Andrew Ng and Yann LeCun on the AI Race Between the US and China Recently, two of the most influential figures in the AI field, Andrew Ng and Yann LeCun, exchanged intriguing views. Their conversation, held on Facebook, went beyond a simple exchange of personal opinions and offered crucial hints about the future direction of the AI technology race. The reason the conversation between the two men garnered so much attention is clear: it offered a concrete and candid analysis of the strategies the two giants, the United States and China, should pursue in the AI field . 🇨🇳 China aims to lead AI with open source Professor Andrew Ng recently made this claim in Deeplearning.ai's newsletter, The Batch: "There's a clear path for China to surpass the United States in AI. While the United States currently holds the lead, China is gaining tremendous momentum through its open-source ecosystem and aggressive semiconductor design and manufacturing strategy." Andrew Ng pointed out that the closed approach taken by major US AI companies in recent model development processes has resulted in slow knowledge circulation and high costs . Indeed, recent AI leaderboards like LMArena and Artificial Analysis show that the top closed models are still dominated by US companies like Google (Gemini 2.5 Pro), OpenAI (o4), and Antropic (Claude 4 Opus). However, the top open models are mostly Chinese-developed, such as the DeepSeek R1, Kimi K2, Qwen3 series, and Zhipu's GLM 4.5. In other words, while the United States is still ahead in terms of model performance itself, China is in hot pursuit with a strategy of rapidly circulating technology and knowledge. 🇺🇸 Yann LeCun agrees: "The speed of AI development = the speed of knowledge diffusion." Yann LeCun, Chief AI Scientist at Meta, added his thoughts via a Facebook share: "I completely agree with Andrew. As I emphasized in my Senate testimony, the pace of scientific and technological progress depends on the speed with which information circulates. The remarkable progress in AI over the past 15 years has been due to the open-source nature of papers and code. More recently, with the secrecy of Google, Antropic, and the increasingly closed OpenAI, despite its name, the pace of AI progress has already begun to slow." LeCun's remarks emphasize the importance of open knowledge sharing in the AI ecosystem, drawing on historical experience. In other words, he made it clear that a slowdown in the speed of information circulation will inevitably lead to a slowdown in the pace of technological innovation. ⚙️ Semiconductors and supply chains, another key frontier Professor Andrew Ng emphasized that China is catching up not only in AI models but also in the hardware competition. Huawei recently unveiled the CloudMatrix 384, a GPU capable of competing with NVIDIA's GB200. This architecture achieves performance by integrating significantly more low-performance chips (384 instead of 72) than the latest high-performance GPUs from the US. China has already rapidly overtaken Europe and the US in the traditional automotive industry by leveraging the emerging field of electric vehicles. Huawei's semiconductor strategy can also be described as embracing this "quantity overwhelms quality" approach. Meanwhile, the US still relies on Taiwan's TSMC for its semiconductor supply chain. Concerns have been raised that if China strengthens its own semiconductor production capacity and the US remains dependent on external sources, the entire US AI strategy could be threatened. A recent column in China's leading state-run media outlet, the People's Daily, reads as follows: Nvidia, how can I trust you? https://www.stcn.com/article/detail/2895954.html They strongly criticized the security issues surrounding Nvidia's H20 chip. They warned that if the chip contained a "backdoor," it could pose a serious threat to essential infrastructure such as automobiles, telemedicine, and payments. Nvidia denied the existence of any backdoors, but they pointed out that it would be difficult to restore market trust without specific security verification at the level required by the Chinese government. They emphasized that respect for the law and security compliance are prerequisites for foreign companies to remain in the Chinese market. They urged CEO Jensen Huang to demonstrate his commitment to "upholding the law" through action. It would be good to read it together. (Of course, I read it using a translator. I don't speak Chinese.) 🚨 Choosing a 'closed door' ultimately slows down innovation. The key points emphasized by the two experts are as follows: AI innovation happens most quickly when knowledge and technology are freely shared.

Personally, since the beginning of this year, I have been giving special lectures at an international school called SALT, and I have felt that this kind of education is absolutely necessary and has potential. On the contrary, I have also thought, why don't they do it elsewhere? When you are young, you have a lot of things you want to do the most, and at that time, there is nothing that has as much synergy as entrepreneurship education. In fact, they are being done in China/USA/Europe, and I think that our country's education should also change. Anyway, I think I will tell you about a really interesting school in Texas, USA. Imagine studying at school for only two hours a day, and the rest of the time following a special curriculum led by artificial intelligence (AI). When I first heard this news, I was honestly skeptical. But Alpha School, which started in Austin, Texas, is exactly that kind of school. The school started in Austin, Texas, a tech hub, and has since expanded to Miami and Brownsville, with plans to expand to several cities across the country this fall, including New York and Orlando. What on earth is it about this school that attracts people's attention? AI and Human Collaboration: ‘Guides’ Instead of ‘Teachers’ The most unique thing about Alpha School is that there is no concept of a teacher. Instead, an adult called a 'guide' supports students' learning and growth. The actual class content and personalized learning plan are provided by AI. AI analyzes each student's ability in real time and provides the best customized learning. Thanks to this, students in the same class learn completely different content depending on their level and interests. For example, 12-year-old Byron Attridge is currently in seventh grade, but is learning math at an eighth-grade level, reading at a ninth-grade level, and language arts at a tenth-grade level. He says: "I like that I can learn at my own level and pace, without being tied to what my friends or teachers teach." MacKenzie Price, co-founder of Alpha School and popular podcaster, puts the point home: "90% of good education is motivation. When AI teaches the subject, the guide can focus on the emotions and motivation of the students." You learned about entrepreneurship in school? At Alpha School, only two hours of the day is devoted to traditional subjects like math and language, while the rest of the time is filled with hands-on, collaborative projects where students can get involved. For example, last year, fifth and sixth graders built and operated a real food truck. In the process, students developed their collaboration and problem-solving skills by budgeting, creating business plans, and cooking. In addition, students create their own creative output through a special program called the 'Masterpiece Project'. In this project, students must find unique and new perspectives that only humans can create, and that AI cannot provide. In fact, the outputs that students created are as follows: A teddy bear that recognizes and reacts to emotions Chatbot that provides dating advice Creating Texas' Largest Mountain Bike Park Through this project, students naturally train creative thinking skills that differentiate them from AI. The success and limitations of this approach But not everyone is sold on Alpha School’s educational approach. Critics say that excessive reliance on AI could diminish children’s social and empathetic abilities, and that an overly personalized learning environment could undermine the fundamental role of schools in socialization. Additionally, it is controversial that it may be considered a high-end education accessible only to a certain class of students, as the annual tuition is approximately $40,000 (about 55 million won) . Still, Alpha School offers an interesting direction for future education. By leveraging AI to respect each individual’s pace of learning and empowering students to solve real-world problems through creative projects, it effectively complements what has been missing from traditional school systems.

