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Live+7 todayUpdated 6m ago

Motional CEO Laura Major Details AI-First Path to Level 4 Robotaxi Commercialization

Motional CEO Laura Major explains the company's AI-first strategy and Large Driving Models to commercialize Level 4 autonomous robotaxis, with plans to launch driverless operations on Uber in Las Vegas by end of 2026.

Driverless launch target

End of 2026

Ride-hailing pilot partners

3 (Uber, Uber Eats, Lyft)

Years as CTO before CEO

5

What Happened

Motional, led by President and CEO Laura Major since 2025, is focused on commercializing Level 4 autonomous vehicles. Major's career includes roles at MIT, Draper Laboratory, and Aptiv, where she helped form Motional. The company is transitioning to an AI-first architecture to enable Large Driving Models (LDMs) for more human-like driving behavior and scalable deployment.

A major accomplishment I’m particularly proud of was the transition of our autonomous-driving system to be AI-first. We saw the opportunity to completely rearchitect our system to incorporate the cutting edge in artificial intelligence.
Laura Major, President and CEO of Motional

The IONIQ 5 robotaxi, developed with Hyundai Motor Group, was designed from the start for ride-hailing and built at the Hyundai Motor Group Innovation Center Singapore. Major calls it the first major demonstration of the powerful potential of what HMG and Motional can do together.

Motional is taking a different path than others in the industry. We are combining the best of state-of-the-art AI innovations with tried-and-true safety backstops.
Laura Major, President and CEO of Motional

Motional is developing Large Driving Models to bring embodied foundation models into its autonomous-vehicle stack. Its Continuous Learning Framework ingests petabytes of daily fleet data to mine rare edge cases. The company also works on 4D data visualization using WebGL and WebGPU, predictive motion forecasting with cycle-loss architectures, and hardware integration of lidar, radar, and camera systems into the IONIQ 5 platform.

Talent Requirements
  • Deep knowledge of modern AI and strong software fundamentals
  • Systems mindset and production focus for real-world deployment
  • First-principles thinking to solve edge cases
  • Cross-functional collaboration across perception, planning, cloud, and hardware
If you want to look back at your career and point to a driverless fleet changing the fabric of urban transit and say, 'I contributed to the architecture that made that happen,' Motional is where you build it.
Laura Major, President and CEO of Motional

Previously from Kia

Hyundai Motor Group, Motional's automotive partner, has been expanding its robotics capabilities. In July 2026, the group moved to acquire SoftBank's entire stake in Boston Dynamics to strengthen AI-powered humanoid robot development.

Background drawn from MotorClaw's earlier coverage of Kia's official releases.

Why this matters

Motional's AI-first architecture and Large Driving Models aim to make Level 4 robotaxis safe, reliable, and scalable for commercial ride-hailing. This matters because it could bring affordable driverless transportation to cities like Las Vegas, affecting passengers and ride-hailing partners. For engineers, it offers the chance to work on cutting-edge AI and real-world deployment of autonomous fleets.

Terms in This Story

Level 4 autonomy
A level of driving automation where the vehicle can handle all driving tasks in specific conditions without human intervention, but only in certain environments (e.g., geofenced areas).
Robotaxi
An autonomous taxi that operates without a human driver, providing ride-hailing services.
Large Driving Model (LDM)
A type of AI model that uses large-scale data to enable autonomous vehicles to drive more human-like and generalize across different scenarios.
AI-first architecture
A system design that prioritizes artificial intelligence and machine learning as the core of the autonomy stack, rather than traditional rule-based methods.
Read Original: Kia

Summarised from the linked release; details can be imperfect — always verify against the original source.