Acoustic anomaly detection using Amazon Lookout for Equipment

As the modern factory becomes more connected, manufacturers are increasingly using a range of inputs (such as process data, audio, and visual) to increase their operational efficiency. Companies use this information to monitor equipment performance and anticipate failures using predictive maintenance techniques powered by machine learning (ML) and artificial intelligence

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Shared by AWS Machine Learning April 10, 2021

Detect abnormal equipment behavior and review predictions using Amazon Lookout for Equipment and Amazon A2I

Companies that operate and maintain a broad range of industrial machinery such as generators, compressors, and turbines are constantly working to improve operational efficiency and avoid unplanned downtime due to component failure. They invest heavily in physical sensors (tags), data connectivity, data storage, and data visualization to monitor the condition

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Shared by AWS Machine Learning April 10, 2021

How to map the knowledge "sticking points"

Knowledge transfer often requires several steps, and knowledge can get stuck along the way. But where are those sticky points? I have often used the analogy of a Supply Chain when looking at knowledge transfer, with knowledge as a resource to be supplied to the knowledge workers on whose decisions

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Shared by Nick Milton April 6, 2021

Join AWS at NVIDIA GTC 21, April 12–16

Starting Monday, April 12, 2021, the NVIDIA GPU Technology Conference (GTC) is offering online sessions for you to learn AWS best practices to accomplish your machine learning (ML), virtual workstations, high performance computing (HPC), and Internet of Things (IoT) goals faster and more easily. Amazon Elastic Compute Cloud (Amazon EC2)

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Shared by AWS Machine Learning April 6, 2021