  Chit-chat models are known to have several problems: they lack specificity,
do not display a consistent personality and are often not very captivating. In
this work we present the task of making chit-chat more engaging by conditioning
on profile information. We collect data and train models to (i) condition on
their given profile information; and (ii) information about the person they are
talking to, resulting in improved dialogues, as measured by next utterance
prediction. Since (ii) is initially unknown our model is trained to engage its
partner with personal topics, and we show the resulting dialogue can be used to
predict profile information about the interlocutors.
