Abstract: Methods and processors for using a Neural Network (NN) are disclosed. The method includes, during a first iteration, determining a first sub-network of the NN and training the first sub-network. The method includes during a second iteration a second sub-network of the NN and training the second sub-network. The method includes during an inference iteration of the NN, selecting a target sub-network amongst the first sub-network and the second sub-network, and generating an inference output by employing only the target sub-network of the NN on inference data for reducing computational resources of the processor for generating the inference output.

Abstract: A computer-implemented method for creating encoded data for use in a cognitive computing system. The method comprises the steps of receiving a plurality of hypervectors, each representing a respective semantic object; element-wise modular addition of two or more of the plurality of hypervectors, thereby binding the corresponding semantic objects; and vector concatenation of two or more of the plurality of hypervectors, thereby superposing the corresponding semantic objects. The method may be carried out by a cognitive processing unit that may be part of a cognitive computing system.