AI, Reviews

US Intelligence Accuses DeepSeek and Alibaba of Mass Knowledge Distillation from GPT and Claude

Иллюстрация к теме: США обвинили DeepSeek и Alibaba в массовом копировании возможностей GPT и Claude

United States intelligence agencies have publicly alleged that six prominent Chinese artificial intelligence developers systematically utilized American frontier AI models to rapidly bootstrap and train their own proprietary systems. A joint advisory formally named DeepSeek, Moonshot AI, Alibaba, MiniMax, StepFun, and Z.ai.

The unclassified report, jointly published by the National Security Agency (NSA), the Cybersecurity and Infrastructure Security Agency (CISA), and the Federal Bureau of Investigation (FBI), accuses Chinese laboratories of employing aggressive “model distillation” techniques against American APIs, effectively bypassing hundreds of millions of dollars in primary R&D expenditure.

US intelligence joint advisory on model distillation and AI capabilities extraction

What Is Knowledge Distillation: Technical Reality vs. Accusation

Knowledge distillation is an established, widely accepted machine learning method wherein a smaller, more efficient “student” model is trained using the synthetic outputs produced by a massive, computationally expensive “teacher” model. Rather than learning raw patterns from uncurated web crawls, the student model absorbs structured reasoning traces directly from the teacher.

American intelligence agencies allege that Chinese developers scaled this approach into an industrial capability extraction mechanism. By submitting millions of automated queries to OpenAI’s GPT-4 and Anthropic’s Claude, Chinese labs harvested millions of high-quality reasoning examples, coding demonstrations, and logical deductions to fine-tune their own foundation architectures at a fraction of standard training budgets.

Evasion of Geoblocking and API Rate Limits

Because major American AI laboratories restrict direct API access from mainland China, Chinese developers reportedly circumvented geoblocking and terms-of-service limitations through coordinated infrastructure evasion:

  • Routing millions of synthetic queries through overseas VPN nodes and residential proxy clusters;
  • Deploying foreign shell entities and commercial credit cards registered across Singapore, Hong Kong, and Europe;
  • Distributing automated query bursts across dozens of third-party API aggregators and hosting providers around the clock.
Diplomatic and technology tensions between the United States and China over AI frontier models

Beijing Rejects Accusations as Anti-Competitive Protectionism

China’s Ministry of Commerce dismissed the U.S. allegations as baseless and politically motivated, emphasizing that knowledge distillation on synthetic data is standard scientific practice utilized by developers globally, including leading American corporations.

Beijing warned that Washington is weaponizing security claims to preserve American corporate monopolies, threatening reciprocal trade measures should the advisory be used as a pretext for fresh sanctions. China’s Ministry of Foreign Affairs asserted that domestic AI breakthroughs are the genuine fruits of indigenous engineering innovation.

The Dispute Over the $5.6 Million DeepSeek V3 Benchmark

The U.S. advisory specifically scrutinizes DeepSeek’s claim that its flagship V3 foundation model was trained for just $5.6 million in compute costs. Intelligence officials argue this figure is misleadingly understated because it excludes the implied commercial value of hundreds of thousands of distillation prompts harvested from Western frontier models.

However, DeepSeek has consistently maintained that the $5.6 million figure referred exclusively to the final GPU cluster pre-training run on its 2,048-accelerator cluster, rather than its cumulative R&D expenditures, custom architecture design, algorithmic optimizations, and staff payroll.

The debate highlights an unresolved technical boundary: where does legitimate training on synthetic datasets end, and illicit commercial capability extraction begin?

Implications for Kazakhstan’s Dual Tech Strategy

The escalating dispute has direct strategic ramifications for Central Asia. Kazakhstan is pursuing a pragmatic multi-vector digital policy: procuring high-performance NVIDIA GPUs and Western cloud instances on one hand, while collaborating closely with Chinese telecommunications leaders and AI research institutes on the other.

As the United States tightens API verification rules, synthetic data safeguards, and export licensing, emerging tech hubs like Kazakhstan must navigate increasingly rigid technological fault lines to maintain unhindered access to both AI ecosystems.

Official sources: Joint Advisory by NSA, CISA, and the FBI and Associated Press.


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