Google DeepMind's AI Forecasts Thousands Of New Materials, Paving Way For Advanced Electric Vehicle Batteries

Alphabet Inc.'s GOOG GOOGL unit, Google DeepMind, used artificial intelligence to predict 2.2 million new crystals, including 380,000 stable materials that could power future technologies.

The research could lead to advancements that potentially develop future transformative technologies ranging from superconductors, powering supercomputers and next-generation batteries to boost the efficiency of electric vehicles.

The firm said the development was equivalent to nearly 800 years worth of knowledge, according to research paper published in Nature.

The Google-backed firm introduced Graph Networks for Materials Exploration (GNoME). This new deep-learning tool dramatically increased the speed and efficiency of discovery by predicting the stability of new materials.

Discovering and synthesizing new materials, such as lithium-ion batteries now used in various devices and electric vehicles, can be a costly, decades-long process, Reuters said in a news report.

"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," Ekin Dogus Cubuk, a research scientist at DeepMind told Reuters.

"We hope that GNoME together with other AI tools can help revolutionize materials discovery today and shape the future of the field," Google DeepMind said in a statement.

Alphabet Price Action: GOOG shares were trading lower by 1.36% to $136.73, while GOOGL shares were trading lower by 1.40% to $135.28 on the last check Wednesday.

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Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors.

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