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Current issue

ELEKTRO 12/2019 was released on December 4th 2019. Its digital version will be available on January 4th 2020.

Topic: Measurement engineering and measuring instruments

Main Article
Innovative process in partial discharge of AC and DC voltage diagnosis

SVĚTLO (Light) 6/2019 was released on December 9th 2019. Its digital version will be available on January 9th 2020.

Professional organizations activities
Light technology konference of Visegrád countries LUMEN V4 2020 – 1st announcement
23rd International conference SVĚTLO – LIGHT 2019
56th Conference of Society for development public lighting in Plzeň
What is new in CIE

Interiors lighting
Halla illuminated new Booking.com offices in Prague centre

Researchers show glare of energy consumption in the name of deep learning

10.06.2019 | Tech Xplore | www.techxplore.com

Wait, what? Creating an AI can be way worse for the planet than a car? Think carbon footprint. That is what a group at the University of Massachusetts Amherst did. They set out to assess the energy consumption that is needed to train four large neural networks.

Deep learning involves processing very large amounts of data. In order to learn something as complex as language, the models have to be large. What price making models obtain gains in accuracy? Roping in exceptionally large computational resources to do so is the price, causing substantial energy consumption.

Deep learning

Researchers reported their findings, that "the process can emit more than 626,000 pounds of carbon dioxide equivalent—nearly five times the lifetime emissions of the average American car (and that includes manufacture of the car itself)."

These models are costly to train and develop—-costly in the financial sense due to the cost of hardware and electricity or cloud compute time, and costly in the environmental sense. The environmental cost is due to the carbon footprint. The paper sought to bring this issue to the attention of NLP researchers "by quantifying the approximate financial and environmental costs of training a variety of recently successful neural network models for NLP."

Read more at Tech Xplore

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