Google is accelerating its AI buildout even as warnings of a tech bubble grow louder. CEO Sundar Pichai touts the company’s in‑house Tensor Processing Units—custom AI chips that underpin Google’s models—as part of a strategy to own the stack from silicon to data. Alphabet is pouring more than $90 billion a year into infrastructure, joining a handful of giants whose valuations—led by Nvidia, Apple and Microsoft—now concentrate roughly a third of the S&P 500 in the “Magnificent Seven,” surpassing the late‑1990s dot‑com peak, according to the IMF. The industry’s divide is widening between cash‑rich platforms that can fund chips and data centers internally and capital‑hungry players that rely on complex financing; OpenAI’s multiyear, trillion‑dollar compute plan has stoked debate over sustainability and the role of public infrastructure. Google’s launch of Gemini intensifies its rivalry with OpenAI’s ChatGPT, while the surge in data‑center power demand collides with climate commitments, raising questions about how to scale the grid. Veterans recall the dot‑com bust’s lesson: even if an AI correction hits, survivors with real cash flow and defensible tech could emerge stronger—especially as the U.S.–China race for AI supremacy makes overbuilding a strategic choice as much as a financial bet.
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— Dot-com Bubble
— Application-Specific Integrated Circuit (ASIC)
— NVIDIA H100 Tensor Core GPU for Data Centers
— U.S. DOE: Data Centers and Servers — Energy Efficiency
