During WAIC, WeRide released WITT (World Intelligence Toward Truth), a physical-AI cognitive foundation model that breaks "understanding the real world" down into recognizable and verifiable "Atomic Physical Facts" (APFs). WITT draws on Wittgenstein's "the world is the totality of facts": instead of treating a driving video as a whole to learn from, the model first identifies minimal fact units such as "ego vehicle turns right, traffic light switches, pedestrian crosses", then performs extraction, reasoning, verification, and orchestration around those facts. The pipeline is split into four tasks — fact extraction, fact reasoning, fact verification, fact orchestration — paired with a "6+1" fact-verification dimension, giving a quantitative grip on the hallucinations, omissions, and temporal misalignments common in autonomous-driving scenarios. On the efficiency side: compared to 100B-parameter general-purpose models, WITT saves about 98% in token cost, processes 10,000 minutes of vehicle video per single card per day, lifts data-processing efficiency by up to 200x, and keeps the average per-segment fact error rate to about one-third that of general-purpose models. The closed-loop meaning lies in the "physical-AI flywheel" that WITT forms together with WeRide's in-house world model GENESIS: the former extracts and verifies facts from real data, the latter generates high-fidelity simulation and long-tail scenarios on that basis. WeRide's moat is not just its 3,000+ L4 Robotaxis, but the ability to continuously turn each fleet's daily video output into "verifiable facts" — a prerequisite for L4 and L2++ data to share a common cognitive foundation, and the hardest piece for Chinese peers to copy.