On Mobileye’s formal model of AV safety

Summary: This short post talks about Mobileye’s new paper (regarding a formal approach to Autonomous Vehicles safety). It claims that the paper has several issues, but is nevertheless an important start. Mobileye came out with a paper titled “On a Formal Model of Safe and Scalable Self-driving Cars” (Bloomberg coverage, summary paper, full pdf). Their … More On Mobileye’s formal model of AV safety

Where Machine Learning meets rule-based verification

Summary: This post addresses some high-level questions like: Longer term, how much of the verification of Intelligent Autonomous Systems can be done with just Machine Learning (ML)? Should most requirements remain rule-based, and if so – how does that connect to the ML part? And how will the uneasy interface between ML and rules influence … More Where Machine Learning meets rule-based verification

DeepXplore and new ideas for verifying ML systems

Summary: This post talks about the DeepXplore paper, and uses it to revisit the topic of verification of ML-based systems The paper DeepXplore: Automated Whitebox Testing of Deep Learning Systems (by folks from Columbia U and Lehigh U) describes a new and (in my view) pretty important way to verify ML-based systems. And it somehow … More DeepXplore and new ideas for verifying ML systems

Misc stuff: Mobileye, simulations and test tracks

Summary: This is another “What’s new in verification land” post. It describes a video and a paper from Mobileye, and takes that opportunity to revisit four topics: How Autonomous Vehicles should handle unstructured human interaction, how to balance Reinforcement Learning and safety, why simulation is the main way to validate safety in these unstructured environments, … More Misc stuff: Mobileye, simulations and test tracks