Artificial Intelligence Fundamentals
What Is Artificial Intelligence?
Artificial Intelligence is the field of building machines that perform tasks requiring human-like intelligence: recognising images, understanding language, making predictions and decisions. The term was coined at the Dartmouth workshop in 1956, and the field has cycled through waves of excitement and 'AI winters' before the current boom.
Key Concepts
- AI is a broad field; machine learning is its most successful branch, and deep learning is a branch of machine learning
- Narrow AI does one task well (spam filters, chess engines); general AI — matching humans across all tasks — does not yet exist
- AI is already everywhere: search ranking, photo tagging, voice assistants, fraud detection, medical imaging
- Modern AI progress is driven by three ingredients: big data, powerful hardware (GPUs) and better algorithms
- The Turing Test asks whether a machine's conversation is indistinguishable from a human's
In Practice
A useful mental model: traditional software follows rules written by programmers, while AI systems learn patterns from examples. This single distinction explains most of what makes AI both powerful and unpredictable.
Try It Yourself
List five apps you used today and identify which ones use AI, and for what task (recommendation, recognition, prediction). Write one sentence per app.
Lessons
▶️ 1. What Is Artificial Intelligence?
▶️ 2. How Machines Learn from Data
▶️ 3. Types of Machine Learning
▶️ 4. Neural Networks and Deep Learning
▶️ 5. Generative AI and Large Language Models
▶️ 6. AI Ethics, Risks and the Future
▶️ 7. AI in Everyday Nepal: Applications…
▶️ 8. How AI Projects Succeed and Fail
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