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Earlier today, Hugging Face, a community-driven machine learning (ML) platform, announced $ 100 million in new funding – raised in just one week – to continue building, with many, including CEO Clement Delangeu, calling it a “github of machine learning.”
“I think that’s an exact analogy,” he told VentureBeat. “With each new technology comes a new category-defined platform that builds it. GitHub was for that software and it looks like we are becoming a platform for machine learning.
Founded in 2016, Hugging Face evolved from a developer of natural language processing (NPL) technology into an open-source library and community platform where popular NLP models such as BERT, GPT-2, T5 and DistillBERT are available. Now, it has moved beyond NLP to become an ML model hub and community – Hugging Face works closely with companies that are seen as competitors, as companies such as Meta’s AI division, Amazon Web Services, Microsoft and Google AI use the platform. Is.
“We have seen the emergence of a new generation of machine learning architectures known as Transformers, based on transfer learning,” Delangu said. “Most users of this new generation model are using it through our platform – it all started with text, but now it’s starting to enter all machine learning domains, a new development for machine learning tools.”
Focus on ethical AI
Hugging Face has created some of the most recent notable jobs in the ethical AI space, which Dalengue said is an important priority. Margaret Mitchell, former head of Google’s Ethical AI research group, joined the board in August 2021. And Giada Pistili, Who holds a Ph.D. AI specializes in philosophy and communication ethics, starting with Hugging Face today.
“It’s a good time – a person with a PhD. Philosophy is a very unusual fare for a technology company, but I think it’s a testament to our commitment to making the machine learning sector more value-driven, as Margaret Mitchell likes to say, “Delangeau said.
Delangue added that Hugging Face has a “strong view” on the future of AI and ML. “As science always works to keep the field open and collaborative, we believe that there is a big risk of keeping machine learning power too concentrated in the hands of a few players, especially when these players do not have a track record. The right thing for the community, “he said.” By building the ecosystem more openly and collaboratively, we can make machine learning a positive technology for everyone and work on some of the short-term challenges we are seeing. ”
An ‘open and collaborative’ ML evolution
Delangue said Hugging Face plans to continue to lead his team from a variety of backgrounds for all positions and capabilities, from science and engineering to the production and business side. “It’s a big evolution for us,” he said. “We also hope to see an increase in the number of models and data sets on the platform.”
The company is also excited about Big Science, a one-year research project on large multilingual models and datasets. “It’s the largest machine learning collaboration we’ve ever had with more than a thousand scientists and 200 organizations, inspired by other major scientific collaborations in physics,” Delangue said. “We wanted to create something like that for machine learning.”
But it emphasizes the Hugging Face’s open collaborative approach, which DeLanguage said has given investors confidence in the 2 billion valuation. “This is what really matters to us, what makes us successful and what sets us apart from others in space.”
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