Here are the top five artificial intelligence applications.
Languages to develop AI applications
|1. Expert System||POP-11, Prolog, LISP|
|2. Dynamic Applications||LISP, Scheme, Dylan|
|3. Computer Vision||C|
|4. Natural Language Systems||Prolog, Oz|
|5. Evolutionary Systems||C, DSLs|
Evolution of Artificial Intelligence
Five examples of AI
1. Expert System
- The definition of Expert system is In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert.
- Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if–then rules rather than through conventional procedural code.
2. Dynamic Applications
- These apps help you take business decisions based on the result provided by AI applications.
- These are called Dynamic applications.
3. Computer Vision
- The applications that work based on Visual applications such as Image application and Video application:
- Computer vision is an interdisciplinary field that deals with how computers can be made for gaining high-level understanding from digital images or videos. From the perspective of engineering, it seeks to automate tasks that the human visual system can do.
4. Natural Language System
- The applications, which are followed by NLP called Natural language Systems. NLP is a way for computers to analyze, understand, and derive meaning from human language in a smart and useful way.
- By utilizing NLP, developers can organize and structure knowledge to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation.
5. Evolutionary System
- Per wiki In computer science, evolutionary computation is a family of algorithms for global optimization inspired by biological evolution, and the subfield of artificial intelligence and soft computing studying these algorithms.
- The best example of an Evolutionary system is an application being researched for machine learning is optimal execution.
- When large trades are executed in the market, it could potentially push prices in an unfavorable direction, so it makes sense that traders are keen on optimizing this cost. So far, most of the interest in applying machine learning technology to reduce trading costs have been from the buy-side.
- Final point is the languages that are most popular in the development of Artificial intelligence applications are LISP, Scheme, Prolog, Erlang, POP-11, Smalltalk. A good book read to understand better on AI applications Artificial Intelligence: A Systems Approach
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