Difference Between AI, Machine Learning, and Deep Learning
Difference Between AI, Machine Learning (ML), and Deep Learning (DL)
Term What It Is How It Works Examples
Artificial Intelligence (AI) The broad field of creating machines that can perform tasks requiring human intelligence. Can be rule-based, logic-driven, or learning-based. Encompasses any technique that enables computers to mimic human intelligence. Chess engines, voice assistants, recommendation systems
Machine Learning (ML) A subset of AI focused on enabling machines to learn patterns from data and improve over time without explicit programming. Algorithms learn from data (examples), build models, and make predictions or decisions. Spam email filters, fraud detection, image classification
Deep Learning (DL) A subset of ML that uses multi-layered neural networks inspired by the brain’s structure to learn from large amounts of data. Neural networks with many layers automatically learn hierarchical features and representations. Facial recognition, speech recognition, GPT language models
Visual analogy:
AI is the whole umbrella — the idea of making machines smart.
ML is one way to achieve AI, by learning from data.
DL is a more advanced, powerful type of ML that uses deep neural networks.
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