Asia's AI Agenda

Asia’s AI agenda How Asia is speeding up global artificial intelligence adoption A briefing paper in association with

Asia’s AI agenda 1 Preface Preface Asia’s AI agenda is a briefing paper by MIT Technology Review. It is based on surveys of business leaders from across the Asia Pacific region conducted between September and October 2016. Further insights were gained through in-depth industry interviews and are included in this report. We would like to thank all participants in this research project as well as the sponsor, human capital management solutions provider ADP. MIT Technology Review has collected and reported on all findings contained in this paper independently, regardless of participation or sponsorship. November 2016 © MIT Technology Review, 2016. All Rights Reserved.

MIT Technology Review 2 Contents 1. Executive summary 3 2. Introduction: AI and Asia 4 3. Positively inclined 5 4. Human Capital and AI 8 5. Aware, but unprepared? 10 6. Conclusion: Putting the “AI” in “Asia” 11 7. Survey demographics and “firmographics” 12 8. Infographics on AI 14 © MIT Technology Review, 2016. All Rights Reserved.

Asia’s AI agenda 3 Executive summary 1. Executive summary sia-based senior executives at global ‹ Executives also feel positively about AI’s ability firms believe that the impact of artificial to add value to their own industries, with the Aintelligence (AI) and robotics on their business exception of financial service executives, who performance in Asia will be profound and positive— are generally less confident that automation and and will be felt sooner than we may think. machine learning will create purely constructive Outside of global robotics industry leaders Korea benefits for their industry. and Japan, most of Asia currently lacks the depth of technical skills and R&D facilities needed to keep ‹ Most C-suite respondents feel AI will significantly pace with AI development. However, China, India, improve their own competitiveness in Asia, and other large Asian economies generate a copious especially their process efficiency and their ability amount of data, a tremendous “natural resource” to delve into customer data to achieve better that is critical to pushing AI’s capabilities forward. insight. Again, financial industry responses lagged Ironically, given the commonly held view that AI will the average. be responsible for disintermediation of jobs at all levels, it is Asia’s massive human capital dividend—the ‹ Only a small percentage of respondents are billions of constantly Internet-connected workers and currently investing in AI development in Asia. 25% consumers—that will propel AI development in the of respondents, however, indicate that their firms region farther and faster. have already made investments at a global level— MIT Technology Review surveyed over 60 Asia- and another 50% are considering doing so. based senior executives to gather perspective on the impact of AI and robotics on Asia’s business landscape. ‹ Some 70% of HR executives feel that AI and Additionally, two dozen senior HR professionals robotics adoption will result in significant job losses were polled to assess the impact on jobs in Asia— in Asia over the next five years. Unsurprisingly, and the future of their roles in particular. Several nearly all of these respondents feel these in-depth interviews were conducted with AI industry technologies will have a major impact on their roles technologists, investors, and application developers. and functions in the future. The key findings of this research are as follows: ‹ Specifically, HR managers and talent professionals ‹ Overwhelmingly, respondents feel technological feel that their roles will evolve into broader, and advancements in AI and robotics will have very more strategic, “productivity management” roles; positive effects on most industrial sectors in Asia. two-thirds of them say their roles will encompass the management of both human and artificial talent ‹ They also believe even more strongly that these in the next five years. technology advancements will specifically improve their own firms’ competitiveness. © MIT Technology Review, 2016. All Rights Reserved.

