MTR Lab backs AI start-up Ensonic in first mainland Chinese investment
Summary
MTR Lab, the venture capital arm of Hong Kong rail operator MTR Corp, has invested an undisclosed amount in Chinese artificial intelligence (AI) company Ensonic, in an effort to help the firm expand overseas.Beijing-based Ensonic is a seven-year-old start-up that produces AI-powered acoustic-detection systems used for equipment quality control and maintenance, the two firms said in a statement on Tuesday. Get the answers with SCMP Knowledge, our new platform of curated content with explainers, FAQs, analyses and infographics brought to you by our award-winning team.He said MTR Lab also hopes to "align with the national strategy" of developing "new quality productive forces" - a term introduced by President Xi Jinping in September last year to describe productivity gains driven by technological innovation.MTR Lab-backed Ensonics solutions use artificial intelligence algorithms to identify potential faults or problems in equipment. Photo: Handout alt=MTR Lab-backed Ensonics solutions use artificial intelligence algorithms to identify potential faults or problems in equipment. Photo: Handout>Over the next three years, Ensonic plans to expand into the rail transport markets of Singapore and Japan, as well as the power grid sectors in the United Arab Emirates and Saudi Arabia, founder and chief executive Dong Liang Ding said in a statement to the Post on Wednesday.MTR Labs latest deal reflects how Chinese AI-related enterprises continue to attract new investment, despite Washingtons efforts to prevent Beijing from making advances in the technology.Established in 2017, Ensonic previously raised six rounds of funding, according to records on Chinese corporate database Qichacha. Its core team members have come from the Institute of Acoustics at the Chinese Academy of Sciences, according to the start-up.Its solutions, which identify potential faults or problems in equipment, use AI algorithms to analyse sound data, extract features and recognise patterns in real-time, according to the Ensonic website.