Manufacturing Bits: Jan. 9


Two-photon lithography Lawrence Livermore National Laboratory (LLNL) has extended the capabilities of a high-resolution 3D printing technique called two-photon lithography (TPL). TPL enables the development of 3D-printed objects. LLNL’s technology could enable 3D-printed embedded structures inside the body, such as stents, joint replacements or bone scaffolds. It could also one day be ... » read more

Blockchain: Hype, Reality, Opportunities


Blockchain buzz has reached deafening levels, and its proponents say we haven’t heard anything yet. The blockchain-enabled transformations they describe make the Internet revolution look almost trivial. Critics argue that too many people drank the blockchain Kool-Aid. Outside the cryptocurrency arena, they say that blockchain amounts to little more than some really slick slideware. The ... » read more

System Bits: Jan. 2


Robots imagine their future to learn By playing with objects and then imagining how to get the task done, UC Berkeley researchers have developed a robotic learning technology that enables robots to figure out how to manipulate objects they have never encountered before. The team expects this technology could help self-driving cars anticipate future events on the road and produce more intel... » read more

System Bits: Dec. 19


Controlling qubits for quantum computing In a major step toward making a quantum computer using everyday materials, a team led by researchers at Princeton University has reported they’ve constructed a key piece of silicon hardware capable of controlling quantum behavior between two electrons with extremely high precision. The team said they have constructed a gate that controls interactio... » read more

The Week in Review: IoT


Products/Services NXP Semiconductors is partnering with Alibaba Cloud, the cloud computing business unit of Alibaba Group, to develop secure smart devices for edge computing. The companies will also work together on Internet of Things offerings. AliOS, the Alibaba IoT operating system, has been integrated with NXP’s application processors, microcontrollers, and Layerscape multicore processor... » read more

System Bits: Dec. 12


Increasing performance scaling with packageless processors Demand for increasing performance is far outpacing the capability of traditional methods for performance scaling. Disruptive solutions are needed to advance beyond incremental improvements. Traditionally, processors reside inside packages to enable PCB-based integration. However, a team of researchers from the Department of Electrical ... » read more

Manufacturing Bits: Dec. 5


Intel vs. GlobalFoundries At the IEEE International Electron Devices Meeting (IEDM) this week, GlobalFoundries and Intel will square off and present papers on their new logic processes. Intel will present more details about its previously-announced 10nm finFET technology, while GlobalFoundries will discuss its 7nm finFET process. As expected, Intel and GlobalFoundries will use 193nm immersi... » read more

System Bits: Dec. 5


[caption id="attachment_429586" align="aligncenter" width="300"] Vivienne Sze, an associate professor of electrical engineering and computer science at MIT. Source: MIT[/caption] Building deep learning hardware A new course at MIT is bringing together both electrical engineering and computer science to educate student in the highly sought after field of deep learning. Vivienne Sze, an assoc... » read more

System Bits: Nov. 21


MIT-Lamborghini to develop electric car Members of the MIT community were recently treated to a glimpse of the future as they passed through the Stata Center courtyard as the Lamborghini Terzo Millenio (Third Millennium) was in view, which is an automobile prototype for the third millennium. [caption id="attachment_429209" align="alignnone" width="300"] Lamborghini is relying on MIT to make i... » read more

System Bits: Nov. 7


Exposing logic errors in deep neural networks In a new approach meant to brings transparency to self-driving cars and other self-taught systems, researchers at Columbia and Lehigh universities have come up with a way to automatically error-check the thousands to millions of neurons in a deep learning neural network. Their tool — DeepXplore — feeds confusing, real-world inputs into the ... » read more

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