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MIOIR Seminar Series - How small is big enough? Open datasets and the Development of Deep Learning

Manchester Institute of Innovation Research written in white on teal
Dates:4 March 2024
Times:15:30 - 16:30
What is it:Seminar
Organiser:Alliance Manchester Business School
Who is it for:University staff, External researchers, Alumni, Current University students, General public
Speaker:Professor Aldo Geuna
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  • In group "(AMBS) MIoIR seminars and workshops"
  • By Alliance Manchester Business School

Join us for the Manchester Institute of Innovation Research Seminar Series 23/24 with Professor Aldo Geuna from University of Torino, on Monday 04th March at 15:30-16:30, in 9.041 AMBS (Hybrid Event).

You can register to attend online or in-person: https://manchester-institute-of-innovation-research.ticketleap.com/mioir-seminar-series-with-professor-aldo-geuna/

How small is big enough? Open datasets and the Development of Deep Learning

Abstract:

Artificial Intelligence technologies promise to revolutionize the knowledge production process. At the core of one of the most important approaches to AI is a series of Machine Learning techniques known as Deep Learning. Deep Learning has been regarded as a new method of invention and potentially a general-purpose technology in which the next industrial revolution may be based. This paper analyses the emergence of Deep Learning as a technoscientific field, that is, a domain in the middle of scientific enquiry and technical problem-solving. More specifically, it examines the role played by labelled datasets (CIFAR-10 and CIFAR-100) and the funding institute that supported the birth and growth of deep learning, the Canadian Institute for Advanced Research (CIFAR). We carried out a qualitative and quantitative analysis of the impact of CIFAR-10 and CIFAR-100 on the fields of computer vision and object recognition and how this impact relates to development of Deep Learning. We assess both scientific and technological impact. We find that CIFAR-10 was fundamental for the developments which lead to the Deep Learning revolution and still shapes the trajectory of the field. We also show that CIFAR-10 is relevant in teaching Deep Learning techniques, which highlights the profound impact of this technological artifact in the development of the field. The econometric analysis confirms that the CIFAR-10 dataset had a very significant early impact in the literature (citation count) and was and still is relevant for technological development as measured by patent-to-paper citations.

Aldo Geuna is Full Professor of Economic Policy at the Department of Cultures, Politics and Society, University of Torino, Fellow CIFAR, Fellow of the Collegio Carlo Alberto and Senior Research Associate at the Innovation Policy Lab, Munk School of Global Affairs, University of Toronto. He was Visiting Fellow at SIPER, Stanford University, Senior Lecturer at SPRU, University of Sussex, Senior Research Fellow at the Robert Schuman Centre for Advanced Studies, European University Institute and Research Fellow at BETA, Université Louis Pasteur (Strasbourg). He has published several books and articles in refereed journals in the area of economics of science, economics of innovation and science and technology policy. He has had editorial responsibilities in Information Economics and Policy, Italian Economic Journal, Journal of Technology Transfer and Research Policy. He has been a member of various scientific committees, expert groups and panels in Italy, Sweden, the UK as well as for the OECD, the National Academies (US) and the EU. He has been an invited speaker in various European countries, the US, Canada, China and Korea. He taught as invited visiting professor in Chile, France, Italy, Spain and Vietnam.

Speaker

Professor Aldo Geuna

Organisation: University of Torino

  • https://sites.carloalberto.org/geuna/index.html

Travel and Contact Information

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Room 9.041 (Hybrid Event)
Aliiance Manchester Business School
Booth Street West
Manchester

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Holly Crossley

holly.crossley@manchester.ac.uk

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