Evolution of Deep Learning from Turing machine to Deep Learning next generation
Working Paper CNR-Ircres 4/2022
Evolution of Deep Learning from Turing machine to Deep Learning next generation
Greta Falavigna
CNR-IRCrES, National Research Council of Italy – Research Institute on Sustainable Economic Growth, Strada delle Cacce 73, 10135 Torino (TO) Italy
corresponding author: greta.falavigna@ircres.cnr.it
Abstract
Despite the increasing of research papers, methodological developments, and applications of Deep Learning algorithms, a paper on the history of these models is still missing. In this study, it is provided a biography of Deep Learning, starting from its origin to this (very) moment considering the most relevant results.
The history of Deep Learning is particularly interesting; indeed, as probably never before, it was born out of the interaction of different expertise, and now we are often in touch with technologies based on these algorithms. Indeed, the first definition of neuron has been possible only for the synergy between a psychologist/neuro-anatomist, McCulloch, and a mathematician, Pitts. Together they laid the foundations for what we now call Deep Learning.
In this paper, the history with the most significant intuitions is shown, as, to our knowledge, it has never been done in previous literature. This work aims at covering this lack, presenting a chronological history of the evolution from the first neuron to today’s sophisticated Evolutionary Computing, and providing the most relevant references for each addressed issue.
Keywords: territorial innovation system, technology, technology innovation, R&D, startups, venture capital, industrial platforms.
DOI: 10.23760/2421-7158.2022.004
How to Cite this Working Paper
Falavigna, G. (2022). Evolution of Deep Learning from Turing machine to Deep Learning next generation. (CNR-IRCrES Working Paper 4/2022). Torino: Istituto di Ricerca sulla Crescita Economica Sostenibile. Available at: http://dx.doi.org/10.23760/2421-7158.2022.004