Artificial intelligence (AI) is widely used and designed to augment human skills such as data analysis, text generation and image recognition. Its performance has surpassed that of humans in many areas, for example in terms of speed. Tasks which would take many hours of work when performed manually can be completed in seconds.
Researchers in the Stiller Lab work on optoacoustics and specifically on the challenge of optical neural networks mediated by acoustic waves. For the upscaling of the optical neural networks, they have now developed an activation function which can be controlled all-optically. The information does not need to be converted back from the optical to the electronic domain. This development is an important step for photonic computing, a physical analog computing alternative which promises to be able to realize energy efficient artificial intelligence in the long term.
A nonlinear activation function is essential for deep learning models to learn to solve complex tasks. In optical neural networks, these parts are ideally implemented in the photonic domain as well. The researchers from the Stiller Research Group at MPL and LUH, in collaboration with Dirk Englund from MIT, have now demonstrated that sound waves can be the mediator for an effective photonic activation function. The optical information does not have to leave the optical domain and is directly processed in optical fibers or photonic waveguides. Via the effect of stimulated Brillouin scattering, the optical input information undergoes a nonlinear change depending on the level of optical intensity.
Including a photonic activation function in an optical neural network preserves the bandwidth of the optical data, avoids electro-optic conversion and maintains the coherence of the signal. The versatile control of the nonlinear activation function with the help of sound waves allows the implementation of the scheme in existing optical fiber systems as well as photonic chips.
For more information, see their publication in Nanophotonics:
G. Slinkov, S. Becker, D. Englund, and B. Stiller, “All-optical nonlinear activation function based on stimulated Brillouin scattering”, Nanophotonics, 2025.
Image on the top: What an image generating AI thinks an optoacoustic nonlinear activation function could look like. © Canva
Artificial intelligence (AI) is widely used and designed to augment human skills such as data analysis, text generation and image recognition. Its performance has surpassed that of humans in many areas, for example in terms of speed. Tasks which would take many hours of work when performed manually can be completed in seconds.
Researchers in the Stiller Lab work on optoacoustics and specifically on the challenge of optical neural networks mediated by acoustic waves. For the upscaling of the optical neural networks, they have now developed an activation function which can be controlled all-optically. The information does not need to be converted back from the optical to the electronic domain. This development is an important step for photonic computing, a physical analog computing alternative which promises to be able to realize energy efficient artificial intelligence in the long term.
A nonlinear activation function is essential for deep learning models to learn to solve complex tasks. In optical neural networks, these parts are ideally implemented in the photonic domain as well. The researchers from the Stiller Research Group at MPL and LUH, in collaboration with Dirk Englund from MIT, have now demonstrated that sound waves can be the mediator for an effective photonic activation function. The optical information does not have to leave the optical domain and is directly processed in optical fibers or photonic waveguides. Via the effect of stimulated Brillouin scattering, the optical input information undergoes a nonlinear change depending on the level of optical intensity.
Including a photonic activation function in an optical neural network preserves the bandwidth of the optical data, avoids electro-optic conversion and maintains the coherence of the signal. The versatile control of the nonlinear activation function with the help of sound waves allows the implementation of the scheme in existing optical fiber systems as well as photonic chips.
For more information, see their publication in Nanophotonics:
G. Slinkov, S. Becker, D. Englund, and B. Stiller, “All-optical nonlinear activation function based on stimulated Brillouin scattering”, Nanophotonics, 2025.
Image on the top: What an image generating AI thinks an optoacoustic nonlinear activation function could look like. © Canva