Upgrade 2021: PHI LAB Speakers

Ryan Hamerly

Senior Scientist | NTT Research Physics & Informatics Lab

The Potential of Optical Neural Networks to Overcome Electronic Hardware Limitations

Convolutional neural networks have seen significant advancements over the past 20 years, but further improvements are difficult to come by due to the limitations of modern hardware. Scientists are working to overcome these limitations by integrating optics, with the goal of expanding the capabilities of deep neural networks.

In his talk at Upgrade 2021, the NTT Research Summit, Dr. Ryan Hamerly, Senior Scientist at NTT Research, discussed how the use of optics in computing can overcome the limitations of chip hardware and minimize energy consumption.

Presented at the NTT Research Upgrade 2021 Summit on September 21, 2021.

Logan Wright

Research Scientist | NTT Research Physics & Informatics Lab

How Applying the Backpropagation Algorithm Enables Deep Physical Neural Networks

It’s possible to turn virtually any physical system into a deep neural network capable of performing computations far faster and more efficiently than traditional electronic computers – if you can find the right physical system and apply an effective algorithm.

That was the gist of Dr. Logan Wright’s talk at Upgrade 2021, the NTT Research Summit, during which he discussed a paper he co-authored with Dr. Tatsuhiro Onodera, “Deep physical neural networks trained with backpropagation.” Wright and Onodera are both Research Scientists in the NTT Research Physics and Informatics (PHI) Lab and visiting scientists in the School of Applied and Engineering Physics at Cornell.

Dr. Wright’s work demonstrated how any physical system could be used to create a physical neural network, or PNN. He showed three examples: a mechanical system that consisted of a speaker connected to an oscillating metal plate, a non-linear analog electronic system, and an optical system.

Presented at the NTT Research Upgrade 2021 Summit on September 21, 2021.

Satoshi Kako

Senior Research Scientist | NTT Research PHI Lab

Demo Shows Promise of Coherent Icing Machine Approach to Computing for Complex Problems

Today’s computers are facing a problem: they can’t keep up with the sorts of problems scientists are trying to solve, such as drug development calculations that involve thousands or millions of variables. NTT Research is proposing a solution with a new approach to computing called Coherent Icing Machine (CIM), which lives at the crossroads of physics, neuroscience and computer science.

At Upgrade 2021, Dr. Satoshi Kako, a Senior Research Scientist at NTT Research, demonstrated the capabilities of a CIM implementation on a single FPGA chip. It proved capable of solving a problem involving 1,000 variables at a speed 10 times faster than existing solutions.

Presented at the NTT Research Upgrade 2021 Summit on September 20, 2021.

Martin Fejer

Professor | Stanford

Nonlinear Nanophotonics: Towards Few-Photons Interactions

Martin Fejer discusses the topic Nonlinear Nanophotonics: Towards Few-Photons Interactions.

Presented at the NTT Research Upgrade 2021 Summit on September 21, 2021.

Project Associate Professor | International Research Center for Neurointelligence, The University of Tokyo

Surya Ganguli

Associate Professor | Stanford University 

Statistical Mechanics of High Dimensional Optimization Landscapes in the CIM

Surya Ganguli discusses the topic Statistical Mechanics of High Dimensional Optimization Landscapes in the CIM.

Presented at the NTT Research Upgrade 2021 Summit on September 21, 2021.

Peter McMahon

Assistant Professor of Applied and Engineering Physics | Cornell University

Computing with Physical Systems

Peter McMahon discusses the topic Computing with Physical Systems.

Presented at the NTT Research Upgrade 2021 Summit on September 21, 2021.

Hiroki Takesue

Scientist | NTT Basic Research Lab, Physics & Informatics Lab

Current Status of Coherent Ising machine/LASOLV at NTT Laboratories

Hiroki Takasue discusses the topic Current Status of Coherent Ising Machine/LASOLV at NTT Laboratories.

Presented at the NTT Research Upgrade 2021 Summit on September 21, 2021.

Hidenori Tanaka

Research Group Leader | NTT Research Physics & Informatics Lab

Natural Science of Artificial Neural Networks

Hidenori Tanaka discusses the topic Natural Science of Artificial Neural Networks.

Presented at the NTT Research Upgrade 2021 Summit on September 21, 2021.

Timothee Leleu

Project Associate Professor | International Research Center for Neurointelligence, The University of Tokyo

A Fast, Scalable, and Reconfigurable Simulation Platform for the Coherent Ising Machine

Timothee Leleu discusses the topic A Fast, Scalable, and Reconfigurable Simulation Platform for the Coherent Ising Machine.

Presented at the NTT Research Upgrade 2021 Summit on September 21, 2021.