Light-powered computer chip can train AI much faster than components powered by electricity

Scientists have designed a new microchip that's powered by light rather than electricity. The tech has the potential to train future artificial intelligence (AI) models much faster and more efficiently than today's best components, researchers claim.

By using photons to perform complex calculations, rather than electrons, the chip could overcome the limitations of classic silicon chip architecture and vastly accelerate the processing speed of computers, while also reducing their energy consumption, scientists said in a new study, published Feb. 16 in the journal Nature Photonics. 

Silicon chips have transistors — or tiny electrical switches — that turn on or off when voltage is applied. Generally speaking, the more transistors a chip has, the more computing power it has — and the more power it requires to operate. 

Throughout computing History, chips have adhered to Moore's Law, which states the number of transistors will double every two years without a rise in production costs or energy consumption. But there are physical limitations to silicon chips, including the maximum speed transistors can operate at, the heat they generate from resistance, and the smallest size chip scientists can make. 

It means stacking billions of transistors onto increasingly small silicon-electronic chips might not be feasible as the demand for power increases in the future — particularly for power-hungry AI systems.

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Using photons, however, has many advantages over electrons. Firstly, they move faster than electrons — which cannot reach the speed of light. While electrons can move at close to these speeds, such systems would need an extraordinary — and unfeasible — amount of energy. Using light would therefore be far less energy-intensive. Photons are also massless and do not emit heat in the same way that electrons carrying an electrical charge do.