Research Cloud

Accelerating open machine learning research with Cloud TPUs
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Use Cloud TPUs for free, right in your browser

You can access Cloud TPUs for free in your browser using Google Colab. Colab is a Jupyter notebook environment that requires no setup to use.

To get started right away, try one of these TPU-compatible notebook examples:

We’re excited to help researchers and students everywhere expand the machine learning frontier by making Cloud TPUs available for free. Learn more about Cloud TPUs.


1,000 Cloud TPUs for the world's top researchers

Researchers need enormous computational resources to train the machine learning models that have delivered recent advances in medical imaging, speech recognition, game playing, and many other domains. The TensorFlow Research Cloud is a cluster of 1,000 Cloud TPUs that provides the machine learning research community with a total of 180 petaflops of raw compute power — at no charge — to support the next wave of breakthroughs.


Cloud TPUs: Built to train and run ML models

Google’s first-generation TPUs made it dramatically faster to run ML models that had already been trained, but the training had to be performed separately. Google’s second-generation Cloud TPUs are even more powerful, designed from the ground up to accelerate training ML models as well as running them. The TensorFlow Research Cloud provides researchers with access to these second-generation Cloud TPUs, each of which provides 180 teraflops of ML acceleration.


Share the benefits of machine learning with the world

Our goal is to ensure that the most promising researchers in the world have access to enough compute power to imagine, implement, and publish the next wave of ML breakthroughs. We’re setting up a program to accept applications for access to the TensorFlow Research Cloud and will evaluate applications on a rolling basis. The program will be highly selective since demand for ML compute is overwhelming, but we specifically encourage individuals with a wide range of backgrounds, affiliations, and interests to apply. The program will start small and scale up.

Participants in the TFRC program will be expected to share their TFRC-supported research with the world through peer-reviewed publications, open-source code, blog posts, or other means. They should also be willing to share detailed feedback with Google to help us improve the TFRC program and the underlying Cloud TPU platform over time.

Machine learning researchers around the world have done amazing things with the limited computational resources they currently have available. We’d like to empower researchers to think even bigger and tackle exciting new challenges that would be inaccessible otherwise. We hope the TensorFlow Research Cloud will allow people from many different backgrounds to expand the frontier of machine learning research with new discoveries!

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