This post is cowritten with Remi Louf, CEO and technical founder of Dottxt. Structured output in AI applications refers to AI-generated responses conforming to formats that are predefined, validated, and […]
Generate structured output from LLMs with Dottxt Outlines in AWS Read More »
Organizations across in Thailand, Malaysia, Singapore, Indonesia, and Taiwan can now access Anthropic Claude Opus 4.6, Sonnet 4.6, and Claude Haiku 4.5 through Global cross-Region inference (CRIS) on Amazon Bedrock—delivering
We’re excited to announce the availability of Anthropic’s Claude Opus 4.6, Claude Sonnet 4.6, Claude Opus 4.5, Claude Sonnet 4.5, and Claude Haiku 4.5 through Amazon Bedrock global cross-Region inference
Critical labor shortages are constraining growth across manufacturing, logistics, construction, and agriculture. The problem is particularly acute in construction: nearly 500,000 positions remain unfilled in the United States, with 40%
Scaling data annotation using vision-language models to power physical AI systems Read More »
In precision medicine, researchers developing diagnostic tests for early disease detection face a critical challenge: datasets containing thousands of potential biomarkers but only hundreds of patient samples. This curse of
How Sonrai uses Amazon SageMaker AI to accelerate precision medicine trials Read More »
This blog post was co-authored with Johannes Maunz, Tobias Bösch Borgards, Aleksander Cisłak, and Bartłomiej Gralewicz from Hexagon. Hexagon is the global leader in measurement technologies and provides the confidence
Accelerating AI model production at Hexagon with Amazon SageMaker HyperPod Read More »
This post is cowritten by Jeff Boudier, Simon Pagezy, and Florent Gbelidji from Hugging Face. Agentic AI systems represent an evolution from conversational AI to autonomous agents capable of complex reasoning, tool
Agentic AI with multi-model framework using Hugging Face smolagents on AWS Read More »
In 2025, Amazon SageMaker AI saw dramatic improvements to core infrastructure offerings along four dimensions: capacity, price performance, observability, and usability. In this series of posts, we discuss these various
In 2025, Amazon SageMaker AI made several improvements designed to help you train, tune, and host generative AI workloads. In Part 1 of this series, we discussed Flexible Training Plans
Amazon Quick supports Model Context Protocol (MCP) integrations for action execution, data access, and AI agent integration. You can expose your application’s capabilities as MCP tools by hosting your own MCP
Integrate external tools with Amazon Quick Agents using Model Context Protocol (MCP) Read More »
