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    Stabilize and Unstabilize A Framework for Real World AI

    Stabilize and Unstabilize A Framework for Real World AI

    AI Is Unsafe Until It Learns to Stabilize

    AI Is Unsafe Until It Learns to Stabilize

    Structured Reasoning as Equilibrium

    Structured Reasoning as Equilibrium

    The End of Algorithmic Obedience and the Birth of Stability Intelligence

    The End of Algorithmic Obedience and the Birth of Stability Intelligence

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    Sam Altman warns AI faces two chief threats: misalignment and dangerous concentration of power

    Trump AI adviser says AI makers—not government—must ensure their systems are safe

    Congress pushes back on Trump’s AI stance as lawmakers ramp up calls for guardrails

    Trump dismisses AI doomsday warnings as a ‘hoax’ while tech leaders decry an ‘unseen hand’ driving regulation

    Could AI doom humanity? The architects of the technology warn of mounting risks and urge oversight

    Trump Rejects New AI Oversight as Industry Chiefs Urge Slowdown on Rapid Advances

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    Sam Altman warns AI faces two chief threats: misalignment and dangerous concentration of power

    Trump AI adviser says AI makers—not government—must ensure their systems are safe

    Trump Rejects New AI Oversight as Industry Chiefs Urge Slowdown on Rapid Advances

    Trump says he alone is the AI ‘guardrail’ America needs as president

    Trump rejects AI guardrails, says a “smart president” is all that’s needed

    Global tech stocks slip as AI leaders urge a slowdown in development

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Home Health

AI model tops internal-medicine doctors at diagnosis in real-world ER cases, study finds

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An AI reasoning system developed by OpenAI outperformed experienced internal-medicine physicians at diagnosing patients using real emergency-department cases, according to a study from Harvard Medical School and Beth Israel Deaconess published in Science. Evaluated across multiple points in care and using only electronic health records, the model matched or exceeded doctors’ performance and bested GPT-4 on clinical reasoning tasks and benchmarks. Researchers and outside clinicians said the results highlight rapid advances in large language models but cautioned that integrating such tools into hospital workflows and proving outcome benefits will require rigorous, prospective trials. The authors stressed the AI is not a substitute for physicians and that real-world care demands inputs beyond text, including images and bedside assessment. A correction clarified the comparison was to internal-medicine doctors, not ER physicians.

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