Google targets AI inference bottlenecks with TurboQuant

Google says its new TurboQuant method could improve how efficiently AI models run by compressing the key-value cache used in LLM inference and supporting more efficient vector search. In tests on Gemma and Mistral models, the company reported significant memory savings and faster runtime with no measurable accuracy loss, including a 6x reduction in memory…

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Databricks Enters Cybersecurity Market With Lakewatch SIEM Platform

Databricks is stepping into the cybersecurity space with Lakewatch, an agentic SIEM platform designed to run on top of its lakehouse architecture and extend it into security operations. Lakewatch is available in private preview. With this move, the San Francisco-based company is positioning its lakehouse as a central control layer for enterprise data. The move…

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Cloudflare launches Dynamic Workers for AI agent execution

Cloudflare has rolled out Dynamic Workers, an isolate-based runtime designed to run AI-generated code faster and more efficiently than traditional containers, as the company pushes lightweight, disposable execution environments as a foundation for enterprise AI applications. The service enables enterprises to spin up execution environments in milliseconds, pointing to a transition away from container-heavy architectures…

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Oracle adds pre-built agents to Private Agent Factory in AI Database 26ai

Oracle has added new prebuilt agents to Private Agent Factory, its no-code framework for building containerized, data-centric agents within AI Database 26ai. These agents include a Database Knowledge Agent, a Structured Data Analysis Agent, and a Deep Data Research Agent.   While the Database Knowledge Agent translates natural-language prompts into queries to fetch specific facts, policies,…

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7 safeguards for observable AI agents

Many organizations are under pressure to take their AI agent experiments and proof of concepts out of pilots and into production. Devops teams may have limited time to ensure these AI agents meet AI agent non-negotiable requirements for production deployments, including implementing observability, monitoring, and other agenticops practices. One question devops teams must answer is…

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