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Texto associado
Access to affordable credit is fundamental to personal resilience and economic advancement. It helps fund housing, education, small businesses, and insurance to protect against financial shocks. Globally, 1.4 billion adults have no access to formal financial services because they lack a credit history, which is only acquired once someone has been granted credit. This paradox means millions of people are financially excluded.
This is not only a problem in emerging and developing markets, but also in developed markets like the US and the UK where millions remain underserved: approximately 45 million Americans are either credit invisible or have unscorable credit files, and around 5 million UK residents lack a mainstream credit history. For financial institutions, this represents not just a moral imperative, but also a major opportunity to unlock a new and largely untapped market through innovative and ethical data use.
Grocery shopping data is emerging as one of the most powerful alternative data sources for understanding the financial behavior of "credit invisibles". These four key characteristics highlight why grocery data is so insightful for credit scoring people with no credit history: universality, recency, granularity and frequency. Everyone buys groceries. Grocery shopping is a universal necessity that cuts across socioeconomic, geographic, and demographic boundaries. This makes grocery data uniquely representative of the broader population, which is a rare attribute among alternative data sources. Unlike many traditional data sources, grocery data is continually refreshed. Most consumers shop for groceries weekly, if not more often. This regularity offers a real-time view into consumer behavior, enabling financial institutions to assess an individual's current financial situation with striking accuracy. Grocery shopping data captures detailed behavioral signals. For example, consistent purchasing of staple goods at the same time each month can indicate budgeting discipline. Price sensitivity and use of discounts may suggest cautious financial management. A high-percentage of healthy food items and lack of junk food can be an indicator of financial responsibility. The high frequency of grocery shopping offers a dense timeline of behavioral data, allowing models to detect consistent financial habits, patterns, and anomalies. Unlike once-off data points like loan applications, grocery data builds a behavioral track record over time.
Research by scholars at Rice University, the University of Notre Dame, and Northwestern University found that variables such as shopping frequency, consistency in spending, choice of products, and use of discount programs correlate strongly with credit risk profiles. Importantly, it demonstrated that these behavioral patterns could significantly improve the predictive power of credit models, particularly for consumers without formal credit histories.
Grocery shopping data is recent, frequent, universal, and rich in behavioral insights. Coupled with banking data within a privacy-preserving data collaboration environment, it's opening the path to financial inclusion and protection for millions. Financial inclusion has remained out of reach for far too many, for far too long. Grocery data, used responsibly and collaboratively, may be the innovation that changes that at scale.
Available at: . Retrieved on: October 26, 2025. Adapted.

In paragraph 5, the sentence "Financial inclusion has remained out of reach for far too many, for far too long" means that

