This article is part of our series that explores the business of artificial intelligence. Last week, Hugging Face announced a new product in collaboration with Microsoft called Hugging Face Endpoints on Azure, which allows users to set up and run thousands of machine learning models on Microsoft's cloud platform. Having started as a chatbot application, Hugging Face made its fame as a hub for transformer models, a type of deep learning architecture that has been behind many recent advances in artificial intelligence, including large language models like OpenAI GPT-3 and DeepMind's protein-folding model AlphaFold. Large tech companies like Google, Facebook, and Microsoft have been using transformer models for several years. But the past couple of years has seen a growing interest in transformers among smaller companies, including many that don't have in-house machine learning talent.

Last week, Hugging Face announced a new product in collaboration with Microsoft called Hugging Face Endpoints on Azure, which allows users to set up and run thousands of machine learning models on Microsoft's cloud platform. Having started as a chatbot application, Hugging Face made its fame as a hub for transformer models, a type of deep learning architecture that has been behind many recent advances in artificial intelligence, including large language models like OpenAI GPT-3 and DeepMind's protein-folding model AlphaFold. Large tech companies like Google, Facebook, and Microsoft have been using transformer models for several years. But the past couple of years has seen a growing interest in transformers among smaller companies, including many that don't have in-house machine learning talent. This is a great opportunity for companies like Hugging Face, whose vision is to become the GitHub for machine learning.

Fresh off a $100 million funding round, Hugging Face, which provides hosted AI services and a community-driven portal for AI tools and data sets, today announced a new product in collaboration with Microsoft. Called Hugging Face Endpoints on Azure, Hugging Face co-founder and CEO Clément Delangue described it as a way to turn Hugging Face-developed AI models into "scalable production solutions." "The mission of Hugging Face is to democratize good machine learning," Delangue said in a press release. "We're striving to help every developer and organization build high-quality, machine learning-powered applications that have a positive impact on society and businesses. With Hugging Face Endpoints, we've made it simpler than ever to deploy state-of-the-art models, and we can't wait to see what Azure customers will build with them." The demand for AI remains high.