Are we actually in an "AI Bubble," or just early infrastructure growing pains?

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Lately, it feels like every financial sub and tech board is flooded with "AI Bubble" warnings. Between massive capital expenditures (CapEx) by hyperscalers, sky-high valuations, and questions over when enterprise monetization catches up, the panic is real.
But looking at the arguments, it feels like two different conversations happening at once:

1. • The "Bubble" Bear Case:
     • Overinvestment vs. Revenue: Billions are being poured into GPUs, data centers, and model training, while many end-user applications are still struggling to show massive, sticky ROI.
     • Index Concentration: A massive chunk of broad market performance (like the S&P 500 or total-market index funds) is heavily tied to a handful of mega-cap AI players, creating real concentration risk.
     • History Repeating: Every major tech wave (railroads, dot-com, fiber-optic) went through a classic overinvestment and debt-fueled hype cycle before the dust settled.
   • The "Secular Shift" Bull Case:
     • Real Infrastructure Buildout: Unlike 2000, the companies driving this have massive cash flows, balance sheets, and actual physical infrastructure being laid down (energy, data centers, hardware) that will outlive any short-term sentiment swing.
     • Productivity Gains: Even if consumer hype dips, backend automation, code generation, and enterprise workflow efficiencies are compounding quietly.