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KMU Establishes AI Center

  • 21.05.26 / 임채원

Kookmin University (KMU) recently established the KMU Artificial Intelligence Center (KMU AI Center), which directs research related to artificial intelligence (AI). The center is an expression of the university’s willingness to lead domestic research and to garner additional support. 

The KMU AI Center is expected to raise the sophistication of AI technology in Korea. In 2022, KMU plans to establish six high-tech field departments, including a department of AI, a department of future mobility, and a department of AI design. The center will serve as a hub for converging AI education while also creating AI-based innovations by cooperating with companies and local communities,
providing solutions to social problems using AI technologies. It’s for this reason that KMU plans to create a practical research organization that can smoothly operate data and cooperate with experts in both professional and civic circles.

AI is already close to universal in certain sectors. As businesses increasingly adopt fourth industrial revolution technologies, AI is being applied to individuals, businesses, and the public sector across a number of fields. 

Inkitt, a world-famous publishing company, based in Berlin, has assigned editorial work previously done by humans to AI, eliminating human error. Any user can freely post articles to Inkitt’s platform, and readers can freely evaluate the uploaded text. AI software analyzes readers’ work and collects data relating to how long readers spend on specific pieces. When a book is selected based on the acquired data, Inkitt flags the article for publication, and the manuscript goes into the revision process. 

Another example of AI’s implementation can be seen in Amazon Go, a self-service grocery store that opened in Seattle on Dec. 5, 2016. The store has no cashiers or counters: purchases and sales are all undertaken by AI. If the customer downloads the Amazon Go app and inputs their payment information, payments are automatically made by removing a product from its shelf and putting it in their cart.

Today, AI’s many advantages are being made increasingly clear — both in terms of time and cost. For more information about AI, We sat down with Jong-Yung Yoon, the head of AI Yangjae Hub, which fosters AI-related professionals and companies with help from KMU. The following are edited excerpts from the interview

 

 What social problems can we solve by using AI technology in the future?
AI technology can solve almost any social problem. But, for example, if a dam built on the Amazon River with the aim of producing hydroelectric power or managing water works incorrectly, it will generate carbon dioxide and pollute the air. Using AI, we can predict where such environmental problems can be minimized. Research into this kind of problem is being conducted at Cornell University in the United States.

AI can also help predict the climate— it helps forecast weather using precipitation- and temperature-related data. AI is also being used in low-income villages in India, where farmers borrow funds that are later repaid using the profits reaped from selling the harvest. When villagers have a bad harvest, there is no way to repay the debt. Villagers urged to repay such debts sometimes commit suicide. However, a company using AI to predict a given year’s crop conditions can now inform farmers of potential results. In doing so, AI is helping solve many contemporary issues — and it will continue to do so.

 

Do you think AI can be applied to other disciplines?
AI technologies are closely linked to several fields. AI is a technology, but to maximize its efficiency it is important to understand how it can be used. Artificial intelligence is another term for machine learning, and machine learning refers to ‘making computers study.’ For example, if you want to teach a machine arithmetic, you first give it the number one. Then, without directly giving it a plus sign, you give it another one — but tell it the answer is two. The machine then learns by itself how to undertake addition. In general software, directly teaching arithmetic is necessary — but in AI, it’s the program that learns. It’s the same for AlphaGo and Lee Se-Dol’s go competition: it’s impossible to teach AlphaGo all of Lee’ s strategies; but once AlphaGo was given data about the basics, it was able to learn and judge data by itself. Once the machine studies the data, it can understand the relationship and apply the method to other situations. AI can be applied to any academic field. What’s important is data. Recent issues with AI chatbots don’t actually stem from the machines — rather, they stem from the biases of those who taught the machine. Those who teach AI are the most important, so we need experts in every area. For example, if we develop AI that can understand and imitate language naturally, linguistics will become important. In this case, experts in linguistics, sociology, psychology, and other natural and social sciences will be needed.

 

Do you think AI development will become an educational program accessible to all fields, even those who don’t specialize in AI? 
Information about processes and facilities of electricity are mostly learned by experts. But we now use electricity conveniently; we don’t know how electricity is produced but know how to turn it on or off with a switch by common sense. The case of AI is the same. Currently, we tend to think that handling AI is quite difficult, but the day will come when we can use it easily. To get there, it’s important to not just educate people about how AI is developed; it’s equally important to eliminate bias and fears about AI. AI is imperfect because it was made by humans: as such, we need to understand the limitations and possibilities of AI. As Yoon emphasized, AI-related education is necessary not simply in AI-specific disciplines, but in all fields of study. For this reason, KMU’ s task of introducing innovative education methods for all students, regardless of their major, is all the more important. The mentoring of AI experts in overseas companies such as Silicon Valley will surely be needed.

