AI

Using Amazon SageMaker AI Random Cut Forest for NASA’s Blue Origin spacecraft sensor data

The successful deorbit, descent, and landing of spacecraft on the Moon requires precise control and monitoring of vehicle dynamics. Anomaly detection provides a unique utility for identifying important states that might represent vehicle behaviors of interest. By producing unique vehicle behavior points, critical spacecraft system states can be identified to be more appropriately addressed and […]

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Build an intelligent multi-agent business expert using Amazon Bedrock

In this post, we demonstrate how to build a multi-agent system using multi-agent collaboration in Amazon Bedrock Agents to solve complex business questions in the biopharmaceutical industry. We show how specialized agents in research and development (R&D), legal, and finance domains can work together to provide comprehensive business insights by analyzing data from multiple sources.

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Driving cost-efficiency and speed in claims data processing with Amazon Nova Micro and Amazon Nova Lite

Amazon operations span the globe, touching the lives of millions of customers, employees, and vendors every day. From the vast logistics network to the cutting-edge technology infrastructure, this scale is a testament to the company’s ability to innovate and serve its customers. With this scale comes a responsibility to manage risks and address claims—whether they

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Merging AI and underwater photography to reveal hidden ocean worlds

In the Northeastern United States, the Gulf of Maine represents one of the most biologically diverse marine ecosystems on the planet — home to whales, sharks, jellyfish, herring, plankton, and hundreds of other species. But even as this ecosystem supports rich biodiversity, it is undergoing rapid environmental change. The Gulf of Maine is warming faster

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Power Your LLM Training and Evaluation with the New SageMaker AI Generative AI Tools

Today we are excited to introduce the Text Ranking and Question and Answer UI templates to SageMaker AI customers. The Text Ranking template enables human annotators to rank multiple responses from a large language model (LLM) based on custom criteria, such as relevance, clarity, or factual accuracy. This ranked feedback provides critical insights that help

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Amazon Bedrock Agents observability using Arize AI

This post is cowritten with John Gilhuly from Arize AI. With Amazon Bedrock Agents, you can build and configure autonomous agents in your application. An agent helps your end-users complete actions based on organization data and user input. Agents orchestrate interactions between foundation models (FMs), data sources, software applications, and user conversations. In addition, agents

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