A for many years, a large number of people have remained unable to access affordable credit.
B in a long time, banks and governmental administration were unable to collaborate systematically.
C many people have not been interested in becoming eligible for low-income credit access programs lately.
D despite the new technology, most people do not have access to e-commerce, because they are in debt.
E the increase in the credit card eligibility has contributed to higher profits for financial institutions.
Texto associado
Access to affordable credit is fundamental to personal resilience and economic advancement. It helps fund housing, education, small businesses, and insurance to protect against financial shocks. Globally, 1.4 billion adults have no access to formal financial services because they lack a credit history, which is only acquired once someone has been granted credit. This paradox means millions of people are financially excluded.
This is not only a problem in emerging and developing markets, but also in developed markets like the US and the UK where millions remain underserved: approximately 45 million Americans are either credit invisible or have unscorable credit files, and around 5 million UK residents lack a mainstream credit history. For financial institutions, this represents not just a moral imperative, but also a major opportunity to unlock a new and largely untapped market through innovative and ethical data use.
Grocery shopping data is emerging as one of the most powerful alternative data sources for understanding the financial behavior of "credit invisibles". These four key characteristics highlight why grocery data is so insightful for credit scoring people with no credit history: universality, recency, granularity and frequency. Everyone buys groceries. Grocery shopping is a universal necessity that cuts across socioeconomic, geographic, and demographic boundaries. This makes grocery data uniquely representative of the broader population, which is a rare attribute among alternative data sources. Unlike many traditional data sources, grocery data is continually refreshed. Most consumers shop for groceries weekly, if not more often. This regularity offers a real-time view into consumer behavior, enabling financial institutions to assess an individual's current financial situation with striking accuracy. Grocery shopping data captures detailed behavioral signals. For example, consistent purchasing of staple goods at the same time each month can indicate budgeting discipline. Price sensitivity and use of discounts may suggest cautious financial management. A high-percentage of healthy food items and lack of junk food can be an indicator of financial responsibility. The high frequency of grocery shopping offers a dense timeline of behavioral data, allowing models to detect consistent financial habits, patterns, and anomalies. Unlike once-off data points like loan applications, grocery data builds a behavioral track record over time.
Research by scholars at Rice University, the University of Notre Dame, and Northwestern University found that variables such as shopping frequency, consistency in spending, choice of products, and use of discount programs correlate strongly with credit risk profiles. Importantly, it demonstrated that these behavioral patterns could significantly improve the predictive power of credit models, particularly for consumers without formal credit histories.
Grocery shopping data is recent, frequent, universal, and rich in behavioral insights. Coupled with banking data within a privacy-preserving data collaboration environment, it's opening the path to financial inclusion and protection for millions. Financial inclusion has remained out of reach for far too many, for far too long. Grocery data, used responsibly and collaboratively, may be the innovation that changes that at scale.
Available at: . Retrieved on: October 26, 2025. Adapted.

In the section of paragraph 3 "These four key characteristics highlight why grocery data is so insightful for credit scoring people with no credit history", the term key can be substituted, with no change in meaning, by

A important
B casual
C peripheral
D unusual
E minor
Texto associado
Access to affordable credit is fundamental to personal resilience and economic advancement. It helps fund housing, education, small businesses, and insurance to protect against financial shocks. Globally, 1.4 billion adults have no access to formal financial services because they lack a credit history, which is only acquired once someone has been granted credit. This paradox means millions of people are financially excluded.
This is not only a problem in emerging and developing markets, but also in developed markets like the US and the UK where millions remain underserved: approximately 45 million Americans are either credit invisible or have unscorable credit files, and around 5 million UK residents lack a mainstream credit history. For financial institutions, this represents not just a moral imperative, but also a major opportunity to unlock a new and largely untapped market through innovative and ethical data use.
Grocery shopping data is emerging as one of the most powerful alternative data sources for understanding the financial behavior of "credit invisibles". These four key characteristics highlight why grocery data is so insightful for credit scoring people with no credit history: universality, recency, granularity and frequency. Everyone buys groceries. Grocery shopping is a universal necessity that cuts across socioeconomic, geographic, and demographic boundaries. This makes grocery data uniquely representative of the broader population, which is a rare attribute among alternative data sources. Unlike many traditional data sources, grocery data is continually refreshed. Most consumers shop for groceries weekly, if not more often. This regularity offers a real-time view into consumer behavior, enabling financial institutions to assess an individual's current financial situation with striking accuracy. Grocery shopping data captures detailed behavioral signals. For example, consistent purchasing of staple goods at the same time each month can indicate budgeting discipline. Price sensitivity and use of discounts may suggest cautious financial management. A high-percentage of healthy food items and lack of junk food can be an indicator of financial responsibility. The high frequency of grocery shopping offers a dense timeline of behavioral data, allowing models to detect consistent financial habits, patterns, and anomalies. Unlike once-off data points like loan applications, grocery data builds a behavioral track record over time.
Research by scholars at Rice University, the University of Notre Dame, and Northwestern University found that variables such as shopping frequency, consistency in spending, choice of products, and use of discount programs correlate strongly with credit risk profiles. Importantly, it demonstrated that these behavioral patterns could significantly improve the predictive power of credit models, particularly for consumers without formal credit histories.
Grocery shopping data is recent, frequent, universal, and rich in behavioral insights. Coupled with banking data within a privacy-preserving data collaboration environment, it's opening the path to financial inclusion and protection for millions. Financial inclusion has remained out of reach for far too many, for far too long. Grocery data, used responsibly and collaboratively, may be the innovation that changes that at scale.
Available at: . Retrieved on: October 26, 2025. Adapted.

