During my elementary school years, I first learned to read financial news and corporate earnings reports. A naive question arose: Companies must continuously grow revenue to sustain performance, but Earth's markets are finite—what happens when expansion hits its limit?

Initially, economics taught me most firms never reach that stage. But studying political economy revealed a darker truth: While individual companies face competitive constraints, entire industries can hit growth ceilings—a symptom of capitalist crises. Today, AI exemplifies this danger, with NVIDIA’s $5 trillion valuation flashing warning signs.

**The Illusion of Infinite Growth** AI proponents might dismiss such concerns, pointing to bullish indicators: Oracle’s stock surged after announcing its OpenAI partnership, briefly making its CEO the world’s richest. AMD’s shares also rallied on an OpenAI deal. NVIDIA’s unprecedented $5 trillion market cap seemingly confirms AI’s boundless potential.

Yet these very deals reveal the cracks. Take Oracle’s $300 billion agreement with OpenAI—a long-term commitment potentially scaling further. But OpenAI lacks the funds. Despite 2024 projections of breakeven by 2027, its latest quarterly loss exceeded $10 billion (per Microsoft’s filings). With aggressive data-center plans, profitability may remain elusive until 2030.

Even if OpenAI secured financing, Oracle couldn’t deliver the required computing power. As a smaller cloud player versus Amazon or Microsoft, Oracle would need years to build sufficient infrastructure. Meanwhile, OpenAI plans additional mega-deals, including a $250 billion Microsoft contract, totaling $1 trillion in commitments—far beyond its or any investor’s capacity.

**Infrastructure Collapse** America’s aging power grid can’t support AI’s energy demands. Post-2000s stagnation in electricity capacity clashes with AI’s voracious needs, forcing compromises: Residents near data centers face power-quality issues, while Cold War-era nuclear plants may reopen as stopgaps. Water scarcity further complicates cooling-intensive data centers.

**The "Too Big to Fail" Bubble** AI now props up the U.S. economy. Estimates suggest $300–500 billion in 2024 data-center investments avert recession. The AI bubble dwarfs the dot-com era (17x larger) and 2008 crisis (4x). This dependency risks systemic collapse, diverting capital from other sectors.

NVIDIA exemplifies this paradox. Despite slowing growth and reliability concerns with power-hungry new GPUs, it invests in GPU-leasing firms—essentially paying others to buy its chips. This self-reinforcing cycle sustains its valuation and U.S. GDP growth, mirroring a precarious "left-foot-on-right-foot" economic model.

**Political and Theological Hype** The Trump-linked Oracle-OpenAI deal reflects tech-right AI evangelism. Like religious fervor around "creating life," AI’s mythos—embodied by dystopian sci-fi tropes—overrides rational analysis. Critics are dismissed as ignoring an "inevitable" AGI future, despite AGI’s undefined profitability and scalability limits.

**China’s Contrast** Sanctions inadvertently spared China’s AI sector from unchecked hype. Investments here fuel domestic semiconductor autonomy (e.g., HBM mass-production) and open-source ecosystems (e.g., DeepSeek’s TileLang-based models). Firms like Tencent back local GPU developers (Moore Threads, Tianshu Zhixin), advancing substitution.

**Conclusion: The Inevitable Crash?** The AI bubble’s burst could trigger global upheaval. Yet as with all "too big to fail" crises, preemptive solutions are unlikely. The tragedy awaits its curtain call—unless rationality prevails.