Тодор Ангелов Тачев, ф.N: 43874
ФМИ, Информатика, гр. 2, 1 курс
Курсова работа по английски език, 2004/2005
An Introduction to Artificial Intelligence
http://www.generation5.org/content/1999/aiintro.asp
Computers can do many wonderful things. They can perform calculations millions or
billions of times faster than human beings. Yet, is this all that computers can do? In the past,
computer scientists have created a great many programs that could perform tasks that people
wouldn't have otherwise believed a computer could do. This is not limited to only playing chess,
or proving theorems, but also programs that can hold a regular conversation with humans,
understand stories and perform many other human-like tasks. Yet, there have also been very
many legitimate questions whether or not the intelligence that these programs exhibit can be
comparable to human intelligence. The problem lies with architecture, the way our programs are
structured. Alan Turing, one of the fathers of AI, once created a theorem that stipulated that all
computers (he uses the term turing machines, which can be likened to digital computers) can
compute anything that is computable. If creating a human being via a digital computer was ever
possible, we must first answer some philosophical questions concerning whether emotion or
consciousness is computable.
There were some scientists that questioned the capability of digital computers. Citing that
the architecture of digital computers would be a terrible approach to emulating human
intelligence, they strove to create artificial neurons. This was based on the architecture of our
own biological brains.
There then came another question. People doubted whether or not symbolic AI programs,
which encompassed just about every program in the 1950s, could exhibit true intelligence. Some
examples of Symbolic AI programs are chess-playing programs, expert systems such as theorem
provers, ELIZA, STUDENT (which solves calculus problems) etc. Just about any task-center AI
program is a symbolic AI program. These programs operate by manipulating symbols. The
critics claimed that the architecture of these programs were not sufficient enough for intelligence.
In essence, they have no "common sense" and can rarely perform tasks other than the tasks that
were assigned to them. One of the early natural language programs could translate Russian to
English, and vice versa. When it converted the English phrase "The spirit is willing but the flesh
is weak" to Russian, then back to English, it came up with "The vodka is good but the meat is
rotten". Of course, the machine translation technology that we have today has certainly
improved, but many "common sense" mistakes like this are common. These critics of Symbolic
AI systems were the connectionists. They in turn created the neural network architecture. Neural
networks are able to draw links between meanings and thus exhibit some form of "common
sense" in some situations. More generally they are based on the architecture of neurons, synapses
and dendrites in brains. As much as these systems have been hyped, they have not nearly been
able to replace symbolic AI systems. On the other hand, they have been very useful for things
such as image recognition.
Adaptability and learning has since been almost essential to many AI programs. This
follows the goal that one day our machines will function completely free of their masters, able to
learn and adapt freely from the environment that they live in.
Тодор Ангелов Тачев, ф.N: 43874
Glossary
Turing machine – abstract machine (algorithm) that solves any solvable task;
Artificial neuron – object in the computer’s memory which emulates the real human neuron;
Natural language program – a form of AI program, which parses, understands (and may answer)
sentences in a given human language (English, Bulgarian, etc.);
Neural network – a collection of artificial neurons connected in a defined (by the task) order,
which emulates the of neurons in human brains;
Expert system – an artificial intelligence used to model and aid human decision, making in a
highly specialized problem domain;
Synapse – the minute space between a nerve cell and another nerve cell, through which nerve
impulses are transmitted from one to another;
Dendrite – the branched part of nerve cell that carries impulses toward the cell body;
Digital computer - a computer which operates with information, numerical or otherwise,
represented in a digital form;
Algorithm - a special
mathematical procedure for solving a particular type of problem;
Тодор Ангелов Тачев, ф.N: 43874
Exercise
1. How operate the symbolic AI program?
a) These programs operate by manipulating symbols.
b) There aren’t such programs.
c) These programs operate by deleting all of the information that you defined.
2. What is turing machine?
a) A part of the computer, which cool the processor.
b) Abstract machine (algorithm) that solves any solvable task.
c) Machine, which the farmers use for harvesting.
3. How was the first researcher of AI?
a) Alan Turing.
b) John Atanasoff.
c) Josh Wink.
4. What did the critics of symbolic AI programs create?
a) Neuron network architecture.
b) Faster computers.
c) Law against these programs.
5. What is dendrite?
a) A program.
b) A part of nerve cell.
c) This is the name of English mathematician.
Тодор Ангелов Тачев, ф.N: 43874
Answers
1.
2.
3.
4.
5.
–a
–b
–a
–a
–b