8. The method of claim 7 , wherein the first intermediate suggestion data includes at least one data type selected from the group consisting of: a domain, an intent, and a slot for generating the first suggestion to the user.
7. A computer-implemented method comprising: receiving a first user input requesting a digital assistant to perform a requested task; identifying a first context for the user; analyzing the first user input to determine first intermediate task data corresponding to the requested first task; providing the first context and the first intermediate task data as inputs to a machine learned language prediction model, wherein the machine learned language prediction model is trained from log data, the log data comprising historical data representing previous interactions between one or more users and one or more digital assistant applications; receiving as output from the machine learned language prediction model, first intermediate suggestion data for generating a first suggestion for the user, wherein the first suggestion is for a second task to be requested based on the inputs to the machine learned language prediction model; presenting the first suggestion to the user; receiving a second user input, wherein the second user input is the same as the first user input; receiving a second context for the user, wherein the second context is different from the first context; analyzing the second user input to determine second intermediate task data corresponding to the requested task; providing the second context and the second intermediate task data as inputs to the machine learned language prediction model; receiving as output from the machine learned language prediction model, second intermediate suggestion data for generating a second suggestion for the user, wherein the second suggestion is different from the first suggestion; and presenting the second suggestion to the user.