NSF Award
1623251
Proposal 1623251<br/><br/>Title: Workshop on Scenario for Brain-Inspired Cognitive Assistants<br/><br/>PI: Jonathan Candelaria<br/><br/>Institution: Semiconductor Research Corporation<br/><br/>Date & Location: San Jose CA, May 12-13th.<br/>Workshop Goal: Explore research opportunities towards a goal of creating cognitive intelligent assistance to improve human productivity and overall quality of life. <br/><br/>Non-Technical:<br/><br/>Today we are at the cusp of a new era of computing. In the first era, machines were designed and built to greatly accelerate the performance of basic arithmetic calculations compared to human "computers" In the second era, these machines, by then called "computers" themselves, were programmed to solve highly complex problem sets, as well as enable global communication networks. We are now beginning to explore the use of machines to expand upon and augment human cognitive capabilities. We envision "machine intelligence" acting as an interface between humans and their environments, providing insight and guidance for problems that cannot be handled by the unaided mind or by computers alone. How to optimize this collaborative interaction between humans and these "intelligent" machines is an open research question. In order to create the foundation for future intelligent systems that can most effectively and efficiently assist individuals, businesses and society at large, it is essential that this research question be addressed.<br/><br/>Technical:<br/><br/>This workshop is designed to discuss and study progress toward developing "intelligent" machines. It can serve as "helpful assistants" to improve human productivity and overall quality of life. The workshop on "Brain-Inspired Cognitive Assistance"<br/>is proposed for San Jose CA, May 12-13th. The goal of this workshop is to formulate scenarios for developing novel architectures for intelligent, energy efficient, brain-inspired perception, computing, decision and management in the future 10-15 years. Various concepts show promise, including cellular automaton assembly, static and dynamic neural networking, deep machine learning, etc. as well as a wide variety of social robotics principles, genetic software, bio-inspired convergence of interaction principles, predictive cognition, natural language and complex pattern recognition algorithms and methodologies.
