Hugging Face, an AI firm, receives funding from tech heavyweights Google, Nvidia, and Amazon

Following a $235 million investment round, the artificial intelligence business Hugging Face revealed a valuation of $4.5 billion, gaining backing from major global IT players including Salesforce, Google's Alphabet, Amazon, and Nvidia.

This funding highlights the fast-paced development of artificial intelligence (AI), which is seen as the upcoming technological frontier and has attracted significant investment from key figures in Silicon Valley.

As a result of OpenAI's ChatGPT's success, financing has also been secured for other AI firms like Microsoft- and Google-backed Runway and Inflection AI.

Nvidia has benefited from the battle among tech giants since its chip designs are essential to generative AI like ChatGPT. Following Wednesday's findings, Nvidia's shares hit a record high, having increased by thrice this year.

Hugging Face's funding round included participation from well-known companies like Intel, Advanced Micro Devices, Qualcomm, IBM, Amazon, and Ashton Kutcher's Sound Ventures.

The business provides an open-source platform for creating machine learning-based apps. For its current 170-person workforce, the cash will be used to support increased employment and technical improvements.

Hugging Face CEO Clément Delangue predicts that this year's revenue will climb fivefold as a result of the significant demand growth. Within five years, he predicts that all tech companies will have implemented AI.

Delangue announced on X (previously Twitter) during the most recent investment round that he is thrilled to welcome the new investors and that the company is now valued at $4.5 billion.

"Super excited to welcome our new investors Salesforce VC, Google, Amazon, Nvidia, AMD, Intel, Qualcomm, IBM, and Sound Ventures, who all participated in Hugging Face's $235M Series D at a $4.5B valuation to celebrate the crossing of 1,000,000 models, datasets and apps on the platform," he stated.

"On Hugging Face, these partners alone have over 10,000 users and have shared over 1,000 open models and datasets. Thanks to open-source, it takes a village to democratize effective machine learning, and we're just getting started, he continued.