Only these eyes aren’t human. They don’t blink or take breaks, and guided by artificial intelligence they can tell the difference between a dust cloud, an insect swarm and a plume of smoke that demands quick attention. In Brazil, the devices help keep mining giant Vale SA working, and protect trees for pulp and paper producer Suzano SA.
The research and development of neural networks is flourishing thanks to recent advancements in computational power, the discovery of new algorithms, and an increase in labelled data. Before the current explosion of activity in the space, the practical applications of neural networks were limited.
Much of the recent research has allowed for broad application, the heavy computational requirements for machine learning models still restrain it from truly entering the mainstream. Now, emerging algorithms are on the cusp of pushing neural networks into more conventional applications through exponentially increased efficiency.
The U.S. Army has confirmed it is trying to speed up high-powered laser weapon program to develop a new system that will acquire, track, engage, and defeat unmanned aircraft system, cruise missile and rocket, artillery, and mortar threats.
The new Army’s high-powered laser weapon system is intended to provide 360º protection and simultaneously engage threats arriving from different azimuths.
The Army will adjust the current High Energy Laser Tactical Vehicle Demonstrator (HEL-TVD), a 100 kW-class laser system integrated on a Family of Medium Tactical Vehicles platform developed by Dynetics and subcontractor Lockheed Martin. Under the new directed energy strategy, the Army is leveraging progress made in that effort in order to merge the HEL-TVD with similar technologies in development by the Navy and the Office of the Secretary of Defense.
The other gaming was that computers don’t really understand words… So you ask, “Who was the sixteenth president of the United States.”? The computer doesn’t know what “sixteenth” and “president of the United States” mean. But it can go and rummage through Wikipedia-like sources and find those words and match them to a president, Abraham Lincoln and come back with “‘Who’ was Abraham Lincoln.”
But then you put anything in that’s like a pun or a joke or a riddle or sarcasm, that you can’t look up in Wikipedia, and computers are helpless. For example, in the first round, one of the final Jeopardy clues was, “Its largest airport is named for a World War II hero; its second largest for a World War II battle.” And the correct answer was “Chicago.” And Watson guessed “Toronto,” apparently because it was confused in the second part of that sentence, what “it” referred to. And that is a common problem with computers. (See: Why did Watson think Toronto was in the U.S.A.?)
Terry Winograd is a computer scientist at Stanford and he thought up this test of computer knowledge. The question is, “What does ‘it’ refer to in this sentence?”
China has declared its ambition to dominate the technology sector from 5G and artificial intelligence to robotics and quantum computing. Joining the infrastructure firms on this year’s list are technology firms such as Alibaba, http://JD.com/, Tencent, Xiaomi, and BOE. Huawei was not included as it is a private entity.
China’s ambition to dominate the technology sector from 5G and artificial intelligence to robotics and quantum computing is bearing fruit.
Given that going viral on the Internet is often cyclical, it should come as no surprise that an app that made its debut in 2017 has once again surged in popularity. FaceApp applies various transformations to the image of any face, but the option that ages facial features has been especially popular. However, the fun has been accompanied by controversy; since biometric systems are replacing access passwords, is it wise to freely offer up our image and our personal data? The truth is that today the face is ceasing to be as non-transferable as it used to be, and in just a few years it could be more hackable than the password of a lifetime.
Our countenance is the most recognisable key to social relationships. We might have doubts when hearing a voice on the phone, but never when looking at the face of a familiar person. In the 1960s, a handful of pioneering researchers began training computers to recognise human faces, although it was not until the 1990s that this technology really began to take off. Facial recognition algorithms have improved to such an extent that since 1993 their error rate has been halved every two years. When it comes to recognising unfamiliar faces in laboratory experiments, today’s systems outperform human capabilities.
Continue reading “How to Hack a Face: From Facial Recognition to Facial Recreation” »
The US Army will field 50 kilowatt (kW)-class lasers on a platoon of four Stryker vehicles in 2022. They will support the Maneuver-Short Range Air Defense (M-SHORAD) mission. The directed energy M-SHORAD capability is intended to protect maneuvering Brigade Combat Teams from unmanned aerial systems (UAS), rotary-wing aircraft, and rockets, artillery and mortar (RAM).
Researchers from North Carolina State University and Elon University have developed a technique that allows them to remotely control the movement of soft robots, lock them into position for as long as needed and later reconfigure the robots into new shapes. The technique relies on light and magnetic fields.
“We’re particularly excited about the reconfigurability,” says Joe Tracy, a professor of materials science and engineering at NC State and corresponding author of a paper on the work. “By engineering the properties of the material, we can control the soft robot’s movement remotely; we can get it to hold a given shape; we can then return the robot to its original shape or further modify its movement; and we can do this repeatedly. All of those things are valuable, in terms of this technology’s utility in biomedical or aerospace applications.”
For this work, the researchers used soft robots made of a polymer embedded with magnetic iron microparticles. Under normal conditions, the material is relatively stiff and holds its shape. However, researchers can heat up the material using light from a light-emitting diode (LED), which makes the polymer pliable. Once pliable, researchers demonstrated that they could control the shape of the robot remotely by applying a magnetic field. After forming the desired shape, researchers could remove the LED light, allowing the robot to resume its original stiffness—effectively locking the shape in place.
As well as Gait Recognition. (Go ahead and wear a disguise.)
The mass surveillance of innocent Americans continues as George Orwell’s 1984 becomes more of a reality with each passing day. “All told, we are barreling toward a future where every ritual of public life carries implicit consent to be surveilled,” writes Sidney Fussell for The Atlantic.
A new report from Georgetown Law‘s Center on Privacy & Technology (CPT) suggests that Immigration and Customs Enforcement (ICE) may be using the rampant problem of illegal immigration as a type of cover to track and spy on Americans in violation of their Fourth Amendment rights. Three years ago, the center revealed that nearly half of all U.S. adults are already in the FBI’s facial recognition database, which is largely sourced from DMV photos.
