The AI Cold War? US tech companies accuse China’s AI firms of stealing billions in research

Euronews · Feb 26, 2026 · Collected from RSS

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As the United States and China race to develop artificial intelligence (AI), American firm Anthropic is the latest company to sound the alarm that Chinese AI companies have been stealing the technology that could decide who wins. DeepSeek, Moonshot AI and MiniMax secretly generated over 16 million conversations with Anthropic's AI chatbot Claude, using more than 24,000 fake accounts, to harvest its intelligence and train their own competing models, the company alleges. OpenAI and Google have also warned about similar accusations at Chinese firms this month, raising fears that China is short-circuiting years of costly AI research. What is AI distillation? Model extraction attacks (MEA), otherwise known as “distillation”, is a technique in which someone with access to a powerful AI model uses it to train a cheaper, faster rival. The method feeds the larger model thousands of questions, collects its answers, and uses those responses to teach a new model to think in the same way. The user can ask the larger model questions and use its responses to train the smaller model, which develops the smaller AI faster and “at a fraction of the cost,” than if the threat actor had done the original work themselves, Anthropic alleges. Distillation is a “legitimate” practice when frontier AI labs distil their own models to “create smaller, cheaper versions for their customers, the US company said. Smaller models answer queries much faster and require fewer computer power or energy to run than the larger model, Google said.​ Meanwhile, the models developed using distillation pose significant national security risks because they “lack necessary safeguards,” according to Anthropic, to limit the potential danger of these models. Anthropic stated that distilled models will not have the safeguards to prevent state and non-state actors from using AI in bioweapons or conducting cyberattacks. There are no risks to ordinary AI consumers in a distillation attack, Google added, because the attacks do not “threaten the confidentiality, availability or integrity of AI services”.​ Meanwhile, OpenAI told US lawmakers in February it had caught DeepSeek trying to secretly copy its most powerful AI models — and warned that the Chinese company was developing new methods to disguise what it was doing. What do hackers teach their models? China’s AI companies allegedly routed traffic through proxy addresses that managed a vast “hydra network,” a large group of fake accounts that spread their activity across platforms to get access to Anthropic, since it is banned in China. Once the companies were in, they generated large volumes of prompts either to collect high-quality responses for model training or to generate tens of thousands of tasks for reinforcement learning, how an agent learns to make decisions from feedback. The DeepSeek accounts that hacked Claude asked the model to articulate how it rationalised an answer to a prompt and write it out step by step, which the company said “generated chain-of-thought training data at scale”. Claude was also used by the DeepSeek accounts to “generate censorship-safe alternatives to politically sensitive queries,” such as questions about opponents to the current Communist Party, Anthropic alleges. The US company theorised that those questions trained DeepSeek’s models “to steer conversations away from censored topics,” which could support a recent study that found Chinese AI models likely censor the same topics as their media. MiniMax AI and Moonshoot AI had larger distillation campaigns than DeepSeek, but Anthropic did not offer examples for the types of information that these two companies collected in their prompts. Google said that its AI chatbot Gemini is consistently misused for coding and scripting tasks, or gathering intelligence such as sensitive account credentials and email addresses. Anthropic says it has built detection measures to identify these campaigns as they happen, but noted that no AI company can solve the problem by itself.