How Artificial Intelligence Is Totally Changing Everything | Engineering - HowStuffWorks

Back in Oct. 1950, British techno-visionary Alan Turing published an article called "Computing Machinery and Intelligence," in the journal MIND that raised what at the time must have seemed to many like a science-fiction fantasy, says Patrick Kiger, HowStuffWorks.

Artificial intelligence (AI) is an interdisciplinary science concerned with building smart machines capable of performing tasks that typically require human thought. The implications will change virtually every aspect of our world.
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"May not machines carry out something which ought to be described as thinking but which is very different from what a man does?" Turing asked.

Turing thought that they could. Moreover, he believed, it was possible to create software for a digital computer that enabled it to observe its environment and to learn new things, from playing chess to understanding and speaking a human language. And he thought machines eventually could develop the ability to do that on their own, without human guidance. "We may hope that machines will eventually compete with men in all purely intellectual fields," he predicted.

Nearly 70 years later, Turing's seemingly outlandish vision has become a reality. Artificial intelligence, commonly referred to as AI, gives machines the ability to learn from experience and perform cognitive tasks, the sort of stuff that once only the human brain seemed capable of doing...

AI works by combining large amounts of data with intelligent algorithms — series of instructions — that allow the software to learn from patterns and features of the data, as this SAS primer on artificial intelligence explains.

In simulating the way a brain works, AI utilizes a bunch of different subfields, as the SAS primer notes.

• Machine learning automates analytical model building, to find hidden insights in data without being programmed to look for something in particular or draw a certain conclusion.
• Neural networks imitate the brain's array of interconnected neurons, and relay information between various units to find connections and derive meaning from data.
• Deep learning utilizes really big neural networks and a lot of computing power to find complex patterns in data, for applications such as image and speech recognition.
• Cognitive computing is about creating a "natural, human-like interaction," as SAS puts it, including using the ability to interpret speech and respond to it.
• Computer vision employs pattern recognition and deep learning to understand the content of pictures and videos, and to enable machines to use real-time images to make sense of what's around them.
• Natural language processing involves analyzing and understanding human language and responding to it.

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Source: HowStuffWorks