Intelligence is the ability to learn about, learn from, understand, and interact with one’s environment. This general ability consists of a number of specific abilities, which include these specific abilities: Adaptability to a new environment or to changes in the current environment Capacity for knowledge and the ability to acquire it Capacity for reason and abstract thought Ability to comprehend relationships Ability to evaluate and judge Capacity for original and productive thought
AI is the study of how to make computers do things which, at the moment, people do better AI is a branch of computer science concerned with teaching computers to think The capability of a device to perform functions that are normally associated with human intelligence, such as reasoning and optimization through experience AI is the branch of computer science concerned with the study and creation of computer systems that exhibits some form of intelligence- Learn new concepts and tasks Can reason and draw useful conclusion Can understand a natural language
AI HI AI, when given the information can be When HI is given the same exact, every time with speed. information, it can not be as exact, and AI are digital is slower. AI uses byte-addressable memory. HI are analogue The HI uses content-addressable There is a appealing hardware/software memory distinction obscures in AI No hardware/software distinction can be made with respect to the brain or mind Processing and memory are performed Processing and memory are performed by the different components. by the same components in the brain AI could do this if it was program to Human intelligence can forget and lose do so, but this would be counter- productive. information
Mundane Tasks Formal Tasks Perception Games Vision Chess Speech Checkers-Go Natural Language Mathematics Understanding Geometry Generation Logic Translation Integral calculus Commonsense reasoning Proving properties of programs Robot control
This assumption was given by Newell and simon. They call this assumption the physical symbol system hypothesis. They define a physical symbol system as follows:- A physical symbol system consists of a set of entities called symbols, which are physical patterns that can occur as components of another type of entity called an expression or symbol structure. A symbol structure is composed of a number of instances (or tokens) of symbols related in some physical way. At any instance of time the system will contain a collection of these symbols structures. Besides these structures ,the system also contains a collection of processes that operate on expressions to produce other expressions: processes of and destruction.
A physical symbol system is a machine that produces through time an evolving collection of symbol structures. This hypothesis is only a hypothesis. There appears to be no way to prove or disprove it on logical grounds. The only way to determine its truth is by experimentation.
An AI technique is a method that exploits knowledge that should be represented in such a way that: The knowledge captures generalization. It can be understood by people who must provide it. It can easily be modified to correct errors and to reflect changes in the world and in our world view. It can be used in a great many situations even if it is not totally accurate or complete. It can be used to help overcome its own sheer bulk by helping to narrow the range of possibilities that must usually be considered.
“What is our goal in trying to produce programs that do the intelligent things that people do?” Are we trying to produce programs that do the tasks the same way people do? Are we attempting to produce programs that simply do the task in whatever way appears easiest?
Efforts to build programs that perform tasks the way people do can be divided into two classes:- In first class:- Programs that attempt to solve problems that do not really fit our definition of an AI task. They are problems that a computer could easily solve. Although that easy solution would exploit mechanisms that do not seem to be available to people.
In second class:- Programs that attempt to model human performance are those that do things that fall more clearly within our definition of AI tasks. They do things that are not trivial for the computers. There are several reasons one might want to model human performance at these sorts of tasks: To test psychological theories of human performance To enable computers to understand human reasoning To enable people to understand computer reasoning To exploit what knowledge we can glean from people.
In 1950,Alan Turing proposed the method for determining whether a machine can think. This method is known as Turing test. To conduct this test, we need 2 people 1 machine One person plays the role of the interrogator, who is in a separate room from the computer and the other person. The interrogator can ask questions of either the person or the computer by typing questions and receiving typed responses. The interrogator knows them only as A and B
The goal of the machine is to fool the interrogator into believing that it is the person. If the machine succeeds at this, then we conclude that the machine can think.