Scientists have demonstrated single-shot tensor computing at the speed of light, marking a remarkable step toward next-generation AGI hardware powered by optical rather than electronic computation.
Tensor operations are a type of mathematical processing that underpins many modern technologies, especially artificial intelligence, but they go far beyond the basic math most people encounter. A useful comparison is the complex movements involved in rotating, slicing, or reorganizing a Rubik’s cube in several dimensions at once. Humans and traditional computers must break these steps into a sequence, while light can carry out all of them simultaneously.
In AI, tasks ranging from image recognition to language understanding depend heavily on tensor operations. As data volumes continue to grow, however, standard computing hardware such as GPUs is being pushed to its limits in speed, scalability, and energy use.
Driven by the need for faster and more efficient computing, an international research has developed a new way to carry out complex tensor calculations using a single pass of light. This technique enables single-shot tensor computing at the actual speed of light.
“Our method performs the same kinds of operations that today’s GPUs handle, like convolutions and attention layers, but does them all at the speed of light,” says Dr. Zhang. “Instead of relying on electronic circuits, we use the physical properties of light to perform many computations simultaneously.”
