Social Media Ideas for Amazon Machine Learning

Streaming benchmark and recommendation results to MLflow with Amazon SageMaker AI

In this post, you learn how to use the new MLflow integration with Amazon SageMaker AI optimized inference recommendation jobs and Amazon SageMaker AI benchmark jobs to automatical...

Launching UI for generative AI inference recommendations in Amazon SageMaker AI

In this post, we introduce the UI for optimized generative AI inference recommendations in Amazon SageMaker AI Studio, a low-code no-code (LCNC) experience. The API already gives y...

Monitoring discriminative ML models using Amazon SageMaker AI with MLflow

Implementing a data and model monitoring solution is necessary to maintain prediction accuracy and help achieve the best outcome for your machine learning use case. This post shows...

Build real-time voice applications with Amazon SageMaker AI and vLLM

Voice agents, live captioning, contact center analytics, and accessibility tools all depend on real-time speech-to-text, where your application streams audio in and receives transc...

Monitor and debug generative AI inference with SageMaker detailed metrics and Insights dashboard on CloudWatch

Amazon SageMaker AI provides fully managed real-time inference hosting for machine learning models. You deploy a model to a SageMaker endpoint backed by one or more compute instanc...

From Hugging Face to Amazon SageMaker Studio in one click

Today, we’re excited to announce a deep-link integration between Hugging Face and Amazon SageMaker AI. Developers can now go from model discovery to hands-on experimentation in Sag...

Announcing OpenAI-compatible API support for Amazon SageMaker AI endpoints

Today, Amazon SageMaker AI introduces OpenAI-compatible API support for real-time inference endpoints. If you use the OpenAI SDK, LangChain, or Strands Agents, you can now invoke m...

How Amazon is moving to integrate catalogs to improve data discovery with Amazon SageMaker

Enterprises face challenges when teams create data assets outside of central data catalogs. It adds overhead for discovery, and limits collaboration. Amazon’s Business Data Technol...

Running ComfyUI workflows on Amazon SageMaker AI processing jobs

In this post, we walk you through how to deploy ComfyUI workflows on Amazon SageMaker AI processing jobs to generate hundreds of high-quality images in a single batch. You learn ho...

Introducing the Agent Toolkit for Amazon Web Services

It’s like having your own personal expert AWS solutions architect and data engineer rolled into one. The post Introducing the Agent Toolkit for Amazon Web Services appeared first o...

Comprehensive observability for Amazon SageMaker AI LLM inference: From GPU utilization to LLM quality

This post demonstrates a comprehensive observability solution using Amazon Managed Grafana dashboards that provides a holistic view of both quality and quantity for LLMs served on...

Deploying quantized models on Amazon SageMaker AI with Unsloth

In this post, you will learn four deployment patterns for taking models that have already been quantized with Unsloth and deploying them on AWS infrastructure. The patterns use Ama...

Amazon Web Services debuts AI retail solution built on Alexa for Shopping

Simplify model selection in Amazon Bedrock with the open source Model Profiler

The Amazon Bedrock Model Profiler is an open source tool that aggregates model metadata from multiple AWS APIs and external sources into a single, searchable interface. In this pos...

Optimize model training on Amazon SageMaker AI with NVIDIA Blackwell

This post shows you how to configure training jobs on Amazon SageMaker AI to get the most out of Blackwell’s architecture on AWS. You learn how to select batch sizes and sequence l...

AWS Unfurls Open Source AI Agent to Enable Better AI Coding Outcomes

Amazon Web Services (AWS) today previewed a customizable lightweight, open-source harness, dubbed Simple Strands Agent (SSA), that looks to provide a more consistent approach to th...

Agentic vision: Building visual intelligence with Amazon Bedrock and MCP servers

In this post, we walk you through the Computer Vision MCP Server, which illustrates this approach, representing how AI systems can process visual information and make intelligent d...

Detecting fraud patterns across Snowflake and AWS using SageMaker Data Agent

Amazon SageMaker Data Agent launches three new capabilities in Amazon SageMaker Unified Studio notebooks: SQL analytics on Snowflake data sources, materialized view management, and...

End-to-end encrypted ML inference with Amazon SageMaker AI and FHE

This blog has previously discussed FHE for ML inference in the post Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing, but this...

AWS is 20—and all in on AI

In 2006, Amazon Web Services was a fledgling—and a bit of an oddity. Amazon had taken the cloud-computing technologies it had created for its own operations and turned them into a...

Accelerate database modernization with agentic AI in AWS DMS Schema Conversion

Starting today, you can use AI agents to orchestrate entire AWS DMS Schema Conversion (DMS SC) workflows through natural language. An AI agent manages the full lifecycle, including...

NVIDIA Nemotron 3 Ultra now available on Amazon SageMaker JumpStart

Deploy NVIDIA Nemotron 3 Ultra on Amazon SageMaker JumpStart. Get 5x faster inference and 30% lower cost for agentic AI workloads with this frontier reasoning model.

AWS Invests $1B To Build An AI Engineering Outsource Team

AWS Invests $1B To Build An AI Engineering Outsource Team

Enhancing enterprise inference on Amazon SageMaker HyperPod with data capture, Hugging Face, NVMe, and Route 53 integrat...

In this post, we walk through five capabilities now available in SageMaker HyperPod inference: multi-tier data capture for auditing and model improvement, direct deployment from Hu...