Computing Community Consortium Blog

The goal of the Computing Community Consortium (CCC) is to catalyze the computing research community to debate longer range, more audacious research challenges; to build consensus around research visions; to evolve the most promising visions toward clearly defined initiatives; and to work with the funding organizations to move challenges and visions toward funding initiatives. The purpose of this blog is to provide a more immediate, online mechanism for dissemination of visioning concepts and community discussion/debate about them.


Archive for the ‘policy’ category

 

CRA’s Career Mentoring Workshop Registration is Now Open!

October 14th, 2019 / in Announcements, CRA, policy, Research News / by Helen Wright

The following is a message to the community from the Computing Research Association (CRA) Executive Director Andrew Bernat.  Dear Colleague, I am pleased to announce that CRA’s Career Mentoring Workshop will take place February 27-28, 2020, in Washington, DC. The application link is here. The deadline to apply (for guaranteed attendance for CRA member institution participants) is October 31st. Appropriate participants from CRA-member institutions are automatically accepted (until we run out of physical space); we will accept participants from non-CRA member institutions if there is space (at a higher registration fee).If you have attended or know someone who has, then you know that this workshop gets raves as a kickstart […]

AI Research: Times They Are A-Changin’ (or They Should Be)

October 2nd, 2019 / in AI, Announcements, policy, research horizons, Research News / by Helen Wright

The following blog was written by Computing Community Consortium (CCC) Vice-Chair Liz Bradley from University of Colorado Boulder and CCC Chair Mark D. Hill from the University of Wisconsin Madison. Times in Artificial Intelligence are or should be changing. See Bob Dylan’s 1964 lyrics below.  Last week the New York Times published an article titled “A.I. Researchers See Danger of Haves and Have-Nots.” Modern AI research, which demands enormous computational resources, large data sets, and significant human expertise, is becoming increasingly difficult for anyone outside the large tech companies like Google, Microsoft, Amazon and Facebook. This includes university labs—which, as the article points out, have traditionally been a wellspring of […]

Upcoming NSF Funding Opportunities

September 4th, 2019 / in Announcements, NSF, policy, research horizons, Research News, resources / by Helen Wright

The National Science Foundation (NSF) has a number of upcoming funding opportunities. Computational and Data-Enabled Science and Engineering  (CDS&E) (PD 12-8084) Full Proposal Window: September 30, 2019 Advanced computational infrastructure and the ability to perform large-scale simulations and accumulate massive amounts of data have revolutionized scientific and engineering disciplines. The goal of the CDS&E program is to identify and capitalize on opportunities for major scientific and engineering breakthroughs through new computational and data analysis approaches. See more at this website here. Computer and Information Science and Engineering (CISE): Core Programs (NSF 19-589) Full Proposal Window: September 30, 2019 The NSF CISE Directorate supports research and education projects that develop new […]

NSF/Intel Partnership on Machine Learning for Wireless Networking Systems (WLWiNS) Program Webinar

August 28th, 2019 / in Announcements, NSF, policy, research horizons, Research News / by Helen Wright

The National Science Foundation (NSF) is holding a webinar on September 11, 2019 at 2:00 PM ET for the NSF/Intel Partnership on Machine Learning for Wireless Networking Systems (MLWiNS) solicitation NSF 19-591, submission requirements, and program updates. The NSF/Intel Partnership on Machine Learning for Wireless Networking Systems (MLWiNS) seeks to accelerate fundamental, broad-based research on wireless-specific machine learning (ML) techniques, towards a new wireless system and architecture design, which can dynamically access shared spectrum, efficiently operate with limited radio and network resources, and scale to address the diverse and stringent quality-of-service requirements of future wireless applications. In parallel, this program also targets research on reliable distributed ML by addressing the challenge […]

CCC Response to NITRD RFI “Information on Update to Strategic Computing Objectives”

August 22nd, 2019 / in Announcements, CCC, policy, Research News / by Helen Wright

The following post was contributed by CCC Director,  Ann Schwartz Drobnis.  The Networking and Information Technology Research and Development (NITRD) National Coordination Office (NCO), on behalf of Federal agencies and the NITRD National Science and Technology Council’s (NSTC) Fast-Track Action Committee (FTAC) on Strategic Computing (SC), put out a Request for Information (RFI) from the public to update for the Strategic Computing R&D goals and approaches. The Computing Community Consortium (CCC) responded to the RFI on behalf of the community. Some snippets from CCC’s response: Many—if not most—of the benefits that information technology has provided to society have in turn depended on tremendous progress in technology (Moore’s Law) and in hardware designs for compute, storage, and communication. Future information […]

White House Issues Plan for Federal Engagement in AI Technical Standards

August 12th, 2019 / in AI, Announcements, policy, resources / by Helen Wright

Today, the White House, through the National Institute of Standards and Technology (NIST), issued a plan for Federal engagement in the development of technical standards for artificial intelligence (AI). The plan was called for as part of the national strategy for U.S. leadership in AI, the American AI Initiative, launched by Executive Order in February 2019. After receiving broad public input, the technical standards plan provides guidance for Federal agencies, the private sector, and the academic community in the development of technical standards and related tools in support of reliable, robust, and trustworthy AI systems, and identifies priorities for Federal government involvement and leadership in AI standards development. “The Trump […]