Artificial Intelligence
How learning systems generalise and how they fail.
AI has moved fast, and it's fragmented. The way we evaluate large learning systems, and the institutions that govern how they're deployed, haven't kept up. We bring together researchers, engineers and practitioners in AI, machine learning and the formal sciences around it. The questions we care most about sit between fields. How do learning systems generalise? Which evaluations actually fit the systems we build now? Where are the current limits, mathematical, computational and empirical? And how do technical decisions and the institutions that deploy them shape each other?
- How do modern learning systems generalise, reason and fail, and why?
- Which methods of evaluation, interpretation and comparison work for the systems we build now?
- Where do the limits of current machine-learning paradigms lie?
- How do technical systems and human institutions reshape one another?
Conferences
AI runs through both our main events. At the AE Global Summit, researchers, builders and policymakers work on open problems in research, infrastructure, application and governance. At the Conference on the Mathematics of Neuroscience and AI, we take the same questions back to the foundations, alongside the cognitive and brain sciences.
AIs that set their own goals - learning general purpose world models for efficient planning & acting
Keynote speaker Professor Juergen Schmidhuber from King Abdullah University of Science and Technology (KAUST) and IDSIA presents his talk "A…
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Panel Discussion - "Open Problems in Computational Neuroscience"
Panel discussion on the topic of “Open Problems in Computational Neuroscience” Panel guests: Dr James Whittington (Chair) Professor Wolfgang…
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Interviews - Dr James Whittington (NM2025)
Interview with Dr James Whittington and Dr Ivana Kejic! We'd like to thank our sponsors for this conference: XTX Markets, Google DeepMind, C…
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Interviews - Professor Eve Marder (NM2025)
Interview with Professor Eve Marder and Ashley Kim! We'd like to thank our sponsors for this conference: XTX Markets, Google DeepMind, Conte…
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Fireside chat: Where next? Perspectives on AI research after grad school
Panel discussion on the topic of “Where next? Perspectives on AI research after grad school” Panel guests: Dr Ruairidh McLennan Battleday (H…
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Mood as a vehicle of reinforcement learning (Professor Eran Eldar)
Professor Eran Eldar presents "Mood as a vehicle of reinforcement learning" Abstract - The science of learning and decision-making has large…
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The Thinking About Thinking Ambassador Programme is open to applications from students and early-career researchers who want to work on intelligence across fields. Ambassadors help run our conferences, workshops and community projects, and bring their universities and countries into the network.
Ambassadors who contribute and lead over a longer period may be invited into the Thinking About Thinking Fellowship. The Fellowship is invitation-only and is for long-term contributors.