The potential applications of AI are as follows:
- Game Playing: One can buy machines that can play master-level chess for a few hundred dollars. There is some AI in them, but they play well against people mainly through brute force computation-looking at hundreds of thousands of positions per second.
- Speech recognition: IN the 1990s, computer speech recognition reached a practical level for limited purposes. Thus United Airlines has replaced its keyboard tree for flight information with a system using speech recognition of flight numbers and city names.
- Understanding natural language: Just getting a sequence of words into a computer is not enough. Parsing sentences is not enough either. The computer has to be provided with an understanding of the domain, the text is about, and this is presently possible only for very limited domains.
- Computer Vision: The world is composed of three-dimensional objects, but the inputs to the human eye and computer TV cameras are two-dimensional. Some useful programs can work solely in two dimensions, but full computer vision requires partial three-dimensions, but full computer vision requires partial three-dimensional information that is not just a set of two-dimensional views. At present, there are only limited ways of representing three-dimensional information directly, and they are not as good as what humans evidently use.
- Expert systems: A "knowledge engineer" interviews experts in a certain domain and tries to embody their knowledge in a computer program for carrying out some task. One of the first expert systems was MYCIN in 1974, which diagnosed bacterial infections of the blood and suggested treatments. it did better than medical students or practicing doctors, provided its limitations were observed.
- Robotics: Although industrial robots to date have been expensive, robot hardware can be cheap. What is needed is perception and intelligence to tell robot effectors what to do; "blind" robots are limited to very well-structured tasks (like spray painting car bodies).
- Theorem proving: Proving mathematical theorems might seem to be mainly of academic interest. However, many practical problems can be cast in terms of theorems.
- Symbolic mathematics: Symbolic mathematics refers to the manipulation of formulas, rather than doing arithmetic or numeric values. Symbolic manipulation is often used in conjunction with ordinary scientific computation as a generator of programs used to actually do the calculations. Symbolic manipulation programs will be an important component of scientific and engineering workstations.