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Share GPU clusters across teams with isolation and fairness using Amazon SageMaker HyperPod

AWS Machine Learning · A reference architecture for securely sharing one Amazon SageMaker HyperPod EKS cluster across multiple teams, using AWS IAM Identity Center for authentication, per-team SageMaker Domains and Kubernetes namespaces for isolation, HyperPod Task Governance for fairness, and namespace-level cost allocation for chargeback.

Claude Haiku 5.5 in GitHub Copilot

GitHub Copilot Changelog · Claude Haiku 5.5, Anthropic’s newest lightweight model, is now generally available in GitHub Copilot. It is designed for fast, high-volume work like subagents, quick edits, and terminal tasks. In early… The post Claude Haiku 5.5 in GitHub Copilot appeared first on The GitHub Blog.

Introducing Claude Haiku 5.5 on AWS

AWS Machine Learning · Claude Haiku 5.5 is now available on Amazon Bedrock and Claude Platform on AWS. According to Anthropic, it is the fastest, most efficient model in the Claude 5.5 family, built for subagents and high-volume, cost-sensitive work, and costs around 75% less than Claude Haiku 4.5 for most tasks. This post covers its improvements and how to get started.

Rethinking access control for RAG with Amazon Quick and Amazon Bedrock

AWS Machine Learning · Enterprise RAG unlocks insights from knowledge sources like SharePoint, Google Drive, and Confluence, but those sources carry complex permissions. Learn how Amazon Quick and Amazon Bedrock Knowledge Bases enforce document-level access controls in real time, verifying permissions directly with authoritative sources at query time.

Secret protection must scale with software

GitHub AI & ML · Developers aren’t becoming more careless; they’re being outpaced. The tools that let developers create more software should also take on more of the work of protecting it. The post Secret protection must scale with software appeared first on The GitHub Blog.

Purpose-built model for leaked secret detection

GitHub Copilot Changelog · Secret protection should keep pace with the way you build software, whether you write code yourself or work with an AI agent. With our new purpose-built model, we’re bringing context-aware… The post Purpose-built model for leaked secret detection appeared first on The GitHub Blog.

Beyond hours saved: Building the business case for agentic automation

AWS Machine Learning · The RPA-era ROI model misses most of the value agentic automation creates. This post gives AI center of excellence leaders a framework to size the full value of agents across time savings, exception handling, decision quality, and maintenance economics, and to prioritize which workflows to automate first.

How Qlik built grounded, enterprise-scale AI with Amazon Bedrock

AWS Machine Learning · Qlik built Qlik Answers on Amazon Bedrock to give its 40,000+ customers grounded, sourced answers across structured and unstructured enterprise data. Learn how a layered, multi-agent architecture with cross-Region inference and Amazon Bedrock Guardrails delivers trusted AI at global scale.

Automate remediation post AWS DevOps Agent investigation

AWS Machine Learning · AWS DevOps Agent can diagnose production incidents but is kept in observe-and-report mode so it does not change resources directly. This post shows how to use AWS Lambda Durable Functions, Amazon EventBridge, and Amazon Bedrock to turn its investigation summaries into pre-validated fixes an on-call engineer can approve with a single action.

Local sandboxing for GitHub Copilot now generally available

GitHub Copilot Changelog · Local sandboxing for GitHub Copilot is now generally available in GitHub Copilot CLI, the GitHub Copilot app, and VS Code sessions using Agent Host. Local sandboxes give developers a secure… The post Local sandboxing for GitHub Copilot now generally available appeared first on The GitHub Blog.

Discover local models in GitHub Copilot CLI

GitHub Copilot Changelog · GitHub Copilot CLI makes it easier to choose a local model without leaving your existing workflow. Starting in CLI version 1.0.94-0, use /model to discover supported models from a running… The post Discover local models in GitHub Copilot CLI appeared first on The GitHub Blog.

Building AI builders: Playbook for closing the AI knowledge-capability gap

AWS Machine Learning · The biggest barrier to AI adoption isn't awareness. It's the gap between talking about AI and building with it. Here's the playbook we used to turn non-technical, customer-facing professionals into confident AI builders in six weeks, and how your organization can replicate it.

How Cornerstone OnDemand cut database diagnosis by 78% with Amazon Bedrock

AWS Machine Learning · Cornerstone OnDemand built Orion AI, a multi-agent system on Amazon Bedrock and Strands Agents, to turn database operations from reactive firefighting into proactive automation. A three-person team cut database diagnosis from 45 minutes to 10, a 78% reduction, in six months. See the design decisions other teams can reuse.

GPT-6 and Intelligent UI for everyone

OpenAI · GPT‑6 is rolling out globally in ChatGPT with Intelligent UI, delivering faster responses with visuals and interactive experiences you can explore and use directly.

Update your IDE to restore agent activity in Copilot usage metrics

GitHub Copilot Changelog · If your Copilot usage metrics have shown agent activity or agent lines of code falling while Copilot usage kept growing, we’ve found the cause, and a fix is rolling out… The post Update your IDE to restore agent activity in Copilot usage metrics appeared first on The GitHub Blog.

Building a context-aware AI assistant on AgentCore and OpenClaw

AWS Machine Learning · Off-the-shelf AI assistants forget you between conversations. This post shows how to build a personal assistant that accumulates context using OpenClaw on Amazon Bedrock AgentCore runtime, with AgentCore memory turning disposable chats into durable, structured knowledge you can retrieve with metadata filters.

Responsible AI governance: How AWS positions customers to align with ISO/IEC 42005:2025

AWS Machine Learning · AWS invests in tools that help customers align with international standards for responsible AI governance. In this post, we explore the AI system impact assessment: what it is, how it improves enterprise-wide risk management, and how ISO/IEC 42005:2025 codifies best practices for conducting and documenting these assessments.

Best practices for Amazon SageMaker HyperPod administration and governance

AWS Machine Learning · Learn how to administer Amazon SageMaker HyperPod through Amazon SageMaker Unified Studio while preserving cluster governance. This post shows platform teams how to design infrastructure boundaries, govern access, allocate shared capacity, and operate HyperPod consistently across the organization, project, cluster, and workload control layers.

Manage Amazon SageMaker HyperPod Spaces directly from SageMaker Studio

AWS Machine Learning · Data scientists and ML engineers can now create, configure, start, stop, and open Amazon SageMaker Spaces on SageMaker HyperPod EKS clusters directly from SageMaker Studio. Launch JupyterLab and Code Editor environments in a few clicks, without using command-line tools.

Sharing AI progress in mathematics

OpenAI · OpenAI publishes new results on open problems in mathematics from an internal frontier model and shares Lean proof formalizations and research details on GitHub.

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