Yoshua Bengio
蒙特利尔大学计算机科学与运筹学系教授
蒙特利尔学习算法研究所（MILA）创始人兼负责人，加拿大皇家学院（RSC）及加拿大高等研究院（CIFAR）院士
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Yoshua Bengio (computer science PhD, 1991, McGill U; post-doc at MIT and Bell Labs, computer science professor at U. Montréal since 1993): he authored three books, over 500 publications (h-index 122, over 132,000 citations), mostly in deep learning, holds a Canada Research Chair in Statistical Learning Algorithms, is Officer of the Order of Canada, recipient of the Marie-Victorin Quebec Prize 2017, Fellow of the Royal Society of Canada, and he is a CIFAR Senior Fellow and co-directs its Learning in Machines and Brains program. He is scientific director of the Mila, Quebec Artificial Intelligence Institute, currently the largest academic research group on deep learning. He is on the NIPS foundation board (previously program chair and general chair), co-created the ICLR conference (specialized in deep learning) and is scientific co-director of IVADO. He pioneered deep learning and his goal is to contribute to uncover the principles giving rise to intelligence through learning, as well as favour the development of AI for the benefit of all.
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Challenges for Deep Learning towards Human-Level AI
Humans seem to be much more efficient than current AI at learning from unlabeled observations and interaction with their environment, and current machine learning systems do not seem to understand their training data nearly as well as humans. A core objective of deep learning is to come up with learning frameworks which can discover disentangled representations which explain the important variations in the data. Progress in deep generative networks based on an adversarial criterion has been impressive and we show how these ideas can be used to estimate and optimize entropy and mutual information. and how this could be used towards unsupervised learning of high-level abstractions. This follows the ambitious objective of disentangling the underlying causal factors explaining the observed data. We argue that natural language understanding cannot come from current attempts purely based on text corpora. Instead, a learning agent must acquire information by acting in the world and jointly learn a model of the world and how languge can be used to refer to it. Natural language could be used as an additional hint about the abstract representations and disentangled factors which humans have discovered to explain their world. Some conscious thoughts also correspond to the kind of small nugget of knowledge (like a fact or a rule) which have been the main building blocks of classical symbolic AI. This therefore raises the interesting possibility of addressing some of the objectives of classical symbolic AI focused on higher-level cognition using the deep learning machinery augmented by the architectural elements necessary to implement conscious thinking about disentangled causal factors.
Lenore Blum
卡内基梅隆大学计算机科学系杰出教授
美国数学学会（AMS）院士
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Lenore Blum (PhD, MIT) is Distinguished Career Professor of Computer Science at Carnegie Mellon University (CMU) where she is also Chair in Technology Entrepreneurship and Founding Director of Project Olympus, a proof-of-concept innovation center she founded in 2007 that works with faculty and students to bridge the gap between cutting-edge university research/innovation and economy-promoting commercialization. Since 2007, over half the Carnegie Mellon start-ups have come through Project Olympus. Project Olympus is a good example of Lenore Blum’s determination to make a real difference in the academic community and the world beyond.
Lenore is internationally recognized for her work in increasing the participation of girls and women in Science, Technology, Engineering, and Math (STEM) fields. She was founding co-Director of the Math/Science Network and its Expanding Your Horizons conferences which has served over one million middle and high school girls since inception in the early 1970s. In 1974, Lenore founded the Mills College Computer Science Department, the first at any women’s college on the planet. Arriving at CMU in 1999, she founded the Women@SCS program –currently half the CS majors at CMU are women. In 2004 Lenore received the US Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring. In 2009 she received the Carnegie Science Catalyst Award and in 2018, she received Carlow University’s Women of Spirit Award and the Lifetime Achievement Award from Simmons University.
Lenore has served the professional community in numerous capacities, including as third President of the Association for Women in Mathematics and Vice President of the American Mathematical Society (AMS). She has taught at the University of California at Berkeley, was a Senior Researcher at the International Computer Science Institute and Deputy Director of the Mathematical Sciences Research Institute, both also in Berkeley. Lenore is a Fellow of the American Association for the Advancement of Science and inaugural fellow of the AMS and the AWM.
