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Aegis Puts Agent Actions Behind a Trusted Runtime

Aegis Puts Agent Actions Behind a Trusted Runtime

Aegis is a runtime governance system that treats agent outputs as action proposals, then evaluates and authorizes them through a trusted policy layer before tool execution. In a sandbox evaluation, it recorded zero governed mock-tool applications and zero governed risky side-effect completions, though the authors caution that this does not establish general agent safety.

Moore Threads’ Growth Comes with Big Questions

Moore Threads’ Growth Comes with Big Questions

Moore Threads’ first post-IPO half-year report shows revenue rising 147% to RMB 1.736 billion, while attributable losses narrowed sharply. However, the improvement relies heavily on concentrated cloud-computing sales, government subsidies, investment gains, and IPO-funded cash reserves rather than a clear recovery in core operations.

虎嗅Media58m ago#gpu#domestic-chips#cash-flow
Scale Agentic AI Without Lock-In

Scale Agentic AI Without Lock-In

AWS outlines enterprise patterns for operating many agentic AI systems across diverse frameworks, models, and providers. The guidance focuses on preserving flexibility and enabling multi-agent systems to scale together without vendor lock-in.

AWS Machine Learning BlogOfficial1h ago#agentic-ai#multi-agent#vendor-lock-in
How LLMs Are Transforming Mental Health Care

How LLMs Are Transforming Mental Health Care

This systematic review examines how large language models support mental-health applications, including social-media analysis, clinical conversational agents, therapy support, and psychoeducation. It also covers multimodal diagnosis, prompt engineering, interpretability, and the ethical and regulatory safeguards needed for responsible deployment.

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