MIT Technology Review 4 2. Introduction: AI and Asia Asia’s quest for technology innovation and sustained economic growth drives tremendous investment in AI peculation on the future of artificial intelligence MIT Technology Review has conducted surveys (AI) and robotics technologies often posits and interviews across Asia in developing this report, Sa binary outcome: either AI will profoundly which assesses how recent advancements in AI and increase efficiency and convenience for the world’s robotics are impacting Asia’s business landscape, economies and its people, or it will irrevocably disrupt looking at the efforts that Asian governments, (if not destroy) nearly every established industry and research institutes, and venture capitalists are making the livelihoods they all support. to hasten their development. The reality will lie between these two extremes. Based on research gathered from surveying Asian business leaders and human resources and AI professionals, this report argues that AI’s future will cleave much more closely to the positive outcome. Moreover, this future appears to be approaching quickly: advances in deep learning and the rapid expansion of process automation in such diverse sectors as manufacturing, transportation, and financial services mean that AI’s impact is growing exponentially with each passing year. Decision makers in all organizations must now begin to understand how AI will alter their own operational processes and those of suppliers, partners, and customers. Asia’s business landscape is poised not only to benefit greatly from AI’s rise, but also to define it. Asia’s quest for technology innovation and sustained economic growth drives tremendous investment in the space. Japan and Korea are looking to infuse all manner of consumer electronics with intelligence. China is attempting to complement and extend, rather than replace, human labor to maintain its dominant role in global manufacturing. China is also striving to build up its intellectual property reserves to ensure that its own firms are globally competitive in the Asia’s business landscape is creation of AI and robotic technologies. Singapore and Hong Kong are in a race to become leading poised not only to benefit greatly financial technology hubs, seeding investment in AI tools in financial service applications. from AI’s rise, but to also define it © MIT Technology Review, 2016. All Rights Reserved.

Asia’s AI agenda 5 Positively inclined 3. Positively inclined Executives feel positively about AI’s ability to add value to their industries urvey respondents were asked whether they increase in the industry’s value and efficiency). felt robotics and AI would have a constructive Across industry sectors, responses were positive— Sor a destructive effect on several market over 3.8. They were higher in more technology- segments; their responses were ranked from 1 (AI dependent industries such as information adoption would result in the destruction of jobs technology and communications (ITC), logistics, and processes) to 5 (AI would bring a significant and manufacturing. Figure 1: AI’s impact on industries in Asia (1 being least positive, 5 being most positive) * 3.7 Chemicals * 3.5 Commodities Consumer 3.9 goods, Retail 3.9 Financial 3.7 services 3.9 Information 4.1 technology & 4.1 communications Manufacturing 4.6 4.1 Pharma, 4 * Healthcare Professional 4 services 3.7 Property, 3.5 Construction 3.6 Transport, 4.4 Logistics 4.1 1 2 3 4 5 Respondents within the sector Average * Sectors for which only the “Average” metric had a statistically significant number of respondents. Source: MIT Technology Review © MIT Technology Review, 2016. All Rights Reserved.

MIT Technology Review 6 only industry cohort that did not feel as positive as the Most CEOs surveyed feel AI will respondent average was the one from the financial bring positive benefits to their own service industry. On average, industry respondents felt most encouraged about the positive impact AI and industry—except executives automation would have on their own competitiveness, from the crisis-plagued financial ranking it 4 out of 5. Once again, the optimism from respondents in retailing, ITC, and manufacturing service industry industries was higher than the average—while sentiment from the financial service industry was noticeably lower. Tellingly, respondents were even more inclined to The relative caution and pessimism among see positive benefits from AI for their own industry: financial sector respondents could have to do with most industry participants ranked the impact of past experiences. The 2007 global financial crisis AI on their own sector higher than the average. may not have started in Asia or hit the region’s banks Respondents from one sector, however, were actually and financial institutions as hard as it did elsewhere, more pessimistic: those from the financial service but the fallout, and the lingering regulatory and industry on average saw AI as a positive influence, compliance burden it created, plague Asian banks yet many also felt that automated processes and to this day. Moreover, mini-crises fomented by new machine-based transactions would destroy value in technologies constantly punctuate the industry their industry. landscape; “flash crashes,” for example, are fast, Banking industry fears of artificial intelligence’s sharp stock market plunges brought about by the destructive potential were also revealed when combination of human error and algorithmic trading. respondents were asked to rate the impact that Financial industry respondents may have these events these technologies would have on Asia’s industrial, in the back of their minds when considering what policy, and competitive landscape. Overall, survey artificial intelligence means for their future. respondents felt that advances in artificial intelligence Modest reticence from finance respondents would significantly boost Asia’s competitiveness as a aside, AI has the potential to affect a number of manufacturing and service center, benefit government Asia’s development challenges, from food security policy makers in their attempts to boost innovation, to public safety, transportation networks, and health and increase overall industry growth prospects. The care. Lin Yuanqing, the director of the Institute of Figure 2: AI’s impact on Asia’s business landscape What degree of impact will advancements in AI and robotics have over the next five years? (1 being least positive, 5 being most positive) 5 4 3.7 3.9 3.9 4 3 3.5 2 1 Asia’s manufacturing Asia’s service Asia’s tech and innovation My industry’s My company’s competitiveness industries government policies growth prospects competitiveness Source: MIT Technology Review © MIT Technology Review, 2016. All Rights Reserved.

