Category: Artificial Intelligence

Amazon Bedrock Guardrails now extends its safety controls to protect code generation across twelve programming languages, addressing critical security challenges in AI-assisted software development. In this post, we explore how to configure content filters, prompt attack detection, denied topics, and sensitive information filters to safeguard against threats like prompt injection, data exfiltration, and malicious code generation while maintaining developer productivity .

Amazon’s AI-powered Amazon Compliance Screening system tackles complex compliance challenges through autonomous agents that analyze, reason through, and resolve cases with precision. This blog post explores how Amazon’s Compliance team built its AI-powered investigation system through a series of AI agents built on AWS.

In this post, we cover how you can use tools from Snowflake AI Data Cloud and Amazon Web Services (AWS) to build generative AI solutions that organizations can use to make data-driven decisions, increase operational efficiency, and ultimately gain a competitive edge.

In this post you will learn how to use Spectrum to optimize resource use and shorten training times without sacrificing quality, as well as how to implement Spectrum fine-tuning with Amazon SageMaker AI training jobs. We will also discuss the tradeoff between QLoRA and Spectrum fine-tuning, showing that while QLoRA is more resource efficient, Spectrum results in higher performance overall.

RoboTic-Tac-Toe is an interactive game where two physical robots move around a tic-tac-toe board, with both the gameplay and robots’ movements orchestrated by LLMs. Players can control the robots using natural language commands, directing them to place their markers on the game board. In this post, we explore the architecture and prompt engineering techniques used to reason about a tic-tac-toe game and decide the next best game strategy and movement plan for the current player.

This blog post introduces two major enhancements to Amazon SageMaker HyperPod that strengthen security and storage capabilities for large-scale machine learning infrastructure. The new features include customer managed key (CMK) support for encrypting EBS volumes with organization-controlled encryption keys, and Amazon EBS CSI driver integration that enables dynamic storage management for Kubernetes volumes in AI workloads.

In this post, I will illustrate how applying platform engineering principles to generative AI unlocks faster time-to-value, cost control, and scalable innovation.

This year, re:Invent will be held in Las Vegas, Nevada, from December 1 to December 5, 2025, and this guide will help you navigate our comprehensive session catalog and plan your week. The sessions cater to business and technology leaders, product and engineering teams, and data and analytics teams interested in incorporating agentic AI capabilities across their teams and organization.

I’m excited to announce AWS Professional Services now offers specialized AI agents including the AWS Professional Services Delivery Agent. This represents a transformation to the consulting experience that embeds intelligent agents throughout the consulting life cycle to deliver better value for customers.

In this post, we explore how Amazon Bedrock AgentCore and Claude are enabling enterprises like Cox Automotive and Druva to deploy production-ready agentic AI systems that deliver measurable business value, with results including up to 63% autonomous issue resolution and 58% faster response times. We examine the technical foundation combining Claude’s frontier AI capabilities with AgentCore’s enterprise-grade infrastructure that allows organizations to focus on agent logic rather than building complex operational systems from scratch.