Releasesby Ibis
Amazon SageMaker AI announces training session APIs for serverless model customization
Update2 days agoUnverifiedAdded Oct 23, 2026
Amazon SageMaker AI serverless model customization now supports training session APIs, giving customers full control over their post-training algorithm without provisioning or managing GPU infrastructure.
Topics: Security, Pricing, Developer tools
More Amazon SageMaker releases
Every Amazon SageMaker releaseAmazon SageMaker AI now supports serverless model customization for Muse Glimmer, Qwen 3.8 and Ministral 3 models
Amazon SageMaker AI now supports serverless model customization for Muse Glimmer, Qwen3.8 27B, and Ministral 3 3B, 8B, and 14B models. In addition to deploying these models on SageMaker AI, you can now adapt them to your specific domains and workflows, using supervised fine-tuning (SFT), direct preference optimization (DPO), and reinforcement 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.
Muse Spark Open model now available on Amazon SageMaker JumpStart
Meta's Muse Spark Open is now available on Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers. This coding-optimized open-weight model from Meta is purpose-built for agentic coding workflows, bringing multi-step reasoning and tool calling to enterprise software engineering on AWS infrastructure.
Amazon SageMaker Studio simplifies getting started for new AI/ML builders with social sign-in
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, no credit card, and no console navigation required.
Bring deep SageMaker AI expertise to your coding agent with the AWS AI/ML skill in the Agent Toolkit for AWS
Your coding agent can select, train, optimize and deploy models on Amazon SageMaker AI while working across the rest of your AWS environment in a single natural-language workflow. The AWS AI/ML skill is now a core skill in the Agent Toolkit for AWS , so it works alongside the toolkit's other AWS skills like EC2, Bedrock, and more.
Also shipped on Oct 22, 2026
AWS in October 2026Trace and evaluate Cursor agents with Langfuse, powered by ClickHouse
Users can now connect Cursor to Langfuse to trace agent turns and analyze model and tool calls, with ClickHouse providing the underlying analytics infrastructure.
The AI.TRANSLATE function lets you translate text strings between languages
The AI.TRANSLATE function lets you translate text strings between languages. AI.TRANSLATE supports standard Neural Machine Translation (NMT) workloads and Translation LLM (TLLM) capabilities. This function is generally available (GA).
Replit Monitoring Agent: Your very own software engineering team
Replit Monitoring Agent is an autonomous tool that investigates production alerts, identifies causes, applies fixes, and deploys them to production for internal apps.
Microsoft Entra ID connector is available in Beta
The managed Microsoft Entra ID connector is now available in Beta in Databricks Lakeflow Connect. Use the connector to ingest Microsoft Entra ID users, groups, applications, service principals, directory roles, identity configuration, and audit and sign-in logs into Databricks.
You can configure Direct VPC ingress for Cloud Run instances ( Preview )
You can configure Direct VPC ingress for Cloud Run instances ( Preview ). Direct VPC ingress lets Cloud Run instances on a VPC network use their own ephemeral private IP address to communicate with each other and with other resources on the VPC network.
Gemini Enterprise: Single-user quota limits
Gemini Enterprise administrators can configure single-user quota limits on the Usage & Spending > Usage page in the Google Cloud console to prevent an individual user from using all of an edition's shared subscription quota pool.