Recently, more and more people are saying here and there that the era of artificial intelligence will come and that if you don't know about artificial intelligence, you will fail, die, and be dangerous. Is that really true? no! It's all nonsense. A younger friend I know asked me about the 0-week artificial intelligence expert course and 00-hour AI marketing lecture, and I answered. Are they that easy to obtain? Can you achieve success by spending just a few dozen hours? In fact, deep learning and artificial intelligence scholars emphasize philosophy and fundamentals? Andrew Ng, a leading deep learning educator, emphasizes that it is important to accept artificial intelligence as a useful tool in our daily lives rather than viewing it as a magic tool that will solve everything. While discussing the potential of artificial intelligence, he emphasized the need for an attitude of understanding and actively utilizing technology instead of excessive fear. Andrew Ng says the popularization of artificial intelligence will allow more people to access high-level knowledge. This means more people can easily solve more complex problems. He likened that artificial intelligence would bring about great changes throughout society, just as it popularized electricity. In fact, Professor Andrew Ng makes most of his lectures available for free on DeepLearning.AI , Coursera , etc. If you go there, the founder of LangChain will teach LangChain, and artificial intelligence scholars will teach you about artificial intelligence and deep learning. For free! Sam Altman also emphasizes that artificial intelligence can benefit everyone and argues that technology should provide opportunities to create a better world. This spoke of the importance of breaking away from the monopoly of artificial intelligence and making it accessible to more people. Both of these stories are stories I heard directly from them. Of course, “ people who don’t use artificial intelligence will be replaced by people who do.” There is a saying: This is similar to the saying, “People who don’t drive arrive at their destination later than people who drive.” It will vary depending on the road environment, situation, and destination. Sometimes public transportation arrives faster than your own car (taxi). I think it is a big social problem to say that if you don't learn, something big will happen in the world. Especially in Korea, where we live a goal-oriented life. It's just the latest technology or service without any further goals. It ends up being a person who feels good after learning about service. In particular, one of the strategies often used in artificial intelligence-related education and marketing is FOMO (Fear of Missing Out). It is a method of encouraging people to purchase a product or service by stimulating their fear of being left behind . However, these strategies can create unnecessary anxiety in people and create false perceptions about artificial intelligence learning. It's not important to learn artificial intelligence, but we need to think more about how to use it. Personally, I think this method itself creates a vicious cycle in which people feel like learning something is a big deal and then blame themselves if they fail to utilize it later. Andrew Ng and Sam Altman, pioneers in the fields of deep learning and artificial intelligence, say that if artificial intelligence becomes popular, anyone will be able to easily access higher levels of knowledge. This means that the importance of basic studies and basic knowledge will increase. You won't die if you don't know artificial intelligence tools. A farmer in the south of France without electricity lives happily, and even a person who has never used the Internet lives well. Andrew Ng compared artificial intelligence to a tool like electricity , emphasizing that it will bring great changes to our lives but that it is not something to be afraid of. Rather, he emphasized that we need to take advantage of this and use it as an opportunity. Rather than being deceived by excessive marketing that stimulates FOMO, it is important to prepare for and respond wisely to the era of artificial intelligence. This is a time when we need the wisdom to strengthen basic knowledge and use artificial intelligence as a tool to create a better future. Ultimately, artificial intelligence is also used in conjunction with existing services. Microsoft, Google, and Apple will do the same. If you don't know how to create an existing service and just take the approach that it's all about artificial intelligence, no coding required, and that basic studies are a waste of time, it may feel good right away, but it won't last long. Let us move away from excessive fear and adopt an attitude toward viewing and utilizing artificial intelligence from a balanced perspective. Just because you don’t know about artificial intelligence doesn’t mean you will fail or fall behind. We all know that people who stick to the basics and use them wisely are important, but I am writing this because I feel like people are worrying about money they don't need to spend, time they don't need to spend, and worries they don't need to spend due to some misguided people who create fear.

Over the past 30 years, the proliferation of online shopping has doubled the volume of small package shipments. However, by 2030, it is expected that around 30% of parcels will not be delivered due to labor shortages. This has created an urgent need for automation of logistics systems. Accordingly, an expert panel from Japan's Ministry of Land, Infrastructure, Transport and Tourism proposed the development of an automated logistics system connecting Tokyo and Osaka. This system transports goods through highway median strips or underground tunnels and is scheduled to be completed by 2034. The biggest challenge is cost. According to a survey by construction companies, the cost of building an underground tunnel would be between 7 and 80 billion yen per 10 kilometers, while a system linking Tokyo and Osaka would cost up to 3.7 trillion yen. This is a much higher cost than the 25.4 billion yen per 10 kilometers planned for the ground logistics link in 2000. “This project will not only solve the logistics crisis, but also help reduce greenhouse gas emissions. We want to quickly advance discussions on this issue,” said Tetsuo Saito, Minister of Land, Infrastructure, Transport and Tourism. Honestly, is it because of my mood that it reminds me of the Third Tokyo from Evangelion more than the environment or anything else? In Japan as well as in the United States, projects are actually underway to make existing elevated highways underground. In Korea, a recent example of major road undergrounding is the Dongtan section of the Gyeongbu Expressway. On March 28, 2024, the 4.7km section between the Dongtan Junction and Giheung Dongtan Interchange of the Gyeongbu Expressway was straightened, and 1.2km of the section was made underground. This is Korea's first urban highway undergrounding project, and was completed after seven years of construction. I think the method of determining the use of the road rather than simply securing space and preserving the environment by putting the road underground is impressive. The idea of ​​creating a separate passageway rather than a car road seems somewhat cartoonish. Personally, I think of the undersea tunnel that connects Japan and Korea, and the Asian Highway that connects to Turkicye. Do you remember any cattails? lol

ToysRUs is a global toy specialty store brought to Korea by Lotte and located in Lotte department stores and malls. This brand film was created in collaboration with Native Foreign using OpenAI's Sora, and the video content shows a young Charles Lazarus, founder of Toys R Us, and Geoffrey the Giraffe, our iconic brand and beloved mascot, in the early 1930s. This is a brand film that depicts people watching and dreaming. Sora is a service that allows you to create videos up to one minute in length containing realistic scenes and multiple characters created through text instructions, and is currently only accessible through partners. I'm very impressed that this is the first "official" branded film produced using Sora.

We started operating an open chat room called RUMOA. It is pw:1024. Skewered Coach, which was previously run only through recommendation, has now been opened as open beta. Please note. Thank you to those who always subscribe, and please promote it to those around you. More than 80% of visitors are non-subscribers ~_~

After writing the last article, I talked with my friends about what language is and what thoughts are. Then I came across an interesting article. For a long time, philosophers have pondered the purpose of language. Plato emphasized the importance of language, saying that thinking is “an internal conversation between the soul and oneself.” Modern scholars such as Chomsky have also argued that language is essential for thinking and reasoning. However, recent research results in the neuroscience community contradict this. A representative example is Dr. Evelina Fedorenko, a cognitive neuroscientist at MIT. She scanned people's brains with fMRI and discovered something interesting. This means that the brain area that processes language is not activated during thinking or problem solving. “We couldn’t find any evidence that language was necessary for thinking,” says Dr. Fedorenko. Research results in brain-injured patients also support this. It is said that even aphasic patients who lost their language skills had no difficulty solving math problems or playing chess. These studies show that language is not essential for thinking. So what is the main purpose of language? Dr. Fedorenko firmly says ‘communication’. Research results support this, showing that words that are used more frequently are shorter in length, and that grammar rules tend to place words close in meaning. It seems as if language has evolved to optimize information transfer. Now, shall we move on to the story of LLM, which has emerged as a big player in the artificial intelligence world these days? Thanks to learning from vast amounts of text, LLMs speak the language as fluently as humans. It seems as if it perfectly imitates the human ‘language network’. However, their reasoning and problem-solving skills are lacking. Considering Dr. Fedorenko's theory that language and thinking are separate, this may be natural. You can say that LLM mastered the language tool well, but failed to develop the ability to think using that tool. Of course, this study does not denigrate the value of language. As Professor Guy Dove of the University of Louisville says, “Language can be a tool to improve thinking.” When we think about democracy, we often think of conversations about democracy, right? Language network: Specific brain regions were activated when participants performed language tasks. This area has remained in the same location over time. Thinking network: Different brain regions were activated when the same participants solved puzzles or did different thinking tasks. But the linguistic network remained quiet. People with aphasia: People whose language networks were damaged by brain damage were still able to perform tasks such as doing arithmetic or playing chess. This was further evidence that language is not essential for thinking. The important thing is that language is not the only or essential tool for thinking. We can and have thought in much more fundamental ways. This seems self-evident, as babies struggle to solve problems and understand the world even before they learn language. Watching the LLM makes me think again about what unique abilities only humans have. The power to go beyond simply exchanging information, but to creatively combine that information and create new knowledge. In order for humans and artificial intelligence to grow together in the future, won't we need both wings, 'language' and 'thinking'?

With the recent explosive development of artificial intelligence (AI) technology, the global data center market is growing rapidly. But what about our country? Unfortunately, Korea is lagging behind in this important trend. Let's take a look at why this is happening and what the problem is. Personally, I think this issue is very important. Did you know that global big tech companies such as Google, AWS, Microsoft, and Apple are racing to build large-scale data centers in Asia? In particular, Malaysia and Taiwan stand out in this competition. Apple announced that it would build a data center worth 4.3 trillion won in northern Taiwan, and Google has already invested 1.7 trillion won. AWS is also said to be investing billions of dollars over the next 15 years. But why did these companies choose Taiwan rather than Korea? The reason is simple. This is because Taiwan is responsible for a significant portion of the world's semiconductor production and occupies a key position in the global semiconductor supply chain. In addition, the Taiwanese government is attracting these companies through active policies such as the 'Asia Silicon Valley Development Plan'. So why is our country falling behind in this competition? The problem is multiple. First, there is a power supply problem . Although Korea's power infrastructure is said to be well-equipped, it is actually insufficient to handle the rapidly increasing power demand from data centers. It is said that data center power consumption will more than double by 2026[5], but there are limits to current power supply capabilities. In particular, in metropolitan areas such as Seoul and Gyeonggi-do, electricity demand is already saturated, making it difficult to build additional large-scale power consumption facilities. Second, there is the issue of securing land . In Korea, the land area is small and the population density is high, so it is not easy to find land to build a large-scale data center. As everything is concentrated in the metropolitan area, it has become more difficult to build a data center in an appropriate location. Third, there is a regulatory environment issue . Our country's data management and personal information protection regulations are more stringent than other countries. This is what is holding global companies back. Lastly, the biggest problem is the ‘network fee’ system. Network usage fees in our country are ridiculously high compared to other countries. This is clearly demonstrated by the fact that Twitch revealed that network fees in Korea are 10 times higher than in other countries. Twitch eventually withdrew from the Korean market because of this. If this situation continues, our country will have no choice but to continue to lag behind in the competition for core infrastructure in the AI ​​era. Then what should I do? First of all, the government must urgently pursue power infrastructure expansion and regional distribution policies. In addition, we must establish active support policies to attract data centers and improve the regulatory environment to meet global standards. In particular, the network usage fee issue must be resolved immediately. We need to create a reasonable network usage fee system that meets international standards and establish a balanced cooperative relationship between global companies and domestic telecommunications companies. Data centers in the AI ​​era are not just corporate assets. It is an important infrastructure that is directly related to national competitiveness. In order for our country to become an AI powerhouse, the government, businesses, and academia must join forces to develop and implement a comprehensive strategy. Otherwise, we will have no choice but to fall into a peripheral country in the AI ​​era. To blame labor costs, there is nothing to say about data centers being built in Taiwan and Japan, and to talk about land prices or infrastructure, there is nothing more to say about them being built in countries such as Malaysia and Thailand, which have relatively weaker infrastructure than Korea. If geopolitical reasons are the problem, there are actually Taiwan, which is under threat from China, and Malaysia and Vietnam, which are friendly with China and Russia. But wait a minute: is attracting a data center always a good thing? Looking at Singapore's case, I have doubts. Although Singapore has over 70 data centers, it is restricting new data center permits. Why is that so? Data centers use enormous amounts of electricity and water. Reporter Lee Bong-ryeol's special article shows that in Singapore, data centers consume 7% of total electricity consumption. In addition, although data centers occupy a large area of ​​land, they do not require many people to operate, so the employment effect is not significant. Because of these problems, Ireland, the US state of Virginia, and the European Union are also strengthening regulations on data centers. Korea Electric Power Corporation is also preventing new data centers from being built in the metropolitan area starting this year. What choice should we make in this situation? Rather than unconditionally attracting data centers, a cautious approach seems necessary. The government must step in and set regulations related to data centers and distinguish between what is essential for domestic information security and what is unnecessary. In addition, measures must be taken to ensure that the energy used to operate data centers is renewable energy rather than fossil fuels. Personally, I still think that it is necessary to attract data centers domestically. Even if it is not necessarily an attraction, I think that at least a domestic company or a national level can at least benefit from this competition if it is made to meet global standards. There are various reasons, such as environmental reasons and institutional reasons, but what can we do? You should think about it once. (Of course, there are small regions in Korea such as Amazon/Google/Meta. However, they are very small in scale and most of them ‘exist’ due to personal information protection laws, etc.)

