Artificial intelligence
Models and reasoning methods that can assist perception, design exploration, and decision support. Outputs require evaluation within their intended use.
Our vision sits across software, intelligence, and physical systems. These foundations describe the fields we intend to explore—not a claim of completed products.
Models and reasoning methods that can assist perception, design exploration, and decision support. Outputs require evaluation within their intended use.
Systems that sense, plan, and act toward an objective under operating constraints, with supervision appropriate to the task.
Intelligence studied through an agent’s interaction with an environment, where perception and action inform one another.
Integration of mechanisms, sensing, computation, and control to perform physical tasks reliably.
Methods for extracting visual information from images or video, including object detection and scene interpretation.
Simultaneous localization and mapping estimates an agent’s pose while constructing a map from sensor observations. Map quality depends on sensors, motion, and environment.
Dedicated computing close to hardware, including firmware, sensing interfaces, timing, and communication.
Circuit models allow analysis before hardware fabrication. Simulation results remain dependent on model quality and must be validated against real conditions.
Control sequences, instrumentation, and interfaces designed around defined processes, interlocks, and qualified engineering review.
AI systems that plan steps and use tools to work toward objectives. Permission boundaries, traceability, and human approvals remain central.
A conceptual feedback loop: observations inform decisions; actions change the environment; evaluation informs the next iteration. Human oversight depends on the application.
We welcome conversations with researchers, engineers, industry partners, and people who believe in thoughtful technology.