Is Taiwan Ready for the Talent Jensen Huang Needs?

This year, when NVIDIA founder Jensen Huang took the stage in Taipei again.

Global media focused on AI factories.

Supercomputers.

GPUs.

The trillion-dollar artificial intelligence industry.

But after the keynote ended.

One remark deserves the attention of every educator.

Taiwan will need a massive number of AI talents in the future.

Not just a few thousand.

But a demand on the scale of tens of thousands.

This is not merely an industry signal.

It is an education signal.

Because as the AI industry begins to scale rapidly.

What Taiwan will truly lack will no longer be chips.

But people.

The First Time Taiwan Stands at the Center of a Global Tech Revolution

For the past forty years.

Taiwan's most important advantage has come from manufacturing capability.

We manufactured computers.

Smartphones.

Chips.

The world's most advanced semiconductors.

Yet the arrival of the AI era.

Marks the first time Taiwan has moved from a supply-chain role.

To the heart of a global technology revolution.

From TSMC to Foxconn.

From Quanta to Wistron.

From NVIDIA to global AI data center construction.

The entire world is revolving around Taiwan.

This is an unprecedented opportunity.

And an unprecedented challenge.

Because the competition in the technology industry.

Has never ultimately been about equipment.

But about talent.

What the AI Era Needs Most Is Not Engineers — But Problem Solvers

Many people believe.

That AI talent simply means people who can write code.

In reality.

What the world's top AI companies are looking for.

Goes far beyond engineers.

They need people who can define problems.

People who can design systems.

People who understand industries.

Leaders who can work alongside AI.

OpenAI needs more than model researchers.

It also needs product designers.

Anthropic needs more than engineers.

It also needs researchers who understand human behavior.

NVIDIA needs more than hardware talent.

It also needs people who can bring AI into every industry.

The most valuable talent of the future.

Will not be the executors.

But the problem definers.

Not the knowledge carriers.

But the knowledge creators.

Why Is the Answer Found in the Math Classroom?

This might seem contradictory.

When AI can already solve math problems.

Why do we need mathematics more than ever?

Because mathematics was never about the answer.

What makes mathematics truly valuable.

Is that it trains children how to think.

A math problem.

Is essentially a problem model.

Students must learn to:

Understand the problem.

Analyze the conditions.

Find the pattern.

Build a model.

Verify the result.

Correct the errors.

These are precisely the most critical skills of the AI era.

Because in the future everyone will have an AI assistant.

But not everyone will know what questions to ask.

AI can produce an answer in three seconds.

But it cannot tell you:

Which problem is most worth solving.

The Next Generation's Edge Will Shift from Solving Problems to Asking Questions

The industrial age valued standard answers.

The AI age values problem definition.

In the past students competed on:

Who calculated faster.

Who memorized more.

Who scored higher.

In the future students will compete on:

Who can spot opportunity.

Who can break down a problem.

Who can collaborate with AI.

Who can lead teams to create value.

This is also why Harvard, Stanford, MIT, and other top universities.

Are rethinking the essence of education.

Because the most precious talent in the future world.

Is not the person who knows the most.

But the person who thinks the best.

AI Education Is Not Teaching Kids to Use ChatGPT — It Is Cultivating Leaders for the AI Age

While many institutions are still teaching children how to write prompts.

The more important question is:

What comes after the prompt?

When everyone can use AI.

The gap will no longer come from the tool.

But from the mindset.

What will truly matter in the future is:

Whether one has cross-disciplinary understanding.

Whether one has business insight.

Whether one has problem-solving ability.

Whether one has the capacity to innovate.

And whether one has leadership capability.

These abilities.

Cannot be acquired through a single coding course.

Nor through rote memorization.

They require long-term cultivation.

Mathematical thinking.

Project-based practice.

Real-world challenges.

ChenLi Mathematics' Next 40 Years

Forty years ago.

ChenLi Mathematics helped a generation master academic competitiveness.

Forty years later.

The rules of competition have changed.

Today's students may join NVIDIA in the future.

May found the next AI company.

May become leaders in the robotics industry.

May even create new professions that do not yet exist today.

Therefore the goal of education must also be upgraded.

From cultivating high-scoring students.

To cultivating high-impact talent.

From mathematics education.

To thinking-skills education.

From exam preparation.

To future preparation.

Coming Soon: ChenLi AI Leadership Program

In 2027.

ChenLi Mathematics will launch a bold new educational experiment.

AI Leadership Program.

This is not a course that teaches children to use AI tools.

But a program that cultivates future AI talent and innovation leaders.

The curriculum will integrate:

• Mathematical thinking and problem-definition skills
• AI tools and Agent collaboration skills
• Entrepreneurship and product design skills
• Business and industry understanding
• Public speaking and leadership training

What we hope to cultivate.

Is not the next exam champion.

But the next creator of the AI era.

When Jensen Huang speaks of a future demand for tens of thousands of AI talents.

That is not industry news.

It is an open letter to the world of education.

Because the talent standing at the front line of the AI industry ten years from now.

May be sitting in a junior-high classroom today.

They are learning mathematics.

Learning to think.

And preparing to embrace a new era defined by artificial intelligence.

The true responsibility of education.

Has never been to chase the future.

But to cultivate, ahead of time, the people who will create it.