If we're in an AI bubble, why doesn't it feel like we're in an AI bubble? (www.businessinsider.com)

Experts — including people inside the industry like Sam Altman — say we’re likely in an AI bubble, but it lacks the mass-market theater of past manias. Unlike dot‑com IPO frenzies, housing booms, or crypto’s pandemic-era hype, AI’s excesses are mostly happening behind corporate walls: huge hiring sprees, jaw‑dropping compensation packages, and massive capital outlays for compute and R&D. Culturally it feels different because ordinary people aren’t trading meme stocks or buying tokens en masse; AI chatter has become a topical worry, not a retail investment obsession. For the AI/ML community this matters. The boom is highly concentrated — companies like Nvidia and Microsoft are driving recent market gains, and big tech’s balance sheets fund most cutting‑edge work, making compute, data and talent the choke points. That concentrates risk: a correction would hit corporate budgets, venture funding and startup valuations more than widespread household portfolios (though index funds indirectly expose many retirees). Technical implications include continued emphasis on scale‑heavy models and infrastructure, potential consolidation of tooling and talent, and a greater role for enterprise procurement and policy debates. If the bubble pops, expect boardroom retrenchment and slower funding rounds rather than the immediate cultural reckoning seen in past bubbles.