🤖 AI Summary
Alphabet CEO Sundar Pichai warned in a Financial Times piece (and a BBC interview) that AI risks a trillion‑dollar bubble if hype outpaces reality. He flagged both societal harms — deepfakes, facial‑recognition misuse — and concentrated market risk as sky‑high valuations (rumors of $3.5T for Alphabet, $500B for OpenAI, $5T for Nvidia) leave even large players exposed if sentiment turns. Investors are already signaling strain: insiders selling, stretched multiples, record venture flows into compute‑hungry generative models with unclear unit economics, and growing short interest.
Technically and economically, Pichai points to hard limits that will shape the next phase: energy and cooling demands (IEA warns data‑center electricity could roughly double), constrained GPU and systems supply, long lead times for packaging/networking, and rising inference costs that can squeeze ad‑ or freemium models. A likely reset would prune undifferentiated apps, consolidate the field, and favor “picks‑and‑shovels” infrastructure — though those too face pressure. Regulatory regimes (EU AI Act, scrutiny in US/UK), model transparency, and compliance will become gating factors. Practical signals to watch are real productivity lift, payback periods, inference‑cost decline, and shift to domain‑specialized, data‑moated models. Pichai’s prescription: discipline and transparent unit economics, not retreat; winners will pair technical advances with sustainable business fundamentals.
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