Asia’s AI agenda 7 Positively inclined Deep Learning at Baidu Research (known as Baidu Figure 3: AI’s impact on growth and competitiveness IDL), believes that all this is coming to a head at What degree of impact will advancements in once: “It is impossible to point to an industry that AI and robotics have over the next five years? will be ‘first’ to adopt AI. Public transportation, (1 being least positive, 5 being most positive) logistics—nearly every critical infrastructure platform can benefit from it, and they are all interconnected. AI will come to all industries at once, and it will come My industry’s sooner than we think.” growth prospects AI industry executives feel that two linked factors My company’s will allow autonomous and intelligent applications competitiveness to proliferate somewhat simultaneously. One is the growth of big data in Asia, fed by many hundreds of Consumer/ millions of people in densely populated cities who are Retail connected to the mobile Internet. “Data is the most 3.9 important resource for successful machine learning 4 development,” says Professor Zhang Yue, a machine language researcher at the Singapore University of Technology and Design. “And mobile data, large in volume and rich in context, provides AI developers Financial with a large amount of useful data.” The harnessing services of big data through analytics gives rise to the second 3.6 factor driving AI development: firms are increasingly 3.6 willing not only to use analytics to increase their own business performance, but to borrow and share automated process insight across sectors. A successful ecosystem for AI development Information requires four input factors, according to Baidu technology & IDL’s Lin: “Big data, the continuous production of communications algorithms, massive computation power, and ‘big 4.3 applications.’” Lin describes this last factor as the 4.2 most crucial: applications that attract a large number of users quickly “drive usage, interaction, and data creation to create a positive development loop” for deep neural networks, which are increasing in scale and capability as processing power becomes ever Manufacturing cheaper and more plentiful. 4 4.2 “Data is the most important resource for successful machine learning development—and Professional services mobile data provides AI 3.6 developers with a large amount of 4.1 useful data.” Source: MIT Technology Review Zhang Yue, Professor, SUTD © MIT Technology Review, 2016. All Rights Reserved.