First-party releases and research from AWS Machine Learning Blog. Headlines and excerpts link to the original articles.
This technical how-to builds a conversational claims assistant on Amazon Bedrock Knowledge Bases that answers natural-language questions with citations. It covers ingesting claim documents from Amazon S3, querying with the AgenticRetrieveStream API, multi-turn follow-ups, metadata filters, and contextual grounding guardrails.
Amazon Bedrock AgentCore Runtime Instances gives multi-agent workflows AWS managed EC2 infrastructure with GPUs, persistent volumes, and multi-day sessions. In this post, we deploy a three-agent music production pipeline where the agents colocate on one GPU instance, share a filesystem, and hand work to each other to produce a finished track.
Anthropic's Claude Opus 5, Claude Sonnet 5, and Claude Haiku 4.5 are now available in India through Amazon Bedrock geographic cross-Region inference. You can access these models while processing data within the India Regions, and get started from the Amazon Bedrock console or with the Messages, InvokeModel, and Converse APIs.
Amazon Bedrock now supports Anthropic's Claude Opus 5 and Claude Sonnet 5 with in-region inference in Seoul, and Claude Sonnet 5 in Singapore. If you have local data processing requirements in South Korea or Singapore, you can now use these Anthropic models at scale, with inference processed entirely within the Region you call.
GPT-6.1 Sol is now generally available on Amazon Bedrock, bringing stronger reasoning to coding, computer use, and professional workloads that run frequently.
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.
Part 2 of our Amazon Quick prompt engineering series goes component by component. Learn the prompt patterns that get the best results from Amazon Quick Research, Quick Flows, Quick Sight, chat agents, and action integrations, plus the common pitfalls to avoid.
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.
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.
xAI's Grok 4.7 is now available on Amazon Bedrock, offering a 500K token context window and four configurable reasoning effort levels: low, medium, high, and xhigh. It is served on the bedrock-runtime endpoint through cross-Region inference profiles and supports the Responses, Chat Completions, and Converse APIs.
Claude Sonnet 5.5 is now available on Amazon Bedrock and Claude Platform on AWS. It's a smarter, more efficient Sonnet model for focused coding and knowledge work, with a lower cost per task at faster speed. This post covers what's new, when to choose Sonnet, and how to get started.
Deploy a text-to-speech model on Amazon SageMaker AI with the AWS vLLM-Omni Deep Learning Container and stream generated speech over a persistent bidirectional connection. This Part 1 tutorial deploys Qwen3-TTS and streams speech through a Gradio application.
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.
AWS published a technical post describing an agent-driven synthetic monitoring solution built on Amazon Nova Act and Amazon Bedrock AgentCore, with a sample repository. The post covers architecture, deployment, cost and security considerations, and reports over 90% accuracy for Nova Act in early enterprise customer browser workflow use cases.
An AWS Machine Learning Blog post describes patterns for managing Amazon Textract adapter lifecycles across AWS accounts, including infrastructure templates, CI/CD promotion, security configuration, and a pre-classification routing approach. It details cross-account copy via AWS Support or a centralized hub account model, and externalizing adapter IDs in Parameter Store.
AWS published a post describing an architecture that combines Amazon EKS, Elastic Fabric Adapter (EFA), and DeepEP to support large-scale MoE reinforcement learning. Across 48 P5en instances running a super-sparse MoE model, enabling DeepEP over EFA increased aggregate RL rollout throughput by 40 percent.
An AWS Machine Learning Blog post walks through running SkyRL, an open-source reinforcement learning framework, on Amazon SageMaker HyperPod to train a Qwen3-VL-8B vision-language model to navigate visual mazes with GRPO. Starting from the VisGym SFT checkpoint, the post reports the maze solve rate rose from 43.75% to more than 95% on a fixed 64-maze evaluation set.
AWS published a post detailing five quality assurance techniques in its NarrateAI assistant built on Amazon Bedrock, used by over 4,000 AWS executive leaders. The techniques are adaptive pipeline orchestration, cross-account multi-model failover, real-time streaming evaluation, composite evaluation framework and data accuracy verification, which AWS says achieve approximately 99 percent numerical accuracy.
Deploy the publicly available Qwen3-TTS-12Hz-1.7B-Base text-to-speech model from Amazon SageMaker JumpStart to a fully managed, real-time endpoint, and clone a voice from a short reference clip. Cross-lingual cloning preserves the speaker's identity across languages.
Learn how Datacor built a self-service rental analytics experience for gas and welding distributors by embedding Amazon Quick Sight dashboards and natural language querying into its TrackAbout platform, powered by an automated cross-cloud data pipeline and multi-tenant row-level security.