Each month, Pinterest draws millions of users searching for new ideas, trends, and visual inspiration. Scroll long enough, and a user may stumble upon boards devoted to the strange and unexpected. Footwear turned into planters. Makeup designed to look like fast food. These playful concepts help fuel Pinterest’s reputation as a place where creativity runs freely.
What many users do not see is the technology shaping what appears on their screens. Behind the colorful images and curated boards, Pinterest has been testing AI systems developed in China to refine how content and products are recommended.
Bill Ready, the company’s CEO, has described Pinterest’s evolution into a tool that functions much like a smart shopping guide. While the firm is based in San Francisco and has access to leading American AI developers, it has increasingly incorporated Chinese-built models into its operations.
That shift gained momentum after the release of DeepSeek R-1 in 2025. The model was made openly available, allowing companies to download and adapt it. Ready has pointed to this decision as a turning point that accelerated interest in open-source AI across the industry.
Other Chinese players have followed a similar path. Alibaba offers its Qwen models, Moonshot has developed Kimi, and ByteDance, the parent company of TikTok, is pursuing comparable technologies. According to Pinterest’s CTO, Matt Madrigal, the appeal lies in flexibility. Open models can be customized in-house, something that is harder to do with many American systems that remain tightly controlled by their creators.
Madrigal says Pinterest’s internal models, trained using open-source methods, outperform standard commercial options while costing far less to run. In some cases, expenses drop by as much as 90% compared with proprietary tools from major U.S. developers.
Other major American companies are quietly weaving Chinese AI into their products. Airbnb chief executive Brian Chesky has said his company relies heavily on Alibaba’s technology to power its automated customer support, citing performance, speed, and affordability as key factors.
The trend is visible on Hugging Face, a popular hub where developers share and download AI models. Jeff Boudier, who works on product development at the platform, said cost considerations often push startups toward Chinese options.
He noted that models from Chinese labs frequently dominate download charts, sometimes accounting for most of the top training tools in a given week. Last September, Qwen overtook Meta’s Llama as the most downloaded family of large language models on the site.
At the start of 2025, many analysts believed U.S. companies were still comfortably ahead after spending billions on AI development. That view has shifted. Boudier said the focus has moved away from nationality and toward openness, arguing that the strongest systems now tend to be open source.
Research published recently by Stanford University supports that assessment, finding that Chinese models now match or exceed global competitors in both capability and adoption. The Stanford researchers also point to government backing as a factor in China’s progress.
Meanwhile, U.S. firms face growing pressure to turn AI into profit. OpenAI, for example, has leaned toward advertising and premium services while continuing to invest heavily in computing infrastructure.
As companies like D-Wave Quantum Inc. (NYSE: QBTS) push to commercialize newer technologies like quantum computing, the debate on whether to keep systems proprietary or have open-source components will continue as different countries race to dominate the tech space.
NOTE TO INVESTORS: The latest news and updates relating to D-Wave Quantum Inc. (NYSE: QBTS) are available in the company’s newsroom at https://ibn.fm/QBTS
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