Power/Performance Bits: Oct. 17


Harvesting body heat Researchers at the Georgia Institute of Technology developed a flexible, wearable thermoelectric generator that can harvest energy from body heat to power simple biosensors. Thermoelectric generators have been available for decades, but standard designs use inflexible inorganic materials that are too toxic for use in wearable devices. The team's device uses thousands... » read more

System Bits: Sept. 12


Neural network cautionary tale As machine learning and neural networks proliferate widely today, there is a need to exercise caution in how they are employed, according to Stanford University researchers Michal Kosinki and Yilun Wang. In a study conducted recently, they have shown that deep neural networks can be used to determine the sexual orientation of a person, and caution that this ma... » read more

Toward Defining Qubits


Quantum computing, by many accounts the future of high-performance computing, will be blazing fast, state-dependent, and it will require extremely cold operating temperatures. But beyond some general areas of agreement, comparing progress made by companies or different research groups is confusing. What's missing is a simple nomenclature to define some of the basic technology used in quantum... » read more

Power/Performance Bits: Sept. 5


Energy-harvesting yarn Researchers at the University of Texas at Dallas and Hanyang University in South Korea developed a carbon nanotube yarn that generates electricity when stretched or twisted. Possible applications for the so-called "twistron" yarns include harvesting energy from the motion of ocean waves or from temperature fluctuations. When sewn into a shirt, these yarns served as a sel... » read more

System Bits: Aug. 29


Could video goggles, and a tiny implant cure blindness? Incredibly, the world of medical research is on the verge of curing blindness. Similar to cochlear implants for deaf people, Stanford University scientists and engineers are developing new devices to this end, including a bionic vision system based on photovoltaic implants, which is awaiting approval for human clinical trials in Europe. A... » read more

System Bits: Aug. 8


Improving robot vision, virtual reality, self-driving cars In order to generate information-rich images and video frames that will enable robots to better navigate the world and understand certain aspects of their environment, such as object distance and surface texture, engineers at Stanford University and the University of California San Diego have developed a camera that generates 4D images... » read more

System Bits: July 25


The language of glove In a development that allows the gestures in American Sign Language to be decoded, University of California San Diego researchers have developed a smart glove that also has application in virtual and augmented reality to telesurgery, technical training and defense. [caption id="attachment_232228" align="alignnone" width="300"] "The Language of Glove": a smart glove that ... » read more

Manufacturing Bits: July 11


China’s storage ring for EUV A group of researchers are banding together to propel the development of a storage ring technology that may one day be used as a power source for extreme ultraviolet (EUV) lithography. The collaboration includes five institutions. Researchers have organized an informal collaboration or study group with plans to develop a storage ring for EUV based on a techno... » read more

Power/Performance Bits: July 11


3D chip integrates computing, storage Researchers at Stanford University and MIT developed a prototype 3D chip that integrates computation and data storage, based on carbon nanotubes and resistive RAM (RRAM) cells. The researchers integrated over 1 million RRAM cells and 2 million carbon nanotube FETs, making what the team says is the most complex nanoelectronic system ever made with emergi... » read more

System Bits: July 11


An algorithm to diagnose heart arrhythmias with cardiologist-level accuracy To speed diagnosis and improve treatment for people in rural locations, Stanford University researchers have developed a deep learning algorithm can diagnose 14 types of heart rhythm defects better than cardiologists. The algorithm can sift through hours of heart rhythm data generated by some wearable monitors to f... » read more

← Older posts