LIVErtising 2018 09 Gr_AI_t Expectations

1. LIVErtising.netS 2017-18 1 11 Issues in Marketing Communication:  LIVErtising 18.09 GrAIt Expectations

2. LIVErtising.net 2

10. LIVErtising.net 8 AI across industries

11. LIVErtising.net 8 AI across industries FInance TELECOM HEALTH CARE TRANSPORTATION AUTOMOTIVE RETAIL ENERGY & RESOURCES CONSTRUCTION

12. LIVErtising.net 9 https://youtu.be/IiDAYktbLfo

16. Machine Learning is a core, transformative way by which we’re rethinking how we’re doing everything. We are thoughtfully applying it across all our products, be it search, ads, YouTube, or Play. And we’re in early days, but you will see us - in a systematic way - apply Machine Learning in all these areas. Sundar Pichai, Google CEO, 2016

17. Machine Learning is a core, transformative way by which we’re rethinking how we’re doing everything. We are thoughtfully applying it across all our products, be it search, ads, YouTube, or Play. And we’re in early days, but you will see us - in a systematic way - apply Machine Learning in all these areas. Sundar Pichai, Google CEO, 2016

18. LIVErtising.net AI marketing services 14

23. LIVErtising.net AI marketing services 14 Email Search Voice assistants E-tail Programmatic Social listening Predictive mktg PAYMENT

24. LIVErtising.net 15 https://seomelbourne.com/seo-content-writing/rankbrain-analysing-page-relevance/

26. LIVErtising.net 16 One very eﬀective way to leverage Google Analytics data to target users who are moﬆ likely to convert when they come back to a site is to use “Smart Liﬆs”. In the words of Google, “a Smart Liﬆ is a remarketing audience that Google Analytics generates to maximize your conversions.”

27. LIVErtising.net 16 The liﬆ is generated in Analytics by using many elements, including conversion data, location, device, browser, referrer, session duration, and page depth, in order to identify users who are moﬆ likely to convert in subsequent sessions. Machine learning at its beﬆ, based on actual relevant data together with Google’s powerful technology. https://www.morevisibility.com/blogs/sem/automate-remarketing-liﬆ-optimization-with-smart-liﬆs.html One very eﬀective way to leverage Google Analytics data to target users who are moﬆ likely to convert when they come back to a site is to use “Smart Liﬆs”. In the words of Google, “a Smart Liﬆ is a remarketing audience that Google Analytics generates to maximize your conversions.”

28. LIVErtising.netIHECS2017-1817 https://event.webcasts.com/starthere.jsp?ei=1191003&tp_key=ae49ec3867&sti=aw_blast1w

30. LIVErtising.net 18 2.What Is AI?

31. LIVErtising.net 19 A I

32. AI (or Machine Intelligence) is the area of computer science that allows the simulation of human intelligence by machines. • perception • learning • reasoning • problem solving • self-correction and • communication.

33. AI (or Machine Intelligence) is the area of computer science that allows the simulation of human intelligence by machines. • perception • learning • reasoning • problem solving • self-correction and • communication. This includes: •perception •learning •reasoning •problem solving •self-correction and •communication

34. AI (or Machine Intelligence) is the area of computer science that allows the simulation of human intelligence by machines. • perception • learning • reasoning • problem solving • self-correction and • communication. This includes: •perception •learning •reasoning •problem solving •self-correction and •communication

35. LIVErtising.net 21 Different meanings of AI 01 02 03

36. LIVErtising.net 21 Different meanings of AI Scientific discipline01 02 03

37. LIVErtising.net 21 Different meanings of AI Scientific discipline01 02 03 Artificial capacity

38. LIVErtising.net 21 Different meanings of AI Scientific discipline01 02 03 Artificial capacity Agents

39. LIVErtising.net 22 It must be stressed that the demarcation between AI and software in general is not sharp. Nick Bostrom, Superintellingence, p19

