This does not, however, mean that one of the sexes is superior, but that they are different, and that these differences have to be worked out and brought into people's minds. This little interlude also brought another point up: the desire to replicate.
This being the most basic of all basic desires, it cannot be ignored. No experiment in the field of AAA has yet specified which gender the mind would be. In a world, where there is no need for a partner to replicate (because there is a simple 'copy'-mechanism, for example), social structures would be completely different from man's.It is even the question, if different genders were necessary at all. Thus, an artificial mind would also need the 'ability' to die, as well as that to mate and replicate, otherwise the resulting being would be beyond any recognition by a human mind. A mind that cannot die and that doesn't feel the need to replicate in a manner similar to humans, would be very different from man.
Such an environment would eve to be created artificially, but in a different sense: The conditions would have to be made more difficult than they needed to be, only to force the beings to act human-like.And only an evolutionary process would lead to a mind similar to a human one. This is the third deficiency. 3. THE ART OF LEARNING : Learning isn't a 'static' ability, but one which continuously changes: You must learn how to learn, and the way you learn changes.
The new-born child can only learn by first-hand experience, and hardly generalize. But the older the child gets, the more he/she can learn without having experienced a corresponding situation. Indeed, most of what you know is what you were taught by others, read in books, etc.This probably is the main advantage of man over all other animals: that we can pass on knowledge, so that the next generation doesn't have to make the same mistakes again (it does anyway, but that's a different problem ...
). Your knowledge includes the first-hand experiences of hundreds of thousands of people, whose knowledge and experiences were collected and put into a structured form, in order to make learning these facts easier. People nowadays aren't more intelligent than 1000 years ago, but we have ore knowledge, and thus can achieve far higher goals.Like Newton said: "I am a dwarf, but I can see very far for I am standing on the shoulders of giants".
But what effects does this have on AAA? The brain changes, and not only does its knowledge change, but also the way it accumulates knowledge and makes use of it. An artificial intelligence must be able to change its own programmer. 4. THINKING OUTSIDE THE BRAIN : The previous point contains another interesting thought: Whatever you do, whatever you think or say - it hasn't been thought up entirely by you, it always contains parts from other people.This is the key to developing beyond what a single generation can reach (see previous section). But it also leads us to a somewhat discomforting question: How much of that brain is actually mine ? What percentage of what I think has been thought by others already ? How different am I ? They're sitting around a table, discussing ideas and problems, taking notes, and thinking about whether or not that last proposal was good.
In the end, they will come up with a solution that will be far better than one that any of them had worked out in his/her own!The result will even be better than if each of them was assigned a fifth f the problem, and solved it alone. This team is able to achieve more than five single persons can do independently. But what is the difference between five isolated persons and a team of five? If the team develops an idea that the single persons don't, which of the members created it? It's not a person that created the idea, but the interaction process, the discussion. An act of thinking has been done by an immaterial process, not a single person.
5.THE IDEA OF A GENERAL CONCEPT OF INTELLIGENCE : All the points made above make one thing clear: In order to build an artificial intelligence, it must be built as human-like as possible. Without basic human 'ingredients', the resulting mind might not even be recognized as such. This boils down to the feeling that the goal is to build a mere copy of the human mind. Why on earth, one might wonder, would anybody want to build a copy of the human mind? Isn't the original working fine? Isn't it superior to everything known? Isn't one's mind the most difficult thing to be examined by itself?What would be the use of such an artificial mind, that would need even more artificial means, only to stay human-like? The only logical solution to this is to completely separate human from artificial intelligence, in order to build something entirely new.
This naturally leads to the idea of a higher principle of Intelligence, that human intelligence is only one manifestation of (in order to distinguish between the traditional human intelligence and this new idea of a more general concept, I want to spell the latter with a capital l: Intelligence).Another one would be artificial intelligence, and another one still the intelligence developed on a planet many lighteners from here. Again, I remind you of the points Just made. Considering these, how should a mind that is the result of evolution on an entirely different planet be animal to ours in any way? There must be similarities, but on a higher level: on the level of Intelligence (note the capital l).
In that hierarchy, AAA is on the same level as human intelligence, together with animal intelligence and any other kind of intelligence that one might encounter.The following figure illustrates this: APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN CAD / CAM / JIM Artificial Intelligence (AAA) technology comprises several areas of current research and development. Some of these are : Expert Systems Natural Language Understanding Neural networks Fuzzy Logic Computer Vision Intelligent Robotics Decision support systems Voice recognition Main thrust of the application of artificial intelligence in CAD/CAM/JIM is that AAA techniques can be used to substitute humans in the decision making process. This is important because decisions are made either intuitively or based on facts.
Once facts are organized in a systematic manner, and the logic of decision making is laid down, then the computer can make the decisions or help the human operator with advice winch will enable him to take the decisions. The advantage of the computer lies in the fact that it can scan a vast area of knowledge and accept a wide range of inputs o base its decisions. If the problem is a structured problem, it is easy to take a decision. However, if the problem is an unstructured one, decision making requires expertise. Busy traffic intersection without a police constable on duty can be likened to an unstructured problem.
