AI vs Machine Learning vs Deep Learning

Artificial Intelligence  —  Human Intelligence Exhibited by Machines

Artificial Intelligence (AI) is a subfield of computer science, that was created in the 1960s, and it was (is) concerned with solving tasks that are easy for humans, but hard for computers. In particular, a so-called Strong AI would be a system that can do anything a human can (perhaps without purely physical things). This is fairly generic, and includes all kinds of tasks, such as planning, moving around in the world, recognizing objects and sounds, speaking, translating, performing social or business transactions, creative work (making art or poetry), etc.

Machine Learning —  An Approach to Achieve Artificial Intelligence

Artificial Intelligence -> Machine Learning

Machine learning is a set of algorithms that train on a data set to make predictions or take actions in order to optimize some systems. For instance, supervised classification algorithms are used to classify potential clients into good or bad prospects, for loan purposes, based on historical data. The techniques involved, for a given task (e.g. supervised clustering), are varied: naive Bayes, SVM, neural nets, ensembles, association rules, decision trees, logistic regression, or a combination of many.

At a high level, ML generally means algorithms or models that

  1. data: get a lot of (cleaned) data, with human-defined features (e.g. “age”, “height”, “FICO score”, “is this email spam?” etc.)
  2. training: use the data to “tune” the relative importance of each feature
  3. inference: predict something on new data

Deep Learning — A Technique for Implementing Machine Learning

Machine Learning -> Deep Learning

Deep learning is a particular kind of machine learning that achieves great power and flexibility by learning to represent the world as nested hierarchy of concepts, with each concept defined in relation to simpler concepts, and more abstract representations computed in terms of less abstract ones. It is about designing algorithms that can make robots intelligent, such a face recognition techniques used in drones to detect and target terrorists, or pattern recognition / computer vision algorithms to automatically pilot a plane, a train, a boat or a car.

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