The following is a blog post from Jonathan Ortiz, a Data Analytics and Big Data student at The University of Texas at Austin. Ortiz participated in data.world, an Austin data startup, through a DataStart fellowship managed by the South Big Data Hub with support from the Computing Community Consortium (CCC) and the National Science Foundation (NSF). This blog was originally published by HUBBUB!, the South Big Data Hubs Blog.  As the summer semester passes its halfway point, I take a moment to reflect on just what an amazing summer it has been and think ahead to what is in store for the second half. I am a Data Analytics and Big Data student at The […]

The following is a guest blog post from Tom Conte of Georgia Tech. Is “Moore’s Law” ending? If so, what does this mean to all of us in the field of Computing? These questions were discussed at a July 2016 panel at Computing Research Association Conference at Snowbird that included a technologist (Paolo Gargini, Intel fellow-emeritus), three computer architects (Profs. David Brooks of Harvard, Mark D. Hill of Wisconsin-Madison, and Tom Conte of Georgia Tech), and a quantum computer scientist (Dr. Krysta Svore of Microsoft Research), organized by Conte and Margaret Martonosi of Princeton. Is “Moore’s Law” ending? The answer depends on what you think Moore’s Law means. First, if Moore’s […]

The White House recently released a blog celebrating the one year anniversary of the National Strategic Computing Initiative (NSCI), which was created to ensure continued U.S. leadership in high-performance computing (HPC). The blog details the important steps various Federal agencies have taken to create the foundation for a long-lasting and successful Federal initiative. A few examples are summarized below. See the White House blog to learn more. The Department of Energy (DOE) has invested in a suite of efforts to continue developing the research base for “Post-Moore’s Law era” computing. These activities include convenings, such as a workshop on neuromorphic computing and a science roundtable with representatives from national laboratories and […]

The AAAI 2017 Spring Symposium on AI for Social Good (AISOC) will be March 27-29, 2017 at Stanford University.  A rise in real-world applications of AI has stimulated significant interest from the public, media, and policy makers, including the White House Office of Science and Technology Policy (OSTP). Along with this increasing attention has come media-fueled concerns about purported negative consequences of AI, which often overlooks the societal benefits that AI is delivering and can deliver in the near future. This symposium will focus on the promise of AI across multiple sectors of society. The organizers are especially interested in addressing societal challenges, which have not yet received significant attention by the AI community […]

The DARPA Spectrum Collaboration Challenge (SC2) is the first-of-its-kind collaborative machine-learning competition to overcome scarcity in the radio frequency (RF) spectrum. Today, spectrum is managed by dividing it into rigid, exclusively licensed bands. This human-driven process is not adaptive to the dynamics of supply and demand, and thus cannot exploit the full potential capacity of the spectrum. SC2 aims to ensure that the exponentially growing number of military and civilian wireless devices will have full access to the increasingly crowded electromagnetic spectrum. Competitors will reimagine spectrum access strategies and develop a new wireless paradigm in which radio networks will autonomously collaborate and reason about how to share the RF spectrum, […]

The following is a guest blog by Vasant G Honavar, a Computing Community Consortium (CCC) council member and a Pennsylvania State University professor. The emergence of “big data” offers unprecedented opportunities for not only accelerating scientific advances but also enabling new modes of discovery. Some have gone so far as to suggest that “big data” makes the scientific method that has characterized natural science since the 17th century, consisting of systematic observation, measurement, and experiment, and the formulation, testing, and modification of hypotheses, obsolete. Nothing could be farther from truth.   The reality is that, in many disciplines, the emergence of big data exacerbates the gap between our ability to acquire, store, […]