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Artificial Intelligence Definition and examples

Artificial Intelligence Definition And Examples

What is Artificial Intelligence (Al)?

Hollywood films and science fiction novels describe artificial intelligence (AI) as human-like robots that control the world, but artificial intelligence is evolving to provide many benefits in every field of industry, and the current development of artificial intelligence technologies is not scary and allows machines to learn from experience, and adapt to New inputs and doing business like humans.

AI systems exhibit some of the behaviors associated with human intelligence such as planning, learning, thinking, problem-solving, knowledge representation, perception, movement, manipulation, and to a lesser degree social intelligence and creativity.

Why is artificial intelligence important?

AI automates repetitive learning and discovery through data, but it differs from robotic automation. Instead of automating tasks manually, AI performs high-volume repetitive computing tasks reliably and effortlessly. For this type of automation, the human investigation remains necessary to set up the system and roll out The right questions.

AI adds intelligence to existing products. In most cases, AI will not be sold as a single app. Instead, the products you actually use will be enhanced with AI capabilities, such as adding Siri as a feature of a new generation of Apple products. Automation, chat platforms, robots, and smart machines can be combined with large amounts of data to improve many technologies at home and at work, from security intelligence to investment analysis.

Artificial intelligence uses:

Artificial intelligence is everywhere. It tells you what to buy online in the future, to understand what you say to virtual assistants like (Amazon's Alexa) and Apple's Siri, to find out who and what is in an image, and detect spam, or Detect credit card fraud.

Types of artificial intelligence:

As we mentioned, artificial intelligence can be divided into two types: narrow artificial intelligence and artificial general intelligence. Narrow AI is what we see all around us today in computers like, intelligent systems that have been taught how to do specific tasks without being explicitly programmed how to do so.

This type of machine intelligence is evident in speech, the language recognition of the virtual assistant (Siri) on iPhones, in vision-recognition systems found in self-driving cars, as well as in recommendation engines that suggest products you might like based on your previous purchases. Unlike humans, these systems cannot learn how to perform certain tasks, so it is called narrow AI.

Narrow Artificial Intelligence Domains:

There are a large number of emerging applications of narrow AI, such as:

  • Interpreting video feeds from drones as they perform visual inspections of infrastructure such as oil pipelines.
  • Organizing personal and business calendars. Respond to simple customer service inquiries.
  • Coordination with other smart systems to perform tasks such as making a hotel reservation at a suitable time and place.
  • Helping radiologists discover possible tumors on X-rays.
  • Marking inappropriate content online, and many more.

Areas of General Artificial Intelligence:

Artificial general intelligence differs significantly from its predecessor, as it is the type of adaptive intelligence found in humans, and a flexible form of intelligence capable of learning how to perform completely different tasks, from cutting hair to creating spreadsheets, or to interpret a wide range of topics based on its accumulated experience This type of AI is common in movies, such as HAL in 2001 and others, but it does not exist today and AI experts differ a lot about when it becomes a reality.

Artificial Intelligence Definition and examples

The goal of artificial intelligence at the level of semiotics

AI research in semiotics is essentially an interdisciplinary field that brings together insights into the same problem of defining general intelligence from computer science, cognitive science, neuroscience, psychology, and linguistics. Important because the only way a social community can unanimously accept that a machine at any time exhibits intelligent, human-like behavior, albeit outwardly, is for everyone to agree that it does.