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Artificial intelligence

In computer science, artificial intelligence ( AI), sometimes called machine intelligence , is
intelligence demonstrated by machines , in contrast to the natural intelligence displayed by humans and animals . Leading AI textbooks define the field 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 often used to describe machines (or computers) that mimic “cognitive” functions that humans associate with the human mind , such as “learning” and “problem solving”.
As machines become increasingly capable, tasks considered to require “intelligence” are often removed from the definition of AI, a phenomenon known as the AI effecT A quip in Tesler’s Theorem says “AI is whatever hasn’t been done yet.”  For instance, optical character recognition is frequently excluded from things considered to be AI, 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 , intelligent routing in content delivery networks , and military simulations
Artificial intelligence was founded as an academic discipline in 1955, 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, information engineering, mathematics ,
psychology , linguistics , philosophy, and many other fields.
The field was founded on the assumption 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. These issues 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.

A typical AI analyzes its environment and takes actions that maximize its chance of success. An AI’s intended utility function (or goal) can be simple (“1 if the AI wins a game of Go , 0 otherwise”) or complex (“Do mathematically similar actions to the ones succeeded in the past”). Goals can be explicitly defined or induced. If the AI is programmed for ” reinforcement learning “, goals can be implicitly induced by rewarding some types of behavior or punishing others. [a] Alternatively, an evolutionary system can induce goals by using a ” fitness function ” to mutate and preferentially replicate high-scoring AI systems, similar to how animals evolved to innately desire certain goals such as finding food. Some AI systems, such as nearest-neighbor, instead of reason by analogy, these systems are not generally given goals, except to the degree that goals are implicit in their training data. Such systems can still be benchmarked if the non-goal system is framed as a system whose “goal” is to successfully accomplish its narrow classification task
AI often revolves around the use of algorithms .

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28 Comments

  1. Reply

    cool

  2. Reply

    Nice

  3. Profile photo ofKreator

    Reply

    That’s nice

  4. Reply

    nice info

  5. Reply

    Nice

    • Reply

      Nice

  6. Profile photo ofItz Kvng Twitch

    Reply

    We are in computer age

  7. Reply

    Good information

  8. Reply

    Good

  9. Reply

    This is really good to know

  10. Reply

    Nice

  11. Reply

    Good

  12. Reply

    Good

  13. Reply

    AI is indeed wonderful

  14. Profile photo ofChukwucee

    Reply

    AI will make the world a better place to stay

  15. Reply

    Good

  16. Reply

    Very nice information.

  17. Reply

    Robots behaving like human, nice piece

  18. Reply

    Impressive

  19. Reply

    Interesting

  20. Reply

    Nice one, the world is changing by the day

  21. Reply

    Good article

  22. Reply

    yes

  23. Reply

    Very nice article
    Thanks for sharing

  24. Reply

    Good info

  25. Reply

    Nice article

  26. Reply

    Thanks for sharing this update

  27. Reply

    Cool

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