self-Powered AI Synapse​ Mimics ‍Human Vision⁣ for Edge Computing

⁤ ‍ ‍ ⁣​ Updated May 12,⁢ 2025

A team at ⁢the Tokyo University​ of science, led‍ by Takashi Ikuno, has created‍ a ‍self-powered artificial⁣ synapse capable of highly precise color recognition. This innovation addresses the⁤ challenge of deploying visual recognition in edge devices by mimicking the human visual system’s efficiency.

The‍ device, detailed in ‍ Scientific Reports, uses dye-sensitized ⁣solar cells ‍to ​generate its ​own⁣ power⁤ from ‌light. This​ eliminates the need for external power‍ sources,‍ making it ideal for applications requiring energy efficiency. the artificial intelligence system can⁣ distinguish colors wiht a resolution of⁢ 10 nanometers,approaching human eye ⁣capabilities.

The system also‍ exhibits ⁤bipolar responses, generating positive ⁤voltage under blue light and negative‌ voltage under red light. This allows it to ‌perform⁢ complex logic operations, reducing ⁢the ‍number ⁣of devices needed. The research highlights the potential⁤ for next-generation optoelectronic devices in low-power AI systems ⁤with visual recognition.

In a demonstration, the team used the device within a ⁢physical reservoir ‌computing framework ⁣to recognise human⁣ movements ⁤recorded in red,⁤ green, ‍and blue.⁤ The system achieved 82% accuracy⁣ in classifying 18 combinations of⁢ colors and movements using a single device.

“The results show great potential​ for‍ the application ⁢of this next-generation optoelectronic device,⁣ which enables high-resolution color discrimination and logical operations together, to low-power artificial intelligence (AI) systems with visual recognition,” said Dr. Ikuno.

The implications of this advancement span‍ various sectors.⁤ Autonomous vehicles could benefit from⁣ more efficient⁣ recognition of traffic⁣ signals and obstacles. Wearable health devices could monitor vital signs⁤ with⁣ minimal battery usage. Consumer electronics could see‌ improved‍ battery life while maintaining⁢ refined‍ visual recognition capabilities.

“We believe this technology will ⁣contribute to the realization of low-power machine vision systems with color discrimination capabilities close to those of the human⁢ eye,‍ with applications in optical sensors‌ for self-driving cars, low-power biometric sensors ‍for medical use, and portable recognition devices,” remarks Dr. Ikuno.

What’s next

Future research will ‌focus on expanding the capabilities of this⁤ technology ⁤and⁣ exploring its integration into various real-world applications, bringing advanced computer vision to everyday devices.