YouTuber Gwidot's Question Answered by Nanoventures — KICEF 2026 M.AX Summit On-Site Report
How far has artificial intelligence come in creating the future?
Nanoventure: The era where 1 person leads 10,000 AI organization members
AI Asks, Nanoventures Answer
The 2nd Korea Industrial Complex Export Expo KICEF 2026 · Industrial Complex M.AX Innovation Summit · Daegu EXCO On-Site Report
Hello, this is Unique Good 🌱
YouTuber Gwidot on the morning stage demonstrated "How far has AI come" with evidence.
The last words he left behind were "Find unchanging values," a mandate.
The afternoon stage's CEO Lee Eun-young's nanoventure special lecture translates that mandate into the language of organizational AX transformation design.
Today, the 2nd Korea Industrial Complex Export Expo KICEF 2026 opened at Daegu EXCO. The Industrial Complex M.AX Innovation Summit, organized alongside the export consultation meeting, was filled with two questions thrown at the manufacturing field.
"Where has AI come so far right now?" And "So how should our organization work together with AI?"
If YouTuber Gwidot answered the first question, then CEO Lee Eun-young's nanoventure special lecture is the stage that answers the second question. Today's newsletter is a field record connecting the two lectures into one flow, seeking clues as to how companies in the AI era should undergo AX transformation.
AI has already received perfect scores on all kinds of test stages.
The title of Gwidot's lecture on stage was "How far has artificial intelligence come in creating the future?" He started with a story about AI that perfectly proved 25 out of 30 International Mathematical Olympiad geometry problems.
At the 2026 International Mathematical Olympiad, AI's correct answer rate was 100%. Gemini received a perfect score on the college entrance exam, and now it doesn't even make mistakes. The sentence he calmly uttered was: "There is no longer any human among humanity that is smarter than AI."
AI has also stepped beyond the screen. Figure 03 precisely grasps the package tag pointing downward and moves it, and lightly transfers heavy objects on a conveyor belt. In actual contests against human workers, people had to rest but robots did not. The Korea Industrial Complex Corporation also reportedly plans to apply an AI assistant created directly by its employees in actual operations.
Where the boundary between real and fake has disappeared
Do you remember the AI video from 3 years ago where Will Smith ate pasta in a grotesque manner? One year later came the singularity. As the Sora engine was released, the same scene became impressive, and after Google Veo 3, it became impossible to distinguish from real footage. He said the chewing sound and the screen synchronization became so refined that watching it made you hungry.
Now fake videos of famous animations supposedly being shot in real-action circulate as if real. Dog diving competition videos are more impressive than reality. In other words, if you have only electricity and subscription fees, you can implement any idea as video.
So the danger grows together. One fake image of a Pentagon explosion shook the stock market, and deepfakes destroy both victims and perpetrators. On the other hand, there is also a righteous use like an AI grandmother that can detain voice phishing criminals for up to 40 minutes. Gwidot's conclusion was clear. Self-driven scientific thinking that identifies cause and effect—that is the survival weapon of the AI era.
Why didn't the go world collapse?
When Lee Sedol lost to AlphaGo and retired, many people talked about the end of go. The reason was that the game became one with a definite answer when it should have been an art with no visible end. Yet the go world did not collapse.
New talents who learned go with AI appeared, and as AI position judgments were displayed on the upper right of the broadcast screen, even people who didn't usually watch go were able to read the board position. The market actually grew because people could see in real time whether a move was effective or not. As the structure that could only be learned by becoming a student of a master broke down, new opportunities also opened for players who self-taught with AI.
And Gwidot changes direction on the last slide. Don't obsess over dividing what AI can and cannot do, he says. Scientists don't ask who does it better; they ask what is preserved, he said, emphasizing that finding unchanging values even with AI's emergence is more important. The sentence by Alan Kay that he quoted becomes the bridge to the next stage: "The best way to predict the future is to invent it."
So on the afternoon stage, nanoventures answer as the work method of AX-transforming companies.
If Gwidot said "invent," then CEO Lee Eun-young (Unique Good Company)'s nanoventure special lecture is a record of someone already executing that invention.
The slogan is just one: From Nano to Giant Impact.
The starting point is an uncomfortable truth about the organization. When the number of members reaches 58, the communication paths they need to exchange exponentially increase. According to Asana's research, 60% of office workers are doing work about work rather than actual work. In a structure where meetings, reports, confirmations, and coordination melt away a day, hiring more people is unlikely to be the answer.
So the nanoventure formula is: Burn tokens, not headcount. Tom Blomfield of Y Combinator reports that startups operated with just 1 employee generated millions of dollars in revenue in 18 months. Organizations that burn tokens rather than labor create 10X, 20X growth.
The difference between a company that uses AI and a company that works with AI
However, simply implementing a tool does not bring results. MIT Sloan Management Review points out that 95% of companies that adopt AI remain in productivity illusions not connected to results. Tool subscriptions have increased, but the way of working remains the same as last year—many workplaces are at this point.
The solution proposed by the nanoventure special lecture is structure. Actually creating a place to work with AI within the organization, like AI Solution Lab, AX Team, and dedicated AI task forces. AI utilization that remains through individual tricks and AI embedded in processes produce different results.
The order of transformation is also concrete. 0-3 months is when individuals become familiar with AI tools, 4-6 months is team-level task application, 7-8 months is organizational process redesign, and 9-10 months is the completion of the nanoventure structure. The fact that 10 months can change an organization's basic grammar means this is a plan size that industrial complex resident companies can start immediately this quarter.
"We've already paid for the AI subscription, so why is the way our company works exactly the same as last year?"
- Record for just one week how much time disappears from our team on "work about work."
- Pick one repetitive task and rewrite it in a form that AI can run 24/7.
- Instead of hiring more people, make a list of what work could burn tokens.
- Let's set our company's AX transformation schedule starting with 0-3 month personal utilization.
Gwidot showed how far AI has come, and the nanoventure special lecture talks about how to work on that reality. The point where the two lectures meet is ultimately one. Unchanging value is held by those who first create an answer to how to work.
If you're currently concerned about where to start with organizational size and workflow, please feel free to contact us when it can help. We'll listen to your current situation and draw up specific directions together with case examples.
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