- •Предисловие
- •4 Тематических текста первого уровня сложности (ia, ib, ic, id) со следующими за ними лексическими упражнениями непосредственно по текстам
- •4 Тематических текста второй степени сложности(iia, iib, iic, iid) со следующими за ними лексическими упражнениями непосредственно по текстам
- •Unit One
- •Vocabulary:
- •Text I-a
- •Part one Primary school
- •Public School
- •University
- •System of higher education in the usa
- •Topics to discuss.
- •American Terminology is sometimes confusing
- •Placement – определение места
- •Many experiments are carried out by us in our laboratory.
- •Ex23: Translate into English using the Passive Voice
- •The articles Ex24: Insert articles where necessary
- •Vocabulary
- •Text 5 "Альма-матер" наших дней.
- •Reviewing Exercises
- •Keys to the above Ex-s:
- •Supplementary material
- •By Anne c.Lewis
- •Vocabulary
- •Benjamin Franklin
- •Сочетания с глаголами широкой семантики: take, get, make – do…
- •The school curriculum and academic programs
- •Vocabulary
- •Vocabulary to the text
- •Managing your study time
- •Vocational Education
- •Text 1-d Text 1-d Easy living at Japan's colleges
- •Text iib
- •By Nicholas Morgan
- •Vocabulary
- •Now a High School Senoir
- •Ex 2 Replace the infinitive in brackets by the correct tense form – the Present Perfect or the Past Indefinite (Active)
- •Ex 3 Make up sentences following the model
- •Ex 4 Draw conclusions.
- •Ex 5 Make up the dialogues following the model using the words given below,
- •Ex 6 Translate the sentences into Russian paying attention to the usage of the Present Perfect Present Perfect Continuous – Past Perfect Continuous.
- •Ex 8 Translate into English using the Present Continuous, the Present Perfect or the Present Perfect Continuous.
- •Ex 9 Open the brackets putting the verbs in the Past Indefinite and Past Perfect.
- •Ex 10 Open the brackets using the proper tense forms.
- •Ex 11 Open the brackets putting the infinitive in the Future Perfect.
- •Ex 12 Put the verbs in brackets in the proper tense form (Active)
- •Ex 14 Change the following sentences into Indirect Speech following the examples. Notice the changes in the pronouns.
- •Vocabulary
- •Зачеты и учебные нагрузки
- •Vocabulary
- •Vocabulary
- •Quotations and jokes.
- •Lord Samuel
- •Flannery o'Connor
- •Модальные глаголы, сослагательное наклонение, условные предложения, многозначность глаголов should, would, could, might, need….
- •Introductory text Some Important things from the Educational Environment
- •Part 1 Uniting two campuses
- •Part 3 Room to grow
- •Text I-c
- •Part 4 New campus to train for future
- •Text I-d
- •Part 6 Lab expands health program
- •Renovating for expansion
- •Shortening Year does no Harm
- •Free and Open competition
- •Avoiding a Brain Drain
- •Grammar Exercises
- •Ex.13 Translate the sentences into English using the verb need as in the examples ( Need)
- •The Comparison of Adjective and Adverbs
- •Foundation Considers Options
- •Bewildering Array of Institutes
- •Efforts to Aid Russia's Scholars Are More Than a Humanitarian Gesture
- •'Someone Specific'
- •Favorable Exchange Rate
- •'Flood of Applications
- •Vocabulary
- •Sports clubs
- •Fencing club
- •The Rugby Club
- •Regular practices
- •Quotations and jokes.
- •What is engineering
- •Word Study to the Text
- •Science and Engineering
- •Word Study to the Text
- •Artificial stupidity
- •Gameboys and girls stay in to play Buy a computer, one mother explains, and life can never be the same again
- •Engineering Ethics
- •The Gerund
- •Speech practice
- •Ex.Interpret the following passages using the given words
- •В сетях компьютера
- •Часть 1. "Персоналки'
- •Часть 2. Компьютер-шпион (spy)
- •Буду вечно молодым?
- •Supplementary Texts Public Image of Engineering
- •Coming soon – robot slave for everyone
- •Engineering Education
- •Electronics
- •Realms of Engineering
- •Ex. Answer the following questions
- •Engineering Work
- •Глобализация образования. Коммуникация Интернет как образовательная система: преимущества и недостатки; возможности
- •Languages
- •The library of the future
- •A lesson learned
- •Distance education: a means to an end, no more, no less.
