Hugging Face
New York
United States
Overview
You know how Reddit is sometimes described as the “front page of the internet”? Think of Hugging Face as the proverbial front page of the open-source (free to use) machine learning community.
If Nvidia is powering the hardware end of many of the AI models the world is relying upon, then Hugging Face is providing the tools for building these machine learning applications. Founded in 2016 by three French entrepreneurs, Hugging Face was initially an attempt to create a chatbot app for teenagers. (The company’s unusual name comes from the “hugging face” emoji popular across social media.) However, one big pivot later, and it has developed into a powerful GitHub-type library for open-source machine learning resources. Which, based on the current AI boom period, is seemingly everyone.
Like a combination tool box and helpful friend, Hugging Face resources include all the demos, models, and datasets necessary to start carrying out tasks like getting an AI to recognize specific objects in an image or generating text. Because many of these tasks are tough to implement (let alone optimize), the presence of established libraries makes learning, experimentation, and implementation significantly easier and faster.
As well as offering the necessary code to build, train, and deploy these open-source ML models, Hugging Face also represents a community of sorts for the likes of data scientists and machine learning engineers to gather, share ideas, and make contributions to a growing number of projects.
With upward of 200,000 daily users and thousands of organizations using its resources to better integrate AI capabilities into their workflow and products, Hugging Face is filling a critical role in the development of modern AI. At a time when more companies than ever are getting involved with AI, and a growing number of practitioners are working remotely, Hugging Face therefore addresses a serious need in the marketplace.
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If Nvidia is powering the hardware end of many of the AI models the world is relying upon, then Hugging Face is providing the tools for building these machine learning applications. Founded in 2016 by three French entrepreneurs, Hugging Face was initially an attempt to create a chatbot app for teenagers. (The company’s unusual name comes from the “hugging face” emoji popular across social media.) However, one big pivot later, and it has developed into a powerful GitHub-type library for open-source machine learning resources. Which, based on the current AI boom period, is seemingly everyone.
Like a combination tool box and helpful friend, Hugging Face resources include all the demos, models, and datasets necessary to start carrying out tasks like getting an AI to recognize specific objects in an image or generating text. Because many of these tasks are tough to implement (let alone optimize), the presence of established libraries makes learning, experimentation, and implementation significantly easier and faster.
As well as offering the necessary code to build, train, and deploy these open-source ML models, Hugging Face also represents a community of sorts for the likes of data scientists and machine learning engineers to gather, share ideas, and make contributions to a growing number of projects.
With upward of 200,000 daily users and thousands of organizations using its resources to better integrate AI capabilities into their workflow and products, Hugging Face is filling a critical role in the development of modern AI. At a time when more companies than ever are getting involved with AI, and a growing number of practitioners are working remotely, Hugging Face therefore addresses a serious need in the marketplace.
