Specialist 'carbon nanotube' AI chip built by Chinese scientists is 1st of its kind and '1,700 times more efficient' than Google's

Scientists in China have built a new type of tensor processing unit (TPU) — a special type of computer chip — using carbon nanotubes instead of a traditional silicon semiconductor. They say the new chip could open the door to more energy-efficient artificial intelligence (AI).

AI models are hugely data-intensive and require massive amounts of computational power to run. This presents a significant obstacle to training and scaling up machine learning models, particularly as the demand for AI applications grows. This is why scientists are working on making new components — from processors to computing memory — that are designed to consume orders of magnitude less energy while running the necessary computations.

Google scientists created the TPU in 2015 to address this challenge. These specialized chips act as dedicated hardware accelerators for tensor operations — complex mathematical calculations used to train and run AI models. By offloading these tasks from the central processing unit (CPU) and graphics processing unit (GPU), TPUs enable AI models to be trained faster and more efficiently.

Unlike conventional TPUs, however, this new chip is the first to use carbon nanotubes —  tiny, cylindrical structures made of carbon atoms arranged in a hexagonal pattern — in place of traditional semiconductor materials like silicon. This structure allows electrons (charged particles) to flow through them with minimal resistance, making carbon nanotubes excellent conductors of electricity. The scientists published their research on July 22 in the journal Nature Electronics.

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According to the scientists, their TPU consumes just 295 microwatts (μW) of power (where 1 W is 1,000,000 μW) and can deliver 1 trillion operations per watt — a unit of energy efficiency. By comparison, Google’s Edge TPU can perform 4 trillion operations per second (TOPS) using 2 W of power. This makes China’s carbon-based TPU nearly 1,700 times more energy-efficient.

"From ChatGPT to Sora, artificial intelligence is ushering in a new revolution, but traditional silicon-based semiconductor technology is increasingly unable to meet the processing needs of massive amounts of data," Zhiyong Zhang, co-author of the paper and professor of electronics at Beijing’s Peking University, told TechXplore. "We have found a solution in the face of this global challenge."