In computer science, the term artificial intelligence (AI) refers to any human-like intelligence exhibited by a computer, robot, or another machine. In popular usage, artificial intelligence refers to the ability of a computer or machine to mimic the capabilities of the human mind — learning from examples and experience, recognizing objects, understanding and responding to language, making decisions, solving problems — and combining these and other capabilities to perform functions a human might perform, such as greeting a hotel guest or driving a car.
After decades of being relegated to science fiction, today, AI is part of our everyday lives. The surge in AI development is made possible by the sudden availability of large amounts of data and the corresponding development and wide availability of computer systems that can process all that data faster and more accurately than humans can. AI is completing our words as we type them, providing driving directions when we ask, vacuuming our floors, and recommending what we should buy or binge-watch next. And it’s driving applications — such as medical image analysis — that help skilled professionals do important work faster and with greater success.
It was in the mid-1950s that McCarthy coined the term “Artificial Intelligence” which he would define as “the science and engineering of making intelligent machines”.
As common as artificial intelligence is today, understanding AI and AI terminology can be difficult because many of the terms are used interchangeably; and while they are actually interchangeable in some cases, they aren’t in other cases. What’s the difference between artificial intelligence and machine learning? Between machine learning and deep learning? Between speech recognition and natural language processing? Between weak AI and strong AI? This article will try to help you sort through these and other terms and understand the basics of how AI works.
Artificial intelligence, machine learning, and deep learning
The easiest way to understand the relationship between artificial intelligence (AI), machine learning, and deep learning is as follows:
Think of artificial intelligence as the entire universe of computing technology that exhibits anything remotely resembling human intelligence. AI systems can include anything from an expert system — a problem-solving application that makes decisions based on complex rules or if/then logic — to something like the equivalent of the fictional Pixar character Wall-E, a computer that develops intelligence, free will, and emotions of a human being.
- Machine learning is a subset of AI application that learns by itself. It actually reprograms itself, as it digests more data, to perform the specific task it’s designed to perform with increasingly greater accuracy.
- Deep learning is a subset of machine learning application that teaches itself to perform a specific task with increasingly greater accuracy, without human intervention.
Another usage of artificial intelligence is related to Improve Industrial processes and Production.
Rampco Machine Learning Software develop a data-driven Machine Learning (ML) model that can use past actual production input parameters and their corresponding output parameters to estimate the system output based on its inputs.
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