Nature Computes Better
We can redefine the way computers process information by exploiting principles found ubiquitously in nature. By better understanding how the natural world around us performs computation, we'll build dramatically more efficient computers.
Opportunity seeds
Outside the scope of programmes, with budgets of up to £500k, these opportunity seeds support ambitious research aligned to the Nature Computes Better opportunity space.
From unravelling the basis of natural computation in single-celled organisms to demonstrating a commercially viable probabilistic processor, we're funding an array of projects across individual research teams, universities and startups to maximise the chance of breakthroughs.
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