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To excel at engineering design, generative AI must learn to innovate, study finds

To excel at engineering design, generative AI must learn to innovate, study finds
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Lyle regenwetterDan gutreundPrakash srivastavaFaez ahmedWatson ai labDecode labComputer aided

To excel at engineering design, generative AI must learn to innovate, study finds

A new study reveals the pitfalls of deep generative models when they are tasked with solving engineering design problems. The MIT researchers say if mechanical engineers want help from AI for novel ideas and designs, they’ll have to refocus those models beyond “statistical similarity.”

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To excel at engineering design, generative AI must first learn to innovate, study finds

To excel at engineering design, generative AI must first learn to innovate, study finds
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Faez ahmedLyle regenwetterPrakash srivastavaDan gutreundMassachusetts institute of technologyDecode labWatson ai labMassachusetts instituteBeyond statistical similarityRethinking metricsDeep generative modelsEngineering designComputer aided design

Microsoft s Project Silica will store terabytes of data on glass plates for cloud storage

Data storage that will last up to 10,000 years and doesn't require electricity, Microsoft's Project Silica will use glass to revolutionize the cloud.

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Microsoft Project Silica: Glass Plates That Store Data for 10,000 Years

Microsoft Project Silica: Glass Plates That Store Data for 10,000 Years
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