The Ethical Questions That Haunt Facial- Recognition
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Ant Financial Case Study.Pdf
EO INTELLIGENCE Cover photo credit to IC photo Deciphering the Trillion-valued Unicorn -Ant Financial Case Study Copyright ©2019 EO Intelligence. All Rights Reserved. EO INTELLIGENCE INTRODUCTION According to the World Development Report 2019 issued by the World Bank in October 2018, Ant Financial was rated as the most valuable fintech company in the world. As a financial services company that has just spun off from Alibaba Group for four years, it does deserve the title "the most valuable company" with a valuation of USD 160 billion. In China, there is a huge gap between the lofty valuation of Ant Financial and the valuation of other unicorn companies. It can be seen that Ant Financial is growing rapidly and outperforming financial institutions that have been developing for decades in China and even the world. Ant Financial cannot be labeled as a simple fintech or a financial company, because in terms of the 15-year accumulation and development from Alipay to Ant Financial, both the innovation capability of its financial business and the technical output capability serving a third-party financial and non-financial institution are indispensable consideration factors for its valuation of USD 160 billion. Why is Ant Financial selected? By making a summary and analysis on the development of Ant Financial, EO Intelligence hopes to have a deep understanding of the impetus for the industry brought by the combination of technology and finance, and the logic behind it. The scale and uniqueness of the Ant Financial ecosystem may not be replicable today, but the exploration course of Ant Financial will definitely give practitioners food for thought. -
Human Rights in China and U.S. Policy: Issues for the 117Th Congress
Human Rights in China and U.S. Policy: Issues for the 117th Congress March 31, 2021 Congressional Research Service https://crsreports.congress.gov R46750 SUMMARY R46750 Human Rights in China and U.S. Policy: Issues March 31, 2021 for the 117th Congress Thomas Lum U.S. concern over human rights in China has been a central issue in U.S.-China relations, Specialist in Asian Affairs particularly since the Tiananmen crackdown in 1989. In recent years, human rights conditions in the People’s Republic of China (PRC) have deteriorated, while bilateral tensions related to trade Michael A. Weber and security have increased, possibly creating both constraints and opportunities for U.S. policy Analyst in Foreign Affairs on human rights. After consolidating power in 2013, Chinese Communist Party General Secretary and State President Xi Jinping intensified and expanded the reassertion of party control over society that began toward the end of the term of his predecessor, Hu Jintao. Since 2017, the government has enacted new laws that place further restrictions on civil society in the name of national security, authorize greater controls over minority and religious groups, and further constrain the freedoms of PRC citizens. Government methods of social and political control are evolving to include the widespread use of sophisticated surveillance and big data technologies. Arrests of human rights advocates and lawyers intensified in 2015, followed by party efforts to instill ideological conformity across various spheres of society. In 2016, President Xi launched a policy known as “Sinicization,” under which the government has taken additional measures to compel China’s religious practitioners and ethnic minorities to conform to Han Chinese culture, support China’s socialist system as defined by the Communist Party, abide by Communist Party policies, and reduce ethnic differences and foreign influences. -
China's Current Capabilities, Policies, and Industrial Ecosystem in AI
June 7, 2019 “China’s Current Capabilities, Policies, and Industrial Ecosystem in AI” Testimony before the U.S.-China Economic and Security Review Commission Hearing on Technology, Trade, and Military-Civil Fusion: China’s Pursuit of Artificial Intelligence, New Materials, and New Energy Jeffrey Ding D.Phil Researcher, Center for the Governance of AI Future of Humanity Institute, University of Oxford Introduction1 This testimony assesses the current capabilities of China and the U.S. in AI, highlights key elements of China’s AI policies, describes China’s industrial ecosystem in AI, and concludes with a few policy recommendations. China’s AI Capabilities China has been hyped as an AI superpower poised to overtake the U.S. in the strategic technology domain of AI.2 Much of the research supporting this claim suffers from the “AI abstraction problem”: the concept of AI, which encompasses anything from fuzzy mathematics to drone swarms, becomes so slippery that it is no longer analytically coherent or useful. Thus, comprehensively assessing a nation’s capabilities in AI requires clear distinctions regarding the object of assessment. This section compares the current AI capabilities of China and the U.S. by slicing up the fuzzy concept of “national AI capabilities” into three cross-sections: 1) scientific and technological (S&T) inputs and outputs, 2) different layers of the AI value chain (foundation, technology, and application), and 3) different subdomains of AI (e.g. computer vision, predictive intelligence, and natural language processing). This approach reveals that China is not poised to overtake the U.S. in the technology domain of AI; rather, the U.S. -