Recently, Elon Musk posted a tweet. It said, “The war of the future will be a drone war.” This story is more interesting than you think. The original article said that drone technology is developing rapidly due to the war in Ukraine. The most impressive part is that a $400 drone destroys hundreds of millions of dollars worth of tanks. Commonly called suicide drones, they literally crash into their targets and self-destruct. This example from the Ukraine war illustrates how quickly drone technology is advancing and how it could change the face of warfare. The idea that low-cost drones could neutralize cutting-edge weapons systems would have presented military strategists with new concerns. However, the power of drones does not lie simply in their cost-effectiveness. As artificial intelligence (AI) technology is applied to drones, their potential is growing further. Drones equipped with AI will be able to independently analyze battlefield situations, identify targets, and determine the optimal attack route. This means that complex missions can be performed without the intervention of a human pilot. These developments in drone and AI technology will have a significant impact on our society as a whole, beyond the military field. Drones are already being used in various fields such as agriculture, logistics, and entertainment. As AI technology becomes more advanced, the scope of drone use will further expand. However, at the same time, concerns are growing about side effects such as privacy infringement, security threats, and job loss. As the computers and internet that we use now are all technologies that were rapidly developed and distributed to the public due to war, drones will also be with us in the future if we keep our wits about them. Even in Korea, there is a continuing movement to use UAM as a means of transportation. In the end, it's all about regulation. Even now, cases of drones being flown in no-drone flying zones are frequently reported, and as access to drones becomes easier, it seems that we will have to fight over regulation and distribution. I would also like to talk about why technological progress occurs so quickly due to wars, etc., but I don't think it's something to discuss in this article. If you look at the link above, you can see a scene where a bomb is attached to a really low-cost drone and destroys an opponent's trench or tank. It makes me think that in the future, the war itself may become a battle between drones without casualties. It also reminds me of the B-1 robot from the Star Wars series that I saw when I was young. (It is not a drone, but the robots below carry out the war instead.)

“GPT-5 will deliver doctoral and college student level performance” This sentence is no longer the stuff of science fiction. A recent interview with Mira Murati, OpenAI's Chief Technology Officer (CTO), shows just how close we are to this exciting future. In a recent interview with Dartmouth Institute of Technology, Mira Murati revealed some exciting information about GPT-5. Murati likened the jump from GPT-4 to GPT-5 to growing from high school to college . What's even more surprising is the prediction that within the next few years, GPT-5 will have 'PhD-level' intelligence for certain tasks. This revolutionary change is expected to be realized between late 2025 and early 2026 . Practical Applications of AI: From Imagination to Reality The development of GPT-5 heralds revolutionary change beyond simple technological evolution. The impact will be felt in a variety of areas: Healthcare : GPT-5 will be able to perform complex diagnostics and suggest innovative treatments. Legal field : By analyzing extensive case law, we will be able to suggest optimal legal strategies. Scientific Research : Accelerate research by analyzing large amounts of data and coming up with new hypotheses. If the current GPT-4 is limited to simple listings and superficial inferences, GPT-5 will be able to go beyond its boundaries and provide more in-depth analysis and creative solutions. AI and the evolution of jobs: From past to future Advances in AI are bringing major changes to the world of work. Historically, the core competencies and main occupations of occupations have constantly evolved with the times: Agricultural society : Agriculture, where physical strength is important, is the main occupation. Industrial Revolution : Factory workers become the mainstream, basic literacy is an important competency Current digital revolution : Office work is the main occupation, knowledge-based work ability is key Future jobs will become more personalized, and collaboration with AI will play an important role. As technology optimist Kevin Kelly predicted, personalized services and products will increase. Mira Murati: A leader in the AI ​​revolution Mira Murati's story illustrates the pace at which AI is advancing and our future. He is also someone I personally look forward to very much. Murati is often jokingly referred to as “the only bachelor in OpenAI technology,” but she is now a key figure in leading one of the world’s leading AI companies. In rocketry from Dartmouth Institute of Technology. In 2013, Tesla entered AI through autonomous driving development. Joined OpenAI in 2018, currently serving as CTO In 2012, when Mira Murati was fresh out of college and working at Zodiac Aerospace, could she have imagined that she would become an iconic figure in the AI ​​industry by 2024? Probably not. This teaches us an important lesson. When we find something we love and devote ourselves to it, unexpected opportunities can present themselves. Advances in AI are amazing in themselves, but the opportunities they bring us are even more amazing. Our Future: Unpredictable Opportunities What role should we play in the AI ​​era? Rather than just watching technology evolve, we need to participate in it and learn how to take advantage of it. Like Mira Murati's journey, we can follow our passion and create new opportunities. The emergence of GPT-5 is the beginning, not the end. Now it is our turn to decide how to use this technology and what kind of future we will create. What kind of future do you envision with AI?

Recently, many advanced countries, including the United States, China, Canada, Japan, and France, have announced that they will invest trillions of dollars in artificial intelligence budgets at the government level. Naturally, with so much news like this coming out, questions are being raised in Korea as well. “Why isn’t Korea spending money on artificial intelligence? What is the government doing?” I would like to explain this and point out the problem. Personally, I think this issue is very important. In fact, South Korea is allocating a lot of money to artificial intelligence. This may sound surprising, but it's true. In fact, even at the central government level in Korea, the combined artificial intelligence budget allocated by local governments, public corporations, etc. exceeds trillions. The articles below report the budget prepared by government ministries related to artificial intelligence in the 2024 budget. “Isn’t that enough?” Why do people in the actual industry think that Korea does not support artificial intelligence? Why can't I feel it? The reason is simple. This is because most of this budget is being allocated to places that are far from actual artificial intelligence. As the world has witnessed, hegemony in the artificial intelligence market is currently coming down to “Who has more AI chips and who creates a better general model?” The United States and China are securing chips that were previously imported for gaming, either by disassembling them or via Southeast Asian countries. In fact, even if you place an order with NVIDIA now, it will take several months to receive the correct product. (This is also why I said that we should continue to buy Nvidia from 2022.) In any case, the NVIDIA product has the best artificial intelligence learning efficiency. However, we have failed to secure this infrastructure nationally. In the recently built artificial intelligence center and wherever you go, most of them are around V100 or A100. Even this isn't much. There are only a few, and some are not even operational. I have seen many cases where models from 5 years ago are being used. Of course it's better than nothing. However, as those of you who know, this makes a difference of at least 3 times to as much as 12 times in the learning speed of artificial intelligence models . This is a gap that is difficult to bridge through ingenious software or learning methods. As I said before, as model learning becomes a battle of scale and speed, high-performance infrastructure is now becoming a necessity. So, the government is building data centers in cooperation with regional organizations, but if you look at the budget, the money is not entirely being spent on artificial intelligence facilities. In the meantime, we are building roads, welfare facilities, and running other projects under the name of artificial intelligence budget. Are artificial intelligence startups in Silicon Valley, New York, Tel Aviv, or Paris doing well because they have easy transportation? The problem is not the budget, but how and who spends it. We live in the cloud era, and there are many ways to assign and use models with just one click. According to a person who recently said that spending money like this could cause problems later on. In addition, if security issues are raised, they try to build their own facilities instead of the cloud, and then they cannot obtain the latest infrastructure. They buy and build old models that can be purchased, but no one uses them, and only places that want to bid for government projects or small companies come in. The bridle is created naturally. In addition, these budgets are currently being budgeted separately by the central government, each ministry, local governments, and public enterprises. There are various groups involved in this work, all issuing separate bids. Ultimately, this is bringing about Galapagosization. We need to pool our budget and talent nationally, but that is not happening right now. This is not something that can be done just by setting a budget, nor can it be done by just hiring people. Is this simply because they are paid a lot so they leave? This is because there is no place in the country that properly supports and supports research. There are many cases where you cannot do research even if you want to. Personally, I think reducing the R&D budget is something that comes from this context, but cutting it off to prevent budget leaks is close to being an understatement. Did you actually catch it? It wouldn't have meant much. Recently, every week I keep seeing talk about government-level fund creation, investment attraction, and bipartisan action in China, Japan, Taiwan, and the United States. I know that there are several people in Korea who are making similar efforts. However, there doesn't seem to be much interest in it in places where decisions are actually made or budgets are prepared. When was the last time Korea was called an IT powerhouse? Is it still an IT powerhouse? Rather than a voucher industry or a consumptive business that is in a hurry to meet performance, shouldn't we prepare an environment that is sustainable and can operate even after 5 or 10 years? When to Concentrate There is a nationally popular project in Korea. These are ‘semiconductors’, ‘displays’, and ‘secondary batteries’. These three are industries that the government takes care of to the extent that there are separate customs laws. Industries that involve all three are electric vehicles and smartphones. The reason why Korea developed so quickly is because it was prepared in the 90s and 00s. How is it now? These technologies are also being pursued at a frightening pace in China, Japan, and Taiwan. CATL, the world's number one company, is looking at the next step in the lithium-ion battery market with sodium-ion batteries, and Japan's Panasonic, Toshiba, and Sony are also sharpening their skills in displays and semiconductors. There is nothing to say about Taiwan. In Korea, the government talks less about the software industry than you might think. There are companies like Naver and Kakao, but they are often regulated rather than actually supported in Korea. In the case of the Naver-Line Yahoo incident that occurred this time, there was actually nothing the government could do. Well, I need something done to say something, but since I haven't done anything, I have no choice but to just watch. The same goes for startups. In fact, you may have learned a lot from investing in startups during the Park Geun-hye and Moon Jae-in administrations, but that has not been carried over. Collaboration is happening at the private enterprise level. Leading the way are Naver, Samsung, and SK. I think we need to lead or support this type of construction and infrastructure industry at the national level. In fact, if it is difficult to break the artificial intelligence development ecosystem created by NVIDIA from the outside, you can approach it by creating compatible chips or chips that can accelerate. In fact, creating a new standard when it has already become the standard does not have much meaning and will only accelerate the Galapagosization. Shall we just talk about digital government for now? Oh, there is already “e-government”? It is difficult for anyone who has used e-government even once to say that it is convenient and good, even if it is empty words. Also, since this is used by central ministries, it is often unavoidable to use it. Even if it comes down to each local organization or agency, it is organized and used independently. If this happens, the budget will be leaking again. We did a lot of things like digital government and DX, but we just did it, but we didn't do it sustainably. Personally, I'm always curious. Is this a problem in the budget planning stage, a problem in selecting a company, or a problem in supervision (audit)? Even now, time and money are passing by and we are missing important decisions like sand in our hands. I don't know if this article will reach them, but we really need to think about what we will do in a few years. The longer this is delayed, the more people will be deceived and dragged into artificial intelligence services, and the wrong people will make money. It's already happening. In fact, we have previously discussed whether the National Assembly (politics) is interested in this, but both the executive and legislative branches should think about it. The judiciary needs to do a better job of monitoring this. We already learned why the separation of powers is a valuable system and why our country chose it in middle school social studies textbooks. I hope the system returns to normal. Summary We are now at an important inflection point. We hope that with the right decisions and implementation, Korea can leap forward into an AI powerhouse. There are several problems with South Korea’s artificial intelligence policy and budgeting: The budget is allocated but not used for actual artificial intelligence development. Failure to secure the latest AI chips and infrastructure Inefficiency due to dispersed budget execution Talent drain problem Lack of long-term vision To solve these problems: Establishment of AI strategy at national level Efficient and focused use of budget Securing the latest AI infrastructure and creating an environment for in-house chip development. Creating an environment to attract and retain talent Strengthening industry-academia-research cooperation Investment and policy establishment from a long-term perspective Please leave a variety of opinions in the comments. I, too, may only be speaking from a narrow tech industry perspective. I believe that better decisions can be made when diverse perspectives come together.

