New Directions for DARPA ISAT Ad Hoc Working Group on DARPA Futures Initial Draft: July 12 2000 Update: July 15 2000 x 2 Beyond Strategic Computing:

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Presentation transcript:

New Directions for DARPA ISAT Ad Hoc Working Group on DARPA Futures Initial Draft: July Update: July x 2 Beyond Strategic Computing:

Beyond Strategic Computing For 18 years, DARPA has successfully pursued the Strategic Computing vision Building on this foundation, we are prepared to confront the critical challenges facing us today. These include: –Augmented cognition –High-confidence systems and software –New computational substrates –Computing and biology

The DARPA Strategic Computing Program (1983) * networks, research machines, rapid machine prototyping,implementation systems & foundries, interoperability protocols, design tools silicon and GaAs technology VLSI systems high-speed signal processing, general purpose systems, symbolic processors, multi-processor programming and operating systems natural language, vision, speech, expert systems, navigation, planning and reasoning autonomous systems pilots associate, battle management develop a broad base of machine intelligence technology to increase our national security and economic strength Major Goals Military Applications Intelligent Functional Capabilities HW/SW System Architecture Microelectronics Infrastructure * New-Generation Technology: A Strategic Plan for its Development and Application to Critical Problems in Defense, DARPA, 1983.

Augmented Cognition Challenge: The volume of information and overall complexity of warfighting continue to grow at a rapid pace, in stark contrast to human cognitive abilities, which remain static: – Memory – Attention – Sensory bandwidth – Comprehension – Visualization abilities On the other hand, computational capabilities have continued to grow rapidly Apply computational power to support / augment cognitive skills, bolstering limited cognitive resources

Augmented Cognition Opportunity: Designs and methods that leverage new understanding about characteristic limitations in cognition: –Enhance memory –Support the analyst with data analysis, discovery, visualization –Automate new aspects of problem solving and filtering –Modulate, triage communications, information –Develop new visualization techniques to enhance understanding, increase effective human-computer bandwidth –Extend abilities to monitor, control semi-autonomous systems, robots

High-Confidence Systems and Software Challenge: Todays systems are fragile, difficult to compose and maintain –Non-robust –Non-adaptive –Untrustworthy Point failures bring down systems Difficult, costly to compose useful systems from multiple components Poor or nonexistent means for building reliable systems from necessarily unreliable components Poor understanding of vulnerabilities, performance under characterized and uncharacterized attacks No clear history, pedigree on data, code

Methods for integrating unreliable components to create reliable systems as foundation of robust computing Methods for addressing, leveraging, harnessing distributed components and resources. Redundancy via replication and efficient restart machinery Develop new approaches to model, understand, control, react to emergent behaviors in complex computational systems at baseline and when stressed Pursue understanding of robustness and adaptation exhibited by biological systems for relevance to computing High-Confidence Systems and Software Consider architectural issues spanning multiple layers of networking, software, computation, hardware Opportunity: Develop hardware, software, algorithms, and overall architectures with a more fundamental approach to security and fault tolerance

New Computational Substrates Challenge: We are nearing the end of exponential growth in processor performance using existing technologies –The current silicon / fabrication paradigm leaves us within sight of a flatlining of the Moores law curve –Atomic dimensions will limit scaling of silicon technology

New Computational Substrates Opportunity: Disruptive technologies for computing, based upon new computational substrates, are potentially on the horizon Substrates –Computational fabric –Smart matter, MEMS –Quantum –Biological approaches to computing DNA Molecular electronics Microbial robotics Engineered genetic networks –Combinations of the above

Computing and Biology Challenge: An explosion of knowledge about biological systems suggests that multiple disruptive technologies lay waiting, yet we remain mired in large amounts of data and limited computational tools and models Biological systems represent powerful architectures for sensing, processing, actuating, and fabrication, and for managing complexity in an elegant manner –IT, computational analysis is essential for cracking key challenges in biology –Increased understanding and applications of knowledge about biology will likely have significant defense implications –Increased understanding of biology will likely reveal new approaches to computing and materialswith significant defense implications

Computing and Biology Opportunity: Apply computation, modeling to pursue conceptual foundations of biological approaches to: robustness, uncertainty, adaptation, inference, replication, repair, communication, transformation, distribution, self- assembly, fabrication, ontogeny / development, identify friend vs. foe Key conceptual challenges include understanding: –Modeling of genetic circuits –Proteomics –Embryogenesis / development –Evolvable systems –Engineered biology

Beyond Strategic Computing Computing, Microsystems, and Biology New Computing Substrates from Electronics, Microsystems, & CS High confidence systems and software Augmented cognition 2020 Application Vision TBD via an ISAT study develop a broad base of machine intelligence technology to increase our national security and economic strength Major Goals HW/SW System Architecture