Accelerate campaign workflow with insights from Adobe Marketing Agent for Amazon Quick
This post shows how to enable Adobe Marketing Agent for Amazon Quick using a Model Context Protocol (MCP). We walk you through how to configure the…
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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…
Amazon Bedrock AgentCore harness is now generally available: Go from idea to production-grade agent in minutes
Today, Amazon Bedrock AgentCore harness is generally available. Two API calls (CreateHarness to define an agent, and InvokeHarness to run it), and you have an agent…
Amazon SageMaker AI Async Inference now supports inline request payloads
Today, we’re announcing inline payload support for Amazon SageMaker AI Async Inference. Customers can now send inference payloads directly in the request body of the InvokeEndpointAsync…
Get back hours every day with autonomous agents in Amazon Quick
Today, Quick gets even more powerful: new autonomous agents that work continuously on your behalf, an activity feed that helps you prioritize your most important work,…
Context intelligence for your data and AI agents at scale
Agents are only as intelligent as the context they can reason over. Today, that context is scattered across data lakes, data warehouses, lakehouses, databases, and streams,…
New in Amazon Bedrock AgentCore: Build agents with broader knowledge and continuous learning
Today we're introducing new capabilities on Amazon Bedrock AgentCore, the platform to build, connect, and optimize agents. In this post, we cover how these capabilities close…
Safeguard your agentic AI applications with the Amazon Bedrock Guardrails InvokeGuardrailChecks API
Today, we’re announcing a new API with Amazon Bedrock Guardrails. With this API, you can apply individual safeguards, also referred to as safety checks, at any…
Introducing container caching in Amazon SageMaker AI for faster model scaling
Today, we’re excited to announce container image caching for Amazon SageMaker AI inference, the next major advancement in our faster scaling optimization journey. This speeds up…
Parallelize speculative decoding with P-EAGLE on Amazon SageMaker AI
This post walks you through how to use P-EAGLE directly within Amazon SageMaker AI. It will demonstrate how to select a compatible model from the SageMaker…