The American companies building artificial intelligence systems are loudly complaining that their Chinese competitors are unfairly copying their technology, and they are pleading with officials to do something about it.
On June 10, Anthropic sent a letter to Senators Tim Scott and Elizabeth Warren, accusing the Chinese tech giant Alibaba of surreptitiously copying its A.I. technologies using a technique called distillation.
Like other Chinese companies, Alibaba tapped into Anthropic’s technologies through tens of thousands of unauthorized accounts, according to the letter, which was viewed by The New York Times. Then it used the data it collected to train its own A.I. systems. Anthropic asked the lawmakers, who lead a Senate committee that was about to hold a hearing on A.I., to explore ways of curbing China’s distillation.
“These distillation attacks are carried out illicitly, systematically and at industrial scale to harvest U.S. A.I. capabilities across frontier labs and repackage them as their own,” Anthropic told the two senators, referring to companies on the frontier of A.I. development.
Experts say China trails the United States in A.I. development by just six months. Anthropic and other U.S. companies argue that without help from distillation, China would be much further behind, which could affect major A.I. uses like business planning, drug research, mass surveillance and military weapons.
Their complaints have new urgency now that the Chinese start-up Z.ai has released an A.I. model, GLM-5.2, that is nearly as powerful as the top American systems. It rivals them when used for cybersecurity, an area that American A.I. companies and the Trump administration have singled out as vitally important to geopolitics.
But what exactly is distillation, and are Chinese companies the only ones doing it? Here is an explanation.
Is distillation a new concept?
Not at all. Distillation has been common in the tech industry for more than a decade. A small team of Google researchers first developed the technique in the early 2010s as a way of building more efficient A.I. systems.
Through distillation, researchers can collect data from a particularly powerful system and use that data to build a system that can run on less expensive hardware.
The first A.I. model essentially shows the second model how to behave, said Geoffrey Hinton, a former Google researcher who helped develop the technique. “Think of one model as the teacher and the other as a student,” he said.
Distillation is a way to copy your own A.I.?
Correct. But some companies used distillation to mimic technologies built by other A.I. labs. They often copied the behavior of open source technologies — systems that anyone can use, modify and copy for free and largely without restriction.
That is what labs hope to encourage when they open source their systems. The idea is that everyone benefits because A.I. is developed more quickly.
When is distillation a problem?
Anthropic, OpenAI and other A.I. labs get annoyed when companies use distillation to mimic the behavior of their proprietary systems — technologies that are not open source. These are typically their most powerful systems.
Anthropic and OpenAI do not allow distillation for their leading systems under their terms of service. But distilling these systems is still common.
In April, while testifying in a federal trial in Oakland, Calif., Elon Musk acknowledged the practice at his A.I. company, xAI. When a lawyer asked if xAI had ever distilled technology from OpenAI, Mr. Musk replied: “Generally A.I. companies distill other A.I. companies.”
Is that illegal?
That’s not clear, said Sarah Tishler, a partner at the law firm Beck Reed Riden who specializes in trade-secret litigation.
Some legal scholars argue that the practice violates the Defend Trade Secrets Act, a 2016 law that allows businesses to sue over the theft of trade secrets, but courts have not explicitly decided that.
Copyright law does not necessarily apply because distillation is an effort to copy the behavior of the system, as opposed to copying text verbatim.
Are the Chinese doing something similar?
It is also not completely clear what Chinese companies are doing. They have likely distilled proprietary models in much the same way that American companies like xAI have done.
Chinese distillation efforts, however, have caused far more concern among Anthropic, OpenAI and the other U.S. companies.
About 18 months ago, the Chinese start-up DeepSeek shocked Silicon Valley when it showed that it could build effective A.I. far more affordably than many of its American counterparts. OpenAI soon accused DeepSeek of distilling its technologies.
In February, Anthropic accused DeepSeek and two other Chinese start-ups of improperly harvesting large amounts of data from its systems. Anthropic said the start-ups had used about 24,000 accounts to generate over 16 million conversations with its Claude chatbot that could be used to teach skills to their own chatbots.
How does Anthropic know this?
Anthropic closely monitors how people use its systems. Certain repeated behavior, the company said, showed that accounts linked to China were lifting data from its proprietary models.
Anthropic claimed that various Chinese companies had used a network of accounts to gain access to its systems. Each Chinese company, Anthropic said, uses this data to help train its own technologies.
Can Anthropic prevent this?
Anthropic, OpenAI and Google are sharing information that they can all use to combat the practice, they said. But it can be difficult to stop. If Anthropic shuts down too many accounts, it may end up barring legitimate users.
Even if U.S. law did bar illicit distillation, Ms. Tishler said, it would most likely have little effect on behavior in China.
“So much of this conduct is happening outside the United States,” she noted. “It would be very challenging to address it through a U.S. court.”
(The Times sued OpenAI and Microsoft in 2023, claiming copyright infringement of news content related to A.I. systems. The two companies have denied those claims.)
What else can U.S. companies do?
Anthropic called on Congress to pass legislation that would allow “deeper collaboration to combat distillation attacks, both between the U.S. government and leading frontier labs as well as between the frontier labs themselves.”
The company also said the U.S. government should extend its efforts to limit China’s access to the specialized computer chips needed to train A.I. technologies. The world’s most powerful chips are designed by American companies, and the federal government has used export controls to stem the flow of those chips to China. It is difficult to do distillation without those chips.
Alibaba declined to comment on Anthropic’s letter to the two senators. Ms. Warren, Democrat of Massachusetts, also declined to comment. Mr. Scott, Republican of South Carolina, did not respond to a request for comment.
Would a distillation crackdown have an impact?
Many experts believe that a crackdown on Chinese distillation would have little effect, and that distillation alone cannot build a top A.I. system as Z.ai did.
Others believe that distillation will become less important as companies build systems, like GLM-5.2, that are designed to serve as A.I. agents. Training these agents — digital assistants that can use other software to perform tasks — is much harder to duplicate through distillation.
Distillation “won’t matter as much for the next era of A.I.,” said Sara Hooker, chief executive of Adaption, an A.I. research lab.
Ryan Mac contributed reporting from Los Angeles, Eli Tan from San Francisco and Steve Lohr from New York.
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