According to Beating Monitoring, in response to Washington and Anthropic's attempt to cut off China's large model "distillation" channels by blocking cutting-edge models, Kevin S. Xu, former head of international strategy at GitHub and founder of Interconnected Capital, pointed out that adversarial distillation is only a desperate shortcut for some independent Chinese labs suffering from data scarcity. Relying on API blocks cannot fundamentally stop the overall progress of Chinese AI. The named entities DeepSeek, Moon Shadow, and MiniMax are all independent labs lacking support from a corporate ecosystem, facing the critical issue of scarce high-quality training data such as reasoning steps. In contrast, large labs backed by Alibaba (Qwen), ByteDance (Seed), or Xiaomi possess massive proprietary scenario data comparable to Google and Apple, and do not rely on distillation. Therefore, blocking policies at most cause short-term setbacks for independent labs and cannot shake the foundation of Chinese tech giants. The so-called "data advantage" of China is a misconception: in terms of high-quality knowledge annotation and evaluation data required for training cutting-edge large models, China not only lacks an advantage but is also severely deficient in mature commercial data supply chains like Scale AI or Surge. Due to the poor quality of domestic data service providers, independent labs, in despair and out of laziness to take shortcuts, have resorted to API distillation as a cheap data acquisition strategy. However, the data annotation industry is a low-threshold commercial model issue, not a technical bottleneck like lithography machines; the domestic supply-demand gap can be easily filled. In the long run, student models trained solely by distillation cannot surpass their teachers in theory, but since large models are still built by human engineers, whether the U.S. forcibly cuts off API channels or not, clever and diligent Chinese developers will ultimately break this upper limit, designing models that surpass their mentors. U.S. sanctions are not only ineffective but may also prematurely cut off the theoretical constraints that could lock Chinese models into the "student" ceiling.

View Original

This page may contain third-party content, which is provided for information purposes only (not representations/warranties) and should not be considered as an endorsement of its views by Gate, nor as financial or professional advice. See Disclaimer for details.

Reward
like
Comment
Repost
Share

Comment

Add a comment

No comments

Trending Topics
View More
#
MyGateTradeStory
684.41K Popularity
#
TradFiCFDGoldMasters
2.04M Popularity
#
PredictWorldCup🏴󠁧󠁢󠁥󠁮󠁧󠁿vs🇭🇷
847.97K Popularity
#
GateSpotVolumeLeadsGlobalGrowth
68.4M Popularity
#
MarvellPlungesNearly10%
138.42K Popularity

Pinned

Sitemap

The effectiveness of large model anti-distillation policies is questionable: distillation is just a shortcut for data in independent labs, and blocking cannot prevent China's AI from catching up.

Trending Topics

MyGateTradeStory

TradFiCFDGoldMasters

PredictWorldCup🏴󠁧󠁢󠁥󠁮󠁧󠁿vs🇭🇷

GateSpotVolumeLeadsGlobalGrowth

MarvellPlungesNearly10%

Pinned