Applications of Generative AI
Class 12 · Artificial Intelligence
7.4 Applications of Generative AI
Generative AI can create new and original content by learning patterns from existing data. It can generate text, images, videos, audio and other forms of digital content.
Generative AI is different from traditional AI systems because it can create new content rather than only analyse existing information or classify data.
7.4.1. Major Applications of Generative AI
| Application | What Generative AI Does | Examples |
|---|---|---|
| Image Generation | Creates new images based on learned patterns and user instructions or prompts. | Canva, DALL-E, Stability AI, Stable Diffusion |
| Text Generation | Generates human-like text such as stories, articles, answers and other written content. | ChatGPT, Perplexity, Google Gemini |
| Video Generation | Creates new video content by learning patterns from existing videos, animations and visual data. | Google Lumiere, Deepfake algorithms |
| Audio Generation | Generates music, sound effects, speech and other forms of audio. | Meta AI Voicebox, Google MusicLM |
1. Image Generation
Generative AI can create new images by learning visual patterns from large collections of existing images. A user can provide a prompt describing the desired image, and the AI generates a new visual based on the learned patterns.
Image generation can be used for creating illustrations, advertisements, educational graphics, concept art and promotional material.
| Tool / Technology | Application |
|---|---|
| Canva | AI-assisted image and visual content creation |
| DALL-E | Image generation from text prompts |
| Stable Diffusion | AI-based image generation |
| Stability AI | Generative AI for visual content |
A teacher can use an image-generation tool to create a visual illustration of the Solar System, a historical scene or a science concept for classroom teaching material.
2. Text Generation
Generative AI can produce human-like text by learning patterns and relationships from large collections of text. It can generate content based on a user's prompt or instruction.
Text generation can be used for writing stories, preparing drafts, generating ideas, answering questions, summarising information and creating other forms of written content.
| Tool | Application |
|---|---|
| ChatGPT | Conversational and creative text generation |
| Google Gemini | Text generation and conversational assistance |
| Perplexity | AI-assisted information and text generation |
A teacher can use Generative AI to prepare a draft lesson plan, generate practice questions, create differentiated learning material or develop a set of competency-based questions for students.
3. Video Generation
Generative AI can create new video content by learning from existing videos, animations and visual effects. It can help produce realistic or creative video sequences based on instructions provided by the user.
Video generation can be used for advertising, education, entertainment, animation and digital storytelling.
| Example | Application |
|---|---|
| Google Lumiere | AI-based video generation |
| Deepfake algorithms | Generation or manipulation of synthetic video content |
AI-generated or manipulated videos can also be misused to create misleading content. This makes responsible use, transparency and ethical considerations important.
4. Audio Generation
Generative AI can create new audio content such as music, sound effects and speech. It learns patterns from existing audio data and uses them to generate new sounds.
| Tool / Technology | Application |
|---|---|
| Meta AI Voicebox | AI-generated speech and audio |
| Google MusicLM | Music generation |
7.4.2. Sector-Specific Applications
Generative AI is being applied across different sectors to automate tasks, create content and provide personalised experiences.
Business and E-Commerce
- Handling customer queries through AI-powered chatbots.
- Providing information about orders, returns and products.
- Creating personalised marketing content.
- Generating dynamic advertisements and promotional material.
Healthcare
- Providing preliminary information and assistance.
- Supporting appointment scheduling and patient interaction.
- Generating synthetic data for training medical AI systems.
- Supporting research involving rare diseases and medical imaging datasets.
Education
- Providing personalised tutoring support.
- Creating customised learning materials.
- Generating practice questions and explanations.
- Supporting teachers in preparing educational resources.
- Assisting with routine administrative tasks.
In a school environment, Generative AI can assist teachers in preparing differentiated worksheets for different learning levels. It can also generate question banks, lesson ideas, summaries and creative classroom resources.
However, the teacher should review the generated content for accuracy, appropriateness, curriculum alignment and academic integrity before using it with students.
Creative Arts
- Brainstorming story and creative ideas.
- Creating visual designs and concept art.
- Generating music and other audio content.
- Creating visualisations for interior design and other creative projects.
7.4.3. Applications of LLMs Beyond Conversation
Large Language Models (LLMs) are primarily associated with Natural Language Processing (NLP), but their capabilities can also support other types of applications.
| Area | Application |
|---|---|
| Text | Story writing, poetry, dialogue generation, summarisation and content creation. |
| Translation | Translating natural language from one language into another. |
| Programming | Translating natural language descriptions into working code. |
| Audio | Supporting text-to-speech applications and generation of natural-sounding speech. |
| Images | Generating image captions and textual descriptions of images. |
| Video | Creating scripts, subtitles and scene summaries. |
7.4.4. Advantages of Generative AI Applications
- Creativity: Helps generate new ideas and creative content.
- Efficiency: Reduces the time required for many content-creation tasks.
- Personalisation: Enables content to be tailored to specific users or audiences.
- Productivity: Assists users in completing writing, design, coding and other tasks more efficiently.
- Accessibility: Can support users through text generation, translation, image descriptions and speech-related applications.
Key Terms
| Term | Meaning |
|---|---|
| Image Generation | Creation of new images using learned visual patterns. |
| Text Generation | Creation of human-like written content. |
| Video Generation | Creation of new video content using learned visual and temporal patterns. |
| Audio Generation | Creation of music, speech and other audio content. |
| Personalisation | Creating content or experiences suited to individual users or groups. |
| LLM | Large Language Model used for a wide range of Natural Language Processing tasks. |
Board Exam & SQP Questions
1. Give examples of applications of Generative AI.
Generative AI can be used for text generation, image generation, video generation and audio generation. Examples include ChatGPT for text generation, DALL-E for image generation and Google MusicLM for music generation.
2. Match the following AI tools with their applications.
| Tool | Application |
|---|---|
| Stable Diffusion | Image Generation |
| ChatGPT | Text Generation |
| Google Lumiere | Video Generation |
| Meta AI Voicebox | Audio Generation |
3. Which of the following is NOT a typical application of Generative AI?
A. Creating original music
B. Crafting promotional videos
C. Analysing sentiment in social media posts
D. Generating story drafts
Answer: C. Analysing sentiment in social media posts
Sentiment analysis is primarily an analytical or discriminative task rather than a content-generation task.
4. How does Generative AI contribute to personalised email campaign content?
Generative AI can analyse relevant customer information and engagement patterns and generate personalised text suited to specific audience segments.
5. What is a significant advantage of using Generative AI for dynamic video advertisements?
It can rapidly generate diverse and innovative video content tailored to different audiences or platforms, reducing the time and effort required for content creation.
6. Identify an application of LLMs beyond simple conversation.
LLMs can translate natural language descriptions into working code, helping streamline software development.
Remember the four major content-generation categories:
Image → Text → Video → Audio
Also remember the key examples:
Stable Diffusion → Image | ChatGPT → Text | Lumiere → Video | Voicebox → Audio
Image Generation: Canva, DALL-E, Stable Diffusion
Text Generation: ChatGPT, Google Gemini, Perplexity
Video Generation: Google Lumiere
Audio Generation: Meta AI Voicebox, Google MusicLM
Key Sectors: Business, Healthcare, Education and Creative Arts