Questões de Vestibular Comentadas sobre inglês
Foram encontradas 2.807 questões
Ano: 2024
Banca:
CESPE / CEBRASPE
Órgão:
UNB
Prova:
CESPE / CEBRASPE - 2024 - UNB - Prova de Conhecimentos I - Inglês - 1° dia |
Q3107432
Inglês
Texto associado
The term AI winter refers to a period of reduced funding
in the development of AI. In general, AI has followed a path on
which proponents overstate what is possible, inducing people
with no technology knowledge at all, but lots of money, to make
investments. A period of criticism then follows when AI fails to
meet expectations, and, finally, the reduction in funding occurs.
A number of these cycles have occurred over the years —
all of them devastating to true progress. AI is currently in a new
hype phase because of machine learning, a technology that helps
computers learn from data. Having a computer learn from data
means not depending on a human programmer to set operations
(tasks), but rather deriving them directly from examples that
show how the computer should behave. It’s like educating a baby
by showing it how to behave through example. Machine learning
has pitfalls because the computer can learn how to do things
incorrectly through careless teaching.
Scientists are working on machine learning algorithms,
each one from a different point of view. At this time, the most
successful solution is deep learning, which is a technology that
strives to imitate the human brain. Deep learning is possible
because of the availability of powerful computers, smarter
algorithms, large datasets produced by the digitalization of our
society, and huge investments from businesses such as Google,
Facebook, Amazon, and others that take advantage of this AI
renaissance for their own businesses.
People are saying that the AI winter is over because of
deep learning, and that’s true for now. However, when you look
around at the ways in which people are viewing AI, you can
easily figure out that another criticism phase will eventually
occur unless proponents tone the rhetoric down. AI can do
amazing things, but they’re a mundane sort of amazing.
John Paul Mueller and Luca Massaron. Artificial Intelligence For Dummies.
Hoboken (New Jersey): John Wiley & Sons, 2022
Judge the following items according to the previous text.
According to the second paragraph of the text, learning from data means not depending on human programming but on examples of behavior.
According to the second paragraph of the text, learning from data means not depending on human programming but on examples of behavior.
Ano: 2024
Banca:
CESPE / CEBRASPE
Órgão:
UNB
Prova:
CESPE / CEBRASPE - 2024 - UNB - Prova de Conhecimentos I - Inglês - 1° dia |
Q3107431
Inglês
Texto associado
The term AI winter refers to a period of reduced funding
in the development of AI. In general, AI has followed a path on
which proponents overstate what is possible, inducing people
with no technology knowledge at all, but lots of money, to make
investments. A period of criticism then follows when AI fails to
meet expectations, and, finally, the reduction in funding occurs.
A number of these cycles have occurred over the years —
all of them devastating to true progress. AI is currently in a new
hype phase because of machine learning, a technology that helps
computers learn from data. Having a computer learn from data
means not depending on a human programmer to set operations
(tasks), but rather deriving them directly from examples that
show how the computer should behave. It’s like educating a baby
by showing it how to behave through example. Machine learning
has pitfalls because the computer can learn how to do things
incorrectly through careless teaching.
Scientists are working on machine learning algorithms,
each one from a different point of view. At this time, the most
successful solution is deep learning, which is a technology that
strives to imitate the human brain. Deep learning is possible
because of the availability of powerful computers, smarter
algorithms, large datasets produced by the digitalization of our
society, and huge investments from businesses such as Google,
Facebook, Amazon, and others that take advantage of this AI
renaissance for their own businesses.
People are saying that the AI winter is over because of
deep learning, and that’s true for now. However, when you look
around at the ways in which people are viewing AI, you can
easily figure out that another criticism phase will eventually
occur unless proponents tone the rhetoric down. AI can do
amazing things, but they’re a mundane sort of amazing.
John Paul Mueller and Luca Massaron. Artificial Intelligence For Dummies.
Hoboken (New Jersey): John Wiley & Sons, 2022
Judge the following items according to the previous text.
Because it does not depend on human programming, machine learning does not make mistakes.
Because it does not depend on human programming, machine learning does not make mistakes.
Ano: 2024
Banca:
CESPE / CEBRASPE
Órgão:
UNB
Prova:
CESPE / CEBRASPE - 2024 - UNB - Prova de Conhecimentos I - Inglês - 1° dia |
Q3107430
Inglês
Texto associado
The term AI winter refers to a period of reduced funding
in the development of AI. In general, AI has followed a path on
which proponents overstate what is possible, inducing people
with no technology knowledge at all, but lots of money, to make
investments. A period of criticism then follows when AI fails to
meet expectations, and, finally, the reduction in funding occurs.
