Artificial intelligence
Artificial intelligence
- AI is the simulation of human intelligence by computer systems.
- It means a computer doing tasks that normally need human thinking.
- AI is grouped into three levels — only one of which exists today.
Characteristics of AI
- AI systems collect data and the rules for using it.
- They can reason (work things out with the rules) and draw conclusions — which may be approximate (a best guess) or definite.
- They can learn from data and adapt — changing their behaviour as they get new data.
Practice
Artificial intelligence is:
AI is a computer doing tasks that normally need human thinking.
Practice
Which is a characteristic of an AI system?
AI collects data + rules, reasons, draws conclusions, learns and adapts.
Examples and levels of AI
- Examples: expert systems (advice like a human expert, e.g. medical diagnosis), natural language processing, and self-driving cars.
- Narrow AI — does only one task or a small set (e.g. a chess program). All AI today is narrow AI.
- General AI — could do any task a human can. Strong AI — would think and be self-aware like a human mind. Neither exists yet.
Practice
An expert system is AI that:
Expert systems use stored knowledge and rules to advise, like a human specialist.
Practice
Narrow AI:
Narrow AI is task-specific (e.g. chess); general and strong AI do not exist yet.
Practice
Strong AI would:
Strong AI would have human-like awareness — still only theoretical. Today's AI is all narrow.
You've got it
Key idea
- AI = a computer simulating human intelligence
- AI characteristics: collect data + rules, reason, draw conclusions, learn, adapt
- examples: expert systems, NLP, self-driving cars
- narrow (all AI today) → general → strong (self-aware, not yet real)