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.

MIT Technology Review 8 4.Human capital and AI Tremendous change is imminent in the profession of human resources n addition to compiling senior executives’ In his view, this not only heightens anxieties for views about AI’s impact on the Asian business talent managers within enterprises but influences Ienvironment, we surveyed two dozen senior human government policy makers as well. “Asian governments resource executives in Asia—HR directors, recruiting are particularly suspicious of the threat AI poses to consultants, and talent acquisition heads—to their efforts to transform skills in the labor force,” understand their views on AI’s potential to disrupt he says, noting that “governments should be more talent management. focused on ways to retrain displaced workers” rather The results revealed an assumption that than defending existing jobs from disintermediation. tremendous change is imminent in the profession of The views of the industry professionals surveyed human resources: 70% of respondents feel that AI suggest that enterprises may soon be shifting and robotics will lead to substantial job losses in Asia their practices in human resource management to over the next five years, underscoring a long-standing achieve that focus. Nearly all respondents felt that anxiety that many in Asia feel when considering their professions would be significantly altered with the impact of new technologies. “The pace of work the advent of AI. However, they also felt that these displacement in Asia will be at a much faster rate, changes would be positive. Rather than the HR because of the relatively higher percentage of function narrowing as robots replace workers, the low-skilled jobs in the labor force relative to more majority of respondents thought that it would be developed economies” says Tak Lo, a partner at Hong expanded to oversee the management of both human Kong–based AI accelerator Zeroth.AI. and machine productivity. Figure 4: Human resources Will advancements in AI and robotics lead to substantial job losses in Asia over the next five years? (% of respondents) Yes (70.8%) No (29.2%) Will these technologies have a major impact on the role and function of the HR chief? (% of respondents) Yes (87.5%) No (12.5%) How will the role of the HR function change with advancements in AI and robotics? (% of respondents) HR will be tasked with managing overall productivity, HR will keep managing people, and therefore both man and machine (66.7%) and only people (33.3%) Source: MIT Technology Review © MIT Technology Review, 2016. All Rights Reserved.

Asia’s AI agenda 9 Human capital and AI AI industry professionals echo this positive view of the technology’s ability to enhance, rather than “This is not scary. All our work lives replace, jobs. The notion that robots will soon steal will be complemented, for the jobs at any skill level and decimate entire professions is an exaggerated one, according to Baidu IDL better—we are not going director Lin Yuanqing. “Even the best robotic financial to be replaced. ” analyst is only going to prepare a report at 70% of the capability and insight of its human counterpart,” he Lin Yuanqing, Director, Baidu IDL says, though admitting that it will happen in a fraction of the time. “This is not scary. All our work lives will be complemented, for the better—we are not going to be replaced.” Despite AI’s rapid advances (or perhaps because of them), skepticism remains, and the industry is taking pains to address the doubts. Recently, an industry coalition called the Partnership on Artificial Intelligence to Benefit People and Society was formed by some of the world’s largest technology firms, including Facebook, Google, and Amazon. But while this group’s almost apologetic name suggests that its main function is to stem the rise of job-robbing machines, the initiative’s primary role is to engender collaboration around data gathering and analysis to accelerate cognitive learning and drive further AI insight. © MIT Technology Review, 2016. All Rights Reserved.

