A new form of magnetic interaction which pushes a formerly two-dimensional phenomenon into the third dimension could open up a host of exciting new possibilities for data storage and advanced computing, scientists say.
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Robert Downey Jr. doesn’t pretend to be a brilliant scientist — even though he’s played Tony Stark, aka Iron Man, for the past 11 years.
But on Tuesday night he attended Amazon’s brand new, premier, open-to-the-public Machine Learning, Automation, Robotics and Space (re: MARS) conference in Las Vegas — a room filled with AI legends, astronauts, and other dignitaries — as a keynote speaker.
He delivered a gag-filled talk that somehow weaved together the history of the Marvel Cinematic Universe, the evolution of Stark’s Iron Man suits, allusions to his own troubled history with drug addiction, the actual history of artificial intelligence and its pioneers, with a bunch of jokes using the Amazon Alexa voice and Matt Damon (including a videotaped guest appearance by Damon).
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Researchers, from biochemists to material scientists, have long relied on the rich variety of organic molecules to solve pressing challenges. Some molecules may be useful in treating diseases, others for lighting our digital displays, still others for pigments, paints, and plastics. The unique properties of each molecule are determined by its structure—that is, by the connectivity of its constituent atoms. Once a promising structure is identified, there remains the difficult task of making the targeted molecule through a sequence of chemical reactions. But which ones?
Organic chemists generally work backwards from the target molecule to the starting materials using a process called retrosynthetic analysis. During this process, the chemist faces a series of complex and inter-related decisions. For instance, of the tens of thousands of different chemical reactions, which one should you choose to create the target molecule? Once that decision is made, you may find yourself with multiple reactant molecules needed for the reaction. If these molecules are not available to purchase, then how do you select the appropriate reactions to produce them? Intelligently choosing what to do at each step of this process is critical in navigating the huge number of possible paths.
Researchers at Columbia Engineering have developed a new technique based on reinforcement learning that trains a neural network model to correctly select the “best” reaction at each step of the retrosynthetic process. This form of AI provides a framework for researchers to design chemical syntheses that optimize user specified objectives such synthesis cost, safety, and sustainability. The new approach, published May 31 by ACS Central Science, is more successful (by ~60%) than existing strategies for solving this challenging search problem.
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We owe our long lives to stem cells, which are nestled deep inside certain tissues in the body and constantly replace old cells. In recent years scientists have been able to correct genetic diseases by removing these stem cells, editing their genomes and then implanting them back into the patient, but that adds complications. Now, new research led by Harvard scientists has successfully edited the genes of stem cells while still in the body.
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The Privacy Project
Posted in biotech/medical, business, internet
Companies and governments are gaining new powers to follow people across the internet and around the world, and even to peer into their genomes. The benefits of such advances have been apparent for years; the costs — in anonymity, even autonomy — are now becoming clearer. The boundaries of privacy are in dispute, and its future is in doubt. Citizens, politicians and business leaders are asking if societies are making the wisest tradeoffs. The Times is embarking on this monthslong project to explore the technology and where it’s taking us, and to convene debate about how it can best help realize human potential.
The New York Times is launching an ongoing examination of privacy. We’ll dig into the ideas, history and future of how our information navigates the digital ecosystem and what’s at stake.
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In solar cells, the cheap, easy to make materials called perovskites are adept at turning photons into electricity. Now, perovskites are turning the tables, converting electrons into light with an efficiency on par with that of the commercial organic light-emitting diodes (LEDs) found in cellphones and flat screen TVs. And in a glimpse of how they might one day be harnessed, researchers reported last week in Science Advances that they’ve used a 3D printer to pattern perovskites for use in full-color displays.
“It’s a fantastic result, and quite inspirational,” says Richard Friend, a physicist at the University of Cambridge in the United Kingdom whose team created the first perovskite LED in 2014. The result raises hopes that the computer screens and giant displays of the future will consist of these cheap crystalline substances, made from common ingredients. Friend cautions, however, that the new perovskite displays aren’t yet commercially viable.
The materials in current semiconductor LEDs, including the organic versions, require processing at high temperatures in vacuum chambers to ensure the resulting semiconductors are pristine. By contrast, perovskites can be prepared simply by mixing their chemical components in solution at room temperature. Only a brief heat treatment is needed to crystallize them. And even though the perovskite crystals end up with imperfections, these defects typically don’t destroy the materials’ ability to emit light.
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