A new global review finds that while artificial intelligence (AI) is transforming health care through advanced diagnostics and automation, its safe adoption will depend on transparency in algorithm design,...

Kubernetes is being enhanced to better support modern applications, particularly AI agents. AI agents perform complex, multi-step tasks that require tools for data querying, processing, and even code generation. The non-deterministic nature of AI agents necessitates strong security and operational guardrails for safe orchestration. Kubernetes is considered a suitable foundation for running AI agents due to its maturity, security, and scalability. Agent Sandbox is a new Kubernetes primitive designed for agent code execution and computer use, offering strong isolation at scale through gVisor and Kata Containers. On Google Kubernetes Engine (GKE), Agent Sandbox leverages managed gVisor and a container-optimized platform for faster scaling and low-latency sandbox execution. GKE Pod Snapshots, a GKE-exclusive feature, enables checkpoint and restore of running pods to drastically reduce startup latency for AI workloads. This feature allows for efficient utilization of compute resources by snapshotting and suspending idle sandboxes. Agent Sandbox is built with AI engineers in mind, providing a user-friendly API and Python SDK for sandbox lifecycle management. The introduction of Agent Sandbox aims to provide the necessary isolation and performance for AI agents.

Nocall Corporation, based in Tokyo, Japan, recently announced its acquisition of ISMS certification, affirming its commitment to information security.

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The CNCF has unveiled the Certified Kubernetes AI Conformance Program, aimed at enhancing the reliability and consistency of AI workloads on Kubernetes and ensuring interoperability across various cloud environments.