Technological advancements mean expanding horizons . In fact, Cursor became the fastest-growing company in SaaS history, going from 1M to 100M ARR in just 12 months . This was not a coincidence, but an achievement made possible by PMs thinking in AI . In this way, AI is opening up new problem spaces and solution spaces for PMs at the same time. I wrote this about 10 months ago. PM's Core Responsibilities: The Three Remain the Same, But How They Are Done Has Changed The three core roles of a traditional PM are: Understand your customers' problems Prioritize and decide which problems to solve Organizing and delivering effective solutions AI doesn’t break this structure, but it does revolutionize how each step is executed . Understand: The problem itself changes ✅ Expanding the problem space Problems that were previously “given up due to technical limitations” are now within the realm of being solvable by AI. In fact, customers don’t directly express needs that they think are “impossible” until they experience it themselves. In the case of Canva, customers didn’t say, “I want to make designing easier with AI,” but once the feature was released, it became the solution they wanted . ✅ Evolution of data analysis methods Qualitative data that was previously scattered across customer interviews, support tickets, chatbot conversations, etc. can now be analyzed in real time and automatically using AI tools. Rather than simply gathering insights, we detect trends as they emerge, like news, and provide deep insights. Prioritize: It’s not a question of can, it’s a question of worth . AI shakes up all the traditional “feasibility, impact, risk, cost” metrics. Feasibility : Thanks to AI, functions that were previously impossible can now be implemented within weeks. Impact : Personalization becomes a strategy, like Duolingo's real-time lesson difficulty adjustment . Risk : Additional AI-specific risk factors, such as hallucinations, bias, and regulatory issues. Cost : It may seem cheap at first, but the cost can explode as usage increases . According to the survey results, AI assistant features were not chosen by 64% of users. If you force a feature that customers don't want, their trust in the product itself can be shaken. Execution: AI is more than just an assistant; it’s a key tool for designing experiences. Previously, AI was just an “add-on,” but now it’s a force for redesigning the entire production experience .

What is GTM? As the name suggests, after creating a good product/service, how do you launch it into the market, make a profit, reach customers, and have them use the product/service repeatedly? 1. What is the difference from existing marketing? What is the difference from existing sales? F1 opens. Marketing Team: Create atmosphere before the game, increase attendance Sales Team: F1 Driver (Running on the Front Line) GTM Team: Planning the flow/strategy of the entire race → When to change tires? How to change tires? How many laps to do? Japanese version Marketing and sales are tactics and GTM strategies. 2. Product Owner/Product Manager What is the difference? It should be iterative and closely linked to building product solutions and defining business models → Market/Sales/Users PO → Product UX/UI, development, planning, business, etc. No matter how great or innovative a product is, it is difficult to establish itself in the market without a GTM strategy. 3. What is the goal of GTM? Market Success: The successful introduction of a product or service into the market. Reaching your target audience: Effectively reaching your product to your defined target audience. Gaining a competitive edge: Gaining a competitive edge over your competitors in the market. Revenue Generation: Ultimately, it's about generating revenue for your business. 'If you make it, it'll sell' → Nonsense... Who would write that??? Side project 'I'll write if you make it' → Friends/family → Malicious indicators (noise) → Long tail indicators appear... What is it? GTM → The process of turning 'this will sell' into a concrete science

"Sorry, that discount doesn't actually exist." Recently, Air Canada’s chatbot was misleading customers by telling them “50% off flights” and ended up in court. The court sided with the customers and the airline had to keep its promise of a discount because of the AI’s “lie.” The problem of ‘hallucinations’ , or false answers produced by the latest language models including ChatGPT, is no longer a simple technical mistake, but a serious issue causing social and legal repercussions. 🧠 What is AI's illusion? The term hallucination makes people feel like they are seeing illusions or illusions. However, AI does not actually see hallucinations, but rather, it simply predicts the next word probabilistically and creates a 'plausible but wrong answer' in the process of connecting the most plausible words. Just as a person cannot suppress a sneeze, AI hallucinations are a natural byproduct of the system's normal operation. For example, when asked, “Who won the 2005 Nobel Peace Prize?”, the AI would answer with a person who was mentioned more frequently in the media than the actual winner. The more often a word appears in the training data, the more likely it is that the AI will think that word is the correct answer. (Insert image: How AI creates hallucinations - The gap between next word probability predictions and actual facts) 🧪 Why is it so difficult to completely solve? Amr Awadallah, founder of Vectara and former Google executive, says: "Because the way AI models work is probabilistic, it is impossible to eliminate hallucinations 100%." This is a structural limitation of AI technology. In particular, the more excellent the reasoning ability of recently emerging models, the more likely it is that they will hallucinate during the process of internally attempting to answer multiple times. The accuracy of the latest models is gradually increasing, but they are still at a level that is unstable for use in important tasks (medical, legal, etc.). 🔍 How to solve it? AI companies are trying several approaches to reduce the likelihood of hallucination. 1. RAG (Retrieval-Augmented Generation) The RAG method is a method in which AI does not rely solely on its own learning data when generating answers, but instead references external data (news, search results, internal documents, etc.) in real time to cite accurate information along with the source . For example, if a customer asks, “What is your product refund policy?”, the AI does not simply answer with what it has learned, but provides the exact answer along with the source from an actual internal corporate document: “Refunds are possible within 7 days according to Article 3, Paragraph 2 of the internal policy document.” 2. Operation of auxiliary model for verification Companies like DeepMind and Cohere run smaller AI models that verify the answers provided by the main AI model , thereby improving accuracy by filtering out incorrect information in advance. 3. Mathematical automatic reasoning AWS uses “automated reasoning checks” to let the AI filter out answers that don’t make sense or make sense logically. This is especially useful in areas like finance and healthcare where accuracy is critical.

Will we ever speak like AI? ChatGPT has achieved the fastest technology adoption in history, reaching 100 million users in just two months since its launch in late 2022. Many people are already using AI to help them write, study, work, and create. But could it be that we are learning AI’s language habits without realizing it? Interesting question. In my recent personal research, I analyzed how AI is influencing the language habits of real people. The results were surprising, so I decided to blog about it. How did you conduct your research? This study consisted of two major stages. The first step was to identify ChatGPT’s signature vocabulary. We edited millions of pages of emails, essays, papers, and articles with ChatGPT, using common prompts like “clean up the text” and “clarify.” We defined the words that ChatGPT repeatedly added as “GPT words.” Examples include “delve,” “realm,” and “meticulous.” The second step was to analyze real language usage patterns. To do this, we analyzed over 360,000 YouTube videos and 770,000 podcast episodes. In particular, we compared them before and after the launch of ChatGPT to measure the degree of change. The surge of GPT words Our research found that since the introduction of ChatGPT, the use of GPT words like “delve,” “boast,” “swift,” “inquiry,” and “meticulous” has increased significantly. Surprisingly, this change occurred not only in structured scripts but also in ordinary, everyday conversations. Cultural feedback loop between humans and AI 1. Humans train AI with text 2. AI generates reconstructed text 3. Humans unconsciously imitate AI patterns 4. Go back to number 1… What’s more interesting is that this phenomenon forms a kind of cultural feedback loop. People train AI to generate text, and AI provides statistically reconstructed text based on this. Eventually, humans unconsciously imitate the language habits of this AI. The study described this as “the phenomenon of patterns stored in AI technology being backpropagated to the human mind.” This study shows that AI like ChatGPT is not just an efficient tool, but is fundamentally changing the language we use and the way we think. This unconscious feedback loop between AI and humans will continue to influence the linguistic culture of our society in the future. What is there in Korean? As I mentioned in my last post, it seems like there are some words that are obvious in Korean too. These are my personal feelings. In fact, these are expressions that are not often used in written or spoken language, but I feel like I am seeing them more and more these days. Is it just my feeling? Personally, when I see these expressions too often, I start to suspect that this person did an LLM assignment. Expression of change/development Develop Improve Improve Promote

