2. Questões de Concurso

Filtrar (abrir filtros)

1.386 Questões de concurso encontradas

1.386 resultados

Página 2 de 278

Questões por página:

5 10 15 20

Concurso: DATAPREV

Concurso: DATAPREV
Cargo: Analista de Processamento (Nível Superior)
Ano: 2026

Ano:

2026

Banca:

FGV

Cargo:

Analista de Processamento (Nível Superior)

Disciplina: Inglês

FC1318051

Dificuldade em análise

notificar erro

Notificar erro

Motivo:

Há um erro no enunciado e/ou alternativas

A resposta no gabarito oficial é outra

A disciplina ou assunto estão incorretos

A questão foi anulada

A questão está desatualizada

Informe mais detalhes

Erro de digitação ou português

As alternativas não aparecem

As imagens não aparecem

As imagens estão ilegíveis

Outro (especifique)

Alternativa A

Alternativa B

Alternativa C

Alternativa D

Alternativa E

Descrição

ENVIAR

Acertou

Errou

adicionar questão na lista de favoritas

remover questão da lista de favoritas

mostrar texto associado esconder texto associado

READ TEXT III AND ANSWER NEXT QUESTION.

TEXT III

From: https://images.cartoonstock.com/lowres/computers-file_cabinet-filepaperwork-unhackable-security-CS630961_low.jpg

In the cartoon, the adjective “non-hackable” refers to a system that cannot be

(a)

set up.

(b)

turned off.

(c)

shut down.

(d)

broken into.

(e)

brought back.

Responder Responder

Carregando

Comentários (0)

Carregando

Estatísticas

Carregando

Cadernos

Carregando

Anotação (0)

Concurso: DATAPREV

Concurso: DATAPREV
Cargo: Analista de Processamento (Nível Superior)
Ano: 2026

Ano:

2026

Banca:

FGV

Cargo:

Analista de Processamento (Nível Superior)

Disciplina: Inglês

FC1318050

Dificuldade em análise

notificar erro

Notificar erro

Motivo:

Há um erro no enunciado e/ou alternativas

A resposta no gabarito oficial é outra

A disciplina ou assunto estão incorretos

A questão foi anulada

A questão está desatualizada

Informe mais detalhes

Erro de digitação ou português

As alternativas não aparecem

As imagens não aparecem

As imagens estão ilegíveis

Outro (especifique)

Alternativa A

Alternativa B

Alternativa C

Alternativa D

Alternativa E

Descrição

ENVIAR

Acertou

Errou

adicionar questão na lista de favoritas

remover questão da lista de favoritas

mostrar texto associado esconder texto associado

READ TEXT III AND ANSWER NEXT QUESTION.

TEXT III

From: https://images.cartoonstock.com/lowres/computers-file_cabinet-filepaperwork-unhackable-security-CS630961_low.jpg

The phrasal verb “looking for” can be replaced, without significant change of meaning, by

(a)

seeking.

(b)

finding.

(c)

picking.

(d)

acquiring.

(e)

surveying.

Responder Responder

Carregando

Comentários (0)

Carregando

Estatísticas

Carregando

Cadernos

Carregando

Anotação (0)

Concurso: DATAPREV

Concurso: DATAPREV
Cargo: Analista de Processamento (Nível Superior)
Ano: 2026

Ano:

2026

Banca:

FGV

Cargo:

Analista de Processamento (Nível Superior)

Disciplina: Inglês

FC1318048

Dificuldade em análise

notificar erro

Notificar erro

Motivo:

Há um erro no enunciado e/ou alternativas

A resposta no gabarito oficial é outra

A disciplina ou assunto estão incorretos

A questão foi anulada

A questão está desatualizada

Informe mais detalhes

Erro de digitação ou português

As alternativas não aparecem

As imagens não aparecem

As imagens estão ilegíveis

Outro (especifique)

Alternativa A

Alternativa B

Alternativa C

Alternativa D

Alternativa E

Descrição

ENVIAR

Acertou

Errou

adicionar questão na lista de favoritas

remover questão da lista de favoritas

mostrar texto associado esconder texto associado

READ TEXT II AND ANSWER NEXT QUESTION.

