An introduction to preparing your own dataset for LLM training
In this blog post, we provide an introduction to preparing your own dataset for LLM training. Whether your goal is to fine-tune a pre-trained model for a specific task or…
Amazon Bedrock
Simplify multimodal generative AI with Amazon Bedrock Data Automation
Amazon Bedrock Data Automation in public preview, offers a unified experience for developers of all skillsets to easily automate the extraction, transformation, and generation of relevant insights from documents, images,…
Advancing AI trust with new responsible AI tools, capabilities, and resources
With trust as a cornerstone of AI adoption, we are excited to announce at AWS re:Invent 2024 new responsible AI tools, capabilities, and resources that enhance the safety, security, and…
Amazon Bedrock Marketplace now includes NVIDIA models: Introducing NVIDIA Nemotron-4 NIM microservices
At AWS re:Invent 2024, we are excited to introduce Amazon Bedrock Marketplace. This a revolutionary new capability within Amazon Bedrock that serves as a centralized hub for discovering, testing, and…
Search enterprise data assets using LLMs backed by knowledge graphs
In this post, we present a generative AI-powered semantic search solution that empowers business users to quickly and accurately find relevant data assets across various enterprise data sources. In this…
Build a read-through semantic cache with Amazon OpenSearch Serverless and Amazon Bedrock
This post presents a strategy for optimizing LLM-based applications. Given the increasing need for efficient and cost-effective AI solutions, we present a serverless read-through caching blueprint that uses repeated data…
Enhance speech synthesis and video generation models with RLHF using audio and video segmentation in Amazon SageMaker
In this post, we show you how to implement an audio and video segmentation solution using SageMaker Ground Truth. We guide you through deploying the necessary infrastructure using AWS CloudFormation,…
Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications
In this post, we introduce the core dimensions of responsible AI and explore considerations and strategies on how to address these dimensions for Amazon Bedrock applications.
From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 2
This post focuses on doing RAG on heterogeneous data formats. We first introduce routers, and how they can help managing diverse data sources. We then give tips on how to…
Amazon Bedrock Prompt Management is now available in GA
Today we are announcing the general availability of Amazon Bedrock Prompt Management, with new features that provide enhanced options for configuring your prompts and enabling seamless integration for invoking them…