In the fragment of paragraph 2, "this represents not just a moral imperative, but also a major opportunity to unlock a new and largely untapped market", the linking words not just... but also indicate a(an)

A absolute alternative
B brief comparison
C clear contrast
D deep consequence
E emphatic addition
Texto associado
Access to affordable credit is fundamental to personal resilience and economic advancement. It helps fund housing, education, small businesses, and insurance to protect against financial shocks. Globally, 1.4 billion adults have no access to formal financial services because they lack a credit history, which is only acquired once someone has been granted credit. This paradox means millions of people are financially excluded.
This is not only a problem in emerging and developing markets, but also in developed markets like the US and the UK where millions remain underserved: approximately 45 million Americans are either credit invisible or have unscorable credit files, and around 5 million UK residents lack a mainstream credit history. For financial institutions, this represents not just a moral imperative, but also a major opportunity to unlock a new and largely untapped market through innovative and ethical data use.
Grocery shopping data is emerging as one of the most powerful alternative data sources for understanding the financial behavior of "credit invisibles". These four key characteristics highlight why grocery data is so insightful for credit scoring people with no credit history: universality, recency, granularity and frequency. Everyone buys groceries. Grocery shopping is a universal necessity that cuts across socioeconomic, geographic, and demographic boundaries. This makes grocery data uniquely representative of the broader population, which is a rare attribute among alternative data sources. Unlike many traditional data sources, grocery data is continually refreshed. Most consumers shop for groceries weekly, if not more often. This regularity offers a real-time view into consumer behavior, enabling financial institutions to assess an individual's current financial situation with striking accuracy. Grocery shopping data captures detailed behavioral signals. For example, consistent purchasing of staple goods at the same time each month can indicate budgeting discipline. Price sensitivity and use of discounts may suggest cautious financial management. A high-percentage of healthy food items and lack of junk food can be an indicator of financial responsibility. The high frequency of grocery shopping offers a dense timeline of behavioral data, allowing models to detect consistent financial habits, patterns, and anomalies. Unlike once-off data points like loan applications, grocery data builds a behavioral track record over time.
Research by scholars at Rice University, the University of Notre Dame, and Northwestern University found that variables such as shopping frequency, consistency in spending, choice of products, and use of discount programs correlate strongly with credit risk profiles. Importantly, it demonstrated that these behavioral patterns could significantly improve the predictive power of credit models, particularly for consumers without formal credit histories.
Grocery shopping data is recent, frequent, universal, and rich in behavioral insights. Coupled with banking data within a privacy-preserving data collaboration environment, it's opening the path to financial inclusion and protection for millions. Financial inclusion has remained out of reach for far too many, for far too long. Grocery data, used responsibly and collaboratively, may be the innovation that changes that at scale.
Available at: . Retrieved on: October 26, 2025. Adapted.

In the excerpt of paragraph 1, "Globally, 1.4 billion adults have no access to formal financial services because they lack a credit history", the pronoun they refers to

