Category: Amazon Bedrock

Learn how researchers in the University of São Paulo Research Center in Greenhouse Gas Innovation (RCGI) greenhouse gas (GHG) program saw an opportunity to develop a system that enabled close monitoring of the forest using data systems and data spaces in the cloud. They created Digital Amazon, a distributed data space network with open access that integrates CO2 and greenhouse gas emissions data collected by the university with other data sources to support critical and timely climate action and intervention in the Amazon Forest.

In this post, we walk you through how FRESH is translating cloud-enabled analytics into practical tools that support resilient, trusted food systems, starting with a deep dive into dynamic shelf-life modeling. Specifically, we detail how AWS services such as Amazon Simple Storage Service (Amazon S3), AWS Glue, and Amazon SageMaker AI are used to build and train predictive models.

Healthcare is entering a new era. Advances in AI, data analytics, and cloud computing are creating opportunities ranging from accelerating drug discovery and enabling precision medicine to helping clinicians detect disease earlier and spend more time with patients. As healthcare organizations embrace these technologies, they face an equally important responsibility: safeguarding some of the world’s […]

Learn how between Amazon Web Services (AWS) and HUMANBULB, the community organization behind the AWS Sacramento User Group — became a model that other cloud companies and community leaders can replicate. In this post, we share what we built, what we learned, and how other AWS teams and community leaders can apply the same approach in their own cities.

The methodology described in this post translates subjective personality requirements into testable behaviors, versioned prompts, and documented boundaries. It addresses several dimensions of Responsible AI at AWS, an eight-dimension framework that guides how we build and evaluate AI systems.

This post explains how to build exactly that using Strands Agents and Amazon Bedrock. The entire solution runs in about 200 lines of Python code, and you can have it working on your computer after completing the pre-requisite steps.

Learn how Amazon Web Services (AWS) operates inside a scoped compute environment with an AWS Identity and Access Management (IAM) execution role, network segmentation, and defense-in-depth security meeting FISMA, FedRAMP, and DoD CCSRG standards.

This post gives you a practical framework for turning project experience into organizational learning and shows how Amazon Web Services (AWS) AI services accelerate the process.

In this blog post, Sanjeev Pulapaka of AWS explores how agentic AI—deploying multiple specialized agents that understand intent and context—can dramatically accelerate the federal rulemaking lifecycle by addressing its three major bottlenecks: NPRM development, public comment analysis, and final rule clearance.

Learn how BMJ Group has developed an AI-powered editorial assistant designed to help journal editors screen submitted research manuscripts to make better decisions about which papers to send for further peer review, which to reject, and why.