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?
Keep Reading
What is RAG (Retrieval-Augmented Generation) in NLP?
Retrieval-Augmented Generation (RAG) is an approach in NLP that combines retrieval-based methods with generative models
What are some common use cases for Vision-Language Models?
Vision-Language Models (VLMs) are designed to process and understand both visual data, like images or videos, and textua
What is the difference between CHAR and VARCHAR?
CHAR and VARCHAR are both data types used to store string values in databases, but they differ fundamentally in how they