Monday, 25 September 2017

ARTIFICIAL INTELLIGENCE APPLICATIONS- under construction


Source: Artificial Intelligence
https://www.google.com.pk/search?dcr=0&source=hp&q=what+is+artificial+intelligence&oq=what+is+artifiial+&gs_l=psy-ab.1.0.0i10k1l4.4085.13330.0.25082.19.18.0.0.0.0.349.3304.2-14j1.15.0....0...1.1.64.psy-ab..4.15.3296.0..0j0i131k1.0.TGbdCDQNQIc
noun

1.    the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

    Artificial intelligence  https://en.wikipedia.org/wiki/Artificial_intelligence

    COMPLEX SYSTEM TOPICS
   
   Emergence
   Self Organization
   Collective Behavior
   Networks
   Evolution
   Adaptation
   Pattern Formations
   Systems
   Non-linear Dynamics
   Game Theory
  *** 
  Artificial intelligence (AI, also machine intelligence, MI) is intelligence exhibited by machines, rather than humans or other animals (natural intelligence, NI). In computer science, the field of AI research defines itself as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of success at some goal.[1] Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".[2]
 The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, leading to the quip "AI is whatever hasn't been done yet."[3] For instance, optical character recognition is frequently excluded from "artificial intelligence", having become a routine technology.[4] Capabilities generally classified as AI, as of 2017, include successfully understanding human speech,[5] competing at a high level in strategic gamesystems (such as chess and Go[6]), autonomous cars, intelligent routing in content delivery networks, military simulations, and interpreting complex data.

 Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism,[7][8] followed by disappointment and the loss of funding (known as an "AI winter"),[9][10] followed by new approaches, success and renewed funding.[11] For most of its history, AI research has been divided into subfields that often fail to communicate with each other.[12] However, in the early 21st century statistical approaches to machine learning became successful enough to eclipse all other tools, approaches, problems and schools of thought.[11]

 The traditional problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing, perception and the ability to move and manipulate objects.[13] General intelligence is among the field's long-term goals.[14] Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, neural networks and methods based on statistics, probability and economics. The AI field draws upon computer science, mathematics, psychology, linguistics, philosophy, neuroscience, artificial psychology and many others.

 The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it".[15] This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence, issues which have been explored by myth, fiction and philosophy since antiquity.[16] Some people also consider AI a danger to humanity if it progresses unabatedly.[17]
I n 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.[18]

     

Contents

   
·         1History
·         2Goals
o    2.1Reasoning, problem solving
o    2.2Knowledge representation
o    2.3Planning
o    2.4Learning
o    2.5Natural language processing
o    2.6Perception
o    2.7Motion and manipulation
o    2.8Social intelligence
o    2.9Creativity
o    2.10General intelligence
·         3Approaches
o    3.1Cybernetics and brain simulation
o    3.2Symbolic
o    3.3Sub-symbolic
o    3.4Statistical
o    3.5Integrating the approaches
·         4Tools
o    4.1Search and optimization
o    4.2Logic
o    4.3Probabilistic methods for uncertain reasoning
o    4.4Classifiers and statistical learning methods
o    4.5Neural networks
o    4.6Deep feedforward neural networks
o    4.7Deep recurrent neural networks
o    4.8Control theory
o    4.9Languages
o    4.10Evaluating progress
·         5Applications
o    5.1Competitions and prizes
o    5.2Healthcare
o    5.3Automotive
o    5.4Finance
o    5.5Video games
·         6Platforms
o    6.1Partnership on AI
·         7Philosophy and ethics
o    7.1The limits of artificial general intelligence
o    7.2Potential risks and moral reasoning
o    7.3Machine consciousness, sentience and mind
o    7.4Superintelligence
·         8In fiction
·         9See also
·         10Notes
·         11References
o    11.1AI textbooks
o    11.2History of AI
o    11.3Other sources
·         12Further reading
·         13External links

   History

   *** 

   

Reasoning, problem solving


Knowledge representation


Default reasoning and the qualification problem

The breadth of commonsense knowledge
The subsymbolic form of some commonsense knowledge

Planning

Learning

Natural language processing

Perception

Motion and manipulation

Social intelligence

Creativity

General intelligence

Approaches

Cybernetics and brain simulation

Symbolic

Cognitive simulation

Logic-based

Anti-logic or scruffy

Knowledge-based

Sub-symbolic

Embodied intelligence

Computational intelligence and soft computing

Statistical

Integrating the approaches

Intelligent agent paradigm
Agent architectures and cognitive architectures

Tools

Search and optimization

Logic

Probabilistic methods for uncertain reasoning

Classifiers and statistical learning methods

Neural networks


Deep feedforward neural networks

Deep recurrent neural networks

Control theory

Languages

Evaluating progress

Applications

Competitions and prizes

Healthcare

Automotive

Finance

Video games

Platforms

Partnership on AI

Philosophy and ethics

The limits of artificial general intelligence

Alan Turing's "polite convention"
The Dartmouth proposal
Newell and Simon's physical symbol system hypothesis
Gödelian arguments
The artificial brain argument
The AI effect

Potential risks and moral reasoning

Existential risk

Devaluation of humanity

Decrease in demand for human labor

Artificial moral agents

Machine ethics

Malevolent and friendly AI

Machine consciousness, sentience and mind


Consciousness

Computationalism and functionalism

Strong AI hypothesis

Robot rights

Superintelligence[edit]

Technological singularity

Transhumanism

In fiction

See also[edit]

·         Abductive reasoning
·         Case-based reasoning
·         Commonsense reasoning
·         Emergent algorithm
·         Evolutionary computing
·         Glossary of artificial intelligence
·         Machine learning
·         Mathematical optimization
·         Soft computing
·         Swarm intelligence

Notes[edit]

1.     ^ Jump up to:a b

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RISKS OF ARTIFICIAL INTELLIGENCE
PHILOSOPHY OF MIND 
GAME DESIGN ELEMENTS
MAJOR FIELDS OF COMPUTER SCIENCE & CYBERNATICS
EVOLUTIONARY COMPUTATION
EMERGING TECHNOLOGIES
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    Artificial Intelligence (AI):  https://www.techopedia.com/definition/190/artificial-intelligence-ai

      

 Definition - What does Artificial Intelligence (AI) mean?

 Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans. Some of the activities computers with artificial intelligence are designed for include:
  • Speech recognition
  • Learning
  • Planning
  • Problem solving

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 Techopedia explains Artificial Intelligence (AI)

 Artificial intelligence is a branch of computer science that aims to create intelligent machines. It has become an essential part of the technology industry.
 Research associated with artificial intelligence is highly technical and specialized. The core problems of artificial intelligence include programming computers for certain traits such as:
  • Knowledge
  • Reasoning
  • Problem solving
  • Perception
  • Learning
  • Planning
  • Ability to manipulate and move objects
 Knowledge engineering is a core part of AI research. Machines can often act and react like humans only if they have abundant information relating to the world. Artificial intelligence must have access to objects, categories, properties and relations between all of them to implement knowledge engineering. Initiating common sense, reasoning and problem-solving power in machines is a difficult and tedious approach.
 Machine learning is another core part of AI. Learning without any kind of supervision requires an ability to identify patterns in streams of inputs, whereas learning with adequate supervision involves classification and numerical regressions. Classification determines the category an object belongs to and regression deals with obtaining a set of numerical input or output examples, thereby discovering functions enabling the generation of suitable outputs from respective inputs. Mathematical analysis of machine learning algorithms and their performance is a well-defined branch of theoretical computer science often referred to as computational learning theory.
 Machine perception deals with the capability to use sensory inputs to deduce the different aspects of the world, while computer vision is the power to analyze visual inputs with a few sub-problems such as facial, object and gesture recognition.
 Robotics is also a major field related to AI. Robots require intelligence to handle tasks such as object manipulation and navigation, along with sub-problems of localization, motion planning and mapping.
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 ARTIFICIAL INTELLIGENCE OVERVIEW

February 16th, 2010 | Author: Robinhttp://intelligence.worldofcomputing.net/ai-introduction/artificial-intelligence-overview.html#.Wci5h8iGPIU

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WHAT IS ARTIFICIAL INTELLIGENCE?

Artificial Intelligence (AI) is the study and creation of computer systems that can perceive, reason and act. The primary aim of AI is to produce intelligent machines. The intelligence should be exhibited by thinking, making decisions, solving problems, more importantly by learning. AI is an interdisciplinary field that requires knowledge in computer science, linguistics, psychology, biology, philosophy and so on for serious research.
AI can also be defined as the area of computer science that deals with the ways in which computers can be made to perform cognitive functions ascribed to humans. But this definition does not say what functions are performed, to what degree they are performed, or how theses functions are carried out.
AI draws heavily on following domains of study.
1.  Computer Science
2. Cognitive Science
3. Engineering
4. Ethics
5. Linguistics
6. Logic
7.  Mathematics
8. Natural Sciences
9. Philosophy
10.    Physiology
11.     Psychology
12.     Statistics

STRONG ARTIFICIAL INTELLIGENCE

It deals with creation of real intelligence artificially. Strong AI believes that machines can be made sentient or self-aware. There are two types of strong AI: Human-like AI, in which the computer program thinks and reasons to the level of human-being. Non-human-like AI, in which the computer program develops a non-human way of thinking and reasoning.

WEAK ARTIFICIAL INTELLIGENCE

Weak AI does not believe that creating human-level intelligence in machines is possible but AI techniques can be developed to solve many real-life problems. That is, it is the study of mental models implemented on a computer.

AI AND NATURE

Nowadays AI techniques developed with the inspiration from nature is becoming popular. A new area of research what is known as Nature Inspired Computing is emerging. Biological inspired AI approaches such as neural networks and genetic algorithms are already in place.

CHALLENGES

It is true that AI does not yet achieve its ultimate goal. Still AI systems could not defeat even a three year old child on many counts: ability to recognize and remember different objects, adapt to new situations, understand and generate human languages, and so on. The main problem is that we, still could not understand how human mind works, how we learn new things, especially how we learn languages and reproduce them properly.

APPLICATIONS

There are many AI applications that we witness: Robotics, Machine translators, chatbots, voice recognizers to name a few. AI tehniques are used to solve many real life problems. Some kind of robots are helping to find land-mines, searching humans trapped in rubbles due to natural calamities.

FUTURE OF AI

AI is the best field for dreamers to play around. It must be evolved from the thought that making a human-machine is possible. Though many conclude that this is not possible, there is still a lot of research going on in this field to attain the final objective. There are inherent advantages of using computers as they do not get tired or loosing temper and are becoming faster and faster. Only time will say what will be the future of AI: will it attain human-level or above human-level intelligence or not.
References:
Related Articles

RELATED ARTICLES:

1.  History Of Artificial Intelligence
2. Super-Intelligent Machines
3. Machine Learning Overview
4. Expert Systems
Posted in AI-Introduction | Tags: AI, Artificial Intelligence, Introduction

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