Fintech startup GNE Tech Holdings has officially launched Riskweather, an innovative AI-based platform designed to analyze the risks associated with various financial products.
Much like checking the weather forecast before stepping outside, Riskweather allows users to “forecast” the financial risks ahead, providing actionable insights and data to help investors navigate an increasingly unpredictable market.

​🌐 What Is GNE?The name GNE stands for "Generate Next Economy", reflecting the company’s mission to help build a new economic framework for the future.
GNE Tech Holdings focuses on harnessing AI, big data, and blockchain technology to deliver next-generation fintech solutions. Rather than following the path of traditional financial institutions, the company positions itself at the forefront of a technology-driven transformation of the financial sector.

​🔍 Key Features of Riskweather

• Real-time financial risk diagnostics powered by AI
• Personalized insights based on individual investor profiles
• Big data analytics to anticipate market trends
• User-friendly and intuitive visual interface (UI/UX)
• Future roadmap includes API integration and institutional partnerships
  
  

With these capabilities, Riskweather is designed not just for professional investors but also for individual users seeking smarter and safer financial decisions.

​💬 A Word from the CompanyA representative from GNE Tech Holdings stated,
“Riskweather isn’t just a platform—it’s an intelligent risk navigator that helps users assess and prepare for the financial weather ahead.”
“We aim to expand its coverage to a broader range of financial products in the near future.”

​📉 Riskweather's Amazing Accuracy in an Unpredictable Market
— AI-based Risk Analysis Platform that Warned of Three Stock Price Declines in Advance
Recently, the global stock market has been greatly affected by political variables.
With a variety of external factors such as changes in tariff policies, trade conflicts, and geopolitical tensions working in a complex manner,
we have entered an era where it is difficult to predict market trends using only traditional analysis.

In this financial environment dominated by high uncertainty and rapid change,
the **AI-based risk analysis service 'Riskweather'** developed by fintech company **GNE Tech Holdings** is showing remarkable results.

🔗 Source:Asia Economy article (in Korean)

​⚠️ Proven Predictive Power in Real Cases
In particular, during the recent stock market volatility,
Riskweather succeeded in accurately warning of three stock price declines in advance.

This prediction was not a simple trend prediction,
but was derived from data analysis and machine learning model-based signals that reflected political factors (tariff increases, policy announcements, etc.).

In fact, at that time, Riskweather provided the prediction signals in the following way

⚠️ [Example 1: XX, 202X]
"Supply chain disruption of global manufacturers is expected due to tariff hike issue.
Risk index surge — Warning of possible decline in the next 5-10 days"

⚠️ [Example 2: XX, 202X]
"Sudden change in exchange rate + increasing uncertainty in US-China trade talks → Detecting a downward signal centered on large-cap stocks"

⚠️ [Example 3: XX, 202X]
"Risk level adjustment centered on technology stocks upward due to surge in oil prices and energy policy uncertainty"

These predictions are not simply feelings or inferences, but rather, they are the judgment of an AI model that integrates multiple variables, algorithmic analysis, and even reflects unstructured data, and are therefore being used as a more objective and preemptive risk management tool for existing investors.

💡 Message to investors
Riskweather's accurate risk prediction case is not simply a 'triumph of technology'.
It is the emergence of a new perspective on reading information in a complex world,
and the beginning of a new paradigm that helps investors make more cool-headed and strategic decisions.

​Accurate predictions depend on how well you read the past, and RiskWeather is increasingly developing into a tool that can design the future based on that data.

​🌦️ From idea to reality, Riskweather's journey
​
— From intangible imagination to real product, to prediction that helps the world
Riskweather was not a project that started with a grand name or huge capital from the beginning.
It all started with a simple but sharp question.
"What if ordinary investors could intuitively read the flow of risk in the complex and uncertain financial market?"

This idea was first ignited by Professor Youngshin Kim, who teaches financial mathematics at the Department of Business Administration at Stony Brook University.
The imagination of combining AI algorithms and mathematical probability models
to express the flow of the financial market like weather
gradually began to take shape with the addition of the team members' skills and visual sense.

​🎨 Small innovations starting with icons

What got me involved in this project was my role as an artist who was in charge of the initial icon design for Riskweather.

The task of reinterpreting the rigid and complex concept of finance into friendly symbols such as sunshine, clouds, lightning, storms, and volcanoes so that anyone can easily understand it had a meaning beyond simple graphics.

These icons became a language that instantly conveyed the intensity and direction of risk to investors, and soon became a core element that visually symbolized Riskweather's philosophy and approach itself.

Small and quiet beginnings as a startup

At that time, Riskweather was a startup that started from a small idea.
The budget was not large, and it was not well known to the world.
But one thing was clear.
“Let’s make the invisible visible.”

And let’s make it actually helpful for someone’s decision.

