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第十八届“二十一世纪的计算”大会演讲视频

 

以“Human and Machine Working as a Team”(人机协作)为主题的第18届“二十一世纪的计算”大型国际学术研讨会于11月3日在韩国首尔举行。本次大会上,微软亚洲研究院的研究人员与包括2002年图灵奖获得者Adi Shamir、微软全球资深副总裁Peter Lee、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洪小文博士等在内的众多计算机领域顶级大师,分享他们各自独特且深远的见解,并深入探讨在人工智能与人类智慧的结合下,改变社会的无限潜能。

大会官方网站https://www.microsoft.com/en-us/research/event/computing-21st-century-2016/

 

Chasing the Next Big Thing: Why Top Companies are Betting on Research

Peter Lee
Corporate Vice President, Microsoft Research NExT
Fellow of ACM

 

 

Abstract:

We are living in a world that is witnessing an incredible pace of innovation. Despite all the rapid advancements – or perhaps, because of them – top companies are working incredibly hard to find new ideas that will create new business opportunities. In other words, companies are more desperate than ever to find the Next Big Thing that will shake up the industry and create growth. What is remarkable today is that, in this quest, companies are increasingly turning to advanced research. This talk will outline the excitement in the industry that surrounds these eventful times, with a focus on the exhilarating journey that researchers are experiencing at Microsoft.

 

Learning at Scale as a Driver of Innovation

Marti A. Hearst
Professor, School of Information and EECS Department, UC Berkeley
Fellow of ACM

 

 

Abstract:

How can we educate the world’s population in a scalable, affordable way?  This question is driving fascinating research at the intersection of human-computer interaction, social computing, natural language processing, machine learning, and learning sciences.    I’ll discuss the state-of-the-art in what is becoming known as learning at scale, with a focus on how to improve peer feedback, how to automate grading, and how to help instructors understand what the students understand.  I will emphasize how tackling this problem is leading to new socio-technical innovations.

 

A Science of Cyber – Security?

Fred Schneider
Samuel B. Eckert Professor and Chairman, Department of Computer Science, Cornell University
Fellow of ACM, Fellow of IEEE

 

 

Abstract:

Cyber-security today is focused largely on defending against known attacks. We learn about the latest attack and find a patch to defend against it. Our defenses thus improve only after they have been successfully penetrated. This is a recipe to ensure some attackers succeed—not a recipe for achieving system trustworthiness. We must move beyond reacting to yesterday’s attacks and instead start building systems whose trustworthiness derives from first principles. Yet, today we lack such a science base for cybersecurity. That science of security would have to include attacks, defense mechanisms, and security properties; its laws would characterize how these relate. This talk will discuss examples of such laws and suggest avenues for future exploration.

 

Democratizing Urban Data Analysis

Juliana Freire
Professor, Computer Science and Engineering and Data Science, New York University
Fellow of ACM

 

Abstract:

Today, 50% of the world’s population lives in cities and the number will grow to 70% by 2050. Cities are the loci of economic activity and the source of innovative solutions to 21st century challenges. At the same time, cities are also the cause of looming sustainability problems in transportation, resource consumption, housing affordability, and inadequate or aging infrastructure. The large volumes of urban data, along with vastly increased computing power open up new opportunities to better understand cities. Encouraging success stories show better operations, more informed planning, improved policies, and a better quality of life for residents. However, analyzing urban data often requires a staggering amount of work, from identifying relevant data sets, cleaning and integrating them, to performing exploratory analyses over complex, spatio-temporal data.

Our long-term goal is to enable domain experts to crack the code of cities by freely exploring the vast amounts of data cities generate. This talk describes challenges which have led us to fruitful research on data management, data analysis, and visualization techniques. I will present methods and systems we have developed to increase the level of interactivity, scalability, and usability for spatio-temporal analyses.

This work was supported in part by the National Science Foundation, a Google Faculty Research award, the Moore-Sloan Data Science Environment at NYU, IBM Faculty Awards, NYU Tandon School of Engineering and the Center for Urban Science and Progress.

 

Co-Evolution of Artificial Intelligence and Human Intelligence

Hsiao-Wuen Hon
Corporate Vice President, Microsoft Asia-Pacific R&D Group and Microsoft Research Asia
Fellow of IEEE

Abstract:

Throughout history, human beings have developed tools and technologies which help civilizations evolve and grow. Computers, and by extension, artificial intelligence, has played important roles in that continum of technologies.

Recently artificial intelligence has garnered much interest and discussion. In this talk, I will describe areas such as computer vision and data mining where artificial intelligence has demonstrated human like capabilities. I will also talk about how human can excel in the areas of creativity and judgment. As artificial intelligence are tools that can enhance human capability, a sound understanding of what the technology can and can not do is also necessary to ensure their appropriate use.

 

Panel – Engaging with AI: How Human and Machine can Work Together to Shape the Future

Baining Guo
Assistant Managing Director, Microsoft Research Asia
Fellow of ACM, Fellow of IEEE

Seong-Whan Lee
President, Korea AI Society
Professor, Korea University
Fellow of IEEE

Jin Hyung Kim
CEO, AIRI (Artificial Intelligence Research Institute)
Professor Emeritus, KAIST Computer Science Department
Chairman, Korea National Open Data Strategy Council

Seung-won Hwang
Professor, Yonsei University

Hideyuki Tokuda
Professor, Graduate School of Media and Governance / Faculty of Environment and Information Studies, Keio University