Analyzes three types of AI large model API reverse proxies (rule abuse, payment fraud, and protection breakthrough), explores criminal regulation paths such as the crime of destroying computer information systems, and advocates for upholding the principle of criminal restraint while adopting a cross-cutting criminal-civil rights protection strategy.
Argues that the subject of software copyright protection should shift from micro-level code to the software's overall architecture, critiques the Copyright Center's zero-tolerance policy against AI-assisted code, and proposes a path of classified registration and mandatory disclosure.
Points out that after authorities standardized 'Token' as 'Ciyuan' in the AI field, translation errors arise in different contexts such as security tokens, blockchain tokens, and game tokens, providing terminology guidance for legal professionals.
Critiques the Copyright Center's requirement for software copyright applicants to pledge no AI usage as disconnected from industry reality, analyzing its impact on one-person companies, malicious reporting, and the pressure it puts on developers to collectively lie.
Based on Tencent's open-source HY-MT 1.5 edge translation model, developed the Android local translation app PrivaTrans, covering installation, model loading, terminology assistance, and Word import/export features.
Sharing the complete process of fine-tuning a legal-specific embedding model: based on Google's EmbeddingGemma-300M, trained on a legal provision-to-colloquial question dataset, outperforming Google and Alibaba's models in legal provision retrieval, now open-sourced.
An in-depth technical analysis of the Beijing Internet Court's first AI image copyright case, exploring the application and controversy of the 'originality' standard in AI-generated content.
Chinese translation of the international Guidelines for Secure AI System Development white paper co-published by CISA, NCSC, 18 countries, and 23 organizations including Microsoft, Google, and OpenAI, covering secure AI development across design, development, deployment, and operation phases.
Examines whether training and using AI voice models constitutes infringement under Chinese Civil Code voice rights protections, analyzing the difference between reproducing a specific person's voice versus generating composite voices from multiple sources.
Argues that AI copyright infringement review should center on the algorithm model's working principles, using Stable Diffusion's diffusion model to show that normally generated outputs reflect learned commonality rather than copying specific training works.