NVIDIA's polite PR statement regarding Google's competing TPU chips contrasts sharply with the aggressive marketing of modern tech leaders. This 'old school' approach is seen as a weakness, suggesting their marketing 'war muscle' has atrophied from years of unchallenged dominance.

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Jensen Huang's core strategy is to be a market creator, not a competitor. He actively avoids "red ocean" battles for existing market share, focusing instead on developing entirely new technologies and applications, like parallel processing for gaming and then AI, which established entirely new industries.

Instead of competing for market share, Jensen Huang focuses on creating entirely new markets where there are initially "no customers." This "zero-billion-dollar market" strategy ensures there are also no competitors, allowing NVIDIA to build a dominant position from scratch.

The high-stakes competition for AI dominance is so intense that investigative journalism can trigger immediate, massive corporate action. A report in The Information about OpenAI exploring Google's TPUs directly prompted NVIDIA's CEO to call OpenAI's CEO and strike a major investment deal to secure the business.

When asked about AI's potential dangers, NVIDIA's CEO consistently reacts with aggressive dismissal. This disproportionate emotional response suggests not just strategic evasion but a deep, personal fear or discomfort with the technology's implications, a stark contrast to his otherwise humble public persona.

Swisher draws a direct parallel between NVIDIA and Cisco. While NVIDIA is profitable selling AI chips, its customers are not. She predicts major tech players will develop their own chips, eroding NVIDIA's unsustainable valuation, just as the market for routers consolidated and crashed Cisco's stock.

Following ChatGPT's 'Pearl Harbor moment,' Google's CEO was seen as a lagging peacetime leader. He responded by issuing a 'code red,' restructuring the company, and empowering AI leaders. This decisive action transformed his image and positioned Google to aggressively compete in the AI race.

As the market leader, OpenAI has become risk-averse to avoid media backlash. This has “damaged the product,” making it overly cautious and less useful. Meanwhile, challengers like Google have adopted a risk-taking posture, allowing them to innovate faster. This shows how a defensive mindset can cede ground to hungrier competitors.

The competitive threat from custom ASICs is being neutralized as NVIDIA evolves from a GPU company to an "AI factory" provider. It is now building its own specialized chips (e.g., CPX) for niche workloads, turning the ASIC concept into a feature of its own disaggregated platform rather than an external threat.

The narrative of endless demand for NVIDIA's high-end GPUs is flawed. It will be cracked by two forces: the shift of AI inference to on-device flash memory, reducing cloud reliance, and Google's ability to give away its increasingly powerful Gemini AI for free, undercutting the revenue models that fuel GPU demand.

While competitors like OpenAI must buy GPUs from NVIDIA, Google trains its frontier AI models (like Gemini) on its own custom Tensor Processing Units (TPUs). This vertical integration gives Google a significant, often overlooked, strategic advantage in cost, efficiency, and long-term innovation in the AI race.