40. LIVErtising.net 23 What horizon does AI have? ANJ 2018 2040 +30

41. LIVErtising.net 23 What horizon does AI have? ANJ ANI2018 2040 +30

42. LIVErtising.net 23 What horizon does AI have? ANJ ANI Agi2018 2040 +30

43. LIVErtising.net 23 What horizon does AI have? ANJ ANI Agi Asi2018 2040 +30

44. LIVErtising.net 24 The basic AI ﬁelds 01 02 03 04 MOVE, WALK, RUN LOOK & SEE Extract / Generate Meaning IDENTIFY PATTERNS, GROUP OBJECTS SPEAK LISTEN WRITE-READ 05

45. LIVErtising.net 24 The basic AI ﬁelds Physical AI 01 02 03 04 MOVE, WALK, RUN LOOK & SEE Extract / Generate Meaning IDENTIFY PATTERNS, GROUP OBJECTS SPEAK LISTEN WRITE-READ 05

46. LIVErtising.net 24 The basic AI ﬁelds Physical AI Computer Vision 01 02 03 04 MOVE, WALK, RUN LOOK & SEE Extract / Generate Meaning IDENTIFY PATTERNS, GROUP OBJECTS SPEAK LISTEN WRITE-READ 05

47. LIVErtising.net 24 The basic AI ﬁelds Physical AI Computer Vision Speech rec & Synt 01 02 03 04 MOVE, WALK, RUN LOOK & SEE Extract / Generate Meaning IDENTIFY PATTERNS, GROUP OBJECTS SPEAK LISTEN WRITE-READ 05

48. LIVErtising.net 24 The basic AI ﬁelds Physical AI Computer Vision Speech rec & Synt NLP 01 02 03 04 MOVE, WALK, RUN LOOK & SEE Extract / Generate Meaning IDENTIFY PATTERNS, GROUP OBJECTS SPEAK LISTEN WRITE-READ 05

49. LIVErtising.net 24 The basic AI ﬁelds Physical AI Computer Vision Speech rec & Synt NLP Heuristic Classification 01 02 03 04 MOVE, WALK, RUN LOOK & SEE Extract / Generate Meaning IDENTIFY PATTERNS, GROUP OBJECTS SPEAK LISTEN WRITE-READ 05

51. LIVErtising.net 25 wHY 3.Now?

52. LIVErtising.net 26 A very brief historical perspective of AI AI Prehistory Alan TURING Isaac ASIMOV Dartmouth Conference “AI winters” Deep Blue IBM Watson ALPHA GO 1945-50 1956 1974-80 1987 - 93 1997 2011 2016

58. LIVErtising.net 27 Why now? 01 02 03 04

59. LIVErtising.net 27 Why now? Big data access 01 02 03 04

60. LIVErtising.net 27 Why now? Big data access Computing power 01 02 03 04

61. LIVErtising.net 27 Why now? ALGORITHMS Big data access Computing power 01 02 03 04

62. LIVErtising.net 27 Why now? ALGORITHMS Big data access Computing power APIs 01 02 03 04

68. LIVErtising.net 28 An ALGORITHM is a set of instructions that tells an agent what to do. ALGORITHMS

69. LIVErtising.net 28 An ALGORITHM is a set of instructions that tells an agent what to do. ALGORITHMS

70. LIVErtising.net 28 An ALGORITHM is a set of instructions that tells an agent what to do. ALGORITHMS (…) it’s a procedure that helps solve a problem, without each time inventing a solution (ABITEBOUL & DOWEK, 2017, 11)

71. LIVErtising.net 29 (…) it’s a procedure that helps solve a problem, without each time inventing a solution (ABITEBOUL & DOWEK, 2017, 11)

72. LIVErtising.net 29 (…) it’s a procedure that helps solve a problem, without each time inventing a solution (ABITEBOUL & DOWEK, 2017, 11)

