Agentic AI represents a fundamental shift in how artificial intelligence operates within industrial environments, moving from passive prediction to autonomous decision-making and action. In this IIoT World explainer, we break down what agentic AI actually means for manufacturers, process engineers, and operations leaders. You will learn how autonomous AI agents differ from traditional machine learning […]
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Digitalization has brought about a radical shift in the world of urban planning. Thanks to the data now available, planners have evidence of user activity that allows them to transition from an “I think” position to an “I know” position. This data and research underpins the decisions urban planners make, empowering them to truly put […]
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Data science in industrial engineering is the application of statistical modeling, machine learning, and computational analysis to the physical systems, processes, and assets that make up modern industry. At IIoTWorld, we cover the intersection of data-driven methods and operational technology because it is here, where algorithms meet the factory floor, that the most consequential productivity […]
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“Having spent, over a decade building machine learning and A.I solutions for E.ON we realized that there is clearly a gap in the technology currently on the market.” TY Burridge-Oakland This gap is the real time machine learning analysis of multi-year data. Seems obvious but due to limitations of data indexing, bandwidth, and internet speeds, […]
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Most organizations lack a methodology for determining the economic value of their data and analytics. But Data and Analytics are unique economic assets that not only never wear out, but they actually can appreciate, not depreciate, in value the more valuable they are used. Learn how your organization can embrace a systematic approach to build out your […]
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Sooner or later the data science jargon and marketing hype is going to subside, and manufacturing companies, among many other sectors, are going to find themselves sitting with broken promises. It is therefore important that these organizations understand clearly how they stand to benefit from and be empowered by data science and the challenges thereof. […]
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