By Alimat Aliyeva

A team of researchers led by Aydogan Ozcan at the University of
California, Los Angeles (UCLA), has developed a groundbreaking
technology that could transform the way generative artificial
intelligence (AI) systems operate — by using light instead of
electricity. Their findings were recently published in the
prestigious journal Nature, Azernews reports.

Modern generative models — especially diffusion-based ones like
DALL•E 2 or Stable Diffusion — require enormous amounts of energy.
Training these models on large datasets can consume tens of
thousands of kilowatt-hours. To put that into perspective, the
average household uses around 3,000 to 10,000 kilowatt-hours of
electricity per year. So training just one AI model can require as
much energy as several homes consume annually.

Even generating a single image isn’t energy-free. On traditional
GPUs, a single full diffusion process can consume tens of
watt-hours. Multiply that by 1,000 steps per image, and you’re
looking at hundreds of watt-hours — roughly equivalent to running
an electric kettle for one or two hours.

The new optical approach, however, is radically different.

Instead of relying on energy-hungry processors, the system uses
a beam of light. A digital encoder first creates a “noise circuit”
— a pattern that requires almost no power. This pattern is then
projected onto a laser beam using a spatial light modulator (SLM).
The light, carrying this noise pattern, passes through a second
SLM, which transforms it into a fully rendered image. In essence,
the laser is doing all the heavy lifting, not the computer.

“Our optical generative models can synthesize countless images
with virtually no computing power, offering a scalable and
energy-efficient alternative to digital artificial intelligence
models,” said Shiqi Chen, the study’s lead author.

The implications of this technology are vast. Thanks to its
ultra-low energy consumption and high processing speed, it could be
integrated into lightweight devices — from virtual and augmented
reality systems to smartphones, wearable gadgets, and even
AI-powered glasses.

Researchers believe that by harnessing light, AI could finally
become both environmentally sustainable and accessible on a much
broader scale. The combination of speed, energy efficiency, and
image quality may signal the beginning of a new era — one where
powerful generative AI doesn’t have to come with a massive carbon
footprint.