Laser neurons revolutionize AI with lightning-fast speed
Scientists from the University of Hong Kong have developed a laser neuron that operates a billion times faster than the biological nerve cells in our brains. This innovative chip will further enhance artificial intelligence's performance.
Researchers from China have created an artificial neuron based on laser technology that mimics the functions of biological neurons in the brain, but operates at much higher speeds, according to PAP. It emulates both the dynamics and information processing methods of living neurons, and its speed exceeds natural cells by an astounding billion times.
The new neuron processed data from 100 million heartbeats in one second
As explained by the team of experts, living organisms possess two types of neurons: those with gradual responses and those with impulsive responses. This innovation focuses on gradual neurons, which process signals more precisely, overcoming the limitations of current photonic impulse structures.
Team leader Chaoran Huang emphasizes that the new laser neuron features exceptional dynamics and rapid data processing, making it ideal for tasks related to pattern recognition or sequence prediction. The unique properties of this new neural system allow it to function like a miniature neural network, enabling advanced tasks even in a single unit.
In tests, the system demonstrated the ability to process vast amounts of data in a fraction of a second. So far, laser-based neurons have processed data from 100 million heartbeats and nearly 35 million digital images in just one second.
Scientists: The potential of artificial neurons can be further increased
Professor Huang, a co-author of the publication, points out that using cascading laser neurons will offer even greater potential.
"In this work, we used a single laser-based neuron with a graded response, but we believe that utilizing a cascade of many such neurons will further unlock their potential, much like in the brain where billions of neurons collaborate in large networks," explains Professor Huang, a co-author of the publication, as quoted by PAP.
