Optical neural networks may provide the high-speed and large-capacity solution necessary to tackle challenging computing tasks. However, tapping their full potential will require further advances. One challenge is the reconfigurability of optical neural networks. A research team has now succeeded in laying the foundation for new reconfigurable neuromorphic building blocks by adding a new dimension to photonic machine learning: sound waves. The researchers use light to create temporary acoustic waves in an optical fiber. The sound waves generated in this way can for instance enable a recurrent functionality in a telecom optical fiber, which is essential to interpreting contextual information such as language.
Optical neural networks may provide the high-speed and large-capacity solution necessary to tackle challenging computing tasks. However, tapping their full potential will require further advances. One challenge is the reconfigurability of optical neural networks. A research team has now succeeded in laying the foundation for new reconfigurable neuromorphic building blocks by adding a new dimension to photonic machine learning: sound waves. The researchers use light to create temporary acoustic waves in an optical fiber. The sound waves generated in this way can for instance enable a recurrent functionality in a telecom optical fiber, which is essential to interpreting contextual information such as language. Optical neural networks may provide the high-speed and large-capacity solution necessary to tackle challenging computing tasks. However, tapping their full potential will require further advances. One challenge is the reconfigurability of optical neural networks. A research team has now succeeded in laying the foundation for new reconfigurable neuromorphic building blocks by adding a new dimension to photonic machine learning: sound waves. The researchers use light to create temporary acoustic waves in an optical fiber. The sound waves generated in this way can for instance enable a recurrent functionality in a telecom optical fiber, which is essential to interpreting contextual information such as language.