I have recently read an article where its author states that the computer will never be able to understand the text as it is understood by the human. He cites a number of impossible tasks to machines as proof with an emphasis on the lack of efficient algorithms and modeling impossibility of a complete system, which would take into account all the possible alternatives of the text. However, is it really that bad? Is it true that for the solution of such tasks is needed special processing power? What is a situation of natural language text processing?
What does it mean to "understand"?
The first thing I was confused is the question itself. Could a computer be able ever to understand the text as it understood by the human? What exactly does it mean to "understand as the human"? Generally, what does it mean to "understand"? In the book “Data Mining: Practical Machine Learning Tools and Techniques” authors asked themselves a similar question. What does it mean to "get trained"? Let us assume that we have applied to the "interpreter" some training technique. How do we check whether or not a student is learning? If a student attended all the lectures on the subject, it does not mean that the student has learned and understood it. In order to test this, teachers hold examinations, where student is asked to complete some tests on the subject. Same thing is with the computer, we want to know whether it has learned (whether it has understood the text). In order to find out that we have to check, as it solves the specific applications, translates the text, highlights the facts, gives concrete meaning of a polysemantic word, etc. In this perspective, the meaning misses the importance at all. The meaning can be assumed as a certain state of the interpreter in accordance with which it handles text.