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Lightning AI

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description Lightning AI Overview

Lightning AI (formerly PyTorch Lightning) offers a cloud platform built specifically for the PyTorch ecosystem. It provides 'Studios' which are collaborative environments where teams can work on notebooks, train models with scalable compute, and deploy them to production. It bridges the gap between experimental notebook coding and professional MLOps practices.

help Lightning AI FAQ

Is Lightning AI the same thing as PyTorch Lightning?

PyTorch Lightning is the open-source framework for structuring PyTorch training code, while Lightning AI is the company and broader cloud platform around it. Lightning Studios provides hosted development environments for notebooks, training, and deployment.

Can an existing Jupyter notebook run inside a Lightning Studio?

Yes, Studios support notebook-based work alongside terminals, editors, and persistent project files. Existing PyTorch or Jupyter projects may still need dependency and path adjustments when moved into the cloud environment.

Does Lightning AI provide GPUs for model training?

Yes, Studios can use cloud GPU machines for training and experimentation. Available hardware, quotas, and hourly cost depend on the current Lightning AI plan and selected machine.

How does Lightning AI differ from Google Colab?

Colab is centered on hosted notebooks, while Lightning Studios combines notebooks with terminals, development tools, persistent environments, and deployment workflows. The Lightning platform is particularly aligned with PyTorch and the PyTorch Lightning framework.

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