Mobileye

Approximately 95% of public roads in the U.S. and Europe are covered by Mobileye REM™, with more than 34 billion miles mapped.

Aggregated real-world driving data helps support continuously updated maps designed to support localization, map freshness, change detection, and driving systems as road conditions evolve.

Learn more about Mobileye REM™: https://okt.to/dOYQmt

Physical AI is designed for the real world, where conditions are constantly changing and the complexity of physical environments cannot be fully scripted or predicted.

Mobileye’s approach to physical AI is built on safety by architecture, edge-case led learning, a purpose-built stack, and scale-first engineering.

Together, these principles are designed to enable autonomous vehicles and humanoids to perform in complex physical environments.

Learn more: https://okt.to/rDH9lo

We'll be in Barcelona for AutoSens Europe 2026.

Across three sessions, Mobileye experts will be sharing insights on tackling the long tail in autonomous driving, enhancing in-cabin sensing with exterior intelligence, and innovation in automotive imaging.

If you're attending, join us for:
📅 Wednesday, 23 September | 3:20 p.m. CEST
Avi Hendler
From Edge Cases to Scalable Intelligence: Driving Long-Tail Learning with VLMs

📅 Thursday, 24 September | 9:50 a.m. CEST
Elad Osherov
Panel Discussion - Beyond Compliance: The Next Generation of Driver & Occupant Monitoring

📅 Thursday, 24 September | 11:25 a.m. CEST
Gabriel Bowers
Motion-Aware Characterization of Automotive HDR Cameras: Quantifying the Trade-Off Between Flicker Mitigation and Dynamic Resolution

Check out more info here: https://okt.to/1P7uc8

Germany continues to set itself as one of the leading global markets in autonomous mobility, and Mobileye Drive™ is helping lead the way.

Official KBA data shows that more than 60% of Germany’s valid SAE Level 4 testing permits include Mobileye Drive™, our fully autonomous solution for Mobility as a Service.

As autonomous transportation moves closer to commercial deployment, we’re proud to push for a future of safer, scalable driverless mobility.

Read more here: https://okt.to/LHaqSl

The hardest part of scaling autonomous driving is not just collecting more data. It is learning from the rare, safety-critical scenarios that are easy to miss inside massive datasets.

At CVPR, Mobileye CTO Prof. Shai Shalev-Shwartz introduced Meteor, Mobileye’s approach to long-tail learning: using AI agents and vision-language models to discover difficult scenarios, identify reproducible failure patterns, and generate targeted variations for training and validation.

Watch the presentation to see how Mobileye is tackling one of autonomy’s biggest challenges: turning edge cases into scalable intelligence: https://okt.to/CxuQFH

Mobileye’s next chapter in Physical AI is about turning advanced intelligence into robust, useful and economically viable systems in the real world. Humanoid robotics brings that challenge into a new domain.

In an exclusive interview with IZON media, Lior Wolf, EVP of Humanoids at Mobileye, explains why Mentee by Mobileye bet on simulation from day one, why it develops hardware and software together to help learned skills transfer reliably into the real world, and what it will take to build a truly general-purpose robot.

He also discusses how Mentee’s startup speed and vertically integrated approach can combine with Mobileye’s experience in productization, supply chain and commercial scale.

Read the full interview here:
https://okt.to/nmdqWp