Artificial Intelligence (AI) is the broader concept of machines being able to perform tasks that typically require human intelligence, such as reasoning, problem-solving, and decision-making. Machine Learning (ML) is a subset of AI that focuses on training systems to learn patterns from data without being explicitly programmed. AI encompasses a wide range of techniques and applications, including rule-based systems, robotics, and expert systems. For example, a chess-playing program that follows predefined strategies can be considered AI even if it does not use machine learning. ML, in contrast, uses algorithms to learn from data. For example, a machine learning model can be trained to classify emails as spam or not spam based on historical data. While all ML is AI, not all AI involves ML; AI can also include techniques beyond learning from data.
What is the difference between AI and Machine Learning?
- AI & Machine Learning
- Retrieval Augmented Generation (RAG) 101
- Evaluating Your RAG Applications: Methods and Metrics
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- Natural Language Processing (NLP) Advanced Guide
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