Motional Open-Sources Dataset to Help Autonomous Vehicles Master Human-Like Reasoning
Motional releases the world's first reasoning-centric, long-tail scenario open dataset designed to teach autonomous vehicles human-like reasoning and decision making. Motional also launches nuReasoning Challenge for researchers and practitioners to advance next-generation driving foundation models.
Motional Recognized on Fast Company’s List of the 100 Best Workplaces for Innovators
Motional earned a spot on Fast Company’s eighth annual Best Workplaces for Innovators list, recognizing businesses that are creating cultures where innovation can thrive at every level.
Inside the Brain of a Self-Driving Car: How Motional and MIT are Cracking Open the Black Box of AI
In a new paper, recently published in Nature, researchers from Motional and MIT have proposed a new approach for making black-box deep learning systems more interpretable: the Concept-Wrapper Network (CW-Net).
Uber and Motional Launch Robotaxi Service in Las Vegas
LAS VEGAS, NEVADA – 13 March, 2026
Our Journey to Commercialize Driverless Ride Hail in Las Vegas
Learn more about our driverless testing that has begun in Las Vegas.
Accelerating the Human-in-the-Loop Data Engine with Visual Web Apps
A deep dive into Motional's data annotation platform that combines a universal, modular data contract-driven shell with an action-driven atomic state management system.
Data Mining & Annotation User Interface: High Performance Web-Based Visualization
The second part in our series on our data annotation UI. By investing in a scalable shell, a high-performance state engine, a maintainable codebase, and workforce management we've created a platform that not only meets the demanding needs of our ML teams, but is also ready to evolve for future needs.
Building Towards End-to-End Machine Learning Autonomy: Improving Multi-Object Tracking with a Single, Unified Model
In autonomous driving, multi-object tracking is a fundamental component that identifies, locates and follows all the relevant objects in the driving scene. Read how Motional is approaching multi-object tracking with a single, unified model.
Why an Exceptional Coach is Needed for Autonomous Vehicles
At Motional, we have a rigorous, multifaceted training curriculum, including supervised, unsupervised and reinforcement learning in simulated environments, ensuring our vehicles are prepared for what they will encounter on the roads. Learn more how we train our autonomous driving system from Motional's President and CEO Laura Major.
Why is Behavior Prediction Important for Autonomous Driving?
Prediction is the ability to accurately reason a driving environment and anticipate the behavior of other road users. This technical blog covers Motional's approach to prediction, and how scaling up our behavior prediction network has been a major part of our vision to develop Large Driving Models (LDMs) that support globally scalable autonomous driving.
How Motional is Accelerating Scale, Affordability and Safety with Large Driving Models (LDMs)
Hear from Motional's President and CEO Laura Major on how we're leveraging the latest breakthroughs in embodied AI and foundation models to develop safe autonomous technology that can effectively scale across cities.