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.


Posts Tagged ‘IARPA

 

IARPA- Future Computer Systems (FCS) RFI

October 22nd, 2018 / in Announcements, research horizons, Research News / by Helen Wright

The Intelligence Advanced Research Projects Activity (IARPA) is seeking information on research efforts in the area of innovative, new computer hardware and software architectures with intelligent computer environments. This request for information (RFI) is issued solely for information gathering and planning purposes; it does not constitute a formal solicitation for proposals. Over the past 60 years, computers have become orders-of-magnitude faster and both more complex and more diverse, but the computational model (i.e., the model for how algorithms/computations are executed) has not substantially changed. Consequently, the demands on users for system expertise have escalated to prohibitive levels. Future computing systems (FCS) should be a revolutionary class of advanced computers with both a […]

IARPA Request For Information – Novel Training Datasets and Environments to Advance Artificial Intelligence

February 16th, 2016 / in Announcements, Research News, resources / by Helen Wright

Artificial intelligence (AI) has captured the public’s imagination for over 60 years, but it has proceeded in fits and starts leading to what has become known as an “AI winter” – a long period of diminished research and funding activity. Until recently, the conventional wisdom has been that new algorithms were the limiting factor in making steady progress towards artificial intelligence. However, recent advances in machine learning, have established that historical algorithms in conjunction with high-performance computers can be used to achieve nearly human-level performance on diverse tasks such as image and speech recognition, language translation, and video game play. In each of these instances rapid progress was facilitated by the […]