Lightmatter, Inc.

David Walter

Nicholas Christopher Harris

Darius Bunandar

Tomo Lazovich

Martin B Z Forsythe

Ayon Basumallik

David Widemann

Nicholas Dronen

Ludmila Levkova

Lakshmi Nair

Described herein are techniques of training a machine learning model and performing inference using an analog processor. Some embodiments mitigate the loss in performance of a machine learning model resulting from a lower precision of an analog processor by using an adaptive block floating-point representation of numbers for the analog processor. Some embodiments mitigate the loss in performance of a machine learning model due to noise that is present when using an analog processor. The techniques involve training the machine learning model such that it is robust to noise.

Machine learning model training using an analog processor

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Boston, MA, United States of America

David Walter