Academic Area
Mathematics & Theory
The formal foundations of intelligence, learning, and complexity.
Thinking About Thinking Inc. supports interdisciplinary inquiry into mathematics, information theory, and the theoretical foundations that underlie intelligent systems.
This focus area brings together researchers and practitioners working across applied mathematics, statistics, information theory, optimization, theoretical computer science, signal processing, and related fields. We are interested in the formal structures that shape how systems learn, represent information, generalize, and fail.
Our emphasis is on clarity, abstraction, and limits, understanding not just how systems work, but what is in principle possible, what is provably impossible, and where current theories break down
Core Questions We Explore
How does embodiment change the nature of intelligence and learning?
How should perception, control, and decision-making be integrated in autonomous systems?
What role do physical constraints play in shaping behaviour and adaptation?
How do robots learn from interaction with dynamic, uncertain environments?
What makes human–robot interaction safe, intuitive, and trustworthy?
Where do current robotic systems fall short of biological intelligence, and why?
Recordings coming soon
We publish recordings of talks, panels, and seminars to make serious thinking about artificial intelligence and machine learning accessible beyond the conference hall.
Artificial intelligence and machine learning are core themes across our flagship events.
At our AE Global Summits, we convene researchers, builders, and policymakers to examine Open Problems in AI research, infrastructure, applications, and governance.
At our Conference on the Mathematics of Neuroscience and AI we explore the deeper mathematical and computational foundations of learning and intelligence, often in dialogue with neuroscience and cognitive science.
Events
Ambassadors
Year 2025
Ambassadors
