Category Archives: Innovation

Leadership and innovation are factors that complement each other within a company. However, if there is no capable leader, the actions and changes that promote innovation may fail.

On the other hand, if the leader does not have access to innovative techniques and ideas, it will be difficult to keep up with the market with a stagnant team and processes.

We decided to explain more about the subject to help business leaders achieve better results. Keep reading!

The importance of implementing a culture of innovation

We can see constant evolution in the market, in consumer behavior and, mainly, in technology. In the past, innovation was a choice. Today, if a company does not keep up with innovation, it loses its position in the competitive sphere.

However, it is essential to define and implement an organizational culture focused on innovation. All employees and stakeholders must be prepared for sudden changes that may impact processes.

We have already discussed the importance of analyzing organizational behavior . This is what will lead to good change management. In fact, at this stage it is possible to identify what really needs to be changed in the company to achieve certain objectives.

See below some practices of the culture of innovation and how this can impact business growth:

• Brainstorming meetings, encouraging the generation of ideas and exchanging experiences;
• Promote self-development and multi disciplinarily;
• Mapping of dynamic and collaborative processes;
• Prioritize investment in training and innovative strategies;
• Apply automation technology;
• Invest in talent retention .

In general, it is essential to create an environment in which analyzing new ideas is a natural and routine behavior, but in which all leaders and employees are comfortable.

Key Characteristics of an Innovative Leader

An innovative leader is someone who transforms a group of ideas into tangible results. In addition, they are able to guide the team towards the best path to achieve the company’s goals.

Self-knowledge

This characteristic greatly helps in the day-to-day work with employees. By recognizing their strengths and weaknesses, it is possible to hone skills that make the leader’s impact even more positive.

Always seeking to improve his knowledge and improve his work methodology with current tools and techniques.

Take the risks

We know that innovation means risk, and risk is part of the development of any business. If the leader is not yet prepared to face the challenges, he or she will likely face problems in achieving the objectives.

A good leader is one who sees challenges as opportunities for improvement, that is, has a strategic vision to overcome difficult situations and prevent other problems of the same nature from occurring in the future.

Meeting of the best talents

The talent acquisition process is entirely linked to organizational innovation. It is necessary to have a strong team to solve any problem and be willing to maximize the company’s results.

The role of the leader is fundamental in innovation. More than supporting, it is necessary to motivate so that everyone is united by the same objective.

As you can see, innovation must be embedded in the company’s DNA and become the main priority in all processes. Furthermore, it must be present in the main growth strategies.

And your company, how does it deal with Innovation Management? How about starting to implement strategies to reap great future opportunities?

In this article we will delve deeper into these issues, defining its concept, presenting its functions in our lives and, above all, reflecting on how its advancement impacts human existence, both in the technological field and in the ethical and social fields.

Understanding the origin of the term Artificial Intelligence

Even though we are not yet familiar with the subject, which is still a novelty, Artificial Intelligence has its origins many decades ago, more precisely after the Second World War. In this post-war period, the English mathematician Alan Turing published an article called ” Computing Machinery and Intelligence ” and in this text he questioned, through some tests, the capacity of machines to be intelligent.

His test, also known as The Imitation Game , or Turing test, aimed to measure the ability of a machine to exhibit intelligent behavior that matched ours. For those who wish to better understand this part of the article, there is a film called The Imitation Game , from 2014, that tells this whole story.

In 1956, years after the publication of Turing’s article, Professor John McCarthy brought the term to life, referring to the ability that machines could have to solve problems that were previously only solved by humans.

A few years later, another essential term in this field of study was introduced: Machine Learning, which gives computers the ability to learn by simply feeding an algorithm with data, and the computer would then be able to perform functions automatically. This is one of the first and greatest advances in AI.

ELIZA, who are you?

To conclude this short chronology, we come to 1964, and with it the creation of the first chatbot, the ELIZA software, a creation of the American computer scientist Joseph Weizenbaum at MIT. ELIZA chatted automatically using responses based on keywords and semantic and syntactic structure that is widely used in today’s world.