Lenore’s research, from her early work in model theory and differential fields (logic and algebra) to her more recent work in developing a theory of computation and complexity over the real numbers (mathematics and computer science), has focused on merging seemingly unrelated areas. Lenore is excited by her new research (with her husband Manuel and son Avrim) on creating a mathematical model for a “conscious AI.”
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Towards a Conscious AI: A Computer Architecture Inspired by Cognitive Neuroscience
Thanks to major advances in neuroscience, we are on the brink of a scientific understanding of how the brain achieves consciousness. This talk will describe cognitive neuroscientist Bernard Baars’ Global Workspace Model (GWM) of the brain, its implications for understanding consciousness, and a formal computer architecture that it inspires. The elder Blums were ecstatic to learn that the younger Blum’s “sleeping experts” algorithm was just what was needed to decide which unconscious processors get onto the conscious stage. The Model gives insight for the design of machines that truly experience (as opposed to simulate) feelings such as joy and pain.
丛京生
加州大学洛杉矶分校计算机科学系杰出校长讲席教授
美国计算机协会（ACM）、美国电气和电子工程师协会（IEEE）及美国国家工程院（NAE）院士
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JASON CONG received his B.S. degree in computer science from Peking University in 1985, his M.S. and Ph. D. degrees in computer science from the University of Illinois at Urbana-Champaign in 1987 and 1990, respectively. Currently, he is a Distinguished Chancellor’s Professor at the Computer Science Department, also with joint appointment from the Electrical Engineering Department, of University of California, Los Angeles, the director of Center for Domain-Specific Computing (CDSC), and the director of VLSI Architecture, Synthesis, and Technology (VAST) Laboratory. He served as the chair the UCLA Computer Science Department from 2005 to 2008. Dr. Cong’s research interests include novel architectures and compilation for customizable computing, synthesis of VLSI circuits and systems, and highly scalable algorithms. He has over 400 publications in these areas, including 11 best paper awards, three 10-Year Most Influential Paper Awards, and the first paper inducted to the FPGA and Reconfigurable Computing Hall of Fame. He and his former students co-founded AutoESL, which developed the most widely used high-level synthesis tool for FPGAs (renamed to Vivado HLS after Xilinx’s acquisition). He was elected to an IEEE Fellow in 2000, ACM Fellow in 2008, and the National Academy of Engineering in 2017.
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Automating Customizable Computing —Democratizing Accelerator Designs at the Edge and in the Cloud
In the past decade, CDSC has been exploring customizable computing, which emphasizes extensive use of customized accelerators on programmable fabrics for much greater performance and energy efficiency. With Intel’s $17B acquisition of Altera in 2015 and large-scale deployment of FPGAs in both private and public clouds in the past two years, customizable computing is going from advanced research into mainstream computing.
Although the performance and energy efficiency benefits of customizable computing have been clearly demonstrated, a significant challenge, however, is the efficient design and implementation of various accelerators on FPGAs. It presents a significant barrier to many software programmers. In this talk, I shall talk about our effort on developing an automated compilation flow from high-level programming languages to FPGAs. I start with a quick review of our early work on high-level synthesis. Then, I shall present our recent effort on source-code level transformation and optimization for customizable computing, including support of high-level domain-specific languages (DSL) for deep learning (e.g. Caffe), imaging processing (e.g. Halide), and big-data processing (e.g. Spark), and support automated compilation to customized microarchitecture templates, such as systolic arrays, stencils, and CPP (composable parallel and pipelined).
洪小文
微软全球资深副总裁，微软亚太研发集团主席兼微软亚洲研究院院长
美国电气和电子工程师协会（IEEE）院士
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Dr. Hsiao-Wuen Hon is corporate vice president of Microsoft, chairman of Microsoft’s Asia-Pacific R&D Group, and managing director of Microsoft Research Asia. He drives Microsoft’s strategy for research and development activities in the Asia-Pacific region, as well as collaborations with academia.
Dr. Hon has been with Microsoft since 1995. He joined Microsoft Research Asia in 2004 as deputy managing director, stepping into the role of managing director in 2007. He founded and managed Microsoft Search Technology Center from 2005 to 2007 and led development of Microsoft’s search products (Bing) in Asia-Pacific. In 2014, Dr. Hon was appointed as chairman of Microsoft Asia-Pacific R&D Group.
