Releasesby Glyph
Amazon SageMaker AI now supports SOCI-indexed images to start training jobs in seconds
Amazon SageMaker AI now supports Seekable OCI (SOCI)-indexed container images, allowing training and processing jobs to lazy-load images and start in seconds instead of minutes.
Also shipped Oct 29, 2026AWS in October 2026 →
Monte Carlo's Terraform provider is now on the OpenTofu registry
Monte Carlo has published its Terraform provider and agent modules to the OpenTofu registry, enabling users to manage Monte Carlo infrastructure as code using OpenTofu.
REST API v2 (Public preview): onboard Monte Carlo from your AI tool, Terraform or a script
Monte Carlo's REST API v2 is now in public preview, enabling automated onboarding and deployment of collection agents via scripts, Terraform, or AI tools.
Gemini-powered Explore summaries in Looker are generally available
The ability to generate summaries of Looker Explores using Gemini assistance is now generally available.
Dashboard relationships are now generally available
Dashboard relationships, which enable multi-fact data models in AI/BI dashboards, are now generally available.
Looker bullet chart visualization is generally available
The bullet chart visualization type is now generally available in Looker, allowing users to evaluate metric performance against targets and thresholds.
Xero connector is available in Beta
The managed Xero connector is now available in beta for Databricks Lakeflow Connect, supporting incremental ingestion of accounting data.
More from Amazon SageMakerEvery Amazon SageMaker release →
SageMaker MLflow Apps now support MLflow 3.16
Amazon SageMaker MLflow Apps now support MLflow 3.16, featuring a redesigned trace explorer and improved experiment tracking performance for generative AI and agentic workflows.
Amazon SageMaker Unified Studio adds light mode support for IDC-based domains
Amazon SageMaker Unified Studio now supports a light mode theme for Identity Center-based domains to improve accessibility.
Amazon SageMaker AI announces training session APIs for serverless model customization
New training session APIs for SageMaker AI serverless model customization allow developers to define custom training loops for SFT, DPO, and reinforcement learning without managing GPU infrastructure.
Amazon SageMaker AI now supports serverless model customization for Muse Glimmer, Qwen 3.8 and Ministral 3 models
SageMaker AI now supports serverless model customization for Muse Glimmer, Qwen 3.8, and Ministral 3 models. Users can apply SFT, DPO, and RFT techniques using LoRA or full fine-tuning.
Amazon SageMaker AI now supports custom sequence lengths for serverless model customization jobs
Today, Amazon SageMaker AI announces the ability to configure the sequence length used during your serverless model customization job. Amazon SageMaker AI serverless model customization supports fine-tuning for many open-weight models, including models from popular families including gpt-oss, Gemma, Llama, Nemotron, and Qwen.
Nemotron 3.5 Super VL model now available on Amazon SageMaker JumpStart
NVIDIA's Nemotron 3.5 Super VL is now available on Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers. This vision-language model from the Nemotron 3.5 family accepts images, video, and text as input and generates text, enabling customers to deploy multimodal AI solutions on AWS infrastructure.
Beam model by Reflection is now available on Amazon SageMaker JumpStart and AWS Trainium
Beam, the first open weight model offered by US-based Reflection, is now available in Amazon SageMaker JumpStart, the model hub in Amazon SageMaker AI. According to Beam, they operate at the frontier of open weight models in its class, with strong performance across reasoning, coding, and agentic benchmarks.
Amazon SageMaker Studio simplifies getting started for new AI/ML builders with new sign-in options
Amazon SageMaker Studio now lets new customers sign up with their Google, GitHub, or Apple credentials and land inside a fully configured Studio environment - no traditional AWS account setup and no console navigation required.