- •В сетях компьютера
- •Мировая паутина
- •Рукописи не горят, а дискеты устаревают
- •В мире изобретений.
- •Самое значительное достижение
- •Compaq computer
- •People Like Electronic Announcers
- •Do men and women speak the same languages?
- •Quatations and jokes
- •Unit VI Карьера и выдающиеся личности современности Биографии выдающихся людей из разных областей знаний, автобиография. Авторское резюме
- •Introductory text Our Century and the next One
- •Young engineers.
- •Oceans of research.
- •The assembly line
- •Still Sprinting
- •Not so snow white after all.
- •William Randolph Hearst
- •They write in the newspapers he was invited to
- •Travel writer
- •Publisher
- •Ines de la Fresange Model
- •Actress
- •Record Producer
- •Improve your interpreting skills
- •It ceases to be the goal. The game is what counts.
- •Скромность украшает.
- •У Нewlett-Рackard - новый президент. Карлтон фьорина сменяет платта.
- •Дело о пеликанах.
- •Кэрол Хиггинс Кларк
- •Профессор Умберто Эко.
- •Billion dollar brain.
- •Pablo Picasso's Fortune
- •The private side.
- •Taking a flier on tne web.
- •Экология человека в естественной и кибер-интеллектуальной среде
- •Introductory text
- •Artificial stupidity
- •We Are in the Middle of a Cyberwar
- •Portable databases help doctors practice more efficient.
- •A case for smokeless zones
- •In Britain’s offices).
- •Nicotine traps
- •Pipe dream
- •Speak English outside of class
- •Use a dictionary when he writs
- •Attending a conference
- •Первый раз дедушка пожаловался на ревматизм в 1812 г.
- •Воздействие (influence) компьютера на человека.
- •Флирт в сети.
- •A workaholic economy.
- •Baltic sea problems.
- •The right time and place
- •Dealing with stress
- •Pollution
- •Quatations and jokes
- •Права человека Права личности и права учащегося.
- •Introductory text age of majority (or gaining rights)
- •Intellectual property.
- •Legal Status of Engineering Societies
- •Bridging the digital divide.
- •1.Government records
- •2. Personal files
- •Book banning must be stopped
- •Five Key Questions about Modern Medical Science
- •Tenancy agreement No._______
- •Improve your interpreting skills
- •Gender in Education
- •Часть 1.
- •Часть 2.
- •Часть 3.
- •Text 4. Хакеры и «крэкеры». Agree or disagree with the author.
- •Invasion of the Sight to Privacy
- •United States Legal System
- •The whole world is watching.
- •By Jennifer Tanaka
- •Secretaries: the wasted asset.
- •Quatations and jokes
- •Список основных сокращений, используемых в деловой корреспонденции:
- •1. Post-school or tertiary education usa
- •Great britain
- •1. University people
- •1. University degrees
- •1. Grading system
- •Grades: a, d, c, d, f Quality points: 4.0, 3.5, 3.0, 2.5, 2.0,0.0
- •1. Some additional university terms
- •Неправильные глаголы
- •Unit I. Системы образования
- •Direct & Indirect Speech. Сочетания с глаголами широкой семантики:
- •Навыки перевода (Rus – Eng)
- •1. Университет...................................................................................
- •1. Grades.. As Others See Us.........................................................................................
- •Unit II. Содержание образования в разных странах
- •You Get What You Pay For* Навыки перевода (Rus – Eng)
- •Unit VII. Экология человека в естественной и кибер-интеллектуальной средe
Artificial stupidity
Creating machines that think like people is a great challenge, but a bad idea. In 1950 Alan Turing, a British mathematician of genius, challenged scientists to create a machine that could trick people into thinking it was one of them. By 2000, Turing predicted, computers would be able to trick most of the people most of the time - at least in conversations where neither party could see or hear the other, but instead "talk" by typing at computer terminals. Thanks to 40 years of research into artificial intelligence - a field which has adopted Turing's test as its semi-official goal - Turing's prediction may well come true. But it will be a dreadful anticlimax.
The most obvious problem with Turing's challenge is that there is no practical reason to create machine intelligences indistinguishable from human ones. People are in plentiful supply. Should a shortage arise, there are proven and popular methods for making more of them; these require no public subsidy and little or no technology. The point of using machines ought to be that they perform differently from people, and preferably better. If that potential is to be exploited, machines will need to be given new forms of intelligence all their own.