There is a strange atmosphere flowing through college these days. 'Overly slick essays' are increasing on exam papers, and assignments that make you think, 'This student couldn't have written such sentences' are being submitted one after another. A new leisure culture has emerged on campus. It is a kind of detective game where you try to guess, "Isn't this written by AI?" But the problem is not simply one of ‘misconduct’. Rather, we are at a point where we need to ask a much more fundamental question: How is AI affecting human creativity and expression? And how will we respond to it? Essays, papers, and cover letters all look like they were written by AI In fact, I decided to test the AI’s capabilities myself. When I asked it to write a Montaigne essay, it mixed one real quote with two fake ones, and when I asked it to write a poem in the style of Elizabeth Bishop, the format was different, but the content was similar, but somehow awkward. The important thing was that it was able to imitate these literary areas. After that, I tried to see if it could be applied to emails, papers, etc. Of course, it was still awkward. This is in 2024. Another surprising thing was that AI was a great helper for 'annoying' tasks such as general assignments, emails, plans, editing notes, and scheduling . Recently, I have been getting dizzy and headaches frequently due to the medication I am taking, and AI formatted my documents for me, polished my speech, and sometimes even comforted me by saying, "I know how complicated and difficult your life is right now." AI replaces the 'unconfident me'. Too gently At this point, it is undeniable that AI is becoming a 'mental labor partner' for humans. AI is tireless, never complains, compliments you, offers another version at any time, and replicates your language. The problem is… the replication is too natural, too smooth. For example, I gave the AI a few of my blog posts and asked it to analyze their style, and it said this: “Your writing style is tense and intellectually precise, revealing a sense of restrained emotion and philosophical thought.” It was so accurate that it was scary. It was like holding up a mirror, but in that mirror I looked more complete. As I repeat this experience, this thought suddenly crosses my mind. After ChatGPT's memory function was added, I felt this way even more. Now, it seems like they know almost all of my secrets? The paradox of eliminating 'writing' from writing classes The same goes for students. At first, they start out by simply summarizing, but before long, they start to entrust AI with structuring, development, and drafting. They rationalize, “Isn’t this basically the same as writing it myself?” And at some point, in a “writing class,” students get an A without even “writing.” A recent study from the MIT Media Lab backs up these concerns with data. After having 54 participants write essays, their EEGs were measured, and the group that relied on AI showed lower memory, initiative, and brain connectivity for their own writing. The researchers called this “cognitive debt,” and feared long-term learning decline. Personally, I made sure to include this part in the book I am publishing this time. The problem is not technology, but the 'outsourcing of thinking' In fact, the technology itself is neutral. The question is 'how' to use it. ChatGPT can help you prepare for class. It can help you organize your schedule and set learning objectives. However, if we indiscriminately accept that help in the name of ‘convenience,’ the muscles of our thinking will gradually become weaker. Ultimately, we are at a crossroads. Will we embrace the temptation of speed and efficiency and hand over creative control to AI? Or will you endure the pain of thinking for yourself and forming sentences in the midst of discomfort and inefficiency ? Things we might really lose

The list of Meta's newly formed team has been leaked, and it's amazing. If you're looking to independently create an AI foundation model in Korea, take a look at the team composition. According to leaked information from within Meta, the personnel composition of Meta's elite AI organization, the 'Superintelligence Team', shows the future direction. Actually, it seems like people are attracted to the aggro because of their annual salary or nationality, but the essence is to analyze what they want to do now. 🧠 Technology Focus Areas LLM Optimization Multimodal learning Eliminate knowledge bias Reinforcement learning-based fine-tuning 1. Strategic talent recruitment Recruiting 15 people (31%) from OpenAI alone is a very aggressive talent acquisition strategy. DeepMind, Google, and other major AI companies are recruiting key talents It seems like they want to solve the implicit part in the process of building and fine-tuning the foundation model. 2. Expertise by field OpenAI alumni are concentrated in the Foundation Models team Many DeepMind alumni are assigned to the Computer Vision team Secure the best experts in each field 3. Proportion of Chinese researchers 47% of the total are Chinese, especially in key research areas Most of them have PhDs from top universities in the United States. Some see this as a security or political issue, but if you look at the papers they have written before, they are just people with great ability or symbolic achievements. Leadership hierarchy Name

Hello, this is Haebom. It's been a long time since I wrote a notice. Thank you so much for always subscribing to my blog and sending me warm comments and interest. Your subscriptions and comments are a great source of strength and encouragement to me. Today, I have a special project I would like to introduce to you. This book is a book that even the publishers themselves tried to make and wrote diligently during the time when e-books were all the rage, but even I forgot about it for a while. At the time, I had a hard time sympathizing with selling e-books for hundreds of thousands of won or writing books about things I had not personally experienced. So I made a series of five books based on things I had personally experienced or understood indirectly. At the time, I received publishing offers from various publishers, but I declined them because I was curious about the e-book market. Now that I think about it, I think I might have been too profit-oriented when I would have kept the physical copies of the books. In fact, each book is about 100 to 200 pages, so if I were to make it into a physical book, I think it would have been about 200 to 300 pages with graphics and typesetting. That was a long digression. •Volume 1: What to Build 101 – Blocking the Creative Process (Difficulty in Completing) •Volume 2: GTM 101 – Uncertainty of Market Reactions (The Difficulty of Selling) •Volume 3: Scale 101 – The Complexity of Growth (The Difficulty of Systematizing) •Volume 4: Iterate 101 – The Chaos of Improvement (The Difficulty of Optimization) •Volume 5: Impact 101 – The Conflict between Purpose and Profit (The Difficulty of Finding Meaning) Thanks to a wonderful person who recently purchased this book, I was able to revise it again, and this time I was able to organize everything from the cover to the ebook more neatly. ✨ In fact, I think I had completely forgotten that I had written it. I can't tell you how much strength I get when I see people contacting me after seeing things I made in the past. Whatever the reason, I sincerely thank you for finding and reading this book. Each and every one of you is a special first reader of this book. I would be even more grateful if you could recommend it to people around you. In fact, I am secretly greedy. Hahaha. And there is an open KakaoTalk room. You are always welcome. (Entry code 1024) Thank you for your continued blog comments and subscriptions. I cherish the time we spend growing together. 🤝 Thank you for always visiting my blog.

