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Computer vision enables machines to interpret, analyse, and pull meaningful data from images
and videos, replicating human sight. It makes use of cameras, sensors, and data from images
and videos. For instance, self-driving cars use cameras to detect traffic and sensors to measure
the distance between vehicles and other objects on the road.
Some examples of Computer Vision are as follows:
• Facial recognition unlocks smartphones and tags people in photos.

• Self-driving cars use cameras to detect roads, signs, and obstacles.
• AI analyses X-rays and scans to help doctors detect diseases.
• Retail stores use cameras to identify products for automated checkout.

Natural Language Processing (NLP)

NLP is a branch of AI that helps machines understand, translate, and respond to human
language like humans’ speech and words. In short, it allows machines to speak and read like us.
Some examples of Natural Language Processing in real life are:
• Voice assistants like Siri and Alexa responding to
questions such as “What is the weather today?”.
• Chatbots on platforms like Amazon answering

queries like “I need help with my order.”.
• Google Translate using NLP to accurately translate
text into a chosen language.
• Email services using NLP to filter messages into categories like spam based on the language
used.

Activity

How We Speak – Through the Lens of AI
Objective: To help students reflect on their speaking habits and understand how AI systems
process and learn from human language.
Instructions: Each student will think about a conversation they had today and answer the
following questions:
1. What was your intention in that conversation? (e.g., request, question, argument,
appreciation)

2. Did you use clear and complete sentences, or more casual and broken phrases?

3. How often did you use filler words? (like "um", "you know", "like", etc.)

4. Did your tone change based on the person you were talking to? (e.g., polite with a
teacher, casual with a friend)

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