Hivemapper is a decentralized global mapping data network built by 10s of thousands of people. At any given time, many 1000s of dashcams are collecting high-quality sensor data somewhere in the world and performing various computations at the edge, including state of the art computer vision tasks. 1000s of other contributors participate as AI Trainers, annotating and confirming the output of ML models. 2024 will see us 10x the number of contributors to the network. High-resolution imagery, GNSS, IMU, and other data, are then promptly uploaded for further processing and analysis (sensor fusion, 3D reconstruction, ML, human-in-the-loop annotation, etc.). Today, different data API products allow transparent and programmatic access for anyone to consume high-resolution imagery and sensor data, precisely extracted Map Features (speed signs, turn restrictions, highway signs, etc.). New data products for traffic, construction detection and more will become available later this year. Enterprise tech, mapping companies, robotaxis, rideshares, and real estate analysts represent just a few of the customers consuming data today. Our work is fast-paced, collaborative, and data-driven. We focus on solving hard problems, and we invest in our rapidly growing team and the tech to do so. Computer Vision @ Hivemapper We work on a variety of computer vision problems at the edge as well as in large compute clusters. These span object detection and stereo depth mapping to feature detection and matching, 3D reconstruction, image classification, OCR, and other general sensor fusion techniques. We solve the problem of distilling large volumes of standardized signals into highly accurate and precise insights.