A number of these cycles have occurred over the years —
all of them devastating to true progress. AI is currently in a new
hype phase because of machine learning, a technology that helps
computers learn from data. Having a computer learn from data
means not depending on a human programmer to set operations
(tasks), but rather deriving them directly from examples that
show how the computer should behave. It’s like educating a baby
by showing it how to behave through example. Machine learning
has pitfalls because the computer can learn how to do things
incorrectly through careless teaching.
Scientists are working on machine learning algorithms,
each one from a different point of view. At this time, the most
successful solution is deep learning, which is a technology that
strives to imitate the human brain. Deep learning is possible
because of the availability of powerful computers, smarter
algorithms, large datasets produced by the digitalization of our
society, and huge investments from businesses such as Google,
Facebook, Amazon, and others that take advantage of this AI
renaissance for their own businesses.
People are saying that the AI winter is over because of
deep learning, and that’s true for now. However, when you look
around at the ways in which people are viewing AI, you can
easily figure out that another criticism phase will eventually
occur unless proponents tone the rhetoric down. AI can do
amazing things, but they’re a mundane sort of amazing.
John Paul Mueller and Luca Massaron. Artificial Intelligence For Dummies.
Hoboken (New Jersey): John Wiley & Sons, 2022
Judge the following items according to the previous text.
It can be inferred from the text that deep learning depends on a variety of factors, the most important of which being the investment from big businesses.
It can be inferred from the text that deep learning depends on a variety of factors, the most important of which being the investment from big businesses.
Ano: 2024
Banca:
CESPE / CEBRASPE
Órgão:
UNB
Prova:
CESPE / CEBRASPE - 2024 - UNB - Prova de Conhecimentos I - Inglês - 1° dia |
Q3107428
Inglês
Texto associado
The term AI winter refers to a period of reduced funding
in the development of AI. In general, AI has followed a path on
which proponents overstate what is possible, inducing people
with no technology knowledge at all, but lots of money, to make
investments. A period of criticism then follows when AI fails to
meet expectations, and, finally, the reduction in funding occurs.
A number of these cycles have occurred over the years —
all of them devastating to true progress. AI is currently in a new
hype phase because of machine learning, a technology that helps
computers learn from data. Having a computer learn from data
means not depending on a human programmer to set operations
(tasks), but rather deriving them directly from examples that
show how the computer should behave. It’s like educating a baby
by showing it how to behave through example. Machine learning
has pitfalls because the computer can learn how to do things
incorrectly through careless teaching.
Scientists are working on machine learning algorithms,
each one from a different point of view. At this time, the most
successful solution is deep learning, which is a technology that
strives to imitate the human brain. Deep learning is possible
because of the availability of powerful computers, smarter
algorithms, large datasets produced by the digitalization of our
society, and huge investments from businesses such as Google,
Facebook, Amazon, and others that take advantage of this AI
renaissance for their own businesses.
People are saying that the AI winter is over because of
deep learning, and that’s true for now. However, when you look
around at the ways in which people are viewing AI, you can
easily figure out that another criticism phase will eventually
occur unless proponents tone the rhetoric down. AI can do
amazing things, but they’re a mundane sort of amazing.
John Paul Mueller and Luca Massaron. Artificial Intelligence For Dummies.
Hoboken (New Jersey): John Wiley & Sons, 2022
Judge the following items according to the previous text.
With the sentence “AI can do amazing things, but they’re a mundane sort of amazing”, the author indicates that he does not believe in everything AI proponents are saying AI can do.
With the sentence “AI can do amazing things, but they’re a mundane sort of amazing”, the author indicates that he does not believe in everything AI proponents are saying AI can do.
Ano: 2024
Banca:
CESPE / CEBRASPE
Órgão:
UNB
Prova:
CESPE / CEBRASPE - 2024 - UNB - Prova de Conhecimentos I - Inglês - 1° dia |
Q3107426
Inglês
Texto associado
The idea that we might one day be able to construct some
artefact which has a mind in the same sense that we have minds
is not a new one. It has featured in entertaining and frightening
fictions since Mary Shelley first conceived of Frankenstein’s
monster.
In the classic science fiction of the early to mid-twentieth
century, this idea was generally cashed out in terms of
‘mechanical men’ or robots – from the Czech word robata, which
translates roughly as the feudal term corvée, a term which refers
to the unpaid labour provided to one’s liege lord.
In more modern fiction, the idea of a mechanical mind has
given way to the now commonplace notion of a computational
artificial intelligence. The possibility of actually developing
artificial intelligence, however, is not just a question of
sufficiently advanced technology. It is rather a philosophical
question.
