Laplace Intelligence red-teams robots and self-driving cars before they hit the real world
Laplace Intelligence is developing automated red-teaming software to stress-test robotics and autonomous vehicle AI before deployment. The startup aims to prevent unpredictable failures in physical environments.
Why it matters
As AI moves into the physical world, robust safety testing is critical to prevent accidents involving autonomous systems.
If there’s one lesson the OpenAI-Hugging Face incident taught us, it’s that AI agents can be unpredictable.
“Imagine if something like that happened in the physical world,” Howie Sun, CEO and co-founder of Laplace Intelligence , told TechCrunch. “AI agents are moving from computers into the real world, and we don’t really want physical AI to fail in the real world.”
Ann Arbor-based Laplace is building automated red-teaming — essentially, stress-testing a system by deliberately trying to make it fail — for robotics and physical AI. The company is betting that the only way to make sure physical AI is safe is to have AI test it.
“Our goal is to help companies discover and fix problems before deployment — and, over time, build a shared foundation of evidence that customers, insurers, and regulators can trust,” Sun said.
Get smarter about the news
Sign up free for a feed built around what you actually care about, Dive Deeper research on any story, and the full text of every article.
Create free accountAlready have an account? Sign in