Key Concepts - Artificial Intelligence

Artificial Intelligence (AI) refers to machines that mimic human cognitive functions like reasoning, decision-making, and problem-solving.

AI is built on three pillars:

• Learning: The ability to adapt to new situations (generalized learning).
• Reasoning: The ability to choose the best course of action (reasoning ability).
• Problem-solving: The ability to use information to find solutions (problem-solving).

Methods:

• Machine Learning: Trains algorithms to learn from data and improve performance.
• Rule-based systems: Programs machines with specific rules and logic to perform tasks.
• Other techniques: Symbolic AI, logic programming, knowledge representation.

Types of AI:

• Narrow AI (Weak AI): excels at specific tasks (e.g., playing chess).
• Artificial General Intelligence (Strong AI): (hypothetical) replicates human-level intelligence and consciousness.

Machine Learning (ML): A technique for achieving AI through algorithms that learn from data and experience.

Deep Learning: A subset of ML inspired by the structure and function of the human brain.

Image source and in-depth reading at - https://www.stratascratch.com/blog/data-science-vs-machine-learning-vs-deep-learning-the-difference/