Elon Musk says Tesla’s real-world simulation and video generation are the best in the world, following OpenAI’s launch of the Sora model.
Canadian researchers led by Montreal radiologist Gilles Soulez have developed a novel approach to treat liver tumors using magnet-guided microrobots in an MRI device.
The idea of injecting microscopic robots into the bloodstream to heal the human body is not new. It’s also not science fiction. Guided by an external magnetic field, miniature biocompatible robots, made of magnetizable iron oxide nanoparticles, can theoretically provide medical treatment in a very targeted manner.
Until now, there has been a technical obstacle: the force of gravity of these microrobots exceeds that of the magnetic force, which limits their guidance when the tumor is located higher than the injection site. While the magnetic field of the MRI is high, the magnetic gradients used for navigation and to generate MRI images are weaker.
Through a first-of-its-kind strategic enterprise agreement with Boston Dynamics, Chevron is a leader in the oil and gas industry’s robotics age.
U.S. software giant Microsoft will expand its artificial intelligence (AI) and cloud infrastructure in Spain through an investment of $2.1 billion in the next two years, the company’s Vice Chair and President Brad Smith said in a post on social media site X.
In a new video, 1X’s EVE robots work together in silence in a test environment, performing actions such as sorting mail, handling objects and tidying up a child’s toys.
The Cactus ransomware gang claims they stole 1.5TB of data from Schneider Electric after breaching the company’s network last month.
25MB of allegedly stolen were also leaked on the operation’s dark web leak site today as proof of the threat actor’s claims, together with snapshots showing several American citizens’ passports and non-disclosure agreement document scans.
As BleepingComputer first reported, the ransomware group gained access to the energy management and automation giant’s Sustainability Business division on January 17th.
Recent technological advances have enabled the development of increasingly sophisticated sensors, which can help to advance the sensing capabilities of robots, drones, autonomous vehicles, and other smart systems. Many of these sensors, however, rely on individual cameras, thus the accuracy of the measurements they collect is limited by the cameras’ field of view (FOV).
Researchers at Beihang University in China recently developed a new multi-camera differential binocular vision sensor with a wider FOV that could collect more accurate measurements. This sensor, introduced in a paper published in Optics & Laser Technology, could be integrated into a wide range of devices and smart robotic systems.
“Aiming at the high-precision requirements of environment perception for unmanned aerial vehicle detection, robot navigation, and autonomous driving, inspired by the multi-camera module of mobile phones, we introduced a visual perception mode based on the principle of high-precision binocular vision measurement,” Fuqiang Zhou, co-author of the paper, told Tech Xplore. “This principle involves a central high-resolution camera and peripheral auxiliary cameras that work together.”
