Accelerating AI tasks while preserving data security
The SecureLoop search tool efficiently identifies secure designs for hardware that can boost the performance of complex AI tasks, while requiring less energy.
The SecureLoop search tool efficiently identifies secure designs for hardware that can boost the performance of complex AI tasks, while requiring less energy.
At MIT, a driving force in the chip-making industry discusses the rise of TSMC and Taiwan as a manufacturing center.
Researchers demonstrate a low-power “wake-up” receiver one-tenth the size of other devices.
In MIT visit, CEO Pat Gelsinger sounds a bullish note on the future of U.S. semiconductor manufacturing.
The Advanced Computing Users Survey, sampling sentiments from 120 top-tier universities, national labs, federal agencies, and private firms, finds the decline in America’s advanced computing lead spans many areas.
19th Microsystems Annual Research Conference reveals the next era of microsystems technologies, along with skiing and a dance party.
The chip, which can decipher any encoded signal, could enable lower-cost devices that perform better while requiring less hardware.
The receiver chip efficiently blocks signal interference that slows device performance and drains batteries.
A wireless technique enables a super-cold quantum computer to send and receive data without generating too much error-causing heat.
Passionate about creating educational opportunities in India, PhD student Siddhartha Jayanti recently explored multiprocessor speed limits, in a paper written in the Indian language Telugu.
Their technique could allow chip manufacturers to produce next-generation transistors based on materials other than silicon.
Researchers have demonstrated directional photon emission, the first step toward extensible quantum interconnects.
New technique significantly reduces training and inference time on extensive datasets to keep pace with fast-moving data in finance, social networks, and fraud detection in cryptocurrency.
A new method uses optics to accelerate machine-learning computations on smart speakers and other low-power connected devices.
The technique could be used to fabricate computer chips that won’t get too hot while operating, or materials that can convert waste heat to energy.