Visualising

Generative AI and chatbots support your learning process by visualising complex concepts with diagrams, mind maps, graphs, and tables. These visual tools help you better understand connections and hierarchies between ideas. You can instruct chatbots to create specific visualisations, such as flowcharts or schematics.

Generating code for visualisations

For instance, chatbots can generate Mermaid code, a programming framework that turns simple text into diagrams and charts. They can also write code to create tables. Some applications include:

flowcharts for processes or algorithms
project timelines for planning
mind maps to organise ideas
graphs to display data

See below for examples from various AI chatbots:

The screenshot features a conversation with an AI model that suggests creating a Mermaid code visual summarizing themes from an article about validity in assessments versus cheating. It displays a flowchart representation of key themes like validity, assessment, and cheating, highlighting their relationships and implications. Below the visual, there's a brief explanation outlining the main points discussed in the article, emphasizing the importance of validity and the complexities involved in maintaining it without compromising accessibility.

Chat interface with user input on the left requesting a flowchart, and AI's response below. On the right, a flowchart visualizes the text-to-image Generative AI process, detailing steps from "Start" to "Generated Image." The URL for the flowchart editor is displayed at the top: https://mermaid.live/edit.

The screenshot shows a conversation with an AI chatbot named Copilot. The user requests a table summarizing different types of Generative AI (GenAI) models, including categories like image-to-image and text-to-image. Copilot responds with a structured table that includes columns for the type of model, its description, and examples. The table lists various models such as Text-to-Text, Text-to-Image, Image-to-Image, and more, with corresponding examples for each type, illustrating the versatility of generative AI technologies.

Chat interface with the AI chatbot Claude on the left, outlining the creation of a pie chart. On the right, a pie chart visualizes the 2023 population distribution of the Benelux countries: Netherlands (59%), Belgium (39%), and Luxembourg (2%).

Example usage

Suppose you ask the chatbot: ‘Generate Mermaid code for a mind map on generative AI with subtopics such as neural networks, data preprocessing, and use cases.’
The chatbot might respond with this code:


```mermaid
  root((Generative AI))
    Neural_Networks
      Convolutional_Networks
      Recurrent_Networks
      Generative_Adversarial_Networks
      Transformer_Models
    Data_Preprocessing
      Data_Collection
      Normalization
      Augmentation
      Cleaning
    Use_Cases
      Artificial_Creation
        Image_Generation
        Sound_Creation
      Natural_Language_Processing
        Chatbots
        Text_Generation
      Game_Development
        Game_AI
        Story_Creation
    Challenges
      Ethical_Questions
      Quality_Control
      Bias_in_Data
```

Some AI chatbots can instantly convert code into a usable display.

You can also use a visualisation tool like MermaidJS turn the code into a usable image.

Other visualisation options

Besides Mermaid, there are other ways to ask chatbots for simple representations:

Simple text request: ‘Provide a brief, bullet-pointed overview of the pros and cons of neural networks.’
Table: ‘Create a table listing the differences between conventional AI and generative AI.’
Graph: ‘Generate a bar chart showing the increase in AI applications over the years.’
Basic diagrams: ‘Draw a simple flowchart of the machine learning process.’

Example table prompt

Question: ‘Create a table that shows the differences between neural networks and conventional algorithms.‘

Feature	Neural networks	Conventional algorithms
data processing	processes large amounts of data	limited to specific tasks
learning	self-learning (deep learning)	predefined rules
flexibility	high, adaptable	limited, specific applications

Example graph prompt

Question: ‘Generate a line chart showing the growth of AI patents between 2010 and 2020.’

GenAI can provide a simple graph description that you can use in software like Excel or online graph tools.

Year    Total Patents
2010    50
2011    75
2012    120
2013    200
2014    320
2015    450
2016    600
2017    750
2018    900
2019    1100
2020    1350

Previous Topic

Back to Course

Next Lesson