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.

翻译：华为的愿景与使命是构建一个全联接的智能世界。自2013年以来，华为诺亚方舟实验室已协助众多产品构建推荐系统及搜索引擎，旨在将正确信息传递给正确用户。每天，我们的推荐系统服务数亿手机用户，推荐各类内容与服务，如应用、新闻推送、歌曲、视频、书籍、主题及即时服务。海量数据与多样化场景为我们开发先进推荐技术提供了巨大机遇。此外，我们见证了推荐模型过去十年的技术趋势，从浅层简单模型（如协同过滤、线性模型、低秩模型）发展到深层复杂模型（如神经网络、预训练语言模型）。基于使命、机遇与技术趋势，我们在推荐系统中也遇到了若干难题。在本次报告中，我们将分享十个重要且有趣的挑战，期望推荐系统社区能从中获得启发，创造更优质的推荐系统。