Machines can learn unsupervised 'at speed of light' after AI breakthrough, scientists say
Performance of photon-based neural network processor is 100-times higher than electrical processor
Your support helps us to tell the story
From reproductive rights to climate change to Big Tech, The Independent is on the ground when the story is developing. Whether it's investigating the financials of Elon Musk's pro-Trump PAC or producing our latest documentary, 'The A Word', which shines a light on the American women fighting for reproductive rights, we know how important it is to parse out the facts from the messaging.
At such a critical moment in US history, we need reporters on the ground. Your donation allows us to keep sending journalists to speak to both sides of the story.
The Independent is trusted by Americans across the entire political spectrum. And unlike many other quality news outlets, we choose not to lock Americans out of our reporting and analysis with paywalls. We believe quality journalism should be available to everyone, paid for by those who can afford it.
Your support makes all the difference.Researchers have achieved a breakthrough in the development of artificial intelligence by using light instead of electricity to perform computations.
The new approach significantly improves both the speed and efficiency of machine learning neural networks – a form of AI that aims to replicate the functions performed by a human brain in order to teach itself a task without supervision.
Current processors used for machine learning are limited in performing complex operations by the power required to process the data. The more intelligent the task, the more complex the data, and therefore the greater the power demands.
Such networks are also limited by the slow transmission of electronic data between the processor and the memory.
Researchers from George Washington University in the US discovered that using photons within neural network (tensor) processing units (TPUs) could overcome these limitations and create more powerful and power-efficient AI.
A paper describing the research, published today in the scientific journal Applied Physics Reviews, reveals that their photon-based TPU was able to perform between 2-3 orders of magnitude higher than an electric TPU.
“We found that integrated photonic platforms that integrate efficient optical memory can obtain the same operations as a tensor processing unit, but they consume a fraction of the power and have higher throughput,” said Mario Miscuglio, one of the paper’s authors.
“When opportunely trained, [the platforms] can be used for performing interference at the speed of light.”
Potential commercial applications for the innovative processor include 5G and 6G networks, as well as data centres tasked with performing vast amounts of data processing.
Dr Miscuglio said: "Photonic specialised processors can save a tremendous amount of energy, improve response time and reduce data centre traffic."
Join our commenting forum
Join thought-provoking conversations, follow other Independent readers and see their replies
Comments