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Innovation Paths for Machine Learning in Robotics [Industry Activities]

Authors :
Freek Stulp
Michael Spranger
Kim Listmann
Stéphane Doncieux
Moritz Tenorth
George Konidaris
Pieter Abbeel
German Aerospace Center (DLR)
Sony AI, Tokyo
Bender GmbH
Institut des Systèmes Intelligents et de Robotique (ISIR)
Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)
Magazino GmbH
Brown University
University of California (UC)
European Project: 951992
Source :
IEEE Robotics and Automation Magazine, IEEE Robotics and Automation Magazine, 2022, 29 (4), pp.141-144. ⟨10.1109/MRA.2022.3213205⟩
Publication Year :
2022
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2022.

Abstract

International audience; Presents interviews conducted with robotics engineers discussing advances in artificial intelligence, with particular use in machine learning. Advances in artificial intelligence (AI), especially in machine learning (ML), are changing the business models of many companies, and creating entirely new ones. Recent research estimates that AI could boost profitability rates by 38% worldwide, leading to an economic boost of €12 trillion across a variety of industries by 2035. This immense number is an accumulation of many smaller numbers, related to the successful deployment of ML at individual companies, including smalland medium-sized enterprises (SMEs) and start-ups.

Details

ISSN :
1558223X and 10709932
Volume :
29
Database :
OpenAIRE
Journal :
IEEE Robotics & Automation Magazine
Accession number :
edsair.doi.dedup.....64fb873b8519918663c1774ea6e4e256