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AI and generative AI are revolutionizing manufacturing…here’s how

CIO Business Intelligence

AI can help with all of these challenges via manufacturing-specific use cases that benefit manufacturers, their employees, and their customers. Process optimization In manufacturing, process optimization that maximizes quality, efficiency, and cost-savings is an ever-present goal. Here’s how. Artificial Intelligence

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3 key digital transformation priorities for 2024

CIO Business Intelligence

After all, every department is pressured to drive efficiencies and is clamoring for automation, data capabilities, and improvements in employee experiences, some of which could be addressed with generative AI. Meanwhile, CIOs must still reduce technical debt, modernize applications, and get cloud costs under control.

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Scaling AI? First—get your data storage right

CIO Business Intelligence

Artificial intelligence (AI) is the analytics vehicle that extracts data’s tremendous value and translates it into actionable, usable insights. In my role at Dell Technologies, I strive to help organizations advance the use of data, especially unstructured data, by democratizing the at-scale deployment of artificial intelligence (AI).

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7 Enterprise Applications for Companies Using Cloud Technology

Smart Data Collective

The sudden growth is not surprising, because the benefits of the cloud are incredible. Cloud technology results in lower costs, quicker service delivery, and faster network data streaming. It also allows companies to offload large amounts of data from their networks by hosting it on remote servers anywhere on the globe.

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Generative AI’s potential as a force multiplier in defense

CIO Business Intelligence

First, there is the need to properly handle the critical data that fuels defense decisions and enables data-driven generative AI. Organizations need novel storage capabilities to handle the massive, real-time, unstructured data required to build, train and use generative AI.

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Belcorp reimagines R&D with AI

CIO Business Intelligence

As Belcorp considered the difficulties it faced, the R&D division noted it could significantly expedite time-to-market and increase productivity in its product development process if it could shorten the timeframes of the experimental and testing phases in the R&D labs. This allowed us to derive insights more easily.”

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Structural Evolutions in Data

O'Reilly on Data

.” Consider the structural evolutions of that theme: Stage 1: Hadoop and Big Data By 2008, many companies found themselves at the intersection of “a steep increase in online activity” and “a sharp decline in costs for storage and computing.” The elephant was unstoppable. Until it wasn’t.