The Defense Advanced Research Projects Agency (DARPA) has posted a new Broad Agency Announcement (BAA), soliciting innovative research proposals in the area of Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE). Proposals are due May 22, 2008.
-Over six decades, modern electronics has evolved through a series of major developments (e.g., transistors, integrated circuits, memories, microprocessors) leading to the programmable electronic machines that are ubiquitous today. Owing both to limitations in hardware and architecture, these machines are of limited utility in complex, real-world environments, which demand an intelligence that has not yet been captured in an algorithmic-computational paradigm. As compared to biological systems for example, today's programmable machines are less efficient by a factor of one million to one billion in complex, real-world environments. The SyNAPSE program seeks to break the programmable machine paradigm and define a new path forward for creating useful, intelligent machines.
-The vision for the anticipated DARPA SyNAPSE program is the enabling of electronic neuromorphic machine technology that is scalable to biological levels. Programmable machines are limited not only by their computational capacity, but also by an architecture requiring (human-derived) algorithms to both describe and process information from their environment. In contrast, biological neural systems (e.g., brains) autonomously process information in complex environments by automatically learning relevant and probabilistically stable features and associations. Since real world systems are always many body problems with infinite combinatorial complexity, neuromorphic electronic machines would be preferable in a host of applications but useful and practical implementations do not yet exist.
-The key to achieving the vision of the SyNAPSE program will be an unprecedented multidisciplinary approach that can coordinate aggressive technology development activities in the following areas: 1) hardware; 2) architecture; 3) simulation; and 4) environment.
- Hardware implementation will likely include CMOS devices, novel synaptic components, and combinations of hard-wired and programmable/virtual connectivity. These will support critical information processing techniques observed in biological systems, such as spike encoding and spike time dependent plasticity.
- Architectures will support critical structures and functions observed in biological systems such as connectivity, hierarchical organization, core component circuitry, competitive self-organization, and modulatory/reinforcement systems. As in biological systems, processing will necessarily be maximally distributed, nonlinear, and inherently noise- and defect-tolerant.
- Large scale digital simulations of circuits and systems will be used to prove component and whole system functionality and to inform overall system development in advance of neuromorphic hardware implementation.
- Environments will be evolving, virtual platforms for the training, evaluation and benchmarking of intelligent machines in various aspects of perception, cognition, and response.
-Realizing this ambitious goal will require the collaboration of numerous technical disciplines such as computational neuroscience, artificial neural networks, large-scale computation, neuromorphic VLSI, information science, cognitive science, materials science, unconventional nanometer-scale electronics, and CMOS design and fabrication.
More information on the BAA is available at the following URL: