The most essential part of the Turing Test is communication. The computer has to be able to communicate with a human. This is called natural language processing.
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In 1950, Alan Turing published his famous paper titled “ Computing Machinery and Intelligence ”. The paper proposed a test to determine if a machine was artificially intelligent. Basically, Turing said that if a machine could have a conversation with a human and trick the human into thinking the machine was a person itself, then it was artificially intelligent. While we still haven’t quite achieved artificial intelligence, natural language processing has become very popular over the past few years and is used in many products today. It’s a fascinating technology that’s already changed the tech world a lot and promises to do so even more in the future. So what makes this bit of technology so exciting?
What is Natural Language Processing?
Natural language processing (NLP) can be defined as the ability of a machine to analyze, understand, and generate human speech. The goal of NLP is to make interactions between computers and humans feel exactly like interactions between humans and humans. And when we say interactions between humans and humans, we’re talking about how humans communicate with each other by using natural language . Natural language is a language that is native to people. English, Spanish, French, and Mandarin are all examples of a natural language. On the other hand, computers have always operated on artificial languages (computer programming languages such as SQL, Java, C++, etc.). These languages were constructed to communicate instructions to machines.
Where do you use NLP in your everyday life?
There are quite a few applications we use everyday that utilize NLP. Listed here are just a few to give a taste of the broad variety of applications.
One of the biggest headaches of email is spam. To set up a first line of defense, services such as Gmail use NLP to determine which emails are good and which are spam. These spam filters scan the text in all the emails you receive, and attempt to understand the meaning of that text to determine if it’s spam or not.
Wouldn’t it be amazing if you could master the stock market without having to do a thing? That’s what algorithmic trading is for. Using NLP, this technology reads news stories concerning companies and stocks and attempts to understand the meaning of them to determine if you should buy, sell, or hold onto certain stocks.
If you’ve ever typed a question in Google search, or asked Siri for directions, then you’ve seen this form of NLP in action. A major use of NLP is to make search engines understand the meaning of what we are asking, and then often times generating natural language in return to give us the answers we’re looking for.
There’s a lot of information on the web, and a lot of that information is in the form of long documents or articles. NLP is used to understand the meaning of this information, and then generates shorter summaries of the information so humans can understand it quicker.