A formal financial services
B 1.4 billion adults
C credit history
D globally
E access
Texto associado
Access to affordable credit is fundamental to personal resilience and economic advancement. It helps fund housing, education, small businesses, and insurance to protect against financial shocks. Globally, 1.4 billion adults have no access to formal financial services because they lack a credit history, which is only acquired once someone has been granted credit. This paradox means millions of people are financially excluded.
This is not only a problem in emerging and developing markets, but also in developed markets like the US and the UK where millions remain underserved: approximately 45 million Americans are either credit invisible or have unscorable credit files, and around 5 million UK residents lack a mainstream credit history. For financial institutions, this represents not just a moral imperative, but also a major opportunity to unlock a new and largely untapped market through innovative and ethical data use.
Grocery shopping data is emerging as one of the most powerful alternative data sources for understanding the financial behavior of "credit invisibles". These four key characteristics highlight why grocery data is so insightful for credit scoring people with no credit history: universality, recency, granularity and frequency. Everyone buys groceries. Grocery shopping is a universal necessity that cuts across socioeconomic, geographic, and demographic boundaries. This makes grocery data uniquely representative of the broader population, which is a rare attribute among alternative data sources. Unlike many traditional data sources, grocery data is continually refreshed. Most consumers shop for groceries weekly, if not more often. This regularity offers a real-time view into consumer behavior, enabling financial institutions to assess an individual's current financial situation with striking accuracy. Grocery shopping data captures detailed behavioral signals. For example, consistent purchasing of staple goods at the same time each month can indicate budgeting discipline. Price sensitivity and use of discounts may suggest cautious financial management. A high-percentage of healthy food items and lack of junk food can be an indicator of financial responsibility. The high frequency of grocery shopping offers a dense timeline of behavioral data, allowing models to detect consistent financial habits, patterns, and anomalies. Unlike once-off data points like loan applications, grocery data builds a behavioral track record over time.
Research by scholars at Rice University, the University of Notre Dame, and Northwestern University found that variables such as shopping frequency, consistency in spending, choice of products, and use of discount programs correlate strongly with credit risk profiles. Importantly, it demonstrated that these behavioral patterns could significantly improve the predictive power of credit models, particularly for consumers without formal credit histories.
Grocery shopping data is recent, frequent, universal, and rich in behavioral insights. Coupled with banking data within a privacy-preserving data collaboration environment, it's opening the path to financial inclusion and protection for millions. Financial inclusion has remained out of reach for far too many, for far too long. Grocery data, used responsibly and collaboratively, may be the innovation that changes that at scale.
Available at: . Retrieved on: October 26, 2025. Adapted.

The main purpose of the text is to

A argue that customers should cultivate better buying habits so that their debt levels decrease and they can become eligible to receive credit from banking institutions.
B emphasize the need for more incisive measures to be taken by the government to curb the rise in popular debt related to monthly household purchases.
C illustrate how grocery shopping data can promote inclusion by providing insights into the financial health of individuals without a formal credit history.
D protest against the use of supermarket customers' personal data by banks and other credit institutions.
E report on the recent increase in debt among shopping center customers, due to habits that indicate consumerism.
Texto associado
Revolution Accelerated

How Digital Transformation is Shaping the Future of Banking

1 Like all businesses, banks have had to act fast to respond to the unprecedented human and economic impact of Covid-19.
2 First, they needed to keep the lights on and ensure business continuity. Second, they had to meet the changing ways customers wanted to engage. Finally, they sought to balance their business priorities with a responsibility to support society. Previous crises cast the banks as part of the problem — this time they are part of the solution.
3 Banks who have embraced modern banking technology have fared better in meeting these challenges. They’ve moved seamlessly to remote working, kept up service for their customers, coped with huge increases in demand and quickly adapted their products. In contrast, banks using legacy ‘spaghetti’ software have struggled.
4 Covid-19 has accelerated the need for modern banking technology, but it didn’t create it. Before coronavirus, the 2020s were already being framed as the decade for digital in the banking industry. Banks’ return on equity were too low and their cost-income ratios were too high. Meanwhile, regulation like open banking was disrupting the industry and increasing competition from new entrants like the GAAFAs (Google, Amazon, Alibaba, Facebook, Apple).
5 Providing seamless digital customer experiences was therefore already a ‘must’. Every year, Temenos partners with the Economist Intelligence Unit (EIU) for a global study on the future of banking. More than 300 banking leaders are interviewed from retail, commercial and private banks. Over half of these are at C-suite level.
6 In 2020, the study took place amid the Covid-19 crisis. The results give a fascinating insight into banking leaders’ approach during these unprecedented times. But they also show how they see their industry in the years to come.
7 And the findings suggest three trends which will shape the future of banking:
New technologies will be the key driver of banking transformation over the next 5 years. 77% of respondents strongly believed that Artificial Intelligence (AI) will be the most game-changing of these technologies. They see a diverse range of uses for AI — from personalised customer experience to fraud detection.
Banks will overhaul their business models to create digital ecosystems. 80% of respondents believe that banking will become part of a platform of services. 45% are committed to transforming their business models into digital ecosystems.
The sun will set on branch banking. World Bank data shows that visits to branches have been steadily declining globally over the last decade. As a result of coronavirus, customers are now more concerned about visiting their branch, and so even more people are willing to try digital applications. This combination of pandemic and increasingly transformative advanced technology has led a majority of respondents (59%) to our survey with the EIU to state that traditional branch-based banking model will be dead in just five years. That’s a 34% increase from last year.
8 The current environment is undoubtedly challenging for banks. But they have the capital, customer relationships and customer data. They are regulated. And most importantly: they still enjoy their customers’ trust.
9 In short, banks are best-placed to succeed if they commit to end-to-end digital transformation. That means a fully digital front office which creates hyper-personalized experiences and ecosystems. And a back office driving efficient operations and rapid innovation. By embracing modern banking technology, banks can support their customers today, create new value for the future and drive new levels of future growth.