Recently, as artificial intelligence (AI) technology has developed rapidly, the shocking fact has been revealed that the texts, photos, and videos we post online are being used without permission for AI training. In particular, there is a huge controversy over claims that famous AI companies such as OpenAI and Anthropic are collecting content without permission, ignoring the wishes of website owners. At the heart of this problem is a small file called 'robots.txt'. What is the problem and what impact will it have on us? The robots.txt file: traffic lights on the web The 'robots.txt' file is a kind of notice that the website owner tells search engines or other 'bots' (automated programs), "You can look here" or "Don't look here." Simply put, it sets the ‘access rules’ for the website. For example, "User-agent: * Disallow: /private/" is the equivalent of telling all bots to stay out of the "/private/" folder. This small text file serves several important roles. Reduce server load : Too many bots at once can slow down your website. Privacy Protection : You can hide information you do not want to make public. Efficient information provision : Important information can be shown first. Controversial actions by AI companies According to reports from Business Insider and Reuters, AI companies such as OpenAI and Anthropic promise to follow these 'robots.txt' rules but are actually ignoring them. This is similar to driving while ignoring traffic signals. This behavior is not only a violation of the website owner's rights, but is also a serious problem that can harm the credibility of the Internet as a whole. Even in Korea, it was revealed that when Claude3 was asked to write in a DC Inside tone or a specific community tone, he would do so in a very bold way, which was used in a very interesting way. In this situation, a company called TollBit is attracting attention. TollBit, a content licensing brokerage, has closely examined the behavior of AI companies. They use AI to track which websites you visit and how often, and based on that calculate the appropriate usage fee. This can be seen as playing a similar role to cracking down on illegal parking. TollBit's activities can contribute to creating a fair relationship between AI companies and content creators. Did TollBit deliberately revive this controversy? Since TollBit is a company that makes money as an intermediary, there may be some business interest in their claims. However, this is a basic business principle, and if TollBit's claims are based on facts, they are legitimate claims. TollBit is committed to promoting fair trade between AI companies and publishers, providing solutions that benefit both parties. TollBit's argument appears to be valid in many respects. Ignoring the robots.txt file may violate the website owner's rights, which may be legally and ethically problematic. TollBit's claim is intended to prevent AI companies from collecting data in unethical ways, and can be said to be a valid claim to protect the rights of publishers. Backlash and legal response from content platforms and media companies Various content platforms and media companies are strongly opposing these actions by AI companies. They claim that unauthorized data collection by AI companies is threatening their business models. Media companies that produce news articles or professional content are expressing concerns about their works being learned and reproduced without permission by AI. Various types of content platforms, including social media platforms, blog hosting services, and expert knowledge sharing sites, are also paying attention to this issue. They are working to prevent content produced by users of their platform from being used without permission to train AI. Some large media companies and content platforms have already begun or are considering legal action. This requires legal judgment on AI companies' data collection practices, and could become an important precedent for future AI development and content use. How do I stop this? With advances in AI technology, we need to be aware that anything we post online can be used to train AI. This can have major implications for our privacy and copyright. However, blindly mandating robots.txt by law will create significant restrictions on the Internet. In fact, blocking it is a one-dimensional method, and not posting information on the Internet is probably not an appropriate method. I think it would be best to reorganize this in a way that also benefits those who upload posts, like Reddit or Tollbit. Of course, it would be good to properly specify the collection of learning information for the artificial intelligence model.

I recently read an article like this. It was an article that clearly revealed opportunities and optimism about the Indian market and interest in Korea. However, there are many parts that may lead to misunderstanding if you just read through them, so I think I need to sort them out. Although the attractiveness of the Indian market is clear, there are various challenges and risks behind it. Personally, I think that India and South Korea are polar opposites in terms of market characteristics, but the reasons why the Indian market is difficult are as follows. Regional variations and economic disparities: The level of economic development in India varies greatly from region to region. The gap between large cities and rural areas leads to differences in consumption patterns and purchasing power. Complex regulations and administrative procedures: India's regulatory environment is very complex and there are uncertainties in tax and customs procedures. If you do not have a good understanding of the local area, it is often a failure. Cultural diversity and language barriers: From religion to language, India is a country that cannot be counted on one finger. This part is more difficult than you think. Changing language, religion, and culture means a new approach every time for service providers. We are not the only ones looking at India: Competition is fierce as many local and global companies have already entered the Indian market. In particular, as it is a market with high price sensitivity, local companies often stamp out industrial products. Infrastructure issues and logistics difficulties: This was recently discussed in Shuka World while talking about India's Prime Minister election, and except for a few major cities, the infrastructure for inter-city transportation is poor. Additionally, Internet distribution is not as smooth as expected. Do you know why I said it was the exact opposite of Korea? It is difficult to search around the world to find a market with one cultural background, one language, and a similar lifestyle as Korea, with half of the population concentrated in the metropolitan area. In addition, Korea is a very well-off developed country in terms of GDP. In other words, it is a great market with purchasing power and similar customers. Sometimes people talk about opportunities for countries with large populations, but personally, we need to look at not only the population, but also the language and culture. There are many more cases where people approach only based on population numbers and end up getting burned. If you are curious about this, try testing it with a Facebook ad and you will get a feel for it. Similar markets include Taiwan, Japan, and China (limited to first-tier cities). East Asian countries are truly attractive markets. Of course, this is not a story about expanding into India or overseas. As I always say in consulting and elsewhere, it is very difficult to approach the “American market” or “Japanese market.” It would be better to target the market by focusing on a specific city in a specific state in the United States, or a city or district in Japan. The moment we define the OO market, we are often swallowed up by the feelings of that country or culture without realizing it, making it difficult to make good decisions.

I was able to interview Jeff Sutherland, the founder of Scrum and the originator of the Agile Manifesto . As some of you may know, I am participating as a writer for EP9, published by Time & Co. I looked for articles on Notion, Slack, etc., and among the articles I had accumulated, there were 'Scrum' and 'Agile'. At that meeting, I asked if it would be cool to talk to Jeff Thuraland in person, and with the active encouragement of editors Ken and Lia, the interview was promoted. result? Fortunately, he readily accepted. Jeff Theraland Ong may be over 80 years old, but the fire in his eyes and the power of his voice are so great that I can't tell his age at all. In this interview, Sutherland talked in depth about a variety of topics, including the journey from the birth of Scrum to the present, the reality and solutions to the distortion of Agile and Scrum, and the role of Scrum in the AI ​​era. The experience of talking directly with someone I had only read about in books was very rare. Jeff Seoraland emphasized that “a scrum master is a true leader who motivates the team and drives business performance,” and emphasized that he should be a coach who grows with the team, not just a meeting facilitator. In particular, I really liked the fact that teams of 5 or less are most effective and that the Scrum Master itself should be the person with the best performance on the team. Another point worth paying attention to is Sutherland’s point that ‘Scrum’ and ‘Agile’ are being spread incorrectly. Actually, I prepared questions about this part. GeekNews also asked questions about articles such as < Scrum is Cancer>, which became a hit, and Jeff Theraland said that he was already aware of this and felt that there were many things wrong with it. The reason this trend has spread is that many companies are only superficially introducing Scrum, but are missing out on the really important things, such as team autonomy, collaboration, and customer-centered thinking. I sympathize 100 times, as I have also felt similar issues in my work. Sutherland also presented an interesting vision for the future of AI and Scrum. Although AI will automate much of the development work, human creativity and collaboration skills will become more important. And during this interview, Seraland actively used Otter and GPT-4 and said that he was more productive thanks to artificial intelligence. GPTs created by Jeff Theraland: He created them by collecting his own writing and daily thoughts. I think it could be a spoiler if I say more... A planned article based on this interview with Sutherland will be uploaded to <EP9>. To properly understand Agile and Scrum, to gain insight to lead the era of change, If you want, I recommend reading the Sutherland interview in <EP9>. Changing the game of business | Tech Story, Ep9 We give you the courage to take on new challenges, along with business stories of people who constantly challenge themselves and create change through technology.

In the past, I talked about the EU general elections in Self-talkHaebom, and recently, the results of the 2023 European Parliament general elections, an important moment that will determine the future of the European Union, came out. This election heralds a change in the European political landscape along with several surprises. The dynamics of the European Union Summit, where the heads of government and administrative heads of each country gather to set the direction of the European Union, the European Commission, which acts as a kind of executive branch of the European Union, and the European Parliament are expected to undergo many changes depending on the results of this election. Will be. European Parliament and major political party coalition The European Parliament is composed of lawmakers elected from each member state and plays an important role in deliberating the EU's legislation and budget. The election was held from June 6 to 9, and voters in each country elected representatives to represent their country. Major political party coalitions and their achievements European People's Party (EPP): A coalition of traditional conservative parties, the main members of which are Germany's Christian Union (CDU) and Spain's People's Party (PP). It won 190 seats in the election, making it still the largest bloc in the European Parliament. Social Democratic and Progressive Alliance (S&D): A center-left coalition that remains the second largest, with 136 seats. European Conservative and Reform Party (ECR): A coalition of hard-right parties led by Italian Prime Minister Giorgia Meloni. 66 seats were secured. Identity and Democracy (ID): A coalition of far-right parties, the Alternative for Germany (AfD) won 58 seats despite the controversy, and if you include the AfD's seats, the number rises to 73. Renew Europe: A liberal and centrist coalition that includes French President Emmanuel Macron's party. Although it secured 96 seats in this election, President Macron's Renaissance Party only won 13 seats, reducing its influence. Greens/EFA: Environmentalist and left-leaning coalition, won 73 seats. Changes in the European Parliament and the rise of the right This election was particularly notable for the strength of right-wing parties. The European People's Party (EPP) remains the largest coalition, but hard-right and far-right parties are making notable advances. The propaganda of the European Conservative and Reform Party (ECR) and Identity and Democracy (ID) shows that Europe's political landscape is shifting to the right. France's political gamble: President Macron declares early general election French President Emmanuel Macron declared early general elections following the Renaissance Party's crushing defeat in the European Parliament elections. This appears to be a strategy to prevent Marine Le Pen's National Coalition, a far-right party, from having a greater influence in French politics. President Macron hopes to regain political leadership through early general elections, but it is unclear whether this gamble will pay off given his low approval ratings. France adopts a dual government system, where the president oversees defense and foreign policy, and the prime minister runs day-to-day state affairs. Because of this, the president and prime minister often belong to different political parties. It remains to be seen whether this early general election will end as a political gamble by President Macron, or whether it will be a decisive moment to prevent the rise of the far-right. Characteristics of European Parliament elections European Parliament elections are often used as a forum to express dissatisfaction with national governments. Since voters' votes are often determined by their own country's political issues rather than the policies of the European Union, the results of this election also had a strong warning to the current government and vested political forces. The 2024 European Parliament elections herald new changes in European politics. The rise of right-wing parties and the weakness of the centrist liberal coalition are reshaping Europe's political balance. In particular, France's early general election is expected to have a big impact throughout Europe. The European Union is at a point where it needs to find a new direction amidst these changes. The results of this election will be an important turning point that will determine the future of Europe.

The number of people who recently participated in skewer coaching was over 50 people. Everyone from juniors to seniors, people from other industries, and retired people applied, so it was a lot of fun because I was able to see new perspectives that I couldn't see. Normally, I would pay for food and drinks, so if this is a business, I think I have spent hundreds so far, but I think it was worth it. Some people may feel very burdened or feel sorry about receiving it, but there is no need to feel burdened at all. As I always say during coaching, my goal is to do well and eat more expensive things later. As a joke, the key is to write down your goals for the second round of coaching. May these things become abundant someday! I was at a loss for words for a moment, but the topic of this article is “The reason why I don’t like the term that_girl and hexagon talent.” Since a little over 2020, I have been very bothered by the phrase “work hard.” What is doing a good job, and what is doing it well? The problem with trying to answer a Zen question is that the word itself is an abstract, flexible, and open-ended expression in the first place. Of course, this inevitably leads to burnout. The video from the Twitter post was made by Professor Nuri Kim of Ruchuk. This was conducted on JTBC's China Class, and I was very impressed by the way he used the expression that_girl as 'self-exploitation'. Personally, I sympathized with this part. I was diagnosed with obsessive compulsive disorder a few years ago and actually took related medication for quite a long time. Burnout is a bonus. For this to work properly, there must be clear incentives, but this is also not easy. (Individual capabilities + market conditions + performance) Honestly, there are three main reasons why the expression that_girl, the expression ‘good workman’, and the expression ‘hexagon’ seem clever. Is there a real that_girl/Hexagon/Worker? Even if you take your time like Hermione, you're bound to make mistakes. Doing everything in itself is like a person with a sharp regression to SSS, but who is this kind of person in our company? As the saying goes, “I am someone’s ㅇㅇ guy, I am also someone’s ㅇㅇ guy”, but this does not necessarily always work. Are their ways and methods valid for me too? Am I going to go to a prestigious university just because I read a textbook called <Incorrect Answer Notes from Students at a Prestigious University>? Even if I know how to make 100 million won a month with ㅁㅁㅁ, do I also make a lot? Does that method apply to me too? You should think about it once. Is that method right for me and has it actually been achieved? Due to lack of effort, low level of understanding, etc., few people went to that area in the first place (not that there are none), hexagon, and that_girl. It's like everyone watching Yuna Kim for figure skating, and watching Son Heung-min for soccer skills. But is this a good way? They also have to find the right training method and figure out things that are meaningful to them. A type of business where it's thanks to a lecture or something that goes well and it's my fault if it doesn't, usually appears in the education and wellness industries. We heard that we got 900 points on TOEIC, but we don't argue with our TOEIC teacher because we got 800 points, right? I know that I didn't study on my own, so even if I receive expensive PT for several months, I don't complain if my body doesn't turn out the way I wanted. because? That's because I don't follow the strict diet and intense exercise that my PT teacher mentioned. What I felt while running the coaching program is that everyone wants to do well, like a hexagon and a good worker, which seems to be the form of obsession and stress that everyone feels the most. This is a cycle I often show when I coach, and it goes something like this. Because depression, obsession, and anxiety feed off of each other... it is very difficult to achieve good results from this. Living hard is never a bad thing. However, if you run at a sprint every time, it is easy for something to break. The problem is that even if something is broken, it's not a good thing to get a clear reward or something. Furthermore, the fact that there are many people who make fake efforts and think they have tried it makes this problem even more problematic. The most important thing is that we must be wary of these things. Among Soljigi that_girl, hexagon talents, and work-skillers, very few are real and many are even self-proclaimed. Personally, I think that doing what you want to do in life, meeting people you care about, and thinking positive and diverse thoughts is the way to be most happy. Anyway, good luck everyone. I wrote an editorial like this before, but this is an extension of it. Professor Seong-Hoon Moon recently published a good column, so I would like to share it with you.

