Laplace Intelligence red-teams robots and AVs, turns a modest profit

Laplace Intelligence traces its origins to academic research. CEO Howie Sun spent eight years studying how to challenge autonomous driving AI in simulation, and in 2023 he and his then-PhD adviser Henry Liu published a paper on the subject that landed on the cover of Nature. That paper prompted calls from autonomous vehicle companies, which led Sun to turn the research into a product. The company is named for "Laplace's demon," an 1814 thought experiment by Pierre-Simon Laplace about predicting the future from complete knowledge of the present.

Its technical approach rests on a simulation environment built as a post-trained version of Nvidia's Cosmos, a world simulation platform. Laplace reconstructs real locations — from an Arizona highway to a Paris pedestrian crossing — by blending real-world map data, and developers can change the setting in real time using language prompts, such as adding afternoon traffic. Sun says the company pulls real-time traffic and congestion information from navigation providers like TomTom. Crucially, the other actors in the scene are simulated too: in a demo, when Sun directed the test vehicle to swerve into oncoming traffic, the car it would have hit moved out of the way rather than letting the vehicle pass through it.

Commercially, the startup stands out for reaching revenue and a modest profit while still early-stage. Most of that money comes from autonomous driving use cases, and most contracts are project-based today; the company is working toward recurring revenue. Its near-term goal is to raise funds and scale so it can compete with rivals, chief among them Applied Intuition, which has raised $1.2 billion to date at a $15 billion post-money valuation. Sun argues Laplace's methodology of using AI to test AI is a new paradigm for physical AI testing and will be its biggest moat.