Artificial Intelligence

Safely Releasing Frontier Models to Customers

Safely Releasing Frontier Models to Customers

It’s our goal for AWS to be the most secure place to run any workload, and in support of that we’ve been deeply investing in security across our services since AWS’s inception more than two decades ago. Our AI services like Amazon Bedrock are built on this foundation and with the same focus. 

Prompt engineering fundamentals for Amazon Quick

Prompt engineering fundamentals for Amazon Quick

Prompt engineering in Amazon Quick shapes how accurately its AI-powered features respond to your requests. Part 1 of a two-part series covers the foundational principles and reusable frameworks (specificity, context-setting, few-shot examples, and the CRISPE framework) for consistent, high-quality results across Amazon Quick.

Building an AI-powered contract intelligence platform with Amazon Quick and Amazon Bedrock AgentCore

Building an AI-powered contract intelligence platform with Amazon Quick and Amazon Bedrock AgentCore

Manually extracting data from hundreds of vendor contracts doesn’t scale, and RAG chat tools fall short on portfolio-wide questions. This post shares a contract intelligence platform on AWS that uses AI agents to extract and verify contract fields, then answers aggregate and single-contract questions through Amazon Quick analytics.

How Condé Nast built multimodal video discovery with Amazon Bedrock

How Condé Nast built multimodal video discovery with Amazon Bedrock

Condé Nast’s editorial teams spent an average of 250 minutes per task searching a library of more than 140,000 videos using only titles and descriptions. Working with the AWS Generative AI Innovation Center, they built a multimodal video discovery solution on Amazon Bedrock and Amazon OpenSearch Service that cut discovery time to under 2 minutes.

Grok 4.7 is now available on Amazon Bedrock

Grok 4.7 is now available on Amazon Bedrock

xAI’s Grok 4.7 is now available on Amazon Bedrock: a frontier model for coding, long-running agents, and knowledge work. It offers a 500K token context window and four configurable reasoning effort levels, reachable through the Responses, Chat Completions, and Converse APIs.

Generate images and video with vLLM-Omni on SageMaker AI - Part 2

Generate images and video with vLLM-Omni on SageMaker AI – Part 2

Deploy two generative media models from one AWS vLLM-Omni Deep Learning Container on Amazon SageMaker AI. Generate an image with FLUX.2-klein through real-time inference, then animate it into video with Wan2.1-VACE through asynchronous inference, and retrieve the MP4 from Amazon S3.