Hugging Face triples investment in open source machine learning models

Hugging Face launched in 2016 with a chatbot app designed to be your “AI friend.” Now the NLP company has more than 100,000 community members and is planning to triple its efforts and expand beyond language models into fields like computer vision. Developers have used a hub on Hugging Face to share thousands of models, and CEO and cofounder Clement Delangue told VentureBeat Hugging Face wants to become to machine learning what GitHub is to software engineering.

As part of that effort, Hugging Face closed a $40 million series B funding round today. The round was led by Addition, with participation from Lux Capital, A.Capital, and Betaworks. Notable individual investors in the round include MongoDB CEO Dev Ittycheria, NBA star Kevin Durant, Dataiku CEO Florian Douetteau, and former Salesforce chief scientist Richard Socher.

Delangue said Hugging Face believes transfer learning is critical to the future of machine learning. As evidence of this trend, Delangue points to an AI research paper published earlier this week by researchers from Google Brain, Facebook AI Research, and UC Berkeley about pretrained language models working with numerical computation, vision, and protein fold prediction. This and other recent advances, he said, signify that “transfer learning models are starting to eat the whole field of machine learning.”

“Everything transfer learning-based we believe is here to stay and is going to transform machine learning for the next five years,” he told VentureBeat. “We’ve seen that they completely changed the NLP field, and they’re starting to change the computer vision fields, like with vision transformers and the speech-to-text fields. Ultimately, we think transfer learning is going to power machine learning, and hopefully we’re going to be able to power all these transfer learning models.”

Hugging Face has also published AI research. A paper about the Transformers NLP library that’s seen more than 10 million Python pip installs and been used by a number of businesses — including Microsoft’s Bing and MongoDB — received the Best Demo paper award at the EMNLP research conference last year.

In addition to tripling efforts to grow an open source community for the development of language models, Delangue said the funds will help ensure Hugging Face has the resources to act as a “counter-power” to major cloud AI services being sold to enterprise customers. NLP is an area of interest for a number of companies hoping to sell AI services to enterprise customers, including Databricks, which raised $1 billion last month and plans to focus on acquiring NLP startups.

“I think one of the big challenges that you have in machine learning, it seems these days, is that most of the power is concentrated in the hands of a couple of big organizations,” he said. “We’ve always had acquisition interests from Big Tech and others, but we believe it’s good to have independent companies — that’s what we’re trying to do.”

Democratization, Delangue said, will be key to assuring the benefits of AI extend to smaller organizations. Hugging Face CTO Julien Chaumond echoed that thought. In a statement shared with VentureBeat, he said democratization of AI will be one of the biggest achievements for society and that no single company, not even a Big Tech business, can do it alone. 

Hugging Face began monetizing ways to help businesses create custom models six months ago, and now it works with over 100 companies, including Bloomberg and Qualcomm. A Hugging Face spokesperson told VentureBeat the company has been cash-positive in the first months of 2021.

“You can start seeing that companies are really going to have dozens of what we call machine learning features or NLP features,” he said. “It’s not going to be like one big feature, but they’re going to have a lot of different NLP features that are going to be really deeply embedded into their products or their workflow in multiple different ways.”

In other recent Hugging Face news, Hugging Face extended into machine translation last year and in recent weeks launched subcommunities for people working with low-resource languages to create language models.

Hugging Face raised $15 million in a 2019 series A funding round and has raised a total of $60 million to date. In 2017, Hugging Face was part of the Voicecamp startup accelerator hosted by Betaworks in New York City.

Hugging Face currently has 30 employees, with offices in New York and Paris.