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Machine Learning In Internet Of Things (IoT) – The next big IT revolution in the making

Openxcell

From human genome mapping to Big Data Analytics, Artificial Intelligence (AI),Machine Learning, Blockchain, Mobile digital Platforms (Digital Streets, towns and villages),Social Networks and Business, Virtual reality and so much more. What is IoT or Internet of Things? What is Machine Learning?

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The impact of AI on edge computing

CIO

AI, including Generative AI (GenAI), has emerged as a transformative technology, revolutionizing how machines learn, create, and adapt. Edge storage solutions: AI-generated content—such as images, videos, or sensor data—requires reliable and scalable storage. over the 2023-2027 forecast period 1.

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How Industry 4.0 Changes Predictive Maintenance From Mobile Apps And What It Means For The Future ?

OTS Solutions

Emerging Technologies in Mobile Apps for Predictive Maintenance Emerging technologies such as artificial intelligence and machine learning are being integrated into predictive maintenance mobile apps to improve their effectiveness. IoT devices can be used to collect performance data from equipment and machinery.

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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. Therefore, the majority of machine learning/deep learning frameworks focus on Python APIs.

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Unlocking the Power of AI with a Real-Time Data Strategy

CIO

Titanium Intelligent Solutions, a global SaaS IoT organization, even saved one customer over 15% in energy costs across 50 distribution centers , thanks in large part to AI. AI is the perception, synthesis, and inference of information by machines, to accomplish tasks that historically have required human intelligence.

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Prioritizing AI? Don’t shortchange IT fundamentals

CIO

As the cost of data storage has fallen, many organizations are keeping unnecessary data, or cleaning up data that’s out of date or no longer useful after a migration or reorganization. All of these additional machines, workloads, and services require trusted identities, which is amplifying the need for machine identity management.”

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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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