Ted Chang, who spoke about artificial intelligence at a forum recently held in Korea, appeared as a speaker. Ted Chiang is one of my favorite authors, but unfortunately I found it hard to agree with much of what he said this time around. Much of what he said can be refuted by Jacques Rancier's structuralist linguistics. It was as if Lewis Banks had his first encounter with an unknown world in the movie <Contact (2016) Arrival>. Are you afraid and not trying to understand something? It was a feeling. "Language is the foundation of civilization. It is the glue that holds a people together. It is the first weapon drawn in a conflict." Language is the cornerstone of civilization, the bond that binds people, and the first weapon in all conflicts. Ted Chang has argued that artificial intelligence is not truly intelligent because it lacks intention and choice, but this is already a topic of conversation among language philosophers and structuralists, such as the Chinese Room debate and various others. This was recently disclosed in a paper by Antropic titled Scaling Monosemanticity. I took two videos related to this. One of the two is artificial intelligence dubbing. Guess which is the artificial intelligence dubbing!

Today, a serious conflict broke out between Coupang, Korea's largest online shopping mall, and the government's Fair Trade Commission (hereinafter referred to as the Fair Trade Commission). This conflict arose when two important factors collided: fair competition in the online market and provision of innovative services. In this column, we will objectively summarize the background of this conflict and the positions of both sides. 1. Background of the conflict Coupang’s growth and market dominance Coupang is Korea's largest online shopping mall, and is gaining great popularity among consumers with its rocket delivery service that quickly delivers a variety of products at low prices. Rapid growth has resulted in a significant increase in market share, creating competition from many smaller stores. Along with this growth, Coupang's market dominance also increased, attracting the attention of the Fair Trade Commission. Role of the Fair Trade Commission The Fair Trade Commission is responsible for promoting fair market competition and protecting consumers. We implement various regulatory measures to prevent abuse of monopoly positions or unfair trading practices in the market. Recently, the Fair Trade Commission has raised issues related to Coupang's monopoly position, claiming that Coupang is dominating the market in unfair ways. 2. Fair Trade Commission’s position Difference between search ranking and display The Fair Trade Commission argues that Coupang's act of exposing its own brand (PB) products at the top of search rankings is fundamentally different from the act of displaying products in specific locations in offline stores. Offline stores only have a prominent location for display, and that location has nothing to do with ranking. On the other hand, search rankings on online platforms indicate product excellence, such as sales volume and consumer satisfaction. Unfair action Coupang, as an online platform and product seller, was pointed out as a problem for exposing its own products in search rankings ahead of brokerage products. Additionally, Coupang's act of manipulating search rankings by having its executives and employees write purchase reviews of its products was considered an unfair means of competition. Comparison with international cases EU competition authorities have sanctioned Amazon for exposing its products first to the 'BUY BOX', and the US FTC and 17 states have banned Amazon from placing products sold at lower prices on other online platforms at the bottom of search results. A lawsuit was filed for the action. Through this, the Fair Trade Commission is emphasizing that Coupang's actions are an unfair practice that is also problematic internationally. 3. Coupang’s position The importance of rocket delivery service Coupang has invested tens of trillions of won every year to purchase Rocket Delivery products directly, deliver them quickly, and provide a free return service. Consumers choose Coupang to use this differentiated rocket delivery service. Coupang claims that it is natural to recommend Rocket Delivery products. Maintain investment and service Coupang argues that if the Fair Trade Commission's sanctions make it difficult to recommend and sell rocket delivery products, it will become difficult to maintain these services and will inevitably cause inconvenience and damage to consumers. If the Fair Trade Commission's measures continue, Coupang's position is that it will have no choice but to stop investing 3 trillion won in logistics to provide 100% free delivery to all citizens and 22 trillion won in investments to purchase rocket delivery products. Excessive sanctions and equity issues Coupang argues that the Fair Trade Commission's sanctions are excessive and hinder its ability to provide innovative services. In particular, we express regret over the Fair Trade Commission's decision to impose fines and criminal charges for Coupang's actions, and plan to actively explain the unfairness in court through administrative litigation. 4. Conclusion and implications The conflict between Coupang and the Fair Trade Commission arose from the conflict between two important factors: fair competition in the online market and provision of innovative services. While the Fair Trade Commission emphasizes fair competition and consumer protection in the market, Coupang emphasizes its innovative services and maintenance of investment. A solution to this conflict will be sought through ongoing discussions and legal procedures. From this conflict, we can gain the following implications: Importance of fair competition: Fair competition in the market provides consumers with a variety of choices and promotes healthy growth of the overall market. Value of innovative services: Innovative services are an important element that provides new value to consumers and increases a company's competitiveness. Balanced regulation: Balanced regulation is needed to resolve conflicts between regulators and businesses. Excessive regulation can hinder corporate innovation, and insufficient regulation can cause unfair competition. Ultimately, it is important to establish a market environment that balances fair competition and innovative service provision. To this end, constructive dialogue and cooperation between the Fair Trade Commission and companies are needed. Based on the lessons learned from resolving this conflict, we hope to create a fairer and more innovative market.

Do you know India's native social media platform Koo? Koo, which emerged as an alternative to Twitter with rapid growth since its launch in 2020 when the coronavirus pandemic was in full swing, has since faced several challenges and is facing a crisis. Koo's number of monthly active users grew rapidly, reaching approximately 1.8 million by the end of 2022. But since then, the number of users has declined rapidly, falling below about 200,000 by early 2024. Initial success factors: localization and government support The secret to Koo's early success came from a deep understanding of the Indian market. By supporting major Indian languages ​​such as Hindi and Tamil, we were able to reach out to local users in a friendly way. In addition, friction between the Indian government and Twitter worked as a boon for Koo. This was because many politicians and celebrities moved to Koo at the time, increasing the visibility of the platform. Based on this momentum, Koo accelerated its overseas expansion. Performance in Nigeria and Brazil is representative, and in particular, Koo emerged as an alternative while access to Twitter was blocked in Nigeria. Growing Pains: Difficulty Raising Funding and Differentiation However, Koo's smooth sail was short-lived, as investment sentiment for startups declined in the aftermath of the global economic downturn, and he began having difficulties in raising funds. This put a brake on marketing and user acquisition activities and ultimately led to large-scale staff reductions. In 2023, we had to go through the pain of restructuring, including laying off 30% of all employees. Here, the platform's own differentiation strategy also revealed its limitations. Multilingual support alone was not enough to retain users. In the face of the overwhelming features and user base of global competitors such as Twitter, Koo's position was inevitably narrowed. Furthermore, influential social figures who were early users created an image of the platform as a conservative platform through political comments, which acted as an obstacle to Koo's growth. Efforts to make a breakthrough Even during the crisis, Koo did not stop investing in the future. A representative example is the encouragement of user participation through a compensation system called ‘Koo Coins’. It is evaluated that it has had the effect of increasing the frequency of users' access by paying coins according to app login and content consumption and allowing them to be cashed. Recently, we also introduced creator-friendly policies. Through premium features, we have laid the foundation for creators to generate revenue through a subscription model. This is expected to have a positive effect on encouraging creators to settle into the platform while also creating a differentiated content ecosystem. Outlook: Coexistence of Opportunities and Risks Looking at Koo's situation, we can see that both opportunities and risks coexist. First, in terms of opportunity, Koo's localization strategy and creator-friendly policies are expected to play a major role in securing competitiveness. Above all, Koo's preemptive entry into emerging markets, including India, is encouraging, given that they still have great growth potential. On the other hand, uncertainty in financing and monetization models can act as a risk factor. This is because if the global economic downturn is prolonged, it may be difficult to attract investment. In addition, competition with existing platforms such as Twitter is a formidable task. Given their overwhelming market share, it is expected to take considerable time for Koo to close the service gap. Koo's case is a good example to talk about the content and platform industry. Although it received a huge investment and secured many users, the use of influential people, which was initially a strength, turned out to be a risk. Since then, various attempts have been made, such as introducing Koo Coins to support users' economic activities and introducing a premium content model. Moreover, with Prime Minister Modi coming back to power in this general election, the people who were active in Koo have gained power again, so I wonder how things will change. Business is not just about market logic.

There are times when our hearts become heavy with worries about the future. But many of those worries are things that may not actually happen. Of course, it may be difficult to completely shake off worrying, but it would be helpful to prepare for the problems we may actually face and pay more attention to finding solutions. Especially these days, as technology develops rapidly, major changes are occurring in the labor market. In these situations, specific preparations are more important than vague worries. Worrying only increases anxiety and does not actually help solve the problem. In contrast, preparedness means approaching a problem practically by making a realistic plan and preparing the necessary things. By doing this, we can control some of our anxiety and increase our capabilities. Of course, as technology develops, some jobs may disappear, but at the same time, many new jobs will be created. And it will be difficult to completely replace tasks that only humans can do, or tasks that require emotion or creativity, with machines. So there is no need to be too afraid of these changes. Rather, we need to take it as an opportunity and adapt to it. There may be people who experience difficulties during this process of change. So we need to further strengthen the social safety net. Institutional support is needed so that everyone can maintain a basic quality of life and enjoy economic benefits equally. Something like the basic income system, which is often discussed these days, could be part of that. Good resource for further reading “Preparing for the (Non-existent?) Future of Work” analyzes the impact of technological advancements on the labor market. Advances in automation and artificial intelligence may replace many jobs, but this will not necessarily have negative consequences. Impact of technological advancements Technological advancements can cause major changes in the labor market. The report highlights that technological advancements can create new types of jobs, even if some jobs disappear. For example, during the Industrial Revolution, when machines replaced human labor, new jobs were created. This suggests that technological progress does not necessarily lead to large-scale unemployment. Economic redundancy Although technological advancements may allow some jobs to be automated, there are also 'nostalgic jobs' that still require human labor. These jobs require special human abilities or emotions and are fields that machines cannot completely replace. Therefore, human labor will not disappear completely, and we must accept this change positively. Social insurance The report argues that a social insurance system is needed to mitigate the risks posed by technological advancements. This is an important factor in reducing inequality in the labor market and helping everyone enjoy economic benefits. For example, by introducing a basic income system, we can solve the unemployment problem caused by automation and help all citizens maintain basic living standards. In conclusion In fact, rather than worrying too much about changes we can't control, it's better to focus on things we can realistically prepare for. You may not be able to stop the coming changes, but if you deal with them wisely, you will be able to get through them well. How about putting down some of the burden on your mind and preparing for the future wisely?

While talking about non-entrepreneurship, we talked about 'snake oil'. Literally translated as snake oil, this word refers to something worthless or fraudulent. The expression is said to have originated from the 18th century European saying that eating or applying snake oil would cure all diseases. I'm a little lost in words, but we are now entering the AI ​​era. Artificial intelligence technology is revolutionizing many aspects of our lives, but it is also true that it is full of exaggerated advertisements and unfounded promises. The so-called ‘AI snake oil’ is rampant. Despite lacking expertise or experience in AI, they use language models to pretend to be experts. They deceive the public with flashy words and exaggerate the potential of AI with unfounded claims. They even lie by claiming that they developed AI technology themselves. Because of these false experts, misconceptions about AI are spreading and distrust of the technology is growing. Startups that receive huge investments and offer fake AI services are also appearing frequently. In fact, consumers who use these services do not receive proper value and suffer damage. In order to properly understand and prepare for the changes that the development of AI technology will bring, we must listen to the voices of people with real expertise. Rather than being deceived by flashy words, we should consider the evidence and logic. We must be able to discuss the limitations and risks of AI with an open attitude. Rather than blindly trusting or fearing technology, we must learn to use it wisely and control it. It is time to prepare for the AI ​​era with an honest and sincere attitude, rather than being deceived by pseudo-gurus who claim to be experts. We must develop a keen sense of criticism and insight into the essence of technology. AI will definitely give us great opportunities. But in the process, we must not play to snake oil salesmen. Only when we all understand and use AI technology with a sense of ownership will we be able to enter the human-centered AI era. What we need now is not blind praise for technology, but an attitude of critical acceptance. This article was written by Claude-3 Opus, excluding the top two paragraphs.