TEXT II

From: https://www.rishabhsoft.com/wp-content/uploads/2024/01/Blog\Pros-andCons-of-Cloud-Computing_Image.jpg

The term “vendor lock-in” indicates the customer is in a situation that is

(a)

binding.

(b)

negligible.

(c)

forbidden.

(d)

disengaged.

(e)

unrestricted.

Responder Responder

Carregando

Comentários (0)

Carregando

Estatísticas

Carregando

Cadernos

Carregando

Anotação (0)

Concurso: DATAPREV

Concurso: DATAPREV
Cargo: Analista de Processamento (Nível Superior)
Ano: 2026

Ano:

2026

Banca:

FGV

Cargo:

Analista de Processamento (Nível Superior)

Disciplina: Inglês

FC1318046

Dificuldade em análise

notificar erro

Notificar erro

Motivo:

Há um erro no enunciado e/ou alternativas

A resposta no gabarito oficial é outra

A disciplina ou assunto estão incorretos

A questão foi anulada

A questão está desatualizada

Informe mais detalhes

Erro de digitação ou português

As alternativas não aparecem

As imagens não aparecem

As imagens estão ilegíveis

Outro (especifique)

Alternativa A

Alternativa B

Alternativa C

Alternativa D

Alternativa E

Descrição

ENVIAR

Acertou

Errou

adicionar questão na lista de favoritas

remover questão da lista de favoritas

mostrar texto associado esconder texto associado

READ TEXT I AND ANSWER NEXT QUESTION.

TEXT I

AI is getting better at writing. Humans must get better at editing.

Writing is hard. For Franz Kafka, putting words on the page was a process of “unending torments”. George Orwell said it felt like “a long bout of some painful illness”. Hunter S. Thompson, a journalist, saw it as the opposite of sex: “only good when it’s over”. Now AI has come to the rescue. Large language models (LLMs) eagerly offer reams of text without any pain or torment. Bots can spew out emails (excellently), longer prose (passably) and poetry (poorly). To them, writer’s block is a 500-sheet pack of paper: any user of an LLM can produce as many words in a day as Kafka did in his life.

For human writers this is a blessing and a curse. If you claim to be an author but use AI, you look like a fraud—bot-busting tools like Pangram are good at spotting when someone has had an AI helping hand. […]

If LLMs keep improving, in a few years they could be as good as professional wordsmiths. In the meantime, though, their baggy prose puts a premium on editing skills. After all, even the best writers need a good editor to keep them sharp. Editing is something The Economist deals with day in, day out, so here are our tips for rewriting AI prose.

First, commission well. George R.R. Martin once said the job of editors is to “clip the wings” of writers, and “tell them in which direction to fly”. When it comes to LLMs, that means giving clear instructions about exactly what you want, and asking them to refine their output as many times as necessary. You’ll get less pushback from machines than men. Mr Martin said editors were “the writer’s natural enemy”; AI would probably say “great observation!” and “love the enemy analogy!”

Second, pay attention to detail. AI writers will make mistakes and offer phrases that sound good but mean nothing. They like to lavish their prose with Latinate words, talking about the “bidirectional flow” and how to “expedite grid enhancements”; remind them that Anglo-Saxon words are often punchier. They like clichéd metaphors: there are lots of “Achilles’ heels”. And AI tends to use the “rule of three” far more than humans. The Economist also likes this rhetorical trick. But whereas we try to group three sensible bits of advice, AI offers such redundant sentences as: “The mystery has been solved—not partially, not ambiguously, but definitively.” Such lines should be cut—definitively.

Finally, know your audience. The editor is an intermediary between writer and reader. LLMs are sycophants and their smarmy tone is often off-key. If you are writing an email to break some bad news to your boss, tell your bot to skip the exclamation marks. AI can be pretentious or pontificating (it was trained on human writing, after all). Most people are short of time, but a verbose AI pins you to the wall like a bore at a party.

“Write drunk, edit sober, ” goes the old writers’ maxim. If that’s right, when the AI-human team gets down to work, the AIs will have all the fun.

Adapted from https://www.economist.com/leaders/2026/07/30/ai-is-gettingbetter-at-writing-humans-must-get-better-at-editing

The action mentioned in “skip the exclamation marks” (6^th paragraph) is semantically equivalent to

(a)

bring in.

(b)

carry on.

(c)

put back.

(d)

leave out.

(e)

move around.

