AWS Machine Learning Blog

Category: Amazon Bedrock

Video auto-dubbing using Amazon Translate, Amazon Bedrock, and Amazon Polly

This post is co-written with MagellanTV and Mission Cloud.  Video dubbing, or content localization, is the process of replacing the original spoken language in a video with another language while synchronizing audio and video. Video dubbing has emerged as a key tool in breaking down linguistic barriers, enhancing viewer engagement, and expanding market reach. However, […]

Using Agents for Amazon Bedrock to interactively generate infrastructure as code

In this blog post, we explore how Agents for Amazon Bedrock can be used to generate customized, organization standards-compliant IaC scripts directly from uploaded architecture diagrams. This will help accelerate deployments, reduce errors, and ensure adherence to security guidelines.

Automating model customization in Amazon Bedrock with AWS Step Functions workflow

Large language models have become indispensable in generating intelligent and nuanced responses across a wide variety of business use cases. However, enterprises often have unique data and use cases that require customizing large language models beyond their out-of-the-box capabilities. Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) […]

Knowledge Bases for Amazon Bedrock now supports advanced parsing, chunking, and query reformulation giving greater control of accuracy in RAG based applications

Knowledge Bases for Amazon Bedrock is a fully managed service that helps you implement the entire Retrieval Augmented Generation (RAG) workflow from ingestion to retrieval and prompt augmentation without having to build custom integrations to data sources and manage data flows, pushing the boundaries for what you can do in your RAG workflows. However, it’s […]

Streamline generative AI development in Amazon Bedrock with Prompt Management and Prompt Flows (preview)

Today, we’re excited to introduce two powerful new features for Amazon Bedrock: Prompt Management and Prompt Flows, in public preview. These features are designed to accelerate the development, testing, and deployment of generative artificial intelligence (AI) applications, enabling developers and business users to create more efficient and effective solutions that are easier to maintain. You […]

Empowering everyone with GenAI to rapidly build, customize, and deploy apps securely: Highlights from the AWS New York Summit

Imagine this—all employees relying on generative artificial intelligence (AI) to get their work done faster, every task becoming less mundane and more innovative, and every application providing a more useful, personal, and engaging experience. To realize this future, organizations need more than a single, powerful large language model (LLM) or chat assistant. They need a […]

Fine-tune Anthropic’s Claude 3 Haiku in Amazon Bedrock to boost model accuracy and quality

Frontier large language models (LLMs) like Anthropic Claude on Amazon Bedrock are trained on vast amounts of data, allowing Anthropic Claude to understand and generate human-like text. Fine-tuning Anthropic Claude 3 Haiku on proprietary datasets can provide optimal performance on specific domains or tasks. The fine-tuning as a deep level of customization represents a key […]

Build your multilingual personal calendar assistant with Amazon Bedrock and AWS Step Functions

This post shows you how to apply AWS services such as Amazon Bedrock, AWS Step Functions, and Amazon Simple Email Service (Amazon SES) to build a fully-automated multilingual calendar artificial intelligence (AI) assistant. It understands the incoming messages, translates them to the preferred language, and automatically sets up calendar reminders.

Medical content creation in the age of generative AI

Generative AI and transformer-based large language models (LLMs) have been in the top headlines recently. These models demonstrate impressive performance in question answering, text summarization, code, and text generation. Today, LLMs are being used in real settings by companies, including the heavily-regulated healthcare and life sciences industry (HCLS). The use cases can range from medical […]

Introducing guardrails in Knowledge Bases for Amazon Bedrock

Knowledge Bases for Amazon Bedrock is a fully managed capability that helps you securely connect foundation models (FMs) in Amazon Bedrock to your company data using Retrieval Augmented Generation (RAG). This feature streamlines the entire RAG workflow, from ingestion to retrieval and prompt augmentation, eliminating the need for custom data source integrations and data flow […]