Freedom of speech is a basic right of every individual, but its exercise comes with responsibilities depending on the situation. Speeches in private settings are mainly limited to the exchange of personal opinions and are therefore unlikely to cause social repercussions. On the other hand, comments made in public or by people with social status have greater influence and require a higher level of responsibility. This is because the words of politicians, celebrities, experts, etc. influence the formation of public opinion. Remarks on public platforms such as SNS can spread quickly and cause social division or misunderstanding. Therefore, public statements must be made accurately, fairly and responsibly. This is essential to prevent the spread of fake news and maintain social trust. Fulfilling responsibility for public speech contributes to the formation of a healthy public sphere and social development. Meanwhile, communication between a speaker and a listener is a very complex process. Speakers have an obligation to clearly convey their opinions and information. However, the listener's understanding and acceptance depends on his cognitive and emotional factors. The speaker's avoidance of responsibility by saying things like "it's annoying" or "I don't know what to do to explain" ignores the listener and undermines a healthy conversation culture . However, the speaker cannot force the listener to understand. This is because the listener's interpretation is influenced by his or her background knowledge, experiences, and emotions. The speaker must provide sufficient explanation, but leave the listener's understanding and interpretation to the listener. In short, speakers must take responsibility for their remarks and explain them faithfully. However, the listener's understanding of it is the listener's own domain, including interpretations based on personal experience and knowledge. In this process, smooth communication becomes possible when both the speaker and the listener take a responsible attitude. Rather, I believe that the more people who explain things, the fewer people will spread the current incorrect information.

Recently, the term of the 21st National Assembly ended and the 22nd National Assembly began. While watching the 21st National Assembly debate on a certain broadcasting station, I saw that they were talking about the artificial intelligence bill, so I was curious and looked up what the artificial intelligence bill was. There were as many as 12 cases. Of course, there is a problem that will naturally disappear as the term of the 21st National Assembly ends and must be dealt with anew in the 22nd National Assembly. Proposal number Prosthetic eye name Proposal date Resolution result Resolution date 2123709 Artificial Intelligence Accountability and Regulation Legislation 2023-08-08 Expiration of term of office 2024-05-29 2120353 Artificial Intelligence Liability Act 2023-02-28 Expiration of term of office 2024-05-29 2118726 Bill on fostering the artificial intelligence industry and securing trust 2022-12-07 Expiration of term of office 2024-05-29 2116986 Artificial Intelligence Education Promotion Act 2022-08-24 Expiration of term of office 2024-05-29 2113509 Bill on Algorithms and Artificial Intelligence 2021-11-24 Expiration of term of office 2024-05-29 2111573 Bill on Artificial Intelligence 2021-07-19 Expiration of term of office 2024-05-29 2111261 Legislation on fostering artificial intelligence and creating a foundation for trust, etc. 2021-07-01 Expiration of term of office 2024-05-29 2110148 Artificial Intelligence Education Promotion Act 2021-05-17 Expiration of term of office 2024-05-29 2104772 Artificial intelligence technology basic bill 2020-10-29 Expiration of term of office 2024-05-29 2104564 Special Act on the Development of Artificial Intelligence Integrated Complexes 2020-10-19 Expiration of term of office 2024-05-29 2103515 Bill on the Promotion of Artificial Intelligence Industry 2020-09-03 Expiration of term of office 2024-05-29 2101823 Legislation on artificial intelligence research and development, industry promotion, ethical responsibility, etc. 2020-07-13 Expiration of term of office 2024-05-29 Looking at these problems, first of all, there is the problem of 'term expiration repeal', in which many bills are automatically discarded when the proposer's term expires. In addition, bills pending in the relevant committees are not receiving sufficient review, resulting in 'delays in review.' This reduces the effectiveness of the bill and makes timely regulation and support difficult. Another problem is that the political world has little interest and priority in artificial intelligence. Considering the social change and impact that artificial intelligence will bring, there is a lack of political will and support for related bills. This weakens the momentum needed to pass legislation and reduces the ability of the National Assembly to respond to the rapidly changing technological environment. Improvement is also needed in terms of the bill's content. Most of the current bills consist of comprehensive and declarative contents, and lack specific implementation plans. Due to the complex and rapidly developing nature of technologies such as artificial intelligence, more detailed and flexible regulatory measures must be established. (Some bills divide artificial intelligence, super-thinking artificial intelligence, high-risk artificial intelligence, etc., but it felt like I was only understanding the concept in terms of what the standards were, so I felt like I wasn't sure what I wanted to do while reading it.) Multifaceted efforts are needed to improve these problems. First, we must establish an institutional mechanism to streamline and expedite the bill review process within the National Assembly. Through this, delays in the review of pending bills will be resolved and the problem of expiration of term of office will also be alleviated. We also need to raise political awareness of artificial intelligence and raise the priority of related bills. This can create a synergy effect when promoted in conjunction with the establishment of a government-wide national strategy for artificial intelligence. If the government and the National Assembly cooperate to proactively respond to the development of artificial intelligence technology and its social impact, we will be able to speed up the overhaul of laws and systems. It is good to set terms, but there seems to be a tendency to try to define terms first when the environment, ecosystem, and human resources to properly create them are not yet ready. I think the standard for defining that term is also Fituru Maturu. It is also important to increase the specificity and effectiveness of the bill's contents. Considering the characteristics of artificial intelligence technology, more detailed and flexible regulatory measures must be developed. To achieve this, a process of collecting opinions from various stakeholders such as technical experts, industry, academia, and civil society, and reaching social consensus appears necessary. I think it should be done bipartisanly, not along party lines. They say that the first quarter of a legislative session is the hardest... please... I recently introduced a case from the United States. In addition, active communication and cooperation between the proposer and related organizations are required. Continued attention and effort must be paid even after the bill is proposed, and after passage, an inter-ministerial collaboration system must be established for implementation. Through this, we will be able to increase the effectiveness of the bill and promote the healthy development of artificial intelligence technology. Actual organizations and ministries are also experiencing difficulties in setting up committee members and supervisors. This seems to be a problem caused by approaching ‘artificial intelligence’ too conceptually to be due to the absence of experts. In fact, when we talk about it, we often see cases where people try to use artificial intelligence, spending high costs on problems that do not need to be solved with artificial intelligence. Artificial intelligence is seen as a key technology that will determine the future of our society. Resolving problems with related laws and finding ways to improve them can be said to be a national task. It is time for various entities, including the legislature, the executive branch, expert groups, and civil society, to add strength and pool their wisdom. I am confident that if we work together, Korea will be able to establish itself as a leading country in the era of artificial intelligence. (Of course, there needs to be some process to filter out strange groups in this process.) I've covered this repeatedly, but our neighboring countries, the US, and the EU are all having deep discussions about artificial intelligence. In addition, I believe that such discussions should continue actively in society, as most countries are adopting protectionist trade rather than free trade due to recent oversupply, and furthermore, their own selfish attitude. Issues such as the First Lady's luxury bag and in-flight meals may be important, but from the perspective of the Republic of Korea, discussions and practical research support related to artificial intelligence are urgently needed.

The various technologies and vision that NVIDIA showcased at Computex 2024 are not just limited to the announcement of new products, but are expected to become a key driving force that will bring innovation to the entire future industry. First of all, the 'Physical AI' and 'Omniverse' platforms are expected to open new horizons in the field of robotics. Physical AI is a technology that allows robots to learn and adapt like humans in real environments. Through Omniverse, NVIDIA presented a pipeline that allows these AI models to be sufficiently trained in a virtual environment and applied to actual robots. As realistic physical simulations become possible, it is expected that great progress will be made in the development of industrial robots as well as service robots. NVIDIA also opened a new chapter in 'digital twin' technology at this event. The Earth-2 project is a digital twin for weather prediction. It is expected to bring about innovation in responding to climate change by combining supercomputing and AI to precisely simulate the Earth's environment. Even in the manufacturing field, digital twins are becoming a key tool for innovation. NVIDIA's Omniverse is expected to become a powerful platform for digital twin implementation throughout the design, simulation, and automation process. In addition, NVIDIA presented the future of ‘accelerated computing’ at this Computex. In the era of big data and AI, existing general-purpose computing has its limitations. Accelerated computing, which combines the advantages of CPU and GPU, is considered a breakthrough that can solve these problems. In particular, 'Rubin', the next-generation GPU architecture unveiled by NVIDIA, is expected to lead innovation in various fields such as HPC, autonomous driving, and robotics by maximizing computational efficiency. In addition, NVIDIA also unveiled solutions that can dramatically simplify the development and deployment of AI models, such as 'NIM (NVIDIA Inference Microservice)'. This is a 'game changer' that can change the paradigm of software development, and is expected to greatly contribute to the easier application of AI technology to industrial sites. In this way, NVIDIA's Computex 2023 announcement is significant in that it presents a vision for future technologies such as artificial intelligence, robotics, and digital twins, while also presenting a comprehensive blueprint that includes specific application plans and the ecosystem. It is expected that it will play a significant role as a bridge connecting cutting-edge technology with industrial innovation. This is why NVIDIA's future moves are attracting attention. Attention is being paid to whether the vision and strategies revealed this time can lead to concrete results and what changes they will bring to the industrial landscape. This is why we look forward to the leadership and innovation that NVIDIA will show in the fields of artificial intelligence and data science, which will be the core drivers of the 4th Industrial Revolution. The most important thing is that Rubin, Blackwell's top model, was revealed. I wonder if the era of physical supercomputing is really coming. Rubin (Ultra): GR100 GPU, R100 SKU, uses HBM4 memory, scheduled for release in 2026-2027. Blackwell (Ultra): GB200 GPU, B100/B200 SKU, using HBM3e memory, scheduled for release in 2024-2025. Hopper: GH200/GH100 GPU, H100/H200 SKU, using HBM2e/HBM3/HBM3e memory, scheduled for release in 2022-2024. Ampere: GA100 GPU, A100 SKU, uses HBM2e memory, available 2020-2022. Volta: GV100 GPU, V100 SKU, uses HBM2 memory, released in 2018. Pascal: GP100 GPU, P100 SKU, uses HBM2 memory, released in 2016.

I once wrote about Albert Hirschman's <To Leave or to Stay?>, and I had the opportunity to contribute to a magazine called Overdose. As a result, I ended up talking about this topic with various people. Everyone agreed on things like protest, departure, and silence, but there were various opinions on 'loyalty.' In this day and age, isn't loyalty too old-fashioned? It's not even about the military. Why loyalty? However, the phenomenon of decreasing loyalty to companies in modern society is the result of complex factors that cannot be explained simply by changes in individual values. Applying Albert Hirshman's concept, we can broadly analyze the causes of this decline in loyalty into four categories. First, because the social contract between companies and employees has been broken . In the past, generous pension and insurance benefits were offered to reward long service, but these benefits have been reduced or eliminated in recent years to cut costs, making it difficult to engender long-term loyalty from employees. Second, the workplace environment is changing rapidly due to rapid technological advancement and globalization. As a result, employees can work anytime, anywhere, free from physical constraints, and do not hesitate to move to a company that offers better conditions in the global competition to attract talent. Additionally, providing customized benefits that meet the expectations of employees with diverse backgrounds and values ​​has become a difficult task for companies. Third, employees now consider work-life balance, self-development, and realization of social value more important than economic compensation. They want to work for a company that matches their values, and because they seek a variety of experiences, they do not prefer to stay at one job for a long time. Fourth, as the reward system for loyalty has weakened, employees have come to recognize that loyalty to the company is not directly linked to individual career development or salary increases . Loyalty itself has become a matter of choice unrelated to personal interests. This decline in loyalty to companies is a complex phenomenon that reflects changes in society as a whole. To overcome this, companies must embrace change and actively respond to the new needs of their employees. If we look for ways to harmoniously connect the values ​​of each employee and the company's vision beyond simply financial compensation, we will be able to create a new form of loyalty.

