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    AI Is Unsafe Until It Learns to Stabilize

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    Structured Reasoning as Equilibrium

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    Why Autoregressive Language Models Cannot Lead to Human-Level Intelligence

    Anthropic’s ‘Mythos’ AI Flags 2,000+ Software Flaws in 7 Weeks, Withheld from Public Release Over Safety Risks

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What burst the dot‑com boom—and what it signals for today’s AI frenzy

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Investors are drawing parallels between today’s AI boom and the late-1990s dot-com era, as capital floods into data centers and valuations soar despite thin profits. The article traces how the 2000 crash stemmed from a mix of Fed rate hikes, global jitters—starting with Japan’s downturn—and business models that couldn’t justify sky-high prices. A key lesson came from telecom’s massive overbuild: tens of millions of miles of fiber were laid on inflated demand forecasts, leaving “dark fiber” and crushing suppliers such as Corning and Ciena. The current AI surge bears similar hallmarks, with Big Tech pledging record capex and initiatives like the $500 billion “Stargate” data center network. Yet there are differences: leading AI players are posting real revenue gains—Azure’s strong growth and OpenAI’s projected $20 billion run rate among them. Still, the revenue-to-investment gap remains glaring, and studies show most AI pilots fail, raising the possibility of excess capacity before demand materializes. The takeaway: transformative technology doesn’t exempt investors from economics; timing and disciplined returns will determine whether this boom endures or retrenches.

Read more


Related articles:

— Dotcom Bubble: Definition, Causes, and Examples
— Dark fibre
— Global Crossing
— Level 3 Communications
— Qwest

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