Patent ID: 7010513

Claim:
A method of parallel processing in a neural network system with a software engine comprising: providing multiple inputs of data in parallel paths, providing converters, supplying the multiple inputs of data in the parallel paths to the converters and converting data inputs in languages other than languages of the software engine to languages of the software engine, providing a primary bus and supplying the multiple inputs of data and converted inputs of data into languages of the software engine from the converters to the primary bus, providing multiple gigabit primary chips connected to the primary bus and providing the inputs of data and the converted inputs of data to the primary chips which have multiple loci for multiple classes, manipulating data through groups or sets of entities from the inputs and the converted inputs in the primary chips, manipulating data in the primary chips by means of Brownian motion equations divided into two vectors sized for solving specific problems and predicting outcomes relating to entities, providing entities that are open ended for coping with unanticipated or random factors affecting the entities, representing element of a matrix as Bayes' equation and representing the denominator of Bayes' equation as a summation of data from a population of entities in a similar class or group, connecting primary chips together for continuously updating the denominator of Bayes' equation, providing multiple secondary chips with multiple loci for specific entities connected to the primary chips, transferring the manipulated data from the primary chips to the secondary chips connected to each of the primary chips, placing the manipulated data in secondary chips which have Brownian motion equations coded for a specific entity and vectors that are a series of matrices with elements of Bayes' equation for a specific entity, providing connections between the secondary chips and a secondary bus bar for continuously updating denominators of a Bayes' equation, providing multiple loci and coding each loci for a specific entity, providing a central processor, transferring the data in matrices or Bayes' equations from the secondary chips to the central processor, providing Brownian motion equations, internal and external vectors to the central processor for evaluation of a specific entity, processing the data in the central processor by manipulating the data in the Brownian motion equations and matrices or Bayes' equations, and producing results of the manipulating from the central computer.