Researchers from CSIRO’s Data61, the data and digital specialist arm of Australia’s national science agency, have developed a world-first set of techniques to effectively ‘vaccinate’ algorithms against adversarial attacks, a significant advancement in machine learning research.
Anyone who tells you the robot apocalypse is upon us—that the machines will not stop stealing our jobs, that they are gearing up to chase us through the streets while doing backflips and fighting off stick-wielding humans—has never tried to program a robot. It’s difficult to get a machine to do so much as move an arm, which requires the precise control and coordination of joint angles and torque.
The difficulty of programming robots is a problem that Facebook, of all companies, wants to fix. Today the social network continues its unlikely dive into robotics by open-sourcing a new robot framework, known as PyRobot, that could simplify the way researchers program their machines, and could even make it easier for non-robotics types to jump into the field. If programming robots has so far been something like wading through a command-line interface, PyRobot promises to be like gliding through the sleekness of macOS. At least, that’s the hope: Many others have tried and failed to do this kind of thing.
Understanding electrons’ intricate behavior has led to discoveries that transformed society, such as the revolution in computing made possible by the invention of the transistor.
Dishwashers already make our washing automated. This robot uses AI scanners for extra cleanliness.
A Southern California police force is welcoming a robot to the department. Huntington Park police say “HP RoboCop” will provide 360-degree high-definition video footage. (June 18)
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A team of researchers from Carnegie Mellon University, in collaboration with the University of Minnesota, has made a breakthrough in the field of noninvasive robotic device control. Using a noninvasive brain-computer interface (BCI), researchers have developed the first-ever successful mind-controlled robotic arm exhibiting the ability to continuously track and follow a computer cursor.
Being able to noninvasively control robotic devices using only thoughts will have broad applications, in particular benefiting the lives of paralyzed patients and those with movement disorders.
BCIs have been shown to achieve good performance for controlling robotic devices using only the signals sensed from brain implants. When robotic devices can be controlled with high precision, they can be used to complete a variety of daily tasks. Until now, however, BCIs successful in controlling robotic arms have used invasive brain implants. These implants require a substantial amount of medical and surgical expertise to correctly install and operate, not to mention cost and potential risks to subjects, and as such, their use has been limited to just a few clinical cases.
The upgrades include changes to make AI programming simpler—and to speed up powerful machines for specific AI tasks.
The news: The International Supercomputing Conference (ISC) kicked off in Frankfurt yesterday with the release of the latest list of the 500 most powerful supercomputers in the world. US machines still top the ranking, but China has the most computers on the list (219 versus 116 for the US).
Supercomputers have already turbocharged some AI applications. For example. the US’s Summit supercomputer (pictured above), which leads the Top 500, has already run a complex machine-learning model for climate research faster than any other machine.
IoT has arrived on the factory floor with the force of Kool-Aid Man exploding through walls.
