Research indicates a fivefold increase in demand for AI skills, yet most schools still ban the use of ChatGPT. A recent survey found that 70% of graduates believe generative AI should be integrated into coursework, and more than half said they felt unprepared for the workforce. At the same time, 66% of teens aged 13-17 express interest in starting their own businesses, according to Junior Achievement data.
The disconnect is apparent: students want to build careers around emerging technology, but traditional education isn’t teaching them how. While schools debate AI policies, forward-thinking programs are already training middle schoolers to launch AI-powered ventures and solve real problems. They’re not preparing students for tomorrow’s job market. They’re teaching them to create it.
The most effective programs abandon traditional classroom simulations in favor of authentic business creation. Students don’t earn grades—they gain customers, revenue, and practical skills that transfer directly to college applications and future careers.
At WIT (Whatever It Takes), which I started in 2009, teens launch actual businesses and social movements that address real community problems. In the college-credit programs, students pitch for actual prize money, receive real-time coaching from successful entrepreneurs, and develop presentations that have landed participants in major publications.
We ask participants one question: “What problem are you passionate about solving?” We then provide the tools, mentorship, and structure to help them build effective solutions.
WIT has worked with over 10,000 young people, providing leadership and entrepreneurial education through hands-on experience. The results speak volumes—our alumni consistently report higher confidence levels, stronger college applications, and clearer career direction compared to peers who only engage in traditional academic activities or simulation business programs.
This shift toward authentic learning experiences isn’t limited to K-12 education. As the demand for AI skills explodes across industries, universities are also abandoning traditional lecture-based models in favor of programs that prepare students to create rather than just consume technology.
Universities Embrace AI Integration
University of South Florida (USF) made history as the first university in Florida—and among the first nationally—to create an entire college dedicated to AI and cybersecurity. The Bellini College of Artificial Intelligence, Cybersecurity and Computing will welcome 3,000 students this fall, with plans to double enrollment in the first five years.
The timing reflects urgent market demands. Research indicates a fivefold increase in demand for AI skills in U.S. jobs, while more than 40% of organizations report being unable to find enough qualified cybersecurity professionals. The National Science Foundation awarded over $800 million for AI-related research in a single year.
“As AI and cybersecurity quickly evolve, the demand for professionals skilled in these areas continues to grow,” USF President Rhea Law explained. “Through the expertise of our faculty and our strong partnerships with the business community, the University of South Florida is strategically positioned to be a global leader in these fields.”
Dr. John Licato, Associate Professor at The Bellini College of Artificial Intelligence, Cybersecurity and Computing, puts this educational shift in perspective: “AI and cybersecurity already touch every single job on earth. Universities everywhere are trying to incorporate these technologies into their programs so students can practically leverage them, but at the same time further develop their own critical thinking and reasoning.”
USF Provost Dr. Prasant Mohapatra told me, “We’re not just producing job seekers—we’re producing job creators.” The college leverages USF’s existing strengths—approximately 200 faculty members already conduct research in related disciplines—while positioning the Tampa Bay region as a technology hub.
USF’s bold move breaks from traditional models of higher education. Most universities incorporate AI courses into their existing programs. USF built an entire college around emerging technologies, combining technical training with business education because students need both skills to succeed.
Bridging the K-12 AI Knowledge Gap
Teenagers already use AI tools regularly. Data shows 63% of U.S. teens use chatbots and text generators for schoolwork. Yet most schools ban these tools or label them as cheating. This creates a problem: students learn AI exists, but not how to use it ethically.
WIT created WITY to fill this gap. Our AI platform helps teens develop business ideas and conduct market research to inform their entrepreneurial endeavors. Students learn to work with AI without losing their creativity or critical thinking abilities.
USF also works with younger students. The Bellini College offers workshops for K-12 students through partnerships with education programs. These sessions introduce kids to AI concepts through hands-on projects.
Dr. Mohapatra shared his philosophy with me: “We want to show kids that AI isn’t something to fear. It’s something they can learn to use responsibly and creatively.”
AI Success Metrics That Matter
Programs that successfully prepare students for an AI-driven economy share several characteristics:
Authentic challenges: Students tackle real problems with genuine consequences, not hypothetical scenarios designed for assessment.
Interdisciplinary approach: Effective programs integrate technology, business, ethics, and social impact rather than teaching these subjects in isolation.
