1. A computer-implemented system for determining an identity of a sensed object or a state of a sensed object associated with spatial patterns and temporal sequences in input data, the input data representing at least one of image, video, audio, text, weather conditions, tactile data or data associated with operation of a machine, comprising: a hierarchy of computing modules configured to receive first input data to learn spatial patterns and temporal sequences in the first input data associated with the object or the state of the object in a learning stage, the hierarchy in an inference stage subsequent to the learning stage farther configured receive second input data and generate the output information representing probabilities that spatial patterns and temporal sequences in the second input data correspond to spatial patterns and temporal sequences learned in the learning stage, wherein at least one of the computing modules comprises: a sequence learner module in the learning stage configured to associate temporal sequences of spatial patterns in the first input data with the output information, the associated temporal sequences having different sequence lengths, the at least one computing module generating the output information responsive to receiving the second input data based on the association in the inference stage.