Category: Intermediate (200)

This post is designed for Kubernetes cluster administrators and ML scientists, providing an overview of the key features that SageMaker HyperPod introduces to facilitate large-scale model training on an EKS cluster.

In this post, we aim to provide business leaders with a non-technical overview of purpose-built accelerators (PBAs) and their role within the financial services industry (FSI).

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.

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.

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.

In this post, we delve into the process of building and deploying a sample application capable of generating multilingual descriptions for multiple images with a Streamlit UI, AWS Lambda powered with the Amazon Bedrock SDK, and AWS AppSync driven by the open source Generative AI CDK Constructs.

In this post, we show you how to perform natural language queries over the indexed GitHub (Cloud) data using the AI-powered chat interface provided by Amazon Q Business. We also cover how Amazon Q Business applies access control lists (ACLs) associated with the indexed documents to provide permissions-filtered responses.

In this post, we demonstrate how to seamlessly automate the deployment of an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and the AWS Cloud Development Kit (AWS CDK), enabling organizations to quickly set up a powerful question answering system.

In this post, we demonstrate how to create an Amazon Q Business application and index website contents using the Amazon Q Web Crawler connector for Amazon Q Business. We use two data sources (websites) here. The first data source is an employee onboarding guide from a fictitious company, which requires basic authentication. We demonstrate how to set up authentication for the Web Crawler. The second data source is the official documentation for Amazon Q Business. For this data source, we demonstrate how to apply advanced settings to instruct the Web Crawler to crawl only pages and links related to Amazon Q Business.

In this post, we will harness the power of generative artificial intelligence (AI) and Amazon Bedrock to help organizations simplify and effectively manage remediations of AWS Security Hub control findings.