Low-power, ultra-fast deep learning neuromorphic chip for unmanned aircraft systems, Phase I

Metadata Updated: May 2, 2019

Artificial Intelligence (AI) is driving the fourth industrial revolution as well as permeating every aspect of our day-to-day life. From big data analysis to language analysis and real time translation, from speech recognition to image recognition. The latter is a powerful and quite general application with a scope that spans from medical imaging to autonomous driving and to military applications. Mentium Technologies Inc., spun from a UC Santa Barbara research lab in the Electrical and Computer Engineering department is committed to embrace the AI revolution strong of the experience of its team in the neuromorphic hardware for AI. Indeed, we will develop a neuromorphic chip able to do higher than real-time image recognition and/or object classification on board the UAS. The chip will use 1/100th of the energy while reaching 100x in speed compared to state of the art. The team already had demonstrated 1000x and 1/1000th energy consumption in a smaller scale experimental demo. From this experience UCSB has a patented technology licensed by Mentium Technologies Inc. thanks to this technology and its develpment within this project, the Neuromorphic Chip will empower the UAS with Cognitive functions enabling autonomous guidance, decision making and complex image processing, while keeping the power consumption low.

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Public: This dataset is intended for public access and use. License: U.S. Government Work

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Metadata Created Date August 1, 2018
Metadata Updated Date May 2, 2019

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Harvested from NASA Data.json

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Resource Type Dataset
Metadata Created Date August 1, 2018
Metadata Updated Date May 2, 2019
Publisher Space Technology Mission Directorate
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Maintainer Email
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Harvest Source Title NASA Data.json
Data First Published 2017-12-01
Homepage URL https://techport.nasa.gov/view/93616
License http://www.usa.gov/publicdomain/label/1.0/
Data Last Modified 2018-07-19
Program Code 026:027
Source Datajson Identifier True
Source Hash 2cec7689ab078fdfa6b5a1c3c78d30f220b70919
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