Research Bits: Dec. 24


Growing multilayered chips Researchers from MIT, Samsung Advanced Institute of Technology, Sungkyunkwan University, and University of Texas at Dallas developed a method to fabricate a multilayered chip with alternating layers of semiconducting material grown directly on top of each other. The approach enables high-performance transistors and memory and logic elements on any random crystalline ... » read more

Research Bits: Dec. 11


Photonic AI processor Researchers from Massachusetts Institute of Technology (MIT), Enosemi, and Periplous developed a fully integrated photonic processor that can perform all the key computations of a deep neural network optically on the chip. The chip is fabricated using commercial foundry processes and uses three layers of devices that perform linear and nonlinear operations. A particula... » read more

Research Bits: Dec. 3


Self-assembly of mixed-metal oxide arrays Researchers from North Carolina State University and Iowa State University demonstrated a technique for self-assembling electronic devices. The proof-of-concept work was used to create diodes and transistors with high yield and could be used for more complex electronic devices. “Our self-assembling approach is significantly faster and less expensi... » read more

Research Bits: Nov. 25


3D-printed ESD protection Researchers from Lawrence Livermore National Laboratory developed a printable elastomeric silicone foam for electronics packaging that provides both mechanical and electrostatic discharge (ESD) protection. The team used a 3D printing technique called direct ink writing (DIW), an extrusion process in which a paste with controlled rheological properties such as elast... » read more

Research Bits: June 18


Gallium nitride can take the heat Researchers from Massachusetts Institute of Technology (MIT), the UAE's Technology Innovation Institute, Ohio State University, Rice University, and Bangladesh University of Engineering and Technology investigated the performance of ohmic contacts in a gallium nitride (GaN) device at extremely high temperatures, such as those that would be required for devices... » read more

Research Bits: June 4


Ultra-pure silicon Researchers from the University of Manchester and University of Melbourne developed a technique to engineer ultra-pure silicon that could be used in the construction of high-performance qubit devices that extend quantum coherence times. The highly purified silicon chips house and protect the qubits so they can sustain quantum coherence much longer, enabling complex calcul... » read more

Research Bits: April 30


Sound waves in optical neural networks Researchers from the Max Planck Institute for the Science of Light and Massachusetts Institute of Technology found a way to build reconfigurable recurrent operators based on sound waves for photonic machine learning. They used light to create temporary acoustic waves in an optical fiber, which manipulate subsequent computational steps of an optical rec... » read more

Ultrathin vdW Ferromagnet at Room Temperature (MIT)


A technical paper titled “Current-induced switching of a van der Waals ferromagnet at room temperature” was published by researchers at Massachusetts Institute of Technology (MIT). Abstract: "Recent discovery of emergent magnetism in van der Waals magnetic materials (vdWMM) has broadened the material space for developing spintronic devices for energy-efficient computation. While there has... » read more

A Hypermultiplexed Integrated Tensor Optical Processor (USC, MIT et al.)


A technical paper titled “Hypermultiplexed Integrated Tensor Optical Processor” was published by researchers at the University of Southern California, Massachusetts Institute of Technology (MIT), City University of Hong Kong, and NTT Research. Abstract: "The escalating data volume and complexity resulting from the rapid expansion of artificial intelligence (AI), internet of things (IoT) a... » read more

Efficient Streaming Language Models With Attention Sinks (MIT, Meta, CMU, NVIDIA)


A technical paper titled “Efficient Streaming Language Models with Attention Sinks” was published by researchers at Massachusetts Institute of Technology (MIT), Meta AI, Carnegie Mellon University (CMU), and NVIDIA. Abstract: "Deploying Large Language Models (LLMs) in streaming applications such as multi-round dialogue, where long interactions are expected, is urgently needed but poses tw... » read more

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