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    AI Reasoning Needs Multiple Viewpoints

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    AI Reasoning Needs Multiple Viewpoints

    AI Reasoning Needs Multiple Viewpoints

    Intelligence as Collaboration

    Intelligence as Collaboration

    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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    AI’s House of Cards

    AI’s rise fuels fears of expanded government surveillance, igniting a Capitol Hill clash over FISA reforms

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    Super Bowl champ Steve Beuerlein turns to AI for early detection of heart risks

    AI Fails When It Confuses Conviction With Intelligence

    AI-fueled data center surge is sending U.S. household power bills soaring

    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

    Medicine Is Care, Not Data

    Mark Cuban-backed AI venture turns elders’ conversations into keepsake family histories

    Nvidia’s Toughest AI-Chip Challenger Isn’t AMD, Intel, or Broadcom—It’s Google

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    Healthcare

    Super Bowl champ Steve Beuerlein turns to AI for early detection of heart risks

    Medicine Is Care, Not Data

    Mark Cuban-backed AI venture turns elders’ conversations into keepsake family histories

    The End of Why

    Silicon Valley’s newest flex: a Sequoia-branded Mac mini to run your AI agent

    U.S. to tighten enforcement against Chinese firms accused of extracting capabilities from American AI models

    OpenAI unveils GPT-5.5, a new AI model aimed at stronger coding, software use, and research

    Robotics and the Dream of Mechanical Mind

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Demystifying Artificial Intelligence: Why It Matters and What You Need to Know

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This article provides an in-depth look at the current state and implications of Artificial Intelligence (AI), particularly focusing on large language models (LLMs) and generative AI. It distinguishes between key concepts like AI, machine learning, deep learning, and LLMs, and explores their rising influence on both defensive and offensive cybersecurity operations. On the defensive side, AI technologies help organizations detect threats, improve productivity, and counter malicious activities; on the offensive, bad actors are beginning to leverage these same tools for phishing and social engineering attacks, though widespread real-world examples remain limited. The article also delves into the business risks of not adopting AI, current and emerging threats from LLMs, legal and resource concerns, and increased attack surfaces resulting from AI integration. It concludes that while AI introduces new challenges, many security fundamentals remain unchanged and urges caution and due diligence as organizations integrate GenAI technologies, learning from the pitfalls of previous digital transformations.

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The Turing Test Has a Problem—And OpenAI’s GPT-4/5 Just Exposed It
How Fraudsters Used AI Voice Cloning in a Multi-Million Dollar Corporate Scam
The More Sophisticated AI Models Get, the More Likely They Are to Lie
The Rise of AI-Powered Voice Spoofing and Vishing Attacks

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