AWS Machine Learning Blog

In this post, we demonstrate how to create an HAQM Q Business application and index website contents using the HAQM Q Web Crawler connector for HAQM 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 HAQM 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 HAQM Q Business.

Today, we are happy to announce the general availability of cross-region inference, a powerful feature allowing automatic cross-region inference routing for requests coming to HAQM Bedrock. This offers developers using on-demand inference mode, a seamless solution for managing optimal availability, performance, and resiliency while managing incoming traffic spikes of applications powered by HAQM Bedrock. By opting in, developers no longer have to spend time and effort predicting demand fluctuations.

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

In this post, we discuss existing prompt-level threats and outline several security guardrails for mitigating prompt-level threats. For our example, we work with Anthropic Claude on HAQM Bedrock, implementing prompt templates that allow us to enforce guardrails against common security threats such as prompt injection. These templates are compatible with and can be modified for other LLMs.

In this post, we introduce the new HAQM Titan Text Premier model, specifically optimized for enterprise use cases, such as building Retrieval Augmented Generation (RAG) and agent-based applications. Such integrations enable advanced applications like building interactive AI assistants that use enterprise APIs and interact with your propriety documents.

In this post, we dive into the architecture and implementation details of GenASL, which uses AWS generative AI capabilities to create human-like ASL avatar videos. GenASL is a solution that translates speech or text into expressive ASL avatar animations, bridging the gap between spoken and written language and sign language.

Through this series of posts, we share our generative AI journey and use cases, detailing the architecture, AWS services used, lessons learned, and the impact of these solutions on our teams and customers. In this first post, we explore Account Summaries, one of our initial production use cases built on HAQM Bedrock. Account Summaries equips our teams to be better prepared for customer engagements. It combines information from various sources into comprehensive, on-demand summaries available in our CRM or proactively delivered based on upcoming meetings. From the period of September 2023 to March 2024, sellers leveraging GenAI Account Summaries saw a 4.9% increase in value of opportunities created.

HAQM Q Business is a conversational assistant powered by generative artificial intelligence (AI) that enhances workforce productivity by answering questions and completing tasks based on information in your enterprise systems, which each user is authorized to access. In an earlier post, we discussed how you can build private and secure enterprise generative AI applications with HAQM Q Business and AWS IAM Identity Center. If you want to use HAQM Q Business to build enterprise generative AI applications, and have yet to adopt organization-wide use of AWS IAM Identity Center, you can use HAQM Q Business IAM Federation to directly manage user access to HAQM Q Business applications from your enterprise identity provider (IdP), such as Okta or Ping Identity. HAQM Q Business IAM Federation uses Federation with IAM and doesn’t require the use of IAM Identity Center. This post shows how you can use HAQM Q Business IAM Federation for user access management of your HAQM Q Business applications.

In this post, we describe the development of the automated summary feature in Verisk’s Discovery Navigator incorporating generative AI, the data, the architecture, and the evaluation of the pipeline. This new functionality offers an immediate overview of the initial injury and current medical status, empowering record reviewers of all skill levels to quickly assess injury severity with the click of a button.

In this post, we provide an overview of HAQM Q Business Confluence Cloud connector and how you can use it for seamless integration of generative AI assistance to your Confluence Cloud.