MIT Technology Review 10 5. Aware, but unprepared? Only a small percentage of companies are currently investing in AI development in Asia ecision makers at Asian-based firms are firmly Asian governments feel they need to take to mitigate convinced of the benefits AI and automation with technology progression,” he says. Dtechnology will bring to their own prospects In China, the hope is to use automation to bolster and the region’s economy as a whole, but most labor productivity as the country’s workforce ages have not yet committed resources to capitalize on and shrinks. Over the longer term, China hopes to these beliefs. A small percentage of respondents build a domestic manufacturing capability in industrial indicate that they have invested in AI in Asia, and robots and, by extension, in process automation and nearly 20% say they have robotics and automation artificial intelligence. Singapore, by contrast “is into a commitments in the region. Larger percentages little bit of everything—fintech, autonomous driving, indicate that they have AI or robotics investments automated customer support,” says Tak. Autonomous at a global level, and fully half indicate that they are driving is considered one of the most likely AI-enabled considering AI investments. applications, observes Professor Zhang of the While multinational firms may not be committing Singapore University of Technology and Design, but resources to AI development in Asia yet, domestic largely as an anchor for establishing a broad-based industries across the region are most certainly doing AI innovation platform. “Singapore is aligning its policy so, driven by a traditional response of policy makers objectives across multiple sectors—urban mobility, in the region, according to Zeroth.AI’s Tak Lo: “The financial data science, health care—in an effort to external shocks that can happen create risk that elicit the synergies across them and speed up AI development overall,” he says. Asia as a regional economy is poised not only to Figure 5: AI investment plans benefit greatly from advancements in AI and robotics (% of respondents) technologies, but to also define them—and perhaps to lead their future development. AI’s rise will create a seismic shift in the processes that senior managers 20 use to manage talent, growth, and productivity across 13 25 nearly every industry sector. Asian businesses stand to leverage AI’s rise faster, thanks to the virtuous 43 AI (analytics, Automation/ cycle created by Asia’s technology investments and machine Robotics learning or other the organic growth of big data. 50 AI capabilities) 13 18 18 AI’s rise will create a seismic shift in the processes that senior We have invested globally We are considering investment managers use to manage talent, We have invested in Asia We have no plans to invest growth and productivity, across Source: MIT Technology Review nearly every industry sector © MIT Technology Review, 2016. All Rights Reserved.

Asia’s AI agenda 11 Conclusion 6. Conclusion: Putting the “AI” in “Asia” A holistic view of productivity development across an entire firm and its assets is emerging sian business leaders need to adopt an Aware, but unprepared. C-level executives surveyed extreme openness to successfully capitalize also firmly believe that process automation will not Aon today’s AI and automation trends—a only improve their own business performance but willingness to actively collaborate in data analytics impact industry growth overall. Yet only a small projects and share best practices and insight percentage of respondents indicate that they are resulting from their own process automation efforts. currently investing in AI or robotics in Asia, and These technologies may have powerful effects on although many more say they are considering an individual firm’s competitiveness (as business investment, it is clear that business leaders in the leaders assume in the survey results), but the quest region must take more active steps to prepare for AI’s for competitive advantage cannot blind business rapid rise. leaders to the greater benefits of collaboration, in much the same way that competitive AI developers Change Asia’s workers can believe in. Most Asia- themselves are increasingly pooling resources based human resource professionals surveyed feel to accelerate their collective progress. It will also AI and automation will soon create significant job require leaders to champion process improvements losses in the region. At first glance, this outlook paints based on automation and machine learning that are a bleak picture for Asia’s workers, who mostly live integrated into their firms’ broader talent management in economies where automation threatens the very programs. AI may start to disintermediate roles and entry-level jobs upon which they depend to build skills responsibilities across Asia’s economies, but it will and advance careers. But when asked what sort of enhance and redefine far more, while increasing the impact this would have on the profession overall, most productivity of all workers. HR industry participants believed that their roles would The research undertaken for this report evolve and expand so that they would manage and has elicited three primary take-aways for senior develop both human capital and inputs from machines. executives managing businesses across Asia: The emergence of a holistic view of productivity development across an entire firm and its assets, AI’s big bang. The C-level executives surveyed and AI coupled with the high hopes Asia-based senior industry experts interviewed are largely aligned in the executives have for AI’s influence on their firms’ belief that AI and robotics will impact every industry success, means it is likely that business leaders significantly, positively, and all at once. Rising investment will focus their investment and adoption efforts on in process automation in Asian manufacturing tends complementing and enhancing job functions with to focus much of the industry’s attention, with good automation, rather than eliminating them. reason: three Asian countries—China, Korea, and Japan—purchased nearly half the world’s shipments of 250,000 articulated robots last year. But importantly, survey respondents largely felt that most other sectors, from retail to logistics, would benefit equally from AI technology. AI industry executives feel that big data’s growth in Asia will allow autonomous and intelligent applications to proliferate across almost all industries in the region more or less simultaneously. © MIT Technology Review, 2016. All Rights Reserved.

