Artificial intelligence (AI) has become a buzzword in China since Google’s AlphaGo beat the 18-time world champion Lee Sedol and later the current world No. 1 ranking player Ke Jie in Go matches. Known as one of the most sophisticated strategy games in the world, Go, mostly referred as Weiqi in China, was once considered impossible for machines to master because there are so many possible moves and combinations. When the matches between the top human Go players and AlphaGo ended with the machine taking down three games in a row, AI was taken seriously more than ever. In 2017, the Chinese government published the New-generation Artificial Intelligence Development Plan to guide the industry’s growth in China. The country has since been on a sprint down the path of AI development. According to the South China Morning Post, China now dominates AI funding. Last year, 48 percent of total equity funding of AI start-ups globally came from China, compared to 38 percent funded by the US, and 13 percent by the rest of the world. This is a significant jump from the 11.3 percent of global funding China made in 2016.
Due to the large scale of data transfer and the ever-increasing expectation on network responsiveness, AI has created new challenges and imposed requirements on network infrastructure. As TechTarget laid out, “Deep learning algorithms are highly dependent on communications, and enterprise networks will need to keep stride with demand as AI efforts expand. That’s why scalability must be a high priority, and that will require high-bandwidth, low-latency and creative architectures.”
Network transmission is critical in all aspects of an AI application scenario, including information collection, analysis and decision-making, and the speed of the network transmission directly affects the user’s experience with the application. Operating in the complicated network environment in Mainland China, AI companies especially need powerful infrastructure to support its development.
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