Model Selection Should Start With Recovery, Not Brilliance
OpenAI, Anthropic, Google Cloud and IBM all bring model selection back to one question: when the model fails, can the team test it, stop it and switch back?
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Governance— How we build AI systems, product by product.
AI Agents Need Authorization Before Autonomy
OpenAI, Anthropic, Microsoft, Google Cloud and IBM all bring agents back to one question: before an agent acts, the company must define who it represents, what data it can touch and where it stops.
Before AI Rollout, Draw the Smallest Boundary Your Team Can Actually Guard
NIST, OpenAI, Microsoft and IBM all point to the same operating rule: do not let AI take over a workflow before the team knows who reviews it, when to stop it and how to recover.
OpenAI: turning frontier AI safety into a governance and procurement question
OpenAI outlines a blueprint for U.S. governance of frontier AI, proposing a federal framework for safety, resilience, and national security.
Gemini’s Multimodal Leap: Why Data Governance is Now the Real Bottleneck
Gemini 3 Deep Think 公開聚焦科研與工程推理流程，重點在可驗證問題拆解與長鏈路思考。
Sovereign Cloud + Trust Framework: Where to Set the AI Kill-Switch
主權雲端訊號對跨境資料、在地法規與營運續航非常關鍵。
Security and Compute Power: Why Enterprise AI Success Requires More Than Just Models
Google 宣布完成收購 Wiz，顯示企業級 AI 的雲端安全與風險治理投資放大。
Microsoft Build 2026’s signal: enterprise agents need control before scale
Microsoft put ASSERT, the Agent Control Specification, and Agent 365 on the same track. The message for teams is simple: do also swap models; make every agent action testable, traceable, reviewable, and reversible.