DeepSeek Reportedly Suspends Funding Round Ahead of IPO

Chinese artificial intelligence startup DeepSeek has reportedly paused its second round of funding.
That’s according to a report Saturday (July 25) from Bloomberg News, which says the decision comes days after viral comments on American-Chinese AI competition, widely attributed to the company’s founder.
Sources familiar with the matter told Bloomberg that DeepSeek had told some would-be investors they would not be signing investment agreements as planned.
According to the report, the sources said the suspension was related in part to founder Liang Wenfeng’s frustration over online reports about his comments to investors during the company’s first funding deal, which raised $7 billion.
The report in question, which Bloomberg said it had not verified, dealt with a transcript of a meeting Liang held with unidentified parties, in which he discussed a reliance on Nvidia chips for AI development and China’s ongoing lag in AI sophistication compared to the U.S.
DeepSeek, the report added, was targeting a raise of at least 10 billion yuan ($1.4 billion) in new funding in the second round, and had been targeting a pre-money valuation of at least 480 billion yuan, or $70.8 billion. The first round valued DeepSeek at $50 billion.
DeepSeek sent shockwaves through the AI world early last year when it debuted an AI model that offered performance comparable to those of American rivals OpenAI and Meta while using substantially fewer Nvidia chips.
The company is also preparing for an initial public offering (IPO) that could come as soon as this year, the report added.
In other AI news, PYMNTS wrote last week about new research showing that weak AI regulation can lead to worse safety outcomes than no regulation at all. 
The research, published in the Proceedings of the National Academy of Sciences by researchers from Cornell University and Carnegie Mellon University, found poorly targeted or insufficiently rigid regulation can incentivize companies to lower their own safety investments and move responsibility to others.
When downstream companies are expected to make sure that their applications adhere to regulatory standards, general-purpose model creators could potentially “free ride” on those investments by scaling back measures like third-party safety audits, the report said.
“There’s a free-riding behavior that occurs,” principal author Benjamin Laufer said. “The regulation acts as a tool for the general provider to offload the safety burden onto the downstream specialist.”
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