Traditional stored-program von Neumann computers are constrained by physical limits, and require humans to program how computers interact with their environments. In contrast the human brain processes information autonomously, and learns from its environment. Neuromorphic electronic machines— computers that function more like a brain— may enable autonomous computational solutions for real-world problems with many complex variables. In 2008 DARPA awarded the first funding to HRL Laboratories, Hewlett-Packard and IBM Research for SyNAPSE (Systems of Neuromorphic Adaptive Plastic Scalable Electronics)—an attempt to build a new kind of cognitive computer with form, function and architecture similar to the mammalian brain. The program sought to create electronic systems inspired by the human brain that could understand, adapt and respond to information in ways fundamentally different from traditional computers.
"The initial phase of the SyNAPSE program developed nanometer scale electronic synaptic components capable of adapting the connection strength between two neurons in a manner analogous to that seen in biological systems (Hebbian learning), and simulated the utility of these synaptic components in core microcircuits that support the overall system architecture" (Wikipedia article on SyNAPSE, accessed 10-20-2013).