Artificial Intelligence (AI) PDF

Artificial Intelligence (AI) What is Artificial Intelligence (AI)? Artificial intelligenc e (AI) is the field of computer scienc e dedicated to developing intelligent machines capable of performing tasks that typically require human intelligence (behave, think and make decisions )....

Artificial Intelligence (AI) What is Artificial Intelligence (AI)? Artificial intelligenc e (AI) is the field of computer scienc e dedicated to developing intelligent machines capable of performing tasks that typically require human intelligence (behave, think and make decisions ). AI don’t need to preprogrammed machine to do some work, you have to create a machine with programmed algorithm which can work with own intelligence.  What is Artificial Intelligence (AI)? AI is the ability for a computer to think, learn and simulate human mental processes, such as perceiving, reasoning, and learning. Different Definition Types of AI?  Types of AI(Based on Capabilities) Weak or narrow AI: it is a type of AI which can perform a predefined narrow set of instructions without exhibiting any thinking capability. General AI: it is the type of AI which can perform the tasks like what human can do. Strong AI: it is the type of AI in which it is expected that the machine will surpass the capacity of human. It will perform better than humans, It may be the situation when it can be said that the machines will be the master and overtake humans. It has been considered as a great threat to the society by scientists including Stephen Hawking. With unlimited number of probabilities we need to AI such as in chess and Go games. AI Aims to : * Simulate human intelligence in machines. * Solve problems that are difficult or impossible for humans to solve. * Create intelligent machines that can improve our lives such as personal virtual assistants (Siri, Alexa, google assistant). * Build a machine can perform tasks that need human intelligence (proving theorems, perform surgery, driving cars in traffic). * Opens a path for new technologies, new devices and opportunities. Intelligence Meaning: Problem Learning Solving Intelligence Language Reasoning Intelligence Perception Learning Activity to gain knowledge, There are a number of different forms of learning as applied to artificial intelligence. The simplest is learning by trial and error. Reasoning Set of process that enable to judgment to make decision or make prediction. An example of the former is, “Fred must be in either the museum or the café. He is not in the ca fé; therefore he is in the museum,” Perception In perception the environment is scanned by means of various sensory organs, real or artificial, and the scene is decomposed into separate objects in various spatial relationships. Natural language processing (NLP) NLP involves analyzing how computers can process and parse language similarly to the way humans do. Problem solving Problem solving, particularly in artificial intelligence, may be characterized as a systematic search through a range of possible actions in order to reach some predefined goal or solution.  Turing Test The Turing test, proposed by Alan Turing (1950), was designed as a thought experiment that would sidestep of the question “Can a machine think?” A computer passes the test if a human interrogator, after posing some written questions, cannot tell whether the written responses come from a person or from a computer. We note that programming a computer to pass a rigorously applied test provides plenty to work on. The computer would need the following ca pabilities: Natural language processing to communicate successfully in a human language. Knowledge representation to store what it knows or hears. Automated reasoning to answer questions and to draw new conclusions. The impact of AI in various fields Fields of Artificial Intelligence  Main Areas of Artificial Intelligence 1 – Machine Learning: The Core of AI Machine Learning (ML) is a fundamental area of AI, focused on developing algorithms that enable computers to learn from and make predictions or decisions based on data. Through this iterative process, ML models improve their performance with each new dataset, eventually becoming more accurate and efficient. 2 – Deep Learning: A Hierarchical Approach Deep Learning is a subset of ML and employs artificial neural networks to simulate the hierarchical structure and function of the human brain. This approach enables the processing of vast amounts of data and the extraction of complex patterns or features. 3 – Robotics: AI Meets the Physical World Robotics bridges the gap between the digital and physical worlds and integrates AI with mechanical design and engineering. Robots can perceive their environment, process information, and execute actions based on AI-driven decisions. 4 – Expert Systems: AI for Decision Support Expert Systems utilize artificial intelligence to emulate human expertise in a specific domain, offering decision support and recommendations based on a knowledge base and a set of rules or heuristics. These systems have found applications in various industries, including finance, medicine, and law. 5 – Natural Language Processing: AI and Human Language Natural Language Processing (NLP) is a subfield of AI that focuses on the interaction between computers and human language. NLP techniques enable machines to understand, interpret, and generate text or speech in a way that is both meaningful and useful. 6 – Computer Vision: Teaching Machines to See Computer Vision is a discipline of artificial intelligence that aims to replicate the human ability to perceive, interpret, and understand visual information from the world. By processing and analyzing images or videos, Computer Vision algorithms can extract valuable insights. Examples of AI applications * Self-driving cars * Facial recognition technology * Machine translation * Chatbots * Medical diagnosis * Fraud detection * Personalized recommendations * Virtual assistants * Smart homes * Industrial automation