Many situations in industries are often unstructured. The various fields of AAA which are of interest to manufacturing engineers are briefly described below : 1 . Expert Systems : An expert can be defined in many ways. An appropriate definition suitable to the present context is : An expert is a person who can take good decisions based on a limited number of facts" An expert system can be designed as an interactive program with an expert like performance in a particular problem-solving domain (area of expertise).Also consisting of facts relevant to the field and heuristics for applying those facts.
Though at present the expert systems are used mostly as assistants to experts, they are being updated so as to be used by a non-expert user. Components of an Expert System : The principal components of an expert system are : a knowledge base, an inference engine and a user interface. I. Knowledge Base : The components of an expert system that contains the system's knowledge (domain knowledge) is called its knowledge base.
This part of the system is critical to the way the system is constructed.It contains both declarative knowledge as well as procedural knowledge. The procedural knowledge often is of rule based type. Lie. Inference Engine : The inference engine also known as rule interpreter decides which heuristic search techniques are used to determine how the roles in the knowledge base are to be allied to the problem.
In effect, an expert system is 'run' by its inference engine which determines which rules are to be invoked, and which rules are excluded when an acceptable solution has been found.An inference engine that works well in one expert system may work Just as well with a different knowledge base, thus reducing development time. Ill. User Interface : The user interface component enables you to communicate with an expert system. The communication performed by a user interface is bidirectional.
The system is able to respond with recommendations and, requests additional information about the problem and so on. Fig - Expert Systems Features of an Expert System : The ideal expert system should possess certain essential criteria such as : The knowledge base should be expandable.The expert system must be capable of acquiring knowledge. Ideally, an expert system must be capable of advice with suitable explanation.
2. Computer Vision : Computers are now being interfaced with a CDC camera and image processing user graphic information about a scene or a part for the purpose of recognition (say recognition of parts coming through a conveyor), inspection, (dimensional inspection, vision injection for defects etc. ). Computer vision systems can be interfaced with CM, welding robots and assembly robots to improve the efficiency of operation.The application of computer vision for inspection has been dealt with in Chapter 8. 3.
Robotics : There are several applications of robots which require adaptively changing the robot program. A typical example is arc welding using robots. Here, a number of sensors are used to measure the welding parameters and the program of weld is controlled by the data received from these sensors. Similarly force / torque / slip sensors are attached to the gripper of some robots to achieve, precise control the gripping force.There is considerable scope for employing intelligent robots in computer integrated manufacturing.
Applications of Industrial Robots : Material Handling. Machine Tending. Welding. Surface Coating. Machining. Assembly.
Inspection. 4. Voice Recognition : The primary methods of human communication being speech, the goal of research in this field is to allow computers to understand speech so that they can recognize spoken words. Automatic speech recognition research seeks to advance the goal of natural language processing by simplifying the process of communication between programmers and computers.Programming of CNN Machine tools and control of robots are two areas where voice recognition can be of substantial help. 5.
Neural Networks : Neural networks is a promising area of AAA. Neural networks can have applications in robotics, object recognition and is a developing Geld of great promise as far as CAD/ CAM/JIM is concerned. 6. Fuzzy Logic : Many decisions in activities connected with JIM operations are carried out without are selected using fuzzy logic in some EDM systems. When decisions are to be made under conditions where exact reasoning is either not available or possible, fuzzy logic provides a better solution.
Brief descriptions of some applications of JIM are discussed below : EXPERT SYSTEMS IN JIM : An expert system is a software package that includes (I) a stored knowledge base in a specialized area and (it) heuristics - the capacity to probe this knowledge base and make decisions or recommendations. An expert system functions very much differently from a common computer. What it does with the information it receives is that it analyses the information and provides a solution to the query input. 1 .
Categories of Expert Systems : The expert systems can be applied to any situation that normally requires human intelligence.The applications of the expert system can be divided into several categories, some of which include interpretation, prediction, diagnosis, design, planning, monitoring, control, instruction etc. The details of these which are of specific interest to JIM are given in Table. There are several categories of expert systems. Rule Based Expert System : In this approach to an expert system, a series of IF-THEN roles based on human expertise is used.
For example : IF the peripheral speed of the gear is high, THEN noise generated will be more. IF the number of teeth on the pinion is less than 14 THEN the pinion be given positive erection.Table : Functional Categories For Expert System Application Category Problem Addressed Application Interpretation Infers situation Speech understanding description from image processing sensor data (Vision systems, Test results) Prediction Estimation of tool wear Diagnosis Infers system malfunctions from observations Fault diagnosis of machines Design Configure objects under constraints PC / VEILS Design Mechanical Design Planning Designs actions Monitoring Controls observations in order to plan Real time control of equipment in FM, JIM etc. Model Based Expert System/ObJect Orientation :This approach is especially useful in diagnosing equipment problems or trouble- shooting. Many empirical design procedures may also be classified under this category. A model based expert system is based on a 'model' of a device that behaves in a particular way, given a set of operating conditions.
Since they draw conclusions from knowledge of structure and behavior of devices and systems model based expert systems are said to reason from first principles. A more detailed representation of knowledge can be achieved by the use of frames. The use of frames make AAA programs more flexible.