 

Si-Hoo Kim Cub-Reporter
sihoo1002@kookmin.ac.kr

KMU Establishes AI Center

Kookmin University (KMU) recently established the KMU Artificial Intelligence Center (KMU AI Center), which directs research related to artificial intelligence (AI). The center is an expression of the university’s willingness to lead domestic research and to garner additional support. 

The KMU AI Center is expected to raise the sophistication of AI technology in Korea. In 2022, KMU plans to establish six high-tech field departments, including a department of AI, a department of future mobility, and a department of AI design. The center will serve as a hub for converging AI education while also creating AI-based innovations by cooperating with companies and local communities,
providing solutions to social problems using AI technologies. It’s for this reason that KMU plans to create a practical research organization that can smoothly operate data and cooperate with experts in both professional and civic circles.

AI is already close to universal in certain sectors. As businesses increasingly adopt fourth industrial revolution technologies, AI is being applied to individuals, businesses, and the public sector across a number of fields. 

Inkitt, a world-famous publishing company, based in Berlin, has assigned editorial work previously done by humans to AI, eliminating human error. Any user can freely post articles to Inkitt’s platform, and readers can freely evaluate the uploaded text. AI software analyzes readers’ work and collects data relating to how long readers spend on specific pieces. When a book is selected based on the acquired data, Inkitt flags the article for publication, and the manuscript goes into the revision process. 

Another example of AI’s implementation can be seen in Amazon Go, a self-service grocery store that opened in Seattle on Dec. 5, 2016. The store has no cashiers or counters: purchases and sales are all undertaken by AI. If the customer downloads the Amazon Go app and inputs their payment information, payments are automatically made by removing a product from its shelf and putting it in their cart.

Today, AI’s many advantages are being made increasingly clear — both in terms of time and cost. For more information about AI, We sat down with Jong-Yung Yoon, the head of AI Yangjae Hub, which fosters AI-related professionals and companies with help from KMU. The following are edited excerpts from the interview

 

 What social problems can we solve by using AI technology in the future?
AI technology can solve almost any social problem. But, for example, if a dam built on the Amazon River with the aim of producing hydroelectric power or managing water works incorrectly, it will generate carbon dioxide and pollute the air. Using AI, we can predict where such environmental problems can be minimized. Research into this kind of problem is being conducted at Cornell University in the United States.

AI can also help predict the climate— it helps forecast weather using precipitation- and temperature-related data. AI is also being used in low-income villages in India, where farmers borrow funds that are later repaid using the profits reaped from selling the harvest. When villagers have a bad harvest, there is no way to repay the debt. Villagers urged to repay such debts sometimes commit suicide. However, a company using AI to predict a given year’s crop conditions can now inform farmers of potential results. In doing so, AI is helping solve many contemporary issues — and it will continue to do so.

 

Do you think AI can be applied to other disciplines?
AI technologies are closely linked to several fields. AI is a technology, but to maximize its efficiency it is important to understand how it can be used. Artificial intelligence is another term for machine learning, and machine learning refers to ‘making computers study.’ For example, if you want to teach a machine arithmetic, you first give it the number one. Then, without directly giving it a plus sign, you give it another one — but tell it the answer is two. The machine then learns by itself how to undertake addition. In general software, directly teaching arithmetic is necessary — but in AI, it’s the program that learns. It’s the same for AlphaGo and Lee Se-Dol’s go competition: it’s impossible to teach AlphaGo all of Lee’ s strategies; but once AlphaGo was given data about the basics, it was able to learn and judge data by itself. Once the machine studies the data, it can understand the relationship and apply the method to other situations. AI can be applied to any academic field. What’s important is data. Recent issues with AI chatbots don’t actually stem from the machines — rather, they stem from the biases of those who taught the machine. Those who teach AI are the most important, so we need experts in every area. For example, if we develop AI that can understand and imitate language naturally, linguistics will become important. In this case, experts in linguistics, sociology, psychology, and other natural and social sciences will be needed.

 

Do you think AI development will become an educational program accessible to all fields, even those who don’t specialize in AI? 
Information about processes and facilities of electricity are mostly learned by experts. But we now use electricity conveniently; we don’t know how electricity is produced but know how to turn it on or off with a switch by common sense. The case of AI is the same. Currently, we tend to think that handling AI is quite difficult, but the day will come when we can use it easily. To get there, it’s important to not just educate people about how AI is developed; it’s equally important to eliminate bias and fears about AI. AI is imperfect because it was made by humans: as such, we need to understand the limitations and possibilities of AI. As Yoon emphasized, AI-related education is necessary not simply in AI-specific disciplines, but in all fields of study. For this reason, KMU’ s task of introducing innovative education methods for all students, regardless of their major, is all the more important. The mentoring of AI experts in overseas companies such as Silicon Valley will surely be needed.

 

Si-Hoo Kim Cub-Reporter
sihoo1002@kookmin.ac.kr

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