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Harvard’s ultra-thin chip could revolutionize quantum computing

Researchers at Harvard have created a groundbreaking metasurface that can replace bulky and complex optical components used in quantum computing with a single, ultra-thin, nanostructured layer. This innovation could make quantum networks far more scalable, stable, and compact. By harnessing the power of graph theory, the team simplified the design of these quantum metasurfaces, enabling them to generate entangled photons and perform sophisticated quantum operations — all on a chip thinner than a human hair. It's a radical leap forward for room-temperature quantum technology and photonics.

A human-inspired pathfinding approach to improve robot navigation

For robots to be successfully introduced in a wider range of real-world settings, they should be able to safely and reliably navigate rapidly changing environments. While roboticists and computer scientists have introduced a wide range of computational techniques for robot navigation over the past decades, many of them were found to perform poorly in environments that are dynamic, cluttered or characterized by narrow pathways.

Google’s deepfake hunter sees what you can’t—even in videos without faces

AI-generated videos are becoming dangerously convincing and UC Riverside researchers have teamed up with Google to fight back. Their new system, UNITE, can detect deepfakes even when faces aren't visible, going beyond traditional methods by scanning backgrounds, motion, and subtle cues. As fake content becomes easier to generate and harder to detect, this universal tool might become essential for newsrooms and social media platforms trying to safeguard the truth.

Review delineates approaches to human-robot interaction using biosignals

A new review paper on the latest trends and advancements in intuitive Human-Robot Interaction (HRI) using bio-potential and bio-impedance has been published in the journal Nature Reviews Electrical Engineering. The joint research team was led by Professor Jung Kim of KAIST Department of Mechanical Engineering and Professor Min-kyu Je of the Department of Electrical and Electronic Engineering.

Innovative robotic slip-prevention method could bring human-like dexterity to industrial automation

A new slip-prevention method has been shown to improve how robots grip and handle fragile, slippery or asymmetric objects, according to a University of Surrey–led study published in Nature Machine Intelligence. The innovation could pave the way for safer, more reliable automation across industries ranging from manufacturing to health care.

A simple twist fooled AI—and revealed a dangerous flaw in medical ethics

Even the most powerful AI models, including ChatGPT, can make surprisingly basic errors when navigating ethical medical decisions, a new study reveals. Researchers tweaked familiar ethical dilemmas and discovered that AI often defaulted to intuitive but incorrect responses—sometimes ignoring updated facts. The findings raise serious concerns about using AI for high-stakes health decisions and underscore the need for human oversight, especially when ethical nuance or emotional intelligence is involved.

Researchers develop new method to boost industrial robot dynamics modeling efficiency

A research team from the Ningbo Institute of Materials Technology and Engineering (NIMTE) of the Chinese Academy of Sciences has developed a new method to enhance the efficiency of dynamics modeling for industrial robots, tackling long-standing bottlenecks in real-time torque computation.

New scrubbing robot could contribute to automation of household chores

While the advent of robotic systems that can complete household chores has been widely anticipated, those commercially released so far are primarily robot vacuums that autonomously clean the floor. In contrast, robots that can reliably clean surfaces, tidy up, cook or perform other tasks in home environments are either too expensive or have not yet reached the market.
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