System Bits: Aug. 15


Machine-learning system for smoother streaming To combat the frustration of video buffering or pixelation, researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed “Pensieve,” an artificial intelligence system that uses machine learning to pick different algorithms depending on network conditions thereby delivering a higher-quality streaming exp... » 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: Aug. 1


Quantum Computing Takes A Step Forward UCLA physicists have developed a technique for measuring and controlling the energy differences of electron valley states in silicon quantum dots, which they view as a key component of quantum computing. Joshua Schoenfield, a UCLA graduate student and one of the paper's authors, explained that "an individual qubit can exist in a complex wave-like m... » 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

System Bits: July 18


Melanoma predicted from images with a high degree of accuracy by neural network model The poke and punch of traditional melanoma biopsies could be avoided in the near future, thanks to work by UC Santa Barbara researchers. UCSB undergrad Abhishek Bhattacharya is using the power of artificial intelligence to help people ascertain whether that new and strange mark is, in fact, the deadly skin... » 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

System Bits: July 3


VW emissions tests cheat code found A team of researchers from UC San Diego, Ruhr University along with an independent researcher has uncovered the mechanism that Volkswagen used to circumvent U.S. and European emission tests over a period of at least six years before the EPA put the company on notice in 2015 for violating the Clean Air Act. The researchers found the code that allowed onboa... » read more

System Bits: June 27


Entangling photons for bug-proof communication With the increasing processing power of computers, conventional encryption of data is becoming increasingly insecure, reminded Fraunhofer researchers that are proposing one solution is coding with entangled photons. The team is developing a quantum coding source that allows the transport of entangled photons from satellites, expected to be an impo... » read more

System Bits: June 20


The case against general-purpose processors With a large number of emerging applications such as implantables, wearables, printed electronics, and IoT have ultra-low area and power constraints, and these applications relying on ultra-low-power general purpose microcontrollers and microprocessors, there are drawbacks, researchers at the University of Illinois and the University of Minnesota rem... » read more

System Bits: June 13


Nimble-fingered robots enabled by deep learning Grabbing awkwardly shaped items that humans regularly pick up daily is not so easy for robots, as they don’t know where to apply grip. To overcome this, UC Berkeley researchers have a built a robot that can pick up and move unfamiliar, real-world objects with a 99% success rate. Berkeley professor Ken Goldberg, postdoctoral researcher Jeff M... » read more

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