币界网报道：The AI native platform DINQ was officially launched, aiming to establish a new standard for the evaluation of scientific and technological talents by integrating multi-dimensional data such as academic papers and open source code contributions. The platform not only analyzes the quality of researchers' paper publications, conference rankings, and authorship weights, but also incorporates GitHub code contributions into the evaluation system to quantify engineering influence. Its core functions include drawing personal "technical fingerprints", evaluating career development trajectories, and providing salary estimates based on data models, helping recruiters identify undervalued talents, assisting investors in technical due diligence, and providing career development references for practitioners. The DINQ team said that the platform is committed to solving the problem of information asymmetry in the current talent evaluation system and promoting the establishment of fairer value measurement standards.