  We focus on the development of AIs which live in lifelong symbiosis with a
human. The key prerequisite for this task is that the AI understands - at any
moment in time - the personal situational context that the human is in. We
outline the key challenges that this task brings forth, namely (i) handling the
human-like and ego-centric nature of the the user's context, necessary for
understanding and providing useful suggestions, (ii) performing lifelong
context recognition using machine learning in a way that is robust to change,
and (iii) maintaining alignment between the AI's and human's representations of
the world through continual bidirectional interaction. In this short paper, we
summarize our recent attempts at tackling these challenges, discuss the lessons
learned, and highlight directions of future research. The main take-away
message is that pursuing this project requires research which lies at the
intersection of knowledge representation and machine learning. Neither
technology can achieve this goal without the other.
