3203. Introduction to Artificial Intelligence
AI Overview
Artificial Intelligence, or AI, is the attempt to build intelligent computer systems, that is, to make computer systems similar to the human mind in certain aspects.
1. Brief history
Whether intelligence/mind/thinking can be understood and reproduced in machines, it is a question that has been considered for a long time by philosophers, mathematicians, scientists, engineers, as well as by writers and movie makers. However, it is the modern digital computer that makes it possible to seriously test various answers to this question.
Computer appeared in the 1940s. Though initially it was used for numerical calculation, soon people realized that it can carry out many other intellectual activities by manipulating various types of symbols. Naturally, people began to wonder whether all mental activities can be carried out by computer, and if not, where is the boundary.
In 1950, British mathematician and computer scientist Alan Turing published an article "Computing machinery and intelligence" that discussed many important theoretical issues. It is generally acknowledged that the forming of AI as a research field was signified by the Dartmouth Meeting in 1956, where a dozen of researchers shared their initial ideas and results in fields like theorem proving and game playing.
In the early days, AI researchers were generally optimistic about AI and were looking for a general-purpose solution of intelligence. For example, a "General Problem Solver" was programmed with the hope that it can solve all kinds of problems (when properly represented). However, later the AI researchers found various kinds of issues which made them to turn to domain-specific knowledge and problem-specific solutions. Consequently, today's AI is a domain where many theories and techniques co-exist and compete with each other.
Reference: brief history of AI
2. Partition of the domain
The current domain of AI research and application can be cut into fields along different dimensions.
- by the answers to the following basic questions:
- What is AI?
- Can AI be built?
- How to build AI?
- Should AI be built?
- by the scope of cognitive functions under research, the fields include:
- core cognitive facilities, such as searching, reasoning, learning, planning, categorizing, ...
- input/output facilities, such as percepting, acting, natural language processing, ...
- by the domains of application, the fields include:
- game playing,
- theorem proving,
- data mining,
- question answering,
- car driving,
- ... ...
- by the type of major techniques, the fields include:
- rule-based system,
- case-based system,
- neural networks,
- genetic programming,
- logic programming (e.g., Prolog),
- functional programming (e.g., Lisp),
- ... ...
References: our textbook, AI Topics
3. Nature of the domain
After hard works by many people in more than half a century, AI is still not mature, in the sense that there are far more problems than solutions.
The difficulty comes not only from the simple fact that mind is one of the most complicated phenomena in the universe, but also from the nature of AI, which must be, at the same time,
- a branch of science, about how intelligence/mind/thinking work, as part of
Cognitive Science(s)
- a branch of engineering, about how to make new computer hardware and software
As a result, a complete AI work consists of three levels:
- a theory on intelligence (or part of it),
- a formal model of the theory,
- a computational implementation of the model.
4. AI and your future
At the current stage, AI is still mostly a domain of research, not ready for applications, except in limited fields.
AI for the minority of the students who really want to take it as career:
- Application opportunity (with a MS or BS degree): you can find jobs in expert systems, Prolog/Lisp programming, data mining, neural network, and so on, but the market is small and the jobs are not secure (though they can be interesting).
- Research opportunity (with a PhD or MS degree): interesting and challenging topics in many places, but you need to be well prepared for hard problems and tough career paths.
AI for the majority of the students:
- to get new ideas from the domain,
- to follow the progress and be prepared for its future development,
- to have a better idea about human thinking,
- to have fun in thinking about the problems!