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Scientists Created "Ghosts" in the Lab

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Have you ever experienced the creepy sensation that you’re not the only person in the room? You get a chill, maybe the hair on the back of your neck stands up, and for a second you think maybe you do believe in ghosts. 

This sensation is commonly reported in people with certain neurological or psychiatric disorders, or those exposed to extreme conditions. In 1970, mountaineer Reinhold Messner reported seeing a “phantom” climber descending the slopes of a particularly extreme summit alongside him. This also happens in people who have recently experienced another extreme condition: the loss of a spouse. In most cases, the sufferer reports the very real sensation of an unseen presence. This is the stuff of which ghost stories are made, but researchers say they know why this feeling occurs, and they’ve even recreated it in the lab. 

Olaf Blanke, a researcher from the Swiss Federal Institute of Technology in Lausanne, Switzerland (EPFL), first had to find the scientific culprit for these strange sensations. He and his team analyzed brain scans of patients suffering from neurological disorders who experience the ghostly feeling. They found abnormalities in the areas controlling how the brain sees the body, or one’s own spatial self-awareness. These abnormalities “can sometimes create a second representation of one’s own body, which is no longer perceived as ‘me’ but as someone else, a ‘presence,’” says Giulio Rognini, who led the study. 

Armed with an understanding of where the feeling of being haunted comes from, the researchers set out to recreate it in “healthy” people. A group of subjects—oblivious as to the experiment’s purpose—were blindfolded, their fingers connected to a robotic device. When the test subjects moved the device, a robotic arm behind them mimicked the movement, poking them in the back. Sounds pretty straightforward, but when researchers introduced a slight delay between the subject’s movement and the resulting poke, the subjects were spooked. They felt they were being touched by another presence. Some even reported sensing more than one “ghost.” 

“Actually some subjects reacted very strongly and they reported not only that they felt that somebody else was touching them but that somebody else was also present,” Blanke says. For some people the sensation was so strong, they didn’t want to finish the experiment. 

“This confirms [the sensation] is caused by an altered perception of their own bodies in the brain,” Blanke says. So the next time you feel like you’re being watched, remember it might just be your brain playing tricks on your perception.

Aside from disappointing ghost hunters, this research could someday help treat disorders like schizophrenia or other neurological and psychiatric conditions. 

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Google's AI Can Make Its Own AI Now
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Artificial intelligence is advanced enough to do some pretty complicated things: read lips, mimic sounds, analyze photographs of food, and even design beer. Unfortunately, even people who have plenty of coding knowledge might not know how to create the kind of algorithm that can perform these tasks. Google wants to bring the ability to harness artificial intelligence to more people, though, and according to WIRED, it's doing that by teaching machine-learning software to make more machine-learning software.

The project is called AutoML, and it's designed to come up with better machine-learning software than humans can. As algorithms become more important in scientific research, healthcare, and other fields outside the direct scope of robotics and math, the number of people who could benefit from using AI has outstripped the number of people who actually know how to set up a useful machine-learning program. Though computers can do a lot, according to Google, human experts are still needed to do things like preprocess the data, set parameters, and analyze the results. These are tasks that even developers may not have experience in.

The idea behind AutoML is that people who aren't hyper-specialists in the machine-learning field will be able to use AutoML to create their own machine-learning algorithms, without having to do as much legwork. It can also limit the amount of menial labor developers have to do, since the software can do the work of training the resulting neural networks, which often involves a lot of trial and error, as WIRED writes.

Aside from giving robots the ability to turn around and make new robots—somewhere, a novelist is plotting out a dystopian sci-fi story around that idea—it could make machine learning more accessible for people who don't work at Google, too. Companies and academic researchers are already trying to deploy AI to calculate calories based on food photos, find the best way to teach kids, and identify health risks in medical patients. Making it easier to create sophisticated machine-learning programs could lead to even more uses.

[h/t WIRED]

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European Space Agency Releases First High-Res Land Cover Map of Africa
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Land Cover CCI, ESA

This isn’t just any image of Africa. It represents the first of its kind: a high-resolution map of the different types of land cover that are found on the continent, released by The European Space Agency, as Travel + Leisure reports.

Land cover maps depict the different physical materials that cover the Earth, whether that material is vegetation, wetlands, concrete, or sand. They can be used to track the growth of cities, assess flooding, keep tabs on environmental issues like deforestation or desertification, and more.

The newly released land cover map of Africa shows the continent at an extremely detailed resolution. Each pixel represents just 65.6 feet (20 meters) on the ground. It’s designed to help researchers model the extent of climate change across Africa, study biodiversity and natural resources, and see how land use is changing, among other applications.

Developed as part of the Climate Change Initiative (CCI) Land Cover project, the space agency gathered a full year’s worth of data from its Sentinel-2A satellite to create the map. In total, the image is made from 90 terabytes of data—180,000 images—taken between December 2015 and December 2016.

The map is so large and detailed that the space agency created its own online viewer for it. You can dive further into the image here.

And keep watch: A better map might be close at hand. In March, the ESA launched the Sentinal-2B satellite, which it says will make a global map at a 32.8 feet-per-pixel (10 meters) resolution possible.

[h/t Travel + Leisure]

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