Amazon SageMaker AI

2026-09-18

COMPANIES · 1 SOURCE · AWS Machine Learning

AWS shows how to migrate multi-model Hugging Face smolagents to Amazon Bedrock AgentCore runtime

AWS published a how-to that migrates a multi-model healthcare AI agent built with Hugging Face smolagents from a self-managed Amazon ECS/Fargate deployment to the managed Amazon Bedrock AgentCore runtime. The solution preserves existing agent logic while offloading container lifecycle, scaling, identity, and observability to AgentCore and demonstrates orchestration across Llama 3.1 70B Instruct on Bedrock, BioM-ELECTRA-Large-SQuAD2 on SageMaker (and containerized), plus vector retrieval via Amazon OpenSearch Service.

6.0

2026-09-18

CODING · 1 SOURCE · AWS Machine Learning

Hugging Face publishes six open-source Skills to deploy models on Amazon SageMaker AI via coding agents

Hugging Face published six open-source 'Skills' (GitHub) that let coding agents orchestrate end-to-end deployment of Hugging Face models to Amazon SageMaker AI. The skills automate selecting the correct serving container from AWS Deep Learning Containers, creating real-time or serverless endpoints with autoscaling and CloudWatch alarms, and provide verified teardown paths; they run using Python and the AWS CLI and are designed to prevent fragile or costly agent-made deployment mistakes.

6.0

2026-09-17

MODELS · 1 SOURCE · AWS Machine Learning

Amazon SageMaker deploys Qwen-Image-Edit-2509 and Rekognition to augment industrial-safety datasets with synthetic people

Amazon demonstrates an end-to-end pipeline on SageMaker AI that uses the diffusion model Qwen-Image-Edit-2509 (hosted on an ml.g5.12xlarge with NVIDIA A10G GPUs) to insert photo-realistic synthetic people into real equipment images, then generates bounding-box annotations automatically via Amazon Rekognition DetectLabels; experiments reportedly showed up to 160% improvement in person-detection mAP50 without manual annotation. The workflow edits real scenes in-place to preserve background fidelity, deduplicates Rekognition boxes with NMS, and converts labels to YOLO format for training.

6.0

2026-09-15

COMPANIES · 1 SOURCE · AWS Machine Learning

Amazon SageMaker AI adds instance preference lists for training and processing jobs

Amazon SageMaker AI now supports instance preference lists for training and processing jobs. You can specify an ordered list of up to five instance types, and SageMaker AI will automatically launch the first type with available capacity, removing the need for manual retry loops and capacity‑watching scripts.

6.0