Artificial Intelligence

2021 ◽  
pp. 1-16
Author(s):  
Satvik Tripathi
Keyword(s):  
Artificial Intelligence ◽  
Problem Solving ◽  
Human Mind ◽  
Human Intelligence ◽  
Future Prospects ◽  
Technology Advances

Artificial intelligence refers to the replication of human intelligence in machines that are encoded to think like humans and imitate their actions. The word may also be applied to any machine that displays qualities related to a human mind for example understanding, learning, and problem-solving. As technology advances, previous benchmarks that defined artificial intelligence become out-dated. Artificial intelligence has made its way to almost every sector and has resulted in better efficiency of the traditional processes. In this chapter, the author discusses the current applications, future prospects, and possible threats of artificial intelligence.

Artificial Intelligence

2019 ◽  
pp. 13-22
Author(s):  
Steven Walczak
Keyword(s):  
Artificial Intelligence ◽  
Problem Solving ◽  
Future Research ◽  
Human Intelligence ◽  
Research Directions ◽  
Intelligent Machines ◽  
History Of ◽  
Future Research Directions ◽  
New Research

Artificial intelligence is the science of creating intelligent machines. Human intelligence is comprised of numerous pieces of knowledge as well as processes for utilizing this knowledge to solve problems. Artificial intelligence seeks to emulate and surpass human intelligence in problem solving. Current research tends to be focused within narrow, well-defined domains, but new research is looking to expand this to create global intelligence. This chapter seeks to define the various fields that comprise artificial intelligence and look at the history of AI and suggest future research directions.

scholarly journals GLOBAL EVOLUTION AND PROSPECTS HUMAN INTELLIGENCE

2021 ◽  
pp. 42-49
Author(s):  
V. Shapoval
Keyword(s):  
Artificial Intelligence ◽  
Evolutionary Process ◽  
Big Bang ◽  
Human Mind ◽  
Cultural Analysis ◽  
Human Intelligence ◽  
General Direction ◽  
Form Of Life ◽  
Global Evolution ◽  
The Big Bang

There are two opposing equally well-argued views on the emergence and development of all things: either the evolution of the world that led to the emergence of life and intelligence is something natural, or everything happened quite by accident and could have been different. It determines the aim and the tasks which are the emergence of intelligence can be considered as a certain stage of such a naturally unfolding evolutionary process, or it is the result of a coincidence. Research methods are complex and is based on philosophicalanthropological and philosophical-cultural analysis of the problems of global evolutionism and the development of human intelligence in their dialectical unity.The principles of systematicity, objectivity, ascent from the abstract to the concrete, etc. are also used to solve specific research tasks. Research results: Analysis of the process of universal evolutionism shows that the general direction of the development of existence is the movement from the appearance of simple objects to the formation of the highest of the material structures known today, which are the bearer of intelligence in its biological forms. The author argues the position that further evolution, with a high probability, will occur as a transition from intelligence on organic carriers - the human mind - to artificial intelligence based on inorganics. Together or separately from the human mind, artificial intelligence has the ability to give a new impetus to the development of earthly civilization, penetration into deep space and the development of its limitless possibilities.Discussion. Opponents of the concept of global evolutionism were limited to the planetary scale and for the most part considered the universe as a whole infinite and stationary, and therefore devoid of history. However, it is more attractive to think that the development of the biosphere embodies a number of trends that affected long before the formation of the Earth and the solar system, and this direction is focused on creating an integrated theory of the past from the Big Bang to the present. Conclusion. The global evolution of all things moves in the direction from inorganics to organics - in the form of life and mind, and then - again to inorganics - in the form of artificial intelligence. There is a kind of denial of denial, the further steps of which, and even more so, the end result, can only be guessed.

Artificial Intelligence

2018 ◽  
pp. 98-105
Author(s):  
Steven Walczak
Keyword(s):  
Artificial Intelligence ◽  
Problem Solving ◽  
Future Research ◽  
Human Intelligence ◽  
Research Directions ◽  
Intelligent Machines ◽  
History Of ◽  
Future Research Directions ◽  
New Research

Artificial intelligence is the science of creating intelligent machines. Human intelligence is comprised of numerous pieces of knowledge as well as processes for utilizing this knowledge to solve problems. Artificial intelligence seeks to emulate and surpass human intelligence in problem solving. Current research tends to be focused within narrow well-defined domains, but new research is looking to expand this to create global intelligence. This chapter seeks to define the various fields that comprise artificial intelligence and look at the history of AI and suggest future research directions.

scholarly journals Solving a hypothetical chess problem: a comparative analysis of computational methods and human reasoning

2019 ◽  
Vol 11 (1) ◽  
pp. 96-103
Author(s):  
Leo Pasqualini de Andrade ◽  
Augusto Cláudio Santa Brígida Tirado ◽  
Valério Brusamolin ◽  
Mateus Das Neves Gomes
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Development ◽  
Human Mind ◽  
Human Intelligence ◽  
Chess Player ◽  
Problem Situation ◽  
Human Reasoning ◽  
Behavioral Patterns ◽  
Human Thinking ◽  
Short Time

Computational modeling has enabled researchers to simulate tasks which are very often impossible in practice, such as deciphering the working of the human mind, and chess is used by many cognitive scientists as an investigative tool in studies on intelligence, behavioral patterns and cognitive development and rehabilitation. Computer analysis of databases with millions of chess games allows players’ cognitive development to be predicted and their behavioral patterns to be investigated. However, computers are not yet able to solve chess problems in which human intelligence analyzes and evaluates abstractly without the need for many concrete calculations. The aim of this article is to describe and simulate a chess problem situation proposed by the British mathematician Sir Roger Penrose and thus provide an opportunity for a comparative discussion by society of human and artificial intelligence. To this end, a specialist chess computer program, Fritz 12, was used to simulate possible moves for the proposed problem. The program calculated the variations and reached a different result from that an amateur chess player would reach after analyzing the problem for only a short time. New simulation paradigms are needed to understand how abstract human thinking works.

