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Bruce G. Cameron. Jouni, Mohammad, S.M. Massachusetts Institute of Technology System Design and Management Program. Massachusetts Institute of Technology. Engineering and Management Program System Design and Management Program. Massachusetts Institute of Technology. Integrated Design and Management Program 2018-03-12T19:29:10Z 2018-03-12T19:29:10Z 2017 2017 http://hdl.handle.net/1721.1/114083 1027216374 Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, 2017. Cataloged from PDF version of thesis. Includes bibliographical references (pages 101-104). With the recent resurgence of Machine Learning and Artificial Intelligence as a competitive advantage in product development, technical executives and managers are interested in learning what it would take to build intelligent platforms that can leverage these advances. In addition, they wish to produce cost estimates for developing such platforms. The goal of this thesis is to develop a reference architecture for an intelligent platform and an associated costing model that allows technical managers to understand the components needed to deliver such a platform and estimate the cost of each module, estimate the cost of the overall architecture, and enable what-if analysis to understand the cost tradeoffs. The intent is not to provide the values of the variables in the model, but to develop a cost model that will enable interested parties to plug in their estimated values for each factor and generate a forecast of the build cost. by Mohammad Jouni. S.M. in Engineering and Management 104 pages eng Massachusetts Institute of Technology MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 Engineering and Management Program. Integrated Design and Management Program. System Design and Management Program. Reference architecture and cost estimation model for building intelligent platforms Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="b01b0406-6099-4564-bd71-ed1b7ca3a3e4"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Reference architecture and cost estimation model for building intelligent platforms</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2017</PublicationDate> <Authors> <Author> <DisplayName>Jouni, Mohammad, S.M. Massachusetts Institute of Technology</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Engineering and Management Program.</Keyword> <Keyword>Integrated Design and Management Program.</Keyword> <Keyword>System Design and Management Program.</Keyword> <Abstract>With the recent resurgence of Machine Learning and Artificial Intelligence as a competitive advantage in product development, technical executives and managers are interested in learning what it would take to build intelligent platforms that can leverage these advances. In addition, they wish to produce cost estimates for developing such platforms. The goal of this thesis is to develop a reference architecture for an intelligent platform and an associated costing model that allows technical managers to understand the components needed to deliver such a platform and estimate the cost of each module, estimate the cost of the overall architecture, and enable what-if analysis to understand the cost tradeoffs. The intent is not to provide the values of the variables in the model, but to develop a cost model that will enable interested parties to plug in their estimated values for each factor and generate a forecast of the build cost.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>