Matt Carter. Minds and Computers: an introduction to the philosophy of artficial intelligence. Edinburgh: Edinburgh University Press, 2007 (adapted).
About the preceding text, judge the following item.
The author suggests that the philosophical question behind the development of AI plays a more central role in the AI related debate than the advanced technology it demands.
The author suggests that the philosophical question behind the development of AI plays a more central role in the AI related debate than the advanced technology it demands.
Ano: 2024
Banca:
CESPE / CEBRASPE
Órgão:
UNB
Prova:
CESPE / CEBRASPE - 2024 - UNB - Prova de Conhecimentos I - Inglês - 1° dia |
Q3107425
Inglês
Texto associado
The idea that we might one day be able to construct some
artefact which has a mind in the same sense that we have minds
is not a new one. It has featured in entertaining and frightening
fictions since Mary Shelley first conceived of Frankenstein’s
monster.
In the classic science fiction of the early to mid-twentieth
century, this idea was generally cashed out in terms of
‘mechanical men’ or robots – from the Czech word robata, which
translates roughly as the feudal term corvée, a term which refers
to the unpaid labour provided to one’s liege lord.
In more modern fiction, the idea of a mechanical mind has
given way to the now commonplace notion of a computational
artificial intelligence. The possibility of actually developing
artificial intelligence, however, is not just a question of
sufficiently advanced technology. It is rather a philosophical
question.
Matt Carter. Minds and Computers: an introduction to the philosophy of artficial intelligence. Edinburgh: Edinburgh University Press, 2007 (adapted).
About the preceding text, judge the following item.
The text states that the idea of developing human-like minds in non-human artefacts has been part of fictional production for many decades.
The text states that the idea of developing human-like minds in non-human artefacts has been part of fictional production for many decades.
Ano: 2024
Banca:
CESPE / CEBRASPE
Órgão:
UNB
Prova:
CESPE / CEBRASPE - 2024 - UNB - Prova de Conhecimentos I - Inglês - 1° dia |
Q3107424
Inglês
Texto associado
The idea that we might one day be able to construct some
artefact which has a mind in the same sense that we have minds
is not a new one. It has featured in entertaining and frightening
fictions since Mary Shelley first conceived of Frankenstein’s
monster.
In the classic science fiction of the early to mid-twentieth
century, this idea was generally cashed out in terms of
‘mechanical men’ or robots – from the Czech word robata, which
translates roughly as the feudal term corvée, a term which refers
to the unpaid labour provided to one’s liege lord.
In more modern fiction, the idea of a mechanical mind has
given way to the now commonplace notion of a computational
artificial intelligence. The possibility of actually developing
artificial intelligence, however, is not just a question of
sufficiently advanced technology. It is rather a philosophical
question.
Matt Carter. Minds and Computers: an introduction to the philosophy of artficial intelligence. Edinburgh: Edinburgh University Press, 2007 (adapted).
About the preceding text, judge the following item.
The first sentence of the first paragraph would still keep both its original meaning and its grammar correctness if the word “might” were replaced with can.
The first sentence of the first paragraph would still keep both its original meaning and its grammar correctness if the word “might” were replaced with can.
Ano: 2024
Banca:
CESPE / CEBRASPE
Órgão:
UNB
Prova:
CESPE / CEBRASPE - 2024 - UNB - Prova de Conhecimentos I - Inglês - 1° dia |
Q3107423
Inglês
Texto associado
The idea that we might one day be able to construct some
artefact which has a mind in the same sense that we have minds
is not a new one. It has featured in entertaining and frightening
fictions since Mary Shelley first conceived of Frankenstein’s
monster.
In the classic science fiction of the early to mid-twentieth
century, this idea was generally cashed out in terms of
‘mechanical men’ or robots – from the Czech word robata, which
translates roughly as the feudal term corvée, a term which refers
to the unpaid labour provided to one’s liege lord.
In more modern fiction, the idea of a mechanical mind has
given way to the now commonplace notion of a computational
artificial intelligence. The possibility of actually developing
artificial intelligence, however, is not just a question of
sufficiently advanced technology. It is rather a philosophical
question.
Matt Carter. Minds and Computers: an introduction to the philosophy of artficial intelligence. Edinburgh: Edinburgh University Press, 2007 (adapted).
About the preceding text, judge the following item.
The word “It”, in the beginning of the second sentence of the text, refers to “some artifact which has a mind in the same sense that we have minds”.
The word “It”, in the beginning of the second sentence of the text, refers to “some artifact which has a mind in the same sense that we have minds”.
