Artificial intelligence

As explained in Grokking Machine Learning

Artificial intelligence is the field concerned with computer systems making decisions or solving problems autonomously.

Artificial intelligence (AI) is the broad field of tasks in which a computer makes decisions or solves problems by itself. Systems may mimic human decision-making, evolutionary or genetic processes, or physical processes. section 1.2

AI includes many ways for computers to make decisions:

• Logic and reasoning: solving a problem by examining relevant features and constraints. section 1.2
• Machine learning: a part of AI in which computers make decisions based on data, their form of experience. section 1.2
• Deep learning: a part of machine learning. section 1.2

Everyday AI decisions

Driving a car, finding a route, diagnosing a patient, and recommending a movie all involve computers solving problems or making decisions autonomously. section 1.2

Figure 1.1 Machine learning is a part of artificial intelligence.

Use the hierarchy diagram to see artificial intelligence as the broader category containing machine learning. section 1.2

How Grokking Machine Learning covers it

How deep it goes

Defines AI in plain language, distinguishes it from machine learning, and illustrates its scope with practical applications.

Examples

Uses autonomous driving, route finding, patient diagnosis, movie recommendation, and car-buying decisions as examples.

What you can do after

Evaluate/understand how artificial intelligence differs from machine learning and recognize AI in everyday computer systems.

How it connects

Connects artificial intelligence with machine learning, deep learning, data, logic and reasoning, and autonomous problem solving.

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Related concepts

• machine learningincludes · Machine learning is a field of computational methods in which systems learn patterns or relationships from data to make predictions, decisions, or other outputs.
• code reviewuses · Code review is the systematic examination of source code or proposed changes to identify problems and assess or improve quality.
• large language modelincludes · A large language model is a machine-learning model, typically neural, trained on extensive text data to process and generate language.
• dependencykind of · A software dependency is a component, resource, or prerequisite on which another software component or operation relies to function or proceed.
• generative modelingincludes · Generative modeling is a machine-learning approach that learns patterns or a data distribution to generate new samples resembling the data.
• language modelincludes · A language model is a computational model that represents patterns in linguistic tokens to estimate sequence probabilities and predict or generate language from context.

This explainer was generated by Manning's knowledge graph from the text of Grokking Machine Learning. The section links point to the parts of the book it draws on.