DeepMap Named to Forbes AI 50 List of Most Promising AI Companies


DeepMap, Inc., a global leader in autonomous driving technology, today announced it has been named to the Forbes AI 50, a list of the top private companies using artificial intelligence to transform industries. DeepMap develops innovative, scalable, and affordable mapping solutions to enable Level 2+ through Level 5 autonomy.

To create the list, Forbes evaluated hundreds of submissions from the U.S. and Canada. An algorithm identified the top 100 companies with the highest quantitative scores. A panel of expert AI judges then reviewed the finalists to hand-pick the 50 most compelling companies.

“We are honored to be included on the Forbes AI 50 list for the second year in a row,” said Mark Wheeler, DeepMap Co-Founder and CTO. “Over the past year, we have executed on our vision to offer a global map-engine-as-a-service for a full range of autonomous driving, from hands off, to eyes off, to mind off. Our customers include the world’s leading automakers and suppliers, who work with us because we enable them to develop solutions that are reliable and affordable, and offer faster time-to-market.”

DeepMap recently announced DeepMap HDR™ (High-Definition Reference), a service for companies who are building hands-free Level 2+ driving systems using crowd-sourced maps. Complementing existing perception-based autonomy platforms, DeepMap HDR registers and aligns myriad crowd-sourced perception outputs to generate and update live, high-fidelity maps with absolute accuracy and better relative accuracy. DeepMap HDR solves a critical piece of the puzzle for companies seeking to validate and improve crowd-sourced mapping data. 

Forbes partnered with venture firms Sequoia Capital and Meritech Capital to create the third annual AI 50, a list of private, promising North American companies that are using artificial intelligence in ways that are fundamental to their operations. To be considered, businesses must be privately-held and utilizing machine learning (where systems learn from data to improve on tasks), natural language processing (which enables programs to “understand” written or spoken language) or computer vision (which relates to how machines “see”). 

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