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How would it do that? By incorporating AI-driven analytics to help individuals, teams and whole organisations make smarter choices about their leads and existing customers.ДЄccording to analyst Kate Leggett from Forrester Research, the new update will reach a wide group of end-users across a number of different fields: The research, which was backed by US public bodies the Department of Energy and the National Science Foundation, also involved Stanford academics Reinhold Dauskardt, professor of materials science and engineering doctoral graduate Nicholas Rolston and Austin Flick and Thomas Colburn as well as Zekun Ren, of the Singapore-MIT Alliance for Science and Technology.According to a report by Search CRMВ for Dynamics CRM professionals, MicrosoftвЂ™s Dynamics 365 CRM platform has now been updated with additional AI-driven BI tools for sales, marketing and service.ДЄt the Microsoft Business Applications Summit 2018, James Phillips, corporate vice president of the vendorвЂ™s business application group, said that the new Dynamics 365 update would turn Dynamics CRM into a business intelligence tool. The AI method has been directed by the researchers to optimize the power output of perovskite cells but Buonassisi said his colleagues are working on being able to direct it to maximize cost and durability, as well as other potential characteristics, at the same time.ДЇormer MIT research assistant Zhe Liu, one of the academics who worked on the project and is now at the Northwestern Polytechnical University, in the Chinese city of Xi-an, told MIT News Chinese perovskite solar companies are focused on small products such as solar roofing tiles but three manufacturers are being pressed by investors, or are already on track, to produce full-sized perovskite solar panels вЂњwithin two years.вЂќ

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The machine learning code developed by the academics has been placed on open-source software development site GitHub, from where perovskite solar manufacturers can download it and MIT professor of mechanical engineering Tonio Buonassisi said the researchers are contacting PV companies to make them aware of the code and their RSPP approach to perovskite manufacture. The material would then move on to a curing stage, providing a rapid and continuous output.вЂќ

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An article published on the MIT News website on Wednesday about the research stated: вЂњThe manufacturing process would involve a moving roll-to-roll surface, or series of sheets on which the precursor solutions for the perovskite compound would be sprayed or ink-jetted as the sheet rolled by. The researchers, whose paper has been published in the latest issue of Joule, came up with the AI system to improve the rapid spray plasma processing (RSPP) production method they have suggested for commercial production of perovskite solar cells.

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There's no substitute for experience and researchers in the US have acknowledged the fact by coming up with a machine learning method for producing perovskite solar cells which can incorporate the observations of seasoned production line staff.ДЄcademics from US institutions MIT and Stanford вЂ“ plus the Singapore-MIT Alliance for Science and Technology вЂ“ have come up with an artificial intelligence (AI) system which can include input from experienced workers as well as data from experiments conducted by other researchers, to help control the many variables which can affect mass production of perovskite cells. Clean Power Research: Solar data solutions to maximize PV project performance.Energy Storage North America Special 2018.The smarter E Europe 2019 special edition.Market overview: Microgrid control systems.Market overview: Large-scale storage systems.