artificial intelligence

Artificial intelligence

Artificial intelligence is intelligence displayed by machines, in contrast with the natural intelligence (NI) 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 success at some goal.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”.

Scope of artificial intelligence

The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring “intelligence” are often removed from the definition,

a phenomenon is 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”,

has become a routine technology.Capabilities generally classified as AI as of 2017 include successfully understanding human speech,

competing at a high level in strategic game systems (chess), military simulation and interpreting complex data, including images and videos.

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Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism followed by new approaches,success and renewed funding.

For most of its history, AI research has been divided into subfields that often fail to communicate with each other.

followed by new approaches, success, and renewed funding.  The traditional problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing, perception and the ability to move and manipulate objects.

General intelligence is among the field’s long-term goals.

Many tools are used in AI, including versions of search and mathematical optimization, neural networks and methods based on statistics, probabilities and economics.

The field of AI research was born at a workshop at Dartmouth College in 1956.

The overall research goal of artificial intelligence is to create technology that allows computers and machines to function in an intelligent manner.

The general problem of simulating (or creating) intelligence has been broken down into sub-problems.

These consist of particular traits or capabilities that researchers expect an intelligent system to display.

The traits described below have received the most attention.

Early researchers

Early researchers developed algorithms that imitated step-by-step reasoning that humans use when they solve puzzles or make logical deductions.By the late 1980s and 1990s,

AI research had developed methods for dealing with uncertain or incomplete information, employing concepts from probability and economics.

Human beings ordinarily use fast, intuitive judgments rather than step-by-step deduction that early AI research was able to model.

Knowledge presentation and knowledge engineering are central to AI research.

Among the things that AI needs to represent are: objects, properties, categories and relations between objects; situations, events, states and time.

In classical planning problems, the agent can assume that it is the only system acting in the world, allowing the agent to be certain of the consequences of its actions.

However, if the agent is not the only actor, then it requires that the agent can reason under uncertainty.

This calls for an agent that can not only assess its environment and make predictions,

but also evaluate its predictions and adapt based on its assessment.

A sub-field of AI addresses creativity both theoretically (the philosophical psychological perspective)

practically (the specific implementation of systems that generate novel and useful outputs).

RESULTS of artificial intelligence

Artificial intelligence is breaking into the healthcare industry by assisting doctors.

According to Bloomberg Technology, Microsoft has developed AI to help doctors find the right treatments for cancer.

There is a great amount of research and drugs developed relating to cancer.

for the treatment of cancer, more than 800 medicines and vaccines are available.

because there are too many options to choose from, making it more difficult to choose the right drugs for the patients.

Microsoft is working on a project to develop a machine called “Hanover”.

Its goal is to memorize all the papers necessary to cancer and help predict which combinations of drugs will be most effective for each patient. It plays a vital role in our daily life.



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