Gradually, this is happening. Many human capabilities remain well beyond the reach of machines. No computer can understand a fairy tale, recognise faces or navigate across a crowded room. But machines have learnt a lot. Computer chess-players can beat all but the very best humans. Machines can solve logical puzzles, apply bureaucratic rules and perform passable translations from one language to another. Computers' new skills are winning them jobs alongside decision-makers in a variety of companies, complementing human weaknesses with computer strengths.
To err is human
With skill and skullduggery, computer intelligence can already be disguised as human. Last year, in a "Turing contest" held at Boston's Computer Museum, a computer program tricked five of the ten judges into believing that it was man rather than machine. But to fit into a human mould, machines have to display human limitations as well as human skills. The judges at the Computer Museum, for example, were particularly impressed by the winning programs’ ability to imitate human typing errors. But who needs a computer that can't type?
Without such artificial stupidity, clever machines are not just people with the bugs worked out. They are different, and profoundly alien. Leave aside the things on which people and machines cannot yet be compared – bodies, sex, a social life or a childhood - and consider only reasoning. Machines can already imitate human performance on many problems, but by using utterly inhuman techniques. Computer chess-players have no concept of strategy; instead, at each turn they scan through several billion possible sequences of moves to pick the one which seems best. Computer logicians make their deductions in ways that no human would - or could. Computer bureaucrats apply the rules more tirelessly and consistently than any of their overworked human brethren. Watching such machines at work, nobody could mistake them for humans - or deny their intelligence.
No wonder. People and machines bring quite different capabilities to the task of reasoning. Human reasoning if limited by the brains that nature evolved; machines are better engineered. Plug in enough memory and a computer can remember everything that ever happened to it, or to anyone else. Given a logical problem to work out or a theoretical model of how a complicated machine works, computers can deduce more consequences more much faster than humans.
The real challenge, then, is not to recreate people but to recognise the uniqueness of machine intelligence, and learn to work with it. Surrendering the human monopoly on intelligence will be confusing and painful. But there will be large consolations. Working together, man and machine should be able to do things that neither can do separately. And as they share intelligence, humans may come to a deeper understanding of themselves. Perhaps nothing other than human intelligence - constantly struggling to recreate itself despite crumbling memories and helter-skelter reasoning - could even conceive of something as illogical and wonderful as machines that think, let alone build them and learn to live with them.
Vocabulary
artificial - искусственный
stupidity - глупость
create - создавать, творить
challenge - вызов
challenge - вызвать (на соревнование)
trick - обманывать, надувать
predict - предсказывать
neither - ни один
instead - вместо
research - исследование
intelligence - разум
adopt - принимать
come true - сбываться
dreadful - ужасный
climax - кульминация, развязка
obvious - очевидный
reason - причина
indistinguishable - неразличимый
human - человек
plentiful supply - множество
shortage - нехватка, дефицит
arise - здесь: возникать
proven - испытанный, доказанный
require - требовать
subsidy - субсидия, дотация
point -здесь: идея
perform - действовать
preferably - предпочтительно
exploit - эксплуатировать, использовать
gradually - постепенно
happen - происходить
capability - способность
remain - оставаться
beyond reach - вне достижимости
fairy tale - сказка
recognise - распознавать, узнавать
navigate - передвигаться
crowded - заполненный людьми
solve - решать
puzzle -загадка, головоломка
apply - применять
passable - сносный
skill - умение
alongside - наряду (с), рядом
variety - здесь: ряд
complement - дополнять
weakness - слабая сторона, минус
strength - сильная торона, плюс
err - ошибаться
skulduggery - надувательство
disguise - маскироваться
contest - состязание
judge - судья
rather than - а не
fit into a human mould - уподобиться человеку
display - проявлять
limitation - ограничение
particularly - особенно
impress - впечатлять, поражать
error - ошибаться
type - печатать
bug - разг.: неполадка, дефект
leave aside - оставить без внимания
compare - сравнивать
body - тело
sex - пол (мужской/женский)
consider - принимать во внимание, рассматривать
reasoning - рассуждение, аргументация
utterly - совершенно
concept - концепция, идея
scan - (бегло) просматривать
sequence - последовательность
pick - выбрать
deduction - вывод, заключение
tireslessly - неутомимо, неустанно
consistently - последовательно, упорно
overworked - переутомленный
brethren - мн.ч. братья, собратья
deny - отрицать
no wonder - неудивительно
brains - разум, мозг
evolve - развивать(ся), эволюционировать
plug in - подключать
recreate - освободить, дать отдых
surrender - уступать
confuse - приводить в замешательство
painful - болезненный
neither - ни один
consolation - утешение
share - делиться
crumble - рушиться, блекнуть
helter-skelter - беспорядок, суматоха
Word Study.
