Category Physics

Imagine a robot that can walk, without electronics, and only with the addition of a cartridge of compressed gas, right off the 3D-printer. It can also be printed in one go, from one material.

That is exactly what roboticists have achieved in robots developed by the Bioinspired Robotics Laboratory at the University of California San Diego. They describe their work in an advanced online publication in the journal Advanced Intelligent Systems.

To achieve this feat, researchers aimed to use the simplest technology available: a desktop 3D-printer and an off-the-shelf printing material...

How many robots does it take to screw in a lightbulb? The answer is more complicated than you might think. New research from Northeastern University upends the riddle by making a robot that is both flexible and sensitive enough to handle the lightbulb, and strong enough to apply the necessary torque.

“What we found is that by thinking about the bodies of robots and how we can make new materials for them, we can actually make a robot that has the benefits of both rigid and soft robots,” says Jeffrey Lipton, assistant professor of mechanical and industrial engineering at Northeastern.

“It’s flexible...

Artificial intelligence (AI) systems promise transformative advancements, yet their growth has been limited by energy inefficiencies and bottlenecks in data transfer. Researchers at Columbia Engineering have unveiled a groundbreaking solution: a 3D photonic-electronic platform that achieves unprecedented energy efficiency and bandwidth density, paving the way for next-generation AI hardware.

The study, “3D Photonics for Ultra-Low Energy, High Bandwidth-Density Chip Data Links,” led by Keren Bergman, Charles Batchelor Professor of Electrical Engineering, is published in Nature Photonics.

The research details a pioneering method that integrates photonics with advanced complementary-metal- oxide-semiconductor (CMOS) electronics to redef...

So-called “memristors” consume extremely little power and behave similarly to brain cells. Researchers from Jülich, led by Ilia Valov, have now introduced novel memristive components that offer significant advantages over previous versions: they are more robust, function across a wider voltage range, and can operate in both analog and digital modes. These properties could help address the problem of “catastrophic forgetting,” where artificial neural networks abruptly forget previously learned information.

The problem of catastrophic forgetting occurs when deep neural networks are trained for a new task...