Professor Kim Young-shin’s mathematical insight, the developers’ technical know-how,
and the visual interpretation that I was in charge of,
were combined to build up the moments when the idea became reality one by one.

​And when it started helping someone,
over time, as RiskWeather was tested in real markets,
and the AI-predicted risk signals started to coincide exactly with actual stock price declines,
we realized,
“This is not just an experiment anymore.”
The three major declines predicted by RiskWeather
had a big impact on someone’s decision-making in volatile markets,
and the results led to trust beyond the numbers.

​Ideas always start small
​
If someone reading this right now has a creative idea,
no matter how small and insignificant it may seem,
if you can execute and connect it, something that never existed before can be born.
Riskweather can be a good example of that.

The Evolution of Art and Design in the Age of AI: A Reflection on Creativity and SurvivalFor decades, graphic designers held a prestigious position in the creative industry. Proficiency in image-editing software like Photoshop and Illustrator was considered a specialized skill, and mastering these tools required patience, dedication, and technical acumen. Graphic designers were not only seen as artists but also as technologically adept professionals who balanced creative intuition with an understanding of digital tools. Their work was regarded as highly valuable, and salaries were structured based on experience, expertise, and the complexity of the tasks they handled.

However, the landscape has shifted dramatically. Artificial intelligence has introduced a level of automation that has fundamentally altered the field of graphic design, making many tasks that once required technical expertise accessible to anyone with an internet connection. AI-powered design tools can now generate professional-grade visuals in seconds, reducing the need for deep technical knowledge. The question now arises: how can graphic designers—and artists in general—adapt and thrive in this new era?

In the past, learning to use design software was a challenging endeavor. Photoshop, Illustrator, and other professional tools required months, even years, to master. Those who possessed these skills were highly sought after in the industry. The process of creating digital artwork was not just about having an artistic eye; it also required an understanding of digital workflows, file formats, typography, color theory, and sometimes even basic programming.

I, too, learned these tools many years ago, and to my amazement, the knowledge I acquired then is still applicable today. Despite incremental improvements and additional features, the core functionalities of these tools have remained largely the same. Like riding a bicycle after years of not cycling, revisiting Photoshop or Illustrator only requires a brief reacquaintance before everything comes back naturally.

But the technological landscape no longer moves at the pace it once did. We are in an era where, overnight, AI can introduce groundbreaking innovations that reshape industries in ways we cannot predict. The very concept of mastering a tool has become transient; what we learn today may become obsolete tomorrow. The implications for young designers and students pursuing careers in digital art and design are profound.

Should We Still Encourage Students to Pursue Graphic Design?

​I deeply desire a bright future for my students. I want to equip them with skills that will allow them to not only survive but thrive in a world that is evolving at an unprecedented pace. However, I sometimes find myself hesitating when students express interest in pursuing graphic design as a career.

Fine art, in its purest form, still holds undeniable value. The ability to create original, thought-provoking, and emotionally resonant works remains a uniquely human endeavor. But in the realm of graphic design—where AI can now produce logos, layouts, and visual assets in seconds—what must designers do to stay relevant?

I believe the key lies in transcending technical skills and embracing creativity, problem-solving, and adaptability. Rather than solely focusing on software proficiency, students must cultivate a mindset that allows them to think critically, conceptualize original ideas, and navigate the ever-changing technological landscape. The future belongs not to those who simply know how to use a tool, but to those who understand how to wield technology creatively and strategically.

As I reflect on these rapid changes, I realize that my art classes must also evolve. Teaching software alone is no longer sufficient; instead, I must foster an environment where students develop curiosity, creativity, and the ability to adapt. My goal is to encourage them to think beyond the tools at their disposal and focus on the essence of artistic expression.

In this new educational paradigm, I see value in introducing elements of competition, exploration, and play into the learning experience. Encouraging students to participate in design challenges and exhibitions, much like a celebration rather than a rigid test of skill, can ignite their creative potential. Just as children learn best through play, I believe artists and designers must approach their craft with a sense of curiosity and excitement.

Moreover, I want to instill in my students the understanding that learning is no longer a finite process. Unlike in previous generations, where mastering a skill could secure a lifetime career, today’s professionals must commit to continuous learning and reinvention. They must embrace emerging technologies, explore interdisciplinary approaches, and remain open to change.

As we move forward, one truth becomes increasingly clear: creativity is the most valuable skill that will stand the test of time. While technology may evolve, the human ability to imagine, innovate, and push boundaries remains unparalleled. AI may generate images, but it does not dream. AI may design layouts, but it does not question why certain aesthetics resonate with people on a deeper level. AI may process vast amounts of data, but it does not feel joy, pain, or inspiration.

This realization extends beyond the realm of art. In every field—science, business, engineering, medicine—the ability to think creatively and adapt to new challenges is becoming the most critical determinant of success. The rigidity of traditional industries is being dismantled, and the fluidity of artistic thought is now more valuable than ever.

