Category: Technical How-to

In this post, we show how you can integrate Amazon Lex with Amazon Bedrock Knowledge Bases and ServiceNow to provide 24/7 automated support and self-service options.

In this post, we show you how Kyndryl integrated Amazon Q Business with ServiceNow in a few simple steps. You will learn how to configure Amazon Q Business and ServiceNow, how to create a generative AI plugin for your ServiceNow incidents, and how to test and interact with ServiceNow using the Amazon Q Business web experience. This post will help you enhance your ServiceNow experience with Amazon Q Business and enjoy the benefits of a generative AI–powered interface.

In this post, we show how you can use our enterprise graph machine learning (GML) framework GraphStorm to solve prediction challenges on large-scale complex networks inspired by our practices of exploring GML to mitigate the AWS backbone network congestion risk.

As organizations navigate the complexities of the digital realm, generative AI has emerged as a transformative force, empowering enterprises to enhance productivity, streamline workflows, and drive innovation. To maximize the value of insights generated by generative AI, it is crucial to provide simple ways for users to preserve and share these insights using commonly used tools such as email. This post explores how you can integrate Amazon Q Business with Amazon SES to email conversations to specified email addresses.

Generative AI applications should be developed with adequate controls for steering the behavior of FMs. Responsible AI considerations such as privacy, security, safety, controllability, fairness, explainability, transparency and governance help ensure that AI systems are trustworthy. In this post, we demonstrate how to use the AWS generative AI best practices framework on AWS Audit Manager to evaluate this insurance claim agent from a responsible AI lens.

In this blog post, we explore a client services agent assistant application developed by the London Stock Exchange Group (LSEG) using Amazon Q Business. We will discuss how Amazon Q Business saved time in generating answers, including summarizing documents, retrieving answers to complex Member enquiries, and combining information from different data sources (while providing in-text citations to the data sources used for each answer).

In this post, we walk you through the process to build an automated mechanism using Amazon SageMaker to process your log data, run training iterations over it to obtain the best-performing anomaly detection model, and register it with the Amazon SageMaker Model Registry for your customers to use it.

In this blog post, we showcase how you can perform efficient supervised fine tuning for a Meta Llama 3 model using PEFT on AWS Trainium with SageMaker HyperPod. We use HuggingFace’s Optimum-Neuron software development kit (SDK) to apply LoRA to fine-tuning jobs, and use SageMaker HyperPod as the primary compute cluster to perform distributed training on Trainium. Using LoRA supervised fine-tuning for Meta Llama 3 models, you can further reduce your cost to fine tune models by up to 50% and reduce the training time by 70%.

TUI Group is one of the world’s leading global tourism services, providing 21 million customers with an unmatched holiday experience in 180 regions. The TUI content teams are tasked with producing high-quality content for its websites, including product details, hotel information, and travel guides, often using descriptions written by hotel and third-party partners. In this post, we discuss how we used Amazon SageMaker and Amazon Bedrock to build a content generator that rewrites marketing content following specific brand and style guidelines.

Organizations are continuously seeking ways to use their proprietary knowledge and domain expertise to gain a competitive edge. With the advent of foundation models (FMs) and their remarkable natural language processing capabilities, a new opportunity has emerged to unlock the value of their data assets. As organizations strive to deliver personalized experiences to customers using […]