Unpacking Google/Hugging Face Partnership to Accelerate Gen AI & ML Development  | Tech Weekly
Channel: SiliconANGLE theCUBE
Date: 2024-02-20

In this episode of This Week in Tech, host Shelly Kramer, managing director and principal analyst at theCUBE Research brings together fellow analyst and member of theCUBE Collective community, Jo Peterson, and Google's Bobby Allen and Brandon Royal to talk about the recently announced Google-Hugging Face partnership and what it means for developers.

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This partnership allows developers to train and operate Hugging Face models on Google Cloud infrastructure, which should go a long way toward accelerating generative AI and machine learning development. Even more compelling: developers will be able to build, train and deploy AI models without needing to pay for a Google Cloud subscription. Outside devs using the Hugging Face platform will have cost effective access to Google’s tensor processing units (TPU) and GPU supecomputers, which will include thousands of NVIDIA’s in-demand and export-restricted H100s.

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The core of Hugging Face is the Transformers model library, dataset library and pipelines. Hugging Face has a library of over 495,000 models grouped into data types called modalities. Some of the tasks that customers can perform are object detection, question answering, summarization, text generation, translation and text-to-speech.  

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This is key, as having a toolset like this in a customer’s back pocket allows them to speed time to market and leapfrog the competition.

Google Cloud customers can deploy Hugging Face models within Google Kubernetes Engine and Vertex AI, the company’s machine learning platform offering Gemini, a multimodal platform from Google DeepMind. It’s expected that Vertex AI and GKE will be available on the Hugging Face platform during the first half of 2024.

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