03/09/2026
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
