Category: Generative AI

In this post, we discuss Bria’s family of models, explain the Amazon SageMaker platform, and walk through how to discover, deploy, and run inference on a Bria 2.3 model using SageMaker JumpStart.

In this post, we demonstrate how to design fine-grained access controls using Verified Permissions for a generative AI application that uses Amazon Bedrock Agents to answer questions about insurance claims that exist in a claims review system using textual prompts as inputs and outputs.

In this post, we show you how to create an AI-powered, event-driven operations assistant that automatically responds to operational events. The assistant can filter out irrelevant events (based on your organization’s policies), recommend actions, create and manage issue tickets in integrated IT service management (ITSM) tools to track actions, and query knowledge bases for insights related to operational events.

Amazon Q Business recently added support for administrators to modify the default access control list (ACL) crawling feature for data source connectors. Amazon Q Business is a fully managed, AI powered assistant with enterprise-grade security and privacy features. It includes over 40 data source connectors that crawl and index documents. By default, Amazon Q Business […]

In this post, we share how SKT customizes Anthropic Claude models for telco-specific Q&A regarding technical telecommunication documents of SKT using Amazon Bedrock.

In this post, we will demonstrate how to set up Slack connector for Amazon Q Business to sync communications from both public and private channels, reflective of user permissions.

In this post, we collaborate with the team working on PyTorch at Meta to showcase how the torchtitan library accelerates and simplifies the pre-training of Meta Llama 3-like model architectures. We showcase the key features and capabilities of torchtitan such as FSDP2, torch.compile integration, and FP8 support that optimize the training efficiency.

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.