Confidence development: Students learn self-advocacy, self-worth, and self-value through entrepreneurial experiences. These capabilities transfer to college applications, job interviews, and leadership roles.
Early exposure: Rather than waiting until senior year, these programs introduce innovative thinking in middle school and early high school.
Research supports this approach. A 2022 Gallup survey found that students involved in entrepreneurship programs were 34% more likely to develop leadership skills and 41% more likely to report feeling prepared for future careers.
The AI Competitive Advantage
Students emerging from these programs possess advantages that traditional education alone cannot provide. They understand how to identify market opportunities, collaborate effectively with AI tools, and communicate their ideas clearly to diverse audiences.
College admissions officers increasingly recognize entrepreneurship as a marker of leadership, innovation, and problem-solving ability. Students who can demonstrate how they built something from the ground up bring more than just an application; they get a track record of action.
These experiences provide rich material for personal statements and interviews while demonstrating the initiative and resilience that colleges value in their incoming classes.
Building Tomorrow’s AI-Driven Economy Today
Programs that combine AI literacy with entrepreneurial education create an exponential multiplier effect. Students don’t just learn to use existing tools—they develop the creative mindset to identify problems that AI can solve and the business acumen to turn those solutions into viable ventures.
The students graduating from these programs represent a new breed of innovator. They’re not just prepared for an AI-driven economy—they’re actively architecting it, armed with both deep technological fluency and the entrepreneurial skills to transform breakthrough ideas into market-changing impact. This represents a fundamental shift in educational philosophy—from preparing students for predetermined career paths in a static economy to empowering them to create entirely new industries and opportunities in our rapidly evolving technological landscape.
As a developer and a human being, you want to push yourself as much as possible to incorporate the intention of things into your practice. By insisting on understanding a project’s intention and uniting it with your own understanding of the particulars of implementation, you become far more valuable. AI then makes it easier to magnify your intentions into automated activity.
We can speculate that AI will get better at this middle ground in the future, but it will never actually have intention. It will only ever move under human direction. Resist becoming just a connector or interpreter of intention to implementation. Keep on working to develop and contribute your own unique understanding. Implementation can be automated, but the unique qualities of understanding cannot.
Why LLMs will not replace higher-level languages
If you follow the hype cycle, it might seem that AI’s ability to mass produce code to meet requirements makes understanding the intention of that code less important. I’d say it makes it less necessary up front. There may even come a time when AI’s natural language interface is something like what fourth-generation languages are today. I can see a possible future where languages like JavaScript and Python are a layer below the AI interface, akin to how C is today. But if that is the analogy we’re using, then it seems clear we will always need people who deeply understand that layer, just as today we still need people who understand C, assembly machine code, and chip wafers.
LG AI Research Institute has released a new model of Exemplary Pass, a precision medical artificial intelligence (AI) model.
On the 9th, LG AI Research Institute unveiled ‘EXAONE Path 2.0’, a next-generation precision medical AI model.
Bio is one of the ABCs (AI, Bio, and Clean Tech) that LG Group Chairman Koo Kwang-mo cited as a future growth engine. Exempathy 2.0 is expected to play an important role in the group’s growth strategy.
Exempathy 2.0 is an upgrade of the 1.0 model released in January last year and the 1.5 model released last month, and has learned much higher quality data than the existing model. Pathologic tissue images (WSI) can precisely analyze and predict genetic variation and expression form, microscopic changes in human cells and tissues, and structural features.
Exemplary Pass 2.0 learned multiomics information such as DNA and RNA containing WSI and genetic information together. WSI is a high-resolution digital image taken during the pathologic diagnosis process of observing a patient’s tissue sample under a microscope. However, if AI simply analyzes this, there is a high possibility that a “characteristic collapse phenomenon” will occur, which will lead to poor prediction accuracy.
Exemplary Pass 2.0 applied a new technology that learns from small units to WSI, increasing the accuracy of predicting genetic mutations to 78.4%, the world’s highest level.
In addition, gene activity can be predicted only by image analysis without expensive dielectric tests.
Park Yong-min, leader of the AI business team at LG AI Research Institute, said, “If Exemplar Pass 2.0 is used, the genetic test time that took more than two weeks can be shortened to less than a minute, helping to secure golden time for treatment of cancer patients. If doctors and pharmaceutical companies use Exemplar Pass 2.0, they can identify target treatments in a short time.” The LG AI Research Institute also released additional models specializing in specific diseases such as lung and colon cancer.
