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The Future of Machine Learning in Cybersecurity

CIO

Machine learning (ML) is a commonly used term across nearly every sector of IT today. This article will share reasons why ML has risen to such importance in cybersecurity, share some of the challenges of this particular application of the technology and describe the future that machine learning enables.

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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 Synergy of IoT and Machine Learning: Unlocking the Potential of Connected Devices

InfoBest

In an era reminiscent of science fiction, two groundbreaking technologies have emerged, poised to reshape our world: the Internet of Things (IoT) and Machine Learning. Enhancing Data Collection and Analysis One of the primary advantages of IoT is its ability to generate vast amounts of real-time data from various sources.

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Predictive analytics helps Fresenius anticipate dialysis complications

CIO

German healthcare company Fresenius Medical Care, which specializes in providing kidney dialysis services, is using a combination of near real-time IoT data and clinical data to predict one of the most common complications of the procedure.

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What is the Role of AI in the Manufacturing Industry?

OTS Solutions

This article aims to provide the role of AI in the manufacturing industry, highlighting the key areas where AI is making a substantial impact and discussing the challenges and prospects associated with its implementation. How AI is Transforming the Manufacturing Industry 1. What are the Benefits of using AI in Manufacturing?

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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly Media - Ideas

In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. As interest in machine learning (ML) and AI grow, organizations are realizing that model building is but one aspect they need to plan for.

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The AI continuum

CIO

Generative AI and large language models (LLMs) like ChatGPT are only one aspect of AI. Downsides: Not generative; model behavior can be a black box; results can be challenging to explain. Don’t use generative AI for a problem that classical machine learning has already solved.