What Is Artificial Intelligence? Definition, Uses, and Types

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18 Jan 2024

What Is Artificial Intelligence? Definition, Uses, and Types

Ditulis oleh Coursera Staff • Diperbarui pada 30 Nov 2023

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Learn what artificial intelligence actually is, how it’s used today, and what it may do in the future.
Artificial intelligence (AI) refers to computer systems capable of performing complex tasks that historically only a human could do, such as reasoning, making decisions, or solving problems.
Today, the term “AI” describes a wide range of technologies that power many of the services and goods we use every day – from apps that recommend tv shows to chatbots that provide customer support in real time. But do all of these really constitute artificial intelligence as most of us envision it? And if not, then why do we use the term so often?
In this article, you’ll learn more about artificial intelligence, what it actually does, and different types of it. In the end, you’ll also learn about some of its benefits and dangers and explore flexible courses that can help you expand your knowledge of AI even further.
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What is artificial intelligence?

Artificial intelligence (AI) is the theory and development of computer systems capable of performing tasks that historically required human intelligence, such as recognizing speech, making decisions, and identifying patterns. AI is an umbrella term that encompasses a wide variety of technologies, including machine learning, deep learning, and natural language processing (NLP).
Although the term is commonly used to describe a range of different technologies in use today, many disagree on whether these actually constitute artificial intelligence. Instead, some argue that much of the technology used in the real world today actually constitutes highly advanced machine learning that is simply a first step towards true artificial intelligence, or “general artificial intelligence” (GAI).
Yet, despite the many philosophical disagreements over whether “true” intelligent machines actually exist, when most people use the term AI today, they’re referring to a suite of machine learning-powered technologies, such as Chat GPT or computer vision, that enable machines to perform tasks that previously only humans can do like generating written content, steering a car, or analyzing data.

Artificial intelligence examples

Though the humanoid robots often associated with AI (think Star Trek: The Next Generation’s Data or Terminator’s T-800) don’t exist yet, you’ve likely interacted with machine learning-powered services or devices many times before.
At the simplest level, machine learning uses algorithms trained on data sets to create machine learning models that allow computer systems to perform tasks like making song recommendations, identifying the fastest way to travel to a destination, or translating text from one language to another. Some of the most common examples of AI in use today include:

ChatGPT: Uses large language models (LLMs) to generate text in response to questions or comments posed to it.
Google Translate: Uses deep learning algorithms to translate text from one language to another.
Netflix: Uses machine learning algorithms to create personalized recommendation engines for users based on their previous viewing history.
Tesla: Uses computer vision to power self-driving features on their cars.

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AI in the workforce

Artificial intelligence is prevalent across many industries. Automating tasks that don't require human intervention saves money and time, and can reduce the risk of human error. Here are a couple of ways AI could be employed in different industries:

Finance industry. Fraud detection is a notable use case for AI in the finance industry. AI's capability to analyze large amounts of data enables it to detect anomalies or patterns that signal fraudulent behavior.
Health care industry. AI-powered robotics could support surgeries close to highly delicate organs or tissue to mitigate blood loss or risk of infection.

What is artificial general intelligence (AGI)?

Artificial general intelligence (AGI) refers to a theoretical state in which computer systems will be able to achieve or exceed human intelligence. In other words, AGI is “true” artificial intelligence as depicted in countless science fiction novels, television shows, movies, and comics.
As for the precise meaning of “AI” itself, researchers don’t quite agree on how we would recognize “true” artificial general intelligence when it appears. However, the most famous approach to identifying whether a machine is intelligent or not is known as the Turing Test or Imitation Game, an experiment that was first outlined by influential mathematician, computer scientist, and cryptanalyst Alan Turing in a 1950 paper on computer intelligence. There, Turing described a three-player game in which a human “interrogator” is asked to communicate via text with another human and a machine and judge who composed each response. If the interrogator cannot reliably identify the human, then Turing says the machine can be said to be intelligent [1].
To complicate matters, researchers and philosophers also can’t quite agree whether we’re beginning to achieve AGI, if it’s still far off, or just totally impossible. For example, while a recent paper from Microsoft Research and OpenAI argues that Chat GPT-4 is an early form of AGI, many other researchers are skeptical of these claims and argue that they were just made for publicity [2, 3].
Regardless of how far we are from achieving AGI, you can assume that when someone uses the term artificial general intelligence, they’re referring to the kind of sentient computer programs and machines that are commonly found in popular science fiction.
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Strong AI vs. Weak AI

When researching artificial intelligence, you might have come across the terms “strong” and “weak” AI. Though these terms might seem confusing, you likely already have a sense of what they mean.
Strong AI is essentially AI that is capable of human-level, general intelligence. In other words, it’s just another way to say “artificial general intelligence.”
Weak AI, meanwhile, refers to the narrow use of widely available AI technology, like machine learning or deep learning, to perform very specifi