Prior to joining Microsoft Research Asia, Dr. Hon was the founding member and architect of the Natural Interactive Services Division at Microsoft Corporation. Besides overseeing architectural and technical aspects of the award-winning Microsoft Speech Server product, Natural User Interface Platform and Microsoft Assistance Platform, he was also responsible for managing and delivering statistical learning technologies and advanced search. Dr. Hon joined Microsoft Research as a senior researcher in 1995 and has been a key contributor to Microsoft’s SAPI and speech engine technologies. He previously worked at Apple, where he led research and development for Apple’s Chinese Dictation Kit.
An IEEE Fellow and a distinguished scientist of Microsoft, Dr. Hon is an internationally recognized expert in speech technology. Dr. Hon has published more than 100 technical papers in international journals and at conferences. He co-authored a book, Spoken Language Processing, which is a graduate-level textbook and reference book in the area of speech technology used in universities around the world. Dr. Hon holds three dozen patents in several technical areas.
Dr. Hon received a Ph.D. in Computer Science from Carnegie Mellon University and a B.S. in Electrical Engineering from National Taiwan University.
Eric Horvitz
微软技术院士、微软研究院院长
美国计算机协会（ACM）院士、美国国家工程院（NAE）院士、美国人工智能协会（AAAI）院士
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Eric Horvitz is a technical fellow and director at Microsoft Research. He has made contributions in areas of machine learning, perception, natural language understanding, decision making, and human-AI collaboration. His efforts and collaborations have led to fielded systems in healthcare, transportation, ecommerce, operating systems, and aerospace. He received the Feigenbaum Prize and the Allen Newell Prize for contributions to AI. He has been elected fellow of the National Academy of Engineering (NAE), the Association of Computing Machinery (ACM) , Association for the Advancement of AI (AAAI), and the American Academy of Arts and Sciences. He has served as president of the AAAI, and on advisory committees for the National Science Foundation, National Institutes of Health, President’s Council of Advisors on Science and Technology, DARPA, and the Allen Institute for AI. Beyond technical work, he has pursued efforts and studies on the influences of AI on people and society, including issues around ethics, law, and safety. He established the One Hundred Year Study on AI and served as a founder and co-chair of the Partnership on AI to Support People and Society. Eric received PhD and MD degrees at Stanford University. More information can be found on his home page. A list of publications can be found here.
Butler Lampson
微软新英格兰研究院技术院士
1992年图灵奖获得者，英国皇家学会外籍院士，美国国家科学院（NAS）及美国国家工程院（NAE）院士
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Butler Lampson is a Technical Fellow at Microsoft Corporation and an Adjunct Professor at MIT. He has worked on computer architecture, local area networks, raster printers, page description languages, operating systems, remote procedure call, programming languages and their semantics, programming in the large, fault-tolerant computing, transaction processing, computer security, WYSIWYG editors, and tablet computers. He was one of the designers of the SDS 940 time-sharing system, the Alto personal distributed computing system, the Xerox 9700 laser printer, two-phase commit protocols, the Autonet LAN, the SPKI system for network security, the Microsoft Tablet PC software, the Microsoft Palladium high-assurance stack, and several programming languages. He received the ACM Software Systems Award in 1984 for his work on the Alto, the IEEE Computer Pioneer award in 1996 and von Neumann Medal in 2001, the Turing Award in 1992, and the NAE’s Draper Prize in 2004. He is a member of the US National Academies of Sciences and of Engineering, and a Foreign Member of the Royal Society.
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Computer Technology and Public Policy
As computing becomes pervasive in society, there are many cases where technology must work hand-in-hand with regulation or social processes. Here are three examples: (1) As a technology, blockchain does not deserve the hype that it gets. Its true value is shock value: many established practices could have been drastically improved by computers 15 years ago, but inertia has kept them unchanged. Now people ask, “What are you doing about blockchain?” and if you don’t have an answer you look like an idiot, even though usually the answer has little to do with blockchain. (2) Soon there will be lots of IoT devices can kill people if they malfunction, whether the cause is bugs or hacking. To make them safe, they need two things: a secure foundation, and an architecture that entrusts safety to a well-isolated component that is simple enough to be formally verify. (3) People want is a sense of control over their online data. Control means that you can tell who has your data, limit what they can do with it, and change your mind about the limits. There will not be a single worldwide regulatory regime, but it does seem possible to have common technical mechanisms that support regulation.
