How to launch AI Notebook?
How to launch AI Notebook?
Updated on 05 Nov 2025

Step 1: From the left menu, select AI Notebook. It takes about 1–2 minutes for the notebook to start.

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Step 2: When it’s ready, your browser will automatically open the AI Notebook Launcher. If the pop-up is blocked, click Open AI Notebook to enter the Launcher.

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Launcher Overview

The Launcher is your starting point in JupyterLab. It lets you create new notebooks, open consoles, and select the type of resources (CPU or GPU) to run your work.
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1. Quick Access on the Navigation Bar

  • File Browser
    Your workspace hub for managing files and folders in the AI Notebook environment. Quickly open, rename, delete, or organize your files.

  • Running Kernels / Notebooks
    Displays all active kernels and open notebooks. Use it to monitor sessions, check GPU/CPU usage, and stop idle ones to free resources.

  • Table of Contents
    Gives a structured view of your notebook’s sections. Easily jump between headings without scrolling through long notebooks.

  • GPU Kernel Management
    Controls and monitors GPU kernels. Check GPU allocation/usage status and shut down unused GPU kernels.

  • Extensions Manager
    Lets you extend your AI Notebook with extra tools and integrations. Install, enable, or disable extensions like Git or code formatters to enhance productivity.

2. Notebook and Console Options

Notebook Section
Use this when you want an interactive, code-plus-output environment. Ideal for developing, visualizing, and documenting code with Markdown, charts, and notes.
Choose a new notebook session with different resources:

  • CPU (Free)
  • 1x GPU H100 SXM5
  • 2x GPU H100 SXM5
  • 4x GPU H100 SXM5
  • 8x GPU H100 SXM5

Console Section
Use this when you only need a lightweight, command-line interface to run quick scripts or test snippets — no rich text or visual output.
Start a console session (command line + code execution) with the same resource options.

Other Section
Create additional files like:

  • Text File
  • Markdown File
  • Python File

3. Resource Selection & Pricing Panel

  • Reminder: Disconnect and delete unused runtimes to avoid extra costs.
  • Displays available GPU configurations with details (CPU, RAM, VRAM, cost per hour).