Ano: 2024
Banca:
CESPE / CEBRASPE
Órgão:
UNB
Prova:
CESPE / CEBRASPE - 2024 - UNB - Prova de Conhecimentos I - Inglês - 1° dia |
Q3107421
Inglês
Texto associado
In January 1818, Mary Shelley anonymously published a
strange little novel that would eventually make her
world-famous. Frankenstein; or, The Modern Prometheus is
the story of a scientist, Victor Frankenstein, who is driven by an
unrelenting “thirst for knowledge,” an ambition to penetrate the
secrets of nature, heaven, and Earth. He works tirelessly to
engineer a sentient being who, upon coming alive, is hideous to
him. Realizing with horror that his plan has gone awry,
Frankenstein flees his creature who in turn angrily chases him to
the end of the Earth and finally destroys him at the novel’s end.
Shelley’s dystopian tale has managed to stay relevant
since its publication. It has a riddling quality that has edified and
entertained readers for centuries, inspiring a range of
interpretations. Recently, it has been making appearances in the
heated debates over generative artificial intelligence, where it
often is evoked as a cautionary tale about the dangers of scientific
overreach. Some worry that in pursuing technologies like AI, we
are recklessly consigning our species to Victor Frankenstein’s
tragic fate. Our wonderchildren, our miraculous machines, might
ultimately destroy us. This fear is an expression of what science
fiction writer Isaac Asimov once called the “Frankenstein
complex.”
Strangely, it’s not only people who are afraid of robots
who are expressing such fears today; it is also some of the people
who are most aggressively at the forefront of technological
innovation. Elon Musk seemed to have had Mary Shelley’s story
in mind when he warned a World Government Summit in Dubai
in 2017 that sometimes “a scientist will get so engrossed in their
work that they don’t really realize the ramifications of what
they’re doing.”
Jennifer Banks. Mary Shelley’s Frankenstein can illuminate the debate over generative AI.
In: Big Think. Internet: (adapted)
Based on the previous text, judge the following item.
The last paragraph of the text states that Elon Musk was thinking of Mary Shelley when he declared scientists didn’t realize the ramifications of what they were doing.
The last paragraph of the text states that Elon Musk was thinking of Mary Shelley when he declared scientists didn’t realize the ramifications of what they were doing.
Ano: 2024
Banca:
CESPE / CEBRASPE
Órgão:
UNB
Prova:
CESPE / CEBRASPE - 2024 - UNB - Prova de Conhecimentos I - Inglês - 1° dia |
Q3107417
Inglês
Texto associado
In January 1818, Mary Shelley anonymously published a
strange little novel that would eventually make her
world-famous. Frankenstein; or, The Modern Prometheus is
the story of a scientist, Victor Frankenstein, who is driven by an
unrelenting “thirst for knowledge,” an ambition to penetrate the
secrets of nature, heaven, and Earth. He works tirelessly to
engineer a sentient being who, upon coming alive, is hideous to
him. Realizing with horror that his plan has gone awry,
Frankenstein flees his creature who in turn angrily chases him to
the end of the Earth and finally destroys him at the novel’s end.
Shelley’s dystopian tale has managed to stay relevant
since its publication. It has a riddling quality that has edified and
entertained readers for centuries, inspiring a range of
interpretations. Recently, it has been making appearances in the
heated debates over generative artificial intelligence, where it
often is evoked as a cautionary tale about the dangers of scientific
overreach. Some worry that in pursuing technologies like AI, we
are recklessly consigning our species to Victor Frankenstein’s
tragic fate. Our wonderchildren, our miraculous machines, might
ultimately destroy us. This fear is an expression of what science
fiction writer Isaac Asimov once called the “Frankenstein
complex.”
Strangely, it’s not only people who are afraid of robots
who are expressing such fears today; it is also some of the people
who are most aggressively at the forefront of technological
innovation. Elon Musk seemed to have had Mary Shelley’s story
in mind when he warned a World Government Summit in Dubai
in 2017 that sometimes “a scientist will get so engrossed in their
work that they don’t really realize the ramifications of what
they’re doing.”
Jennifer Banks. Mary Shelley’s Frankenstein can illuminate the debate over generative AI.
In: Big Think. Internet: (adapted)
Based on the previous text, judge the following item.
According to the text, at the end of Mary Shelley’s novel, Doctor Frankenstein kills the monster he created.
According to the text, at the end of Mary Shelley’s novel, Doctor Frankenstein kills the monster he created.
