Lifeboat Foundation

Millions of faces and car license plates were stored in a sizable Chinese database that was publicly accessible for months before it was silently removed in August.

A tech business called Xinai Electronics with headquarters in Hangzhou on China’s east coast is the owner of the disclosed data. In China, the firm creates systems for regulating entry for people and cars to workplaces, schools, construction sites, and parking lots. Its website boasts the use of facial recognition for a variety of uses beyond building access, including personnel management, such as payroll, monitoring employee attendance and performance, while its cloud-based vehicle license plate recognition system enables drivers to pay for parking in unattended garages that are managed by staff remotely.

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By managing and automating many of the steps involved in continual learning, Janus is helping Amazon’s latest robots adapt to a changing environment.

Are you ready to put mini robots in your mouth?

Do you get lazy about brushing your teeth? Well, soon microbots could do the whole thing for you. A multidisciplinary team at the University of Pennsylvania has created a novel automated way to perform brushing and flossing through robotics, according to a press release published by the institution last month.

The development could be particularly useful for those who lack the manual dexterity to clean their teeth effectively themselves.

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With all our global instability and still-nascent grasp on tech, adding in ASI would be lighting a match next to a fireworks factory.

Why do we think that reducing risks from AI is one of the most pressing issues of our time? There are technical safety issues that we believe could, in the worst case, lead to an existential threat to humanity.

Human languages are notoriously complex, and linguists have long thought it would be impossible to teach a machine how to analyze speech sounds and word structures in the way human investigators do.

But researchers at MIT, Cornell University, and McGill University have taken a step in this direction. They have demonstrated an artificial intelligence system that can learn the rules and patterns of human languages on its own.

When given words and examples of how those words change to express different grammatical functions (like tense, case, or gender) in one language, this machine-learning model comes up with rules that explain why the forms of those words change. For instance, it might learn that the letter “a” must be added to end of a word to make the masculine form feminine in Serbo-Croatian.

How to create a Robotic Arm under the control of the new KRIA Robotic Starter Kit By Adam Taylor.

Researchers have developed a new chip-based beam steering technology that provides a promising route to small, cost-effective, and high-performance lidar systems. Lidar, or light detection and ranging, uses laser pulses to acquire 3D information about a scene or object. It is used in a wide range of applications such as autonomous driving, 3D holography, biomedical sensing, free-space optical communications, and virtual reality.

“Optical beam steering is a key technology for lidar systems, but conventional mechanical-based beam steering systems are bulky, expensive, sensitive to vibration, and limited in speed,” said research team leader Hao Hu from the Technical University of Denmark. “Although devices known as chip-based optical phased arrays (OPAs) can quickly and precisely steer light in a non-mechanical way, so far, these devices have had poor beam quality and a field of view typically below 100 degrees.”

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