Available at: . Retrieved on: July 13th, 2021. Adapted.

The overall purpose of the text is

A to explain how the banking industry works.
B to discuss the impact of the coronavirus pandemic on the health system.
C to launch new investment opportunities in the banking industry.
D to state that digital transformation in banking has been accelerated by the coronavirus pandemic.
E to promote new AI technology that will change the future of banking.
Texto associado
COVID-19 Economy: Expert insights on what you need to know

1 As we practice social distancing and businesses
struggle to adapt, it’s no secret the unique challenges
of Covid-19 are profoundly shaping our economic
climate. U.S. Bank financial industry and regulatory
affairs expert Robert Schell explains what you need
to know in this uncertain time.
• Don’t panic while things are “on pause”
2 Imagine clicking the pause button on your favorite
TV show. Whether you stopped to make dinner or put
kids to bed, hitting pause gives you time to tackle what
matters most. Today’s economy is similar. While we
prioritize health and safety, typical activities like driving
to work, eating at restaurants, traveling and attending
sporting events are on hold. This widespread social
distancing takes a toll on our economy, putting strain
on businesses and individuals alike.
3 Keep your financial habits as normal as possible
during this time. Make online purchases, order
takeout, pay bills and buy groceries. These everyday
purchases put money back into the economy and
prevent it from dipping further into a recession.
• Low interest rates could help make ends meet
4 In March, the Federal Reserve cut rates drastically
to boost economic activity and make borrowing more
affordable. For you, this means interest rates are low
for credit cards, loans and lines of credit, and even
fixed-rate mortgages. Consider taking advantage of
these low rates if you need extra help paying your
bills, keeping your business running or withstanding a
period of unemployment.
• Spend on small businesses
5 Looking to make a positive impact? Supporting
small businesses is an easy and powerful way to help.
You can order takeout, tip generously or donate to
your local brick-and-mortar retail store, if they provide
that option. Your support makes a big impact for
struggling business owners.
• Prior economic strength may help us bounce
back
6 The thriving economy of 2019 isn’t just a distant,
bittersweet memory. When our health is no longer
at risk and social distancing mandates begin to
diminish, we’ll slowly start to rebuild. The stability,
low unemployment rate and upward-trending market
we experienced prior to Covid-19 puts us in a good
position to kick-start economic activity and rebound
more quickly.

Available at . Retrieved on: Jul. 20, 2021. Adapted.

