Category: Generative AI

In this post, we describe the development of a generative AI Slack application powered by Amazon Bedrock and Amazon Kendra. This is designed to be an internal-facing Slack chat assistant that helps answer questions related to the indexed content.

In this post, we implement a fashion assistant agent using Amazon Bedrock Agents and the Amazon Titan family models. The fashion assistant provides a personalized, multimodal conversational experience.

In this post, we discuss how you can use the ApplyGuardrail API in common generative AI architectures such as third-party or self-hosted large language models (LLMs), or in a self-managed Retrieval Augmented Generation (RAG) architecture.

In this post, we show how the team at Schneider collaborated with the AWS Generative AI Innovation Center (GenAIIC) to build a generative AI solution on Amazon Bedrock to solve this problem. The solution processes and evaluates each requests for proposal (RFP) and then routes high-value RFPs to the microgrid subject matter expert (SME) for approval and recommendation.

In this post, we discuss scaling up generative AI for different lines of businesses (LOBs) and address the challenges that come around legal, compliance, operational complexities, data privacy and security.

In this post, we explore how Amazon Q Business uses personalization to improve the relevance of responses and how you can align your use cases and end-user data to take full advantage of this capability

AWS has been recognized as a Leader in the 2024 Gartner Magic Quadrant for Data Science and Machine Learning Platforms. The post highlights how AWS’s continued innovations in services like Amazon Bedrock and Amazon SageMaker have enabled organizations to unlock the transformative potential of generative AI.

In this post, we presented how to create a fully serverless voice-based contextual chatbot using Amazon Bedrock with Anthropic Claude.

In this post, we provide a step-by-step approach of fine-tuning a Mistral model using SageMaker and import it into Amazon Bedrock using the Custom Import Model feature.

In this blog post, we will show you how to leverage AI21 Labs’ Task-Specific Models (TSMs) on AWS to enhance your business operations. You will learn the steps to subscribe to AI21 Labs in the AWS Marketplace, set up a domain in Amazon SageMaker, and utilize AI21 TSMs via SageMaker JumpStart.