Introduction :
Intelligence was the development of the General Problem Solver; the General Problem Solver was capable of solving problems such as the Tower of Hanoi.
This development led to the collaborative effort to work on projects that marked the development of the domain of Artificial Intelligence. For example, artificial intelligence was used to develop games such as Chess and develop machines capable of making decisions based on common sense reasoning.
Artificial Intelligence Dropdown :
After the development of intelligent machines such as ELIZA and the General Problem Solver, a drop in the progress of Artificial Intelligence was seen. This drop was basically because Artificial Intelligence was considered to formalize human intelligence with the help of “if-then” statements.
Therefore, problems that can be formalized using the “if-then” were qualified to develop intelligent machines. For example, the chess program Deep Blue developed by IBM is an example of an expert system developed by formalizing the human logic using the “if-then” statement.
The problems that were not formalized using the “if-then” logic fall short of the development of the machines based on Artificial Intelligence. The problems dealing with the interpretation of the data were not successfully replicated using the “if-then” conditions.
Problems requiring data interpretation and using the data interpretation results to achieve desired objectives need rules that were not completely represented using the “if-then” condition. Statistical methods were used to develop machines capable of making decisions using complicated rules represented using the programming construct other than “if-then” programming constructs.
Artificial Intelligence in Use :
The upcoming machines capable of achieving the desired tasks are equipped with Artificial Intelligence. The use of Artificial Intelligence in self-driving vehicles gives glimpses of the future of Artificial Intelligence. Artificial Intelligence algorithms are growing at a fast pace. These algorithms cause the growth of stable AI systems.
AI systems are using Deep Learning techniques to produce quality output. To develop intelligent systems, problems are cracked down into sub-problems. This is done by reasoning, problem-solving, knowledge representation, Planning, Learning, Natural Language Processing, Perception, Motion and manipulation, Social and General Intelligence.
AI algorithms are used to develop reasoning and problem-solving techniques to solve problems faster. The reasoning and problem-solving techniques use a sequential technique to model problems.
Conclusion :
iPhones, Alexa smart speakers, Voice recognition, Image recognition are examples of what Artificial Intelligence can do. Artificial Intelligence systems can process data and use its outcome to make decisions.
Artificial Intelligence algorithms can process large amounts of data and perform tasks in much the same way as humans. Artificial Intelligence is a Computer Science paradigm that works to develop machines that think and make decisions. To do this, algorithms are developed using the
well-established methodologies of Computer Science, Statistical Analysis of data, and principles of mathematics.
Different types of algorithms are developed to develop intelligent systems, such as Classification Algorithms, Regression Algorithms, and Clustering Algorithms. Classification algorithms include the Naïve Bayes algorithm, Decision Tree algorithm, Random Forest algorithm, Support vector algorithm, and k Nearest Neighbours.
Regression algorithm includes linear regression, lasso regression, logistic regression, multivariate regression, and multiple regression algorithms. Clustering algorithm includes K-Means Clustering, Fuzzy algorithms, expectation-maximization algorithm, and hierarchical clustering algorithm.
