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This paper is the second installment of From Passive Selection to Active Discovery, a research series examining structural limitations in venture capital investment selection and value recognition. Drawing on practical engagement with investment institutions, innovation-support organizations, and technology validation channels, the paper examines how conventional screening criteria, including existing customers, revenue, established teams, commercial readiness, and independent validation, may obscure underlying technological, competitive, and structural investment risks. Historical venture return distributions, venture fund vintage benchmarks, and selected institutional investment outcomes provide the empirical context. HAS-CORE, an independently developed lightweight AI safety infrastructure, serves as a practical case for examining the relationship between commercial maturity, technical validation, and potential future value. The paper argues for a structural re-examination of investment selection mechanisms while reserving detailed reform methodologies for professional advisory and research collaboration.
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Qingyun Hu-Yang (2026) studied this question.
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