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In a recent move to make AI more accessible and democratize good machine learning, Amazon Web Services (AWS) and Hugging Face have announced an expanded collaboration. This joint effort will accelerate the training and deployment of models for generative AI applications.

Huugging Face, the company behind the transformers library for PyTorch, TensorFlow and other architecture, believes that everyone should have easy access to quality machine learning training models. This collaborative effort will provide users with scalable and adjustable models, as well as multiple computing environments for deploying and running models for inference.

Both companies have already been collaborating since 2019. AWS supports Hugging Face’s mission to democratize good machine learning with computing resources and services on Amazon SageMaker, Amazon Elastic Compute Cloud (EC2), and Amazon Elastic Container Service (ECS). On the other hand, Hugging Face provides expertise in deep learning, NLP and AI, as well as its growing library of models.

The extended collaboration makes it easier for developers, data scientists, and researchers to quickly experiment and build machine learning models. This promises to speed up the process and make AI accessible to more people.

As Hugging Face CEO, Thomas Wolf, puts it, “We can’t all be experts in the field of machine learning. However, Hugging Face and AWS’s mission is to make AI accessible and easily understandable to any expert or everyday user. We are confident that this collaboration will ensure AI is available to everyone.”

The extended partnership between AWS and Hugging Face could be a game-changer for the AI industry. It could lead to advances like never seen before, as AI will no longer be a technology easily accessible only to expert users, but a tool anyone can use.