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4 ways generative AI addresses manufacturing challenges

IBM Big Data Hub

Facing a constant onslaught of cost pressures, supply chain volatility and disruptive technologies like 3D printing and IoT. Contextual data understanding Data systems often cause major problems in manufacturing firms. The manufacturing industry is in an unenviable position.

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Achieving Trusted AI in Manufacturing

Cloudera

Here are some of the key use cases: Predictive maintenance: With time series data (sensor data) coming from the equipment, historical maintenance logs, and other contextual data, you can predict how the equipment will behave and when the equipment or a component will fail. Eliminate data silos.

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Building an Open Data Processing Pipeline for IoT

Cloudera

Last week Cloudera introduced an open end-to-end architecture for IoT and the different components needed to help satisfy today’s enterprise needs regarding operational technology (OT), information technology (IT), data analytics and machine learning (ML), along with modern and traditional application development, deployment, and integration.

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Cropin’s agriculture industry cloud to provide apps, data frameworks

CIO Business Intelligence

The second layer, Data Hub, can ingest data from a variety of sources including on-farm devices, drones, IoT devices and satellites. Agriculture businesses and farmers can use the hub to access structured and contextualized data from various sources for correlation and analysis at scale, the company said.

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BRIDGEi2i Newsletter: July 2021 Recap

bridgei2i

The emergence of IoT, cloud computing, and big data analytics combined with AI tech has brought enterprises to a tipping point in their journey towards making AI real. View All Recognitions. AI For Digital Enterprises – Thought Leadership. Back to News Page. www.BRIDGEi2i.com.