“” We’re looking at Flippy as a tool that helps us increase speed of service and frees team members up to focus more on other areas we want to concentrate on, whether that’s order accuracy or how we’re handling delivery partner drivers and getting them what they need when they come through the door.”, said White Castle’s Vice President, Jamie Richardson.”
Flippy is the world’s first autonomous robotic kitchen assistant that can learn from its surroundings and acquire new skills over time.
NEW: A microchip carrying more than 27,000 Civil Air Patrol names with related messages and images is set to be carried to the moon later this year aboard space robotics company Astrobotic’s Peregrine lunar lander. https://www.cap.news/next-stop-the-moon-for-27000-cap-names/
A microchip carrying more than 27000 Civil Air Patrol names with related messages and images is set to be carried to the moon later this year aboard space robotics company Astrobotic’s Peregrine lunar lander.
A silicone robot has survived a journey to 10900 metres below the ocean’s surface in the Mariana trench, where the crushing pressure can implode all but the strongest enclosures. This device could lead to lighter and more nimble submersible designs.
A team led by Guorui Li at Zhejiang University in China based the robot’s design on snailfish, which have relatively delicate, soft bodies and are among the deepest-living fish. They have been observed swimming at depths of more than 8000 metres.
The submersible robot looks a bit like a manta ray and is 22 centimetres long and 28 centimetres in wingspan. It is made of silicone rubber with electronic components spread throughout the body and connected by wires, rather than mounted on a circuit board like most submersibles. That’s because the team found in tests that the connections between components on rigid circuit boards were a weak point when placed under high pressure.
The Facebook research builds upon steady progress in tweaking deep learning algorithms to make them more efficient and effective. Self-supervised learning previously has been used to translate text from one language to another, but it has been more difficult to apply to images than words. LeCun says the research team developed a new way for algorithms to learn to recognize images even when one part of the image has been altered.
Most image recognition algorithms require lots of labeled pictures. This new approach eliminates the need for most of the labeling.