Ano: 2024
Banca:
CESPE / CEBRASPE
Órgão:
UNB
Prova:
CESPE / CEBRASPE - 2024 - UNB - Prova de Conhecimentos I - Inglês - 1° dia |
Q3107416
Inglês
Texto associado
In January 1818, Mary Shelley anonymously published a
strange little novel that would eventually make her
world-famous. Frankenstein; or, The Modern Prometheus is
the story of a scientist, Victor Frankenstein, who is driven by an
unrelenting “thirst for knowledge,” an ambition to penetrate the
secrets of nature, heaven, and Earth. He works tirelessly to
engineer a sentient being who, upon coming alive, is hideous to
him. Realizing with horror that his plan has gone awry,
Frankenstein flees his creature who in turn angrily chases him to
the end of the Earth and finally destroys him at the novel’s end.
Shelley’s dystopian tale has managed to stay relevant
since its publication. It has a riddling quality that has edified and
entertained readers for centuries, inspiring a range of
interpretations. Recently, it has been making appearances in the
heated debates over generative artificial intelligence, where it
often is evoked as a cautionary tale about the dangers of scientific
overreach. Some worry that in pursuing technologies like AI, we
are recklessly consigning our species to Victor Frankenstein’s
tragic fate. Our wonderchildren, our miraculous machines, might
ultimately destroy us. This fear is an expression of what science
fiction writer Isaac Asimov once called the “Frankenstein
complex.”
Strangely, it’s not only people who are afraid of robots
who are expressing such fears today; it is also some of the people
who are most aggressively at the forefront of technological
innovation. Elon Musk seemed to have had Mary Shelley’s story
in mind when he warned a World Government Summit in Dubai
in 2017 that sometimes “a scientist will get so engrossed in their
work that they don’t really realize the ramifications of what
they’re doing.”
Jennifer Banks. Mary Shelley’s Frankenstein can illuminate the debate over generative AI.
In: Big Think. Internet: (adapted)
Based on the previous text, judge the following item.
In the second sentence of the first paragraph, the excerpt “an ambition to penetrate the secrets of nature, heaven, and Earth” can be understood as an explanation for the “unrelenting ‘thirst of knowledge’” that drove Victor Frankenstein.
Ano: 2024
Banca:
COMVEST - UNICAMP
Órgão:
UNICAMP
Prova:
COMVEST - UNICAMP - 2024 - UNICAMP - Vestibular |
Q3107204
Inglês
Leia o resumo de uma pesquisa que, em 2021, já alertava para
questões climáticas e fatores a elas relacionados.
Politics of attributing extreme events to climate change
Climate change shapes weather events. However, describing it as the cause of disasters can be misleading, since disasters are caused by pre-existing fragilities and inequalities on the ground. Attribution is not neutral. Hence, analytic frames that attribute disaster to climate can divert attention from place-based vulnerabilities and their sociopolitical causes. While politicians may blame climate change, the public may hold the government accountable for inadequate investments in flood or drought prevention. To be strategic and moral, framing choices must therefore be sensitive to context and to how the values implicit within analytic frames about the causes of disasters shape policy responses. Such sensitivity requires multicausal analysis of weather-linked disasters to reduce the damages. Through examples from around the world, especially Brazil, we discuss how and why climate-centric disaster framing can erase from view—and, thus, from policy agendas—the very socioeconomic and political factors that centrally cause vulnerability and suffering in weather extremes.
(Adaptado de https://wires.onlinelibrary.wiley.com/doi/full/10.1002/wcc.750. Acesso em 15/05/2024.)
Qual alternativa expressa corretamente os argumentos dos autores do texto?
Politics of attributing extreme events to climate change
Climate change shapes weather events. However, describing it as the cause of disasters can be misleading, since disasters are caused by pre-existing fragilities and inequalities on the ground. Attribution is not neutral. Hence, analytic frames that attribute disaster to climate can divert attention from place-based vulnerabilities and their sociopolitical causes. While politicians may blame climate change, the public may hold the government accountable for inadequate investments in flood or drought prevention. To be strategic and moral, framing choices must therefore be sensitive to context and to how the values implicit within analytic frames about the causes of disasters shape policy responses. Such sensitivity requires multicausal analysis of weather-linked disasters to reduce the damages. Through examples from around the world, especially Brazil, we discuss how and why climate-centric disaster framing can erase from view—and, thus, from policy agendas—the very socioeconomic and political factors that centrally cause vulnerability and suffering in weather extremes.
(Adaptado de https://wires.onlinelibrary.wiley.com/doi/full/10.1002/wcc.750. Acesso em 15/05/2024.)
Qual alternativa expressa corretamente os argumentos dos autores do texto?
