China's Large-Scale Ecological Exploration: Industry Fears ByteDance and Alibaba's Financial Dominance, Only DeepSeek Recognized as Technology Leader

According to Scout Beating monitoring, Nathan Lambert, Head of Post-Training Team at the Allen Institute for Artificial Intelligence (AI2) and an authority in the field of Human Feedback-based Reinforcement Learning (RLHF), published an observation report after visiting several top AI labs in China. He revealed a fragmented competitive mentality in China's local large model ecosystem: the entire industry is in awe and fear of ByteDance and Alibaba's financial power, but at the same time, DeepSeek is recognized as the true technological leader.

Lambert pointed out that ByteDance, as the only closed-source cutting-edge lab in China, makes its peers feel "fearful," seen as a monopolistic giant that will eventually dominate the market through capital. In contrast, DeepSeek, with its excellent taste in research, has set the industry's technological direction, earning pure respect from peers, although everyone also believes that its current situation is "not geared to win in business." Additionally, in the development chain, Chinese developers heavily rely on Claude for assisted programming and have an extreme thirst for NVIDIA's computing power.

Explaining why Chinese models have been able to quickly catch up to the United States, Lambert believes that the moat is cultural rather than technological. Today's large model training is an extremely laborious systems engineering task. The U.S. scientific community is dominated by a culture of "star-making," where researchers' personal interests often conflict with the overall optimization of the model, and Silicon Valley-style scientific arrogance hinders collaboration (the Llama team has been in turmoil because of this).

In contrast, in China, where OpenAI and Anthropic rarely allow interns to touch core business, the absolute main force in Chinese labs is a large number of students. These young people have not experienced the early AI hype and do not carry the philosophical baggage of discussing the "future of humanity." They are extremely practical and willing to take on the most boring fine-tuning work.

This lengthy article breaks the stereotype that Chinese models only copy open source and also reveals a harsh reality: the large model competition is no longer a research battle based on "genius ideas" but rather a discipline test of engineering consumption. China is rapidly bridging the gap with its unburdened "student soldiers."