Over the past few years, we have seen considerable advances in AI, which are becoming a regular part of our daily lives, from virtual assistants and chatbots to healthcare and diagnostic tools. Meanwhile, tech companies have continued to work behind the scenes to improve artificial intelligence (AI) technology. Chinese scientists have now developed a new computing architecture that could lead to more efficient and advanced AI models and potentially even artificial general intelligence (AGI) in the future. As a producer of and firm believer in the potential of carbon nanotubes (CNTs), it comes as no surprise to us that CNTs are at the beating heart of this major technological transformation!

A CNT Based AI Chip

AI models are incredibly data-intensive, and running them requires enormous amounts of computational power. This makes them highly energy-intensive and hinders the development of more advanced models such as AGI.  

To overcome these limitations, researchers at Peking University and collaborators from other institutions developed a new type of chip that uses nanotubes instead of traditional semiconductor materials like silicon. The chip is composed of 3,000 nanotube that are arranged into a processing unit. CNTs' ultra-thin cylindrical structures allow electrons to flow through them, both on the outside and thorugh the inside with minimal resistance, making them excellent conductors – just one of their many useful properties. 

What Does This Mean For the Future of AI Technology?

In the study published in Nature Electronics, the researchers built a five-layer neural network on the CNT-based tensor processing unit (TPU). They tested its ability on a Modified National Institute of Standards and Technology (MNIST) image recognition task, reporting an accuracy rate of 88% alongside a power consumption of just 295 μW (with the capacity to deliver 1 trillion operations per watt). To put it into context, Google’s silicon TPU can perform up to 4 trillion operations per second but requires 2 W of power, making the new CNT-based chip almost 1,700 times more efficient! Moreover, the authors reported a 99.9999% semiconductor purity and ultraclean surfaces, supporting the production of transistors with high on-current densities and uniformity.

This showed how CNT-based chips outperform silicon-based chips in terms of power consumption and processing speed. This makes chips smaller, lighter, and more powerful, hopefully enabling the production of more energy-efficient systems. However, the work doesn’t stop there, as the scientists plan to refine the chip further to make it more scalable and improve its performance. 

This represents an enormous breakthrough for energy-intensive computing tasks such as AI processing, where nanotube-based AI architecture has the potential to help us reach human-level AGI in the near future. At TrimTabs, we can’t wait to see what the future holds for AI and how CNTs will help make this a reality! 

To learn more, check out the full study in Nature Electronics, and make sure to explore our Nanotube News for more exciting stories about the potential of CNTs!