Photonics for sustainable AI
The rising computational demands of Artificial Intelligence (AI) are driving a rapid surge in carbon emissions from the Information and Communications Technology (ICT) sector. Traditional CMOS-based computing is reaching its scaling limits and struggling to meet these immense demands in a carbon-sustainable manner—underscoring the need for alternative hardware solutions for AI. Photonic computing has emerged as a promising alternative to CMOS through its energy-efficient computing capabilities in the optical domain. This perspective explores the potential of photonics as a carbon-sustainable solution for the next-generation AI hardware. The growing computational demands of AI are significantly increasing carbon emissions from the ICT sector, while traditional CMOS-based computing faces scaling and sustainability limits. This perspective explores photonic computing as a promising, energy-efficient alternative for enabling carbon-sustainable next-generation AI hardware.
Authors
- Satyavolu S. Papa Rao (ORCID: https://orcid.org/0000-0002-5893-2535)
- Darius Bunandar (ORCID: https://orcid.org/0000-0002-8218-5656)
- Udit Gupta (ORCID: https://orcid.org/0000-0002-9118-0961)
- Cansu Demirkiran (ORCID: https://orcid.org/0000-0002-1418-7422)
- Ajay Joshi (ORCID: https://orcid.org/0000-0002-3256-9942)
- Farbin Fayza (ORCID: https://orcid.org/0000-0002-9211-6443)
Institutions
- Cornell University (US)
- Lightmatter (United States) (US)
- Advocates for Children of New York (US)
Publication Details
- Journal
- Communications Physics
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1038/s42005-025-02300-0
- Citations
- 2
- Primary Topic
- Neural Networks and Reservoir Computing
- Type
- article
- Field-Weighted Citation Impact
- 4.96