The Age of Artificial Intelligence- Impact and Implications.pdf

Since AlphaGo’s historical victory over humans, Artificial Intelligence (AI) has attracted more and more attention from the public. In fact, AI has become a part of our everyday life and it exists almost everywhere, e.g. when you chat with Siri or read news articles on Toutiao, In a nutshell, AI is an interdisciplinary science based on the integration of computer science, physiology and philosophy. To some extent, all machine behaviors augmenting human to perceive, identify, analyze and make decisions could be regarded as the applications of AI. This technology, with a history of over 60 years, recently became a focus again after going through two cycles of ups and downs. As a technology company using AI to reshape the connection between humans and information, Jinri Toutiao has launched this report, The Age of Artificial Intelligence: Impact and Implications, to recognize the most influential companies, technologies and scientists, and to understand and record the fears and expectations of AI in our society today. PrefaceThe firms involved in comprehensive AI research are much more influential than those focused on a single field of applicationThe open-source platforms developed by leading companies will drive the growth of applications downstream Evolving from universal chips to customized chips and then brain-like chips is the path to the future.With the further opening of open-source platforms and improvement of algorithms and chips, the key components of AI competition will move to the competition for talents and application scenarios, from competition in technologies today. Chinese people’s AI-Confidence Index stands at 83, which shows an optimistic and rational attitude towards AI.Key FindingsCONTENTSThe Knowledge Map of AIThe Influences of AI Firms and TechnologiesThe Influences of AI Brands in Applications ScenariosAI-Confidence Index and User Profiles01The Knowledge Map of AI•The Relations among AI-Related Fields and Their Hotness Levels•The Influences of Basic AI Applications•The Three Tides of AI Development•The Three Key Factors for AI Development •The Value Chain of AI IndustryP1Machine LearningDeep LearningData MiningDatabaseStatisticsThe concepts of ‘Artificial Intelligence’, ‘Machine Learning’ and ‘Deep Learning’ are intertwined with one another but no one is subject to another.‘Neural Net Algorithm’ and ‘Artificial Intelligence’ are overlapped, but the former is not simply an application of AI or its subject. KnowledgeDiscoveryData Souces: SAS, 2014 and PwC, 2016Connections among the AI-Related Fields PART ONE: The Knowledge Map of AIThe Family Tree of AIPatternRecognition Artificial IntelligencePattern RecognitionStatisticsData MiningDatabaseDeep LearningNeural Net AlgorithmMachine LearningArtificial Intelligence2956861117936711059994169949175262209881918018128P2PART ONE: The Knowledge Map of AIThe Influences of AI-Related Fields Data Source: Toutiao IndexIn 1975, Paul Werbos put forward the BP algorithm which made the learning of multi-layer artificial neural networks possible, enabling the rise of two-layer neural networks in 1986 which laid the foundation of the second tide in AI development.In 1956, The Dartmouth Artificial Intelligence Conference came up with the name and vision, and thus marked the birth of AI.1956-1976The First Tide of AI1976-2000The Second Tide of AI2000 to nowThe Third Tide of AI DevelopmentP390sThe research of AI encountered the issue of insufficient funds in the 1990s.70s Due to the bottleneck of computer performance, increasing complexity of competing, as well as data insufficiency, a lot of projects were unaccomplished in the 1970s.In 2012, Geoff Hinton’s team defeated Google in the ImageNet ILSVRC (Large Scale Visual Recognition Challenge), which was of great significance academically and also triggered a large-scale investment in deep learning in the industry.PART ONE: The Knowledge Map of AIOverview of AI05010015020042005200620072008200920102011201220132014201520162017人工智能大数据机器学习数据科学深度学习05010015020042005200620072008200920102011201220132014201520162017Artificial intelligencebig datamachine learningdata sciencedeep learningGoogle Trends (Search with Chinese Names)Searching key words related to AI in google trends, e.g. ‘Artificial Intelligence’, ‘Big Data’, ‘Machine Learning’ and ‘Deep Learning’, you can see the different focuses and how they evolve. To compare the trends of ‘Artificial Intelligence’ and ‘Big Bata’, the former attracted attention in both the English and Chinese contexts as early as 2004. Yet its search volume started to decline in the Chinese context around 2006-2007, with its hotness level outpaced by ‘Big data’ at that time.In English language searching, the search volume of ‘Big Data’ only outpaced AI around 2012.The hotness level of ‘Deep Learning’ in Chinese searching was almost the same as ‘Artificial Intelligence’ in 2009. However in English searching, public awareness of “Deep Learning” didn't show a significant increase until 2013.P...