The latest AI application ecosystem, Gemini3, launched by tech giant Google in late November, has taken the world by storm, driving an explosive surge in AI computing demand. The Gemini3 series products immediately generated massive AI token processing volumes upon release, forcing Google to significantly reduce free access to Gemini 3 Pro and Nano Banana Pro while temporarily restricting usage for Pro subscribers. Concurrently, strong trade export data from South Korea highlights robust demand for HBM memory systems and enterprise-grade SSDs, further validating Wall Street’s assertion that the AI boom remains in its early infrastructure-building phase with supply struggling to meet demand.

Since early April, when unprecedented aggressive global tariffs introduced by the Trump administration rattled stock markets, AI computing leaders such as NVIDIA, Google, Broadcom, TSMC, Micron, Advantest, SK Hynix, and Foxconn Industrial Internet have spearheaded a global market rebound, emerging as the "strongest alpha" in equities. This rally is underpinned by the relentless expansion of global AI computing demand and the gradual easing of Trump-era tariffs through multiple trade negotiations.

After a brief downturn in early November due to widespread "AI bubble" fears, the AI computing investment theme has rebounded sharply—particularly with Google’s AI ecosystem sparking a global investment frenzy. Leading AI computing stocks are once again propelling U.S. and global markets toward new highs. Statistical evidence confirms that AI computing, with its unrelenting demand growth, remains the dominant "alpha" force in global equities since April, sustaining the "long-term bull market" narrative for the AI infrastructure sector.

Wall Street giants like Morgan Stanley, JPMorgan, and Deutsche Bank argue that bearish "AI bubble" rhetoric fails to undermine the "excess alpha" generated by AI computing investments. These institutions project that AI will remain the core driver of record-breaking U.S. stock market highs through 2026, recommending continued allocation to AI-driven stocks for their superior "alpha" potential—outperforming the S&P 500 and eclipsing returns from consumer, energy, and mining sectors.

Dan Greenhaus, Chief Strategist at Solas Alternative Asset Management, noted that the early November "AI panic" was short-lived. He expects no major shifts in market dynamics heading into 2026, citing two key pillars—AI fundamentals and the Fed’s potential rate-cut path—as tailwinds for investors. "It was merely a technical sell-off and profit-taking phase," Greenhaus explained. "The panic was transient, not indicative of a lasting trend."

**Gemini3 Goes Viral, Overwhelming Google’s Servers** User feedback and social media buzz suggest Gemini3 is hailed as "humanity’s most powerful multimodal AI model," poised to exponentially enhance enterprise efficiency and consumer software collaboration. Institutions like Morgan Stanley and Mizuho are increasingly bullish on Google’s stock and its broader AI ecosystem.

Beyond Google, key ecosystem players like Broadcom (AVGO.US)—the developer of Google’s TPU chips—are poised to benefit from unprecedented AI computing demand. Data center storage leaders and high-performance networking infrastructure providers tied to Google’s "optical interconnect" ecosystem are also entering an "AI golden age."

Google’s Gemini3 rollout triggered such massive AI token processing that free tiers were slashed, with Pro users facing temporary caps. Similarly, OpenAI’s Sora2 video generator reduced free user limits due to overwhelming demand. Last Friday, Sora’s lead Bill Peebles cited "melting AI GPUs" as the reason for capping free users to six daily videos. Google now enforces dynamic daily limits on Gemini3 Pro and Nano Banana Pro, citing "overwhelming demand."

Google Cloud’s AI infrastructure head, Amin Vahdat, reportedly stated that the company must "double computing capacity every six months," targeting a 1,000-fold increase over 4–5 years. Wall Street analysts predict Google’s TPU clusters could capture 30–40% of the AI infrastructure market, challenging NVIDIA’s 90% dominance.

Morgan Stanley, Citi, and Wedbush project the AI infrastructure investment wave, fueled by "unprecedented inference-side demand," will scale to $3–4 trillion by 2030.

**AI to Drive Record U.S. Stock Highs in 2026** As year-end approaches, Wall Street firms are issuing bold 2026 forecasts, with Deutsche Bank targeting an S&P 500 at 8,000 (versus Friday’s close at 6,849), citing AI’s transformative impact on growth and earnings. Morgan Stanley dubs 2026 "The Year of Risk Reboot," expecting AI data center expansion to foster a "Goldilocks" soft landing for the U.S. economy.

JPMorgan shares this optimism, forecasting S&P 500 at 8,000+ on the back of AI’s "supercycle" and resilient U.S. growth. The bank notes extreme concentration in AI-heavy "Magnificent Seven" stocks will persist, with tech-driven structural shifts reshaping markets.