Category: Public Sector

We’re excited to introduce US-based frontier open-weight models in AWS GovCloud (US). With this release, Amazon Bedrock now supports OpenAI’s open-weight GPT OSS models (120B and 20B) and NVIDIA Nemotron (Nano 9B v2, Nano 12B v2, Nano 30B, Super 120B) models. In this post, we cover these models and their capabilities, the inference options for data residency, the available service tiers and how to get started.

In this post, we build a multimodal retrieval system for aerospace manufacturing documents using Amazon Nova Multimodal Embeddings on Amazon Bedrock and Amazon S3 Vectors. We evaluate the system on 26 manufacturing queries and compare generation quality between a text-only pipeline and the multimodal pipeline.

In this post, we show you how to use Amazon SageMaker AI to build and deploy a deep learning model for detecting solar flares using data from the European Space Agency’s STIX instrument.

In this post, we explore how the multimodal foundation models (FMs) of Amazon Bedrock enable scalable video understanding through three distinct architectural approaches. Each approach is designed for different use cases and cost-performance trade-offs.

In this post, you will understand how Policy in Amazon Bedrock AgentCore creates a deterministic enforcement layer that operates independently of the agent’s own reasoning. You will learn how to turn natural language descriptions of your business rules into Cedar policies, then use those policies to enforce fine-grained, identity-aware controls so that agents only access the tools and data that their users are authorized to use. You will also see how to apply Policy through AgentCore Gateway, intercepting and evaluating every agent-to-tool request at runtime.

Experts at the Generative AI Innovation Center share several strategies to help organizations excel with generative AI.

In this post, we will walk through the performance constraints and design choices by OARC and REMAP teams at UCLA, including how AWS serverless infrastructure, AWS Managed Services, and generative AI services supported the rapid design and deployment of our solution. We will also describe our use of Amazon SageMaker AI and how it can be used reliably in immersive live experiences.

This post demonstrates how to quickly build sophisticated AI agents using Strands Agents, scale them reliably with Amazon Bedrock AgentCore, and make them accessible through LibreChat’s familiar interface to drive immediate user adoption across your institution.

In this post, we provide a data imputation solution using Amazon SageMaker AI, AWS Lambda, and AWS Step Functions. This solution is designed for environmental analysts, public health officials, and business intelligence professionals who need reliable PM2.5 data for trend analysis, reporting, and decision-making. We sourced our sample training dataset from openAFRICA. Our solution predicts PM2.5 values using time-series forecasting.

In this post, we explore each component in detail, along with the technical implementation of the two core modules: course outline generation and course content generation.