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American Honda IT to fuel innovation with generative AI

CIO

Generative AI takes a front seat As for that AI strategy, American Honda’s deep experience with machine learning positions it well to capitalize on the next wave: generative AI. The ascendent rise of generative AI last year has applied pressure on CIOs across all industries to tap its potential.

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Ford’s high-tech business transformation, fueled by cloud

CIO

Musser himself has spent his entire career developing software, at Ford, on Wall Street, with the Bill Gates Foundation, and at several startups, including one he sold to MuleSoft. AI everywhere Ford also plans to leverage generative AI across the company, though that initiative remains in its infancy, Musser says.

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Artificial Intelligence 101: What It Is, Its Evolution and Potential Jobs

Apiumhub

Since its conception in the mid-20th century, AI has evolved considerably thanks to advances in machine learning, neural networks, and complex algorithms, enabling its application in increasingly sophisticated fields. This includes activities such as pattern recognition, learning, decision-making, and problem-solving.

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JLR revs up AI and intelligent automation initiatives

CIO

“We’re not short of generous opportunities afforded by our strategic suppliers and vendors,” says Battle, wryly. When it comes to anything generative AI or automation orientated, “Everybody wants to help us on that journey.” There’s demand for it, too. Our business is absolutely craving it,” he adds. That seals the deal.

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Edmunds sets stage for AI with data infrastructure consolidation

CIO

For a decade, Edmunds, an online resource for automotive inventory and information, has been struggling to consolidate its data infrastructure. Now, with the infrastructure side of its data house in order, the California-based company is envisioning a bold new future with AI and machine learning (ML) at its core.

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What is NLP? Natural language processing explained

CIO

How natural language processing works NLP leverages machine learning (ML) algorithms trained on unstructured data, typically text, to analyze how elements of human language are structured together to impart meaning. It was primarily developed at the University of Massachusetts Amherst.

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Parallel Domain says autonomous driving won’t scale without synthetic data

TechCrunch

Parallel Domain has been focused on the automotive market, supplying synthetic data to some of the major OEMs that are building advanced driver assistance systems and autonomous driving companies building much more advanced self-driving systems.

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