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.
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While high capex is often seen as a negative, for giants like Alphabet and Microsoft, it functions as a powerful moat in the AI race. The sheer scale of spending—tens of billions annually—is something most companies cannot afford, effectively limiting the field of viable competitors.
When evaluating AI startups, don't just consider the current product landscape. Instead, visualize the future state of giants like OpenAI as multi-trillion dollar companies. Their "sphere of influence" will be vast. The best opportunities are "second-order" companies operating in niches these giants are unlikely to touch.
Fal strategically chose not to compete in LLM inference against giants like OpenAI and Google. Instead, they focused on the "net new market" of generative media (images, video), allowing them to become a leader in a fast-growing, less contested space.
Cramer's conviction in NVIDIA wasn't from a balance sheet. His "edge" came from privileged access at NVIDIA HQ, where CEO Jensen Huang personally demonstrated generative AI capabilities—like creating Cezanne-style paintings and AI clones—years before the technology became mainstream. This firsthand experience provided a unique informational advantage.
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.
Fal strategically focused on generative media over LLMs, identifying it as a "net new" market. They reasoned that LLM inference directly competed with Google's core search business—a fight an incumbent would win at all costs. The emergent media market lacked a dominant player, creating a perfect greenfield opportunity for a startup to lead and define.
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.
For venture capitalists investing in AI, the primary success indicator is massive Total Addressable Market (TAM) expansion. Traditional concerns like entry price become secondary when a company is fundamentally redefining its market size. Without this expansion, the investment is not worthwhile in the current AI landscape.
When evaluating revolutionary ideas, traditional Total Addressable Market (TAM) analysis is useless. VCs should instead bet on founders with a "world-bending vision" capable of inducing a new market, not just capturing an existing one. Have the humility to admit you can't predict market size and instead back the visionary founder.
NVIDIA's primary business risk isn't competition, but extreme customer concentration. Its top 4-5 customers represent ~80% of revenue. Each has a multi-billion dollar incentive to develop their own chips to reclaim NVIDIA's high gross margins, a threat most businesses don't face.
