I will present my recent research on expanding the AI skills of digital assistants through explicit human-in-the-loop dialogue and demonstrations. Digital assistants learn from other digital assistants with each assistant initially trained through human interaction in the style of a“Master and Apprentice”. For example, when a digital assistant does not know how to complete a requested task, rather than responding “I do not know how to do this yet”, the digital assistant responds with an invitation to the human“can you teach me?”. Apprentice-style learning is powered by a combination of all the modalities: natural language conversations, non-verbal modalities including gestures, touch, robot manipulation and motion, gaze, images/videos, and speech prosody. The new apprentice learning model is always helpful and always learning in an open world – as opposed to the current commercial digital assistants that are sometimes helpful, trained exclusively offline, and function over a closed world of “walled garden” knowledge. Master-Apprentice learning has the potential to yield exponential growth in the collective intelligence of digital assistants.