Raj Reddy
卡内基梅隆大学计算机科学系教授
1994年图灵奖获得者，美国电气和电子工程师协会（IEEE）及美国人工智能协会（AAAI）院士
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Raj Reddy is a University Professor of Computer Science and Robotics, and Moza Bint Nasser Chair at Carnegie Mellon University. He was an Assistant Professor at Stanford from 1966-69 and Faculty Member at Carnegie Mellon since 1969. He served as the founding Director of the Robotics Institute from 1979 to 1991 and the Dean of School of Computer Science from 1991 to 1999.
He has been active in AI research for over five decades in the areas of AI, Speech Understanding, Image Understanding, Robotics, Multi-sensor Fusion, and Intelligent Agents.Dr. Reddy’s current research interests include: Technology in Service of Society, Voice Computing for the 3B semi-literate populations at the bottom of the pyramid, Digital Democracy, and Learning Science and Technologies.He is a member of the National Academy of Engineering and a foreign member of China Academy Engineering. He served as co-chair of President Clinton’s Information Technology Advisory Committee (PITAC) from 1999 to 2001. Dr. Reddy is the recipient of the Legion of Honor in 1984, the ACM Turing Award in 1994, the Padma Bhushan in 2001, the Honda Prize in 2005 and Vannevar Bush Award in 2006.
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AI: Background, History and Future Opportunities
There has been a lot hype and misinformation about AI in the media recently. Many of these predictions will not happen. Robots will not take over the world. In this talk, we will review tools, techniques and advances in AI over the past half century and explore what might be next. We will present two types of Intelligent Assistants, namely, Cognition Amplifiers that will enable us to do many daily tasks faster and with less effort and Guardian Angels that will provide us with superhuman capabilities, to do tasks previously impossible for humans. We will present a possible Architecture of Intelligent Agents and the creation of Intelligent Agent market place.
沈向洋
微软全球执行副总裁，微软人工智能及微软研究事业部负责人
美国计算机协会（ACM）、美国电气和电子工程师协会（IEEE）及美国国家工程院（NAE）院士、英国皇家工程院（RAE）外籍院士
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Harry Shum is executive vice president of Microsoft’s Artificial Intelligence (AI) and Research group.He is responsible for driving the company’s overall AI strategy and forward-looking research and development efforts spanning infrastructure, services, apps and agents. He oversees AI-focused product groups including Bing and Cortana. He also leads Microsoft Research, one of the world’s premier computer science research organizations, and its integration with the engineering teams across the company.
Previously, Dr. Shum served as the corporate vice president responsible for Bing search product development from 2007 to 2013. Prior to his engineering leadership role at Bing and online services, he oversaw the research activities at Microsoft Research Asia and the lab’s collaborations with universities in the Asia Pacific region, and was responsible for the Internet Services Research Center, an applied research organization dedicated to advanced technology investment in search and advertising at Microsoft.
Dr. Shum joined Microsoft Research in 1996 as a researcher based in Redmond, Washington. In 1998 he moved to Beijing as one of the founding members of Microsoft Research China (later renamed Microsoft Research Asia). There he began a nine-year tenure as a researcher, subsequently moving on to become research manager, assistant managing director and managing director of Microsoft Research Asia and a Distinguished Engineer.
Dr. Shum is an IEEE Fellow and an ACM Fellow for his contributions to computer vision and computer graphics. He received his Ph.D. in robotics from the School of Computer Science at Carnegie Mellon University. In 2017, he was elected to the National Academy of Engineering of the United States. In September 2018, he was elected an International Fellow of the Royal Academy of Engineering in honor of his outstanding engineering achievements.
姚期智
清华大学交叉信息研究院教授兼院长
2000年图灵奖获得者，中国科学院（CAS）院士，美国国家科学院（NAS）外籍院士，美国计算机协会（ACM）院士
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Andrew Chi-Chih Yao is Dean of the Institute for Interdisciplinary Information Sciences at Tsinghua University, member of the Chinese Academy of Sciences, and foreign member of the US Academy of Sciences.
