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Machine Learning and Deep Learning Patentable Developments and Applications for Cost Reduction in Business and Industrial Organizations

ANWESH: International Journal of Management & Information Technology

Volume 5 Issue 2

Published: 2020
Author(s) Name: Hugo César Enríquez García and Edith Roque Huerta | Author(s) Affiliation: Univ. Center for Economic and Managerial Sciences, Univ. of Guadalajara, Zapopan, Jalisco, Mexico.
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The objective of this research is to determine the feasibility of cost reduction through the use of technologies based on two of the most relevant recent branches of Artificial Intelligence (AI), such as Machine Learning (ML) and Deep Learning (DL), with such cost reduction it is expected that companies or industries can obtain a competitive and comparative advantage. Likewise, emphasis will be placed on locating Mexican private or public organizations that have developed and registered patents that have helped them to reduce costs or be more competitive at a business or industry level. The materials and methods carried out will be 1) A literature review. 2) A documentary review in databases of the Mexican Institute of the Intellectual Property (IMPI), with it will be announced the quantity of investigations, developments and most recent applications for the reduction of costs, and finally to know the position and competences of Mexico at the moment of patenting technologies based on ML and DL. It is concluded that in several business and industrial areas more and more patents, ML & DL developments applications are being used and registered for cost reduction, however in Mexico there is a lack of R&D contribution in this type of technological developments, since there is only one patent registered by a university.

Keywords: Business, Cost reduction, Deep learning, Industries, Machine learning, Patents.

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