"You have to brush your teeth while showering, wear shoes without laces, and save every minute of your day." Have you ever thought about this? If you look at SNS or YouTube recently, you can see that so-called 'micro-efficiency' is deeply embedded in people's daily lives. It is a movement to save even a minute of time with a thoroughly calculated strategy for even the smallest actions. The philosophy behind a cup of tea Veronica Pullen, 54, from the UK, makes two cups of tea every time she drinks it. One cup is lukewarm with milk, and the other is perfect 40 minutes later. This way, she saves 20 minutes a day, or about 10 days over two years. Such small efficiency can make a big difference in the long run. Pullen’s habits don’t end there. She always has boiled eggs for breakfast, an omelet for lunch, and a set menu for dinner. She also repeats a set pattern for her clothes every day. This minimizes the stress of having to make new decisions every time. She says that this habit gives her enough energy to do what she wants. Why are people so obsessed with one minute? This phenomenon is by no means limited to the habits of unique individuals. The tag #LifeHack has been mentioned more than 11 million times on TikTok, and countless productivity influencers are emphasizing the “1% rule.” The best-selling book Atomic Habits preaches to the public how the cumulative effects of small habits can bring about big changes. In a social context, this micro-efficiency is not just a hobby or a trend, but also a phenomenon that reveals the pressures of modern society. Technological advancements have made it possible to do things faster, but the paradoxical situation of having more work to do in the remaining time is repeated. Psychologists interpret this as an early symptom of "active burnout." Good Habits vs. Obsessions People who pursue efficiency have various reasons. They range from people who are sick and want to save even a little energy to people who simply want to practice 'laziness' more comfortably. However, experts warn that if the habit of efficiency becomes too obsessive, it can lead to obsessive-compulsive disorder or depression. Being efficient does not necessarily mean being satisfied. In fact, a British survey found that on average, people only have 23 hours a week where they feel truly free. That creates pressure to save every minute. 3 Tips for Healthy Efficiency But unconditionally pursuing efficiency is not the answer. So how should we approach healthy efficiency? Check your purpose. It is a good idea to make a clear plan on how you will use the time you save. If it ends with just saving time, efficiency will eventually lose its meaning. Allow yourself some 'looseness'. Overly strict rules can actually increase fatigue. It's also a good idea to intentionally break away from efficiency habits on weekends or vacations. Review and reset constantly. As your life circumstances change, your efficiency strategy should change as well. Periodically check whether your current habits are really meaningful to you, and if they need to be changed, do not hesitate to modify them. What really matters is not the quantity of time but the quality. "What will we do with the time we save?" This is the key question that we must not miss. The habit of saving time should ultimately be a means to make our lives happier and more meaningful. Not simply to live busy, but rather to regain leisure in life. Actually, this is a continuation of the article...

Someone once said, "You do planning, development, and marketing. What on earth are you?" What is your specialty? To this question, I actually don't know. I just did everything I could. I just answered, "We're doing everything we can to make it work." Originally, GTM (Go-To-Market) refers to the entire process of launching a product or service to the market and making it successfully adopted by customers. The GTM manager in charge of this is in charge of everything from the product development stage to actually reaching the hands of customers. The Secret to Small Teams Growing Big While working at Kakao Brain and Nexon Korea, I definitely worked on great projects and had great colleagues, but I couldn't shake the feeling that something was lacking. In fact, I had a lot of concerns. Above all, while talking about the word 'growth', I couldn't really feel the actual growth of the product. Is what I'm making really providing value to my customers? Am I creating meaningful growth in my career? I don't like terms like growth/newbie/hexagon in the first place. Real Growth Experiences Learned from Notion Then, working with Notion completely changed my perspective. I learned how to build a product that has tens of millions of users globally, how to increase monthly recurring revenue (MRR), and how to create maximum efficiency with a small team. Notion wasn't just a company with a lot of people. It had clear values, a well-polished product, and users who believed in it. Through this experience, I realized the most important thing in my career. "Rather than focusing on large organizations, we need to focus on the relationship between products and users." Why I joined Gamma, and the results With this realization, I joined Gamma. And in two years, we achieved $50 million in ARR and have been profitable for 15 consecutive months. Gamma is a small but mighty team, and I am now a senior GTM (Go-To-Market) manager. It was an incredible growth, reaching 50 million users and $50 million in annual revenue (ARR) with just 35 people. Behind Gamma’s rapid growth were the following key strategies. I was promoted from the previous GTM Manager to Senior GTM Strategy Manager . The method we use when we attack a market is simple: set principles and stick to them. Let me share a few. 1. User-centric pricing strategy (Van Westendorp) We never guess when it comes to pricing. Gamma used the Van Westendorp Methodology to figure out exactly what users were “ready to pay” and set their prices accordingly. This created a solid revenue structure from the beginning and allowed them to maintain steady growth without changing their prices once for the next two years. Price is a signal to the customer. Accurate pricing creates trust between the product and the user. 2. Maximum growth with minimum manpower Gamma creates AI-based presentation tools that sell and market themselves. Our go-to-market strategy was simple:

The intense ending scene of 『Squid Game Season 3』, which I watched on Netflix a while ago, is still lingering in my mind. The final game is the so-called 'high-altitude squid game' that takes place in the sky. The game is played on square, equilateral triangle, and perfect circular pillars in order. Especially in the round pillar scene in the final stage, the protagonist chooses to sacrifice himself to escape the shackles of greed that dominated him. Until now, the circle symbolized greed and obsession, but when the protagonist chooses death on this circle for his child and future, its meaning is completely reversed. This scene vividly shows that the reality we see is not absolute, and its meaning can change at any time depending on the environment or experience. For reference, I found Squid Game Season 3 very boring. Culture Changes the Way We See? Two Interesting Illusion Studies A similar story can be found in two recent studies of visual illusions. Ivan Kroupin's research team at the London School of Economics (LSE) in the UK showed a picture called the 'Coffer illusion' to Western people and rural Namibians. Interestingly, Western participants mostly saw squares, while rural Namibians mostly saw circles. The research team explains this with the 'carpentered world' hypothesis, which states that the environment we live in determines the way our brains see the world. But another study challenges this hypothesis. Dorsa Amir and Chaz Firestone have shown that the Müller-Lyer illusion occurs in humans, animals, and even blind children, regardless of their environment. These two studies may seem to conflict, but they actually send an important message: the world we see is not an objective reality, but something our brains are constantly interpreting and creating. Seeing and speaking are ultimately 'hallucinations of the brain' Neuroscientist Anil Seth describes reality as "a controlled hallucination created by the brain." In other words, our brain does not show us the objective world as it is, but rather interprets the world subjectively based on our experiences, environment, and culture. What's interesting is that this phenomenon applies equally to language as to vision. Take, for example, a study by Stanford University psychologist Lera Boroditsky, who asked German and Spanish speakers to describe the words “key” and “bridge,” and found that the genders of these words were reversed in both languages. In German, key is a masculine noun, and leg is a feminine noun. In Spanish, key is a feminine noun, and leg is a masculine noun. Surprisingly, German speakers described keys with masculine traits such as “heavy, strong,” and legs with feminine traits such as “beautiful, elegant.” Spanish speakers, on the other hand, described keys with the opposite traits. Likewise, the language we use ultimately determines how our brain creates and interprets reality. What we believe we ‘see’ and what we believe we ‘say’ are ultimately controlled illusions of the brain. 『Squid Game』, Visual Illusion, The Same Story That Language Tells The reason why the final circular pillar scene in 'Squid Game' was so powerful and why language changes our perception of reality is ultimately the same. The meaning of the world that we believed to be absolute can change at any time, and the world can be completely different depending on the language, culture, and experiences we have. The common message that optical illusions, language studies, and drama give us is clear. The world is always being reinterpreted and recreated in our minds. So if we want to change our lives to be more positive, shouldn't we first change the way we look at the world? Just as the protagonist of 'Squid Game' changed the meaning of the archetype from greed to sacrifice, we too can change the meaning of what we see and say in our lives. The difficulties, pain, and even happiness we experience can ultimately be changed by how we look at them. In fact, the reason why the work called "Squid Game" received attention was because the games that we remember from our daily lives or from our childhood have become games that adults who are obsessed with greed risk their lives to play. If we change our perspective a little, wouldn't something completely new or fun come out?

