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Unit 8 Topic: Artificial intelligence and Robotics

I Reading skills

1. Read and remember the following words and word combinations used in their specialized meanings.

artificial intelligence

- штучний інтелект

human-like intelligence

- людиноподібний інтелект




спірний, дискусійний

assembly line

складальний конвеєр


розв'язання проблем; прийняття рішень

fuzzy logic

нечітка логіка, формальна система логіки


нечіткий, невиразний,

to predict

передбачати, прогнозувати

generalized analytical ability

здібність аналітично узагальнювати

infamous example

сумно відомий приклад

largely theoretical

досить теоретичний

frustrating task

ускладнене завдання

sophisticated field of study

сучасна сфера дослідження

2. Read and translate the following text into Ukrainian Artificial Intelligence

Artificial intelligence (AI) is arguably the most exciting field in robotics. It's certainly the most controversial. Everybody agrees that a robot can work in an assembly line, but there's no consensus on whether a robot can ever be intelligent.

Like the term "robot" itself, artificial intelligence is hard to define. Computer scientists prefer a looser definition, calling AI the study of how to make computers to do things. According to the technical dictionary − artificial intelligence is a field of study that explores how computers can be used for tasks that require the human characteristics of intelligence, imagination and intuition. Ultimate AI would be a recreation of the human thought process − a man-made machine with our intellectual abilities. This would include the ability to learn just about anything, the ability to reason, the ability to use language and the ability to formulate original ideas. But today’s AI machines can only replicate some specific elements of intellectual ability.

In early days of artificial intelligence, scientists thought that the computer would experience something like an electronic childhood, in which it would gobble up the world’s libraries and then begin generating new wisdom. Few people talk like this today because the problem of simulating intelligence is far more complex.

Today the term artificial intelligence encompasses several subsets of interests.

Problem solving. This area of AI includes a spectrum of activities from playing games to planning military strategy. The basic idea of AI problem-solving is very simple, though its execution is complicated. The computer can only solve problems it's programmed to solve − it doesn't have any generalized analytical ability. Existing chess computers are one example of this sort of machine.

Natural language. It is associated with artificial intelligence because humans can make the best use of AI if they can communicate with the computer in natural language. Furthermore, understanding natural language is a skill thought to require intelligence. In one of infamous example, the computer was supposed to demonstrate its prowess by translating a phrase from English to Russian and back. Despite the computer’s best efforts “The spirit is willing, but the flesh is weak” came back “The vodka is good, but the meat is spoiled”. One of the most frustrating tasks for AI scientists is providing the computer with the sense of context that humans have.

Fuzzy logic. This is a type of artificial intelligence that allows machines to “think” more like humans, providing a method of precisely measuring vague concepts. Fuzzy logic was invented more than 25 years ago and had been used successfully in electronically controlled devices ranging from vacuum cleaners and automobile transmissions to subway system and rocket-docking system. It also helps guide self-guidance system in robots.

Expert systems. An expert system is a software package used with an extensive set of organized data that presents the computer as an expert on a particular topic. For example, a computer can be an expert on where to drill oil wells, or what stock purchase looks promising or how to cook soufflés. Therefore, these AI systems present programs that mimic the decision-making and problem-solving thought processes of human expert on some particular topic.

Robotics. This field involves endowing computer-controlled machines with electronic capabilities for vision, speech, and touch. Scientists hypothesize on how and why we learn and think, and they experiment with their ideas using robots. Some scientists focus on humanoid robots because they feel that being able to experience the world like a human is essential to developing human-like intelligence. It also makes it easier for people to interact with the robots, which potentially makes it easier for the robot to learn.

Although considerable progress has been made in these sophisticated fields of study, a hard band of scientists are continuing to explore AI, focusing on how computers to learn.

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