Nature-Inspired Computation
Unsustainable energy requirements and limited datasets demand alternative scaling pathways for AI. Novel computing, learning and perception paradigms inspired by nature will enable radically greater efficiency and adaptability.
Opportunity seeds
Within opportunity spaces, but outside the direct scope of our programmes, ARIA funds opportunity seeds: flexible funding of up to an initial £500k for speculative and ambitious research aligned to the opportunity space.
Explore Suraj's opportunity seed projects
From unravelling the basis of natural computation in single-celled organisms to demonstrating a commercially viable probabilistic processor, in this portfolio, we're funding an array of projects across individual research teams, universities and startups to maximise the chance of breakthroughs.
See where the opportunity lies – read Suraj's perspective.
Cell Learning for Natural Computing
David Jordan, Independent researcher
Physically-Reconfigurable Computing: Learning how to learn
Neil Gershenfeld, Massachusetts Institute of Technology
(Bio)active Matter Based Computation
Juliane Simmchen + Kimia Witte, University of Strathclyde
Probabilistic Computing with Magnetic Tunnel Junctions
Shannon Egan, Brock Doiron + Ashraf Lotfi, Deep Science Ventures
Embodied Cognition in Single Celled Organisms
Kirsty Wan, University of Exeter
Analog and Digital Representation of Distributions of AI Computations
Phillip Stanley-Marbell, Signaloid
Creating Scalable Manufacturing for Optical Computing
Martin Booth, University of Oxford
Brain-inspired Polychromic Spatially Embedded Neuromorphic Networks with Unprecedented Memory
Danyal Akarca, Imperial College London
Lossy Computational Models
Viv Kendon, University of Strathclyde; Susan Stepney, University of York
Two-Point Neurons-Inspired Economic and Ethical Neuromorphic Co-Design
Ahsan Adeel, University of Stirling