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Narrow AI: AI designed for one specific task (like facial recognition).General AI: A theoretical AI that could do anything a human can do.
Garbage In, Garbage Out: If the training data is bad or biased, the AI’s output will be too.
Basic Terminology in AI
1. Artificial Intelligence (AI)
The “umbrella” term. It refers to the broad concept of machines being programmed to simulate human intelligence, performing tasks such as reasoning, problem-solving, and understanding language.
2. Machine Learning (ML)
A subfield of AI. Instead of a human writing specific rules for every scenario, we give the computer data and let it “learn” the patterns on its own.
Think of it this way: Traditional programming is like giving someone a recipe. Machine Learning is like giving someone 1,000 photos of cake and letting them figure out the recipe on their own.
3. Deep Learning (DL)
A specialised type of Machine Learning inspired by the structure of the human brain. It uses Neural Networks with many layers (hence “deep”) to process complex data like photos, voice, and text.
4. Neural Networks
The “engine” of Deep Learning. These are software systems consisting of interconnected nodes (neurons) that process information. They are designed to mimic how biological neurons fire in our brains to recognize patterns.
5. Algorithms
In AI, an algorithm is essentially a set of mathematical instructions or a “logic flow” that tells the AI how to process data to conclude.
6. Large Language Model (LLM)
This is the tech behind tools like me! An LLM is a type of AI trained on massive amounts of text data. It predicts the next most likely word in a sequence, allowing it to “converse” and generate human-like writing.
7. Training Data
The “textbook” for an AI. To teach an AI to identify a cat, you have to show it thousands of images of cats. That collection of images is the training data.
8. Generative AI (GenAI)
The current “buzzy” category of AI. While older AI was mostly used to analyze or classify data, Generative AI can create new content—like images, music, code, or essays.
Quick Comparison Table
Term
Scope
Real-World Example
AI
The broad field
A self-driving car system
ML
Learning from data
Netflix suggesting a movie you’ll like
DL
Complex pattern recognition
Google Translate converting speech in real-time
GenAI
Creating new content
Creating a digital painting from a text prompt
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