China’s most prominent AI leaders are publicly lowering expectations about overtaking the United States in the global artificial intelligence race.
At a recent AGI-Next summit in Beijing, senior executives and researchers from China’s leading AI organizations say the probability of a Chinese company leapfrogging US leaders such as OpenAI and Anthropic within the next several years is slim, reports Bloomberg.
The clearest assessment came from Justin Lin, who leads the Qwen open-source model program at Alibaba Group Holding Ltd.
Before offering his estimate, Lin says the challenge is one of resources rather than talent, pointing to the scale of investment behind US frontier research.
“A massive amount of OpenAI’s compute is dedicated to next-generation research, whereas we are stretched thin — just meeting delivery demands consumes most of our resources.”
Lin says he puts the odds of any Chinese company achieving a fundamental breakthrough ahead of US rivals at below 20% over the next three to five years, raising what he described as a recurring question in technology development.
“It’s an age-old question: does innovation happen in the hands of the rich or the poor?”
Lin’s caution was echoed by peers across China’s AI ecosystem. Tang Jie, founder and chief AI scientist of Zhipu AI, warns against mistaking open-source releases for true parity.
“We just released some open-source models, and some might feel excited, thinking Chinese models have surpassed the US. But the real answer is that the gap may actually be widening.”
Yao Shunyu, a former OpenAI research scientist who jumped ship to Tencent Holdings to lead its AI strategy, expresses a similar view. He urges Chinese developers to focus less on internal rivalry and more on unresolved technical bottlenecks.
“Meaningless internal competition serves no purpose. We should represent China to push AGI further for the world.”
Across the panel, executives cite constrained access to advanced chips, US export controls on lithography equipment and limited compute budgets as structural headwinds. While acknowledging progress, they argue that frontier AI development increasingly depends on sustained capital, compute and long-term research focus.
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