Huawei's artificial intelligence lab denied that one of its Pangu models copied Alibaba's Qwen model and stated that development and training were independent. According to the entity, there are experimentation records, data traceability, and internal audits showing differences in architecture, preprocessing, and training sources, which supports the claim of autonomous development.
Officials noted that similarity in behaviors and capabilities among large models is common when using common techniques, public datasets, and open-source components, and that such convergence does not equate to direct copying of code or weights. They added that validation, reproducibility, and quality control processes are key to resolving disputes and protecting intellectual property and research ethics.
Independent experts and external audits are often necessary to settle such controversies and to ensure transparency in model training and deployment. In parallel, the industry reaffirms the importance of responsible artificial intelligence practices, data governance policies, and continuous evaluation against biases and operational risks.
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