A wave of AI-driven techniques, from generative models to autonomous labs, is transforming materials science by enabling inverse design, rapid property prediction, and automated synthesis.
Those involved in product development understand it is a deeply iterative process driven by strict timetables, and the path is riddled with trial-and-error ...
The transformation of design, planning, and construction documentation from analog, time-intensive processes in homebuilding and residential development to real-time, generative, and fully integrated ...
Maybe you believe generative design and artificial intelligence (AI) are years away—nothing to think about. If so, you’re not alone. In Protolabs’ recently released report, Product Development Outlook ...
When Mt. Hope Elementary in Lansing, Michigan, opened its doors early this month, the ribbon-cutting wasn’t the only first. Beneath its floors and behind its walls lies 11,000 feet of electrical ...
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Generative AI may cut costs in machine-learning systems, but it increases risks of cyberattacks and data leaks
Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...
From medical image interpretation to remote monitoring to digital pathology systems, artificial intelligence is already at the forefront of medical device innovation. While manufacturers continue to ...
Software developer Bentley Systems has doubled down on its emphasis on open data standards and data lakes for design and construction, introducing two products earlier this month—OpenSite+ for civil ...
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