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Written evidence submitted by the Centre for Neuromorphic Technologies (CeNT) to the Low-Energy Computing Inquiry

Executive Summary

The Centre for Neuromorphic Technologies (CeNT) highlights the potential of neuromorphic computing and silicon photonics to substantially reduce the growing energy demands of AI. Neuromorphic computing is an engineering approach that mimics the human brain to process information with extreme energy efficiency. The UK has strong scientific capabilities in neuromorphic technologies, advanced materials and photonics, but remains limited in manufacturing, pilot-line prototyping and hardware scale-up. CeNT argues that sustained investment in research, fabrication infrastructure and skills is needed to strengthen the UK’s capability in low-power AI hardware and future semiconductor technologies.

CeNT recommends that future government interventions prioritise:

  1. Long-term support through specific neuromorphic calls from EPSRC for interdisciplinary centres linking materials, photonics, devices, architectures and algorithms for neuromorphic computing.
  2. Two shared-access pilot-line semiconductor fabrication infrastructures : a large-scale facility for manufacturing, heterogeneous integration and advanced packaging, and a small-scale agile prototyping facility for emerging neuromorphic and beyond-CMOS devices. ¾ÅÉ«ÊÓÆµ could play a key role in shaping these pilot-lines due to its world class expertise in electronic and photonic nanofabrication. These pilot lines will enable resilient UK supply chains in future computing hardware and semiconductors
  3. UKRI funding calls with a lower entrance barrier for SMEs.
  4. Centre for Doctoral Training (CDT) and technical skills programmes aligned with neuromorphic computing.

Contributors:

Dr Soumya Sarkar , Assistant Professor in the School of Electronics and Computer Science at the ¾ÅÉ«ÊÓÆµ

Professor Dimitra Georgiadou , Professor of Flexible Nanoelectronics at the ¾ÅÉ«ÊÓÆµ

Professor David Thomas , Professor of Computer Engineering at the ¾ÅÉ«ÊÓÆµ

Dr Vahid Yazdanpanah , Assistant Professor in the School of Electronics and Computer Science at the ¾ÅÉ«ÊÓÆµ

Read the full submission

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