Tag: AI/ML

This post discusses the adoption and evaluation of HAQM Nova foundation models by Trellix, a leading company delivering cybersecurity’s broadest AI-powered platform to over 53,000 customers worldwide.

By leveraging the generative AI capabilities and tooling of HAQM Bedrock, you can create an intelligent nerve center that connects diverse data sources, converts data into actionable insights, and creates a comprehensive plan to mitigate supply chain risks. This post walks through how HAQM Bedrock Flows connects your business systems, monitors medical device shortages, and provides mitigation strategies based on knowledge from HAQM Bedrock Knowledge Bases or data stored in HAQM S3 directly. You’ll learn how to create a system that stays ahead of supply chain risks.

In this post, we review how Aetion’s Smart Subgroups Interpreter enables users to interact with Smart Subgroups using natural language queries. Powered by HAQM Bedrock and Anthropic’s Claude 3 large language models (LLMs), the interpreter responds to user questions expressed in conversational language about patient subgroups and provides insights to generate further hypotheses and evidence.

Accurately converting free text inputs into structured data is crucial for applications that involve data management and user interaction. In this post, we introduce a real business use case from Cato Networks that significantly improved user experience. By using HAQM Bedrock, we gained access to state-of-the-art generative language models with built-in support for JSON schemas and structured data.

In this post, we show how to extend HAQM Bedrock Agents to hybrid and edge services such as AWS Outposts and AWS Local Zones to build distributed Retrieval Augmented Generation (RAG) applications with on-premises data for improved model outcomes. With Outposts, we also cover a reference pattern for a fully local RAG application that requires both the foundation model (FM) and data sources to reside on premises.

This post provides step-by-step instructions for creating a collaborative multi-agent framework with reasoning capabilities to decouple business applications from FMs. It demonstrates how to combine HAQM Bedrock Agents with open source multi-agent frameworks, enabling collaborations and reasoning among agents to dynamically execute various tasks. The exercise will guide you through the process of building a reasoning orchestration system using HAQM Bedrock, HAQM Bedrock Knowledge Bases, HAQM Bedrock Agents, and FMs. We also explore the integration of HAQM Bedrock Agents with open source orchestration frameworks LangGraph and CrewAI for dispatching and reasoning.

In this post, we discuss how HAQM SageMaker and Tecton work together to simplify the development and deployment of production-ready AI applications, particularly for real-time use cases like fraud detection. The integration enables faster time to value by abstracting away complex engineering tasks, allowing teams to focus on building features and use cases while providing a streamlined framework for both offline training and online serving of ML models.

In this post, we demonstrate how the HAQM SageMaker model parallel library (SMP) addresses this need through support for new features such as 8-bit floating point (FP8) mixed-precision training for accelerated training performance and context parallelism for processing large input sequence lengths, expanding the list of its existing features.

This post demonstrates how to use HAQM Bedrock Agents, HAQM Knowledge Bases, and the RAGAS evaluation metrics to build a custom hallucination detector and remediate it by using human-in-the-loop. The agentic workflow can be extended to custom use cases through different hallucination remediation techniques and offers the flexibility to detect and mitigate hallucinations using custom actions.

In this post, we explore how to integrate HAQM Q Business with SharePoint Online using the OAuth 2.0 ROPC flow authentication method. We provide both manual and automated approaches using PowerShell scripts for configuring the required Azure AD settings. Additionally, we demonstrate how to enter those details along with your SharePoint authentication credentials into the HAQM Q console to finalize the secure connection.