AWS Machine Learning Blog
Set up a custom plugin on Amazon Q Business and au...
In this post, we demonstrate how to build a custom plugin with Amazon Q Business for backend integration. This plugin can integrate existing systems, including third-party systems, with little to no development in just weeks and automate critical workflows....
Detect hallucinations for RAG-based systems
This post walks you through how to create a basic hallucination detection system for RAG-based applications. We also weigh the pros and cons of different methods in terms of accuracy, precision, recall, and cost.
AWS machine learning supports Scuderia Ferrari HP ...
Pit crews are trained to operate at optimum efficiency, although measuring their performance has been challenging, until now. In this post, we share how Amazon Web Services (AWS) is helping Scuderia Ferrari HP develop more accurate pit stop analysis...
Accelerate edge AI development with SiMa.ai Edgema...
In this post, we demonstrate how to retrain and quantize a model using SageMaker AI and the SiMa.ai Palette software suite. The goal is to accurately detect individuals in environments where visibility and protective equipment detection are essential for...
How Apoidea Group enhances visual information extr...
Building on this foundation of specialized information extraction solutions and using the capabilities of SageMaker HyperPod, we collaborate with APOIDEA Group to explore the use of large vision language models (LVLMs) to further improve table structure recognition performance on...
How Qualtrics built Socrates: An AI platform power...
In this post, we share how Qualtrics built an AI platform powered by Amazon SageMaker and Amazon Bedrock.
Vxceed secures transport operations with Amazon Be...
AWS partnered with Vxceed to support their AI strategy, resulting in the development of LimoConnect Q, an innovative ground transportation management solution. Using AWS services including Amazon Bedrock and Lambda, Vxceed successfully built a secure, AI-powered solution that streamlines...
Cost-effective AI image generation with PixArt-Σ i...
This post is the first in a series where we will run multiple diffusion transformers on Trainium and Inferentia-powered instances. In this post, we show how you can deploy PixArt-Sigma to Trainium and Inferentia-powered instances.
Cost-effective AI image generation with PixArt-Sig...
This post is the first in a series where we will run multiple diffusion transformers on Trainium and Inferentia-powered instances. In this post, we show how you can deploy PixArt-Sigma to Trainium and Inferentia-powered instances.
Customize DeepSeek-R1 671b model using Amazon Sage...
In this post, we use the recipes to fine-tune the original DeepSeek-R1 671b parameter model. We demonstrate this through the step-by-step implementation of these recipes using both SageMaker training jobs and SageMaker HyperPod.
Build a financial research assistant using Amazon ...
In this post, we show you how Amazon Q Business can help augment your generative AI needs in all the abovementioned use cases and more by answering questions, providing summaries, generating content, and securely completing tasks based on data...
Securing Amazon Bedrock Agents: A guide to safegua...
Generative AI tools have transformed how we work, create, and process information. At Amazon Web Services (AWS), security is our top priority. Therefore, Amazon Bedrock provides comprehensive security controls and best practices to help protect your applications and data....
Build scalable containerized RAG based generative ...
In this post, we demonstrate a solution using Amazon Elastic Kubernetes Service (EKS) with Amazon Bedrock to build scalable and containerized RAG solutions for your generative AI applications on AWS while bringing your unstructured user file data to Amazon...
How Hexagon built an AI assistant using AWS genera...
Recognizing the transformative benefits of generative AI for enterprises, we at Hexagon’s Asset Lifecycle Intelligence division sought to enhance how users interact with our Enterprise Asset Management (EAM) products. Understanding these advantages, we partnered with AWS to embark on...
Build an intelligent community agent to revolution...
In this post, we demonstrate how your organization can reduce the end-to-end burden of resolving regular challenges experienced by your IT support teams—from understanding errors and reviewing diagnoses, remediation steps, and relevant documentation, to opening external support tickets using...
Elevate marketing intelligence with Amazon Bedrock...
In the media and entertainment industry, understanding and predicting the effectiveness of marketing campaigns is crucial for success. Marketing campaigns are the driving force behind successful businesses, playing a pivotal role in attracting new customers, retaining existing ones, and...
How Deutsche Bahn redefines forecasting using Chro...
Whereas traditional forecasting methods typically rely on statistical modeling, Chronos treats time series data as a language to be modeled and uses a pre-trained FM to generate forecasts — similar to how large language models (LLMs) generate texts. Chronos...
Use custom metrics to evaluate your generative AI ...
Now with Amazon Bedrock, you can develop custom evaluation metrics for both model and RAG evaluations. This capability extends the LLM-as-a-judge framework that drives Amazon Bedrock Evaluations. In this post, we demonstrate how to use custom metrics in Amazon...