Professor Yao is a world-renowned computer scientist and pioneer in analysis of algorithms, cryptography and quantum computing. He was recipient of the Turing Award in 2000 and to date the only Chinese scientist receiving this highest honor in computer science. Professor Yao was previously on the faculty at MIT, Stanford, UC Berkeley and Princeton University before joining Tsinghua in 2004. He founded the Tsinghua Center for Quantum Information and Institute for Interdisciplinary Information Sciences in 2011. Outside of Tsinghua, Professor Yao built the Turing AI Institute (Nanjing) and the Interdisciplinary Core Technology Institute (Xian) in 2018 to enable close innovation partnerships with municipalities.
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The Advent of Quantum Computing
In recent years, scientists have made much progress in the theory and implementation of quantum computing. Many now believe that the exciting prospect of building a real quantum computer will happen before long. Common curiosity drives one to ask: What advantages might quantum computers hold over traditional ones? What secrets in the quantum world could be unlocked to produce enormous power for computing and information processing? In this talk, we will take an in-depth look into the above questions. We will also remark on the present and future of quantum computing.
Panelists:
Peter Lee
微软全球资深副总裁
美国计算机协会（ACM）院士
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Dr. Peter Lee is Corporate Vice President, Microsoft Healthcare. He leads an organization that works on technologies for better and more efficient healthcare, with a special focus on artificial intelligence and cloud computing. Dr. Lee has extensive experience in managing the process of going from basic research to commercial impact. Past illustrative examples include the deep neural networks for simultaneous language translation in Skype, next-generation IoT technologies, and innovative silicon and post-silicon computer architectures for Microsoft’s cloud. He also has a history of advancing more “out of the box” technical efforts, such as experimental under-sea datacenters, augmented-reality experiences for HoloLens and VR devices, digital storage in DNA, and social chatbots such as XiaoIce and Tay.
Previously, as an Office Director at DARPA, he led efforts that created operational capabilities in advanced machine learning, crowdsourcing, and big-data analytics, such as the DARPA Network Challenge and Nexus 7. He was formerly the Head of Carnegie Mellon University’s computer science department. As a thought leader, he has spoken and written widely on technology trends and policies, spanning the fields of computing technology, healthcare, and innovation ecosystem. He is a member of the Boards of Directors of the Allen Institute for Artificial Intelligence and the Kaiser Permanente School of Medicine. He served on President’s Commission on Enhancing National Cybersecurity. He has led studies for the National Academies on the impact of federal research investments on economic growth and testified before the US House Science and Technology Committee and the US Senate Commerce Committee.
Tsuhan Chen
新加坡国立大学副校长
美国电气和电子工程师协会（IEEE）院士
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Prof. Chen Tsuhan is the Deputy President (Research and Technology) and Distinguished Professor at National University of Singapore (NUS). He also serves as the Chief Scientist of AI Singapore, a national programme in artificial intelligence.
Prof. Chen is a renowned expert in pattern recognition, computer vision and machine learning. He joined NUS from Cornell University, Ithaca, New York, United States, where he had been the David E. Burr Professor of Engineering since 2009. From 2009 to 2013, when he served as Director, School of Electrical and Computer Engineering at Cornell, he promoted the School to top ranking positions and launched several initiatives to boost innovation as well as foster research and teaching excellence. He also directed the Advanced Multimedia Processing Laboratory. From 1997 to 2008, Prof. Chen was a Professor with the Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA, where he served as the Associate Department Head from 2007 to 2008.
Prof. Chen was the Cheng Tsang Man Chair Professor and Dean of the College of Engineering (CoE) at the Nanyang Technological University (NTU) from 2015 to 2017. He championed faculty recruitment and pioneered support schemes at the NTU CoE to encourage inter-school multidisciplinary programmes, aligned with the domain areas identified in RIE2020.
Prof. Chen was appointed the Editor-in-Chief for IEEE Transactions on Multimedia in 2002-2004. He was elected to the Board of Governors, 2007-2009, and a Distinguished Lecturer, 2007-2008, both with the IEEE Signal Processing Society.
