Open-source AI model developer AI model repository, Hugging Face, has successfully secured a substantial $235 million in its Series D fundraising round. This latest financial boost has propelled the company's valuation to an impressive $4.5 billion. The fundraising saw participation from tech giants including Google, Amazon, Nvidia, Intel, and notably Salesforce, among others.
Hugging Face, often likened to GitHub but for machine learning and AI models, has been at the forefront of the AI community. The platform hosts a plethora of generative AI models, including notable ones like Stable Diffusion from Stability AI and Meta's Llama 2.
The company also develops its own generative AI models, including the SafeCoder AI code assistant that Hugging Face revealed this month. The design of SafeCoder allows for on-premises deployment, giving enterprises ownership of their code. In July, Hugging Face announced Agent.js, a JavaScript library that allows developers to create conversational agents that can run in the browser or on the server.
Clement Delangue, the CEO of Hugging Face, shared that the funds would be channeled towards expanding their team, which currently stands at 170, and further investing in open-source AI and platform development. Delangue emphasized the significance of the open-source community in the growth of generative AI, stating, “It's a validation both for Hugging Face, but also for the broader open-source AI ecosystem.”
https://twitter.com/Benioff/status/1694122632193659248
Salesforce Ventures Leads the Way
Salesforce Ventures took the lead in this funding round, expressing their belief in the transformative power of open-source AI. They view Hugging Face as a pivotal player in this domain, with the platform acting as a central hub connecting AI developers, researchers, and enthusiasts. Their official announcement highlighted their conviction that open-source AI will shape the future of the AI landscape, emphasizing the importance of collaboration, transparency, and innovation. This sentiment was echoed in a tweet from Salesforce CEO Marc Benioff, celebrating Hugging Face's role in accelerating the AI ecosystem.
From Chatbot to AI Pioneer
Founded in 2016 by Delangue, Julien Chaumond, and Thomas Wolf, Hugging Face initially started as a chatbot designed for teenagers. However, the founders soon recognized the potential of the underlying natural language processing models and shifted their focus. Today, the company offers a range of data science tools and has established itself as a go-to platform for AI developers seeking code repositories, datasets, and AI models, according to Decrypt.
With a vision to democratize AI, Hugging Face plans to delve deeper into various domains, scaling its efforts and expanding its workforce in the upcoming months. Their commitment to open-source AI, combined with the backing of major tech players, positions them as a key influencer in the future of the AI industry.
Hugging Face is becoming an increasingly important player in the growing AI market. In February, the company announced a strategic partnership with Amazon Web Services (AWS), selecting Amazon as its preferred cloud provider for the future.
With this partnership, developers and companies can harness the power of machine learning models and deliver NLP features more quickly. The Hugging Face community can tap into AWS's machine learning offerings and infrastructure. They can use Amazon SageMaker, the cloud machine-learning platform, AWS Trainium, the custom machine-learning processor, and AWS Inferentia, the machine learning accelerator, to train, fine-tune and deploy their models.
In March, that Azure Machine Learning now has Hugging Face foundation models. Microsoft and Hugging Face has been in partnership since last year. That initial collaboration focused on building Hugging Face Endpoints – a machine learning inference service that is underpinned by Azure ML Managed Endpoint.
Last month, Hugging Face also struck a partnership with chip giant AMD. The partnership will allow developers to train and deploy large language models (LLMs) on AMD hardware, which will significantly improve performance and reduce costs.