After all, what is Artificial Intelligence?

The answer in theory is simple, and can be summed up in the following line of reasoning: AI is an intelligence identical to human intelligence, but built on the basis of technological tools, and its objective is to carry out actions that, if carried out by humans, would be considered intelligent.

An AI has the ability to learn and decide, according to a rational perspective, which path to follow in a given action. It only needs to have all the necessary algorithms and data inserted in it for that path to be a valid rational option.

Thus, a machine learns and performs an action, but is not yet able to reflect on it. And this is where we come back to the beginning of the article, and the scene from the movie AI: will we one day have thinking, reflective machines, and most importantly, machines with emotions? This is a trend and also an area of ​​AI study that comes as an evolution of ANI – Weak Artificial Intelligence , a concept that we have already described in another article.

And how does an AI work?

AIs work in such a way that they simulate human intelligence perfectly. Their goal is to be able to respond to diverse demands, ranging from suggesting new films to a user of a certain streaming service, to helping consumers in an appliance store who are having after-sales problems.

It is impossible to think about our daily lives without coming across forms of artificial intelligence that are visible to our eyes. We can see it in the spell checker on our cell phones, in the shopping suggestions we receive via email or on social media. Speaking of social media, it is incredible how our news feed often seems tailored to our tastes.

Well, it is in fact made especially for you, through AI, after analyzing all the information that you unknowingly leave behind on the internet.

That said, it is easy to understand that AI works through:

• Structures used to process, divide, catalog, organize and analyze data through a data model;
• Big Data, that is, the provision of large volumes of data;
• And finally, the system’s ability to process information in order to choose the most appropriate action to take.

Machine Learning

The idea behind the concept of Machine learning is literal, that is, machine learning, which means that it will analyze all the data in its system and will learn to make decisions that match the functions it was assigned.

Let’s take as an example an AI that captures a user’s click on a baby diaper website. The system will analyze the entire path taken by the user, then combine it with the entire database it has and from there make the decision, correct from the point of view of its function, to suggest a series of websites, stores and baby products to this user.

And what normally happens in cases like this: the user ends up consuming more products from the niche, making the customer acquisition process successful, and largely due to the Artificial Intelligence that detected, gathered information, and presented specific suggestions for that potential customer.

Thus, Machine Learning is an area of ​​AI that affirms the thesis that systems learn from data and thus identify patterns and, consequently, are able to perform actions and make choices with minimal human intervention.

Deep Learning

Deep Learning is a subfield of machine learning that uses multiple layers of data and knowledge to reproduce a human neural network as faithfully as possible, and thus teach the computer how to understand and then predict certain patterns.

Deep Learning is an area that is inspired by the way our brain absorbs information and learns, which is why it is seen as a reproduction of our mechanism for thinking and choosing actions. We can conclude that Deep Learning is the closest we can get to imitating human intelligence in computers and its applications cover several areas, such as:

• Voice recognition
• Image processing
• Natural language rocessing

Artificial Intelligence in today’s world

With the inevitable advancement of technology, it is a fact that at some point we will come closer to the scenario described at the beginning of the article, where AI will be so advanced that it will look more like human systems. This scenario brings us to a series of reflections that, until now, only we, humans, can make.

What will be the limits of AI in the evolution of the world? The Battlestar Galactica series ends up offering one of these apocalyptic scenarios, which are more possible. In the plot, we have a context where technology has advanced to such an extent that the artificial intelligence used by humans has gained the status of a life form and self-awareness; however, this AI ends up rebelling against its creators because they feel that they are not valued by the human race.

Could it be that, as we advance in this area and seek to create machines with all our characteristics, we do not run the risk of being overtaken by them?

There is also the question of what are the limits of Artificial Intelligence. Will we ever have a machine that can not only simulate, but actually feel human emotions? And if that happens, even if it is hypothetical, what will be the line that defines what is human and what is machine?

