How Artificial intelligence will change the future

Everyone is talking about Artificial intelligence (AI).  AI systems are now in routine use in economics, medicine, engineering, and the military, as well as being built into many common home computer software applications, and traditional strategy games like computer chess and other video games. 

What is AI?

Artificial intelligence is exhibited by an artificial entity, a system is generally assumed to be a computer. It includes various advanced systems such as Neural networks, Fuzzy Systems and Evolutionary computation. AI is used in typical problems such as Pattern Recognition, Natural language processing and more. This system is working throughout the world as an artificial brain. 

AI researchers are free to use methods that are not observed in people or that involve much more computing than people can do.

Definition of Artificial

The simple definition of artificial objects that are made or produced by human beings rather than occurring naturally. 

Definition of Intelligence

The simple definition of intelligence is a process of entails a set of skills of problem-solving, enabling to resolve genuine problems or difficulties that encounter and create an effective product must also entail the potential for finding or creating problems and thereby laying the groundwork for the acquisition of new knowledge. 

Artificial Intelligence

Artificial intelligence is a branch of science that deals with helping machines find a solution to complex problems in a more human-like fashion. This generally involves borrowing characteristics from human intelligence and applying them as algorithms in a computer-friendly way. 

AI is mainly concerned with the popular mind with the robotics development, but also the main field of practical application has been as an embedded component in the areas of software development which require computational understandings and modelling such as finance and economics, data mining and physical science. 

History of AI

The intellectual roots of AI, and the concept of intelligent machines, may be found in Greek mythology.  After modern computers became available following World War II, it has become possible to create programs that perform difficult intellectual tasks. 

The first working AI programs were written in 1951 to run on the Ferranti Mark I machine of the University of Manchester (UK). 

The person who finally coined the term artificial intelligence and is regarded as the father of the AL is John McCarthy. 

From the 1990s until the turn of the century, AI has reached some incredible landmarks with the creation of intelligent agents. Intelligent agents use their surrounding environment to solve problems most efficiently and effectively. 

Goals of AI

The deduction, reasoning and problem-solving:- The search for more efficient problem-solving algorithms is a high priority for AI research.

Knowledge representation:- Knowledge representation and knowledge engineering are central to AI research.

Planning: - Intelligent agents must be able to set goals and achieve them.

Natural language processing: - Natural language processing gives machines the ability to read and understand the languages that humans speak.

Motion and manipulation: - The field of robotics is closely related to AI. Intelligence is required for robots to be able to handle such tasks as object manipulation and navigation.

Perception: - Machine perception is the ability to use input from sensors (such as cameras, microphones, sonar and others more exotic).

Social intelligence:- Emotion and social skills play two roles for an intelligent agent.

General intelligence:- Most researchers think that their work will eventually be incorporated into a machine with general intelligence (known as strong AI), combining all the skills above and exceeding human abilities at most or all of them.

 

CATEGORIES OF AI

AI divides roughly into two schools of thought: 

Conventional AI:-

Conventional AI mostly involves methods now classified as machine learning, characterized by formalism and statistical analysis. This is also known as symbolic AI, logical AI, neat AI and Good Old Fashioned Artificial Intelligence (GOFAI).

Computational Intelligence (CI) :-

Computational Intelligence involves iterative development or learning (e.g. parameter tuning e.g. in connectionist systems). Learning is based on empirical data and is associated with non-symbolic AI, scruffy AI and soft computing. 

Typical problems to which AI methods are applied:-

• Pattern recognition
• Optical character recognition
• Handwriting recognition
• Speech recognition
• Face recognition
• Natural language processing, Translation and Chatterbots
• Non-linear control and Robotics
• Computer vision, Virtual reality and Image processing
• Game theory and strategic planning

Other fields in which AI methods are implemented:-

Automation:- Automation is the use of machines, control systems and information technologies to optimize productivity in the production of goods and delivery of services.

Cybernetics:- Cybernetics in some ways is like the science of organisation, with special emphasis on the dynamic nature of the system being organised.

Hybrid intelligent system :- Hybridization of different intelligent systems is an innovative approach to constructing computationally intelligent systems consisting of an artificial neural network, approximate reasoning and derivative-free optimization methods.

Intelligent agent:- In artificial intelligence, an intelligent agent (IA) is an autonomous entity which observes through sensors and acts upon an environment using actuators (i.e. it is an agent) and directs its activity towards achieving goals.

Intelligent control:- Intelligent Control or self-organising/learning control is a new emerging discipline that is designed to deal with problems. Rather than being model based, it is experientially based.

Automated reasoning:-The study of automated reasoning helps produce software that allows computers to reason completely, or nearly completely, automatically. Although automated reasoning is considered a sub-field of artificial intelligence, it also has connections with theoretical computer science and even philosophy.

Data mining:- Data mining (the analysis step of the "Knowledge Discovery in Databases" process, or KDD).  The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use.

Behaviour-based robotics:- Behavior-based robotics is a branch of robotics that bridges artificial intelligence (AI), engineering and cognitive science. 

Developmental robotics:- Developmental Robotics (DevRob), sometimes called epigenetic robotics, is a methodology that uses metaphors from neural development and developmental psychology to develop the mind for autonomous robots.

Evolutionary robotics:- Evolutionary robotics (ER) is a methodology that uses evolutionary computation to develop controllers for autonomous robots.

Chatbot:- Chatterbot, a chatter robot is a type of conversational agent, a computer program designed to simulate an intelligent conversation with one or more human users via auditory or textual methods.

Knowledge Representation:- Knowledge representation (KR) is an area of artificial intelligence research aimed at representing knowledge in symbols to facilitate inferencing from those knowledge elements, creating new elements of knowledge.

Applications of AI

Artificial intelligence has been used in a wide range of fields including medical diagnosis, stock trading, robot control, law, scientific discovery and toys. 

Future scope of AI

• In the next 10 years, technologies in narrow fields such as speech recognition will continue to improve and will reach human levels.
• In 10 years, AI will be able to communicate with humans in unstructured English using text or voice.
• Will recreate some parts of the human (animal) brain in silicon. There are two major projects aiming for human brain stimulation, CCortex and IBM Blue Brain.
• There will be an increasing number of practical applications based on digitally recreated aspects of human intelligence, such as cognition, perception, rehearsal learning, or learning by repetitive practice.
• The development of meaningful artificial intelligence will require that machines acquire some variant of human consciousness.
• Systems that can demonstrate conclusively that they possess self-awareness, language skills, and deep knowledge about the world around them.
•  However, the field of artificial consciousness remains in its infancy.
• The early years of the 21st century should see dramatic strides forward in this area. 

Conclusion

AI systems are now in routine use in various fields such as economics, medicine, engineering and the military, as well as being built into many common home computer software applications, traditional strategy games etc. 

AI is an exciting and rewarding discipline.  AI is branch of  computer  science  that  is  concerned  with  the  automation  of  intelligent  behaviour.  The revised definition of  AI  is  - AI  is  the  study  of  mechanisms  underlying  intelligent  behaviour  through  the  construction  and  evaluation  of  artefacts  that  attempt  to  enact  those  mechanisms. So, it is concluded that it works as an artificial human brain which has an unbelievable artificial thinking power.