This month, NASA will fire its first interplanetary mission from Vandenberg Air Force Base north of Los Angeles. Why the snub for Cape Canaveral in Florida?
Source: Wired
The v2 creator and Vine co-founder says the new project is postponed indefinitely.
Source: CNET
A company exec reportedly ordered a Bluetooth headset that never came. His colleagues eventually cracked down on 5,000 merchant accounts that were scamming users.
Source: CNET
The volume of data particle physicists have to sort through at the Large Hadron Collider is staggering, and it’s about to increase by an order of magnitude. To cope with this torrent of data, CERN is turning to machine learning, offering prizes for AI models that can cut through the clutter and help make the next breakthrough.
Inside the massive detectors that dot the rings of the LHC, protons accelerated to near light speed smash into each other with incredible energy and produce a fountain of exotic, short-lived particles that impact on sensors lining the walls. Improvements being made to the magnetic fields guiding these protons around the ring mean that where once you could expect a couple dozen collisions to draw data from, soon there may be hundreds.
Great for the scientists, but with more collisions comes more data, in this case an order of magnitude more. The old methods of sorting and categorizing the data are too slow, researchers told Nature. So they’re doing what any modern data scientist would do when faced with a massive set of noisy data: hand it over to the AIs.
I use the term loosely, of course — machine learning models are just really great at chewing through reams of data in search of what they’ve been trained to find. Medicine, astronomy, and of course psychology (courtesy of Facebook) have all been advanced by this convenient ability to separate the statistical wheat from the chaff. Particle physics is just another example of it.
A little healthy competition, as always, is a good way to jump-start the field. So CERN established TrackML, a relatively low-key contest in which physicists and data scientists can download gigs of real collider data and train up models to classify it correctly. Of course, there are terabytes available for the picking, but you’ll want to use this particular dataset.
The prize pool is relatively small, with a total of $25,000 available to the winners. Perhaps they used up all their money on… you know, upgrading the world’s biggest particle collider with state of the art cryomagnets.
There’s no entry fee, so if you’re interested in giving it a shot, head over to Kaggle, where the contest is hosted, and download your own copy of the data. You’ve got plenty of time — submissions are due in August. Oh, and anything you submit will be open sourced, so don’t worry that they’re going to commercialize your algorithm.
Source: TechCrunch
The heart of the joke hides in the fine print at the end of the bit.
Source: CNET
Notches have become a trend since the iPhone X, but LG told reporters it had the idea before.
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Blasting off Star Wars-style in Bryant Park for May the 4th, the Millennium Falcon pedicab is built from over 20,000 Lego bricks.
Source: CNET
Amazon halted plans for two buildings in Seattle in response to a proposed tax that would cost the company about $22.5 million a year.
Source: Wired
Researchers at Ben-Gurion University of the Negev in Israel are building a tic-tac-toe game to help patients with their rehabilitation exercises. The game is played on a grid of boxes and includes “embodied” and non-embodied play. Embodied play means a robotic arm will grab and place a marker – in this case a small cup – and non-embodied play includes bright lights that light up to mark the computer’s spot.
The system uses a Kinova arm and cups. The cups are part of the rehabilitation process and help users learn to grasp and manipulate objects after an illness or accident.
“Playing Tic Tac Toe with a set of cups (instead of X’s and O’s) is one example of a game that can help rehabilitate an upper limb,” said Dr. Shelly Levy-Tzedek. “A person can pick up and place many cups while enjoying a game and improving their performance of a daily task.”
Interestingly the speed of the robot had an effect on the users. A slower robot would make users perform more slowly while a faster robot sped up the game. This could be used to modify the game for individual patients and individual needs. Because the robot never gets tired the rehabilitation staff can pay attention to the minute movements of a patient, catering the speed and type of play as appropriate for their specific rehabilitation regimens.
The research paper appeared in Restorative Neurology and Neuroscience.
Source: TechCrunch
Elon Musk’s automaker says the semi-autonomous feature cuts crashes by 40 percent, but a closer look at the math reveals some major caveats.
Source: Wired