IARPA posts Future Computing Systems RFI
On October 17, the Intelligence Advanced Research Projects Activity posted a request for information about Future Computing Systems. Responses are due by 4:00 p.m. Eastern on December 14.
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. The following sections of this announcement contain details on the scope of technical efforts of interest, along with instructions for the submission of responses.
Future computing systems (FCS) should be a revolutionary class of advanced computers with both a new highly-capable architecture and an intelligent computational environment that “understands” its own state (as well as natural input commands), learns new concepts (which are then codified into knowledge), and uses this knowledge to skillfully deliver directed goals. FCS should enable users to focus on (rather than be distracted from) their applications, and to assist (rather than hinder) them in achieving their goals.
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. Concurrently, the need for real-time (or near-real-time) analysis of massive amounts of heterogeneous data in this new era of explosive data growth has dramatically broadened the application space for advanced computers beyond conventional HPC applications and has compounded the need for ever-increasing computer capacity, capability, response times, and agility. The current volume and variety of data are already beginning to exceed the ability of today’s most advanced classical systems to deliver optimal solutions.
The time is long overdue for redesigning computers to be smarter and more self-sufficient, while continuing to deliver increasing performance to meet escalating demands. Computers need to be “intelligent systems” capable of assisting humans and other computers in executing extremely complex and data-intensive tasks, as well as of monitoring and maintaining their own operation. Such systems must be able to assist users in solving not only problems critical to national security and economic prosperity but also equally those that characterize all aspects of modern life.
To accomplish these goals, FCS should have three important new aspects: 1) a knowledge base/inference engine of cognitive and computer system management functions that is integral to system operation at all levels, 2) a machine learning capability that is integrated with the knowledge base to provide a unified “informed learning system” (i.e., the knowledge base guides learning and the newly learned concepts are then codified and incorporated into the knowledge base, and 3) a system design that enables efficient execution of these capabilities while minimizing “time to solution.” To ensure that the learned knowledge is correct and appropriate, the system for generating and growing the knowledge base system should include a monitoring subsystem that involves human oversight. The cognitive/management component is a key new feature that must provide comprehensive system-wide capabilities intrinsic and integral to system operation at every level to preclude the system from being blind-sided by partial knowledge or oversights.
Full information is available here.