The present invention relates to an improved artificial neural network for predicting one or more next items in a sequence of items based on an input sequence item. The artificial neural network is implemented on an electronic device comprising a processor, and at least one input interface configured to receive one or more input sequence items, wherein the processor is configured to implement the artificial neural network and generate one or more predicted next items in a sequence of items using the artificial neural network by providing an input sequence item received at the at least one input interface and a side input as inputs to the artificial neural network, wherein the side input is configured to maintain a record of input sequence items received at the input interface.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An electronic device comprising: a processor, and at least one input interface configured to receive one or more input sequence items; wherein the processor is configured to: implement an artificial neural network; and generate one or more predicted next items in a sequence of items using the artificial neural network by providing an input sequence item received at the at least one input interface and a side input as inputs to the artificial neural network, wherein the side input is configured to maintain a record of input sequence items received at the input interface. 2. The electronic device of claim 1, wherein the processor is configured to generate the one or more predicted next items in the sequence of items by providing the input sequence item and the side input as inputs to an input layer of the artificial neural network. 3. The electronic device of claim 2, wherein the processor is configured to generate one or more subsequent predicted items in the sequence. 4. The electronic device of claim 3, wherein the processor is configured to generate the one or more subsequent predicted items in the sequence by providing a second input sequence item and the side input as inputs to an input layer of the artificial neural network. 5. The electronic device of claim 4, wherein the second input sequence item is the previously predicted next item in the sequence output by the artificial neural network. 6. The electronic device of claim 1, wherein the artificial neural network is a fixed context neural network. 7. The electronic device of claim 1, wherein the processor is configured to generate the one or more predicted next items in a sequence of items by further providing one or more additional input sequence items as input to the artificial neural network. 8. The electronic device of claim 7, wherein the input sequence item and one or more additional sequence items are consecutive previous sequence items. 9. The electronic device of claim 1, wherein the input sequence items and the side input are concatenated to form an input vector that is provided to an input layer of the artificial neural network. 10. The electronic device of claim 1, wherein the artificial neural network is a recurrent neural network. 11. The electronic device of claim 10, wherein the processor is configured to generate one or more predicted next items in the sequence of items by: processing the side input with the artificial neural network by providing the side input to an input layer of the artificial neural network to initialise the artificial neural network; and processing the input sequence item with the artificial neural network by providing the input sequence item to the input layer of the artificial neural network to generate the one or predicted next items in the sequence of items. 12. The electronic device of claim 10, wherein the processor is configured to generate one or more subsequent predicted items in the sequence. 13. The electronic device of claim 12, wherein the processor is configured to generate the one or more subsequent predicted items in the sequence by providing a second input sequence item as an input to an input layer of the artificial neural network. 14. The electronic device of claim 13, wherein the second input sequence item is the previously predicted next item in the sequence output by the artificial neural network. 15. An electronic device comprising: a processor, and at least one input interface configured to receive one or more input sequence items; wherein the processor is configured to: implement an artificial neural network; estimate an initial state of the artificial neural network based on a side input, wherein the side input is configured to maintain a record of input sequence items received at the input interface; and generate one or more predicted next items in a sequence of items using the artificial neural network by providing an input sequence item received at the at least one input interface as input to the artificial neural network. 16. The electronic device of claim 15, wherein the artificial neural network is a recurrent neural network. 17. The electronic device of claim 16, wherein the processor estimates an initial state of the artificial neural network by estimating values for a recurrent hidden vector of the recurrent neural network. 18. The electronic device of claim 17, wherein the artificial neural network further comprises a side input layer. 19. The electronic device of claim 18, wherein the processor is configured to estimate the initial state of the artificial neural network based on a side input by providing the side input to the side input layer. 20. A computer-implemented method comprising: receiving one or more input sequence items using at least one input interface; implementing, at a processor, an artificial neural network; estimating an initial state of the artificial neural network based on a side input, wherein the side input is configured to maintain a record of input sequence items received at the input interface; and generating one or more predicted next items in a sequence of items using the artificial neural network by providing an input sequence item received at the at least one input interface as input to the artificial neural network.