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Zhejiang Builds AI Hub Around Computing Power and Open Source
China’s Zhejiang province is positioning itself as a major artificial intelligence hub by expanding computing infrastructure, supporting open-source model development, and bringing AI into manufacturing and commercial applications. The strategy was highlighted at the 2026 World Internet Conference Wuzhen Summit, where provincial industry figures showed core AI industry revenue reaching 582.87 billion yuan in the…
Redis Iris Adds Six Capabilities to Support Production AI Agents
Redis is expanding Redis Iris, its real-time context engine for AI agents, with six capabilities designed to address a persistent challenge in enterprise AI: making agents reliable and efficient beyond pilot deployments. Announced in November 2026, the expanded platform combines intent-based routing, reusable agent procedures, persistent memory, context access, observability, and agent-to-agent communication in one…
Deep Principle Launches Hydrogen-1.0 for AI-Driven Science
Deep Principle has introduced Hydrogen-1.0, an open-weight scientific AI model designed to help researchers plan laboratory experiments, execute computational workflows, investigate chemical reactions, and identify materials with targeted properties. Announced November 4, 2026, the model is available through the company’s Mira AI Scientist, downloadable model weights, and an API. Built by post-training GLM-5.3 on scientific…
Edera Uses Object Capabilities to Limit AI Agent Authority
As enterprises give AI agents access to source-code repositories, APIs and infrastructure, controlling what those agents can do is becoming as important as isolating where they run. Edera has introduced Object Capability Bounded Authority, a security approach designed to let autonomous agents perform narrowly authorized actions without holding the underlying credentials. The technology separates permission…
EnGenius Unveils Data Center and Edge AI Computing Portfolio
SuperComputing 2026 (SC26), scheduled for November 15–20 in Chicago. The portfolio targets workloads across AI model training, high-performance computing (HPC), virtualization, distributed processing, and real-time edge inference. The announcement highlights a broader infrastructure shift: as AI moves beyond centralized cloud environments, organizations need computing platforms that can handle intensive processing in data centers while supporting…
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