AI emerges as a means of improving the functionalities of our era, and creating situations of convenience, ease and well-being for us, humans. When we come across an email offering exactly the product we were thinking of buying, the first action we usually take is to click on the suggestion and often buy that product.

What we fail to think about in cases like this is the lack of privacy and the tenuous security we currently have with our data. The case of the English company that used data from Facebook users to capture the mood of the British and thus offer material about England’s exit from the European Union is an example of the side effects that the use of AI can bring to our society.

In this article we will delve deeper into these issues, defining its concept, presenting its functions in our lives and, above all, reflecting on how its advancement impacts human existence, both in the technological field and in the ethical and social fields.

Understanding the origin of the term Artificial Intelligence

Even though we are not yet familiar with the subject, which is still a novelty, Artificial Intelligence has its origins many decades ago, more precisely after the Second World War. In this post-war period, the English mathematician Alan Turing published an article called ” Computing Machinery and Intelligence ” and in this text he questioned, through some tests, the capacity of machines to be intelligent.

His test, also known as The Imitation Game , or Turing test, aimed to measure the ability of a machine to exhibit intelligent behavior that matched ours. For those who wish to better understand this part of the article, there is a film called The Imitation Game , from 2014, that tells this whole story.

In 1956, years after the publication of Turing’s article, Professor John McCarthy brought the term to life, referring to the ability that machines could have to solve problems that were previously only solved by humans.

A few years later, another essential term in this field of study was introduced: Machine Learning, which gives computers the ability to learn by simply feeding an algorithm with data, and the computer would then be able to perform functions automatically. This is one of the first and greatest advances in AI.

ELIZA, who are you?

To conclude this short chronology, we come to 1964, and with it the creation of the first chatbot, the ELIZA software, a creation of the American computer scientist Joseph Weizenbaum at MIT. ELIZA chatted automatically using responses based on keywords and semantic and syntactic structure that is widely used in today’s world.

After all, what is Artificial Intelligence?

The answer in theory is simple, and can be summed up in the following line of reasoning: AI is an intelligence identical to human intelligence, but built on the basis of technological tools, and its objective is to carry out actions that, if carried out by humans, would be considered intelligent.

An AI has the ability to learn and decide, according to a rational perspective, which path to follow in a given action. It only needs to have all the necessary algorithms and data inserted in it for that path to be a valid rational option.

Thus, a machine learns and performs an action, but is not yet able to reflect on it. And this is where we come back to the beginning of the article, and the scene from the movie AI: will we one day have thinking, reflective machines, and most importantly, machines with emotions? This is a trend and also an area of ​​AI study that comes as an evolution of ANI – Weak Artificial Intelligence , a concept that we have already described in another article.

And how does an AI work?

AIs work in such a way that they simulate human intelligence perfectly. Their goal is to be able to respond to diverse demands, ranging from suggesting new films to a user of a certain streaming service, to helping consumers in an appliance store who are having after-sales problems.

It is impossible to think about our daily lives without coming across forms of artificial intelligence that are visible to our eyes. We can see it in the spell checker on our cell phones, in the shopping suggestions we receive via email or on social media. Speaking of social media, it is incredible how our news feed often seems tailored to our tastes.

Well, it is in fact made especially for you, through AI, after analyzing all the information that you unknowingly leave behind on the internet.

That said, it is easy to understand that AI works through:

• Structures used to process, divide, catalog, organize and analyze data through a data model;
• Big Data, that is, the provision of large volumes of data;
• And finally, the system’s ability to process information in order to choose the most appropriate action to take.

Machine Learning

The idea behind the concept of Machine learning is literal, that is, machine learning, which means that it will analyze all the data in its system and will learn to make decisions that match the functions it was assigned.

Let’s take as an example an AI that captures a user’s click on a baby diaper website. The system will analyze the entire path taken by the user, then combine it with the entire database it has and from there make the decision, correct from the point of view of its function, to suggest a series of websites, stores and baby products to this user.

