Artificial Intelligence (AI) is the branch of computer science concerned with making computers behave like humans. The term was coined in 1956 by John McCarthy at the Massachusetts Institute of Technology.
The central goals of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects.
For example, Optical character recognition is no longer perceived as an exemplar of “artificial intelligence”, having become a routine technology. Capabilities currently classified as AI include successfully understanding human speech, competing at a high level in strategic game systems (such as Chess and Go), self-driving cars, and interpreting complex data using synthetic data generation technology.
Artificial Intelligence includes the following areas of specialization:
- Games playing: programming computers to play games against human opponents
Game playing demonstrates several aspects of intelligence, particularly ability to plan (at both immediate tactical-level and long-term strategic level) and the ability to learn.
- Expert systems: programming computers to make decisions in real-life situations (for example, some expert systems help doctors diagnose diseases based on symptoms)
- Natural language: programming computers to understand natural human languages which has given rise to Article generators using this technology
- Neural networks: Systems that simulate intelligence by attempting to reproduce the types of physical connections that occur in animal brains
- Robotics: programming computers to see and hear and react to other sensory stimuli. To do this, they will need to input electronic components into the system by taking a look at tape and reel services here as well as check out other programming components, so everything is done correctly.
Currently, no computers exhibit full artificial intelligence (that is, are able to simulate human behaviour). The greatest advances have occurred in the field of games playing. The best computer chess programs are now capable of beating humans. In May, 1997, an IBM super-computer called Deep Blue defeated world chess champion Gary Kasparov in a chess match.
General intelligence is among the field’s long-term goals. Approaches include
- Statistical methods,
- Computational intelligence,
- Soft computing (e.g. machine learning)
- Traditional symbolic AI.
Many tools are used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics. The AI field draws upon computer science, mathematics, psychology, linguistics, philosophy, neuroscience and artificial psychology.
Applications of artificial intelligence
AI researchers have created many tools to solve the most difficult problems in computer science. Many of their inventions have been adopted by mainstream computer science and are no longer considered a part of AI. the following were originally developed in AI laboratories:
- Time sharing,
- Interactive interpreters,
- Graphical user interfaces and the computer mouse,
- Rapid development environments
- The linked list data structure,
- Automatic storage management
- Symbolic programming
- Functional programming
- Dynamic programming
- Object-oriented programming.
- Financial institutions have long used artificial neural network systems to detect charges or claims outside of the norm, flagging these for human investigation.
- Use of AI in banking can be tracked back to 1987 when Security Pacific National Bank in USA set-up a Fraud Prevention Task force to counter the unauthorised use of debit cards. Apps like Kasisito and Moneystream are using AI in financial services
- Banks use artificial intelligence systems to organize operations, maintain book-keeping, invest in stocks, and manage properties.
- There are also wallets, like Wallet.AI that monitor an individual’s spending habits and provides ways to improve them.
- AI has also reduced fraud and crime by monitoring behavioral patterns of users for any changes or anomalies.
Hospitals and medicine
- Artificial neural networks are used as clinical decision support systems for medical diagnosis, such as in Concept Processing technology in EMR software. (Note: Individuals can learn more about EMR here, if they are not familiar with this software)
- Computer-aided interpretation of medical images. Such systems help scan digital images, e.g. from computed tomography, for typical appearances and to highlight conspicuous sections, such as possible diseases. A typical application is the detection of a tumor.
- Heart sound analysis
- Watson project is another use of AI in this field,a Q/A program that suggest for doctors of cancer patients.
- Companion robots for the care of the elderly
- Mining medical records to provide more useful information
- Design treatment plans
- Assist in repetitive jobs including medication management
- Provide consultations
- Drug creation
- Robots have become common in many industries and are often given jobs that are considered dangerous to humans.
- Robots have proven effective in jobs that are very repetitive which may lead to mistakes or accidents due to a lapse in concentration and other jobs which humans may find degrading.
- In the automotive industry, a sector with particularly high degree of automation, Japan had the highest density of industrial robots in the world.
Online and telephone customer service
- Artificial intelligence is implemented in automated online assistants that can be seen as avatars on web pages.
- A major underlying technology to such systems is natural language processing.
- Pypestream uses automated customer service for its mobile application designed to streamline communication with customers
- Many companies have been progressing quickly in this field with AI.
- Fuzzy logic controllers have been developed for automatic gearboxes in automobiles. For example, the 2006 Audi TT, VW Touareg and VW Caravell feature the DSP transmission which utilizes Fuzzy Logic.A number of koda variants ( koda Fabia) also currently include a Fuzzy Logic-based controller.
- Many telecommunications companies make use of heuristic search in the management of their workforces, for example BT Group has deployed heuristic search in a scheduling application that provides the work schedules of 20,000 engineers.
- Toys and games
- The Digital Revolution, and helped introduce people, especially children, to a life of dealing with various types of Artificial Intelligence, specifically in the form of Tamagotchis and Giga Pets, iPod Touch, the Internet, and the first widely released robot, Furby.
- An improved type of domestic robot was released in the form of Aibo, a robotic dog with intelligent features and autonomy.
- Artificial intelligences can even produce music usable in a medical setting, with Melomics’s effort to use computer-generated music for stress and pain relief.
- At Sony CSL Research Laboratory, their Flow Machines software has created pop songs by learning music styles from a huge database of songs.
- By analyzing unique combinations of styles and optimizing techniques, it can compose in any style.
- The Air Operations Division (AOD) uses AI for the rule based expert systems. The AOD has use for artificial intelligence for surrogate operators for combat and training simulators, mission management aids, support systems for tactical decision making, and post processing of the simulator data into symbolic summaries.
- Multiple aircraft are needed to get good approximations for some calculations so computer simulated pilots are used to gather data.
- These computer simulated pilots are also used to train future air traffic controllers.
News, publishing and writing
- The company Narrative Science makes computer generated news and reports commercially available, including summarizing team sporting events based on statistical data from the game in English.
- Echobox is a software company that helps publishers increase traffic by ‘intelligently’ posting articles on social media platforms such as Facebook and Twitter.
- Boomtrain’s is another example of AI that is designed to learn how to best engage each individual reader with the exact articles.
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