The Japanese Hayabusa 2 spacecraft will drop off samples of dust and rocks from the asteroid Ryugu on 6 December before heading off to visit another asteroid.
Google has started negotiating with Japanese media companies to sign them up as partners in its new program called Google News Showcase.
The recently launched project involves Google paying news publishers to deliver their stories.
Google has already signed partnerships with about 400 news organizations in 7 countries, including Germany and France. The company has invested more than 1 billion dollars in the project.
A 15-year-old Colorado high school student and young scientist who has used artificial intelligence and created apps to tackle contaminated drinking water, cyberbullying, opioid addiction and other social problems has been named Time Magazine’s first-ever “Kid of the Year.”
Gitanjali Rao, a sophomore at STEM School Highlands Ranch in suburban Denver who lives in the city of Lone Tree, was selected from more than 5,000 nominees in a process that culminated with a finalists’ committee of children, drinking water crisis in Flint, Michigan, inspired her work to develop a way to detect contaminants and send those results to a mobile phone, she said.
“I was like 10 when I told my parents that I wanted to research carbon nanotube sensor technology at the Denver Water quality research lab, and my mom was like, ” A what?” Rao told Jolie. She said that work ” is going to be in our generation’s hands pretty soon. So if no one else is gonna do it, I’m gonna do it.”
NASA’s New Horizons spacecraft has detected light with no obvious source coming from beyond our galaxy.
A hyper-sensitive instrument, deep underground in Italy, has finally succeeded at the nearly impossible task of detecting CNO neutrinos (tiny particles pointing to the presence of carbon, nitrogen, and oxygen) from our sun’s core. These little-known particles reveal the last missing detail of the fusion cycle powering our sun and other stars.
In results published on November 26, 2020, in the journal Nature (and featured on the cover), investigators of the Borexino collaboration report the first detections of this rare type of neutrinos, called “ghost particles” because they pass through most matter without leaving a trace.
The neutrinos were detected by the Borexino detector, an enormous underground experiment in central Italy. The multinational project is supported in the United States by the National Science Foundation under a shared grant overseen by Frank Calaprice, professor of physics emeritus at Princeton; Andrea Pocar, a 2003 graduate alumna of Princeton and professor of physics at the University of Massachusetts-Amherst; and Bruce Vogelaar, professor of physics at the Virginia Polytechnical Institute and State University (Virginia Tech).
There is a renaissance occurring in the field of artificial intelligence. For some drawn-out specialists in the field, it isn’t excessively self-evident. Many are making against the advancements of Deep Learning is anyway an amazingly radical departure from classical methods.
Old style A.I. procedures has zeroed in generally on the legitimate premise of cognition, Deep Learning by contrast works in the territory of cognitive intuition. Deep learning frameworks display behavior that seems biological despite not being founded on biological material. It so happens that humankind has fortunately discovered Artificial Intuition as Deep Learning.
Artificial intuition is a simple term to misconstrue since it seems like artificial emotion and artificial empathy. In any case, it contrasts fundamentally. Scientists are dealing with artificial intuition so that machines can impersonate human behavior all the more precisely. Artificial intuition plans to distinguish a human’s perspective in real-time. Along these lines, for instance, chatbots, virtual assistants and care robots can react to people all the more appropriately in context. Artificial intuition is more similar to human intuition since it can quickly evaluate the totality of a situation, including subtle indicators of a specific activity.
A new survey of our galaxy by astronomers with VERA in Japan has shown that Earth is both moving faster and is closer to the supermassive black hole at the center of our galaxy than previously thought. But don’t worry, our planet is safe!
Over the past decade or so, roboticists and computer scientists have tried to use reinforcement learning (RL) approaches to train robots to efficiently navigate their environment and complete a variety of basic tasks. Building affordable robots that can support and manage the exploratory controls associated with RL algorithms, however, has so far proved to be fairly challenging.
Researchers at Aalto University and Ote Robotics have recently created RealAnt, a low-cost, four-legged robot that can effectively be used to test and implement RL algorithms. The new robotics platform, presented in a paper pre-published on arXiv, is a minimalistic and affordable real-world version of the ‘Ant’ robot simulation environment, which is often used in RL research.
“The initial inspirations for our work were RL studies that successfully demonstrated learning to walk from scratch on ant-like quadruped and humanoid robot simulations,” Jussi Sainio, co-founder of Ote Robotics, told Tech Xplore. “The underlying premise with RL algorithms is that programming a robot to do tasks becomes much easier and more ‘natural’—one just needs to define the available sensor measurements, motor actions, then set a target goal and plug them all into a reinforcement learning algorithm, which figures out the rest.”
For a new pancreatic cancer treatment, researchers attached a chemotherapy drug to an antibody that targets a molecule on the outside of cancer cells.
Remember when the idea of a robotic hand was a clunky mitt that could do little more than crush things in its iron grip? Well, such clichés should be banished for good based on some impressive work coming out of the WMG department at the U.K.’s University of Warwick.
If the research lives up to its potential, robot hands could pretty soon be every bit as nimble as their flesh-and-blood counterparts. And it’s all thanks to some impressive simulation-based training, new A.I. algorithms, and the Shadow Robot Dexterous Hand created by the U.K.-based Shadow Robot Company (which Digital Trends has covered in detail before.)
Researchers at WMG Warwick have developed algorithms that can imbue the Dexterous Hand with impressive manipulation capabilities, enabling two robot hands to throw objects to one another or spin a pen around between their fingers.