>When engineer Kuang Kaiming was assigned to a team developing artificial intelligence (AI) technology for a Shanghai start-up, the company went with two leading open-source software libraries, Google’s TensorFlow and Facebook’s Pytorch. The decision to adopt US core technology over Chinese alternatives was telling of China’s weakness in basic AI infrastructure, despite the country’s success in producing AI companies that are commercially successful. Kuang’s company, whose AI product detects abnormalities in X-rays, is by no means alone. Nearly all small- to mid-sized Chinese AI companies rely on the US-originated open-source platforms, which also include MXNet and Caffe, because building an in-house framework from scratch requires a large investment of time and dedicated resources, as well as top-tier talent, to ensure the framework runs smoothly and covers a variety of use-cases.
