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Machine-learning model generates images using light

An optical system that induces random fluctuations in a laser beam could be faster and more efficient at generating images than conventional computers are.
By
  1. Daniel Brunner

    1. Daniel Brunner is in the Optics Department, Marie and Louis Pasteur University, CNRS UMR 6174, FEMTO-ST Institute, 25000, Besançon, France.

As machine-learning models become more powerful and complex, it is increasingly challenging to implement them efficiently on conventional computers. This has created interest in building physical systems with intrinsic behaviour that can be used to implement those machine-learning models directly. Instead of performing computational operations on a digital computer, these systems function according to their own physical laws, with the goal of reducing the time and energy requirements of computation. Writing in Nature, Chen et al.1 report a model that uses a combination of digital and optical components to generate new (unseen) images. The system directly modifies a beam of light to create pictures of numbers, objects and van Gogh-style paintings.

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Nature 644, 886-887 (2025)

doi: https://doi.org/10.1038/d41586-025-02523-9

References

  1. Chen, S., Li, Y., Wang, Y., Chen, H. & Ozcan, A. Nature 644, 903–911 (2025).

    Article  Google Scholar 

  2. Skalli, A. et al. Preprint at arXiv https://doi.org/10.48550/arXiv.2503.16943 (2025).

  3. Antonik, P., Haelterman, M. & Massar, S. Phys. Rev. Appl. 7, 054014 (2017).

    Article  Google Scholar 

  4. Ahmed, S. R. et al. Nature 640, 368–374 (2025).

    Article  PubMed  Google Scholar 

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Competing Interests

The author declares no competing interests.

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