Hugging Face only started to offer paid features last year and counts more than 1,000 companies as customers, according to Delangue, including Intel and his former stomping ground eBay. Pharmaceutical giants Pfizer and Roche pay for enterprise-grade security features, while Bloomberg uses Hugging Face to build new natural language products on top its existing infrastructure. Microsoft is not a customer, but prominently uses Hugging Face as the basis to train its Bing search engine to better understand natural language queries.

“They prioritized adoption over monetization, which I think was correct,” says Sequoia partner Pat Grady, one of the new investors. “They saw that transformer-based models working their way outside of NLP and saw a chance to be the GitHub not just for NLP, but for every domain of machine learning.” Indeed, over the course of the last year, Hugging Face has started to become a hub for machine learning models for a variety of uses, such as computer vision to train image recognition in self-driving cars and recommender systems to help pharmaceutical companies predict the effectiveness of new drug therapies.

If his assumptions of machine learning supremacy are wrong, Delangue says Hugging Face is close to breakeven and has all $40 million from its previous fundraise still in the bank to reorient. “One of my personal learnings as an entrepreneur is to not think too much strategically with a big business plan of ten years, but more to experiment and follow the validation of the community and what they’re telling you,” he says. If the vision pans out, Reeves thinks the prize could be a $50 billion or $100 billion market capitalization on the stock market. It’s no wonder that Delangue says he’s turned down multiple “meaningful acquisition offers” and won’t sell his business, like GitHub did to Microsoft.

Source : www.forbes.com