Is artificial intelligence capable of understanding? An analysis based on philosophical hermeneutics

2021 ◽  
pp. 209660832110564
Author(s):  
Jing Wang
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Problem Solving ◽  
Human Intelligence ◽  
Philosophical Hermeneutics ◽  
Empty Shell ◽  
Deep Blue ◽  
Public Resource ◽  
Human Understanding ◽  
The Subject

From Deep Blue to AlphaGo, the rapid advance of artificial intelligence (AI) in the areas of problem solving and deep learning has lent credence to the prospect that it may one day develop an ability for understanding similar to that of humans or even surpass human intelligence. However, understanding is not a piece of knowledge, a method or an ability. Knowledge can be possessed as an impersonal and public resource. In a certain sense, it can be objectified by a group's understanding, which is characterized by certainty, whereas understanding seems to be in a state of constant transformation and movement. Moreover, a method cannot be separated from the subject and is always subsumed by understanding and interpretation. For a method to be useful, it must be the product of understanding and interpretation. Understanding is not enabled by a method; rather, it is understanding that possesses the method. Finally, understanding cannot be described and defined simply as ability. As an important manifestation of human intelligence, understanding is not an empty shell of method filled by its objects, but an appreciation and extension of the meaning of the objects. Computers are good at dealing with simple and formalized activities that are not associated with a context, but the human activities of understanding are not formalized. From the perspective of philosophical hermeneutics, understanding is filled with elements of reflection and in itself is a form of self-understanding. Furthermore, AI lacks the fore-structure of human understanding. Therefore, whether understanding can be viewed from the perspective of historicity is an important difference between human intelligence and AI, and the missing historical connection of computational programs of AI may be an important reason why it cannot acquire understanding in a real sense.

scholarly journals A review article on artificial intelligence

2021 ◽  
Vol 5 (1) ◽  
pp. 013-014
Author(s):  
C Nagendraswamy ◽  
Salis Amogh
Keyword(s):  
Artificial Intelligence ◽  
Problem Solving ◽  
Review Article ◽  
Human Intelligence

Artificial intelligence (AI) is the emulation of human intelligence in computers that have been trained to think and behave like humans. The word may also refer to any computer that exhibits human-like characteristics like learning and problem-solving. Artificial intelligence is intelligence demonstrated by machines, as opposed to natural intelligence, which involves consciousness and emotionality and is demonstrated by humans and animals [1].

Intelligence, Artificial and Otherwise

2019 ◽  
Vol 24 (2) ◽  
pp. 241-258
Author(s):  
Paul Dumouchel
Keyword(s):  
Artificial Intelligence ◽  
Human Intelligence

The idea of artificial intelligence implies the existence of a form of intelligence that is “natural,” or at least not artificial. The problem is that intelligence, whether “natural” or “artificial,” is not well defined: it is hard to say what, exactly, is or constitutes intelligence. This difficulty makes it impossible to measure human intelligence against artificial intelligence on a unique scale. It does not, however, prevent us from comparing them; rather, it changes the sense and meaning of such comparisons. Comparing artificial intelligence with human intelligence could allow us to understand both forms better. This paper thus aims to compare and distinguish these two forms of intelligence, focusing on three issues: forms of embodiment, autonomy and judgment. Doing so, I argue, should enable us to have a better view of the promises and limitations of present-day artificial intelligence, along with its benefits and dangers and the place we should make for it in our culture and society.

Robots as cognitive tools

2002 ◽  
Vol 1 (1) ◽  
pp. 125-143 ◽  
Author(s):  
Rolf Pfeifer
Keyword(s):  
Artificial Intelligence ◽  
Problem Solving ◽  
Main Tool ◽  
Human Cognition ◽  
Abstract Thinking ◽  
Cognitive Tools ◽  
Developmental Robotics ◽  
Information Theoretic ◽  
Natural Forms ◽  
Over Time

Artificial intelligence is by its very nature synthetic, its motto is “Understanding by building”. In the early days of artificial intelligence the focus was on abstract thinking and problem solving. These phenomena could be naturally mapped onto algorithms, which is why originally AI was considered to be part of computer science and the tool was computer programming. Over time, it turned out that this view was too limited to understand natural forms of intelligence and that embodiment must be taken into account. As a consequence the focus changed to systems that are able to autonomously interact with their environment and the main tool became the robot. The “developmental robotics” approach incorporates the major implications of embodiment with regard to what has been and can potentially be learned about human cognition by employing robots as cognitive tools. The use of “robots as cognitive tools” is illustrated in a number of case studies by discussing the major implications of embodiment, which are of a dynamical and information theoretic nature.

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