Lecture 1
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The document discusses the history and scope of artificial intelligence, including definitions of AI as designing intelligent systems, different perspectives on what constitutes intelligence, and approaches to AI such as strong AI, weak AI, applied AI, and cognitive AI. It also examines what current AI systems can and cannot do and provides examples of tasks that have been achieved as well as limitations.
Lecture 1
- 1. Introduction
- 2. What is AI ? • Artificial Intelligence is concerned with the design of intelligence in an artificial device • The term was coined by McCarthy in 1956.
- 3. What is intelligence? • Is it that which characterize humans? • Behave as intelligently as a human • Behave in the best possible manner • Behavior strategies • Thinking? • Action?
- 4. Scope and view of Artificial Intelligence Ideal Performance (rationality) Human-Like Performance Thought/ Reasoning Behavior System that think like Humans (Turing Test) System that think Rationally (Laws of thought/logic) System that act Humans (Cognitive Science) System that act Rationally (Rational Agents)
- 5. Scope and view of Artificial Intelligence. • One view is that artificial intelligence is about designing systems that are as intelligent as humans. • Trying to understand human thought • Effort to build machines that emulate the human thought process. • Cognitive science approach to AI.
- 6. Scope and view of Artificial Intelligence • Turing test for intelligence. – ‘Imitation game‘ – Turing argued that if the interrogator could not distinguish them by questioning, then it would be unreasonable not to call the computer intelligent.
- 7. Turing test
- 8. Turing test • There are two rooms, A and B. • One of the rooms contains a computer. The other contains a human. • The interrogator is outside and does not know which one is a computer. • He can ask questions through a teletype and receives answers from both A and B. • The interrogator needs to identify whether A or B are humans. • To pass the Turing test, the machine has to fool the interrogator into believing that it is human
- 9. Scope and view of Artificial Intelligence. • Logic and laws of thought – Deals with studies of ideal or rational thought process and inference. – The emphasis in this case is on the inference mechanism, and its properties. – That is how the system arrives at a conclusion, or the reasoning behind its selection of actions is very important in this point of view.
- 10. Scope and view of Artificial Intelligence. • Rational agents. – Deals with building machines that act rationally. – The focus is on how the system acts and performs, and not so much on the reasoning process. – A rational agent is one that acts rationally, that is, is in the best possible manner.
- 11. Typical AI problems • “Intelligent entity” need to perform both “common-place” tasks as well as expert tasks • Common task are done routinely by people and some other animals. • Common task examples – Recognizing people – objects. – Communicating (through natural language) Navigating around obstacles on the streets
- 12. Typical AI problems • Expert tasks cannot be done by all people, and can only be performed by skilled specialists. • Expert tasks include – Medical diagnosis – Mathematical problem solving – Playing games like chess
- 13. Intelligent behavior • Perception involving image recognition and computer vision ƒ • Reasoning (With information we have) ƒ • Learning • ƒUnderstanding language involving natural language processing, speech processing ƒ • Solving problems
- 14. What’s easy and what’s hard? • It’s been easier to mechanize many of the high level cognitive tasks we usually associate with “intelligence” in people – e. g., symbolic integration, proving theorems, playing chess, some aspect of medical diagnosis, etc. • It’s been very hard to mechanize tasks that animals can do easily – walking around without running into things – catching prey and avoiding predators – interpreting complex sensory information (visual, aural, …) – modeling the internal states of other animals from their behavior – working as a team (ants, bees)
- 15. Practical Impact of AI • AI components are embedded in numerous devices • AI systems are in everyday use – Copy machines – Identifying credit card fraud, – Advising doctors – Recognizing speech – Helping complex planning tasks – Systems that provide students with personalized attention
- 16. Approaches to AI • Strong AI – Aims to build machines that can truly reason and solve problems – Self aware – Intellectual ability need to be indistinguishable from that of a human being.
- 17. Approaches to AI • Weak AI – Intelligence that cannot truly reason and solve problems – Acts as if it were intelligent • Applied AI – Aims to produce commercially viable "smart" systems such as, for example, a security system that is able to recognize the faces of people who are permitted to enter a particular building.
- 18. Approaches to AI • Cognitive AI: Computers are used to test theories about how the human mind works • For example, – Theories about how we recognize faces and other objects – About how we solve abstract problems.
- 19. Limits of AI Today • What can AI systems do ? – In Computer vision, the systems are capable of face recognition – In Robotics, we have been able to make vehicles that are mostly autonomous. – In Natural language processing, we have systems that are capable of simple machine translation. – Today’s Expert systems can carry out medical diagnosis in a narrow domain – Speech understanding systems are capable of recognizing several thousand words continuous speech – Planning and scheduling systems had been employed in scheduling experiments with the Hubble Telescope. – The Learning systems are capable of doing text categorization into about a 1000 topics – In Games, AI systems can play at the Grand Master level in chess (world champion), checkers, etc.
- 20. What can AI systems NOT do yet? • Understand natural language robustly (e.g., read and understand articles in a newspaper) • Surf the web • Interpret an arbitrary visual scene • Learn a natural language • Construct plans in dynamic real-time domains • Exhibit true autonomy and intelligence
- 21. Assignment # 1 • History of AI?