And what normally happens in cases like this: the user ends up consuming more products from the niche, making the customer acquisition process successful, and largely due to the Artificial Intelligence that detected, gathered information, and presented specific suggestions for that potential customer.

Thus, Machine Learning is an area of ​​AI that affirms the thesis that systems learn from data and thus identify patterns and, consequently, are able to perform actions and make choices with minimal human intervention.

Deep Learning

Deep Learning is a subfield of machine learning that uses multiple layers of data and knowledge to reproduce a human neural network as faithfully as possible, and thus teach the computer how to understand and then predict certain patterns.

Deep Learning is an area that is inspired by the way our brain absorbs information and learns, which is why it is seen as a reproduction of our mechanism for thinking and choosing actions. We can conclude that Deep Learning is the closest we can get to imitating human intelligence in computers and its applications cover several areas, such as:

• Voice recognition
• Image processing
• Natural language rocessing

Artificial Intelligence in today’s world

With the inevitable advancement of technology, it is a fact that at some point we will come closer to the scenario described at the beginning of the article, where AI will be so advanced that it will look more like human systems. This scenario brings us to a series of reflections that, until now, only we, humans, can make.

What will be the limits of AI in the evolution of the world? The Battlestar Galactica series ends up offering one of these apocalyptic scenarios, which are more possible. In the plot, we have a context where technology has advanced to such an extent that the artificial intelligence used by humans has gained the status of a life form and self-awareness; however, this AI ends up rebelling against its creators because they feel that they are not valued by the human race.

Could it be that, as we advance in this area and seek to create machines with all our characteristics, we do not run the risk of being overtaken by them?

There is also the question of what are the limits of Artificial Intelligence. Will we ever have a machine that can not only simulate, but actually feel human emotions? And if that happens, even if it is hypothetical, what will be the line that defines what is human and what is machine?

AI emerges as a means of improving the functionalities of our era, and creating situations of convenience, ease and well-being for us, humans. When we come across an email offering exactly the product we were thinking of buying, the first action we usually take is to click on the suggestion and often buy that product.

What we fail to think about in cases like this is the lack of privacy and the tenuous security we currently have with our data. The case of the English company that used data from Facebook users to capture the mood of the British and thus offer material about England’s exit from the European Union is an example of the side effects that the use of AI can bring to our society.

Technology, one of the main factors responsible for the evolution of our world, has undergone and continues to undergo a constant process of renewal, improvement and enhancement. If decades ago the greatest technological achievement was made up of tools such as computers, cell phones and the internet, today artificial intelligence is the great driving force behind the technological revolution.

And in the corporate world, AIs, as they are called, are already responsible for a huge part of the functioning of companies, and seek to bring to their employees and customers all technological innovations, ranging from interactive chats made without human presence, to security tools that aim to block cyber attacks.

In this article, we will better understand the types of Artificial Intelligence that we already have in our social environment, and how they work and improve our lives. Each AI designed has the function of improving and perfecting our lives in some way.

Understanding the concept of AI

The concept of Artificial Intelligence dates back to the post-World War II period, with the publication of the article ” Computing Machinery and Intelligence ” by the English mathematician Alan Turing. There is a film about him called ” The Imitation Game “, from 2014, which explains his thinking in depth and is worth watching.

Years after the publication of the article, Professor John McCarthy – in 1956 – specifically created the term, referring to the ability that machines could have to solve problems that were previously only solved by humans.

In other words, AI is an intelligence similar to human intelligence, but built on the basis of technological tools, and its objective is to perform actions that, if performed by humans, would be considered intelligent.

AI is important for companies

One of the areas that has benefited greatly from the advance of artificial intelligence is the corporate sector, which sees technological evolution as a huge opportunity to optimize services, improve communication with customers and enhance security systems. In this sense, AIs are not only important, but essential for the growth of companies in various sectors.

The impact of Artificial Intelligence on business is so great that many experts call it a revolution, just as electricity was at the beginning of the 20th century, when it allowed manufacturing to grow to such an extent that it became giants in the commercial sector.