Recently, I met someone who is fluent in Chinese through Skewer Coaching. We talked about apps that are frequently used in China, and I told them about the ones I have used. Even those who don’t know much about China have probably heard of WeChat. There is even a joke that you can’t do almost anything in China without WeChat. Ordering food, calling a taxi, shopping, making payments, and even using government services can all be done within WeChat. Compared to KakaoTalk or Naver, which are commonly used in Korea, it offers a much wider range of functions within a single app. Is this “super app” phenomenon in China simply because Chinese people prefer convenience? Or is there another reason? When explaining the differences between Eastern and Western app design, it is often said that "Asians like apps with a lot of information and complexity, while Westerners prefer simple apps." However, this is not actually the case. Recently, apps in Asian countries such as China, Korea, and Japan have also gradually changed to a cleaner and simpler design. Nevertheless, why have super apps become so strong in China? The starting point of the 'mobile first' era that began with smartphones In the early 2010s, the Internet was not yet fully established in China. At that time, the Internet penetration rate in China was less than 35%, and there were not many people using desktop computers. In this situation, smartphones became the first personal computing devices for Chinese consumers. Since the mobile-centric Internet environment was built from the beginning, existing Internet habits were not formed. For example, in the US and Europe, desktop-based Internet usage habits such as web browsers and emails were already established, but in China, mobile apps were mainstream from the beginning. This gap was filled by Tencent's WeChat. WeChat started as a messenger, but began to provide almost all Internet services through 'Official Accounts' and 'Mini Programs'. In fact, WeChat is like a browser that acts as China's Google Chrome. Instead of moving existing web-based services to mobile, it created an app-centric environment from the beginning. Here, I always think of the words of Tencent Chairman Ma Huateng. When Tencent's QQ and games were ridiculed as copycats, Ma Huateng said, "We drew a tiger after seeing a cat." The early days of China’s digital economy were poorly developed. Banks did not provide consumer-friendly online payment systems, shopping was largely cash-based, and e-commerce was in its early stages of lack of trust. In this situation, Alibaba developed Alipay for online transactions on Taobao, creating its own payment system. Companies had to create their own services if they didn’t have what they needed. This is the real reason why super apps were born. In other words, it was an inevitable choice to fill a gap in the market and quickly take over the entire industry, not for the sake of an ideal user experience (UX). The emergence of the 'wall-building' competitive strategy The rise of China’s super apps can be explained by another reason: the extreme competition. Giants like Tencent, Alibaba, Baidu, and ByteDance have long used a so-called “walled garden” strategy, blocking links to each other’s platforms. For example, if you try to open a shopping link on Taobao in WeChat, it won’t work. So each company tries to pack as many services as possible into its own app. This has led to super apps like WeChat offering food delivery, taxi hailing, payments, shopping, and social media all in one app. Although the Chinese government only banned such link blocking in 2021, consumer habits have hardened and the super app model is deeply entrenched. Another reason can be found in economic terms. The online spending power of early Chinese consumers was lower than that of the West, so the lifetime value of each individual app was small. Accordingly, companies tried to maximize revenue per customer by providing as many services as possible to each customer. Also, because the initial cost of acquiring customers was very high, they integrated more services to avoid sending users to competitors once they had gathered users in one app. This was part of the strategy when Tencent ran the “red envelope (hongbao)” campaign during the Chinese New Year (CNY) to promote WeChat Pay. Strategic choice, not cultural preference The reason super apps succeed in China is not because of user demand, but because of a combination of unique market conditions: a mobile-first environment, lack of industry infrastructure, fierce competition, and low spending power. So should companies in other countries just copy the super app model? Not necessarily. Rather, the important lesson is to understand what drives product design decisions. Super apps aren’t always the answer. In some cases, it might be better to bundle multiple services into one app, while in other cases, it might be more effective to create a single app that provides the best user experience. In reality, WeChat is not a 'perfect super app' that can solve everything. The way it allows users to experience simple services through mini programs is essentially the 'Open Web' of the mobile environment. Users can experience the service in advance and then download a separate app if necessary. In Korea, there were some who once boasted that super apps were the future. But who actually achieved this? Personally, Toss is the only company that has truly achieved a super app. I think Toss's current app is the real beginning of this. The biggest Takeaways we can get from the case of China's super apps is to understand how business needs evolve products. After all, product growth begins not with user needs, but with strategic responses to the environment and market conditions that companies face. Personally, I think Korea is the place that most underestimates China's digital ecosystem and technological prowess. As I always say, if you go to a developed city in China or even Shanghai, you will realize that this is not the China I knew.

