OpenAI — the company behind the ChatGPT large language model — has raised an additional $6.6 billion in capital from institutional investors, bringing the private company’s valuation to $157 billion.

The funding round included venture capital firms Thrive Capital and Khosla Ventures as well as tech giants Nvidia and Microsoft.

OpenAI raised the funds by offering investors convertible debt that will convert to equity if the company manages to successfully pivot to a for-profit business entity without restrictions such as profit caps on investment returns and reliance on nonprofit governance structures.

OpenAI’s proposed shift to a profit model

OpenAI is purportedly working on restructuring the company to a purely for-profit business model — a shift that will require overcoming regulatory red tape and raising questions about the legality of the restructuring.

Following OpenAI’s announcement that it was seeking to change its business model, Elon Musk — a co-founder of OpenAI — criticized the purported shift as “illegal.”

However, California — where OpenAI is headquartered — does allow nonprofit corporations to convert to for-profit models through a complex process that first transforms the entity into a for-profit stock corporation and later a limited liability corporation (LLC).

To justify its more than $150 billion valuation, OpenAI is seeking to expand its revenue streams by exploring high-end subscription plans that could cost upward of $2,000 per month. In September 2024, OpenAI revealed that it acquired 1 million users across its suite of products — a 67% increase since April 2024.

ChatGPT gets new features

On Oct. 1, OpenAI announced an update to ChatGPT that enhances the vision and speech capabilities of the large language model.

The upgrade to the Realtime API gives developers a more streamlined process to create voice-to-voice applications that mimic natural speech patterns.

Enhancements to ChatGPT’s image processing capabilities were also rolled out during the latest updates. This allows human operators to provide feedback to the language model to reinforce its abilities and train the model to improve its responses over time.

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