An electronic device (102, 104, 106; 700) comprising: at least one processor; a communications interface to communicate with a server (108; 800) over a communications network, the server (108; 800) storing a neural network (110; 820) and a process which generates item embeddings of the neural network (110; 820); and a memory communicatively coupled to the at least one processor, the memory storing thereon: a copy (116; 720) of at least part of the neural network (110; 820) and a plurality of item embeddings of the neural network (110; 820); and computer-readable instructions that, when executed by the at least one processor, cause the electronic device (102, 104, 106; 700) to perform operations comprising: receiving, from at least one input interface, data indicative of at least one item of a sequence of items, wherein the items can be words, phrases, morphemes, characters or other units of language, or images which are used as part of text; initiating transfer of an item embedding corresponding to the received at least one item from the server storing the neural network (110; 820) when the corresponding item embedding is not available at the electronic device (102, 104, 106; 700); accessing item embeddings for a plurality of candidate next items and item embeddings for one or more other preceding items when available; and predicting at least one candidate next item in the sequence of items by processing the corresponding item embedding, and the item embeddings for one or more other preceding items if available, with the copy (116; 720) of at least part of the neural network (110; 820) and using the item embeddings for the plurality of candidate next items. at least one processor; a communications interface to communicate with a server (108; 800) over a communications network, the server (108; 800) storing a neural network (110; 820) and a process which generates item embeddings of the neural network (110; 820); and a memory communicatively coupled to the at least one processor, the memory storing thereon: a copy (116; 720) of at least part of the neural network (110; 820) and a plurality of item embeddings of the neural network (110; 820); and computer-readable instructions that, when executed by the at least one processor, cause the electronic device (102, 104, 106; 700) to perform operations comprising: receiving, from at least one input interface, data indicative of at least one item of a sequence of items, wherein the items can be words, phrases, morphemes, characters or other units of language, or images which are used as part of text; initiating transfer of an item embedding corresponding to the received at least one item from the server storing the neural network (110; 820) when the corresponding item embedding is not available at the electronic device (102, 104, 106; 700); accessing item embeddings for a plurality of candidate next items and item embeddings for one or more other preceding items when available; and predicting at least one candidate next item in the sequence of items by processing the corresponding item embedding, and the item embeddings for one or more other preceding items if available, with the copy (116; 720) of at least part of the neural network (110; 820) and using the item embeddings for the plurality of candidate next items. a copy (116; 720) of at least part of the neural network (110; 820) and a plurality of item embeddings of the neural network (110; 820); and computer-readable instructions that, when executed by the at least one processor, cause the electronic device (102, 104, 106; 700) to perform operations comprising: receiving, from at least one input interface, data indicative of at least one item of a sequence of items, wherein the items can be words, phrases, morphemes, characters or other units of language, or images which are used as part of text; initiating transfer of an item embedding corresponding to the received at least one item from the server storing the neural network (110; 820) when the corresponding item embedding is not available at the electronic device (102, 104, 106; 700); accessing item embeddings for a plurality of candidate next items and item embeddings for one or more other preceding items when available; and predicting at least one candidate next item in the sequence of items by processing the corresponding item embedding, and the item embeddings for one or more other preceding items if available, with the copy (116; 720) of at least part of the neural network (110; 820) and using the item embeddings for the plurality of candidate next items. receiving, from at least one input interface, data indicative of at least one item of a sequence of items, wherein the items can be words, phrases, morphemes, characters or other units of language, or images which are used as part of text; initiating transfer of an item embedding corresponding to the received at least one item from the server storing the neural network (110; 820) when the corresponding item embedding is not available at the electronic device (102, 104, 106; 700); accessing item embeddings for a plurality of candidate next items and item embeddings for one or more other preceding items when available; and predicting at least one candidate next item in the sequence of items by processing the corresponding item embedding, and the item embeddings for one or more other preceding items if available, with the copy (116; 720) of at least part of the neural network (110; 820) and using the item embeddings for the plurality of candidate next items.