Artificial Intelligence
AWS launches frontier agents for security testing and cloud operations
I’m excited to announce that AWS Security Agent on-demand penetration testing and AWS DevOps Agent are now generally available, representing a new class of AI capabilities we announced at re:Invent called frontier agents. These autonomous systems work independently to achieve goals, scale massively to tackle concurrent tasks, and run persistently for hours or days without constant human oversight. Together, these agents are changing the way we secure and operate software. In preview, customers and partners report that AWS Security Agent compresses penetration testing timelines from weeks to hours and the AWS DevOps Agent supports 3–5x faster incident resolution.
Introducing granular cost attribution for Amazon Bedrock
In this post, we share how Amazon Bedrock’s granular cost attribution works and walk through example cost tracking scenarios.
Optimize video semantic search intent with Amazon Nova Model Distillation on Amazon Bedrock
In this post, we show you how to use Model Distillation, a model customization technique on Amazon Bedrock, to transfer routing intelligence from a large teacher model (Amazon Nova Premier) into a much smaller student model (Amazon Nova Micro). This approach cuts inference cost by over 95% and reduces latency by 50% while maintaining the nuanced routing quality that the task demands.
Power video semantic search with Amazon Nova Multimodal Embeddings
In this post, we show you how to build a video semantic search solution on Amazon Bedrock using Nova Multimodal Embeddings that intelligently understands user intent and retrieves accurate video results across all signal types simultaneously. We also share a reference implementation you can deploy and explore with your own content.
Nova Forge SDK series part 2: Practical guide to fine-tune Nova models using data mixing capabilities
This hands-on guide walks through every step of fine-tuning an Amazon Nova model with the Amazon Nova Forge SDK, from data preparation to training with data mixing to evaluation, giving you a repeatable playbook you can adapt to your own use case. This is the second part in our Nova Forge SDK series, building on the SDK introduction and first part, which covered kicking off customization experiments.
From hours to minutes: How Agentic AI gave marketers time back for what matters
In this post, we share how AWS Marketing’s Technology, AI, and Analytics (TAA) team worked with Gradial to build an agentic AI solution on Amazon Bedrock for accelerating content publishing workflows.
Cost-efficient custom text-to-SQL using Amazon Nova Micro and Amazon Bedrock on-demand inference
In this post, we demonstrate two approaches to fine-tune Amazon Nova Micro for custom SQL dialect generation to deliver both cost efficiency and production ready performance.
Transform retail with AWS generative AI services
Online retailers face a persistent challenge: shoppers struggle to determine the fit and look when ordering online, leading to increased returns and decreased purchase confidence. The cost? Lost revenue, operational overhead, and customer frustration. Meanwhile, consumers increasingly expect immersive, interactive shopping experiences that bridge the gap between online and in-store retail. Retailers implementing virtual try-on […]
How Automated Reasoning checks in Amazon Bedrock transform generative AI compliance
In this post, you’ll learn why probabilistic AI validation falls short in regulated industries and how Automated Reasoning checks use formal verification to deliver mathematically proven results. You’ll also see how customers across six industries use this technology to produce formally verified, auditable AI outputs, and how to get started.
Create rich, custom tooltips in Amazon Quick Sight
Today, we’re announcing sheet tooltips in Amazon Quick Sight. Dashboard authors can now design custom tooltip layouts using free-form layout sheets. These layouts combine charts, key performance indicator (KPI) metrics, text, and other visuals into a single tooltip that renders dynamically when readers hover over data points.
Accelerating decode-heavy LLM inference with speculative decoding on AWS Trainium and vLLM
In this post, you will learn how speculative decoding works and why it helps reduce cost per generated token on AWS Trainium2.










