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1. Introduction to Artificial Intelligence

Getting Started

What is Artificial Intelligence?

Artificial Intelligence (AI) is the simulation of human intelligence by machines, particularly computer systems. It encompasses learning (acquiring knowledge), reasoning (using knowledge to draw conclusions), problem-solving, perception, and language understanding.

John McCarthy, who coined the term in 1956, defined AI as "the science and engineering of making intelligent machines."

Goals of AI

Approaches to AI

AI vs Machine Learning vs Deep Learning

AI is the broad field. Machine Learning is a subset of AI where systems learn from data. Deep Learning is a subset of ML using multi-layered neural networks. Think of it as concentric circles: AI ⊃ ML ⊃ Deep Learning.

Why AI Now?

Three factors converged: massive data availability, powerful computing (GPUs/TPUs), and algorithmic breakthroughs (transformers, backpropagation, attention mechanisms). These have driven rapid advances in image recognition, natural language processing, and generative AI.

Practice Task: Identify 5 examples of AI you interact with daily (e.g., virtual assistants, recommendation systems, email spam filters). For each, classify which AI approach it likely uses (symbolic, connectionist, statistical, or hybrid). Write a one-paragraph definition of AI in your own words.