Artificial Intelligence Sub-fields

Artificial Intelligence (AI) is a broad field that contains many different sub-disciplines and approaches. Some standard divisions within AI include:

Machine Learning This type of AI allows systems to learn and improve from data without being explicitly programmed. Machine learning techniques include supervised learning, unsupervised learning, and reinforcement learning.

Deep Learning or Neural Networks: This is one if not the most popular sub fields of AI. Inspired by the structure and function of the human brain, Neural Networks process information using interconnected layers of nodes. Neural networks are used for a wide range of tasks, such as image recognition, natural language processing, and game playing.
Reinforcement Learning: Reinforcement learning is a type of machine learning in which the computer learns by taking actions in an environment and receiving rewards or penalties for those actions.

Natural Language Processing (NLP): This is the study of how computers can understand and generate human language, such as speech recognition, translations, and machine translation. NLP techniques are used to understand and generate human languages.

Computer Vision (CV): This is the study of how computers can interpret and understand visual data, such as images and videos. Computer vision techniques are used in object recognition, image segmentation, and facial recognition.

Robotics: This is the study of how to design and control robots, which are machines that can mimic human actions and behavior. Robotic techniques are used to control robots’ movement and sense and develop intelligent behaviors for them.

Expert Systems: These are computer programs that mimic the decision-making abilities of human experts in a specific field. They use knowledge and rule-based systems to solve complex problems and make decisions.

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