Hkai Lab Accelerator Program
HKAI LAB ACCELERATOR PROGRAM APPLICATION INFORMATION KIT WHAT we offer Empowering 1. Financial Investment Startups • Alibaba Hong Kong Entrepreneurs Fund (AHKEF) will invest US$100,000 in a HKAI LAB offers a form of a zero-interest convertible note of 18-month maturity to companies 12-month who are admitted to the HKAI LAB Accelerator Program. Accelerator • The convertible note shall give the holder an option to convert into equity at Program that the next equity round of financing at a conversion price which depends on takes your startup the actual scenario and stage of the company. After conversion, AHKEF will to the next level. own, at most, 6% of the company on a fully-diluted basis. The shares received upon conversion shall be pari passu with the same class of shares issued at We focus on the next round of equity financing. empowering startups to 2. Access to Proprietary AI Technologies develop and • GPU-equipped high-performance computer resources commercialize • PAI, a machine-learning platform powered by Alibaba Cloud their AI inventions • and technologies. Parrot, a deep-learning platform powered by SenseTime We run two 3. Strong Advisory, Network & Opportunities accelerator • HKAI LAB facilitates knowledge sharing by a wide spectrum of our advisors, cohorts every coaches, and experts, including AI scientists, eminent professors, and year. technical experts. You will also have the chance to meet venture capitalists and potential strategic partners through various events held at or outside of the lab. There may also be opportunities to work with Alibaba Group and SenseTime on different business ventures. 4. Dedicated Support & Resources • To support your growth, you will have access to US$10,000 worth of Alibaba Cloud services credit, technical consultation and support from Alibaba Cloud, SenseTime and Alibaba DAMO Academy teams. -
Responsible Facial Recognition and Beyond
Responsible Facial Recognition and Beyond Yi Zeng1,2,3, Enmeng Lu1, Yinqian Sun1, Ruochen Tian1 1. Institute of Automation, Chinese Academy of Sciences, China 2. Research Center for AI Ethics and Safety, Beijing Academy of Artificial Intelligence, China 3. Berggruen Research Center, Peking University, China Email: [email protected] Abstract Facial recognition is changing the way we live in and interact with our society. Here we discuss the two sides of facial recognition, summarizing potential risks and current concerns. We introduce current policies and regulations in different countries. Very importantly, we point out that the risks and concerns are not only from facial recognition, but also realistically very similar to other biometric recognition technology, including but not limited to gait recognition, iris recognition, fingerprint recognition, etc. To create a responsible future, we discuss possible technological moves and efforts that should be made to keep facial recognition (and biometric recognition in general) developing for social good. The Two Sides of Facial Recognition Like other technologies that change the world and the way we live, the original motivation for facial recognition is for human good. In the area of public safety, facial recognition technology has been widely used in surveillance systems, tracking criminals and identifying fugitives (Moon 2018; Lo 2018). It has also been used to fight human trafficking, detect kidnappers, and help to trace long-missing children for family reunion (Jenner 2018; Yan 2019; Cuthbertson 2018). In business and finance, facial recognition is becoming a more and more popular choice in payment and courier services, and helps to maximize security and minimize fraud (A. -
The 2Nd International Artificial Intelligence Fair (IAIF) I
Official Call for Participation The 2nd International Artificial Intelligence Fair (IAIF) I. Introduction to Sponsor and Organizer: The second International Artificial Intelligence Fair is sponsored by the Global AI Academic Alliance (GAIAA), which was founded at the 2018 World AI Conference in Shanghai, China. The founding members include MIT, University of Sydney, Nanyang Technological University, Chinese University of Hong Kong, Tsinghua University, Zhejiang University, University of Science and Technology of China, Beijing University of Aeronautics and Astronautics, Fudan University, Harbin Engineering Industrial University, Shanghai Jiaotong University, Shanghai University, Shanghai University of Science and Technology, Tongji University, Xi'an Jiaotong University, SenseTime Group, and other world renown universities and scientific research institutions. The Alliance aims to build and continue to promote the world's top AI academic exchange and collaboration platform. In addition, the Academic Alliance will engage public policy makers and the public in important issues, accelerate the industrialization of artificial intelligence technology, and strive to improve the public awareness and understanding of artificial intelligence. It brings together universities, research institutions, enterprises, experts and scholars in the field of global artificial intelligence to gather the world's "strongest brains" to jointly advance the rapid and sustainable development of artificial intelligence technology. As a key founding member of the Alliance, SenseTime Group created a global leading artificial intelligence education platform, and is committed to contributing to the global development of AI, to help build an AI academic exchange platform, to assist in industry research cooperation, to provide industry benchmarks, and to identify and develop AI talents. The development of college AI education is inseparable from the AI education at primary and secondary school levels to build the foundation and nurture creative thinking at an early stage. -
