Google DeepMind AI reveals potential for thousands of new materials
Google DeepMind has used artificial intelligence (AI) to predict the structure of more than 2 million new materials, a breakthrough it said could soon be used to improve real-world technologies.
In a research paper published in science journal Nature on Wednesday, the Alphabet-owned AI firm said almost 400,000 of its hypothetical material designs could soon be produced in lab conditions.
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Offering CollegeCourseWebsiteIIM KozhikodeIIMK Advanced Data Science For ManagersVisitIndian School of BusinessISB Product ManagementVisitIIT DelhiIITD Certificate Programme in Data Science & Machine LearningVisit Potential applications for the research include the production of better-performing batteries, solar panels and computer chips.
The discovery and synthesis of new materials can be a costly and time-consuming process. For example, it took around two decades of research before lithium-ion batteries — today used to power everything from phones and laptops to electric vehicles — were made commercially available.
«We're hoping that big improvements in experimentation, autonomous synthesis, and machine learning models will significantly shorten that 10 to 20-year timeline to something that's much more manageable,» said Ekin Dogus Cubuk, a research scientist at DeepMind.
DeepMind's AI was trained on data from the Materials Project, an international research group founded at the Lawrence Berkeley National Laboratory in 2011, made up of existing research of around 50,000 already-known materials.
The company said it would now share its data with the research community, in the hopes of accelerating further breakthroughs in material discovery.
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