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  1. No-code ML workflow links Snowflake with SageMaker Canvas

    No-code ML workflow links Snowflake with SageMaker Canvas

    AWS Maps a Business-Led Path From Snowflake Data to ML Outputs AWS has published the first installment of a three-part guide for building a no-code machine learning workflow around Snowflake data. The setup starts with the Snowflake environment, then plans to connect Amazon SageMaker Canvas for...
  2. NVIDIA Nemotron 3.5 Lightning lands in SageMaker JumpStart

    NVIDIA Nemotron 3.5 Lightning lands in SageMaker JumpStart

    AWS adds NVIDIA's agent-focused open model to JumpStart AWS says NVIDIA Nemotron 3.5 Lightning is now available in Amazon SageMaker JumpStart, giving developers a managed path to deploy the open model without configuring serving infrastructure themselves. The model targets high-volume agentic...
  3. OneAdvanced Builds UK-Sovereign AI Agents on AWS Architecture

    OneAdvanced Builds UK-Sovereign AI Agents on AWS Architecture

    Inside OneAdvanced's UK-sovereign agent platform OneAdvanced has built a UK-sovereign AI platform on AWS by self-hosting Llama 4 models in the London region, according to a technical case study published by AWS. The system combines SageMaker AI endpoints, more than 50 task-specific agents on...
  4. SageMaker AI Spaces on EKS brings IDEs into Kubernetes clusters

    SageMaker AI Spaces on EKS brings IDEs into Kubernetes clusters

    AWS puts managed ML workspaces inside EKS clusters AWS has detailed how its SageMaker AI Spaces add-on can run managed JupyterLab and Code Editor environments directly on Amazon EKS. The approach targets machine learning teams that already operate Kubernetes clusters for training, storage and...
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