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Today on In Case You Missed It: DroneShield has been touring airports across the country to test out its DroneGun, a rifle-sized UAV jammer that disable a drones’ GPS and GLONASS positioning from over a mile away. While it hasn’t received FCC certification yet, the DroneGun aims to force UAVs to land --unharmed -- and could possibly lead authorities to the pilot and launch point, which could prove to be helpful in removing drones from air space or protecting soldiers against drone bombs.
Meanwhile, MIT’s CSAIL has developed a deep learning algorithm that can generate video that accurately predicts the outcome of a scene. The algorithm uses two neural networks working in opposition to each other; the first network has watched millions of videos and uses that data to generate a new 1-2 second video of what it expects to happen. The second network determines if a video is original, or generated by the first neural network. While the technology has its limitations, it could at some point be used to help self-driving automobiles anticipate the movement of pedestrians and other cars. So, it’s got that going for it.
And if you’re interested in boldly going where no man has gone before, you might want to brush up on the tolls the trip will take on your very human body from vision problems and weakening bones to a changing heart shape. As always, please share any interesting tech or science videos you find by using the #ICYMI hashtag on Twitter for @mskerryd.
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Today on In Case You Missed It: DroneShield has been touring airports across the country to test out its DroneGun, a rifle-sized UAV jammer that disable a drones’ GPS and GLONASS positioning from over a mile away. While it hasn’t received FCC certification yet, the DroneGun aims to force UAVs to land --unharmed -- and could possibly lead authorities to the pilot and launch point, which could prove to be helpful in removing drones from air space or protecting soldiers against drone bombs.
Meanwhile, MIT’s CSAIL has developed a deep learning algorithm that can generate video that accurately predicts the outcome of a scene. The algorithm uses two neural networks working in opposition to each other; the first network has watched millions of videos and uses that data to generate a new 1-2 second video of what it expects to happen. The second network determines if a video is original, or generated by the first neural network. While the technology has its limitations, it could at some point be used to help self-driving automobiles anticipate the movement of pedestrians and other cars. So, it’s got that going for it.
And if you’re interested in boldly going where no man has gone before, you might want to brush up on the tolls the trip will take on your very human body from vision problems and weakening bones to a changing heart shape. As always, please share any interesting tech or science videos you find by using the #ICYMI hashtag on Twitter for @mskerryd.
Subscribe to Engadget on YouTube:
Get More Engadget:
• Like us on Facebook:
• Follow us on Twitter:
• Follow us on Instagram:
• Add us on Snapchat:
• Read more:
Engadget is the definitive guide to this connected life.
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