A new report from Bloomberg says that once-again CEO of OpenAI Sam Altman’s efforts to raise billions for an AI chip venture are aimed at using that cash to develop a “network of factories” for fabrication that would stretch around the globe and involve working with unnamed “top chip manufacturers.”

A major cost and limitation for running AI models is having enough chips to handle the computations behind bots like ChatGPT or DALL-E that answer prompts and generate images. Nvidia’s value rose above $1 trillion for the first time last year, partly due to a virtual monopoly it has as GPT-4, Gemini, Llama 2, and other models depend heavily on its popular H100 GPUs.

Accordingly, the race to manufacture more high-powered chips to run complex AI systems has only intensified. The limited number of fabs capable of making high-end chips is driving Altman or anyone else to bid for capacity years before you need it in order to produce the new chips. And going against the likes of Apple requires deep-pocketed investors who will front costs that the nonprofit OpenAI still can’t afford. SoftBank Group and Abu Dhabi-based AI holding company G42 have reportedly been in talks about raising money for Altman’s project.

Other companies developing AI models have also ventured into making their own chips. Microsoft, an investor in OpenAI, announced in November that it’s built its first custom AI chip to train models, closely followed by Amazon announcing a new version of its Trainium chip. Google’s chip design team is using its DeepMind AI running on Google Cloud servers to design AI processors like its Tensor Processing Units (TPU).

AWS, Azure, and Google use Nvidia’s H100 processors as well. This week, Meta CEO Mark Zuckerberg told The Verge reporter Alex Heath that “by the end of this year, Meta will own more than 340,000 of Nvidia’s H100 GPUs” as the company pursues the development of artificial general intelligence (AGI).

Nvidia has already announced its next-generation GH200 Grace Hopper chips to extend its dominance in the space, while competitors AMD, Qualcomm, and Intel have launched processors designed to power AI models running on laptops, phones, and other devices.