What is pattern?
Artificial Intelligence (AI) is a branch of computer science that creates machines or software that can think, learn, and make decisions similar to humans. Instead of following strict, pre‑written instructions, AI systems use data and algorithms to recognize patterns, solve problems, and improve over time.
Let's break it down
- Data: The raw information AI learns from (pictures, text, numbers, etc.).
- Algorithms: Step‑by‑step formulas that tell the computer how to process data.
- Models: The result of training an algorithm on data; it’s what actually makes predictions or decisions.
- Training: Feeding data into the algorithm so the model can learn the right patterns.
- Inference: Using the trained model to answer new questions or perform tasks.
Why does it matter?
AI can handle huge amounts of information far faster than a person, spotting trends or making predictions that would be impossible manually. This helps businesses save time, doctors diagnose diseases earlier, and everyday devices become smarter and more helpful.
Where is it used?
- Voice assistants (e.g., Siri, Alexa)
- Recommendation engines (Netflix, Amazon)
- Image and speech recognition (photo tagging, transcription)
- Autonomous vehicles
- Fraud detection in banking
- Personalised marketing and chatbots
Good things about it
- Increases efficiency and reduces repetitive work.
- Enables new products and services that weren’t possible before.
- Can improve accuracy in fields like healthcare and finance.
- Helps make data‑driven decisions quickly.
Not-so-good things
- Requires large amounts of data, which can raise privacy concerns.
- Can be biased if the training data is biased, leading to unfair outcomes.
- Complex models are often “black boxes,” making it hard to understand how decisions are made.
- High development costs and need for specialized talent.