I remember when I was making <Wild Land: Durango>, the director said that we had to create a sensation. It was a story about creating an atmosphere where people don't do something because they feel it's the 'trend' and feel bad about it, but at that time, expressions such as micro-influencer were used instead of the fancy word 'supersharer'. Rather than giving advertising to millions of game YouTubers, the method was to give advertising to around 100,000 YouTubers. Well, let's stop talking about old times. As the US presidential election gets closer, various news is coming out. I found the expression “super spreader” or “super sharer” recently published in the journal Science very interesting. Of course, in the article and survey itself, it was used in a very negative sense. It was about a small number of extreme users spreading fake news. ( original text ) Who is the superspreader that Science magazine talks about? These are a small group of users who actively spread information online and have great influence. According to a recent study, the top 1% of Twitter followers spread 80% of all fake news . Their average age was 58 years old, and a high proportion of them were women. Interestingly, they were real people, not automated bots . This is not just an American story. Shall we take another example? A study analyzing news comments on domestic portal sites revealed that the top 10% of users wrote more than 70% of all comments. This shows that a small number of passionate users exert enormous influence as 'super spreaders' that influence public opinion on the Internet. In some ways, it may seem like a harmful thing, but I think it is necessary for startups, companies, and individuals to discover and use them well when promoting something. When we usually advertise and promote, we often do it towards the public (Mess). This is not only expensive because of its large scale, but also difficult to track performance. Here you can find methods that were popular in the past, such as micro-influencer and vertical viral. In a way, these are customized advertisements for super spreaders. So how can we take advantage of superspreaders? You need to lead them to become true fans of your brand or idea through continuous, authentic communication rather than a one-off approach. Furthermore, offering special benefits as a reward for sharing content could be a good strategy. Sometimes, there is a misconception that these super spreaders are people with 1 million subscribers on YouTube and tens of thousands of followers on Twitter, but surprisingly, this is not the case. These are often ordinary people with fewer followers than you might think. Instead, it is said that many of the person's friends are million YouTubers and influencers. So, rather than picking a popular person, a better approach is to pick a well-known ordinary person who is around famous people. From the content producer's perspective, if the content is properly delivered to the super spreader, the super spreader shares it in a high density and frequency manner, and influencers close to them quote it, creating a multiplication effect rather than simple addition. Rather than vaguely shouting at the public, I think the best way to create a buzz is to turn our attention to influential super-spreaders.

What I always say to people who ask me about artificial intelligence is, “Artificial intelligence = not LLM, and LLM is not all-powerful.” But there doesn't seem to be much interest. I earned an LLM in the field of marketing, and the hottest field right now is the LLM, so it was actually a weak cry, but after an error occurred as a result of a Google search, I personally think that some of the exaggerated expectations were eliminated and there was something to think about. Recently, Google's new AI-based search feature "AI Overviews" caused a stir when it provided incorrect information. Many people are pouring out provocative comments about this, predicting the fall of Google's search empire. However, it is important to determine the underlying cause of this incident and understand why similar errors may occur in other AI systems. I think a more productive way for us to talk about this is not to simply criticize, but to look at the cause of Google AI search errors, and prepare for the fact that the same problem may occur in other AI systems such as OpenAI, Grok, and LLaMA. In fact, there are posts on Reddit and other sites that say Grok and LLaMA's method of intentionally eliciting similar answers has been successful. (The key point is that this is a problem that the “creative” model must overcome, not simply flaw other models.) 1. Inherent limitations of large language models (LLM) Large language models generate text by learning from massive amounts of data from the web. Although it is excellent at generating contextually natural answers, it has the following fundamental limitations: Bias in training data : LLM is trained with public data from the internet. However, although there is reliable information on the Internet, there is also a lot of incorrect information. This forces the model to learn inaccurate information and ultimately increases the likelihood of giving incorrect answers. Lack of context understanding : Because LLM operates based on statistical relationships between words and sentences, it is difficult to achieve in-depth understanding like humans. This often leads to misunderstanding the context or leading to incorrect conclusions. 2. Hallucination phenomenon In the field of AI, the phenomenon of LLM generating incorrect information is called “hallucination.” Hallucinations occur when the LLM creates strange content that does not fit the context or presents information that is different from the facts. Incorrect token prediction : LLM generates text by predicting which token is most likely to appear next. However, if inappropriate tokens are selected during this process, absurd content may appear. Learning from misinformation : LLM even accepts misinformation contained in training data as is. For example, you may take an Internet joke or an unfounded article as truth. 3. Limitations of Retrieval-Augmented Generation (RAG) RAG is a proposed method to increase the accuracy of LLM. This method first searches for related documents and then generates text based on them. It is a method that has been mentioned a lot recently as a way to increase accuracy, but it is a methodology that existed in existing search operations. In some ways, it is a proven method, so its effectiveness is certain, but this method also has limitations. Inappropriate document search : RAG finds documents based on vast amounts of data on the web. At this time, documents containing inaccurate information may be retrieved, which in turn leads to incorrect answers. Error in context interpretation : Although LLM generates text based on retrieved documents, the context of the document may still be misunderstood . Google AI search error case Google's AI Overviews feature clearly demonstrated these limitations of LLM. AI Overviews attempts to directly answer user questions, but often provides inaccurate or misleading information. This leads to the following problems: There are two main errors that are currently spreading on the Internet. (screenshot above) Suggestion to put glue on pizza Providing incorrect information about using glue to properly stick cheese to pizza Recommendation to eat stones Giving incorrect health advice to eat a small stone every day. Google's AI search failure is not an anomaly. Other AI systems, including OpenAI's ChatGPT, Grok, LLaMA, and Claude, may face similar problems. Ultimately, this stems from the inherent limitations of LLM technology itself. This was revealed to Google in the process of incorporating it into its services. (In a way, it could be said that it was TDD), but there have already been incidents like chatGPT's King Sejong MacBook throwing incident. Errors in Google AI search result from inherent limitations of LLM and problems with training data. This problem can commonly occur not only in Google, but also in many AI systems such as OpenAI, Grok, and LLaMA. Finding a solution will require securing high-quality training data and developing models with improved context understanding capabilities. In addition, it is worth exploring ways to increase the accuracy of information by using technologies such as RAG. In fact, as mentioned above, in this case, the document itself as a reference in the RAG method is the problem. The important thing is not to simply criticize this problem, but to identify the root cause and come up with solutions. Only then will we be able to showcase a more advanced AI search function. (Even if it's not necessarily Google) We can give you a few more thoughts here. In the future, RAG based on verified information will become more important. Where can I find preprocessed and verified information? Same thing.

This is the <50 Things Koreans Like> series, which has been run by Gallup Korea since 2004. It's been 20 years this year. When I was a college student, I was a little shocked to learn that Gallup Korea (Gallup Korea Research Institute) was a different company with no connection to Gallup in the United States, but this is an editorial, and there are some notable aspects of this survey. @無異on Twitter visualized it better. There is something that came to mind in this survey, and that is reading. If reading was that important, book sales could not be this low. My personal guess is that people also responded by reading webtoons and web novels. The phenomenon of people enjoying more active hobbies as they get younger and switching to more passive hobbies as they get older can be explained by a number of social, psychological, and physiological reasons. First of all, differences in physical energy and stamina play an important role. Younger generations have more physical energy and are able to enjoy physically active activities. This naturally leads to active hobbies such as games, sports, and travel. At the same time, young people have a strong tendency to seek new experiences. This is related to what psychology calls ‘exploratory motivation’, which leads to the desire to explore and learn about the world through various activities. Additionally, young people value social interaction with friends and colleagues, and sports, games, and club activities are great ways to promote this interaction. At first, when I looked at this survey, I thought that people do a lot of active activities when they are young and do a lot of passive things as they get older, but when I thought about the fact that the survey was conducted between 2004 and 2020, I realized that people in their 40s today are still enjoying games from 20 years ago. And when I think about how this will be inherited in the future, I thought that it should not be simply viewed as active or passive. (Of course, there are physical issues that prevent you from enjoying it more due to physical limitations...) On the other hand, as we age, our physical abilities decline and it becomes difficult to continue doing activities we previously enjoyed. This naturally leads to a shift towards less active hobbies. According to cognitive psychology, as we age, our ability to process new information and learn decreases. Therefore, we prefer familiar and comfortable activities rather than complex and new activities. Additionally, after middle age, the tendency to seek stability and tranquility in life becomes stronger, which increases the preference for passive hobbies such as reading or watching videos that can be enjoyed in a quiet and calm environment. Changes in family members or social roles can also lead to more limited time and a preference for less energy-intensive activities. It is especially noteworthy that among men, a strong hobby of gaming has emerged since the Internet generation. Men in their teens and 40s enjoy gaming as their main hobby, reflecting their strong interest in digital content and interactive media. Beyond simple entertainment, games are also used as a social networking tool, which promotes social interaction among young men. In the case of women, it is impressive that listening to music has emerged as an important hobby from childhood due to the influence of K-POP and other genres. Listening to music has emerged as one of the most popular hobbies among women in their teens and twenties, showing that they find emotional comfort in music and prefer listening to it as a way to spend their free time. Additionally, the process of forming social bonds through fandom activities and feeling a sense of belonging as a member of a community is related to this. These changes in hobbies are also closely related to generational consumption patterns. Younger generations spend a lot of money on travel, new experiences, and consuming digital content. On the other hand, middle-aged and older people are more interested in health care, comfortable household items, and cultural activities (e.g. reading, listening to music). Actual industries are also reflecting these changes. Fitness centers, clubs, and sporting events target young people, while media content, cultural classes, and comfortable travel packages are increasingly targeting middle-aged and older people. Theoretically, this phenomenon can be explained through life cycle theory, social choice theory, and activity theory. Life cycle theory explains behavioral changes throughout the human life cycle, emphasizing the importance of adventure and exploration in youth and stability and rumination after middle age. Social choice theory emphasizes that as people get older, they value efficiency and stability in their choice of social relationships and activities, which explains the shift towards hobbies that provide mental satisfaction rather than active hobbies. Activity theory argues that maintaining active activity is important for successful adaptation to old age, but emphasizes that this activity does not necessarily have to be physical and may also include mental activity. In conclusion, the phenomenon of people enjoying active hobbies as they get younger and switching to passive hobbies as they get older is due to not only physical and cognitive changes, but also changes in social roles and the desire to pursue stability. By understanding this, I think it will be possible to develop customized services and products that reflect the characteristics of each generation. Considering the population, the market size of hobbies enjoyed by those in their 40s and 50s will grow larger, and the market size of hobbies enjoyed by those in their 10s and 20s will inevitably become smaller. Considering the predicted future, I think this would be a good point to think about.

When I meet startup CEOs recently, many of them are dreaming of entering the overseas market, especially the United States. Naturally, interest in community building is growing. However, many people mistakenly believe that creating a community is as easy as magic. Come to your senses! Community isn't that simple. One of the most common mistakes is rushing to set up a branch or office. We often see startups entering the U.S. setting up offices in major cities such as New York and San Francisco. This misunderstands the essence of community building. Running an office requires a lot of resources, including rent and staff costs. Can these investments really guarantee ROI? In most cases, no. You can't build a community by simply providing space. The key to community building is consistency. For example, you need to open Meetup consistently. You need to keep the event going even if there are only 3 or even 1 participants. It is important for the community to remain consistently present. It is rare for people to voluntarily become obsessed with a specific product and expend energy on it. Most people will not actively participate unless prompted. The first step toward community begins with individual meetings. Whether you have a large number of users or a small number of users, you need to personally meet and interview the people who use your product. You should ask them why they left, why they continue to use them, what features they find most useful, and collect their feedback. Based on the information obtained in this way, users are connected to each other. For example, you could introduce a few active users of your product in a certain region to each other and help them form a network. These small-start networks become the foundation of the community. Another problem is the deactivation of channels. We've created community channels on Slack or Discord, but most channels are only active with moderators or a small number of users. In these situations, it is unlikely that new users will actively participate. Most users see other people being active and get involved themselves. This requires consistent activity from community managers, but even managers will eventually get tired. Personally, what was very surprising was that there were many people who paid thousands of dollars to create such a community, and also paid fixed expenses of tens of dollars to run bots, etc. If you go to a restaurant where there are no customers, I should become a regular there! Or maybe I should promote this place! Do you think so? It can be if the taste is fantastic, or the service or something else provides an overwhelming experience. The same goes for products. Unless there is great innovation, most users are likely to be indifferent. In other words, the most reliable method is not to hope for a fluke and to attract someone, but to persistently engage in individual interviews, discussions, and consistent meetups. To solve this problem, a deep connection with users is critical. We meet with users individually to hear their experiences, reflect on their feedback, and connect them with each other. All products that we commonly refer to as having a successful community are doing that. If we tried to artificially create a community, every community would have done well. Communities directly operated by big tech companies are often less active than expected. This means that it is not an area where you can simply invest money. In fact, community building is something that team members or representatives who are passionate about our product must passionately expend energy on. It introduces users who use the product in a specific region and provides opportunities for them to communicate with each other. These small encounters become the starting point of a community. Lastly, it's actually easy for community builders/managers to fall into a trap. If the community does well, it's worth it, and if it doesn't do well, it's okay to take responsibility, but the work of creating and managing the community itself is often overlooked. There are many cases where you have to work 24/7, which requires more energy than expected and requires constant response. Community building is not magic. It requires consistent effort, dedication, and a deep connection with users. Communities aren't just created; they're carefully built. Come to your senses and create a community with a realistic approach.