Recently, while consulting on AI planning and architecture for a company that creates financial services, I felt that this kind of discussion is accelerating in the financial industry. Although generative AI such as ChatGPT is receiving a lot of attention, the financial sector has been actively utilizing AI for a long time. From fraud detection to credit risk management, and even ultra-short-term trading strategies, AI is playing a key role in many core financial tasks. However, there are still many tasks left for AI to be actually trusted and used ethically. The most important issue among them is explainability. In the financial sector, the more complex the AI model, the more difficult it becomes to understand how it makes decisions. This is the so-called 'black box' problem. Even if an AI model makes accurate predictions, if it cannot explain the criteria and process by which the predictions were made, it can be a serious problem, especially in a field like finance where trust is essential. So today, I would like to take a deep look at what this 'explainability' is and how it can be implemented in the financial sector. Can I give you an interesting example? In 2019, Apple Card became a social issue due to the controversy over gender-discriminatory loan screening. A couple with the same income and credit rating applied, but the husband's credit limit was set much higher than the wife's. People immediately criticized this decision as 'gender-based discrimination.' However, the card issuers and financial institutions that managed the screening algorithm failed to explain exactly why this problem occurred. As a result, their image suffered serious damage. This case illustrates the potential problems that can arise when AI operates in the financial sector. AI makes decisions based on data, but if the data itself is biased or the algorithm’s judgment criteria are not clearly revealed, financial institutions can face serious ethical and legal responsibilities. In this context, the financial sector must ask the following questions when using AI: “Why did our AI model make that decision?” “Are the decisions made by AI really fair?” “Can we explain the judgment criteria of AI models?” Three Key Elements of AI Explainability Explainability is more than just showing the technical details of how a model works. To properly implement explainability in AI in finance, all three of the following elements must be present: (1) Transparency It's about making it clear to stakeholders how the AI model is structured, what data it was trained with, and what prerequisites or assumptions it operates on. For example, trust can be built by disclosing to customers and regulators the data sources for credit rating models and the reasons for selecting assessment variables. (2) Interpretability The goal is to make AI decisions easily understandable to humans. The way the model works should be explained using simple algorithms or visual tools. For example, you should be able to explain why you declined a loan application with specific data points (“Your loan was declined because of your high credit card utilization”). (3) Accountability It's about establishing clear accountability for decisions made by AI models and deciding in advance how to respond when problems arise. When a model makes a bad decision, establish clear processes and accountability to immediately correct it and remediate the damage. An integrated approach that embraces all three elements is key to properly implementing the explainability of AI in finance.

When we visit a hospital, we always expect accurate diagnosis and quick treatment. However, the reality is that it is not easy to receive treatment when you want it due to long waiting times and a lack of doctors. However, a surprising study recently released by Microsoft has presented a new possibility to the medical field. It is that a diagnosis system using artificial intelligence (AI) made a diagnosis four times more accurately than a human doctor. It is true that there are doubts such as, "Can AI really replace doctors?" AI Diagnostic Orchestrator Enters the Medical Field Microsoft 's AI Diagnostic Orchestrator (MAI-DxO) isn't just a simple AI model. It's designed like a panel of five doctors with different roles. Each AI agent develops a hypothesis, selects a test item, and consults with each other to arrive at a final diagnosis, deriving the most appropriate treatment method. What’s interesting here is that it clearly shows the process by which the AI arrives at its conclusion. Microsoft calls it the “Chain of Debate,” and it transparently discloses the logic through which the AI solves the problem. Accuracy that surpasses human doctors? So how effective is this AI in real-world medical settings? To test this, Microsoft presented the AI with 304 of the most challenging diagnostic cases published in the New England Journal of Medicine (NEJM), the top medical journal in the United States. The results were astonishing. When AI worked best (using OpenAI’s o3 model), the diagnostic accuracy was a whopping 85.5%. Experienced human doctors diagnosing the same cases had a success rate of only 20%. Despite the limitations of human doctors not having access to textbooks or colleagues, AI’s overwhelming performance came as a huge shock to the medical community. AI that saves both cost and time In addition to accuracy, the cost-saving effect was also noteworthy. Microsoft set the AI to consider cost in the diagnostic process, and as a result, the number of tests required was significantly reduced, saving hundreds of thousands of dollars in real-world cases. “This system is the most advanced AI performance we’ve ever seen, and could open new doors to healthcare accessibility,” said Microsoft’s Dr. Dominic King. AI models are now 'products', real competitiveness is 'combination power' In this experiment, Microsoft used AI models from several companies, including OpenAI, Meta, Anthropic, Google, and xAI. In particular, Mustafa Suleyman emphasized that even the best-performing OpenAI model will ultimately be “commoditized,” and the real difference lies in the “orchestrator” that integrates and combines these models. Microsoft said it plans to apply the technology to its AI chatbot Copilot and its Bing search engine, which could have huge potential on a platform that processes more than 50 million health-related questions a day. The Era of 'Medical Superintelligence' Needs Preparation Mustafa Suleiman describes this research as a first step toward “medical superintelligence.” A future where faster, more accurate, and cheaper diagnoses are possible is just around the corner. However, further verification is needed before it can be applied to clinical settings. Dr. Eric Topol, a cardiologist and AI medical authority, also evaluated this research as an important study that proved the possibility of AI’s medical efficiency, although it was not conducted in a real medical setting.

"Young people these days don't have enough sex. It's hard to believe." In 2016, the American media outlet Bustle reported the shocking results of a study showing that the frequency of sexual intercourse among young people in their early 20s had plummeted, and declared this. Since then, this phenomenon has been called the "Sex Recession" and has become a hot topic. The image of a bee and a bird turning their backs on each other on the cover of the American magazine The Atlantic strongly expressed this generation's sexual disconnection. In the past, adults were worried about 'young people who are too promiscuous,' but today's older generation is more worried about 'young people who avoid sex.' In fact, recent statistics show that the frequency of sexual intercourse among Generation Z (born in the mid-1990s to early 2010s) is unprecedentedly low. According to a 2018 survey, about a third of men and a fifth of women aged 18 to 24 had not had sex in more than a year, and the pandemic has further exacerbated this phenomenon. In 2021, nearly 40% of Californians aged 18 to 30 said they had never had sex. A generation where everything is possible but nothing is wanted Interestingly, Generation Z is a generation that is more open and has more diverse choices about sex than previous generations. They live in an era where they can easily have short and casual encounters through dating apps with just a smartphone, and various sexual preferences are freely accepted. So why do they stay away from sex? On this issue, British journalist Louise Perry offers a somewhat conservative but interesting perspective. Her book A New Guide to Sex in the 21st Century takes sex seriously, acknowledges the biological differences between men and women, and warns of the dangers of casual sex. Perry strongly warns that “any man can kill almost any woman with his bare hands,” and argues that women should choose their sexual partners carefully. Meanwhile, Guardian journalist Carter Sherman, in his book The Second Coming, explains why Generation Z is experiencing a sexual recession as a result of being caught between political conservatism and the massive power of the internet. The internet provides an endless supply of sexual content while also encouraging the commodification of sexuality, which in turn hinders real intimacy. Generation Z is overexposed to pornography from a young age, making it harder for them to form healthy attitudes toward sex. The Real Reason for the Sexual Recession is the Recession of 'Relationships' The fundamental problem of the sexual recession is 'loneliness'. Generation Z suffers from anxiety and depression much more than previous generations, and has difficulty forming close relationships with others. It is also noteworthy that alcohol consumption has decreased. Alcohol was a medium for forming close relationships quickly with previous generations, but Generation Z is distancing itself from this and is having even more difficulty forming relationships. The influence of social media also hinders the formation of intimacy in an environment where people are constantly evaluated on their attractiveness based on numerical criteria. Ultimately, the sexual recession reflects a social phenomenon where relationships are difficult to form and true connections with others are scarce. What should we do? Both Louis Perry and Carter Sherman point out the causes of the sexual recession from their own perspectives, but what both authors ultimately overlook is the 'power of pleasure and connection' that sex has. Sex is not just about physical pleasure, but it is a precious area where humans can connect most deeply and directly with others. In intimate relationships, we learn to understand, respect, and love each other. Our society needs to discuss how to help Generation Z re-establish healthy relationships and enjoyable experiences through sex. Rather than reducing the root causes of the sexual recession to mere personal problems, it is time to start a more comprehensive and in-depth social conversation. Recently, I've been reading articles like this, and I think that what Generation Z wants is not just a 'simple meeting', but a process of understanding and getting to know the other person. I'm not sure if that's the area called 'self-satisfaction'... or something like the resume blind date that was popular in the past. I found the expression 'sex recession' interesting, so I looked it up.

