted to providing a software platform. The initial product wasn't compelling enough to displace direct relationships with providers like CoreWeave, demonstrating the challenge of disintermediating a powerful ecosystem.

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.

Jensen Huang strategically allocates GPUs to NeoClouds and new AI labs to prevent a world dominated by a few hyperscalers building their own custom chips (like TPUs). This ensures a diverse customer base and prevents NVIDIA's core products from being commoditized by a handful of powerful buyers.

Nvidia retreated from building its own cloud service due to the difficulty and unreliability of its 'cloud of clouds' model, which leased competitor infrastructure. It has now pivoted to a less complex marketplace model, connecting customers to smaller cloud providers instead.