Ano: 2024
Banca:
COMVEST - UNICAMP
Órgão:
UNICAMP
Prova:
COMVEST - UNICAMP - 2024 - UNICAMP - Vestibular |
Q3107202
Inglês
Texto associado
Texto 1
The fact that so few African Americans write science fiction is
perplexing since they, in a very real sense, inhabit a sci-fi nightmare
in which unseen but no less palpable acts of intolerance frustrate
their movement; official histories undo what has been done;
and technology is too often brought to bear on black bodies.
Moreover, the sublegitimate status of science fiction in literature
mirrors the subaltern position to which blacks have been relegated
throughout American history. The notion of Afrofuturism gives
rise to a troubling antinomy: can a community whose past has
been deliberately rubbed out, and whose energies have been
consumed by the search for legible traces of its history, imagine
possible futures?
(Adaptado de DERY, M. Black to the future: interviews with Samuel R. Delany, Greg Tate,
and Tricia Rose. In: ___. (Ed.) The Discourse of cyberculture. Durham; London: Duke
University Press, p. 179-222, 1994.)
Texto 2
“Parable of the Talents” (Octavia E. Butler)
“To survive, Let the past Teach you-- Past customs, Struggles, Leaders and thinkers. Let These Help you. Let them inspire you, Warn you, Give you strength. But beware: God is Change. Past is past. What was Cannot Come again. To survive, know the past. Let it touch you. Then let The past Go.”
(BUTLER, Octavia E. Parable of the Talents. New York, Durham and London: Open Road, 1998.)
O texto 2 toca em um aspecto central do afrofuturismo e remete ao tema do questionamento do texto 1. Assim, pode-se dizer que o poema reconhece que
“Parable of the Talents” (Octavia E. Butler)
“To survive, Let the past Teach you-- Past customs, Struggles, Leaders and thinkers. Let These Help you. Let them inspire you, Warn you, Give you strength. But beware: God is Change. Past is past. What was Cannot Come again. To survive, know the past. Let it touch you. Then let The past Go.”
(BUTLER, Octavia E. Parable of the Talents. New York, Durham and London: Open Road, 1998.)
O texto 2 toca em um aspecto central do afrofuturismo e remete ao tema do questionamento do texto 1. Assim, pode-se dizer que o poema reconhece que
Ano: 2024
Banca:
COMVEST - UNICAMP
Órgão:
UNICAMP
Prova:
COMVEST - UNICAMP - 2024 - UNICAMP - Vestibular |
Q3107201
Inglês
Texto associado
Texto 1
The fact that so few African Americans write science fiction is
perplexing since they, in a very real sense, inhabit a sci-fi nightmare
in which unseen but no less palpable acts of intolerance frustrate
their movement; official histories undo what has been done;
and technology is too often brought to bear on black bodies.
Moreover, the sublegitimate status of science fiction in literature
mirrors the subaltern position to which blacks have been relegated
throughout American history. The notion of Afrofuturism gives
rise to a troubling antinomy: can a community whose past has
been deliberately rubbed out, and whose energies have been
consumed by the search for legible traces of its history, imagine
possible futures?
(Adaptado de DERY, M. Black to the future: interviews with Samuel R. Delany, Greg Tate,
and Tricia Rose. In: ___. (Ed.) The Discourse of cyberculture. Durham; London: Duke
University Press, p. 179-222, 1994.)
De acordo com o texto 1, a escassez de autores afro-americanos
em obras de ficção científica representa um
Ano: 2024
Banca:
COMVEST - UNICAMP
Órgão:
UNICAMP
Prova:
COMVEST - UNICAMP - 2024 - UNICAMP - Vestibular |
Q3107198
Inglês
Leia o texto a seguir.
Police under fire after threat to arrest
‘openly Jewish’ man near pro-Palestinian
protest
Scotland Yard criticised after suggesting Gideon Falter’s presence was ‘provocative’ and he was ‘antagonising’ protesters
(https://www.telegraph.co.uk/news/2024/04/19/. Acesso em 20/04/2024.)
Depreende-se, da leitura desse texto, que
Q4150348
Inglês
Texto associado
British workers are increasingly likely to work into their
70s, according to a research that found the cost of living
crisis has left older people with little choice but to stay in
employment. There were 446,601 people above the age of 70
still in work in 2022, a rise of 61% compared with 277,926 in
2012, said Rest Less, an online community for the over-50s
that offers advice to older workers.
While most of the over-70s workforce is male, the rise has
been more significant among women, most likely in response
to the gradual equalisation of pension ages between 2010
and 2020. Women were previously able to retire five years
earlier. The number of women working beyond the age of 70
is up 66% since 2012, compared with an increase of 58% for
men.
