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Apple is considering using NVIDIA's NVLink Fusion to connect its own M-series chips for its server ambitions, signaling a thaw in a historically frosty relationship. This highlights NVIDIA's strategy to unbundle and sell its core technologies, like networking, to other chipmakers, ensuring relevance even if customers don't buy its GPUs.
By investing in chip designer Marvell, NVIDIA ensures that even when hyperscalers develop custom chips, they must still use NVIDIA's NVLink interconnect. This keeps NVIDIA embedded in the stack, preventing competitors like Broadcom from creating a completely proprietary, NVIDIA-free system.
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.
As GPU data transfer speeds escalate, traditional electricity-based communication between nearby chips faces physical limitations. The industry is shifting to optics (light) for this "scale-up" networking. Nvidia is likely to acquire a company like IR Labs to secure this photonic interconnect technology, crucial for future chip architectures.
Apple's move to partner with Intel isn't just about geopolitics; it reflects its diminishing leverage with primary supplier TSMC. The insatiable demand for AI chips from companies like NVIDIA means Apple is no longer the undisputed top priority, forcing it to find additional manufacturing capacity to avoid its own product supply constraints.
NVIDIA's strategy extends beyond selling GPUs. By packaging compute, software, and industrial partnerships, its 'AI Factory' model provides a full-stack blueprint for national and corporate AI infrastructure, effectively defining the entire ecosystem from silicon to robotics.
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.
Nvidia maintains partnerships with everyone, including rivals. By positioning itself as a neutral, essential supplier rather than a direct competitor, it has become central to every company's AI bet, securing its dominant and indispensable market position.
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 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.
For decades, NVIDIA was an "add-on" to the PC ecosystem, requiring separate drivers and coexisting with official OS graphics APIs like Microsoft's DirectX. Its new position at the core of AI PCs with its CUDA stack represents a fundamental shift, challenging the traditional OS-centric control held by Microsoft and Apple.