What is Artificial Intelligence and why it is necessary – Artificial Future

Artificial Intelligence


What is Artificial Intelligence?

Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction. Particular applications of AI include expert systems, speech recognition and machine vision.

Importance of Artificial Intelligence

Artificial Intelligence solve those problems which were difficult to solve before the existence of artificial intelligence. No matter how complex the problem is artificial intelligence provides every possible solution to that problem. Although now we are limited in numbers who can perform this but with the artificial intelligence, we can build thousands of computers (AI) that could all work in unison to solve our greatest and most dire problems. One of the many examples is global warming. Whether we are responsible for this or not, the temperature goes on increasing and we need a way or an idea to slow down the process. For this, we need artificial intelligence which will solve this problem sooner or later. Artificial intelligence can solve the problems much faster than the humans could solve.

Goals of AI

  • AI automates repetitive learning and discovery through data. But AI is different from hardware-driven, robotic automation. Instead of automating manual tasks, AI performs frequent, high-volume, computerized tasks reliably and without fatigue. For this type of automation, human inquiry is still essential to set up the system and ask the right questions.
  • AI adapts through progressive learning algorithms to let the data do the programming. AI finds structure and regularities in data so that the algorithm acquires a skill: The algorithm becomes a classifier or a predicator. So, just as the algorithm can teach itself how to play chess, it can teach itself what product to recommend next online. And the models adapt when given new data. Back propagation is an AI technique that allows the model to adjust, through training and added data, when the first answer is not quite right.

  • AI analyzes more and deeper data using neural networks that have many hidden layers. Building a fraud detection system with five hidden layers was almost impossible a few years ago. All that has changed with incredible computer power and big data. You need lots of data to train deep learning models because they learn directly from the data. The more data you can feed them, the more accurate they become.
  • AI achieves incredible accuracy though deep neural networks – which was previously impossible. For example,  In the medical field, AI techniques from deep learning, image classification and object recognition can now be used to find cancer on MRIs with the same accuracy as highly trained radiologists.

Applications of AI

         AI has been dominant in various fields such as −

  • Gaming − AI plays crucial role in strategic games such as chess, poker, tic-tac-toe, etc., where machine can think of large number of possible positions based on heuristic knowledge.
  • Natural Language Processing − It is possible to interact with the computer that understands natural language spoken by humans.
  • Vision Systems − These systems understand, interpret, and comprehend visual input on the computer. For example,
    • Doctors use clinical expert system to diagnose the patient.
    • Police use computer software that can recognize the face of criminal with the stored portrait made by forensic artist.
  • Speech Recognition − Some intelligent systems are capable of hearing and comprehending the language in terms of sentences and their meanings while a human talks to it. It can handle different accents, slang words, noise in the background, change in human’s noise due to cold, etc.
  • Intelligent Robots − Robots are able to perform the tasks given by a human. They have sensors to detect physical data from the real world such as light, heat, temperature, movement, sound, bump, and pressure. They have efficient processors, multiple sensors and huge memory, to exhibit intelligence. In addition, they are capable of learning from their mistakes and they can adapt to the new environment.

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