Stuart Lewis, the chief executive of Rest Less, drew a
comparison between older workers and King Charles, but
acknowledged that most continue working “for very different
reasons” to the hereditary monarch. “At the age of 74, King
Charles is a fantastic example of someone who both enjoys,
and benefits from, continuing to work post-state pension1
age,” said Lewis. “Our latest analysis shows that there are
far more over-70s in the workplace today than a decade ago.
Until Covid hit and life expectancy dropped for the first time
in a decade, there were more people reaching their state
pension age than ever before, which meant there were more
experienced people in the workplace than ever before too.”
Lewis said many of those reaching the theoretical age of
retirement were staying in the workplace for lack of any other
option. “Like King Charles, many of these people will have no
choice but to work, although for very different reasons to the
king. We see many older workers today who are struggling
to survive amidst the cost of living crisis, with inadequate
retirement savings meaning they must work in order to survive
financially.” The state pension age in the United Kingdom (UK)
is 66 for men and women but is due to start rising from 2026.
(Rob Davies. www.theguardian.com, 30.04.2023. Adaptado.)
1
state pension: a regular payment from the government to someone
who does not work anymore.
No trecho do quarto parágrafo “in order to survive financially”,
a expressão sublinhada transmite a ideia de
Q4150347
Inglês
Texto associado
British workers are increasingly likely to work into their
70s, according to a research that found the cost of living
crisis has left older people with little choice but to stay in
employment. There were 446,601 people above the age of 70
still in work in 2022, a rise of 61% compared with 277,926 in
2012, said Rest Less, an online community for the over-50s
that offers advice to older workers.
While most of the over-70s workforce is male, the rise has
been more significant among women, most likely in response
to the gradual equalisation of pension ages between 2010
and 2020. Women were previously able to retire five years
earlier. The number of women working beyond the age of 70
is up 66% since 2012, compared with an increase of 58% for
men.
Stuart Lewis, the chief executive of Rest Less, drew a
comparison between older workers and King Charles, but
acknowledged that most continue working “for very different
reasons” to the hereditary monarch. “At the age of 74, King
Charles is a fantastic example of someone who both enjoys,
and benefits from, continuing to work post-state pension1
age,” said Lewis. “Our latest analysis shows that there are
far more over-70s in the workplace today than a decade ago.
Until Covid hit and life expectancy dropped for the first time
in a decade, there were more people reaching their state
pension age than ever before, which meant there were more
experienced people in the workplace than ever before too.”
Lewis said many of those reaching the theoretical age of
retirement were staying in the workplace for lack of any other
option. “Like King Charles, many of these people will have no
choice but to work, although for very different reasons to the
king. We see many older workers today who are struggling
to survive amidst the cost of living crisis, with inadequate
retirement savings meaning they must work in order to survive
financially.” The state pension age in the United Kingdom (UK)
is 66 for men and women but is due to start rising from 2026.
(Rob Davies. www.theguardian.com, 30.04.2023. Adaptado.)
1
state pension: a regular payment from the government to someone
who does not work anymore.
No trecho do terceiro parágrafo “most continue working”, o
termo sublinhado refere-se
Q4150346
Inglês
Texto associado
British workers are increasingly likely to work into their
70s, according to a research that found the cost of living
crisis has left older people with little choice but to stay in
employment. There were 446,601 people above the age of 70
still in work in 2022, a rise of 61% compared with 277,926 in
2012, said Rest Less, an online community for the over-50s
that offers advice to older workers.
While most of the over-70s workforce is male, the rise has
been more significant among women, most likely in response
to the gradual equalisation of pension ages between 2010
and 2020. Women were previously able to retire five years
earlier. The number of women working beyond the age of 70
is up 66% since 2012, compared with an increase of 58% for
men.
Stuart Lewis, the chief executive of Rest Less, drew a
comparison between older workers and King Charles, but
acknowledged that most continue working “for very different
reasons” to the hereditary monarch. “At the age of 74, King
Charles is a fantastic example of someone who both enjoys,
and benefits from, continuing to work post-state pension1
age,” said Lewis. “Our latest analysis shows that there are
far more over-70s in the workplace today than a decade ago.
Until Covid hit and life expectancy dropped for the first time
in a decade, there were more people reaching their state
pension age than ever before, which meant there were more
experienced people in the workplace than ever before too.”
Lewis said many of those reaching the theoretical age of
retirement were staying in the workplace for lack of any other
option. “Like King Charles, many of these people will have no
choice but to work, although for very different reasons to the
king. We see many older workers today who are struggling
to survive amidst the cost of living crisis, with inadequate
retirement savings meaning they must work in order to survive
financially.” The state pension age in the United Kingdom (UK)
is 66 for men and women but is due to start rising from 2026.