Responder Responder

Carregando

Comentários (0)

Carregando

Estatísticas

Carregando

Cadernos

Carregando

Anotação (0)

Concurso: DATAPREV

Concurso: DATAPREV
Cargo: Analista de Processamento (Nível Superior)
Ano: 2026

Ano:

2026

Banca:

FGV

Cargo:

Analista de Processamento (Nível Superior)

Disciplina: Inglês

FC1318045

Dificuldade em análise

notificar erro

Notificar erro

Motivo:

Há um erro no enunciado e/ou alternativas

A resposta no gabarito oficial é outra

A disciplina ou assunto estão incorretos

A questão foi anulada

A questão está desatualizada

Informe mais detalhes

Erro de digitação ou português

As alternativas não aparecem

As imagens não aparecem

As imagens estão ilegíveis

Outro (especifique)

Alternativa A

Alternativa B

Alternativa C

Alternativa D

Alternativa E

Descrição

ENVIAR

Acertou

Errou

adicionar questão na lista de favoritas

remover questão da lista de favoritas

mostrar texto associado esconder texto associado

READ TEXT I AND ANSWER NEXT QUESTION.

TEXT I

AI is getting better at writing. Humans must get better at editing.

Writing is hard. For Franz Kafka, putting words on the page was a process of “unending torments”. George Orwell said it felt like “a long bout of some painful illness”. Hunter S. Thompson, a journalist, saw it as the opposite of sex: “only good when it’s over”. Now AI has come to the rescue. Large language models (LLMs) eagerly offer reams of text without any pain or torment. Bots can spew out emails (excellently), longer prose (passably) and poetry (poorly). To them, writer’s block is a 500-sheet pack of paper: any user of an LLM can produce as many words in a day as Kafka did in his life.

For human writers this is a blessing and a curse. If you claim to be an author but use AI, you look like a fraud—bot-busting tools like Pangram are good at spotting when someone has had an AI helping hand. […]

If LLMs keep improving, in a few years they could be as good as professional wordsmiths. In the meantime, though, their baggy prose puts a premium on editing skills. After all, even the best writers need a good editor to keep them sharp. Editing is something The Economist deals with day in, day out, so here are our tips for rewriting AI prose.

First, commission well. George R.R. Martin once said the job of editors is to “clip the wings” of writers, and “tell them in which direction to fly”. When it comes to LLMs, that means giving clear instructions about exactly what you want, and asking them to refine their output as many times as necessary. You’ll get less pushback from machines than men. Mr Martin said editors were “the writer’s natural enemy”; AI would probably say “great observation!” and “love the enemy analogy!”

Second, pay attention to detail. AI writers will make mistakes and offer phrases that sound good but mean nothing. They like to lavish their prose with Latinate words, talking about the “bidirectional flow” and how to “expedite grid enhancements”; remind them that Anglo-Saxon words are often punchier. They like clichéd metaphors: there are lots of “Achilles’ heels”. And AI tends to use the “rule of three” far more than humans. The Economist also likes this rhetorical trick. But whereas we try to group three sensible bits of advice, AI offers such redundant sentences as: “The mystery has been solved—not partially, not ambiguously, but definitively.” Such lines should be cut—definitively.

Finally, know your audience. The editor is an intermediary between writer and reader. LLMs are sycophants and their smarmy tone is often off-key. If you are writing an email to break some bad news to your boss, tell your bot to skip the exclamation marks. AI can be pretentious or pontificating (it was trained on human writing, after all). Most people are short of time, but a verbose AI pins you to the wall like a bore at a party.

“Write drunk, edit sober, ” goes the old writers’ maxim. If that’s right, when the AI-human team gets down to work, the AIs will have all the fun.

Adapted from https://www.economist.com/leaders/2026/07/30/ai-is-gettingbetter-at-writing-humans-must-get-better-at-editing

In the sentence “Anglo-Saxon words are often punchier” (5^th paragraph), “punchier” indicates that these words tend to be more

(a)

complex and obscure.

(b)

powerful and effective.

(c)

mysterious and intricate.

(d)

formal and sophisticated.

(e)

ambiguous and confusing.

Responder Responder

Carregando

Comentários (0)

Carregando

Estatísticas

Carregando

Cadernos

Carregando

Anotação (0)