Cognitive Computing Synaptic Networks. Lisa and Lars Wood first discussed the novel QAI synaptic self-programming computer language on the balcony of a suite they were staying at the Saint Regis Hotel in New York City in 1995. The synaptic self-programming language and system implementation was implemented and applied to a variety of challenges ranging from cyber warfare in 1998 to therapeutic small molecule design, advanced materials design and VFX synthesis. Now FVG is updating this novel cognitive artificial intelligence technology as a plug-in cognitive engine.

The entire instruction set, including its novel super-tasking recurrent machine learning machine capabilities are taken from its instruction set manual below. The instructions are referred to as chronons because system time is an emergent property of the execution of the instruction set. Originally conceived based upon foundational work on artificial neural networks and quantum computing, the instruction set is immune to failure and programs itself from examples of the paradigm case, i.e. implementing a Category IV machine learning and understanding capability. The instruction set is architecturally massively threaded and executes efficiently on GPU based processing systems or Field Programmable Gate Array implementation computational substrates.

The language is synaptic since connectivity between one instruction and another is undefined. This can be thought of as an artificial neural network without connections. Instead instruction interactions are described by diffusion equations, which results in complete self-organization self-programming. The language has characteristics of the Heat Seeker Algorithm and other Foundation Mechanics self-organizing capabilities as a self-programming computer language.

Since instruction execution is defined by message diffusion equations the instructions can exist anywhere as long as its virtual machine is present. The language virtual machine is a network centric system, implemented to run on all current forms of hardware including smart phones, mobile devices and even the Apple iWatch. The instructions of the FVG cognitive computing engine can reproduce or age and self-delete as needed. This FVG intelligent technology first developed in the 1990s and applied privately for two decades on a wide variety of applications is being redesigned for its first general deployment. The intelligent swarm based deployment is an embedded cognitive computing engine. In the documentation below the term reactor should be replaced with the word synapse since in the new implementation the strings implement associative reinforcement learning artificial neurons organized around networks of digital synaptic junctures.