Amazon SageMaker AI integrated MLflow for model monitoring in a July 7, 2026 AWS blog post, separating data drift from model drift to help ML teams identify whether input distribution changes or predi…
Amazon Web Services introduced a model monitoring architecture using the open-source Evidently Python library and Amazon SageMaker AI with MLflow to detect data and model drift in discriminative ML mo…
Amazon Web Services announced a new pipeline using Amazon Nova foundation models to automatically redact Personally Identifiable Information (PII) in images, addressing compliance with regulations lik…
Amazon SageMaker AI now integrates with MLflow to stream benchmark and recommendation results into a unified tracking interface, reducing data silos and accelerating iteration cycles for generative AI…
Amazon Web Services released best practices for multi-turn reinforcement learning in Amazon SageMaker AI, covering environment design, reward alignment, and evaluation. The guidance helps developers t…
Amazon Web Services announced BoltzGen on Amazon SageMaker AI, a diffusion-based generative model for protein binder design that manages GPU compute infrastructure end to end. The service reduces oper…
Amazon Web Services announced that fine-tuning Amazon Nova models using SageMaker AI can achieve up to 94.77% accuracy in extracting data from emails, reducing costs by 50% and latency by over 30%. Th…
Amazon SageMaker AI now supports NVIDIA Blackwell GPUs with P6-B200 instances, enabling optimized training for large AI models through expanded memory and new precision formats. The integration allows…
ByteDance's open-source SeedVR2 video restoration model is now deployable on Amazon SageMaker AI, enabling scalable super resolution for low-resolution video libraries. The solution uses a three-tier …
NVIDIA and AWS announced a collaboration to bring AI to production scale, introducing Amazon EC2 G7 instances with NVIDIA RTX PRO 4500 Blackwell GPUs that deliver up to 4.6x AI inference performance, …
Amazon Web Services announced support for running ComfyUI workflows on Amazon SageMaker AI processing jobs, enabling enterprises to automate content generation at scale. The integration allows users t…
Amazon SageMaker AI now emits over 100 detailed inference metrics and provides a built-in Insights dashboard in Amazon CloudWatch, enabling teams to monitor and debug generative AI inference endpoints…
Amazon Web Services announced container image caching for Amazon SageMaker AI inference, reducing end-to-end latency by up to 2x for generative AI models during scale-out events by eliminating contain…
Amazon has introduced a method for running machine learning inference on Amazon SageMaker AI using fully homomorphic encryption (FHE), which keeps data encrypted throughout the entire process—includin…
Fundamental’s NEXUS large tabular model is now available on Amazon SageMaker JumpStart, enabling enterprises to deploy a foundation model purpose-built for structured data prediction. The model genera…
Amazon Web Services announced a new method for improving AI agent tool-calling accuracy using Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO) on Amazon SageMaker AI. The approach…
Amazon Web Services has introduced a comprehensive observability solution for large language model inference on Amazon SageMaker AI, addressing both infrastructure performance and output quality monit…
Azercell Telecom LLC, Azerbaijan's leading telecommunications provider, trained an Azerbaijani large language model on Amazon SageMaker AI in collaboration with the AWS Generative AI Innovation Center…
Amazon SageMaker AI now supports OpenAI-compatible API for real-time inference endpoints, allowing users to invoke models by changing only the endpoint URL without custom clients or code rewrites. The…
Amazon SageMaker AI now supports bidirectional streaming for real-time inference, enabling developers to build voice applications that process audio and return transcriptions simultaneously over a sin…