“Artificial intelligence is helping to accelerate the identification of promising new materials” || Dario Gil Vice president of IBM.

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Dario Gil, vice president of science and solutions at IBM Research, at EmTech Digital 2017.
Artificial intelligence is helping to accelerate the identification of promising new materials, said Dario Gil, vice president of science and solutions at IBM Research, at the EmTech Digital conference in San Francisco on Monday.
Machine learning software on a laptop can extract the critical information from scientific papers in seconds, enabling the creation of vast knowledge graphs across wide bodies of research in weeks rather than decades, Gil said. It means scientists can apply algorithms and simulations to extract insights from a far bigger pool of patents, papers and other reports than any single person could ever hope to read.
Gil didn’t point to specific breakthroughs to date. But he said IBM is already applying its Watson artificial intelligence system in an effort to discover novel polymers. For all the advances in AI and computing, though, he said even the world’s most powerful supercomputers are still often stumped, such as in trying to predict the electronic structure of molecules. IBM, however, sees great potential here in the rise of quantum computing, which can dramatically accelerate calculations and more closely mimic nature by tapping into the weird properties of quantum physics.
The company unveiled a new quantum chip last year, and earlier this month announced plans to build a cloud-based, commercially-available quantum computing system. “We anticipate that we’re going to see quite dramatic advances in this year and the next, in terms of the power of quantum computers,” he said
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