DeepSeek vs. ChatGPT fuels debate over AI building blocks

The icons for the smartphone apps DeepSeek and ChatGPT are seen on a smartphone screen in Beijing

When Chinese startup DeepSeek released its AI model this month, it was hailed as a breakthrough, a sign that China’s artificial intelligence companies could compete with their Silicon Valley counterparts using fewer resources.

The narrative was clear: DeepSeek had done more with less, finding clever workarounds to U.S. chip restrictions. However, that storyline has begun to shift.

OpenAI, the U.S.-based company behind ChatGPT, now claims DeepSeek may have improperly used its proprietary data to train its model, raising questions about whether DeepSeek’s success was truly an engineering marvel.

In statements to several media outlets this week, OpenAI said it is reviewing indications that DeepSeek may have trained its AI by mimicking responses from OpenAI’s models.

The process, known as distillation, is common among AI developers but is prohibited by OpenAI’s terms of service, which forbid using its model outputs to train competing systems.

Some U.S. officials appear to support OpenAI’s concerns. At his confirmation hearing this week, Commerce secretary nominee Howard Lutnick accused DeepSeek of misusing U.S. technology to create a "dirt cheap" AI model.

"They stole things. They broke in. They’ve taken our IP," Lutnick said of China.

David Sacks, the White House czar for AI and cryptocurrency, was more measured, saying only that it is "possible" that DeepSeek had stolen U.S. intellectual property.

In an interview with the cable news network Fox News, Sacks added that there is "substantial evidence" that DeepSeek "distilled the knowledge out of OpenAI’s models," adding that stronger efforts are needed to curb the rise of "copycat" AI systems.

At the center of the dispute is a key question about AI’s future: how much control should companies have over their own AI models, when those programs were themselves built using data taken from others?

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DeepSeek vs. ChatGPT fuels debate over AI building blocks