What is the Artificial Intelligence, Machine Learning, Data Science and what is the difference between them?

What is an artificial intelligence (AI)?

Most of us can not imagine a single day without a computer. With the rapid development of technology, various devices that simplify people's lives become more accessible. This is also connected with modern computers, which are capable of providing impressive fast processing of information.

     Modern business uses the full potential of information technology. This allows you to store important data and manage it effectively. Large firms create their databases, which display employee information and keep records of their employment. Also, it is popular nowadays to work with a computer anywhere on the planet - at home, in the park, in a cafe, and the results are transmitted through the Internet to the employer. It is quite convenient for everyone.

     Other popular devices are artificial intelligence (AI), machine learning (ML), data science (DS). In this article, we want to provide you with the information of its meaning, as they are such technical miracles, that we have to, first of all, study the instructions for their use. After all, many technical workers work on the creation of more advanced devices, household appliances, and computers. And as you know, there is no limit to perfection.

     Artificial intelligence is a section of computer linguistics and computer science that cares for formalizing problems and tasks that resemble cases performed by a person. In most cases, the problem-solving algorithm is not known in advance. There is no exact definition of this science, as philosophy has not solved the question of the nature and status of human intelligence yet. There is no precise criterion for the computer to achieve "reasonableness," although a number of hypotheses were proposed before artificial intelligence, such as the Turing test, or the Newell-Simon hypothesis. Nowadays, there are many approaches to both understanding artificial intelligence and the creation of intelligent systems.

     Artificial intelligence is a system that can operate with knowledge, and the most important, it can learn. First of all, we are talking about recognizing the class of expert systems (the name comes from the fact that they are capable of replacing "on the post" of expert people) with intelligent systems.

     The only answer to the question of what artificial intelligence (AI) cares for does not exist. Almost every author, who writes a book on artificial intelligence, relies on a definition and sees in his light the achievements of this science. Typically, these definitions are reduced to the following:

     - Artificial intelligence studies methods for solving tasks that require human understanding. Its main goal is to teach the AI to solve the intelligence tests. This involves the development of methods for solving tasks by analogy, methods of deduction and induction, the accumulation of basic knowledge and the ability to use them.

     - Artificial intelligence studies methods for solving problems for which there are no solutions, or they are not correct (due to time constraints, memory, etc.). Because of this definition, intelligent algorithms are often used to solve NP-complete tasks, for example, salesman tasks.

     - Artificial intelligence is engaged in the simulation of human higher nervous activity.

Machine learning - what does it mean?

     The term "artificial intelligence" is understood as a specific group of technologies that are sharpened for specific purposes. Such technologies are often called cognitive. The possibilities of their application provoke significant changes in business processes, in many business sectors and our daily lives.

     We want to pay your attention to machine learning, that is related the most to that technology. Machine learning is the algorithms that allow a computer to draw conclusions based on data, without following certain rules. There are two main directions:

  1. Education based on the discovery of regularities in the data.
  2. Training based on the formalization of knowledge of experts and their transfer in the form of a knowledge base.

     The goal of machine learning is the development of algorithms with the ability to reproduce the work of the human brain in analyzing information and in making decisions. The current stage of development of learning algorithms is such that the term "training" is understood as the ability to solve equations on the basis of certain data.

Data Science - what is it?

      Data Science is a set of specific disciplines from different directions, responsible for data analysis and searches for optimal solutions based on them. Previously, only mathematical statistics were involved in this, then they started using machine learning and artificial intelligence, which, as methods of data analysis, added optimization and computer science (that is computer science but in a broader sense).

     It is very important for data scientists to understand what is happening in the subject area (for example, in financial processes, bioinformatics, banking or even in a computer game) in order to answer real questions: what risks accompany this or that company, what sets of genes correspond to a certain disease, how to recognize fraudulent transactions or what behavior of people correspond to players who need to be banned.

     Due to the analysis of large data, it is more efficient to make decisions. This, for example, was shown on the recent election campaigns in the US: while using data-array algorithms, one can capture the mood of the audience and more accurately target advertising messages (which Donald Trump's team probably showed during the campaign).

     The benefit of data analysis can be extracted in areas, where there is enough data. For example, in medicine, algorithms allow better diagnosis of diseases and prescribe a treatment plan.

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Tags: Artificial, computer, data, intelligence, learning, machine, science


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