Artificial intelligence is evolving at a staggering pace, but so is its demand for energy and cooling. Powering a single chatbot can require thousands of GPUs, and large data centers consume electricity at levels comparable to power plants. It’s becoming increasingly clear that electronics-based computing is reaching its limits. One emerging solution that promises to address this challenge at its core is 'photonic computing' — that is, computing with light.

In 2025, a research team from China published a groundbreaking study in the prestigious journal 'Nature Photonics'. They announced the development of a 'photonic computing chip capable of performing simultaneous calculations using 100 different light wavelengths (colors)'. It marked the first time such a high number of parallel channels operated within a single chip, signaling that the era of computing with light instead of electrons is no longer distant.

Light travels much faster than electrons and moves through media without resistance or friction. This means it generates minimal heat and suffers from almost no energy loss. Furthermore, different wavelengths of light (e.g., red, green, blue) do not interfere with each other and can be processed simultaneously. Because of these properties, light is seen as an ideal medium for massively 'parallel computation', capable of processing countless operations at once in theory.

Now, this concept is becoming reality—not just in theory but at the hardware level. The newly developed photonic chip features a completely different architecture from traditional computer chips, integrating two core technologies: the 'soliton microcomb' and the 'Mach–Zehnder interferometer mesh'.

This technology acts as a 'light splitter' that divides a single laser beam into dozens of different wavelengths. Like a single light source generating multiple colors at once, it creates 'multiple, independent computational pathways', each operating as its own channel. These wavelengths can be routed and processed simultaneously, like autonomous streams of information.

Put simply, if a traditional computer resembles a one-lane road where cars (bits of data) move one at a time, this technology creates a '100-lane superhighway' where 100 cars can drive side by side at once.

This device 'splits a beam of light into different paths and then recombines them', using the differences between those paths to compute results. In physics, this type of “interference” is used to calculate phase differences in waves. The research team arranged dozens of these interferometers in a mesh pattern, allowing each wavelength to pass through a dedicated computing structure, functioning like a neuron in an optical neural network.

In simple terms, a Mach–Zehnder interferometer can be understood as a combination of 'light switch' and 'calculator'—it changes, adds, and compares light paths to perform operations.

The new photonic chip has demonstrated the potential to be 'up to 30,000 times more energy-efficient than traditional GPUs'. In current deep learning systems, most of the electrical energy is converted into heat. In contrast, photonic computing results in virtually no energy loss and can operate stably without any cooling systems.

Moreover, because light travels faster than electrons, it can 'perform large matrix multiplications—the core of deep learning—nearly in real time'. This makes the technology especially powerful in applications that require instantaneous response, such as 'image recognition, real-time translation, and sensor signal interpretation in autonomous vehicles'.

While Korea is a global leader in memory semiconductors, it lags in system semiconductors such as GPUs and AI chips. However, when a technological paradigm shift occurs—as in the case of photonic computing—latecomers have a rare chance to leapfrog. This is reminiscent of how Korean firms like Samsung and LG became global players during the early smartphone era.

Korea already possesses world-class infrastructure and talent in fields such as 'optical communication, sensors, and precision optics'. Photonic chip technology aligns well with these existing strengths and lies at the 'intersection of AI processing, telecommunications, and sensing'.

The Korean government is simultaneously pushing for carbon neutrality and digital transformation. But AI and digital technologies inherently consume significant amounts of energy. Photonic computing offers a 'path to achieving both digital innovation and energy conservation', solving this dilemma at the technological level.

The current technology is still in the 'prototype stage'. While a single chip can now handle 100 wavelengths, scaling this to thousands, designing suitable interfaces for large-scale operations, and ensuring compatibility with existing software all remain as challenges. However, the 'direction of progress is clear'. Just a few years ago, splitting and guiding light in a lab was an achievement; now we can integrate 'precision-controlled photonic computing structures onto a single chip'.

If commercialized, we could see the rise of 'ultra-low-power AI chips,' 'light-powered mobile devices,' and even 'implantable neural computers based on photonics.' It’s not a question of if, but when.

This research is more than a scientific milestone for one country. It offers a 'strategic solution' to global problems such as 'computing efficiency bottlenecks, rising AI energy consumption, and the structural saturation of the semiconductor industry'. Coincidentally, the answer is tightly connected to industries where Korea already excels.

Now is the time for Korea to move from being a 'user of this technology to a global leader'. If government, academia, and private industry collaborate around a long-term roadmap for photonic computing, then 'computing with light' will no longer be a fantasy—but a reality made in Korea.

Nature Photonics, June 2025, “Massively parallel photonic computing with 100 wavelength channels using a soliton microcomb and Mach–Zehnder mesh,” Zhang et al.