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Defining AI Terms

Precisely defining artificial intelligence is tricky. John McCarthy proposed that AI is the simulation of human intelligence by machines for the inaugural summer research project in 1956. Others have defined AI as the study of intelligent agents, human or not, that can perceive their environments and take actions to maximize their chances of achieving some goal. Jerry Kaplan wrestles with the question for an entire chapter in his book Artificial Intelligence: What Everyone Needs To Know before giving up on a succinct definition.

Rather than try to define AI precisely, we'll simply differentiate AI's goals and techniques:

Artificial Intelligence, Machine Learning, and Deep Learning

Some people use Artificial Intelligence and Machine Learning interchangeably. In this guide, we'll treat Artificial Intelligence as the broadest term which includes all Machine Learning techniques, and we'll treat Deep Learning as subset of Machine Learning techniques.

While deep learning is deservedly enjoying its moment in the sun, we're particularly excited about ensemble techniques that use a wide variety of machine learning and non-machine learning based approaches to solve problems. Google's AlphaGo program, for instance, uses Monte Carlo tree search in addition to convolutional neural networks (a special type of neural network) to guide the search process. We expect most autonomous driving systems to use traditional search techniques for route planning and deep learning for "safe path detection".

Strong vs weak AI, or narrow vs deep AI

One other distinction you might see as you continue your AI journey is between hard/soft, strong/weak, and deep/narrow AI. All of them basically distinguish between systems that work in a specific domain (soft, weak, narrow) such as vision recognition and language translation with systems that can generalize across many specific problems and continuously learn. Google's DeepMind and OpenAI (in general) are working on hard/strong/deep AI. Google Brain (in general) is working on concrete capabilities that make all Google products better (e.g., better Inbox Smart Replies, better face and object detection in Google Photos, better search results in Google search, etc.).