Thus, companies use AI’s ability to automate and augment work to increase profits and improve the efficiency of tasks in companies. Medical companies use AI to assist doctors in diagnoses, banks use it to improve loan programs, and companies in general use it to ensure organizational security, especially in their databases.

Types of Artificial Intelligence

Among so many AIs available on the market, we have selected for you the most relevant and important ones that have been developed today. Check them out!

ANI – Weak Artificial Intelligence

Artificial Narrow Intelligence is an AI system focused on a single objective, which seeks to solve a specific task. For example: the AI ​​used in a chess game builds all imaginable options for moves in the game of chess, in addition to building a database of all the rules of the game. However, its use is limited to the game of chess, unless it seeks to cover more games.

Within this perspective, we still have two possibilities (or subgroups) of ANI, one characterized as 1) Reactive Machines, which have more limited resources, with a smaller data storage capacity and which have the ability to react to more restricted stimuli, and this according to their configuration.

In the process of evolution, reactive machines undergo an advancement, reaching 2) Limited Memory, as a much greater possibility of storing information, which is used in decision-making. Large companies benefit from this advancement, and use it to expand the options for their customers. Let’s take as an example a specific streaming service, which based on the movie you chose to watch will suggest other similar ones.

Well, in this case we are faced with a fully functioning AI, for the benefit of the company and its customers.

Thus, we realize that weak AIs are in almost everything we experience today, whether in a video game, in an automatic chat that you enter from a company, and several other examples, which show us that they are restricted (or weak) precisely because they are focused on a single task, always a consequence of their configuration.

AGI – Artificial General Intelligence (Strong AI)

The second type of Artificial Intelligence, AGI, is still far from our reality, and so far its concept flirts more with science fiction than with our reality.

This is because this type of AI is characterized by the ability to reason, solve problems and make decisions, having the ability to plan, learn and even communicate.

In short, AGI has the ability to mimic human intelligence in such a way that we cannot distinguish one from the other. And it is because of this challenge that this type of intelligence has not yet become a practical reality.

One of the biggest obstacles to this type of intelligence being manifested is precisely the ability to not only learn, but above all to think. Let’s imagine a machine that can memorize an entire dictionary and even “swear”, but cannot understand why this swear word is an offensive word. This lack of understanding, of thinking about why, is still the gap that Artificial General Intelligence aims to fill.

To do this, researchers will need to answer questions such as: “What makes us aware of our own consciousness?” For those who have watched the film “AI – Artificial Intelligence”, by Steven Spielberg, this question must already be memorized, as it is one of the main elements of the entire story.

SI – Artificial Superintelligence

It is a concept still surrounded by a lot of fiction and no reality. It would be a kind of tendency of our humanity, we will reach a point where artificial intelligences would be able to surpass us, and even surpass us.

An AI at this level would have the ability to make decisions and, consequently, think about the choices and actions that will be produced. In the world of science fiction, there is still the million-dollar question: will AIs one day have the ability to love? To feel emotions? Even though technological evolution gives us an answer close to yes, this is a topic that affects not only technology or social evolution, but also ethics and anthropology.

After all, if a machine could not only think, but also feel, what would characterize a machine and what would characterize a human? The distinction between the two would blur and become a major philosophical question.

But all of this is still relatively far from happening, especially because we are in the initial phase of AI.

Conclusion

In this article, you have seen the main types of Artificial Intelligence that the world envisions for our current context, and already thinking about the future. Understanding its types, and, above all, its advances, will provide the reader with the ability to understand what AI we already have around us.

Search suggestions, shopping suggestions, automated chats from retail companies, interactive voices on cell phones, and dozens and hundreds and thousands of other examples make us realize that we are living in the early era of Artificial Intelligence. It is up to us, humans, to make this era characterized by advances in truly necessary areas, such as health, business and well-being.

