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    AI Is Unsafe Until It Learns to Stabilize

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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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Mounting Concerns Over a Trillion-Dollar AI Bubble

AI’s House of Cards
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A stampede of capital into artificial intelligence is testing investors’ nerves. Tech giants and startups are pouring hundreds of billions of dollars into chips and data centers to power chatbots and other generative tools, with total outlays projected to reach into the trillions. Even AI’s boosters concede the market looks frothy, as business models remain unproven and executives feel compelled to match rivals’ spending to avoid being outscaled later.
OpenAI’s Sam Altman has floated a $500 billion “Stargate” infrastructure plan and now says the company expects to spend trillions. Meta’s Mark Zuckerberg has pledged hundreds of billions on data centers. In a sign of financial engineering that recalls late-cycle exuberance, Nvidia agreed to invest up to $100 billion to help fund OpenAI’s buildout—an arrangement that could keep demand flowing for the chipmaker’s own products while raising questions about sustainability and risk transfer.
The warning signs echo the dot-com era: rapid, debt-fueled capex, unconventional financing, and a wide gap between technological promise and near-term profits. For now, the AI gold rush continues, but the bill for scale may come due before the payoff is clear.

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— Dot-com bubble
— Data center

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