Artificial intelligence: Explained
Artificial intelligence
Artificial intelligence (AI),
sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural
intelligence displayed by humans and other animals. In computer science AI research is defined
as the study of "intelligent agents":
any device that perceives its environment and takes actions that maximize its
chance of successfully achieving its goals. Colloquially, the
term "artificial intelligence" is applied when a machine mimics
"cognitive" functions that humans associate with other human minds, such as "learning" and
"problem solving" The scope of AI is disputed: as machines become
increasingly capable, tasks considered as requiring "intelligence"
are often removed from the definition, a phenomenon known as the AI effect, leading to the quip, "AI is
whatever hasn't been done yet."[ For instance, optical
character recognition is frequently excluded from
"artificial intelligence", having become a routine technology.Modern
machine capabilities generally classified as AI include successfully understanding
human speech, competing at the highest level in strategic game systems (such as chess and Go), autonomously operating cars, and intelligent
routing in content delivery
networks and military simulations.
Artificial intelligence
was founded as an academic discipline in 1956, and in the years since has
experienced several waves of optimism, followed by disappointment and the loss
of funding (known as an "AI winter"), followed
by new approaches, success and renewed funding. For most of its history, AI research
has been divided into sub fields that often fail to communicate with each other. These
sub-fields are based on technical considerations, such as particular goals
(e.g. "robotics" or "machine learning"),the use of particular tools
("logic" or artificial neural
networks), or deep philosophical differences. Sub fields have also
been based on social factors (particular institutions or the work of particular
researchers).[
The traditional problems
(or goals) of AI research include reasoning, knowledge
representation, planning, learning, natural
language processing, perception and
the ability to move and manipulate objects. General
intelligence is among the field's long-term goals. Approaches
include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used
in AI, including versions of search and mathematical optimization, artificial neural
networks, and methods based on statistics, probability and economics.
The AI field draws upon computer science, mathematics, psychology, linguistics, philosophy and many others.
The field was founded on
the claim that human intelligence "can
be so precisely described that a machine can be made to simulate it". This
raises philosophical arguments about the nature of the mind and
the ethics of creating artificial beings endowed with human-like intelligence
which are issues that have been explored by myth, fiction and philosophy since antiquity. Some people also consider AI
to be a danger to
humanity if it progresses unabated. Others believe that AI,
unlike previous technological revolutions, will create a risk of mass
unemployment.[
In the twenty-first
century, AI techniques have experienced a resurgence following concurrent
advances in computer power,
large amounts of data, and theoretical
understanding; and AI techniques have become an essential part of the technology industry,
helping to solve many challenging problems in computer science, software engineering and operations research.
MN (C) 2018
InfoTech Networks Manoj K Wilzon.
Bit :https://en.wikipedia.org/wiki/Artificial_intelligence
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