73. LIVErtising.net 30 Algorithm to convert Fahrenheit into Celsius: 1. Read Fahrenheit temperature 2. Calculate and write Celcius temperature 3. Stop

74. LIVErtising.net 30 Algorithm to convert Fahrenheit into Celsius: 1. Read Fahrenheit temperature 2. Calculate and write Celcius temperature 3. Stop

75. LIVErtising.net 31 1.1 1.2 Algorithm to convert Fahrenheit into Celsius: 1. Read Fahrenheit temperature and write it to memory as “F” 2.Calculate and write Celcius temperature: 1. Subtract 32 from F and multiply by 5/9 2. Write the result to memory as C 3.Stop

76. LIVErtising.netIHECS2017-1832 He introduced the theory that information is a measurable element and deﬁned the basic unit, which would later be called a “bit”.

78. LIVErtising.net 33 Replace a by b Do c then d While e, repeat f If g then h

79. LIVErtising.net 33 1. Attribution 2. Sequence 3. Loop 4. Test Replace a by b Do c then d While e, repeat f If g then h

80. LIVErtising.netIHECS2017-1834

85. LIVErtising.net 36 Symbolic approach / Deterministic Programming

86. LIVErtising.net 36 Symbolic approach / Deterministic Programming

87. LIVErtising.net 36 Symbolic approach / Deterministic Programming 1. Space Complexity 2. Time Complexity 3. Human Complexity

92. LIVErtising.net 39 4.machine LEARNING

95. LIVErtising.net 41 https://a360-wp-uploads.s3.amazonaws.com/wp-content/uploads/hearingr/2018/03/Figure1-3.jpg

99. AI is the replication of human intelligence in computers Radu Raicea

100. AI is the replication of human intelligence in computers Radu Raicea Machine Learning refers to the ability of a machine to learn using large data sets instead of hard coded rules Radu Raicea

101. AI is the replication of human intelligence in computers Radu Raicea Machine Learning refers to the ability of a machine to learn using large data sets instead of hard coded rules Radu Raicea Deep learning are algorithms arranged in layers to mimic the brain’s learning patters Daniel Ramsay

102. LIVErtising.net 43 Machine learning / Deep Learning Symbolic approach / Deterministic Programming

103. LIVErtising.net 43 Machine learning / Deep Learning Symbolic approach / Deterministic Programming

108. LIVErtising.net 45 https://medium.freecodecamp.org/want-to-know-how-deep-learning-works-heres-a-quick-guide-for-everyone-1aedeca88076

109. LIVErtising.net 46 https://medium.freecodecamp.org/want-to-know-how-deep-learning-works-heres-a-quick-guide-for-everyone-1aedeca88076

112. LIVErtising.net 49 https://www.mathworks.com/content/dam/mathworks/tag-team/Objects/i/88174_92991v00_machine_learning_section1_ebook.pdf

117. LIVErtising.net 51 Two stages in ML https://insidebigdata.com/2016/06/03/how-to-use-analytics-driven-embedded-systems-to-drive-smart-technology-development/ 2 1

118. LIVErtising.net 51 Two stages in ML https://insidebigdata.com/2016/06/03/how-to-use-analytics-driven-embedded-systems-to-drive-smart-technology-development/ 2

119. LIVErtising.net 51 Two stages in ML https://insidebigdata.com/2016/06/03/how-to-use-analytics-driven-embedded-systems-to-drive-smart-technology-development/

120. LIVErtising.net 52 https://teachablemachine.withgoogle.com/

122. LIVErtising.net 53 5.LIMITS

123. LIVErtising.net 54 The limits of Machine Learning 01 02 03 04 05

124. LIVErtising.net 54 The limits of Machine Learning 01 02 03 04 05 Data sets

125. LIVErtising.net 54 The limits of Machine Learning 01 02 03 04 05 Data sets Data labelling

126. LIVErtising.net 54 The limits of Machine Learning 01 02 03 04 05 Data sets Data labelling Opacity

127. LIVErtising.net 54 The limits of Machine Learning 01 02 03 04 05 Data sets Data labelling Opacity Generalization

128. LIVErtising.net 54 The limits of Machine Learning 01 02 03 04 05 Data sets Data labelling Opacity Generalization Bias generation