In the 4 th paragraph, in the fragment “In March, the Federal Reserve cut rates drastically to boost economic activity”, the verb cut indicates a

A habitual action repeatedly carried out by the Federal Reserve to address certain economic situations.
B future action to be carried out by the Federal Reserve to address possible problems.
C promised action to be carried out by the Federal Reserve to address the present economic challenges.
D one-time action carried out by the Federal Reserve to address the present situation.
E current action carried out by the Federal Reserve to address a permanent situation.
Texto associado
Robots, the next generation of soccer players

1 ____ If you think a robot will steal your job, you are not
alone. Soccer players should be worried too. The next
Messi probably won’t be of flesh and blood but plastic
and metal.
2 ____ The concept emerged during the conference
“Workshop on grand challenges in artificial
intelligence,” held in Tokyo in 1992, and independently,
in 1993, when Professor Alan Mackworth from
the University of Bristol in Canada described an
experiment with small soccer players in a scientific
article.
3 ____ Over 40 teams already participated in the first
RoboCup tournament in 1997, and the competition is
held every year. The RoboCup Federation wants to
play and win a game against a real-world cup humans’
team by 2050.
4 ____ The idea behind artificially intelligent players
is to investigate how robots perceive motion and
communicate with each other. Physical abilities like
walking, running, and kicking the ball while maintaining
balance are crucial to improving robots for other tasks
like rescue, home, industry, and education.
5 ____ Designing robots for sports requires much more
than experts in state-of-the-art technology. Humans
and machines do not share the same skills. Engineers
need to impose limitations on soccer robots to imitate
soccer players as much as possible and ensure
following the game’s rules.
6 ____ RoboCup Soccer Federation, the “FIFA” of robots,
which supports five leagues, imposes restrictions
on players’ design and rules of the game. Each has
its own robot design and game rules to give room
for different scientific goals. The number of players,
their size, the ball type, and the field dimensions are
different for each league.
7 ____ In the humanoid league the players are human-
like robots with human-like senses. However, they are
rather slow. Many of the skills needed to fully recreate
actual soccer player movements are still in the early
stages of research.
8 ____ The game becomes exciting for middle and small
size leagues. The models are much simpler; they
are just boxes with a cyclopean eye. Their design
focuses on team behavior: recognizing an opponent,
cooperating with team members, receiving and giving
a standard FIFA size ball.
9 ____ Today, soccer robots are entirely autonomous.
They wireless “talk” to each other, make decisions
regarding strategy in real-time, replace an “injured”
player, and shoot goals. The only person in a
RoboCup game is the referee. The team coaches
are engineers in charge of training the RoboCups’
artificial intelligence for fair play: the robots don’t
smash against each other or pull their shirts.
10 ____ The next RoboCup competition will soon be
played, virtually, with rules that will allow teams to
participate without establishing physical contact.

Available at: . Retrieved on: July 4th, 2021. Adapted.

In the sentence fragment of the fifth paragraph “ Designing robots for sports requires much more than experts in state-of-the-art technology”, the words in bold can be replaced, without any change in meaning, by the following words:

A drawing / scholars
B creating / amateurs
C planning / specialists
D finishing / professionals
E manufacturing / engineers
Texto associado
Robots, the next generation of soccer players

