Vote for ACM Session Proposals for SXSW 2017
ACM is once again submitting proposals to participate in the South by Southwest Interactive Conference (SXSW Interactive), a 10-day event that gathers diverse topics and people to explore what’s next in the worlds of entertainment, culture, and technology. The conference takes place in Austin, Texas, March 10 to 19, 2017.
Public voting is an important component of the proposal selection process, so we encourage you to help make sure ACM continues to be represented at this dynamic interdisciplinary event. Voting is open to anyone with access to the Internet, and all you need to do to vote is to set up an SXSW PanelPicker account, which is quick, easy and free. Voting is open until September 2.
Please vote, and help ACM in our bid to be a part of this unique convergence of original music, independent film, and emerging technologies.
The four ACM submissions are:
- Wendy Hall: Saving the Web: Internet Histories for the Future
Preserving the contents of the World Wide Web is an increasingly vital activity. The Web today is a ubiquitous global information system, and yet significant amounts of its contents disappear daily. The average Web page remains online for barely 100 days and increasingly the content is fleetingly dynamic. In this session we will explore the challenges involved with archiving the Internet—how do we decide what should be preserved, who should be responsible for preserving it, how do we make it available for the scholars of the future, and why is it so important for the future of the Internet and the good of humanity that we treat this as an activity of increasing global significance.
- Jeff Heer: Interactive Data Analysis: Visualization & Beyond
Data analysis is a complex process with frequent shifts among data formats, tools and models, as well as between symbolic and visual thinking. In this session, we will consider how to accelerate people's exploration and understanding of data by crafting a careful balance of interactive and automated methods. We will examine how to combine concepts from data visualization, machine learning, and computer systems to design novel interactive analysis tools, covering both interactive demos and principles from academic research. Participants should expect to learn about current trends in visual data analysis tools and gain new insights applicable to their own work.
- Chris Bregler: Next Gen Motion Capture for Movies and Crowd Games
Motion Capture, originally a technology used in medical labs to record human performance, is now ubiquitous in film and TV, games, sports, surveillance, and home entertainment. This talk will show the cutting edge of Motion Capture and new Computer Vision techniques in journalism, Olympic sports, interactive games for crowds, and film effects, for which Bregler won an Academy Award in 2016. From setting up underwater cameras in Olympic pools to tracking actors’ facial subtleties for Hollywood movie footage, Bregler will explore the outer limits of Motion Capture. As an option, at the end of the talk, Bregler’s team could involve the SXSW audience in an interactive mocap game.
- Eric Horvitz: AI on the Horizon: Challenges, Directions, Futures
Artificial intelligence (AI) is at an inflection point and is poised to move into the open world and into our lives in numerous ways that will have numerous influences on people and society. While AI promises to provide great value, along with the promises and aspirations come concerns about potential costs, failures, and rough edges. Concerns include failures of automation in safety-critical domains, influences on jobs and economy, use of biased data and algorithms, and runaway AI. I address short- and longer-term challenges and touch on reflections and studies including the AAAI Asilomar Study and the One Hundred Year Study on AI at Stanford University.
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ACM Queue’s “Research for Practice” is your number one resource for keeping up with emerging developments in the world of theory and applying them to the challenges you face on a daily basis. In this installment, Dan Crankshaw and Joey Gonzalez provide an overview of machine learning server systems. What happens when we wish to actually deploy a machine learning model to production, and how do we serve predictions with high accuracy and high computational efficiency? Dan and Joey’s curated research selection presents cutting-edge techniques spanning database-level integration, video processing, and prediction middleware. Given the explosion of interest in machine learning and its increasing impact on seemingly every application vertical, it's possible that systems such as these will become as commonplace as relational databases are today.