A U.S. military drone crashed in northern Syria while carrying out a combat mission against ISIS, the Air Force said Tuesday. According to a statement, the MQ-9 Reaper drone was not brought down by enemy fire and there were no reports of civilian injuries or damage in the crash. The statement added that aircraft of the U.S.-led coalition destroyed the crashed drone before it could fall into ISIS hands. An investigation will be conducted to determin the exact cause of the crash. The Obama administration has often used unmanned aircraft to target leaders of terror groups.

Jibo will be one of the first robots for the home that can actually see its users. The first wave of home robots is already upon us with the Amazon Echo, and the coming Google Home. While these barebones bots can take simple commands, they can't really add anything to the conversation or scoot around your home. That's what the makers of Jibo are trying to create--a robot that can initiate conversation to complete tasks in the home--and they're tapping some of the world's foremost A.I. researchers to do it. Today, Jibo Inc. announces that its adding veteran researcher Michael I. Jordan to its advisory board.

The dreaded act of parallel parking could soon become a thing of the past with Chinese inventors backing their new parking robot to take away the stress for anxious drivers. The laser-guided'Geta' (get a car) robot slides under your vehicle to pick it up. It then finds a parking space in the lot and places the car in the tightest of spots. The laser-guided'Geta' (get a car) robot slides under your vehicle to pick it up. The laser-guided'Geta' (get a car) robot slides under your vehicle to pick it up.

With warehouses full of robots that can move shelves from place to place, the only reason that Amazon needs humans anymore is to pick things off of those shelves and put them into boxes, and pick other things out of boxes and put them onto those shelves. Amazon wants robots to be doing these tasks too, but it's a hard problem--hard enough that the enormous bajillion dollar company is asking other roboticists to solve it for them. The first Amazon Picking Challenge was held at ICRA last year in Seattle, Amazon's home town. Amazon followed it up this year with another, tougher challenge at RoboCup 2016, which just wrapped up. And the winner is...Team Delft from the Netherlands!

Lecture Title: Machines that learn: big data or explanatory models? Abstract: A leading question about machines that learn concerns two distinct styles of learning. Will they turn out to depend more on probabilistic models that explain the data, or on networks that react to data and are trained on data at ever greater scale? In machine vision systems, for instance, this boils down to the comparative roles of two paradigms: analysis-by-synthesis versus empirical recognisers. Each approach has its strengths, and empirical recognisers especially have made great strides in performance in the last few years, through deep learning.

A chimpanzee has learned to walk again after an illness left him paralysed. The male, named Reo, was 24 when part of his spinal cord became inflamed, rendering him unable to move. Now, ten years later, thanks to a dedicated programme of training using a touch screen and reward training, he is able to walk again. Lead author Yoko Sakuraba of Kyoto University described the triumph in an article in Primates, the official journal of the Japan Monkey Centre. The study marks the first time a dedicated training progamme using touch screen technology to study chimpanzees' cognitive abilities has helped a chimp recover after paralysis.

Natural Language Processing seems to have become somewhat of a commodity in recent years. More than a few companies have sprung up that offer basic NLP capabilities through a cloud API. If you'd like to know whether a text carries a positive or negative message, or what people or companies it mentions, you can just send it to one of these black boxes, and receive the answer in less than a second. Superficially, all these NLP APIs look more or less the same. Textrazor, AlchemyAPI, Aylien, MeaningCloud and Lexalytics all offer similar services (named entity recognition, sentiment analysis, keyword extraction, topic identification, etc.), and do so through similar interfaces.

Someone needed to address the elephant in the room. Mosha, an Asian elephant who lost her right foreleg at just 7 months old when she stepped on a land mine on Thailand's border with Myanmar got her ninth prosthetic limb on June 29, which ended up saving her life. "The way she walked was unbalanced and her spine was going to bend," Dr. Therdchai Jivacate, the orthopedist surgeon who designed the artificial leg, told Reuters. Jivacate made Mosha her first prosthetic leg six years ago when he met her at Friends of the Asian Elephant Foundation when the majestic mammal was 2 and a half. Back then, Mosha weighed 1,300 pounds, now she weighs 4,000 and her artificial legs need to be redesigned to keep up with her growing body.

The skies above are growing increasingly crowded with satellites zipping across Earth's upper atmosphere, relaying signals for everything from the picture on your television to the map on your phone. While this constant communication makes the world go round, all of that orbiting technology brings with it a problem, in the form of space junk – the debris from rocket launches and defunct satellites which hangs on in space. Lapping the Earth at thousands of miles per hour means even smallest chunks of metal or flecks of paint can cause significant damage if they run into the path of a satellite. But scientists at the University of Surrey are gearing up to test technologies which could target potentially hazardous space junk and remove it from orbit before it can cause any damage. The first experiment will use a net to capture a target in the form of a small CubeSat launched from the main satellite.

Do you get what overfitting means in machine learning? If you don't, then you better learn about it if you want to use or leverage machine learning. Because overfitting can ruin the effectiveness of machine learning. I wrote this blog because I found existing explanations of overfitting to be too technical. I hope this one is more consumable by non specialists. Machine learning involves a fairly complex workflow, see Machine Learning Algorithm!