A new episode of the Computing Community Consortium‘s (CCC) official podcast, Catalyzing Computing, is now available. Khari Douglas interviews Gregory D. Hager, a professor of computer science at Johns Hopkins University and the founding director of the Johns Hopkins Malone Center for Engineering in Healthcare. In this episode, Hager discusses medical applications for AI and robotics, tactile perception, the founding of the Malone Center, and data privacy. This will be the​ last episode of Catalyzing Computing hosted and produced by Khari, because he will be joining the editorial team at Overheard at National Geographic, “a podcast which follows explorers, photographers, and scientists to the edges of our big, weird, beautiful world.” Thanks for listening […]

Bayer, the pharmaceutical company that owns big name brands such as Aspirin, Aleve, Midol, Cenesten and Iberogast, recently partnered with Ada Health, an AI-based assessment platform. This free app uses an AI chat robot to collect information on symptoms, patient history and other user targeted questions to generate data-driven suggestions for next steps and proper care. “Ada’s technology is based on a custom-built reasoning engine and a highly comprehensive medical knowledge base, covering thousands of conditions. In fact, in a recent vignettes study testing the eight most popular online symptom assessment apps, Ada was proven to have the most comprehensive condition coverage, providing a condition suggestion 99% of the time, […]

The following Great Innovative Idea is from Yonatan Bisk, Assistant Professor in the School of Computer Science and member of the Language Technologies Institute at Carnegie Mellon University. The Idea Language learning requires physically existing in the world (not being just a brain in a jar). A child doesn’t learn language from reading Wikipedia.  They build rich models of the world by seeing and doing.  They understand other humans as socially intelligent and cooperative agents with whom to speak and from whom to learn.  Yet, natural language “understanding” systems have focused on training in an impoverished disembodied text-only setting — trying to download as much text off the internet and […]

The National Artificial Intelligence (AI) Research Resource (NAIRR) Task Force convened its third virtual public meeting to further develop a vision and implementation plan for the NAIRR. Computing Community Consortium (CCC) Council member Ian Foster (Argonne National Laboratory and University of Chicago), was invited to speak about the recently published A National Discovery Cloud: Preparing the US for Global Competitiveness in the New Era of 21st Century Digital Transformation white paper.  In addition, 84 responses from industry, academia, and government stakeholders were recently released regarding the White House Office of Science and Technology Policy and the National Science Foundation request for information to develop an implementation roadmap for the NAIRR. […]

Rika Antonova began her CIFellowship in January 2021 after receiving her PhD from KTH Royal Institute of Technology in Stockholm in December 2020. Antonova is at Stanford University working with Jeannette Bohg, Assistant Professor of Robotics at Stanford.  Current Project Machine learning is transforming robotics: we can now solve high-dimensional problems that have been intractable before, if given large amounts of data and ample training time. However, to go beyond structured factory settings, it is important for robots to adapt to changes in the environment/task without lengthy re-training and data collection. A related problem is closing the simulation-to-reality gap: adapting to the real world after training in simulation. My goal […]

The Computing Community Consortium (CCC) is pleased to announce the release of a new white paper,  A National Discovery Cloud: Preparing the US for Global Competitiveness in the New Era of 21st Century Digital Transformation, led by Ian Foster with significant support from Daniel Lopresti, Bill Gropp, Mark D. Hill, and Katie Schuman. The three “pillars,” as the paper calls them, of this new computation fabric include the “emergence of public cloud utilities as a new computing platform; the ability to extract information from enormous quantities of data via machine learning; and the emergence of computational simulation as a research method on par with experimental science.”  In order for the […]