BREAKING: The First U.S. Test to Detect If a Person Has Potential Immunity to COVID-19 Was Just Developed

BREAKING: The First U.S. Test to Detect If a Person Has Potential Immunity to COVID-19 Was Just Developed

Testing for immunity to COVID-19 will allow frontline health workers to safely go back to work, knowing they can't spread the disease.

(© chompoo/Adobe)


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Kira Peikoff

Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.

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Podcast: The Friday Five weekly roundup in health research

Researchers are making progress on a vaccine for Lyme disease, sex differences in cancer, new research on reducing your risk of dementia with leisure activities, and more in this week's Friday Five

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The Friday Five covers five stories in health research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.

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Matt Fuchs

Matt Fuchs is the editor-in-chief of Leaps.org. He is also a contributing reporter to the Washington Post and has written for the New York Times, Time Magazine, WIRED and the Washington Post Magazine, among other outlets. Follow him on Twitter @fuchswriter.

Scientists Want to Make Robots with Genomes that Help Grow their Minds

Giving robots self-awareness as they move through space - and maybe even providing them with gene-like methods for storing rules of behavior - could be important steps toward creating more intelligent machines.

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One day in recent past, scientists at Columbia University’s Creative Machines Lab set up a robotic arm inside a circle of five streaming video cameras and let the robot watch itself move, turn and twist. For about three hours the robot did exactly that—it looked at itself this way and that, like toddlers exploring themselves in a room full of mirrors. By the time the robot stopped, its internal neural network finished learning the relationship between the robot’s motor actions and the volume it occupied in its environment. In other words, the robot built a spatial self-awareness, just like humans do. “We trained its deep neural network to understand how it moved in space,” says Boyuan Chen, one of the scientists who worked on it.

For decades robots have been doing helpful tasks that are too hard, too dangerous, or physically impossible for humans to carry out themselves. Robots are ultimately superior to humans in complex calculations, following rules to a tee and repeating the same steps perfectly. But even the biggest successes for human-robot collaborations—those in manufacturing and automotive industries—still require separating the two for safety reasons. Hardwired for a limited set of tasks, industrial robots don't have the intelligence to know where their robo-parts are in space, how fast they’re moving and when they can endanger a human.

Over the past decade or so, humans have begun to expect more from robots. Engineers have been building smarter versions that can avoid obstacles, follow voice commands, respond to human speech and make simple decisions. Some of them proved invaluable in many natural and man-made disasters like earthquakes, forest fires, nuclear accidents and chemical spills. These disaster recovery robots helped clean up dangerous chemicals, looked for survivors in crumbled buildings, and ventured into radioactive areas to assess damage.

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Lina Zeldovich
Lina Zeldovich has written about science, medicine and technology for Scientific American, Reader’s Digest, Mosaic Science and other publications. She’s an alumna of Columbia University School of Journalism and the author of the upcoming book, The Other Dark Matter: The Science and Business of Turning Waste into Wealth, from Chicago University Press. You can find her on http://linazeldovich.com/ and @linazeldovich.