The Vibe Coding article I recently posted received more attention than I expected. In particular, when I honestly shared specific profit stories, many people sympathized and found it interesting. Thanks to that, I was feeling good, but recently, I encountered an unexpected situation. This is what happened when an anonymous person reported something to me about an overseas corporation I run . At first, I was really surprised. I didn't do anything illegal, but I was suddenly reported, so it was absurd. Through this experience, I would like to share a story that may be useful to those who are considering overseas corporations or global payments like me. 🚨 What was the report? The content of the report is as follows. It was a complaint about whether I was properly following the various reporting and procedures required in Korea regarding the overseas corporation I established with Stripe Atlas. To conclude, fortunately, I had no problems. This is because I had been processing tax returns (comprehensive income tax) and foreign exchange transaction reports from the beginning through a professional tax accountant. It was also the season for the final income tax, so I was preparing the documents thoroughly with the tax accountant. I am always grateful to Ichon Tax Accounting Firm. What you need to know when operating an overseas corporation in Korea However, I learned something through this experience. In my case, I had already prepared, but if I hadn't prepared properly in advance, a complicated and troublesome situation could have arisen. There are obligations that must be fulfilled when establishing or operating an overseas corporation in Korea. I actually don't know the details, so I followed the advice and instructions of the tax accountant. Foreign exchange transaction report (reporting of overseas direct investment and regular reporting required through foreign exchange bank) Comprehensive income tax return (including income earned overseas in addition to income earned domestically) The above procedure is not difficult, but if you don't do it in advance or forget, it can become unnecessarily complicated. Tips that helped me personally The reason I was able to get through this without any problems this time is because of the following reasons. 1️⃣ Get help from a professional tax accountant Whether you are a sole proprietor or a corporation, you can deal with these situations right away by working with a tax accountant. (A tax accountant is especially helpful during the comprehensive income tax filing season.) 2️⃣ Use the Creator Automatic Deposit Service (Shinhan Bank) If you are a developer or creator, revenue management can be complicated, but I use Shinhan Bank's 'Creator Automatic Deposit Service', so revenue management is neatly organized. Thanks to this, it was convenient when reporting. 3️⃣ If you don’t absolutely need an overseas corporation, use a domestic solution In fact, if you don’t absolutely need an overseas corporation, there are many solutions that allow you to easily build a payment system domestically. Personally, I think services like Latpeed and Toss Payments are the most realistic and recommended. If you are a self-employed person and do not like complicated things, I recommend Lepid. If you can handle development yourself and are a corporate business, I recommend Toss. Of course, if you can establish and handle an overseas corporation, I recommend Stripe Atlas or LemonSqueeze. Is an overseas corporation really necessary? "Unless there's a really special reason for it, offshore corporations can be unnecessarily complicated."

The post I recently uploaded about Vibe Coding drew more attention than I expected. While many people focused only on the success story, there were actually a number of trials, errors, and failures during the process. Today, I want to share one of the more interesting 'struggles' I experienced with you. At the time, the service I developed was a PDF protection system called "PDF AI SHIELD." It came from the idea that, as more and more LLMs (large language models) easily read and summarize PDF documents, there should be a way to prevent this. When I'd distribute materials to students at university or carefully prepare and share official documents, people would just have AI summarize and read them—so I started wondering how to limit that. The way LLMs organize and summarize the documents and data we provide is pretty straightforward. They read the document → pick out key points → group and condense them → express them briefly → and then output the information for us. During this process, I came up with a method to interfere in the "reading" step, preventing LLMs from even chunking the data. Standard PDF security typically uses passwords, certificates, or OCR removal, but I added a unique approach on top of these methods. That trick was basically spraying "invisible paint" on the PDF. To the human eye, everything seemed normal, but for LLMs, it acted as a kind of "transparent paint" on the document that prevented them from reading it. I also encrypted tags in the form of certificates and the PDF metadata, making it difficult for LLMs to access. Technically speaking, it worked better than I expected—well-known LLMs like ChatGPT, Claude, and even local models were all blocked by this method. Seeing the results, it almost felt like I'd scored a small victory against the big AI companies. With this boost in confidence, I set up the pricing policy and started promoting in Reddit and several overseas communities. Buyers came in faster than I thought, and it really felt like the business would take off quickly. Honestly, I admit I was a little carried away at that point. Here's how I structured the business model: First use is free without logging in Log in and you can use it once per day (based on 24 hours) With a monthly subscription, you can use it up to 30 times a day Unlimited use with an annual subscription But it didn’t take long for an unexpected issue to pop up. While the protection worked well with models like GPT-4o, Claude Sonnet 3.5, and Gemini Pro, it was completely bypassed by newer models such as o3 and Sonnet 3.7. Plus, with some mini models or in certain situations, even the encrypted metadata was breached. Luckily, one of the early users kindly reported this problem, and I immediately processed refunds for all buyers. Since this was a security service, even a single breach meant I couldn't keep selling the product. Because of payment fees and such, the profit I'd made up front quickly turned into a loss, but handling it quickly saved me from bigger troubles. Better that than getting dragged into some security lawsuit, right? It's not like I rashly counted a deposit as profit. I've got a few more stories like this. If people are interested, I'll try sharing more of them in the future. As I said in my first post about Vibe Coding, when you get into it, there's way more trial, error, and revision than you'd expect—and I think this process actually increases the demand for developers. Plus, I feel like the more you 'struggle' through these processes, the better your product gets. People seem to prefer success stories and dramatic tales over failure stories, but personally, I have plenty of the latter. Even though I call these 'struggles,' I learned a lot from them. I'm not sure how posts like this will be received, but if folks like it, I'll definitely keep sharing parts two and three as well.