MIT Technology Review 12 7. Survey demographics and “firmographics” ver 60 Asia-based senior decision makers were CEOs, and a further 20% of respondents responded to our 10-question survey. We were CFOs or other C-suite executives. The sought their opinions on advancements in majority of our respondents were executives at O the artificial intelligence and robotics industries, and large multinationals headquartered outside of Asia; we asked how these industries would impact growth roughly equal percentages reported that their head prospects for Asian business. offices were in Europe, North America, or the Asia- Our respondents were senior regional decision Pacific region. Over 70% of respondent firms had makers from over a dozen industries, with large global annual revenues of over US$1bn, and over a representation from the financial service industries, quarter represented firms with turnovers in excess of consumer goods and retail, and professional US$10bn annually. service sectors. More than half of our respondents Figure 6: Respondent demographics and firmographics (% of respondents) Industries .6 .3 3 0.6 .6 .3 9 .6 .6 1.1 .6 5 9 1 14 6. 2 1 14 7. 1 1 1 1 9. 7. Chemicals Consumer goods, Retail Engineering Financial services Hotels, Leisure Information technology & communications Manufacturing Media, Marketing Pharma, Healthcare Professional services Property, Construction Transport, Logistics Other Roles 5 .6 9 2.7 .3 54 9. 1 7. 1 14 CEO/Managing Director/President CFO CIO CXO Director of Sales and/or Marketing Other Director-level HQ .9 .3 8.6 .2 34 33 2 3 Europe North America Asia Australasia Size of firm 1.1 .9 8 .3 1 15 4. 27 14 27 < $50m $50m to $500m $500m to $1bn $1b to $5bn $5bn to $10bn > $10bn Source: MIT Technology Review © MIT Technology Review, 2016. All Rights Reserved.

Asia’s AI agenda 13 Survey demographics and “firmographics” Within the region, most respondents were based in Southeast Asia, where their firms’ Figure 7: Regional presence regional headquarters were located, with (% of respondents) sizable numbers based in Greater China and South Asia as well. 14.8 Respondents managed diversified 16.9 3.3 businesses across Asia. A third reported direct manufacturing presence in the region, roughly 42.2 9.6 equally present across China, Southeast Asia, 52.5 Regional HQ and South Asia. Over half reported sales, Respondent location 27.9 distribution, and investment activities in each 21.7 of those Asian regions. Respondents managed diversified businesses across Asia. A third reported direct manufacturing presence in the 9.6 region, roughly equally present across China, 1.6 Southeast Asia, and South Asia. Over half reported sales, distribution, and investment activities in each of those Asian regions. ANZ Greater China East Asia (Korea, Japan) ASEAN India/South Asia Source: MIT Technology Review Figure 8: Regional activities (% of respondents) ANZ Greater China East Asia ASEAN South Asia 7.9 12.7 Manufacturing 25.4 27 30.2 presence Direct wholesale 34.9 44.4 36.5 54 42.9 and/or retail activities Third-party 25.4 27 27 39.7 34.9 distribution or franchises 14.3 19 Investment 33.3 39.7 47.6 activities Source: MIT Technology Review © MIT Technology Review, 2016. All Rights Reserved.

