Bridging Context Engineering in AI with Requirements Engineering

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How AI-driven context engineering can transform requirements: dynamic, multimodal scenario generation and proactive need inference.

OpenAI’s New Muzzle: When “Safety” Means Gatekeeping Knowledge

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OpenAI restricts tailored medical and legal advice—protecting users or guarding professional monopolies? Call for open-source guardrails.

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Transformers may be injective and invertible: hidden activations can reconstruct inputs—big gains for interpretability, major privacy risks.

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Tesla could use millions of idle cars as a distributed AI inference fleet—turning parked vehicles into gigawatt-scale compute and revenue.

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Apple’s MGIE uses LLM-guided text editing that learns from imperfect edits, making photo retouching conversational, faster and more creative.