Twitter is a unique source of real-time information, offering amazing opportunities for automatic content understanding. The format of this content is diverse (tweets, photos, videos, music, hyperlinks, follow graph, ...), the distribution of topics ever-changing (on a weekly, daily, or sometimes hourly basis), and the volume ever-growing; making it very challenging to automatically and continuously expose relevant content. Manually defining features to represent this data is showing its limits. In this talk, I provide an overview of how automated, content-driven representationsenabled by modern deep-learning algorithmsenables us to build adaptive systems which capture the richness of this content. Specifically, the presentation focuses on deep representations for images and images+text.