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    <title>MLflow — USASI news</title>
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    <description>Dated, sourced news items in the USASI catalog that mention MLflow. Independent project. Not a United States government website.</description>
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    <lastBuildDate>Tue, 13 Oct 2026 12:00:00 GMT</lastBuildDate>
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      <title>MLflow 3.17.0 released with fine-grained permissions and TypeSafe judge support</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/mlflow-3-17-0-released/</link>
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      <pubDate>Thu, 08 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>On October 7, 2026 the MLflow project published version 3.17.0 on GitHub. The release notes list &quot;Jev Decisions Across Evaluation, Gateway, and Tracing&quot;, which lets TypeSafe models be used in built-in scorers and custom judges, and &quot;Fine-Grained Permissions for Shared Resources&quot;, with wildcard grants and explicit DENY for contained resource types such as runs, traces, and versions. They also describe opt-in daily summaries for trace analytics. The notes say SQL-backed servers need a coordinated mlflow db upgrade with all writers stopped, and that mixed-version rolling upgrades are not supported. USASI has not tested these changes.</description>
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    <item>
      <title>Red Hat AI 3.5 becomes generally available with EvalHub and wider llm-d support</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/red-hat-ai-3-5-generally-available/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>Red Hat announced on September 9, 2026 that Red Hat AI 3.5 is generally available, including as part of Red Hat AI Factory with NVIDIA. The release makes EvalHub generally available for safety benchmarking and compliance reporting before deployment, shows Garak results on evaluated catalog models, integrates NeMo Guardrails to intercept malicious tool calls, and adds AutoRAG and observability features such as per-user token metering and MLflow agentic tracing. Red Hat says llm-d distributed inference now extends beyond OpenShift to third-party Kubernetes services, generally available on CoreWeave CKS and Microsoft Azure, with Amazon EKS in technology preview. USASI has not tested Red Hat AI 3.5.</description>
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