Areas of Interest
Domains
Where perception, modeling, and constraint-awareness are essential.
PALI's foundational research has implications across multiple domains where perception, modeling, and constraint-awareness are essential. We are not building products for these domains; we are investigating the principles that would make such products possible.
The domains listed here share a common characteristic: they are areas where current AI approaches face fundamental limitations, not merely engineering challenges. Pattern recognition and statistical prediction, however sophisticated, are insufficient when the task requires genuine understanding of structure and causality.
Physical Systems
Robotics, autonomous systems, and any domain where AI must interact with the physical world and respect its laws. Intelligence that operates in physical space must perceive physical structure and reason within physical constraints.
Complex Infrastructure
Energy systems, transportation networks, and industrial processes where understanding system dynamics matters more than pattern matching. These domains require models that capture causal relationships and respect conservation laws.
Scientific Discovery
Domains where AI can assist in model construction, hypothesis generation, and the interpretation of experimental observations. Science advances through the construction of better models, not through the accumulation of predictions.
Safety-Critical Applications
Contexts where the cost of hallucination or constraint violation is unacceptable, and where robust reasoning is non-negotiable. Medical diagnosis, structural engineering, and aerospace are examples where plausibility is not enough.
A Note on Scope
This is not a comprehensive list of applications, nor is it a roadmap. These are areas where we believe perception-first intelligence could make a meaningful difference—areas where we are interested in dialogue with researchers and practitioners who share our conviction that current approaches have fundamental limitations.