1 ____ If you think a robot will steal your job, you are not
alone. Soccer players should be worried too. The next
Messi probably won’t be of flesh and blood but plastic
and metal.
2 ____ The concept emerged during the conference
“Workshop on grand challenges in artificial
intelligence,” held in Tokyo in 1992, and independently,
in 1993, when Professor Alan Mackworth from
the University of Bristol in Canada described an
experiment with small soccer players in a scientific
article.
3 ____ Over 40 teams already participated in the first
RoboCup tournament in 1997, and the competition is
held every year. The RoboCup Federation wants to
play and win a game against a real-world cup humans’
team by 2050.
4 ____ The idea behind artificially intelligent players
is to investigate how robots perceive motion and
communicate with each other. Physical abilities like
walking, running, and kicking the ball while maintaining
balance are crucial to improving robots for other tasks
like rescue, home, industry, and education.
5 ____ Designing robots for sports requires much more
than experts in state-of-the-art technology. Humans
and machines do not share the same skills. Engineers
need to impose limitations on soccer robots to imitate
soccer players as much as possible and ensure
following the game’s rules.
6 ____ RoboCup Soccer Federation, the “FIFA” of robots,
which supports five leagues, imposes restrictions
on players’ design and rules of the game. Each has
its own robot design and game rules to give room
for different scientific goals. The number of players,
their size, the ball type, and the field dimensions are
different for each league.
7 ____ In the humanoid league the players are human-
like robots with human-like senses. However, they are
rather slow. Many of the skills needed to fully recreate
actual soccer player movements are still in the early
stages of research.
8 ____ The game becomes exciting for middle and small
size leagues. The models are much simpler; they
are just boxes with a cyclopean eye. Their design
focuses on team behavior: recognizing an opponent,
cooperating with team members, receiving and giving
a standard FIFA size ball.
9 ____ Today, soccer robots are entirely autonomous.
They wireless “talk” to each other, make decisions
regarding strategy in real-time, replace an “injured”
player, and shoot goals. The only person in a
RoboCup game is the referee. The team coaches
are engineers in charge of training the RoboCups’
artificial intelligence for fair play: the robots don’t
smash against each other or pull their shirts.
10 ____ The next RoboCup competition will soon be
played, virtually, with rules that will allow teams to
participate without establishing physical contact.

Available at: . Retrieved on: July 4th, 2021. Adapted.

According to the second paragraph, the concept of robotic soccer players emerged

A in 1997
B in the 1990s
C before the 1990s
D in the beginning of the 20 th century
E in the beginning of the 21 st century
Texto associado
Robots, the next generation of soccer players

1 ____ If you think a robot will steal your job, you are not
alone. Soccer players should be worried too. The next
Messi probably won’t be of flesh and blood but plastic
and metal.
2 ____ The concept emerged during the conference
“Workshop on grand challenges in artificial
intelligence,” held in Tokyo in 1992, and independently,
in 1993, when Professor Alan Mackworth from
the University of Bristol in Canada described an
experiment with small soccer players in a scientific
article.
3 ____ Over 40 teams already participated in the first
RoboCup tournament in 1997, and the competition is
held every year. The RoboCup Federation wants to
play and win a game against a real-world cup humans’
team by 2050.
4 ____ The idea behind artificially intelligent players
is to investigate how robots perceive motion and
communicate with each other. Physical abilities like
walking, running, and kicking the ball while maintaining
balance are crucial to improving robots for other tasks
like rescue, home, industry, and education.
5 ____ Designing robots for sports requires much more
than experts in state-of-the-art technology. Humans
and machines do not share the same skills. Engineers
need to impose limitations on soccer robots to imitate
soccer players as much as possible and ensure
following the game’s rules.
6 ____ RoboCup Soccer Federation, the “FIFA” of robots,
which supports five leagues, imposes restrictions
on players’ design and rules of the game. Each has
its own robot design and game rules to give room
for different scientific goals. The number of players,
their size, the ball type, and the field dimensions are
different for each league.
7 ____ In the humanoid league the players are human-
like robots with human-like senses. However, they are
rather slow. Many of the skills needed to fully recreate
actual soccer player movements are still in the early
stages of research.
8 ____ The game becomes exciting for middle and small
size leagues. The models are much simpler; they
are just boxes with a cyclopean eye. Their design
focuses on team behavior: recognizing an opponent,
cooperating with team members, receiving and giving
a standard FIFA size ball.
9 ____ Today, soccer robots are entirely autonomous.
They wireless “talk” to each other, make decisions
regarding strategy in real-time, replace an “injured”
player, and shoot goals. The only person in a
RoboCup game is the referee. The team coaches
are engineers in charge of training the RoboCups’
artificial intelligence for fair play: the robots don’t
smash against each other or pull their shirts.
10 ____ The next RoboCup competition will soon be
played, virtually, with rules that will allow teams to
participate without establishing physical contact.

Available at: . Retrieved on: July 4th, 2021. Adapted.

In paragraph 9, there is the information that in RoboCup competitions the game referee and the team coaches are

A humanoids
B computers
C real people
D robotic engineers
E virtual mechanisms