WeRide Unveils WIIT, a Physical AI Perception Model to Decode the Real World

At the 2026 World Artificial Intelligence Conference (WAIC), WeRide unveiled WIIT, a physical AI cognitive foundation model that charts a new course for artificial intelligence, shifting the focus from data interpretation to real-world cognition.
WIIT introduces the concept of "Minimum Physical Fact Units" derived from real-world scenarios. It dissects dynamic environments into identifiable, verifiable basic units, establishing a robust AI framework for understanding the physical world.
Leveraging these physical facts, WIIT delivers four core capabilities: fact extraction, reasoning, verification, and orchestration. Fact extraction identifies key elements within complex settings, while fact reasoning clarifies relationships between different facts. Fact verification strengthens the AI's ability to assess real-world information accuracy, and fact orchestration enables the model to organize tasks and generate decisions based on factual data.
WeRide highlights that the primary challenge in physical AI is enabling models to comprehend spatial relationships, behavioral logic, and dynamic changes in the real world. By constructing a cognitive system grounded in physical facts, WIIT aims to improve AI's environmental understanding and decision-making capabilities for embodied intelligence applications, including autonomous driving and robotics.
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At the 2026 World Artificial Intelligence Conference (WAIC), WeRide unveiled WIIT, a physical AI cognitive foundation model that charts a new course for artificial intelligence, shifting the focus from data interpretation to real-world cognition.
WIIT introduces the concept of "Minimum Physical Fact Units" derived from real-world scenarios. It dissects dynamic environments into identifiable, verifiable basic units, establishing a robust AI framework for understanding the physical world.
Leveraging these physical facts, WIIT delivers four core capabilities: fact extraction, reasoning, verification, and orchestration. Fact extraction identifies key elements within complex settings, while fact reasoning clarifies relationships between different facts. Fact verification strengthens the AI's ability to assess real-world information accuracy, and fact orchestration enables the model to organize tasks and generate decisions based on factual data.
WeRide highlights that the primary challenge in physical AI is enabling models to comprehend spatial relationships, behavioral logic, and dynamic changes in the real world. By constructing a cognitive system grounded in physical facts, WIIT aims to improve AI's environmental understanding and decision-making capabilities for embodied intelligence applications, including autonomous driving and robotics.
Ex-Ramp Engineers Raise $20M for Melius Platform After Pivoting From First Product
Melius, an AI-driven platform for creating ad campaigns, images, and videos, announced on Tuesday that it has secured $25 million in total funding. This includes a $20 million Series A round led by CRV and a $5 million seed round backed by General Ca
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