Cambricon Technologies, co-founded by brothers Chen Yunqi and Chen Tianshi from the Institute of Computing Technology of the Chinese Academy of Sciences, recently announced the successful completion of a $100 million Series A funding round. This round was led by SDIC Ventures and included prominent investors such as Alibaba Venture Capital, Lenovo Capital, Guoke Investment, Zhongke Turing, Yuanhe Origin (as the Angel Round leader), and Yongzheng Investment.
China is actively pursuing advancements in artificial intelligence chips in an effort to close the technological gap with global leaders. The name "Cambrian" itself draws inspiration from the geological era approximately 600 million years ago when a vast array of invertebrates emerged in what scientists call a "Cambrian Explosion." Similarly, the world’s first commercial artificial intelligence processor, developed by the Chen Institute and the Chen Tianshi team, marks the beginning of a potential explosion in AI technology.
This recent round of financing has valued Cambricon at $1 billion. According to the company's website, its 1A chip, launched last year, is the world’s first commercial neural network processor designed for smartphones, security surveillance, drones, wearable devices, and various terminal equipment like intelligent vehicles. When running mainstream AI algorithms, the chip offers superior performance-to-power consumption ratios compared to traditional processors.
Chen Tianshi, CEO of Cambricon, explained that while deep learning applications are abundant, they rely heavily on traditional general-purpose processors like CPUs or GPUs. For instance, Google once famously used tens of thousands of CPUs to train a cat face recognition model. As neural networks grow in complexity toward human-scale, neither CPUs nor GPUs will suffice. He emphasized the necessity of specialized AI processors, stating that the Cambrian chip outperforms traditional processors by at least two orders of magnitude in tasks like image and speech recognition, with several times greater integration capacity. This allows for embedding AI capabilities into mobile devices.
When comparing general-purpose and specialized chips, Chen Yunqi often uses metaphors like the "Swiss Army Knife" versus a "kitchen knife." While a general-purpose processor is versatile, it lacks efficiency compared to a specialized deep learning processor, which excels in specific tasks.
Chen Yunqi, co-founder of Cambricon and a researcher at the Institute of Computing Technology of the Chinese Academy of Sciences, highlighted that the Cambrian 1A chip addresses two critical issues: first, significantly boosting computational power in AI systems, surpassing traditional CPUs and GPUs by two orders of magnitude; second, enabling offline intelligence in terminal devices, ensuring user data remains secure without needing to upload to the cloud.
Currently, Cambricon's terminal processor IP products include models like 1A and 1H. With the proceeds from the A round, the company plans to accelerate the commercialization of its processors in both terminal and cloud environments. This includes enhancing the intelligence of various terminal devices and providing high-performance, low-power cloud-based intelligent processing solutions.
Commercialization efforts are focused on two fronts: terminals and clouds. On the terminal side, products like smartphones, smart glasses, and fitness bands require chips capable of recognizing images, videos, and text. In the cloud, well-known clients like iFlytek and Inspur are already using Cambricon solutions.
Industry experts have mixed opinions about China's progress in AI chips. A researcher from the University of Science and Technology of China noted that the Cambrian project leverages the high starting point of the Institute of Computing Technology of the Chinese Academy of Sciences, which has a strong track record in nurturing tech companies like Lenovo. Others believe that given China's focus on security, military, and video AI algorithms, demand for such chips is assured as long as the technology proves robust.
Shengling Hai, Vice President of Research at Gartner, remarked that China’s AI chips could potentially replace NVIDIA’s popular Jetson development boards if the technology meets expectations. However, a representative from NVIDIA pointed out that the Cambrian chip, being an application-specific integrated circuit (ASIC), differs fundamentally from NVIDIA’s GPUs, which are more flexible and adaptable to various algorithms and upgrades.
"The era of intelligence is upon us," said Chen Yunqi, emphasizing how each era has a defining technological core—like the steam engine in the Industrial Age or the general-purpose CPU in the Information Age. Consulting firm Tractica predicts that the market for deep learning chips tied to AI will grow from $500 million last year to $12.2 billion by 2025, representing a compound annual growth rate of over 40%.
Despite these strides, the average age of Cambricon’s team members is just 25, reflecting a youthful yet promising force in China’s tech landscape. While some question whether China’s AI chips truly lead globally, others see this as a natural evolution of the country’s burgeoning technological prowess.
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