Capítulo 6. Crea mapas conceptuales complejos en 10 segundos con Inteligencia Artificial.

How to Create Concept Maps Using Artificial Intelligence

Introduction to the Process

• The session focuses on creating concept maps using artificial intelligence, outlining the process that will be followed.

• Users can start with either a text or an image that they want to convert into a concept map.

Steps for Conversion

• If starting with text, it is directly inputted into ChatGPT. For images, they must first be converted to text before being processed by ChatGPT.

• After inputting the text or transformed image into ChatGPT, it generates code that represents the concept map.

Finalizing the Concept Map

• The generated code is then copied and pasted into a specific website designed to create diagrams from such code.

• The goal of this process is to effectively create a visual representation of concepts through a structured flow.

Example Walkthrough

• An example begins with an image explaining artificial intelligence and its components, including machine learning and deep learning.

• Key areas within AI are identified: machine learning, deep learning, discriminative models, generative models, and natural language processing programs like ChatGPT.

Image Transformation Process

• To convert an image into text, the presenter uses ChatGPT by asking it to explain the image in simple terms suitable for a child.

• The output describes AI as akin to a large computer brain capable of learning various concepts related to machine learning and deep learning.

Utilizing GPT Agents for Mapping

• Once the text is ready, it is introduced not just into any version of ChatGPT but specifically into an agent designed for creating concept maps.

• The presenter navigates through GPT's application marketplace looking for tools specifically aimed at generating concept maps.

Generating Code for Visualization

• After selecting an appropriate agent (Markmap), users paste their prepared text which prompts them about their preferred format (e.g., Markmap or Mermaid).

Charting Tool Overview

Introduction to Mermade

• The presenter introduces the charting tool, Mermade, and provides a link to access it: merm.js.org.

• Users are guided to create a new diagram using Mermade, emphasizing that the initial screen may appear empty.

Code Generation and Error Handling

• The presenter demonstrates how Mermade generates code automatically for the user’s input.

• In case of errors during code generation, users are encouraged to copy the error message and seek solutions from ChatGPT or similar tools.

Creating Concept Maps

• After resolving errors, users can successfully create a conceptual map that includes topics like Artificial Intelligence, Machine Learning, Deep Learning, and Natural Language Generative Models.

Saving and Sharing Diagrams

• To save diagrams in Mermade, users must click on "Save Diagram," which allows them to store their work securely.

• Users need to be logged in (e.g., with Google account) to share their diagrams. They can copy an SVG link for sharing purposes.

Recap of Steps Taken