131. LIVErtising.net 56 6.advert(A)Ising?

132. LIVErtising.net 57 AI contribution to Marketing Communication

133. LIVErtising.net 57 AI contribution to Marketing Communication Predicting consumer behaviour

134. LIVErtising.net 57 AI contribution to Marketing Communication Predicting consumer behaviour Personalizing contents & com

135. LIVErtising.net 57 AI contribution to Marketing Communication Predicting consumer behaviour Personalizing contents & com Detecting trends

136. LIVErtising.net 57 AI contribution to Marketing Communication Predicting consumer behaviour Personalizing contents & com Detecting trends Optimizing the Ps

137. LIVErtising.net 57 AI contribution to Marketing Communication Predicting consumer behaviour Personalizing contents & com Detecting trends Optimizing the Ps Integrating Mar & Com data

138. LIVErtising.net 57 AI contribution to Marketing Communication Predicting consumer behaviour Personalizing contents & com Detecting trends Optimizing the Ps Integrating Mar & Com data Analytics & Attributing Results

139. LIVErtising.net 57 AI contribution to Marketing Communication Predicting consumer behaviour Personalizing contents & com Detecting trends Optimizing the Ps Integrating Mar & Com data Analytics & Attributing Results Monitoring the Brand

140. LIVErtising.net 58 Personalizing contents & com

144. LIVErtising.netS 2017-18 Personalizing contents & com

145. LIVErtising.netS 2017-18 Personalizing contents & com DSA

147. LIVErtising.net 63 Optimizing the Ps

148. LIVErtising.net 64 Optimizing the Ps

149. LIVErtising.net 65 Analytics & Attributing Results

150. LIVErtising.net 65 Analytics & Attributing Results

151. LIVErtising.net 66 Attribution models

152. LIVErtising.net 67 AI contribution to Marketing Communication Predicting consumer behaviour Personalizing contents & com Detecting trends Optimizing the Ps Integrating Mar & Com data Analytics & Attributing Results

153. LIVErtising.net 67 AI contribution to Marketing Communication Predicting consumer behaviour Personalizing contents & com Detecting trends Optimizing the Ps Integrating Mar & Com data Analytics & Attributing Results Monitoring the Brand

154. LIVErtising.net 68 Monitoring the Brand

155. LIVErtising.net 68 Monitoring the Brand

157. LIVErtising.netS 2017-18 70 Monitoring the Brand

161. LIVErtising.net IHECS 2016-17 74

162. LIVErtising.netIHECS2017-1875 http://www.altimetergroup.com/pdf/reports/Image-Intelligence-Making-Visual-Content-Predictive-Altimeter.pdf

167. LIVErtising.netS 2017-18 76

168. LIVErtising.netS 2017-18 76

174. LIVErtising.netIHECS2017-1878 https://pages.crimsonhexagon.com/rs/284-XQB-702/images/Consumer-Insights-Team-Guide.pdf

175. LIVErtising.netS 2017-18 79 pre-‘90s promotion interaction SOCIAL connect tivity immersion offline digital ‘90s 2004 2007 2015 2017 community MOBILE & local virtual Based on Rori Duboff, Next Frontiers of Marketing, Slideshare, 2016. Recent evolution of THE MEDIA algo rhithmic singularity

176. LIVErtising.net 80 Recent evolution of COMMUNICATION MODELS 1 2 3 4

177. LIVErtising.net 81 7.all Rosy?

184. LIVErtising.net 84 Succes means always wanting to get more. Happiness means realising that what you have is fabulous.

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