Placement PLI (Primeira Aula)

According to the text, choose the CORRECT alternative:

• Artificial intelligence is starting to learn how to sing ‘Despacito’.
  

• Researchers are teaching Artificial Intelligence the strict definitions of the words in the dictionary.

  
  

• Artificial Intelligence is still struggling to understand sayings and idioms.
  

•  Artificial intelligence is getting the ability to recognize and interpret literal language. 

Choose the INCORRECT alternative, according to the text, about Artificial Intelligence:

• A recent research shows AI can distinguish between literal and figurative phrases in writing.

  
  

•  AI still struggles to understand humans’ intent.
  

•  There is already a system able to gauge what a person really means when speaking.

• In written communication, it is easier to understand someone’s intent because all AI has to do is string together the literal meanings of the words.

  
  

What is the best translation for the word ‘IDIOMS’ in the sentence: ‘Idioms are tricky because they can be interpreted literally or figuratively, depending on context.’?

• Expressões idiomáticas.

• Idiomas.

• Linguagens.

• Dialetos.

Which of the following statements is FALSE about emotions and the meaning of words?

• Someone’s facial expression or intonation can significantly change the implication of their words.

• AI is already able to recognize sarcasm in the words observing someone’s facial expression and tone of voice.

• Nonverbal cues, like facial expressions and voice pitch, can affect the meaning of spoken words.

• AI was 78 percent accurate in rating how much negative or positive sentiment a video subject expressed.

 Choose the alternative that can NOT replace the expression ‘STUMBLING BLOCK’ in the sentence: ‘This kind of ambiguity can be a stumbling block for AI systems that analyze sentiments expressed online or translate documents into other languages’:

• Obstacle.

• Aid.

• Difficulty.

• Barrier.

According to the text, mark the CORRECT alternative about the system that can determine whether a phrase is meant literally or figuratively:

• The same researchers are tackling similar problems with metaphor and irony.

• This system uses strict meanings of the words from the dictionary.

• This system was designed by computer scientists at Purdue University in West Lafayette, Ind.

• This system learned how to associate different words by reading sentences from Wikipedia entries.

According to the text, mark the INCORRECT alternative about Julia Rayz and her research:

• She is involved in studies about metaphor and irony.

• She studies Natural Language Processing at Purdue University in West Lafayette.

• She recognizes the importance of computers that interpret nonliteral language.

• For her, AI is becoming more and more integrated into our lives.

According to the text, mark the alternative that DOES NOT correspond to Robert West and his research:

• He believes it is possible that using AI will be nearly like talking to a human.

• In his opinion, we will never have intelligent machines.

• For him, it is essential to understand linguistic nuance to improve AI.

• He believes that, in the future, AI will become good in simple conversations.

 The sentence ‘To get around this problem, Changsheng Liu and Rebecca Hwa, computer scientists at the University of Pittsburgh, designed a system that determines whether a phrase is meant literally or figuratively based on the surrounding words.’ means that:

• The system can transform a literal sentence into a figurative one.

• The system analyzes sentiments and translates documents into other languages.

• The system is able to understand metaphors and irony.

• The system uses context to solve the problem of ambiguity in sentences.

According to the text, mark the alternative that DOES NOT correspond to Louis-Philippe Morency’s AI system:

• This system recognizes when someone’s facial expression and tone of voice are lacing their words with sarcasm.

• This system proved adept at distinguishing between different expressed emotions.

• This system identified happiness with 87.3 percent accuracy.

• This system was 78 percent accurate in rating how much negative or positive sentiment a video subject expressed.