AWS Machine Learning Blog
Category: Generative AI
Generative AI-powered technology operations
In this post we describe how AWS generative AI solutions (including Amazon Bedrock, Amazon Q Developer, and Amazon Q Business) can further enhance TechOps productivity, reduce time to resolve issues, enhance customer experience, standardize operating procedures, and augment knowledge bases.
Enabling complex generative AI applications with Amazon Bedrock Agents
In this post, we take a closer look at Amazon Bedrock Agents. They empower you to build intelligent and context-aware generative AI applications, streamlining complex workflows and delivering natural, conversational user experiences.
Align Meta Llama 3 to human preferences with DPO, Amazon SageMaker Studio, and Amazon SageMaker Ground Truth
In this post, we show you how to enhance the performance of Meta Llama 3 8B Instruct by fine-tuning it using direct preference optimization (DPO) on data collected with SageMaker Ground Truth.
Exploring data using AI chat at Domo with Amazon Bedrock
In this post, we share how Domo, a cloud-centered data experiences innovator is using Amazon Bedrock to provide a flexible and powerful AI solution.
How Vidmob is using generative AI to transform its creative data landscape
In this post, we illustrate how Vidmob, a creative data company, worked with the AWS Generative AI Innovation Center (GenAIIC) team to uncover meaningful insights at scale within creative data using Amazon Bedrock.
Ground truth curation and metric interpretation best practices for evaluating generative AI question answering using FMEval
In this post, we discuss best practices for working with Foundation Model Evaluations Library (FMEval) in ground truth curation and metric interpretation for evaluating question answering applications for factual knowledge and quality.
Build powerful RAG pipelines with LlamaIndex and Amazon Bedrock
In this post, we show you how to use LlamaIndex with Amazon Bedrock to build robust and sophisticated RAG pipelines that unlock the full potential of LLMs for knowledge-intensive tasks.
Evaluating prompts at scale with Prompt Management and Prompt Flows for Amazon Bedrock
In this post, we demonstrate how to implement an automated prompt evaluation system using Amazon Bedrock so you can streamline your prompt development process and improve the overall quality of your AI-generated content.
Effectively manage foundation models for generative AI applications with Amazon SageMaker Model Registry
In this post, we explore the new features of Model Registry that streamline foundation model (FM) management: you can now register unzipped model artifacts and pass an End User License Agreement (EULA) acceptance flag without needing users to intervene.
Build an ecommerce product recommendation chatbot with Amazon Bedrock Agents
In this post, we show you how to build an ecommerce product recommendation chatbot using Amazon Bedrock Agents and foundation models (FMs) available in Amazon Bedrock.