AI

Delight your customers with great conversational experiences via QnABot, a generative AI chatbot

QnABot on AWS (an AWS Solution) now provides access to Amazon Bedrock foundational models (FMs) and Knowledge Bases for Amazon Bedrock, a fully managed end-to-end Retrieval Augmented Generation (RAG) workflow. You can now provide contextual information from your private data sources that can be used to create rich, contextual, conversational experiences. The advent of generative

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Introducing document-level sync reports: Enhanced data sync visibility in Amazon Q Business

Amazon Q Business is a fully managed, generative artificial intelligence (AI)-powered assistant that helps enterprises unlock the value of their data and knowledge. With Amazon Q, you can quickly find answers to questions, generate summaries and content, and complete tasks by using the information and expertise stored across your company’s various data sources and enterprise

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LLMs develop their own understanding of reality as their language abilities improve

Ask a large language model (LLM) like GPT-4 to smell a rain-soaked campsite, and it’ll politely decline. Ask the same system to describe that scent to you, and it’ll wax poetic about “an air thick with anticipation” and “a scent that is both fresh and earthy,” despite having neither prior experience with rain nor a

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Derive generative AI-powered insights from ServiceNow with Amazon Q Business

Effective customer support, project management, and knowledge management are critical aspects of providing efficient customer relationship management. ServiceNow is a platform for incident tracking, knowledge management, and project management functions for software projects and has become an indispensable part of many organizations’ workflows to ensure success of the customer and the product. However, extracting valuable

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MIT researchers use large language models to flag problems in complex systems

Identifying one faulty turbine in a wind farm, which can involve looking at hundreds of signals and millions of data points, is akin to finding a needle in a haystack. Engineers often streamline this complex problem using deep-learning models that can detect anomalies in measurements taken repeatedly over time by each turbine, known as time-series

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