Challenges and Practices of Large Scale Visual Intelligence in the Real-World

Abstract

Visual intelligence is one of the key aspects of Artificial Intelligence. Considerable technology progresses along this direction have been made in the past a few years. However, how to incubate the right technologies and convert them into real business values in the real-world remains a challenge. In this talk, we will analyze current challenges of visual intelligence in the real-world and try to summarize a few key points that help us successfully develop and apply technologies to solve real-world problems. In particular, we will introduce a few successful examples, including "City Brain", "Luban (visual design)", from the problem definition/discovery, to technology development, to product design, and to realizing business values. City Brain: A city is an aggregate of a huge amount of heterogeneous data. However, extracting meaningful values from that data is nontrivial. City Brain is an end-to-end system whose goal is to glean irreplaceable values from big-city data, specifically videos, with the assistance of rapidly evolving AI technologies and fast-growing computing capacity. From cognition to optimization, to decision-making, from search to prediction and ultimately, to intervention, City Brain improves the way we manage the city, as well as the way we live in it. In this talk, we will introduce current practices of the City Brain platform, as well as what we can do to achieve the goal and make it a reality, step by step. Luban: Different from most typical visual intelligence technologies, which are more focused on analyzing, recognizing or searching visual objects, the goal of Luban (visual design) is to create visual content. In particular, we will introduce an automatic 2D banner design technique that is based on deep learning and reinforcement learning. We will detail how Luban was created and how it changed the world of 2D banner design by creating 50M banners a day.