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Innovative data integration in 2024: Pioneering the future of data integration

CIO

Of late, innovative data integration tools are revolutionising how organisations approach data management, unlocking new opportunities for growth, efficiency, and strategic decision-making by leveraging technical advancements in Artificial Intelligence, Machine Learning, and Natural Language Processing.

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P&G enlists IoT, predictive analytics to perfect Pampers diapers

CIO

Hot Melt Optimization employs a proprietary data collection method using proprietary sensors on the assembly line, which, when combined with Microsoft’s predictive analytics and Azure cloud for manufacturing, enables P&G to produce perfect diapers by reducing loss due to damage during the manufacturing process.

IoT 246
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Review of Industrial IoT Solutions – Part I

Perficient

It would take way too long to do a comprehensive review of all available solutions, so in this first part, I’m just going to focus on AWS, Azure – as the leading cloud providers – as well as hybrid-cloud approaches using Kubernetes. Configuration can also be pushed backed to the sites post-analysis. Data Collection.

IoT 69
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10 Key Trends of Digital Transformation in Healthcare in 2022

OTS Solutions

Clinics that use cutting-edge technology will continue to thrive as intelligent systems evolve. At the heart of this shift are AI (Artificial Intelligence), ML (Machine Learning), IoT, and other cloud-based technologies. The intelligence generated via Machine Learning. IoMT and wearable technology.

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MLOps: Methods and Tools of DevOps for Machine Learning

Altexsoft

When speaking of machine learning, we typically discuss data preparation or model building. The fusion of terms “machine learning” and “operations”, MLOps is a set of methods to automate the lifecycle of machine learning algorithms in production — from initial model training to deployment to retraining against new data.

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

OTS Solutions

Predictive maintenance utilizes real-time monitoring and analysis of equipment data to forecast potential equipment failures and take corrective action to prevent downtime. These technologies allow mobile apps to learn and adapt to specific equipment conditions, further reducing the risk of equipment failures. Industry 4.0 Industry 4.0

Mobile 130
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Generative AI is pushing unstructured data to center stage

CIO

For example, generative AI models are especially adept at making sense of diverse, unstructured datasets to create realistic content, enhance data for machine learning training, simulate and model complex scenarios and environments, and personalize algorithms for targeted marketing and product recommendations.