Global Artificial Intelligence Industry Whitepaper
Global artificial intelligence industry whitepaper Global artificial intelligence industry whitepaper | 4. AI reshapes every industry 1. New trends of AI innovation and integration 5 1.1 AI is growing fully commercialized 5 1.2 AI has entered an era of machine learning 6 1.3 Market investment returns to reason 9 1.4 Cities become the main battleground for AI innovation, integration and application 14 1.5 AI supporting technologies are advancing 24 1.6 Growing support from top-level policies 26 1.7 Over USD 6 trillion global AI market 33 1.8 Large number of AI companies located in the Beijing-Tianjin-Hebei Region, Yangtze River Delta and Pearl River Delta 35 2. Development of AI technologies 45 2.1 Increasingly sophisticated AI technologies 45 2.2 Steady progress of open AI platform establishment 47 2.3 Human vs. machine 51 3. China’s position in global AI sector 60 3.1 China has larger volumes of data and more diversified environment for using data 61 3.2 China is in the highest demand on chip in the world yet relying heavily on imported high-end chips 62 3.3 Chinese robot companies are growing fast with greater efforts in developing key parts and technologies domestically 63 3.4 The U.S. has solid strengths in AI’s underlying technology while China is better in speech recognition technology 63 3.5 China is catching up in application 64 02 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry 4. AI reshapes every industry 68 4.1 Financial industry: AI enhances the business efficiency of financial businesses -
Megvii Technology Limited
Megvii Technology Limited Profiling China’s AI Unicorns: Megvii Technology Limited Summary Megvii Technology is a leading Chinese developer of artificial intelligence algorithms for facial recognition. Founded in 2012 by Yin Qi and two other students at Tsinghua University, Megvii developed the “Face++” application that has become the basis for popular mobile facial recognition apps as well as city surveillance and management systems. Megvii claims that 70 percent of Android apps in China have adopted its face-scanning technology. Although operating at a loss, Megvii has been attractive to Chinese and foreign investors and has a current valuation of perhaps two billion dollars. This report profiles the development of Megvii as a company, the facial recognition services that it provides and who uses them, and Megvii’s plans for developing AI-enabled systems for new categories of enterprises. Megvii’s business model for Face++ is to maKe its application programming interfaces (API’s) available for free while licensing software kits to developers to build apps to access the API’s. Face++ services include face detection in an image, comparing faces for a match, mapping facial landmarKs, emotion recognition, gaze direction estimation, and 3D face model construction. Megvii’s products are used by major Chinese software companies such as Alipay, which uses Face++ for identity verification in its online payment system. Other companies use it for identity in computer login, dating apps, and ride sharing, and it is also used in photo editing and video sharing apps. Megvii claimed in 2017 that police use of its technology had resulted in the arrest of 5,000 wanted criminals. -
The Chinese Social Credit System
Iowa State University Capstones, Theses and Creative Components Dissertations Spring 2021 The Chinese Social Credit System Seerat Marwaha IOWA STATE UNIVERSITY Follow this and additional works at: https://lib.dr.iastate.edu/creativecomponents Part of the Management Information Systems Commons Recommended Citation Marwaha, Seerat, "The Chinese Social Credit System" (2021). Creative Components. 767. https://lib.dr.iastate.edu/creativecomponents/767 This Creative Component is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Creative Components by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. The Chinese Social Credit System Seerat Marwaha Iowa State University Masters of Science in Information Systems Gerdin- Ivy College of Business Ames, Iowa- 50014 (515) 357 9460 Office Internet: [email protected] Chinese Social Credit System ` 1 The Chinese Social Credit System ABSTRACT Financial consumer rating is a great way to track an individual consumer’s financial health, their financial decisions, and their financial management. Many countries use financial consumer ratings to gauge how responsible their citizens are when it comes to money. This allows them to know how good one is with their money, and how risky it is for them to lend any type of loan to someone. (Avery et al, 2003) Similarly, many countries now also use rating systems in relation to online platforms and in the ‘sharing economy’, such as eBay, Uber and Airbnb. This rating system helps consumers evaluate their experience and rate in order to help new consumers to make better decisions. -
Junjie Yan, Ph.D. Q [email protected]
