Hugging Face and AWS Partner

The A.I. arms race in the Cloud feels a bit like picking sides here.

Photo by José Ramos on Unsplash

Hey Everyone,

The Cloud race of A.I. startup affiliating is heating up in 2023. AWS already got Stability.AI late last year, now it’s the turn of Hugging Face. This is actually a bigger deal than people realize.

Just as BingAI moved fast and is breaking things for Microsoft’s brand reputation with their $13 Billion partnership with OpenAI, Google Cloud and AWS are keeping up with Azure in their own ways.

Hugging Face is a huge hub for all things machine learning as you know. Amazon Web Services (AWS), the cloud computing arm of Amazon.com Inc, on Tuesday said it is collaborating with startup Hugging Face, a software development hub, to make it easier to carry out artificial intelligence work (AI) in Amazon's cloud.

Hugging Face is one of the most AI-native startups around. Think about it, Hugging Face, Inc. is an American company that develops tools for building applications using machine learning. It is most notable for its Transformers library built for natural language processing applications and its platform that allows users to share machine learning models and datasets.

Of course Hugging Face is using the “democratizing AI” card in how they pitch this. They said:

There have been significant advances in new Transformer and Diffuser machine learning models that process and generate text, audio, and images. However, most of these popular generative AI models are not publicly available, widening the gap of machine learning capabilities between the largest tech companies and everyone else.

If you go with a Cloud partner, it’s not all accessibility and democratization. But it sounds great on paper.

AWS and Hugging Face are partnering to contribute next-generation models to the global AI community and democratize machine learning. Through the strategic partnership, Hugging Face will leverage AWS as a preferred cloud provider so developers in Hugging Face’s community can access AWS’s state-of-the-art tools (e.g., Amazon SageMaker, AWS Trainium, AWS Inferentia) to train, fine-tune, and deploy models on AWS.