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AI

How AI Benchmarks Actually Work and Where They Mislead

AI benchmarks are standardized task suites with a named publisher and a public scoring method, and they supply most of the evidence behind claims that one model beats another. ARC-AGI-2, launched on March 24, 2025 by ARC Prize, reports that pure large language models score 0 percent on its…

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AI

What Open-Source AI Actually Means — From Weights to Full Transparency

An open-source AI system, under the Open Source Initiative's Open Source AI Definition 1.0 released October 28, 2024, must give users the freedoms to use, study, modify, and share it — and that requires code, model parameters, and detailed data information, not just downloadable weights…

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AI

How Google's Gemma 4 Open Models Actually Work — and Where They Run

Google DeepMind launched Gemma 4 on April 2, 2026, a family of open models released under the Apache 2.0 license in five parameter sizes from E2B to 31B. Per Google's documentation, the models run on-device rather than only in the cloud, enabling agents that plan and act without a network…

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AI

How AI Entered Medicine for Real — The FDA's Device Record Explained

AI entered American medicine through the medical-device pathway, not a general AI law: the FDA does not regulate AI as such — it regulates medical devices, including AI-enabled devices, through 510(k) clearance, De Novo classification, and premarket approval (regulatory, FDA). On January 7,…

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AI

How AI Safety Works: Risk Frameworks, Capability Thresholds, and Regulators

AI safety is the discipline of preventing harm from AI systems through measurement, mitigation, and governance, and it runs on two tracks. One is public: NIST published its AI Risk Management Framework in January 2023 as a voluntary standard. The other is internal: Google DeepMind's Frontier…