China AI startup Cambricon receives new funding of US$1…

China-based AI chip startup Cambricon Technologies has newly raised US$100 million in series A round funding to support its development of advanced AI chips, which is expected to help turn the company into a tech unicorn with over US$1 billion in valuation in the near future, according to company sources.

The funding was led by SDIC Chuangye Investment Management, a subsidiary of China’s State Development and Investment Corporation, with prominent investors including Alibaba, Lenovo, robot maker Zhongke Tuling Century Beijing Technology and the investment arm of the Chinese Academy of Sciences (CAS), among others.

Chen Tianshi, founder and CEO of the company, said while the company has utilized the funds raised in a pre-A round in 2016 to industrialize its Cambricon-1A chip as the first chip dedicated for high-performance neural network applications, the new proceeds will be used to support deployments of more advanced AI chip products and processors for cloud and terminals, and development of standard AI instruction set architectures.

Last year alone, Cambricon received a total of CNY100 million (US$15 million) worth of licensing orders for the IP instruction set of Cambricon-1A chips from makers of smartphones, security devices, and wearable devices. Huawei’s HiSilicon Kirin 970 chipset, to be rolled out in September, is also reportedly to carry Cambricon-1A chip instruction set.

Commercial production of AI chips through TSMC

In addition, Cambricon is negotiating with Taiwan Semiconductor Manufacturing Company (TSMC) for fabricating its AI chips using 14nm process, with official production likely to start in one year. Market observers said that whether Cambricon’s AI chips can be successfully fabricated by TSMC will determine whether the China company can smoothly transition from the licensing of IP instruction set to the commercialization of AI chips.

As a startup incubated by the Chinese Academy of Science, Cambricon also bears a mission of developing into a unicorn in China’s AI chip sector, observers said. At the moment, GPU (graphics processing unit) chips boast wide applications in deep neural network training areas, but many tech heavyweights and startups have remained active developing more applications. Among them, Intel released last year its Nervana AI processor that can accelerate various neural networks, Google also launched its TPU (tensor processing unit) chips to expedite deep neural networks, while Micrsosoft, AMD and Baidu have also joined the arena.

In response, Cambricon’s Chen said that GPU chips currently constitute the mainstream AI computing platform, but their basic architecture is not designed for AI application, leading to its limited computing efficiency for AI. He stressed the ideal AI chip should be a brand-new processor that can handle multimode capabilities of processing voice, speech, images, videos, and natural languages, among others, and should also boast much higher operating efficiency than CPU and GPU.

To achieve this, a brand-new AI instruction set is badly needed to support agile applications of diverse algorithms on AI chips, which will be a sharp contrast to the past scenario: software and hardware ecosystems all built on ARM and x86 instruction sets, according to Chen.

Boasting the world’s largest AI application market, Chen stressed, China is very likely to significantly affect the international AI ecosystem. In this regard, it is the most crucial job for China to develop, on its own, core AI instruction sets and make them become international standards for AI applications.

Categories: Bits + chips IC design, distribution

Tags: 14nm AI China semiconductor startup US

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