MIT Technology Review 14 What Is AI? A Time Line of AI 1914 It has grown up out of many different After a century of ups and downs, disciplines and has many definitions. artificial intelligence is getting smarter. In what would come to be described as the Here is ours. world’s first computer game, Spanish inventor Leonardo Torres y Quevedo debuts El rtificial intelligence, as we 1943 Ajedrecista, a machine that can automatically use the term in this report, is play chess thanks to a simple algorithm built into Aan evolving constellation of Neuroscientist Warren McCulloch and its mechanical design. technologies that enable computers to logician Walter Pitts present a calculus simulate elements of human thinking— based on neuron-like “logic units” that can learning and reasoning among them. be connected together in networks to Regular improvements in Google’s model the action of a real brain. 1950 search algorithm, for example, come In a paper that helps establish a practical goal from machine learning, a type of AI that for artificial-intelligence research, Alan Turing programs systems to learn from data, proposes a game to answer the question “Can find patterns in it, and make predictions machines think?” He predicts that by 2000 about it. The same technology has 1956 been pivotal to voice and image computers will be able to pass as human more recognition as well as advances in self- John McCarthy, Marvin Minsky, and than 30 percent of the time. driving cars. Integral to many recent Claude Shannon organize a summertime improvements in the field is a form of research meeting at Dartmouth that machine learning called deep learning. brings together the leading thinkers Loosely modeled on the way neurons on information theory, artificial neural 1958 and synapses in the brain change networks, and symbolic logic, christening as they are exposed to new input, it the field “artificial intelligence.” Oliver Selfridge presents a paper in England has been used independently or in describing Pandemonium, a new model of a combination with other AI approaches neural network based on lower-level “data to help machines tackle tricky tasks and demons” working in parallel with higher-level exhibit something resembling intuition, 1960 “cognitive demons” in order to perform pattern in some cases performing tasks better recognition and other tasks. than humans. Frank Rosenblatt demonstrates the Mark I Perceptron, an attempt to create an artificial neural network for image recognition that the New York Times 1961 calls the first step toward a computer Marvin Minsky publishes his foundational paper, “able to walk, talk, see, write, reproduce ... “Steps Toward Artificial Intelligence.” and be conscious of its existence.” Placing That Face 4 3.67 As of 2015, groups ecognition3 reported different results r ace using AI techniques like f deep learning on large in 2 data sets, but computers or 1.65 err are sometimes better 1 than humans at tage 0.53 Human recognizing a face. cen 0.37 0.23 er0 P Microsoft Facebook Chinese Google Baidu University of Hong Kong Source: MIT Technology Review’s “AI Takes Off” Business Report © MIT Technology Review, 2016. All Rights Reserved.

Asia’s AI agenda 15 Infographics on AI 2004 2011 DARPA sponsors its first “Grand IBM’s Watson defeats Jeopardy! champions Challenge,” which pits research teams Ken Jennings and Brad Rutter in a televised against each other to design driverless two-game, three-night face-off that ends with 2000 vehicles capable of independently the computer amassing more than three times traversing the Mojave Desert. the winnings of its human competitors. Cynthia Breazeal designs a sociable humanoid robot named Kismet that is able to express emotion and recognize cues from interaction with humans. 1997 2012 IBM’s Deep Blue chess computer avenges its prior defeat to world A team from Geoff Hinton’s lab wins 1987 champion Garry Kasparov in a tense the ImageNet Large Scale Visual match commemorated in a documentary Recognition Challenge with deep- Ernst Dickmanns and collaborators equip film, The Man vs. the Machine. learning software that could within five a Mercedes van with video cameras, guesses identify a thousand types of microprocessors, and other electronics to objects about 85 percent of the time, a demonstrate autonomous driving at almost 60 1984 huge improvement in accuracy. miles per hour. After much other AI research falls short, DARPA cuts the project’s budget. Douglas Lenat begins the Cyc project, an ambitious attempt to create a common- 2014 sense knowledge base that can 1979 eventually become self-educating. Little Google acquires DeepMind progress is seen for decades. Technologies, a small London-based A backgammon program developed by startup focused on deep learning, Hans Berliner defeats the reigning world a relatively new field of artificial champion in a match, the first time a 1972 intelligence that aims to achieve tasks computer has defeated a champion-level like recognizing faces in video or words in competitor in an intellectual game. AI takes a hit when philosopher Hubert human speech. Dreyfus publishes “What Computers Can’t Do,” a manifesto challenging the 2016 1966 predictions of AI researchers, and scientist James Lighthill pens a pessimistic review Google’s AlphaGo decisively beats the Joseph Weizenbaum demonstrates ELIZA, of progress in AI research in the U.K., world champion of the complex board the world’s first chat program, which is able to leading to funding cuts. game Go. converse using a series of preprogrammed phrases, sometimes to comic effect. Improving Translation By adding industry- and company-specific words, sentences, With this many translated and translated documents, Microsoft has created tools that sentences to help users improve translation. work with, quality Translated system begins sentences learning new tion added to terms in their Adds industry improve business Focused ansla or business tone and context r Translation is by type of T done without specific words terminology content to be only customization translated Microsoft Translator Standard Dictionary 1,000-5,000 5,000-50,000 Models Category Parallel Sentences Parallel Sentences Source: MIT Technology Review’s “AI Takes Off” Business Report © MIT Technology Review, 2016. All Rights Reserved.

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