Nvidia CEO Jensen Huang says the company’s widely discussed plan to invest up to $100 billion in OpenAI was never a firm promise. Speaking with reporters in Taipei, he explained that the invitation to invest was appreciated, but the company intended to proceed slowly and assess each stage rather than commit the full amount upfront. His comments follow a report from Bloomberg News outlining the remarks and a separate piece from the Wall Street Journal claiming the investment talks had slowed due to internal doubts at Nvidia.
According to that earlier report, some inside Nvidia questioned the scale of the proposed deal, and Huang had privately emphasized that the agreement was nonbinding. He was also said to have raised concerns about how OpenAI was running parts of its business and about growing competition across the AI sector. Huang rejected the idea that he was unhappy with OpenAI, calling such claims inaccurate. He said Nvidia still intends to invest heavily, praising OpenAI’s work and describing the company as one of the most influential of the current era.
The discussion comes at a time when OpenAI is reportedly moving faster toward a potential initial public offering, which could arrive as early as the fourth quarter. Market watchers are paying close attention because such a move would test how willing investors are to back large AI projects that require significant spending on chips and data infrastructure. These costs affect cloud services, eCommerce and payments, creating broader economic ripple effects.
Recent data from PYMNTS shows that OpenAI continues to dominate consumer AI usage. Among people who have used a dedicated AI platform for at least one task, 83 percent tried ChatGPT, compared with 48 percent for Google’s chatbot and 30 percent for Microsoft’s. The finding highlights how consumers often stay with the first major platform they try, shaping expectations for the entire category. The report notes that even a single interaction can influence long-term behavior because the first platform someone uses often becomes their reference point for what AI tools should feel like.
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