01 / representation
Physical world models
Learning compact latent states that keep the causal and geometric structure needed for prediction, planning, and control.
World Superintelligence.
build world model with superintelligence step by step
Contact
Blog
Focus
world models · physical AI · embodied planning
WSI Labs
We are building toward World Superintelligence: AI systems that understand physical causality, reason across continuous time and space, and plan reliable actions in the real world.
Large language models changed how machines work with text. They still live mostly inside symbolic space.
Roads, factories, homes, weather, bodies, machines, and robots do not arrive as clean tokens. They arrive as continuous, noisy, multimodal streams where small actions change what can happen next.
WSI Labs builds world models for that setting. Our systems learn representations of the physical world that preserve causality, geometry, dynamics, memory, and long-horizon intent while leaving behind details that do not matter for action.
Our research path joins frontier architecture work with hard deployment problems: intelligent driving without high-definition map dependence, embodied robots that adapt to unfamiliar spaces, and planning systems that connect perception, memory, and control.
World Superintelligence is not a single launch. It is a disciplined sequence of measurable steps: better representation, stronger prediction, safer planning, more capable embodiments, and open scientific exchange.
Research
We focus on world models that can be tested in demanding physical systems, not only in text benchmarks.
02 / autonomy
Map-free intelligent driving
Building driving intelligence that understands scenes, intent, uncertainty, and local physics without depending on brittle high-definition maps.
03 / embodiment
Robots that reason in motion
Connecting perception, memory, and action so robots can recover from change, choose useful experiments, and work in real environments.
04 / cognition
High-dimensional planning
Developing reasoning systems that can keep many constraints in view, simulate consequences, and select safe action sequences.
Research Blog
Research notes, technical essays, and deployment reports from the lab.
If you are building physical AI systems, robotics platforms, autonomous driving stacks, or new model architectures, we would like to talk.