When Liu talks about a new AI “paradigm” (the term he repeatedly used in interviews), he is referring to a breakthrough that reshapes how AI is built, used, and commercialized, rather than incremental improvements to existing models.
Examples of paradigm‑level shifts in recent years include:
These breakthroughs did more than improve accuracy—they changed workflows and user behavior, creating new industry centers of gravity.
From Liu’s perspective, competing by making slightly stronger chatbots is not enough. Instead, success requires creating the next category‑defining advance that reorganizes the field itself.
Liu spent years as a key figure in Tencent’s AI efforts, helping lead development of the company’s Hunyuan large language model. But in late 2024 he left Tencent after more than eight years with the company.
He subsequently founded Video Rebirth, an AI startup focused on video generation and so‑called “world models.”
The company is building AI systems designed to generate high‑fidelity video with strong physical consistency and control for professional uses such as advertising, e‑commerce, film, and animation.
Video Rebirth raised tens of millions of dollars in early funding and plans to develop models aimed at professional creators rather than consumer novelty tools.
The direction of the company suggests Liu believes multimodal and video‑based world models could represent a new frontier in AI, potentially forming the foundation for the next paradigm shift.
Despite his criticism of China’s current position in LLMs, Liu does not believe the overall AI race is settled.
His argument is that AI progress happens in waves of paradigms, and leadership can shift when the next major breakthrough arrives.
That means the key strategic question is not simply:
Instead, it is:
If China can originate a new paradigm—whether in agents, multimodal systems, world models, or another emerging direction—it could redefine the competitive landscape rather than playing catch‑up within it.
In Liu’s framing, losing the current LLM phase does not necessarily mean losing the future of AI. The decisive factor will be who creates the next breakthrough that reshapes the industry.
Liu Wei’s perspective reflects a broader debate within the global AI community. Some analysts argue the United States still holds a lead in frontier models and infrastructure, while China has moved quickly to scale deployment and develop its own model ecosystem.
His warning highlights a strategic tension common in technology races: catching up to the present can be less important than inventing the future.
For Liu, the real opportunity lies not in building a slightly better version of today’s large language models—but in discovering the next paradigm that makes them look outdated.
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