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.

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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
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Photonics for sustainable AI

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Photonics for sustainable AI

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article en
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Abstract

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.

Communications PhysicsVol. 8(1)
Cornell University (US), Lightmatter (United States) (US), Advocates for Children of New York (US)
Openalex Percentile: Top 5%
Neural Networks and Reservoir Computing
4.96
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