A computer-implemented method for reducing touch latency when responding to touch inputs from a user input touch object, the touch inputs being received at a touch sensitive computing device, wherein the method comprises predicting motion of the user input touch object, said predicting comprising: obtaining, by one or more computing devices including the touch sensitive computing device, a first set of motion data associated with the user input touch object, the first set of motion data descriptive of a location of the user input touch object over time; inputting, by the one or more computing devices, the first set of motion data into a recurrent neural network of a machine-learned motion prediction model (200, 400); receiving, by the one or more computing devices as an output of the recurrent neural network, a high-dimensional context vector; inputting, by the one or more computing devices, the high-dimensional context vector and a time vector descriptive of one or more future times at which the future location of the user input touch object is to be predicted into one of: (i) a feed forward neural network, or (ii) a recurrent decoder neural network of the motion prediction model (200, 400); and receiving, by the one or more computing devices as an output of the motion prediction model (200, 400), a motion prediction vector that describes one or more predicted future locations of the user input touch object respectively for the one or more future times, comprising receiving, by the one or more computing devices, the motion prediction vector as an output of the feed forward neural network or the recurrent decoder neural network of the motion prediction model (200, 400); and performing, by the touch sensitive computing device, one or more actions requested by an input action that includes the one or more predicted future locations described by the motion prediction vector. obtaining, by one or more computing devices including the touch sensitive computing device, a first set of motion data associated with the user input touch object, the first set of motion data descriptive of a location of the user input touch object over time; inputting, by the one or more computing devices, the first set of motion data into a recurrent neural network of a machine-learned motion prediction model (200, 400); receiving, by the one or more computing devices as an output of the recurrent neural network, a high-dimensional context vector; inputting, by the one or more computing devices, the high-dimensional context vector and a time vector descriptive of one or more future times at which the future location of the user input touch object is to be predicted into one of: (i) a feed forward neural network, or (ii) a recurrent decoder neural network of the motion prediction model (200, 400); and receiving, by the one or more computing devices as an output of the motion prediction model (200, 400), a motion prediction vector that describes one or more predicted future locations of the user input touch object respectively for the one or more future times, comprising receiving, by the one or more computing devices, the motion prediction vector as an output of the feed forward neural network or the recurrent decoder neural network of the motion prediction model (200, 400); and performing, by the touch sensitive computing device, one or more actions requested by an input action that includes the one or more predicted future locations described by the motion prediction vector.