In this talk, Dr Lilian Tang will discuss the information variability in natural language and vision systems, the ambiguity caused by noisy data and their processing modules, and how context /reasoning can be modelled in order to perform application tasks in large-scale systems. This is to enable a system not just to deal with uncertainty and variability, but more to adapt to its unpredictable environment. She will review her progress so far in this form of contextual modelling and this will lead on to some open research challenges which now need to be addressed.