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AI algorithms will unlock the true value of R&D data

In order to make sense of the vast quantities of product data available, automotive engineers must reconsider the value of AI. By Will Girling

Around US$124bn was spent on global automotive R&D in 2022—representing year-on-year growth of 6.8%, according to online market data platform Statista. But, as the industry’s digital transformation changes the way vehicles are designed, tested, and manufactured, is that money being channelled optimally?

Special report: The future of automotive research and development

Richard Ahlfeld, Chief Executive and Founder of Monolith AI, doesn’t think so. Monolith, which provides a no-code AI algorithm software platform built specifically for engineers, believes it can better leverage test data to make R&D cheaper, faster, and more precise. However, Ahlfeld tells Automotive World that automotive engineers’ neglect of machine learning means that accumulated R&D information is often underutilised and inaccessible.

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