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from the WSJ daily AI Journal:
Recent developments show AI's true potential. Two recent AI developments demonstrate AI's explosive potential, reports Fortune, although both went largely unnoticed.
Speeding drug development. A Hong Kong biotechnology startup called InSilico Medicine, working with University of Toronto researchers, used machine learning to develop—in just 46 days—a potential new drug to prevent tissue scarring. It traditionally takes more than a decade to bring a drug to market. InSilico used reinforcement learning, "to rapidly design 30,000 new molecules and then narrow them down to six, which were synthesized and further tested in the lab," according to the report.
Answering quantum mechanical problems. Researchers at DeepMind, which is owned by Google parent Alphabet, and the Imperial College London used a deep neural net to come up with more precise answers to quantum mechanical problems. "To date, the only element for which we can completely solve the underlying quantum equations is the simplest, hydrogen, which has just one proton and one electron. For every other element, we rely on approximations. Get better approximations, and you potentially get new chemistry – and that means new materials," said Fortune.
fortune.com
Recent developments show AI's true potential. Two recent AI developments demonstrate AI's explosive potential, reports Fortune, although both went largely unnoticed.
Speeding drug development. A Hong Kong biotechnology startup called InSilico Medicine, working with University of Toronto researchers, used machine learning to develop—in just 46 days—a potential new drug to prevent tissue scarring. It traditionally takes more than a decade to bring a drug to market. InSilico used reinforcement learning, "to rapidly design 30,000 new molecules and then narrow them down to six, which were synthesized and further tested in the lab," according to the report.
Answering quantum mechanical problems. Researchers at DeepMind, which is owned by Google parent Alphabet, and the Imperial College London used a deep neural net to come up with more precise answers to quantum mechanical problems. "To date, the only element for which we can completely solve the underlying quantum equations is the simplest, hydrogen, which has just one proton and one electron. For every other element, we rely on approximations. Get better approximations, and you potentially get new chemistry – and that means new materials," said Fortune.
Two Developments Highlighting Artificial Intelligence's Industry Shattering Potential
Two important developments in artificial intelligence research hint at just how earth shaking – or at least industry-shattering – A.I.’s potential really is.
