  Huawei's vision and mission is to build a fully connected intelligent world.
Since 2013, Huawei Noah's Ark Lab has helped many products build recommender
systems and search engines for getting the right information to the right
users. Every day, our recommender systems serve hundreds of millions of mobile
phone users and recommend different kinds of content and services such as apps,
news feeds, songs, videos, books, themes, and instant services. The big data
and various scenarios provide us with great opportunities to develop advanced
recommendation technologies. Furthermore, we have witnessed the technical trend
of recommendation models in the past ten years, from the shallow and simple
models like collaborative filtering, linear models, low rank models to deep and
complex models like neural networks, pre-trained language models. Based on the
mission, opportunities and technological trends, we have also met several hard
problems in our recommender systems. In this talk, we will share ten important
and interesting challenges and hope that the RecSys community can get inspired
and create better recommender systems.
