> For the complete documentation index, see [llms.txt](https://ai-docs.fptcloud.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ai-docs.fptcloud.com/other/ai-notebook/overview.md). # Overview {% embed url="" %} ### What is AI Notebook? AI Notebook is a Jupyter-based development environment running on FPT’s AI Factory infrastructure. With one click, you can launch a pre-configured notebook server with GPU/CPU resources and persistent storage. ### How does it work? Each AI Notebook runs in an isolated, containerized environment connected to FPT’s GPU/CPU infrastructure. JupyterLab is used as the main interface for writing, running, and visualizing code in the browser. ### Why AI Notebook? 1. **1-Click Deployment:** Launch a ready-to-use environment without manual setup. 2. **GPU-Accelerated:** Use NVIDIA H100 (80GB VRAM) for compute-intensive training and inference. 3. **Persistent Workspace:** Store datasets, models, and experiments that remain available across sessions. 4. **Granular Pricing:** Resources are billed based on actual usage (CPU, GPU, storage). --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://ai-docs.fptcloud.com/other/ai-notebook/overview.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.