LG AI Research Institute also announced a plan to cooperate with Vanderbilt University Medical Center in the United States. It is joined by a research team led by Korean scholar Hwang Tae-hyun, who leads the stomach cancer project of Cancer Moonshot, a cancer conquest project led by the U.S. government. Professor Hwang said, “Our goal is to create an AI platform that can help medical staff treat and treat patients in the actual medical field. The AI platform will not be just a diagnostic tool, but a game changer that innovates the entire process of new drug development.”
Starting with the field of cancer, LG AI Research Institute and Professor Hwang’s research team plan to expand the scope of research to rejection of transplants, immunology, and diabetes in the future. LG AI Research Institute is planning to introduce Exemite Pass 2.0 at the ‘LG AI Talk Concert 2025’ on the 22nd.
Bae Kyung-hoon, head of LG AI Research, speaks at a conference held at LG Science Park in Magok-dong, western Seoul, on July 19, 2023. [LG]
LG AI Research on Wednesday unveiled Exaone Path 2.0, its upgraded artificial intelligence (AI) model designed to enhance cancer diagnosis and drug development. The move aligns with LG Group Chairman Koo Kwang-mo’s vision of making AI and biotechnology core growth engines.
Exaone Path 2.0 learns from higher-quality data than the 1.0 version, which was launched in August last year, according to LG AI Research.
It can precisely analyze and predict not only genetic mutations and expression patterns but also subtle changes in human cells and tissues. The institute says this could enable earlier detection of cancers, forecast disease progression and support new drug discovery and personalized treatments.
A key breakthrough comes from new technology that trains the AI not only on small pathology image patches but also on whole-slide imaging. This pushed genetic mutation prediction accuracy to a globally leading level of 78.4 percent.
LG AI Research expects it will help secure the critical “golden hour” for cancer patients by cutting gene test times from over two weeks to under a minute. The institute also unveiled models tailored to specific diseases, including lung and colorectal cancers.
Dr. Hwang Tae-hyun, an expert in AI-driven research in precision oncology, immuno-oncology, cellular therapy and 3D/4D molecular modeling, is a professor at Vanderbilt University Medical Center. [LG]
LG is bolstering this initiative through a partnership with Dr. Hwang Tae-hyun at Vanderbilt University Medical Center, a leading expert in biomedicine. Hwang, a prominent Korean scientist, heads a U.S. government-backed “Cancer Moonshot” project targeting gastric cancer.
LG AI Research and Hwang’s team plan to jointly build a multimodal medical AI platform that utilizes real clinical tissue samples, pathology images and treatment data from cancer patients in clinical trials. They believe this will usher in an era of personalized, precision medicine.
Their collaboration also underscores Chairman Koo’s push to position AI and bio as technologies that transform customers’ lives. LG AI Research and Hwang’s team see this platform as the world’s first attempt to implement clinical AI in this way.
Starting with oncology, the team will expand into transplant rejection, immunology and diabetes research.
“Our goal isn’t just to develop another AI model. We want to create a platform that actually helps doctors treat patients in real clinical settings,” Hwang said. “This won’t just be a diagnostic tool — it has the potential to become a game changer that transforms the entire process of drug development.”
Performance level of LG AI Research’s precision medical AI model EXAONE Path 2.0 [LG]
Translated from the JoongAng Ilbo using generative AI and edited by Korea JoongAng Daily staff. BY NA SANG-HYEON [[email protected]]
![Dr. Hwang Tae-hyun, an expert in AI-driven research in precision oncology, immuno-oncology, cellular therapy and 3D/4D molecular modeling, is a professor at Vanderbilt University Medical Center. [LG]](https://mlojngrtu3xf.i.optimole.com/w:auto/h:auto/q:mauto/ig:avif/https://aistoriz.com/wp-content/uploads/2025/07/aa2d7b78-47c1-4a7e-90f1-b613daea6ca1.jpg)
![Performance level of LG AI Research's precision medical AI model EXAONE Path 2.0 [LG]](https://mlojngrtu3xf.i.optimole.com/w:auto/h:auto/q:mauto/ig:avif/https://aistoriz.com/wp-content/uploads/2025/07/fa03b735-a3bd-43ef-94bf-4cd0000642bd.jpg)