Nowadays the market has become faster and more complex than ever. In this situation, traditional market analysis tools alone have limitations. In order to survive among numerous products and services, a differentiated strategy is needed, and an emerging methodology is ‘Minimum Marketable Difference (MMD).’ Although it is written in grandiose terms, it is a method of quickly responding to the market by selecting marketing points with minimal differences like MVP. The theoretical basis of MMD is as follows: Importance of Market Positioning: MMD helps your product occupy a unique position in the market. The key to positioning is to clearly convey the value of a product to consumers and differentiate it from competing products. Competitive advantage theory: MMD is a specific and practical way to realize competitive advantage. Drive consumer choice by highlighting the clearest, most market-appealing differences that set your product apart from competitors. Economic Value Proposition: MMD succinctly expresses the actual value consumers get from using the product. This makes it easier for consumers to recognize the economic benefits when choosing a product. Let’s take a closer look at the three elements that make up MMD: Minimum: MMD should be concise and clear. It should be simple enough to be expressed in a one-line summary. Marketing: MMD must appeal to the market. The focus should be on solving real problems for your customers. Difference: The MMD must clearly differentiate itself from competing products. Even if it addresses the same problem, you need to show why your product should be chosen. In conclusion, MMD is a key strategy for successfully positioning a product in the market and driving consumer choice. It helps you gain a competitive advantage by communicating your product's characteristics concisely and effectively. In order to survive and grow in a complex market, it is most important to find your own MMD and provide differentiated value. Rather than the retention management method of hooking, maintaining, and tracking that was popular in the past, I think this is a good methodology to use when you need to find an initial marketing outlet or quickly bring a product to the market. Division Detail Target Customer Customer characteristics Main needs Problem Problems customers are experiencing Limitations of current solutions Solution Solutions we provide Core functions and features MMD Differences from competing products Unique value we provide to our customers Competitive Advantage Advantage over the competition Position in the market Messaging Key messages to convey to customers Marketing and Sales Strategy Metrics Performance Measurement Indicators (KPI) Evaluate and improve the success of your strategy Customer Engagement How to communicate with customers How to collect feedback Market Trends Detect market changes Strategies for seizing opportunities How to use templates This template is designed to help you fill out specific information for each item. In each 'Details' column, provide specific information about that segment. for example: Target audience: This details the characteristics of your target audience, including their age, gender, occupation, and interests. Additionally, we summarize their main needs and the pain points they experience. Problem: Describes the problem the customer is currently facing and the limitations of the solution they are currently using to solve that problem. MMD: Clarify what unique value or functionality your product or service offers compared to the competition.

There is a heated debate among office workers in the United States over the topic of not properly using vacation time. The so-called “quiet vacation” concept refers to the behavior of spending almost a vacation-like time without using vacation time. This kind of thing is usually called sabotage... Well, it seems like a topic that came up in the context of a quiet resignation. Data revealed through the "Out of Office Culture Report" report recently released by research firm harrispoll shows that this problem is more serious than expected. Surveys show that most workers are satisfied with their vacation policies. However, only a small number of people actually use all of their permitted vacation time. In particular, millennials responded that they were unable to enjoy their vacations properly due to the constant pressure and heavy workload of work. What's interesting is that even if the workplace maintains an "unlimited vacation" policy, there are many people who don't actually go on vacation. But that really just means you don't take any official "vacation". The emergence of ‘quiet vacation’ Faced with these challenges, millennials are responding in a unique way: ‘quiet vacations.’ This refers to the act of informally taking time off without formally requesting leave. For example, some employees use methods such as making it look like they are active on work messengers or scheduling messages outside of regular business hours to make it look like they are working overtime. Cultural factors hindering vacation use Research shows that many workers fear being judged negatively when they request time off. This culture discourages workers from openly expressing their need for rest, which in turn has a negative impact on the quality of work and personal well-being. Future plans? The report highlights the need for a workplace culture that encourages leave use. It is important to regularly encourage vacation use within the workplace and create an environment where employees can completely disconnect from work while on vacation. Additionally, it is necessary to ensure that workers can sufficiently rest and recharge through vacation. How is it different from sabotage? ‘Quiet vacation’ refers to the act of office workers taking a break unnoticed without going through formal vacation procedures. This is usually done by passively taking breaks during work hours, or by pretending to stay on task while actually taking breaks. These behaviors occur due to a strict work environment, heavy workload, pressure or fear of using vacation, and are often self-protective as employees seek to relieve stress or seek personal well-being. On the other hand, ‘Sabotage’ refers to an intentional act that intentionally disrupts or causes damage to work within the workplace. This may be due to dissatisfaction, revenge, or other negative feelings toward the company or co-workers, and may result in intentionally reducing work efficiency or causing losses to the organization. Sabotage is an act that causes clear harm to an organization and is a serious problem that may be punishable by law. In the end, the problem arises from not being busy. From a legal perspective, it may be due to intention, but in the end, it can be seen as a result of a survey that if there is no 'atmosphere where one can relax to their heart's content,' people rest vaguely and engage in behaviors that actually reduce productivity. The so-called "work hard and rest properly" behavior is occurring in startups that do not divide work as properly as expected, mid-sized companies that have too many people, and large companies that have severe silos. Although this is a story about American office workers, I think Korea is actually no different. In the past, while talking with CEO Han, I talked about an employee who disrupts the work atmosphere by using blinds, communities, DM, etc. The conclusion was ‘I’m not busy’. If you're really busy, you can't do politics or do nonsense. Rather, these things are much more likely to occur when there is nothing to do and you are looking at other things, so it is important at the company and organizational leader level to work hard and rest well with clear goals and schedules.

The concept of a language model has emerged and the method and principles of its operation have been discussed several times. Attention method and transformer method are already widely known operation methods. However, this is a concept understood by those interested in existing ML, and was generally accepted as 'I guess there is such a thing.' The Scaling Monosemanticity paper published in Anthropic explains the operating principles of artificial intelligence (represented by language models) in a more understandable way. What do you usually think of when you hear the words ‘The Golden Gate Bridge’? Some people may immediately think of the Golden Gate Bridge in San Francisco, while others who hear it for the first time may think, 'Is it a bridge with a golden gate?' In our heads, we form thoughts based on associations based on keywords such as ‘San Francisco’, ‘bridge’, ‘door’, and ‘bridge’. The picture above provides a visual representation of how these related concepts are positioned within the AI ​​model. Main Component Description Nearest neighbors to the Golden Gate Bridge feature : This section shows other features related to the 'Golden Gate Bridge' feature. Each feature indicates how close they are to each other within the model. San Francisco region : Concepts closely related to the 'Golden Gate Bridge' feature and include various references, primarily related to San Francisco. For example, 'San Francisco, California', 'San Francisco references', 'San Francisco area locations', etc. Earthquake region : Contains earthquake-related concepts that relate to the 'Golden Gate Bridge' function. There are earthquake-related references, such as '1906 SF earthquake', 'San Andreas fault system', and 'Northridge and Loma Prieta earthquake'. Other related concepts : A variety of geographic and cultural concepts are included, including the San Francisco 49ers team, UC Berkeley identifiers, New York City districts, the Eiffel Tower, tourist attractions and landmarks, and more. To get a clearer picture of how an AI model understands text, we analyzed the activation patterns of neurons within the AI ​​model. ‘Features’ refer to the patterns in which multiple neurons fire together, and analyzing them can reveal how AI understands the same concept across different languages ​​and formats. This research helps us better understand how AI models work, making them more secure and trustworthy. Main concepts Feature Extraction (Dictionary Learning) : Neurons in an AI model individually represent different concepts. A ‘function’ is a combined pattern of activation of multiple neurons. Just as several letters come together to form a word, the combination of several neurons creates a specific function. Analyzing features provides a clearer picture of how an AI model understands text. Characteristics of the function : Features can appear the same in different languages ​​and formats (text, images, etc.). For example, a feature called 'Golden Gate Bridge' is activated equally across text in different languages, including English, Japanese, and Chinese. Functional manipulation experiments : We experimented with how the AI ​​model's response changed by artificially enhancing or suppressing certain features. For example, activating the 'Golden Gate Bridge' feature will cause the model to mention 'Golden Gate Bridge' in almost every question. Language density: Where are the words clustered? Density : The upper left portion of the graph indicates that most data points are located at activation level 0. This means that most inputs will rarely activate this feature. Conditional Distribution : It represents the distribution of activation of a feature according to its activation level (from 0 to 1). Colors represent Claude's concreteness score: Blue (0 points): Not relevant Light Orange (1 point): Vaguely related Dark Orange (2 points): Related to adjacent text Red (3 points): Clearly identifies text Examples inputs sampled from intervals : The example input below shows text and images sampled within each activation interval. The example on the left represents a low activation level (0.1 to 0.3), and the example on the right represents a high activation level (0.7 to 1.0). For example, at lower activation levels, less relevant text such as 'Presidio' and 'Union Square' appears. At high activation levels, text appears that explicitly mentions the 'Golden Gate Bridge'. Easy to understand To get a clearer picture of how an AI model understands text, we analyzed the activation patterns of neurons within the AI ​​model. ‘Function’ refers to the pattern in which multiple neurons fire together, and analyzing this can reveal how AI understands the same concept across different languages ​​and formats. This research helps us better understand how AI models work, making them more secure and trustworthy. What is meaningful about this paper is that it clarifies how language models work. It also means that the pace toward multimodal artificial intelligence will accelerate in the future. Due to the above neuron-based association methods, there can also be talk about how language models can be used better.

Last night, Microsoft presented the future of computing by unveiling its new Copilot+ PC based on artificial intelligence (AI). In this article, we will take a closer look at how this innovative technology will change our daily lives and work. The dawn of a new era, Copilot+ PC Copilot+ PC is not just a computer with improved performance. It aims to be a true AI companion that can understand and predict users' intentions and needs. Dubbed the ‘everyday AI companion’, this technology will provide seamless support across all the devices and applications we use. Core features of Copilot+ PC Multimodal interface: It provides a richer work environment for creators and developers by freely handling input and output in various formats such as text, images, and video. Personalized data management: Significantly reduce time wasted searching for information with a memory system that remembers important information and context and instantly retrieves it when you need it. Enhanced Reasoning Capabilities: New AI capabilities that help us perform complex tasks will help us solve everyday problems. In addition, Copilot+ PC boasts NPU performance of up to 40 trillion operations/second, ultra-fast AI processing, and excellent battery life. Additionally, the 'Recall' function allows you to easily find all content you have accessed on your PC, and you can experience a variety of AI-based functions such as live captions, real-time translation, and photo/video editing. Evolution toward the future The advent of Copilot+ PC will fundamentally change the relationship between users and their devices. Microsoft introduced various use cases where AI contributes to improving individual creativity and productivity. For example, you can instantly find key information in documents or perform complex data analysis with a single command. Copilot+ PCs are available starting at $999, and leading manufacturers including Surface Laptop and Pro, including Acer, ASUS, DELL, HP, LENOVO, and Samsung, are preparing to release them. As it surpasses Apple's MacBook in terms of performance and price competitiveness, it is expected that Korean consumers will also find more attractive options. Microsoft has declared its vision to bring AI innovation to the PC market with Copilot+ PC. Looking at the features released this time, we can see that multimodal Copilot using cameras, microphones, etc. has been actively introduced to the “easy to carry” Surface series. Summary of functions Features of Copilot+ PC Equipped with a powerful NPU (Neural Processing Unit) with 40+ TOPS performance to achieve the highest performance and efficiency AI workload processing speed up to 20 times and efficiency improved by 100 times compared to existing PCs Delivers great battery life and app experiences Windows Copilot Runtime Development platform that combines AI with Windows Includes over 40 on-device AI models Enables developers to import their own models and run them on Windows Windows Copilot Library A collection of AI APIs shipped with Windows Helps developers easily add AI features to their apps Provides various APIs such as Studio Effects, Live Captions, OCR, Recall, etc. A new AI-powered experience Recall: The ability to instantly find almost anything you see on your PC CoCreator: A collaborative AI image generator that turns ideas into reality using natural language and ink. Restyle Image: A photo editing feature that reorganizes your personal photos into a new style. Productivity tools for developers Dev Drive: High-performance storage optimized for development tasks Sudo for Windows: Support for running elevated commands in the terminal File Explorer source code integration: track commit messages, file status, etc. WinUI 3 and WPF improvements WinUI 3: Latest UI framework with Maps control and .NET 8 support WPF: Windows 11 theme support makes it easy to modernize your app design Manufacturing your own chips? Since Microsoft has expertise in software and operating systems, it has unveiled the Silicon chip with the goal of providing the best user experience through close integration of hardware and software through collaboration with chip manufacturers. In terms of performance, it was announced that it is comparable to Apple's M3, which means that consumers have an increased number of very attractive options. However, this is a slightly different approach than Apple designing and manufacturing its own silicon. Instead, both companies have something in common in that they seek to achieve optimal performance and user experience through the harmony of hardware and software.