(Rob Davies. www.theguardian.com, 30.04.2023. Adaptado.)
1
state pension: a regular payment from the government to someone
who does not work anymore.
De acordo com o texto,
Q4150345
Inglês
Texto associado
British workers are increasingly likely to work into their
70s, according to a research that found the cost of living
crisis has left older people with little choice but to stay in
employment. There were 446,601 people above the age of 70
still in work in 2022, a rise of 61% compared with 277,926 in
2012, said Rest Less, an online community for the over-50s
that offers advice to older workers.
While most of the over-70s workforce is male, the rise has
been more significant among women, most likely in response
to the gradual equalisation of pension ages between 2010
and 2020. Women were previously able to retire five years
earlier. The number of women working beyond the age of 70
is up 66% since 2012, compared with an increase of 58% for
men.
Stuart Lewis, the chief executive of Rest Less, drew a
comparison between older workers and King Charles, but
acknowledged that most continue working “for very different
reasons” to the hereditary monarch. “At the age of 74, King
Charles is a fantastic example of someone who both enjoys,
and benefits from, continuing to work post-state pension1
age,” said Lewis. “Our latest analysis shows that there are
far more over-70s in the workplace today than a decade ago.
Until Covid hit and life expectancy dropped for the first time
in a decade, there were more people reaching their state
pension age than ever before, which meant there were more
experienced people in the workplace than ever before too.”
Lewis said many of those reaching the theoretical age of
retirement were staying in the workplace for lack of any other
option. “Like King Charles, many of these people will have no
choice but to work, although for very different reasons to the
king. We see many older workers today who are struggling
to survive amidst the cost of living crisis, with inadequate
retirement savings meaning they must work in order to survive
financially.” The state pension age in the United Kingdom (UK)
is 66 for men and women but is due to start rising from 2026.
(Rob Davies. www.theguardian.com, 30.04.2023. Adaptado.)
1
state pension: a regular payment from the government to someone
who does not work anymore.
The main purpose of the text is to show that many British
workers over 70
Ano: 2023
Banca:
VUNESP
Órgão:
FCM/SANTA CASA
Prova:
VUNESP - 2023 - FCM/SANTA CASA - Vestibular - Medicina |
Q4149754
Inglês
Texto associado
Some of the world’s leading artificial intelligence (AI)
researchers are calling for a pause on research into AI,
claiming that safety issues must first be urgently addressed.
If not, the outcomes could be devastating for humanity.
Others say any pause in development would not only be
impractical to enforce on a global scale, but could also stand
in the way of advances that could both improve and save
lives.
The AI that is currently available already has the power
to radically alter society, in new ways that we are seeing
every day. So how might it progress over the coming years?
Are we on the brink of an artificial intelligence-powered
utopia or dystopia?
Firstly, technology has been automating jobs since the
Industrial Revolution, though never before has it happened
on this scale. Everyone from truck drivers to voice over artists
are at risk of being replaced by AI. A recent study found that
just over 30 jobs are considered safe from automation in the
near future. They range from mechanics to athletes, though
they represent just a sliver of the current labour market.
While new jobs will be created, there is a significant chance
that the majority of the population will be left jobless. This
could either lead to:
Utopia: A new leisure class emerges, living off a
universal basic income funded by taxes on robots and the
companies that operate them.
Dystopia: Mass unemployment results in social unrest,
similar to the way laid off factory workers trashed the
machines that replaced them. With so many jobs at risk and
the potential for huge wealth inequality, some fear it could
ultimately result in societal collapse.
Secondly, artificial intelligence is already contributing
to major scientific advances, dramatically accelerating
the time it takes to make discoveries. It has been used to
invent millions of materials that did not previously exist, find
potential drug molecules 1,000 times faster than previous
methods, and improve our understanding of the universe.
This could either lead to:
Utopia: Cancer and all other life-threatening diseases
are cured, leading to a new age of health and prosperity.
Scientists are already using AI tools to make breakthroughs
in longevity medicine, which aims to end or even reverse
ageing.
Dystopia: The same AI-enabled technology could
be used for malevolent purposes, creating entirely new
diseases and viruses. These could be used as bioweapons,
capable of devastating populations that don’t have access to
cures or the tech needed to develop them.
(Anthony Cuthbertson. www.independent.co.uk, 03.05.2023. Adaptado.)
In the excerpt from the seventh paragraph “which aims to end
or even reverse ageing”, the underlined word refers to
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