Intelligent Systems - Introduction PDF

Intelligent Systems - Introduction  What is an intelligent system? An intelligent system is an advanced computer system that can gather, analyze and respond to the data it collects from its surrounding environment. It can work and communicate with other agents, such as users or other computer s...

Intelligent Systems - Introduction  What is an intelligent system? An intelligent system is an advanced computer system that can gather, analyze and respond to the data it collects from its surrounding environment. It can work and communicate with other agents, such as users or other computer systems. It can also learn from experience and adapt according to current data. An intelligent system might also support remote monitoring and management. There is no single standard that defines an intelligent system. It is often determined by degrees of intelligence rather than a checklist of characteristics. An intelligent system is: 1. operates in an environment with other agents, 2. possesses cognitive abilities such as perception, action control, deliberative reasoning or language use, 3. follows behavioral principles based on rationality and social norms and 4. has the capacity to adapt through learning. However, an intelligent system is not the same thing as AI, although the terms are sometimes used interchangeably. With AI, computers and other machines attempt to simulate human intelligence, but its presence does not automatically imply an intelligent system. For example, a computer running an AI-based application does not mean that the computer itself is an intelligent system, although it might contribute to such a system as one of its agents. What are examples of intelligent systems? Intelligent systems are omnipresent and offer endless possibilities. They can benefit many industries and affect both our personal and professional lives. The following table provides examples of how intelligent systems can be used in different industries. This is just a glimpse into the potential application of intelligent systems.  Underlying Technologies Natural Language Processing (NLP): Focusing on specific NLP tasks like machine translation, sentiment analysis, text summarization, chatbot development, and the challenges in achieving truly human-like language understanding. Computer Vision: Exploring object detection, image classification, facial recognition, and their applications in areas like autonomous driving, medical imaging, and surveillance. Robotics and AI: The intersection of AI and robotics, including areas like motion planning, control systems, human-robot interaction, and the ethical considerations of robots in society. Machine Learning: Machine learning (ML) is a type of artificial intelligence (AI) that enables computers to learn from data without being explicitly programmed. Instead of relying on specific instructions, ML algorithms identify patterns and insights from data, allowing them to make predictions or decisions.  Underlying Technologies (Cont’d) Data science: It is a multidisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. It's like a detective, looking for clues and patterns in data to solve mysteries and answer questions. Expert Systems and Decision Support Systems: How expert systems use knowledge bases to mimic human expertise in specific domains, and how decision support systems assist humans in making complex choices. AI in Healthcare: Examining applications like medical diagnosis, drug discovery, personalized medicine, and the ethical implications of AI in healthcare. AI in Finance: Exploring applications like algorithmic trading, fraud detection, risk management, and the challenges in ensuring fairness and transparency. Industry Examples Transportation Traffic control systems, traffic flow analysis and congestion monitoring, delivery fleet coordination, autonomous cars, public transportation systems, accident prevention Aerospace Airline cockpit controls, drones, spacecraft monitoring, mission planning, advanced guidance and navigation, air traffic control Human Visual surveillance, biometric identification monitoring (such as face or fingerprint recognition), character or speech recognition Industry Examples Manufacturing Advanced robotics and automation, autonomous systems, diagnostics and repairs, inventory management, visual inspection Education Tutoring, identifying student learning patterns, question and answer systems, course planning and scheduling, interactive online education Climatology Forecasting, advance warning systems (such as tornados or tsunamis), field research and monitoring, satellite imaging and analysis Retail Online shopping recommendations, point-of-sale (POS) terminals, digital signage, product planning and delivery Industry Examples Home Smart appliances, climate and automation lighting control, entertainment Public health Medical care, medical diagnostics, telemonitoring, health crisis management (such as the COVID-19 pandemic), violence pattern detection, biomedical engineeri ng