Using Deep Learning at Scale in Twitter's Timelines

For more than a year now since we enhanced our timeline to show the best Tweets for you first, we have worked to improve the underlying algorithms in order to surface content that is even more relevant to you. Today we are explaining how our ranking algorithm is powered by deep neural networks, leveraging the modeling capabilities and AI platform built by Cortex, one of our in-house AI teams at Twitter. In a nutshell: this means more relevant timelines now, and in the future, as this opens the door for us to use more of the many novelties that the deep learning community has to offer, especially in the areas of NLP (Natural Language Processing), conversation understanding, and media domains. Your timeline composition before the introduction of the ranking algorithm is easy to describe: all the Tweets from the people you follow since your last visit were gathered and shown in reverse-chronological order. Although the concept is simple to grasp, reliably serving this experience to the hundreds of millions of people on Twitter is an enormous infrastructural and operational challenge.