Ex. 1. Match the words with their Russian equivalents:
utterly a/ неудивительно
complicated b/ очевидный
logician c/ переутомленный
sequence d/ неутомимо
5. brains e/ сложный
brethren f/ последовательность
no wonder g/ совершенно
consistently h/ концепция, идея
overworked i/ разум
10. concept g/ последовательно, упорно
tirelessly h/ братья, собратья
12. obvious i/ логик
Ex. 2. Match the verbs with their Russian equivalents:
to deduce a/ творить
To plug in b/ требовать(ся)
To deny c/ дополнять
To evolve d/ узнавать
To remain e/ отрицать
6. To pick f/ передвигаться
To create g/ ошибаться
9. To recognise h/ маскировать(ся)
To accept i/ обманывать, надувать
To compare j/ предсказывать
11. To trick k/ сравнивать
to complement l/ эволюционировать
To navigate m/ выбирать
To perform n/ принимать
To require о/ бегло просматривать
16. To despise p/ оставаться
To predict q/ действовать
To scan r/ делать выводы
19. To err s/ включать в эл.сеть
Ex. 3. Match the phrases with their Russian equivalents:
to come true a/ чисто человеческий
To display human limitations b/ доказанный метод
3. semi-official goal c/ разбиение на категории
in plentiful supply d/ решать головоломки
merely human e/ множество
To define precisely f/ задача аргументирования
7. who needs it g/ очевидная проблема
assigning into categories h/ сбываться
To solve puzzles i/ точно определять
10. proven method g/ ошибочно принимать за людей
obvious problem k/ проявлять человеческие ограничения
task of reasoning l/ последовательность ходов
13. To mistake for humans m/ полу-официальная цель
sequence of moves n/ подключить память
typing error o/ применять правила
16. To plug in memory p/ имитировать ошибки
unravel mysteries q/ государственная дотация
To make deductions r/ сбываться
19. public subsidiary s/ кому это нужно
To imitate errors t/ ошибочная логика
faulty logic u/ печатные ошибки
22. To apply rules v/ делать заключения, выводы
Ex. 4. Translate the following sentences into English.
Алан Туринг и другие ученые решили создать компьютер, который мог бы обманывать людей, заставляя их думать, что он (ПК) - один из них.
Благодаря 40 годам исследования искусственного разума их полуофициальная цель стала возможной.
На самом деле, нет практической причины создавать машины, неотличимые от человека.
В случае возникновения дефицита, есть опробированные методы, которые не требуют государственных дотаций.
Ни один компьютер не может понимать сказки, узнавать лица или передвигаться по комнате, полной людей.
Компьютеры-шахматисты могут побить любого человека-шахматиста.
Умение ошибаться - это чисто человеческая черта (feature).
Посредством надувательства, компьютерный разум может быть замаскирован под человеческий.
На прошлом "Состязании Туринга" компьютерная программа обманула пять из десяти судей, заставив их думать, что они "общались" с человеком, а не с машиной.
Чтобы "уподобиться" человеку (to fit into human's mould), машины должны проявлять человеческие ограничения, равно как и человнческие умения.
Судьи, например, были поражены программой, которая могла имитировать печатные ошибки.
Но кому нужен компьютер, который не умеет печатать?
Компьютер применяет правила более неустанно и последовательно, чем любой из его переутомленных собратьев.
Даже разбиение слов на классы человек и машина делают по-разному.
Comprehension Check.
Answer the following questions:
1. What task did Alan Turing offer to other scientists in 1950?
2. What was his prediction?
3. What was the most obvious problem with Turing's challenge?
4. What can computers do?
5. Did the computer's program in a "Turing's Contest" manage to trick the judges?
6. What were they particularly impressed by?
7. Which things can't people and machines be compared on?
Topics to Discuss.
1. Computer and human chess-players.
Task of reasoning for people and machines.
Text 1C