The education sector has been undergoing a process of continuous evolution in recent decades, driven mainly by social transformations, technological revolutions and pedagogical innovations that have emerged in the world. MBA courses, an important part of this segment, reflect this scenario and need to be constantly updated, leading us to a natural question: “What will the future of executive education be like?”

In this content, we will learn about everything important that the future of MBA courses has in store for us.

We will learn about trends for the exercise of education that is more in line with the new scenarios that are to come, in addition to presenting cases of educational innovations developed by corporate education institutions around the world.

Happy reading!

Executive education in perspective

Executive education has always played a relevant role in the training of new managers, managing to form new generations of leaders, who saw this learning model as an excellent opportunity to improve specific skills and technical abilities necessary for strategic positions within a company.

As the decades passed and the world underwent all the transformations, including events such as the pandemic and new contexts such as those arising from technological and behavioral revolutions, pedagogical approaches changed and today we need to train managers who combine technical knowledge with socio-emotional skills, analytical capacity, critical thinking, as well as various soft skills.

MBA courses have been following this path of change and adapting to new scenarios that have been presenting trends and innovations that we will see below.

Strategic people management has never been so strategic

One of the great skills of today’s leader, and which will remain in the future, is the ability to manage people.

We live in a context that has shown high rates of mental health problems in companies, employees with occupational diseases, as well as tense and stressful work environments.

This is the scenario in which leaders find themselves, and they need to constantly exercise their socio-emotional skills, such as the ability to be empathetic, to practice active listening, to be open to different opinions and feedback, and to resolve conflicts intelligently.

Executive education has already presented solutions to train managers who develop this more humane work perspective, but also in line with market reality.

Experiential education as a major trend

Theoretical knowledge has always been very important in the learning process, and its role will not be diminished in any future educational scenarios.

However, the need to emphasize experiential learning is increasingly emerging as a trend in executive education.

Today’s world’s leaders and managers feel pressured to seek an executive education project that provides real-world experiences through teaching.

This means that it is very important to put knowledge into practice in real-world projects, through real organizations and companies, so that they can deliver the solutions learned in theory in a practical way.

Executive education schools are already able to deliver pedagogical experiences that meet this new demand, which is increasingly demanded by leaders.

Continuing education and constant learning

The traditional education model has always been focused on the idea of ​​lifelong knowledge, that is, you received that technical and standardized education and were ready to perform your function eternally.

The world has changed and the ideas of lifelong education and constant updating have gained ground, and they need to be disseminated in corporate education schools as well.

MBA courses have been adapting and today they are able to constantly update their content, approaches and formats, so that the knowledge passed on is always as current and new as possible.

Another idea that has been taking shape is that of microlearning, with schools increasingly working with quick and objective teaching and learning practices.

Embracing technology

It is no secret that any institution or organization that neglects technological advancement will lose ground in its sector.

MBA courses have been transformed over time due to technological developments, and this is a trend that will continue into the future, being intrinsically linked to the idea of ​​innovation.

We will see more and more schools using artificial intelligence to promote more collaborative and participatory education formats.

We will see technologies being used on a large scale to analyze individual and collective performances, in addition to contributing to the technical evolution of the courses themselves.

Promoting critical thinking

One of the major trends for the future of executive education, which is already being encouraged in current MBA courses, is the promotion of critical thinking.

In times of the internet and social media, with millions of pieces of information, real and false, being published every minute, it is essential that we have the ability to know how to filter all of this and reflect in a healthy and intelligent way.

Promoting the idea of ​​criticism is essential for executive education schools to be able to train new leaders, within a context in which the company’s values ​​and mission tend to be worth a lot.

Therefore, having leaders who can represent their values ​​intelligently and in a way that is consistent with their values ​​will be the greatest desire of large organizations around the world.

Conclusion

As we have seen today, the future holds a hopeful and very fertile scenario for executive education.

The new MBA courses are born with this contemporary DNA, seeking to train leaders capable of combining technical knowledge with socio-emotional intelligence and soft skills.

More traditional courses adapt and are constantly updated to continue being a relevant part of your professional journey.