Gamification is not just a fad, but an essential strategy for user engagement and service maintenance. Considering gamification, especially in the early stages of a service, can be an important approach to maximizing user experience and securing long-term customer loyalty. 1. What is gamification? Gamification is a strategy that introduces elements of games to engage users, change their behavior, and form habits. This aims to motivate users and provide them with a more positive user experience, thereby increasing the frequency and length of time they use our services. 2. Benefits of gamification Improved user engagement : Game elements (rewards, achievements, levels, etc.) encourage users to use the service frequently and consistently. Data collection : User activity data can be analyzed and used to improve services. Increased user loyalty : Gamification allows users to engage more deeply with your service, which leads to long-term user retention. 3. Successful gamification cases LinkedIn : LinkedIn keeps users engaged by motivating them to complete their profiles and providing opportunities to be recognized for their expertise. Duolingo : Duolingo, a language learning app, encourages users to stick with the app through daily learning goals, consecutive study days, and more. Google Maps : Users of Google Maps can earn points and level up by writing reviews, adding photos, and updating information. When you level up, you become a local guide, which provides a powerful incentive for users to continue contributing. 4. Necessity of early introduction of gamification Integrating gamification from the early stages of service development is critical to maximizing user experience from the start and securing an early user base. The more positive the initial user experience is, the more likely users are to trust your service and continue to use it over the long term. Additionally, gamification strategies can be an important means of strengthening the characteristics of a service and differentiating it from other competing services. Gamification is more than just a trend, it is an essential element for the successful launch and growth of a service. Gamification, which enriches the user's initial experience and encourages continued participation, must be carefully considered from the initial stage of the service. This will help you maximize user engagement and ensure the long-term success of your service. This story does not refer to the early stages of ‘product’ development. This means that it is better to start planning a specific function or service early on.

Until last year, the United States, Japan, China, and the EU had been preparing various bills since the keyword “Large Scale AI” emerged. The EU seemed to put a little more emphasis on regulation, while the US/Japan/China seemed to put more emphasis on promotion. This is a topic we talk about every year, but currently, this discussion is not taking place properly in Korea. There are numerous political scandals and incidents in Japan and the United States, but these are handled bipartisanly. ( Biden is preparing for the presidential election , and the Kishida cabinet is also recording an approval rating of less than 20% due to the bribery scandal ) The United States, home to the world's leading artificial intelligence companies such as OpenAI, MS, and Google, has publicly released its entire national roadmap. This roadmap announcement is a report created through nine rounds of “AI Insight Forum” in which the bipartisan Senate Task Force and more than 150 experts from industry, academia, and civil society participated. (I attached it after OCR processing.) The content can be broadly divided into three categories. We have made an in-depth plan on topics such as things to be implemented immediately: budget preparation and execution, procedures to be followed: bill proposal, things that do not yet have answers: artificial intelligence ethics, AGI, etc. Artificial intelligence becomes a rising priority for institutional and policy funding AI research and development (R&D) support between government agencies Enhancing AI competitiveness by providing funding for semiconductor R&D Expansion of National AI Research Resources (NAIRR) and support for AI Grand Challenge Program National Institute of Standards and Technology (NIST) strengthens AI safety improvement activities AI and robotics convergence research and development and policy establishment Proposal of new law Leveraging public-private partnerships to advance AI Establishment of legislation related to human resources education and training for participation in AI economy Promote consistent and effective application of existing laws on AI Development of AI-related legislation in areas such as online child/deepfake sexual exploitation, privacy, and medical care Additional research areas Long-term impact of AI on labor and exploration of countermeasures Assessing best practices regarding the level of automation of high-risk tasks Assessing the feasibility of developing artificial general intelligence (AGI) and the resulting risk scale Establishment of strong export control standards for AI systems that pose a national security threat The 22nd National Assembly of the Republic of Korea will begin soon, and I hope that lawmakers with bipartisan expertise will join forces in this area. There are quite a few IT-related lawmakers with engineering backgrounds in this National Assembly, so I look forward to it.

While reading a newspaper article some time ago, I came across the expression ‘The Toilet Theory of the Internet’. This refers to the phenomenon of users using the Internet in the bathroom or during other short moments of spare time . To be more precise, in the past, users considered the act of ‘searching’ to be a high-level action and did it with great effort, but now they do it briefly and lightly. This theory suggests that Internet use has gone beyond simple knowledge acquisition and has become a tool to fill trivial gaps in daily life. These changes provide search engine providers with the opportunity to increase user accessibility and maximize the efficiency of information consumption. Introduction of Google’s AI tools and their impact When looking at the keyword search, Google cannot be mentioned. Google recently introduced new tools that utilize AI technology to provide faster and more accurate summaries of search results. This allows users to obtain information more quickly and fits well with the user behavior mentioned in the 'Toilet Internet Theory'. However, these changes may have negative impacts on website operators and content creators, such as reduced traffic. Recently, Google talked about artificial intelligence-powered search through its 2024 I/O. Personalized search results Advances in AI technology are likely to advance in the direction of providing user-tailored search results. We will provide more accurate and personalized information by analyzing the user's previous search history, location information, and preferences. The rise of voice and visual search With the increased use of mobile devices, the proportion of voice and image searches will increase. This can make information more accessible and improve user experience. Search optimization through deep learning AI technology will evolve to better understand users’ search intent and deliver more relevant results. This provides a path to increase search accuracy and improve user satisfaction. The “search engine” itself is a relic of the past. This somewhat cheeky remark was said by Perplexity, who recently became a unicorn. They describe themselves as answer engines and say that the future of search engines will be answer engines. Perplexity is building the next-generation answer engine to help users find information in new and effective ways. “Perplexity is building the next generation answer engine , empowering our users to find information in new and more effective ways.” Their argument is that existing search engines pass all the burden on to users. The user is responsible for the entire process of thinking about the search term, entering it, and finding the desired answer from the results, which creates a difference in finding good information. So they said they would provide the correct answer, but on the other hand, I thought it was dangerous. What if the answer is wrong? That thought. As seen in the CEO's recent interview with Bloomberg after seeing Google's announcement, they seem to be acting with a fairly clear philosophy. I've become a unicorn and now I have to run. Can we really make Dr. Cheokcheok say only the correct answers they say? (Of course, not everyone who is a doctor knows this ^^) Google is shaping the future of search. For the past 20 years, we have been exploring the Internet through search engines such as Google. But with each passing year, these search engines become increasingly noisy and less reliable. Those 10 blue links provided by search engines have turned into sponsored posts, ads, and clunky, ad-filled blogs. The future of search is delivering instant answers from quality sources across the web, not links. From academic research to news articles, explore every corner of the Internet in real time. Answers are derived from reliable sources and include transparent citations. Perplexity is the world's first answer engine, redefining search with answers to all your questions. Original text We are building the future of search. For the past two decades, we have navigated the internet through search engines like Google. With every passing year, however, these search engines have become noisier and less reliable. The ten blue links they provide have transformed into sponsored posts, advertisements, and clunky, ad-filled blogs. The future of search provides immediate answers, not links, from quality sources across the web. It explores the corners of the internet in real-time - from academic research to news articles. The answers are derived from trusted sources and include transparent citations. Perplexity is the world's first answer engine: redefining search with answers to all of your questions. Recently, Arc Browser also released a separate app called Arc Search, introducing a new approach to search results. When you search, a results page and additional links are provided, and the experience itself is very refreshing. In particular, I was impressed that Search only released a mobile app so that it could be used at any time in accordance with the bathroom theory. I can't move my hands very well... In this context, GPT-4o, recently released by OpenAI, also made artificial intelligence lighter and easier to use. Now, if we reduce the hallucination here and make it possible to give more professional answers, it will become an answer engine. Were we all hoping for a magic lamp genie to get the right answer? Could it be that I wanted an employee who would share my work with me? A thought suddenly occurred to me.

Not long ago, I came across the nutrition section of ‘Made in Gyeongsang’ by Physic University. To be more precise, I was watching the news and the content was very criticism-oriented, so I wondered what it was like. In fact, there seems to be a clear line in the content that strays somewhere between rudeness and comedy. Among the people who came out, if even one of them had anything to do with nutrition, it could be considered a self-destructive joke, but I don't think there's anything like that. Last night, Physic University posted a polite apology. In fact, as I was watching the video, I naturally looked at YouTube operated by the Yeongyang County Office and learned that a wild vegetable festival was recently held. I watched several videos and what surprised me was that there were no people there. Personally, I have lived in Seoul and Seongnam since elementary school, so I actually go to the countryside only for holidays. As a result, I used to indirectly see the topic of fat loss as something that was covered in the media. Last week, I had to go to Gimcheon for some business at the Road and Urban Corporation. Even though I arrived at lunchtime on a Thursday, it was very quiet. It was a neighborhood called Yulgok-dong, and although it was a new city, it felt very neat and orderly, but it was strange because there were no people. There are a lot of apartments, a school, a shopping mall, a library, etc., but I don't know if it was the time when there were no people or if there really wasn't any floating population, but it was very peaceful, or rather quiet, even though it was around 12 o'clock. Anyway, my interest naturally fell on the word fat loss, and both Korea, China, and Japan have similar problems. Among them, I recently watched a short documentary on population extinction that aired on NHK, and I thought it might be a hint to us in some way, so I'm leaving this summary. Japan's fat loss crisis is not just a statistical warning; it is a social problem that can have a serious impact on current and future generations. According to the 'Population Strategy Council' chaired by the Japanese government, approximately 43% of Japan's more than 1,700 municipalities are likely to face extinction. This is mainly due to the decline in the young population, especially women in their 20s and 30s, who are essential to the economic activity of the community. Some regions of Japan are trying a variety of creative responses to the problem of population decline. For example, Nagashima Village is encouraging young people to return to the village after studying through the 'Yellow Tail Student Loan' program, and Ohira Village is revitalizing the local economy and population by encouraging young families to move through strengthened childcare support. . Metropolitan areas such as Tokyo, Kyoto and Osaka have been pointed out as 'black holes' and attract a young population, but their high cost of living and low birth rates are worsening the population problems in rural areas. This is giving rise to the problem of not being able to increase the birth rate while absorbing the local population. In fact, this problem is well expressed in Korea as a phenomenon of concentration in the metropolitan area, and in Japan, each region is allowing the 2030 generation to live and engage in economic activities in the region by providing direct economic support or providing welfare to local governments. It seems like they are considering even inducing childbirth. In the case of Japan, it is said that if you go to live in a rural area, you will not go even if various financial support is provided, including settlement fees. (In response to this, former Interior Minister Hiroya Mitsuda said, “Success stories at the community level do little to solve the overall population problem.”) For reference, in China, a policy is being implemented to force young people to stay in rural areas. (This is possible because it is China) In fact, we all know that moving out of the metropolitan area will lower housing prices by about 30% and provide various advantages, but we do not go to the provinces for various reasons such as friends, work, culture, and infrastructure. It's the same for me too. It may seem like Seoul is just moving in the direction of expanding more and more, but in fact, our government is also doing various things. In fact, even a year or two ago, I had some hope that if working from home became routine, people would live more spaciously as the need for proximity to work would decrease, but it seems that working from home has not taken hold, and that does not mean that routes such as GTA, SRT, or KTX will be popular. I don't think this can be solved by pressing for a long time. I think it would be a way to make local governments or companies take root in local areas like Dongtan, Ulsan, Jinju, or Sejong and make them look like local pros, but I wonder who would go for it. In fact, although we all understand the phenomenon and the cause, it seems like a problem we cannot solve because it is difficult to do it ourselves. Everyone knows how to solve it. Don't fight, don't compare, go down to the countryside, have a lot of kids, and live satisfied with what you lack... But do you really want to do this? If you say that, everyone says that's not the case... It's frustrating because I don't know whether to call this situation a state of cognitive dissonance where everyone knows the answer but can't put it into action, or the elephant in the room. The idea came to this point while watching the story of the nutritional group at Food University, but it would be difficult for me to put it into practice right away. I have a lot to think about. The elephant in the room This expression is used metaphorically in a particular situation to refer to an obvious problem or uncomfortable truth that everyone is aware of but is reluctant to talk about. It is an expression mainly used to refer to a big, obvious problem that people want to ignore or avoid, but that ultimately needs to be solved.