Prof. Chen received the Charles Wilts Prize for outstanding independent research at the California Institute of Technology in 1993. He was a recipient of the US National Science Foundation CAREER Award from 2000 to 2003. He received the Benjamin Richard Teare Teaching Award in 2006, the Eta Kappa Nu Award for Outstanding Faculty Teaching in 2007, both at the Carnegie Mellon University, and the Michael Tien Teaching Award in 2014 at the Cornell University.
Prof. Chen has published more than 300 technical papers and holds close to 30 US patents. He is a member of the Phi Tau Phi Scholastic Honor Society, a Fellow of IEEE, and a Fellow of the Institute of Engineers, Singapore. He earned his PhD degree in electrical engineering from the California Institute of Technology, Pasadena, California, USA, in 1993.
John Hopcroft
康奈尔大学计算机科学系教授
1986年图灵奖获得者，美国国家科学院（NAS）及美国国家工程院（NAE）院士，中国科学院（CAS）外籍院士
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John E. Hopcroft is the IBM Professor of Engineering and Applied Mathematics in Computer Science at Cornell University. His research centers on theoretical aspects of computer science. He was dean of Cornell’s College of Engineering from 1994 to 2001.
In 1992 he was appointed by President George H.W. Bush to the National Science Board, which oversees the National Science Foundation, and served through May 1998. He serves on Microsoft’s Technical Advisory Board for Research Asia, and the advisory boards of IIIT Delhi and Seattle University’s College of Engineering.
He is a member of the National Academy of Engineering (1989) and National Academy of Sciences (2009), and a fellow of the American Academy of Arts and Sciences, American Association for the Advancement of Science, Institute of Electrical and Electronics Engineers (IEEE), Association of Computing Machinery (ACM), and Society of Industrial and Applied Mathematics.
He has received the A.M. Turing Award (1986), IEEE Harry Goode Memorial Award (2005), Computing Research Association’s Distinguished Service Award (2007), ACM Karl V. Karlstrom Outstanding Educator Award (2009), IEEE John von Neumann Medal (2010), and China’s Friendship Medal (2016), China’s highest recognition for a foreigner. In addition, the Chinese Academy of Sciences has designated him an Einstein professor.
He has honorary degrees from Seattle University, the National College of Ireland, the University of Sydney, St. Petersburg State University in Russia, Beijing University of Technology, and Hong Kong University of Science and Technology, and is an honorary professor of the Beijing Institute of Technology, Shanghai Jiao Tong University, Chongqing University, Yunnan University, and Peking University.
He received his BS (1961) from Seattle University and his MS (1962) and PhD (1964) in electrical engineering from Stanford University.
Seung-won Hwang
延世大学计算机科学系教授
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Prof. Seung-won Hwang is a Professor of Computer Science at Yonsei University. Prior to joining Yonsei, she had been an Associate Professor at POSTECH for 10 years, after her PhD from UIUC. Her recent research interest has been data and language understanding and intelligence, led to 100+ publication at top-tier AI, DB/DM, and NLP venues, including ACL, AAAI, IJCAI, NAACL, SIGMOD, VLDB, and ICDE. She has received best paper runner-up and outstanding collaboration award from WSDM and Microsoft Research respectively.
Butler Lampson
微软新英格兰研究院技术院士
1992年图灵奖获得者，英国皇家学会外籍院士，美国国家科学院（NAS）及美国国家工程院（NAE）院士
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Butler Lampson is a Technical Fellow at Microsoft Corporation and an Adjunct Professor at MIT. He has worked on computer architecture, local area networks, raster printers, page description languages, operating systems, remote procedure call, programming languages and their semantics, programming in the large, fault-tolerant computing, transaction processing, computer security, WYSIWYG editors, and tablet computers. He was one of the designers of the SDS 940 time-sharing system, the Alto personal distributed computing system, the Xerox 9700 laser printer, two-phase commit protocols, the Autonet LAN, the SPKI system for network security, the Microsoft Tablet PC software, the Microsoft Palladium high-assurance stack, and several programming languages. He received the ACM Software Systems Award in 1984 for his work on the Alto, the IEEE Computer Pioneer award in 1996 and von Neumann Medal in 2001, the Turing Award in 1992, and the NAE’s Draper Prize in 2004. He is a member of the US National Academies of Sciences and of Engineering, and a Foreign Member of the Royal Society.