When I quit my job and started my own business, the biggest thing I felt was a thirst for good stimulation . Thankfully, thanks to the help of many people and the flow of the times, I didn't have to worry about starving, and the company got on a stable track faster than I thought. However, my thirst for constant communication with good colleagues was not easily quenched. As a one-man business owner, I worked with several freelancers in a remote work format, so I naturally missed the relationship where we could talk comfortably and stimulate each other like coworkers . It was burdensome to hire valuable personnel just for this reason, and although I occasionally worked once a week at other companies, it was a bit different from the stimulation or inspiration I had hoped for. I tried hosting or participating in certain reading groups, but as expected, something was lacking. When I was young, I liked gathering with many people and making noise, but now I feel tired from such places. Then I thought about coaching . I had learned the skills and programs from my previous agile coaching training, so I decided to do free coaching based on them. At first, I started out without specifying the target audience, mainly targeting low-level workers and job seekers. As time went by, surprisingly, people in their 50s and 60s came to me. They were people who were preparing for the second act of their lives or were already running vigorously. One time, I met and talked with a person who builds small ships. He was running a shipyard in Geoje that specialized in small ships under 20 tons. He made hybrid ships using aluminum and fiber-reinforced plastic, which is not even known, and the way he customized the superstructure of the ship according to the ship owner’s detailed requirements was very impressive. I had seen countless ships while traveling around Busan, Incheon, and Gangneung, but I had never thought about who made the ships and how they were made. It was like getting a glimpse into a new world when I learned that these small shipyards were flexible in customizing their ships in a different way than the big ones. It was also very interesting to learn how they charge commissions and roughly how much each cost. One day, while talking to current nurses, I learned about an app called 'MyDuty'. MyDuty was a tool that helped nurses efficiently manage their complicated shift schedules and easily share them with colleagues. The biggest advantage of this app was that it allowed me to see the work schedules of colleagues in the same ward at a glance. It was a service I had never heard of even while working in the IT industry, and this app, which was created by accurately identifying the needs of a specific job group, was a great inspiration to me. It has expanded globally and is now an app that many people can't live without. Through this person who works at Mando, I learned how complex and precise the collaborative structure is needed to make a single car. Mando is a company that develops and produces core parts that are directly related to driver safety, such as braking, steering, and suspension systems. The fact that even a single car we drive every day is so closely intertwined with so many parts and companies was a very refreshing stimulus for me in the IT field, who usually works by making a single product as a whole. The manufacturing method, where individual parts are specialized and each company organically collaborates to complete the final product, showed me a completely different charm from the forms of collaboration I had experienced. Of course, I knew in my head that it was made that way, but it was even more unique when I heard the story directly from someone who actually does the work and works in the industry. As I met people from various fields through this skewer coaching, I felt that the world I see has become wider and deeper . It wasn’t just meeting people, but I felt that my perspective on the world had broadened through various lives and experiences. Sometimes, people I met would connect with each other and lead to employment, or business collaborations would begin. When I received unexpected inspiration from unexpected places, it was a great joy for me. Talking to many people eventually made me realize one thing. The world I thought I knew was so narrow, and only when we share our stories can we see a wide and colorful world. In the future, I want to meet more people through skewer coaching, weave more stories, and connect our lives more meaningfully. As I met each person, I ended up meeting them for over 100 minutes individually, not cumulatively, and this became a huge asset. It cost a lot of money for food and coffee, but I think it was worth it. I think it would be good to meet more systematically in the future, and I will end here.

Last weekend, I spent a pleasant time at the home of a couple who both served as judges and experienced various cases. Both have now put down their judicial gavels and are living as a lawyer and enjoying rural life. As the night deepened and we gathered around a bonfire, our conversation expanded from my curious and somewhat impertinent question about "whether judges are truly impartial" to how they train for and affirm this quality. Since then, I've been organizing these thoughts bit by bit, though I'm far from being a legal professional and only possess minimal legal knowledge as a citizen. The only formal legal education I ever had was a high school course called "Law and Society" in my first year. So please be generous as you read my thoughts, which are based on news articles and my own reflections. Judicial Delays Occurring Worldwide "Justice delayed is justice denied." This age-old adage is becoming reality across the world. While researching the judiciary, I noticed cases from the UK in particular. From Europe to Korea, judicial systems are suffering from case backlogs and trial delays. Especially in the UK and Europe, serious delays are occurring one after another, threatening to paralyze the entire judicial system. According to the UK Ministry of Justice, court case backlogs that were only about 48,000 in 2016 have increased to over 70,000 as of 2024. In London, a case involving a defendant who threatened someone with a knife has been scheduled for 2028, despite requiring only a three-day trial, causing significant social repercussions. Across Europe, investment in judicial systems is chronically insufficient, with the Council of Europe reporting that judicial budgets across European countries have effectively decreased over the past decade, standing at just 0.31% of GDP. In Lisbon, Portugal, frequent strikes by court employees regularly paralyze judicial proceedings. France and Spain are struggling as well... and the US has also been facing various challenges recently. Korea's judiciary is also in crisis. According to a survey by the Legal Times, Korean judges handle about five times as many cases annually as German judges and three times as many as Japanese judges. In a situation where 12 Supreme Court Justices process approximately 40,000 appeals each year, frequent rotations of judges significantly undermine case continuity and fairness. Recently, case backlogs have worsened as political issues draw attention at both the Constitutional Court and Supreme Court, causing tangible harm to citizens' rights to trial and legal remedies. Well, even without such textbook statements... Replace the Judiciary with Artificial Intelligence? Although the National Assembly passed a bill last year to increase the number of judges by 370, many point out that simply increasing personnel will not solve the fundamental problems. Instead, there are growing calls for structural and efficient reform of the judicial system itself. In this context, some are now claiming that replacing judges with artificial intelligence could enable fair judgments. But this is a significant misconception. AI is more likely to amplify existing biases, and recent deep learning-based large language models operate like black boxes, making it difficult to even trace the sources of bias. Ultimately, the issue with judgment-making entities isn't their imperfection, but rather the consistency of their judgments. The most fundamental reason the judiciary exists is because we have entrusted them with authority, trusting they will deliver consistent judgments under clear principles and philosophy. However, we're increasingly seeing cases where the basic logic and philosophy of judgments are being shaken in the name of public opinion or majority views. This could be the beginning of the gradual collapse of the rule of law. Judicial Confusion Caused by Excessive Legislation One of Korea's problems is excessive legislation. Our country produces an overwhelmingly higher number of new laws annually compared to other nations. When there are too many laws, the room for interpretation narrows and various social and economic activities become constrained. Conflicts between laws occur frequently, creating the paradoxical situation where it becomes difficult for businesses and citizens to comply with the law itself. To solve this problem, what we need is rather the digitalization of the legislature. Instead of AI replacing or assisting judges, we need a system that thoroughly reviews potential conflicts between laws and their social impacts using data during the legislative stage. The current practice of supporting bills at the request of party colleagues must be improved. We might consider initially evaluating bill content objectively through blind assessment, followed by roll-call voting to enhance accountability. Ultimately, justice is not a luxury but an essential value we must preserve. Overcoming our current crisis requires fundamental and systematic reforms to maintain the consistency and independence of the judiciary, along with digitalization of the legislature to build a more transparent and efficient legal system. Nation Average number of bills introduced per member per year Total Annual Bills Proposed Proportion of Legislator-Proposed Bills (%) Proportion of Government-Proposed Bills (%) Overall Bill Pass Rate