The AI inference process involves two distinct phases: "prefill" (reading the prompt, which is compute-bound) and "decode" (writing the response, which is memory-bound). NVIDIA GPUs excel at prefill, while companies like Grok optimize for decode. The Grok-NVIDIA deal signals a future of specialized, complementary hardware rather than one-size-fits-all chips.

While competitors chased cutting-edge physics, AI chip company Groq used a more conservative process technology but loaded its chip with on-die memory (SRAM). This seemingly less advanced but different architectural choice proved perfectly suited for the "decode" phase of AI inference, a critical bottleneck that led to its licensing deal with NVIDIA.

Nvidia paid $20 billion for a non-exclusive license from chip startup Groq. This massive price for a non-acquisition signals Nvidia perceived Groq's inference-specialized chip as a significant future competitor in the post-training AI market. The deal neutralizes a threat while absorbing key technology and talent for the next industry battleground.

Despite bubble fears, Nvidia’s record earnings signal a virtuous cycle. The real long-term growth is not just from model training but from the coming explosion in inference demand required for AI agents, robotics, and multimodal AI integrated into every device and application.

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.

NVIDIA's deal with chip startup Grok, which includes hiring 90% of its staff and a massive valuation payout, is structured as a licensing agreement. This is a transparent maneuver to function as an acquihire and neutralize a competitor while avoiding the intense antitrust scrutiny a direct acquisition would trigger.

NVIDIA's multi-billion dollar deals with AI labs like OpenAI and Anthropic are framed not just as financial investments, but as a form of R&D. By securing deep partnerships, NVIDIA gains invaluable proximity to its most advanced customers, allowing it to understand their future technological needs and ensure its hardware roadmap remains perfectly aligned with the industry's cutting edge.

NVIDIA’s business model relies on planned obsolescence. Its AI chips become obsolete every 2-3 years as new versions are released, forcing Big Tech customers into a constant, multi-billion dollar upgrade cycle for what are effectively "perishable" assets.

NVIDIA funds OpenAI's compute purchases (of NVIDIA chips) with an equity investment. This effectively gives OpenAI a discount without lowering market prices, while NVIDIA gains equity in a key customer and locks in massive sales.