Jupyter is the open source project on which Colab is based. Colab allows you to use and share Jupyter notebooks with others without having to download, install, or run anything.

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Google Colab is a free, browser-based product from Google Research. It allows users to create, edit, and share Jupyter notebook .ipynb files without any intallation or set up. Colab notebooks allow you to combine executable code and rich text in a single document, along with images, HTML, LaTeX and more. You can easily share your Colab notebooks with co-workers or friends, allowing them to comment on your notebooks or even edit them. 


One of the biggest advantages of Colab is the ability to tap into the power of hardware accelerators such as GPUs and TPUs. You can not choose which accelerator you connect to, but they often include Nvidia K80s, T4s, P4s and P100s. 


While this is pretty impressive for a free product, the resources available fluctuate in accommodation with demand. This means that you can not guarantee the computing power you will have access to each time you use Colab. Those looking for more reliable options will have to look towards paid options, such as Colab pro. 


Colab notebooks are stored in Google Drive and can be shared just like any other Google document. 

Google Colaboratory

https://research.google.com/colaboratory/faq.html#resource-limits

Google Colab FAQ

What is the difference Jupyter and Google Colab then?

Google Colab allows for easy access to data within the Google suite. 

- Local files
- Google Drive
- Google Sheets

Working with External Data within Colab

A type of prompt directed at a language model to perform a code completion task. The example, 'Complete the rest of the sequence, making sure that the parentheses are closed properly. Input: [ {', tests the model's ability to understand natural language instructions and apply knowledge of formal syntax, such as that of JSON, to generate a correct continuation.

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