Mathematical Foundations of AI
Investigating the mathematical structures that shape learning, generalization, optimization, and the representation of information.
Topics: Statistics · Information theory · Optimization · Learning theory
WHAT WE EXPLORE
Research
Understanding intelligence calls for more than one discipline. These are the scientific directions that guide our exploration.
RESEARCH DIRECTIONS01 / FIELD OF INQUIRY 02 / FIELD OF INQUIRY 03 / FIELD OF INQUIRY 04 / FIELD OF INQUIRY
Intelligence Inspired by Nature
Exploring what brains, cognition, biological evolution, and adaptive natural processes can teach us about artificial intelligence.
Topics: Neuroscience · Cognitive science · Evolution · Adaptation
Complex Systems & Emergence
Studying how intelligent behavior arises from interacting components, collective dynamics, and self-organizing systems.
Topics: Emergence · Dynamical systems · Collective intelligence
Scientific Methods for AI
Developing a more rigorous science of AI through falsifiable hypotheses, causal reasoning, transparent evaluations, and reproducible experiments.
Topics: Experimentation · Causality · Reproducibility · Evaluation
These areas describe our research vision and will evolve as the organization grows.