When a small Chinese company called DeepSeek revealed that it had created an A.I. system that could match leading A.I. products made in the United States, the news was greeted in many circles as a warning that China was closing the gap in the global race to build artificial intelligence.
DeepSeek also said it built its new A.I. technology more cost effectively and with fewer hard-to-get computers chips than its American competitors, shocking an industry that had come to believe that bigger and better A.I. would cost billions and billions of dollars.
But A.I. experts inside the tech giant Meta saw DeepSeek’s breakthrough as something more than the arrival of a nimble, new competitor from the other side of the world: It was vindication that an unconventional decision Meta made nearly two years ago was the right call.
In 2023, Meta, in a widely criticized move, gave away its cutting-edge A.I. technology after spending millions to build it. DeepSeek used parts of that technology as well as other A.I. tools freely available on the internet through a software development method called open source.
Meta executives believe DeepSeek’s breakthrough shows that upstarts now have a chance to innovate and compete with the tech giants that have mostly had the A.I. playing field to themselves because A.I. costs so much to build. It was something Meta executives hoped would happen when they gave away their own technology.
“Our open source strategy was validated,” said Ragavan Srinivasan, a Meta vice president, in an interview on Tuesday. “The more people who have access to the technology needed to move things forward faster, the better.”
Meta is also taking a close look at the work done at DeepSeek. Following Meta’s lead, the Chinese company released its technology to the open source tech community as well. Meta has created several “war rooms” where employees are reverse engineering DeepSeek’s technology, according to two people familiar with the effort who spoke on the condition of anonymity.
The Meta employees are looking for ways to lower the cost of training its software — a term used to to describe the way A.I. technologies learn from data — and apply it to Meta’s own A.I. The Information earlier reported on the war rooms.
Before Meta, which owns Facebook, Instagram and WhatsApp, gave away its A.I. tech, the company had been focused on projects like virtual reality. It was caught flat-footed when OpenAI introduced the chatbot ChatGPT in late 2022. Other tech giants like Microsoft, OpenAI’s close partner, and Google were also well ahead in their A.I. efforts.
(The New York Times has sued OpenAI and its partner, Microsoft, claiming copyright infringement of news content related to A.I. systems. The two tech companies have denied the suit’s claims.)
By freely sharing the code that drove its A.I. technology, called Llama, Meta hoped to accelerate the development of its technology and attract others to build on top of it. Meta engineers believed that A.I. experts working collaboratively could make more progress than teams of experts siloed inside companies, as they were at OpenAI and the other tech giants.
Meta could afford to do this. It made money by selling online ads, not A.I. software. By accelerating the development of the A.I. it offered to consumers for free, it could bring more attention to online services like Facebook and Instagram — and sell more ads.
“They were the only major U.S. company to take this approach. And it was easier for them to do this — more defensible,” said Chris V. Nicholson, an investor with the venture capital firm Page One Ventures, who focuses on A.I. technologies. Meta can offer A.I. below the cost to build it — or even give it away — to attract customers and increase sales of other services, he added.
Many in Silicon Valley said Meta’s move set a dangerous precedent because the chatbots could help spread disinformation, hate speech and other toxic content. But Meta said that any risks were far outweighed by the benefits of open source. And most A.I. development, they added, had been shared around through open source until ChatGPT made companies leery of showing what they working on.
Now, if DeepSeek’s work can be replicated — particularly its claim that it was able to build its A.I. more affordably than most had thought possible — that could provide more opportunities for more companies to expand on what Meta did.
“These dynamics are invisible to the U.S. consumer,” said Mr. Nicholson. “But they are hugely important.”
Yann LeCun, an early A.I. pioneer who is Meta’s chief A.I. scientist, said in a post on LinkedIn that people who think the takeaway from DeepMind’s work should be that China is beating the United States at A.I. development are misreading the situation. “The correct reading is: ‘Open source models are surpassing proprietary ones,’” he said.
Dr. LeCun added that “because their work is published and open source, everyone can profit from it. That is the power of open research.”
By last summer, many Chinese companies had followed Meta’s lead, regularly open sourcing their own work. Those companies included DeepSeek, which was created by a quantitative trading firm called High-Flyer.
Some Chinese companies offered “fine-tuned” versions of technology open sourced by companies from other countries, like Meta. But others, such as the start-up 01.AI, founded by a well-known investor and technologist named Kai-Fu Lee, used parts of Meta’s code to build more powerful technologies.
U.S. tech experts still argue that U.S. companies like Meta should not be open sourcing their technologies because they were fueling A.I. in China. But others say that if American companies stopped freely providing their technology, the epicenter of open source development would simply shift to China anyway.
Earlier this year, students at the University of California, Berkeley built an A.I. system that in many ways rivaled the performance of OpenAI’s latest system. They did this by building on top of two open-source technologies released by the Chinese tech giant Alibaba.
“When you are in a race to build technology, the best way to compete is to share code, strengthen the foundation and accelerate the rate of progress,” said Clément Delangue, chief executive of Hugging Face, a company that hosts many of the world’s open-source A.I. projects.
