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New Hardware Integrates Mechanical Devices into Quantum Tech

Stanford University researchers have developed a key experimental device for future quantum physics-based technologies that borrows a page from current, everyday mechanical devices. Reliable, compact, durable, and efficient, acoustic devices harness mechanical motion to perform useful tasks. A prime example of such a device is the mechanical oscillator. When displaced by a force – like sound, for instance – components of the device begin moving back-and-forth about their original position. Creating this periodic motion is a handy way to keep time, filter signals, and sense motion in ubiquitous electronics, including phones, computers, and watches. https://www.semiconductor-digest.com/new-hardware-integrates-mechanical-devices-into-quantum-tech/

How to Make the Universe Think for Us

Inside a soundproofed crate sits one of the world’s worst neural networks. After being presented with an image of the number 6, it pauses for a moment before identifying the digit: zero. Peter McMahon, the physicist-engineer at Cornell University who led the development of the network, defends it with a sheepish smile, pointing out that the handwritten number looks sloppy. Logan Wright, a postdoc visiting McMahon’s lab from NTT Research, assures me that the device usually gets the answer right, but acknowledges that mistakes are common. “It’s just this bad,” he said. https://www.quantamagazine.org/how-to-make-the-universe-think-for-us-20220531/

HPC Career Notes: May 2022 Edition

NTT Research, Inc., a division of NTT, appointed Dr. Al Emondi as its head of partner strategy. Emondi joined NTT Research in March 2022 on a contract basis as part of its leadership advisory team. He is also president and chief executive officer of Piontier, LLC, a technology development and neurotech product line consultancy. https://www.hpcwire.com/2022/05/02/hpc-career-notes-may-2022-edition/

Former DARPA Program Manager Dr. Al Emondi Named NTT Head of Partner Strategy

An organizational and technology leader, Dr. Emondi joined NTT Research last month on a contract basis as part of its leadership advisory team, with responsibilities that include growth and research partner opportunities, strategic project and program support, partner enablement and value, and research investments. Dr. Emondi is also President and CEO of Piontier, LLC, a technology development and neurotech product line consultancy. He was previously a program manager for the Defense Advanced Research Projects Agency (DARPA) and CTO of the U.S. Naval Information Warfare Center (NAVWAR) Atlantic. Dr. Emondi received his M.S. in Electrical Engineering and Ph.D. in neuroscience from Syracuse University. https://insidehpc.com/2022/04/former-darpa-program-manager-dr-al-emondi-named-ntt-head-of-partner-strategy/

MIT AI Hardware Program Aims To Lead in Artificial Intelligence Technology Development

The MIT AI Hardware Program is a new academia and industry collaboration aimed at defining and developing translational technologies in hardware and software for the AI and quantum age. A collaboration between the MIT School of Engineering and MIT Schwarzman College of Computing, involving the Microsystems Technologies Laboratories and programs and units in the college, the cross-disciplinary effort aims to innovate technologies that will deliver enhanced energy efficiency systems for cloud and edge computing. https://scitechdaily.com/mit-ai-hardware-program-aims-to-lead-in-artificial-intelligence-technology-development/

Deep physical neural networks trained with backpropagation

Deep-learning models have become pervasive tools in science and engineering. However, their energy requirements now increasingly limit their scalability. Deep-learning accelerators aim to perform deep learning energy-efficiently, usually targeting the inference phase and often by exploiting physical substrates beyond conventional electronics. Approaches so far have been unable to apply the backpropagation algorithm to train unconventional novel hardware in situ. The advantages of backpropagation have made it the de facto training method for large-scale neural networks, so this deficiency constitutes a major impediment.  https://www.nature.com/articles/s41586-021-04223-6

Physics of Quantum Electronics (PQE)-2022 Conference Honors NTT Research PHI Lab Director Yoshihisa Yamamoto with Willis E. Lamb Award

Physics of Quantum Electronics (PQE) Conference has named Yoshihisa Yamamoto, NTT Research Physics & Informatics (PHI) Lab Director and Emeritus Professor of Applied Physics and Electrical Engineering at Stanford University, one of the three winners of the Willis E. Lamb Award for Laser Science and Quantum Optics. The award was presented on January 12 at the PQE-2022 Winter Colloquium in Snowbird, Utah. https://quantumhermit.com/physics-of-quantum-electronics-pqe-2022-conference-honors-ntt-research-phi-lab-director-yoshihisa-yamamoto-with-willis-e-lamb-award/

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