Tang Jie, founder of Chinese artificial intelligence company Zhipu and a lecturer at Tsinghua University, told Bloomberg that frontier AI should remain broadly accessible rather than confined to a narrow group of developers as debate intensifies over how to balance innovation with national security and safety concerns.
Open-source stance and recent release
Reflecting that view, Zhipu has released its latest GLM-5.2 model under an open-source license that allows users to download, adapt and commercialize the technology. Tang emphasized that, in his view, "meaningful AI safety comes from broad participation, transparency and public oversight" rather than limiting who can use the most advanced models.
Zhipu's GLM-5 platform is positioned for complex coding tasks and agentic AI applications. The platform has been benchmarked against Anthropic's Claude Opus series, according to the company's disclosures.
Industry divergence on access and regulation
The comments arrive against a backdrop of differing approaches by AI companies and governments toward frontier models. Some firms, including Anthropic, have restricted access to their most advanced systems citing national security considerations. At the same time, Reuters has reported that Chinese authorities are considering measures to limit overseas access to certain Chinese-developed AI models.
China's AI sector has broadly embraced open-source development, a strategy that has helped accelerate adoption of models such as Alibaba's Qwen family and narrowed the technology gap with U.S. competitors. That trend has made Chinese developers prominent contributors to the expanding open-source AI ecosystem.
Safety concerns and policy responses
As frontier models grow more capable, concerns about cybersecurity and potential misuse have increased. Recent systems have demonstrated the ability to identify complex software vulnerabilities with limited human supervision, prompting both governments and AI companies to strengthen safeguards around the most advanced models.
Company priorities and market signals
Rather than chasing immediate commercial returns, Zhipu plans to concentrate on technological progress over the next two years. Tang said the firm will channel investment into long-horizon reasoning, autonomous AI agents and self-training models instead of aggressively monetizing AI applications in the near term.
The company recently announced a $4 billion share sale in Hong Kong and disclosed plans to pursue a listing in Shanghai, signaling investor interest in China's expanding AI industry.
Where the debate stands
Tang's public endorsement of open-source access highlights a central tension in today's AI discourse: whether greater transparency and widespread participation offer a more effective path to safety, or whether tighter controls are required to prevent misuse and mitigate national security risks. Zhipu's release of GLM-5.2 and its stated research priorities make the company a visible case study in that debate.