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Introduction to Artificial Intelligence: Levels, History, Applications, and Components

This video provides an introduction to artificial intelligence, discussing the different levels of AI, the history of AI, various applications of AI, and the components of AI, including knowledge.

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Introduction to Artificial Intelligence: Levels, History, Applications, and Components

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  1. Unit I – Chapter 1 Introduction Prof. Sujata Rizal

  2. Introduction to AI • A machine with the ability to perform cognitive functions such as perceiving, learning, reasoning and solve problems are deemed to hold an artificial intelligence. • Artificial intelligence exists when a machine has cognitive ability. The benchmark for AI is the human level concerning reasoning, speech, and vision. Prof. Sujata Rizal

  3. Introduction to AI Levels • Narrow AI: A artificial intelligence is said to be narrow when the machine can perform a specific task better than a human. The current research of AI is here now • General AI: An artificial intelligence reaches the general state when it can perform any intellectual task with the same accuracy level as a human would • Strong AI: An AI is strong when it can beat humans in many tasks Prof. Sujata Rizal

  4. https://youtu.be/-RiiXVUrAdc • https://www.youtube.com/watch?v=mJeNghZXtMo Prof. Sujata Rizal

  5. History of AI Prof. Sujata Rizal

  6. Prof. Sujata Rizal

  7. Prof. Sujata Rizal

  8. https://www.youtube.com/watch?v=cwmIHnEHfr8 Prof. Sujata Rizal

  9. Applications of AI • Gaming − AI plays crucial role in strategic games such as chess, poker, tic-tac-toe, etc., where machine can think of large number of possible positions based on heuristic knowledge. • Natural Language Processing − It is possible to interact with the computer that understands natural language spoken by humans. • Expert Systems − There are some applications which integrate machine, software, and special information to impart reasoning and advising. They provide explanation and advice to the users. Prof. Sujata Rizal

  10. Vision Systems − These systems understand, interpret, and comprehend visual input on the computer. For example, • A spying aeroplane takes photographs, which are used to figure out spatial information or map of the areas. • Doctors use clinical expert system to diagnose the patient. • Police use computer software that can recognize the face of criminal with the stored portrait made by forensic artist. • Speech Recognition − Some intelligent systems are capable of hearing and comprehending the language in terms of sentences and their meanings while a human talks to it. It can handle different accents, slang words, noise in the background, change in human’s noise due to cold, etc. Prof. Sujata Rizal

  11. Handwriting Recognition − The handwriting recognition software reads the text written on paper by a pen or on screen by a stylus. It can recognize the shapes of the letters and convert it into editable text. • Intelligent Robots − Robots are able to perform the tasks given by a human. They have sensors to detect physical data from the real world such as light, heat, temperature, movement, sound, bump, and pressure. They have efficient processors, multiple sensors and huge memory, to exhibit intelligence. In addition, they are capable of learning from their mistakes and they can adapt to the new environment. Prof. Sujata Rizal

  12. Components of AI Prof. Sujata Rizal

  13. AI Dimension • First Dimension: Logic, Cognition, Computation • Second Dimension • Third Dimension Prof. Sujata Rizal

  14. Knowledge • The data is collection of facts. The information is organized as data and facts about the task domain. Data, information, and past experience combined together are termed as knowledge. • Knowledge in Philosophy • Knowledge in Science • Knowledge in Engineering Prof. Sujata Rizal

  15. Knowledge in Philosophy • In philosophy, the study of knowledge is called epistemology; the philosopher Plato famously defined knowledge as "justified true belief", though this definition is now thought by some analytic philosophers to be problematic because of the Gettier problems, while others defend the platonic definition. Prof. Sujata Rizal

  16. Knowledge in Science • Science is about understanding the world, but it's a process rather than a body of knowledge. Scientific knowledge is what we learn from the scientific process, which involves experimenting and collecting data. Scientific research is the collecting of data to investigate and explain a phenomenon. Prof. Sujata Rizal

  17. Knowledge in Engineering • Knowledge engineering is a field of artificial intelligence (AI) that tries to emulate the judgment and behavior of a human expert in a given field. • Knowledge engineering is the technology behind the creation of expert systems to assist with issues related to their programmed field of knowledge. Expert systems involve a large and expandable knowledge base integrated with a rules engine that specifies how to apply information in the knowledge base to each particular situation.  Prof. Sujata Rizal

  18. Components of Knowledge Base • The knowledge base of an ES is a store of both, factual and heuristic knowledge. • Factual Knowledge − It is the information widely accepted by the Knowledge Engineers and scholars in the task domain. • Heuristic Knowledge − It is about practice, accurate judgement, one’s ability of evaluation, and guessing. Prof. Sujata Rizal

  19. Knowledge Based Systems • KBCS is a computer program designed to act as an expert in specific field of knowledge. These are designed to solve complex problems. KBCS simulates the human reasoning process and applying specific knowledge and inferences. Prof. Sujata Rizal

  20. Prof. Sujata Rizal

  21. Inference Engine • Use of efficient procedures and rules by the Inference Engine is essential in deducting a correct, flawless solution. • In case of knowledge-based ES, the Inference Engine acquires and manipulates the knowledge from the knowledge base to arrive at a particular solution.

  22. AI in Future • Automated Transportation • Cyborg Technology • Taking over dangerous jobs: bomb defusing • Solving climate change • Robot as friends  • Improved elder care Prof. Sujata Rizal

  23. Applications • Chatbots • Artificial Intelligence in eCommerce • Healthcare • Entertainment • Finance • Data security • Manufacturing: market demand • Automotive industry: self-driven cars • Artificial Intelligence in Logistics and Supply Chain Prof. Sujata Rizal

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