Given the increasingly pervasive use in AI technologies in all sectors of industry and government, and the enormous potential for future AI-based technologies, NSF has asked the Computing Community Consortium to organize an AI Roadmap to help prioritize research investments. The first workshop theme is Integrated Intelligence and will take place on November 14-15, 2018 in Chicago. The chairs of the Integrated Intelligence workshop are Marie desJardins (Simmons University) and Ken Forbus (Northwestern University). This is part of the AI Roadmap workshop series – view the series page here.
Thermodynamics has been a historical concern in the engineering of conventional computing systems due to its role in power consumption, scaling, and device performance. Today, we see thermodynamics re-emerging in a new role as an algorithmic technique in areas such as machine learning, annealing, quantum, and neuromorphic systems. Recent theoretical developments in non-equilibrium thermodynamics suggest thermodynamics may become the basis of a new “thermodynamic computing” paradigm. For example, it may lead to computing systems that self-organize in response to external input.
Over the last two decades, the internet has—in many ways—transformed our daily lives from work routines to social networking. The internet is an impressive media for interconnecting computers. However, almost all these computers are passive devices with no or very limited facilities for interaction with the physical world. Robots—on the other hard—are devices designed to interact intelligently with the environment. Over the next decade or two the prediction is that robotics will impact our daily lives in manners that, at least, matches the way the internet has impacted our life.
The workshop was 1.5 days in the Washington, DC area. It was an opportunity for attendees to meet National Science Foundation program officers as well as representatives from other agencies. The content covered at the workshop came from the 2017 CCC Symposium, recent CCC visioning workshops, and CRA programs for Career Mentoring and Leadership in Science Policy.
The Cybersecurity Taskforce of the CCC will hold a leadership workshop to envision the future of embedded security research and education from hardware to cyberphysical systems to human factors.
While it has been known for some time that quantum computers could in principle solve problems that are intractable on today’s supercomputers such as breaking public key cryptography and solving hard computational chemistry problems, the field of quantum computing is still at an early stage. Recent progress in realizing small scale quantum computers is encouraging and these devices may scale up further in the near future. However, currently, only very few opportunities exist to bring quantum computing experts together with experts from other computer science fields with much to offer: programming languages, compiler design, computer architecture, and design automation in an exchange of ideas.
The Robotic Materials workshop showcased some of the ongoing interdisciplinary work at the intersection of computing, robotics, and material science.
The Computing Community Consortium (CCC) has attended and hosted sessions at the American Association for the Advancement of Science (AAAS) Annual Meeting since 2013. AAAS is the world’s largest multidisciplinary scientific society dedicated to advancing science for the benefit of all people.Below you can find information about CCC participation during each year and links to slides, resources, and related CCC white papers.
In this cross-disciplinary workshop, we will bring together leading researchers in computing, health informatics, and behavioral medicine to develop an integrative research agenda regarding sociotechnical interventions to reduce health disparities and improve the health of socio-economically disadvantaged populations. As part of these discussions, approaches for guarding against unintended consequences of general interventions will also be explored. To do so, this workshop will focus on integrating insights and findings from each of these fields, identifying gaps in understanding between fields, and surfacing opportunities for future interdisciplinary research to address relevant challenges.
This workshop aims to identify key challenges and open questions that currently limit both our theoretical understanding of fairness and machine learning, and their applicability in practice.