Machine Learning and Cognitive Computing: A Proposed Framework to Navigate the Opportunities By Ajay Bhilegaonkar M.S. Electrical Engineering University of Texas Submitted to the System Design and Management Program in Partial Fulfillment of the Requirements for the Degree of Master of Science in Engineering and Management at the MASSACHUSETS INSTITUTE Massachusetts Institute of Technology OF TECHNOLOGY June 2016 OCT 26 2016 C 2016 Ajay Bhilegaonkar LIBRARIES All rights reserved ARCHVES The author hereby grants to MIT permission to reproduce and to distribute publicly paper and electronic copies of this thesis document in whole or in part in any medium now known or hereafter created. Signature of Author .Signature redacted \j 'JAjay Bhilegaonkar System D esign and Management Program 'Signature redacted 06 May 2016 Certified by Jeanne Ross Thesis Su ech Qctor a Principal Research Scientist Center for Info stems Rese , MI7Sl9In/Ichool of Management Accepted by -Signature red acted- Patrick Hale Director, System Design & Management Program Machine Learning and Cognitive Computing: A Proposed Framework to Navigate the Opportunities By Ajay Bhilegaonkar Submitted to the System Design and Management Program on February, 2016 in Partial Fulfillment of the Requirements for the Degree of Master of Science in Engineering and Management Abstract Machine Learning and Cognitive Computing universe is buzzing again. Recent significant events are special. There is also talk about beginning of a general purpose "Smart Machine Age" Advances in computing power, storage capacity and machine learning / cognitive computing technologies have a gained critical mass. This combination is driving significant growth and heavy investments. Cognitive computing is coming of age, the market is experiencing exponential growth and there are literally thousands of startups competing to seize the opportunities and hundreds of products hitting the market every quarter. Businesses definitely need to pay attention. But for a business professional, there is so much happening out there that, it is extremely hard to decide which way to turn. CC/ML opportunities may have huge potential to improve business performance or there may be opportunities to waste money. This is a major concern for large businesses and business professionals. This thesis aims to develop an end to end framework to navigate CC/ML opportunities. The framework will guide a business professional to navigate the complex landscape of CC/ML and arrive at a solution approach recommendation. Thesis Advisor: Jeanne Ross Title: Research Director and Principal Research Scientist Center for Information Systems Research, MIT Sloan School of Management 2 This page left intentionally blank. 3 Acknowledgements I would like to express my sincere gratitude towards my Thesis Advisor Dr. Jeanne Ross. This work would not have been possible without her guidance and advice. I would like to sincerely thank SDM Director Patrick Hale for giving me this opportunity to participate in this program. Thanks to all the professors and students at MIT, who I learned form. Thanks to my wife for her support and patience throughout this program. I would also like to thank my family for encouragement. 4 This page left intentionally blank. 5 Table of Contents Chapter 1. Introduction...................................................................................................................8 1.1 Shifting paradigm in CC/M L Universe ............................................................................... 8 1.2 Hype and Excitem ent in CC/M L is evident ......................................................................... 8 1.3 Recent growth of the CC/ M L m arket is explosive ............................................................ 9 When research from Gartner 5'' and IDC6 is synthesized, following list emerges:.. 12 1.4 Research M otivation ...................................................................................................... 12 1.5 Thesis Statem ent & Prim ary Research Objectives ......................................................... 13 Chapter 2. The State of the Art of Artificial Intelligence / Cognitive Computing / Machine Le a rn in g ......................................................................................................................................... 1 6 2.1 Artificial Intelligence............................................................................................................ 17 2.2 Cognitive Com puting ........................................................................................................... 18 2.3 Davenport Cognitive Com puting Categories'................................................................... 18 2.4 M achine Learning................................................................................................................21 2.5 Tenets of machine Learning8 ... ..... ..... .. .. .. ... ..... ..... 21 2.6 Learning M echanism s for M achine Learning .................................................................. 22 2.7 Supervised Learning ............................................................................................................ 24 2.8 Sim ple exam ple of supervised learning ........................................................................... 24 2.9 Anthom orphizing Technology adds to confusion............................................................ 26 Chapter 3 CC/ M L Use Cases .................................................................................................... 27 U se C a se 1 ................................................................................................................................. 2 7 U se C a se 2 ................................................................................................................................. 2 8 U se C a se 3 ................................................................................................................................. 2 8 U se C a se 4 ................................................................................................................................. 2 9 Use Case 5 ................................................................................................................................. 30 U se C a se 6 ................................................................................................................................. 3 0 U se C a se 7 ................................................................................................................................. 3 1 U se C a se 8 ................................................................................................................................. 3 1 U se C a se 9 ................................................................................................................................. 3 2 Use Case 10...............................................................................................................................32 Use Case 11...............................................................................................................................33 Use Case 12 ............................................................................................................................... 34 Chapter 4 Technology Landscape ............................................................................................. 35 6 4.1 Software Development Tools ........................................................................................... 35 4.2 Cloud Platforms and Services......................................................................................... 38 4.3 Enterprise Scale Software Solutions................................................................................ 43 4.4 Cognitive Com puting/ M achine Learning Startups ......................................................... 44 4.5 Software Development Tools / Program ming Languages .............................................. 45 4.6 Cloud Development Platforms / Software as a Service................................................... 46 4.7 Traditional Enterprise Solutions ....................................................................................... 46 4 .8 S ta rtup s ............................................................................................................................... 4 7 Chapter 5 Analysis Framework.................................................................................................. 48 5.1 Davenport Categories of Cognitive Com puting Technologies1 ................... .................. 48 5.2 Davenport / Kirby Knowledge Task Survey ...................................................................... 48 5.3 Original Davenport / Kirby M atrix .................................................................................... 50 5.4 Technology Readiness Level ........................................................................................ 51 5.5 M odified Davenport/Kirby M atrix.................................................................................. 52 5.6 TRIL scores on Davenport Kirby Matrix ........................................................................... 54 5.7 Accenture M odel for Cognitive Com puting34 ................................................................. 55 5.8 Realizing Business Value from CC/M L Projects is a Journey............................................. 58 5.9 Enterprise Capability Assessment for M IL