A system for enhanced data processing in an artificial intelligence/machine learning computing environment, the system comprising: at least one neural network processor; at least one memory component (220, 225, 605); at least one primary neuron buffer comprising at least N rows, the or each neuron buffer comprising a primary neuron buffer memory component (615, 630) and a shadow neuron buffer memory component (620, 625); and at least one memory in communication with the at least one neural network processor, the at least one memory having computer-readable instructions stored thereupon that, when executed by the at least one processor, cause the at least one processor to: receive one or more processing parameters from a component of the computing environment, the processing parameters representative of characteristics of data processing and comprising the characteristics of input data and the type of processing to be performed by the computing environment; read the input data from the memory component (220, 225, 605); implement a row shifting operation on one or more of the rows N to another row based on a stride value which indicates the number of rows to shift the data; write the read input data to the primary neuron buffer such that each row N in the neuron buffer can receive the same M bytes of input data simultaneously, wherein writing the read input data to the primary neuron buffer comprises: writing the read input data to the primary neuron buffer memory component (615, 630) and, upon the primary neuron buffer memory component (615, 630) being filled, copying the data written to the primary neuron buffer memory component (615, 630) to the shadow neuron buffer memory component (620, 625); communicate the data copied to the shadow neuron buffer memory component (620, 625) to the at least one neural network processor for processing; the write of the read input data to the primary neuron buffer being further dependent on the one or more processing parameters of the artificial intelligence/machine learning computing environment. at least one neural network processor; at least one memory component (220, 225, 605); at least one primary neuron buffer comprising at least N rows, the or each neuron buffer comprising a primary neuron buffer memory component (615, 630) and a shadow neuron buffer memory component (620, 625); and at least one memory in communication with the at least one neural network processor, the at least one memory having computer-readable instructions stored thereupon that, when executed by the at least one processor, cause the at least one processor to: receive one or more processing parameters from a component of the computing environment, the processing parameters representative of characteristics of data processing and comprising the characteristics of input data and the type of processing to be performed by the computing environment; read the input data from the memory component (220, 225, 605); implement a row shifting operation on one or more of the rows N to another row based on a stride value which indicates the number of rows to shift the data; write the read input data to the primary neuron buffer such that each row N in the neuron buffer can receive the same M bytes of input data simultaneously, wherein writing the read input data to the primary neuron buffer comprises: writing the read input data to the primary neuron buffer memory component (615, 630) and, upon the primary neuron buffer memory component (615, 630) being filled, copying the data written to the primary neuron buffer memory component (615, 630) to the shadow neuron buffer memory component (620, 625); communicate the data copied to the shadow neuron buffer memory component (620, 625) to the at least one neural network processor for processing; the write of the read input data to the primary neuron buffer being further dependent on the one or more processing parameters of the artificial intelligence/machine learning computing environment. receive one or more processing parameters from a component of the computing environment, the processing parameters representative of characteristics of data processing and comprising the characteristics of input data and the type of processing to be performed by the computing environment; read the input data from the memory component (220, 225, 605); implement a row shifting operation on one or more of the rows N to another row based on a stride value which indicates the number of rows to shift the data; write the read input data to the primary neuron buffer such that each row N in the neuron buffer can receive the same M bytes of input data simultaneously, wherein writing the read input data to the primary neuron buffer comprises: writing the read input data to the primary neuron buffer memory component (615, 630) and, upon the primary neuron buffer memory component (615, 630) being filled, copying the data written to the primary neuron buffer memory component (615, 630) to the shadow neuron buffer memory component (620, 625); communicate the data copied to the shadow neuron buffer memory component (620, 625) to the at least one neural network processor for processing; the write of the read input data to the primary neuron buffer being further dependent on the one or more processing parameters of the artificial intelligence/machine learning computing environment.