Llewellynn, Tim and Fernández-Carrobles, M. Milagro and Deniz, Oscar and Fricker, Samuel and Storkey, Amos and Pazos, Nuria and Velikic, Gordana and Leufgen, Kirsten and Dahyot, Rozenn and Koller, Sebastian and Goumas, Georgios and Leitner, Peter and Dasika, Ganesh and Wang, Lei and Tutschku, Kurt (2017) BONSEYES: Platform for Open Development of Systems of Artificial Intelligence: Invited paper. ACM International Conference on Computing Frontiers 2017. pp. 299-304.

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Abstract

The Bonseyes EU H2020 collaborative project aims to develop a platform consisting of a Data Marketplace, a Deep Learning Toolbox, and Developer Reference Platforms for organizations wanting to adopt Artificial Intelligence. The project will be focused on using artificial intelligence in low power Internet of Things (IoT) devices ("edge computing"), embedded computing systems, and data center servers ("cloud computing"). It will bring about orders of magnitude improvements in efficiency, performance, reliability, security, and productivity in the design and programming of systems of artificial intelligence that incorporate Smart Cyber-Physical Systems (CPS). In addition, it will solve a causality problem for organizations who lack access to Data and Models. Its open software architecture will facilitate adoption of the whole concept on a wider scale. To evaluate the effectiveness, technical feasibility, and to quantify the real-world improvements in efficiency, security, performance, effort and cost of adding AI to products and services using the Bonseyes platform, four complementary demonstrators will be built. Bonseyes platform capabilities are aimed at being aligned with the European FI-PPP activities and take advantage of its flagship project FIWARE. This paper provides a description of the project motivation, goals and preliminary work.

Item Type:	Article
Keywords:	Data marketplace; Deep Learning; Internet of things; Smart Cyber; Physical Systems;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	15257
Identification Number:	https://doi.org/10.1145/3075564.3076259
Depositing User:	Rozenn Dahyot
Date Deposited:	18 Jan 2022 11:10
Journal or Publication Title:	ACM International Conference on Computing Frontiers 2017
Publisher:	ACM
Refereed:	Yes
URI:	Organisation
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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