Artificial Intelligence
A broad field of computer science focused on building systems that can perform tasks normally requiring human intelligence, such as understanding language, recognizing patterns, and making decisions.
Why it matters
AI is the umbrella term for everything from spam filters to ChatGPT. Understanding the breadth of the field prevents you from conflating one technique with the whole discipline.
What counts as AI
Artificial intelligence is not one thing. It is a family of technologies that ranges from simple rule-based systems to large neural networks that generate text and images. The common thread is that each system processes input, applies some form of learned or encoded logic, and produces output that would otherwise require a human.
Most of what people call "AI" today is specifically machine learning, and more narrowly, generative AI built on large language models. But the field is much wider than that.
Four functional types
- Predictive AI — forecasts outcomes from historical data. Credit scoring, demand forecasting, recommendation engines.
- Generative AI — creates new content: text, images, code, audio. ChatGPT, Midjourney, GitHub Copilot.
- Analytical AI — finds patterns and anomalies in large datasets. Fraud detection, medical imaging, log analysis.
- Conversational AI — handles natural language dialogue. Virtual assistants, customer support bots, voice interfaces.
A practical framing
Rather than debating philosophical definitions, it helps to ask: what kind of task does this system do? Is it predicting, generating, analyzing, or conversing? That tells you more about what it can and cannot do than the label "AI" alone.