Category: Generative AI

In this post, we walk you through configuring and integrating Amazon Q for Business with Aurora PostgreSQL-Compatible to enable your database administrators, data analysts, application developers, leadership, and other teams to quickly get accurate answers to their questions related to the content stored in Aurora PostgreSQL databases.

In this post, we illustrate the importance of generative AI in the collaboration between Tealium and the AWS Generative AI Innovation Center (GenAIIC) team by automating the following: 1/ Evaluating the retriever and the generated answer of a RAG system based on the Ragas Repository powered by Amazon Bedrock, 2/ Generating improved instructions for each question-and-answer pair using an automatic prompt engineering technique based on the Auto-Instruct Repository. An instruction refers to a general direction or command given to the model to guide generation of a response. These instructions were generated using Anthropic’s Claude on Amazon Bedrock, and 4/ Providing a UI for a human-based feedback mechanism that complements an evaluation system powered by Amazon Bedrock.

In this post, we illustrate how EBSCOlearning partnered with AWS Generative AI Innovation Center (GenAIIC) to use the power of generative AI in revolutionizing their learning assessment process. We explore the challenges faced in traditional question-answer (QA) generation and the innovative AI-driven solution developed to address them.

Amazon Q Business is a generative AI-powered assistant that enhances employee productivity by solving problems, generating content, and providing insights across enterprise data sources. Beyond searching indexed third-party services, employees need access to dynamic, near real-time data such as stock prices, vacation balances, and location tracking, which is made possible through Amazon Q Business plugins. […]

Today, we are excited to announce that Mistral-NeMo-Base-2407 and Mistral-NeMo-Instruct-2407 large language models from Mistral AI that excel at text generation, are available for customers through Amazon SageMaker JumpStart. In this post, we walk through how to discover, deploy and use the Mistral-NeMo-Instruct-2407 and Mistral-NeMo-Base-2407 models for a variety of real-world use cases.

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 implementing foundation models (FMs). In this post, we discuss the advantages and capabilities of Amazon Bedrock Marketplace and Nemotron models, and how to get started.

In this post, we explore how to deploy AI models from SageMaker JumpStart and use them with Amazon Bedrock’s powerful features. Users can combine SageMaker JumpStart’s model hosting with Bedrock’s security and monitoring tools. We demonstrate this using the Gemma 2 9B Instruct model as an example, showing how to deploy it and use Bedrock’s advanced capabilities.

This post introduces the workflow of Amazon Bedrock Model Distillation. We first introduce the general concept of model distillation in Amazon Bedrock, and then focus on the important steps in model distillation, including setting up permissions, selecting the models, providing input dataset, commencing the model distillation jobs, and conducting evaluation and deployment of the student models after model distillation.

In this post, we’ll show how anyone in your company can use Amazon Bedrock in SageMaker Unified Studio to quickly create a generative AI chat agent application that analyzes sales performance data. Through simple conversations, business teams can use the chat agent to extract valuable insights from both structured and unstructured data sources without writing code or managing complex data pipelines.

Amazon has introduced the Amazon Kendra GenAI Index, a new offering designed to enhance semantic search and retrieval capabilities for enterprise AI applications. This index is optimized for Retrieval Augmented Generation (RAG) and intelligent search, allowing businesses to build more effective digital assistants and search experiences.