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Although machine learning is only one part of the AI field, let me also provide the famous definition of machine learning by Tom Mitchell.

A computer program is said to learn from experience $E$, with respect to some class of tasks $T$ and performance measure $P$ if its performance at tasks in $T$ as measured by $P$ improves with experience $E$

There are other problems and techniques that are part of AI, such as SLAM, constrained optimization, and knowledge bases.

There is no formal definition that most people agree on. Hence here is what I, as a data science / machine learning consultant, think:

Artificial intelligence as a research field is the study of agents which sense and act autonomously in an environment and improve their situation according to some metric with their actions.

I don't like the term, because it is too broad / vague. Instead, look at the definition of machine learning by Tom Mitchell:

A computer program is said to learn from experience 'E', with respect to some class of tasks 'T' and performance measure 'P' if its performance at tasks in 'T' as measured by 'P' improves with experience E

Machine learning is an important part of AI, but not the only one. Search algorithms, SLAM, constrained optimization, knowledge bases and automatic inference are also certainly part of AI.

There is no formal definition that most people agree on. Hence here is what I, as a data science / machine learning consultant, think:

Artificial intelligence as a research field is the study of agents which sense and act autonomously in an environment and improve their situation according to some metric with their actions.

I don't like the term, because it is too broad / vague. Instead, look at the definition of machine learning by Tom Mitchell:

A computer program is said to learn from experience 'E', with respect to some class of tasks 'T' and performance measure 'P' if its performance at tasks in 'T' as measured by 'P' improves with experience E

Machine learning is an important part of AI, but not the only one. Search algorithms, SLAM, constrained optimization, knowledge bases and automatic inference are also certainly part of AI.

Although machine learning is only one part of the AI field, let me also provide the famous definition of machine learning by Tom Mitchell.

A computer program is said to learn from experience $E$, with respect to some class of tasks $T$ and performance measure $P$ if its performance at tasks in $T$ as measured by $P$ improves with experience $E$

There are other problems and techniques that are part of AI, such as SLAM, constrained optimization, and knowledge bases.

There is no formal definition that most people agree on. Hence here is what I, as a data science / machine learning consultant, think:

Artificial intelligence as a research field is the study of intelligent agents which sense and act autonomously in an environment.

I don't like the term, because it is too broad / vague. Instead, look at the definition of machine learning by Tom Mitchell:

A computer program is said to learn from experience 'E', with respect to some class of tasks 'T' and performance measure 'P' if its performance at tasks in 'T' as measured by 'P' improves with experience E

Machine learning is an important part of AI, but not the only one. Search algorithms, SLAM, constrained optimization, knowledge bases and automatic inference are also certainly part of AI.

There is no formal definition that most people agree on. Hence here is what I, as a data science / machine learning consultant, think:

Artificial intelligence as a research field is the study of agents which sense and act autonomously in an environment and improve their situation according to some metric with their actions.

I don't like the term, because it is too broad / vague. Instead, look at the definition of machine learning by Tom Mitchell:

A computer program is said to learn from experience 'E', with respect to some class of tasks 'T' and performance measure 'P' if its performance at tasks in 'T' as measured by 'P' improves with experience E

Machine learning is an important part of AI, but not the only one. Search algorithms, SLAM, constrained optimization, knowledge bases and automatic inference are also certainly part of AI.