Junjie Yan, Ph.D. Q [email protected] http://yan-junjie.github.io/ Working Experience SenseTime CTO of Smart City Group & Vice Head of Research [Since 2019.01] Lead the R&D Team within Smart City Group (SenseTime’s largest business group) to build system architectures and algorithms that make cities safer and more efficient. Lead the SenseTime Deep Learning Toolchain Team to develop the toolchain from algorithm components to distributed training and inference platform enables deep learning solutions scale up to more than 700 customers. Vice Head of Research [Since 2017.01] Founded and led the Video Intelligence Department (SenseTime’s largest research team) to build intelligent solutions about face, pedestrian, vehicle and text. Founded and led the Fundamental Research Department, which explores techniques such as AutoML, making deep learning techniques scale up to more than 400 custom- ers. Research Director [2014.11 – 2017.01] Founded the Object Perception Group and Face Recognition Group, which had led the exponential growth in both accuracy and applicable usage of face recognition. The first SenseTime Prize, and the only one Best Team Award. Baidu Research Intern [2014.04 – 2014.11]. Institute of Deep Learning, Baidu. Initialized the Reserarch of Object Detection in Baidu. Baidu Fellowship (one of the eight Chinese PhD students around the world), 2014 Excellent Research Intern (one of the two interns at Baidu IDL), 2014 Education 2016.04 – 2018.03 Postdoctoral Fellow, Department of Computer Science, Tsinghua Uni- versity in Computer Vision. Thesis title: Ecient Object Detection. Supervisor: Prof. Bo Zhang (Fellow of Chinese Academy of Sciences). 2010.09 – 2015.06 Ph.D., (Hons) National Laboratory of Pattern Recognition, Chinese Academy of Sciences in Computer Vision. -
738B APRU NYT Writing Comp Booklet V2.Indd
Artificial Intelligence Asia-Pacific Case Competition 2018 Top 10 Case Submissions Come Think With Us Digital Access. Academic Rate. The ideas, the opinions, the perspectives, the stories — that only The New York Times can provide. Written, edited and assiduously updated by the world’s leading journalists and editors, The New York Times is a powerful tool of knowledge and an indispensable means to success in the academic world. To learn more about our Education program or set up a complimentary trial for your school, please contact Fern Long at [email protected] or call +65 6391 9627 nytimes.com/groupsubs Asia-Pacific Case Competition 2018 Contents About APRU and The New York Times 6 Introduction 7 Top 10 Case Submissions Winner University of Auckland Artificial Intelligence: How A.I. Is Edging Its Way Into Our Lives Marcus Wong Jaffar Al-Shammery Bui Tomu Ozawa 9 1st Runner-up National University of Singapore Artificial Intelligence: A Policy Proposal Samuel Lim Tien Sern Marissa Chok Kay-Min 13 2nd Runner-up Nanyang Technological University Policies for the Next Digital Revolution: “01000001 01001001” Lim Zhi Xun Tan Ghuan Ming Nigel 17 3 Contents University of Sydney Artificial Intelligence Developed Intelligently Lena Wang 23 University of Hong Kong Shaping a Human-Centered Artificial Intelligence Framework Jasmine Poon 26 The Hong Kong University of Science and Technology How Asean Can Feed A.I. the Right Data Rebecca Isjwara 30 University of Sydney Artificial Intelligence in Australia: Accelerating Beyond Our Means Jonathan Gu Anton Nguyen Alan Zheng 34 University of Sydney Ensuring the Development of A.I. -
Arxiv:2003.14111V2 [Cs.CV] 19 May 2020 1
Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition Ziyu Liu1,3, Hongwen Zhang2, Zhenghao Chen1, Zhiyong Wang1, Wanli Ouyang1,3 1The University of Sydney 2University of Chinese Academy of Sciences & CASIA 3The University of Sydney, SenseTime Computer Vision Research Group, Australia Abstract Spatial-temporal graphs have been widely used by Spatial Information skeleton-based action recognition algorithms to model hu- Flow man action dynamics. To capture robust movement patterns from these graphs, long-range and multi-scale context ag- gregation and spatial-temporal dependency modeling are critical aspects of a powerful feature extractor. However, Temporal Spatial-Temporal Disentangled Multi- existing methods have limitations in achieving (1) unbi- (a) Information Flow (b) Information Flow (c) Scale Aggregation ased long-range joint relationship modeling under multi- Figure 1: (a) Factorized spatial and temporal modeling on skeleton scale operators and (2) unobstructed cross-spacetime in- graph sequences causes indirect information flow. (b) In this work, formation flow for capturing complex spatial-temporal de- we propose to capture cross-spacetime correlations with unified pendencies. In this work, we present (1) a simple method to spatial-temporal graph convolutions. (c) Disentangling node fea- disentangle multi-scale graph convolutions and (2) a uni- tures at separate spatial-temporal neighborhoods (yellow, blue, red fied spatial-temporal graph convolutional operator named at different distances, partially colored for clarity) is pivotal for ef- G3D. The proposed multi-scale aggregation scheme dis- fective multi-scale learning in the spatial-temporal domain. entangles the importance of nodes in different neighbor- hoods for effective long-range modeling. The proposed ing conditions, clothing), allowing action recognition algo- G3D module leverages dense cross-spacetime edges as skip rithms to focus on the robust features of the action.