Thus, rather than viewing AI as a threat, I choose to see it as an opportunity. It is an invitation to rethink, reimagine, and reinvent. It is a challenge to push beyond comfort zones, to merge art with technology in ways never before possible, and to harness the power of creativity in ways that machines cannot replicate.

As an artist and educator, I have decided to dedicate this year to exploring the intersection of art, AI, and innovation. I want to investigate how creative minds can thrive in an era of automation, how artistic expression can influence other fields, and how we can cultivate a mindset that embraces change rather than fears it.

I believe that art must evolve alongside technology, not resist it. Just as artists of the past adapted to new media—from oil paint to photography, from film to digital art—we must now embrace AI and use it as a tool for expanding our creative possibilities. The role of the artist is not to reject progress, but to infuse it with imagination and meaning.

The future of art and design is uncertain, but one thing is clear: those who embrace creativity, adaptability, and lifelong learning will always find a way forward. In this new era, the most important lesson we can teach the next generation is not how to use a specific tool, but how to think, create, and evolve.
​
AI may change the way we work, but it will never replace the human spirit of innovation. And that, above all, is why I remain optimistic about the future of art, design, and creativity.

Asian stock markets, including Korea, fell sharply today (the 5th).

KOSPI recorded the largest decline in stocks ever, and circuit breakers were activated on KOSPI and KOSDAQ, temporarily halting trading.

​My husband showed me a graph showing that his stock market risk prediction program, RiskWeather, warned me three times about the recent stock market crash. I don't invest in stocks and I don't enjoy it, but I like this program that warns me about the risks of stocks and investments. There are people around me who actually lost all their money because of stock investments. That's why I think programs like RiskWeather should be developed and promoted more.

​RiskWeather is a program that provides a simple, visual representation of the risks of the stock market, much like a weather forecast.

-The classical philosophers said this.
I never think without fantasy. This means that thinking requires materials.

-Imagination is needed to create images. Imagination is an ability that is distinct from concepts and is explained as the ability to materialize thoughts and make a concept appear as an image.


“For example, I can conceptualize freedom.
We can also explain what freedom is conceptually.
But showing freedom is very difficult.
To show you freedom, you will have to draw.
I would have to compose a scene.
Then I can help you imagine the freedom in that materialization, in that scene.

Therefore, we must think of imagination as an ability.
The mental ability to describe objects in producing images.
And what we want to show is that there is a certain kind of imagination.” (The Architectural Imagination
​
(Excerpted by The Architectural Imagination: An Introduction)"

Note: When I draw, people ask me how I can draw what I imagine in my head. The answer to this is right here.

​In order to concretize a concept, it is necessary to concretize the imagined image.
This is the process of materialization.
​
To do this, identify the properties and locations of each material, compare them, and understand a single concept. These materials will then be refined and rearranged to fit the concept we are presenting. And if this comes within the framework of one perception, it can be made into something new.
​

​Generative artificial intelligence (Generative AI) is a type of AI that can create new content and ideas, such as conversations, stories, images, videos, and music. AI technologies attempt to mimic human intelligence in new computing tasks such as image recognition, natural language processing (NLP), and translation.

​Recently, Google introduced a new Large Language Model (LLM) artificial intelligence (AI) tool that can generate videos. On the 20th (local time), foreign media such as VentureBeat, an IT media outlet, reported that Google Research has unveiled 'VideoPoet', which creates videos based on text input.

Not only can you create a video according to the text description, but you can also convert a static image to a dynamic image or change the video to your desired style. The explanation is that various types of videos can be created, from short films to music videos and explanation videos. Videopoet is a large-scale language model trained based on massive text and video data sets.

Therefore, you can not only understand the relationship between text and video, but also create consistent and visually attractive videos. In particular, its ability to create consistent motion in long videos is also a strength. This model stitches together short video clips to create videos that are several minutes long. This means that it becomes possible to produce more complex and nuanced videos.

Source: AI Post (AIPOST) (http://www.aipostkorea.com)
​

​Generative AI is transforming the content creation industry and breathing new life into unimaginable stories and ideas. But on the other hand, video creation is becoming easier due to rapidly evolving AI tools. There are also concerns that there will be a lot of ‘fake’ or ‘hate’ content.

​‘Open AI,’ an American company that developed ChatGPT, a generative artificial intelligence (AI), is expected to further accelerate development competition by unveiling a new generative AI that creates videos from sentences.

​https://cdn.openai.com/sora/videos/art-museum.mp4

​Sora can create complex scenes with multiple characters, specific types of actions, and precise details of subjects and backgrounds, and the model understands not only what the user requests in the prompt, but how this exists in the real world.

The company also says that the model has a deep understanding of language, allowing it to accurately interpret prompts and create compelling characters that express vivid emotions, as well as multiple scenes within a single generated video that accurately maintain the character and visual style. He explained that it could be made.

As an example, I tried to use it by Invideo Ai as below: