Xia Zhijin's background sets him apart from typical finance-trained VCs: with a degree in electronic engineering from Tsinghua and research experience at Thomson's Beijing lab, he judges AI investments less by how novel a model or algorithm is and more by whether it solves a real problem for a specific industry or customer, often favoring labor-intensive, repetitive tasks like warehousing, customer service, security, and manufacturing automation where technology can meaningfully cut costs and boost efficiency.

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He also brings a distinct approach to chips and people: he leans toward edge and terminal AI chips rather than the crowded cloud chip space, looks for founders who combine strong technical skill with someone able to push that technology into real commercial use, and tends to stay calm and check whether a product can truly scale rather than getting swept up in AI hype cycles.