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Comment by No Agency 28 minutes ago

Who Is Geoffrey Hinton? by ICONADA Research Team 

Today, I would like to introduce a scientist who changed the world — Geoffrey Hinton (1948– ).

Many people call him the “Godfather of AI” because many of the artificial intelligence technologies we use today — such as chatbots, machine translation, facial recognition, and even self-driving cars — are deeply connected to his research.

Geoffrey Hinton received the 2024 Nobel Prize in Physics for combining ideas from physics and neural networks to lay the foundations of modern artificial intelligence and deep learning, fundamentally changing the way humans interact with computers.

Some of you may wonder:

“Didn’t artificial intelligence suddenly appear only in recent years?”

Actually, no.

AI research has a history of several decades, and Professor Hinton is one of the most important figures in that story. He spent more than forty years developing a technology that many people had nearly abandoned, eventually turning it into a force that changed the world.

1.A Dream Inspired by the Human Brain

Geoffrey Hinton was born in the United Kingdom and later conducted research in Canada. He always had one important idea:

“If the human brain can learn, could computers learn in a similar way?”

Because of this question, he began studying “artificial neural networks.”

A neural network is a system designed to imitate the way neurons in the human brain work.

Our brains learn through experience. For example:

* A child falls down and learns to be more careful next time.
* A student gets a math problem wrong and learns how to improve.

Hinton believed computers should also be able to learn from mistakes.

2.The Most Important Breakthrough: Backpropagation

In the 1980s, artificial neural networks faced a major problem: computers did not know what mistakes they had made, so they could not truly “learn.”

In 1986, Hinton and other researchers introduced a revolutionary technique called “backpropagation.”

Don’t be frightened by the name.

Simply put, it works like correcting an exam paper.

For example:

* The computer first gives an answer.
* It discovers the answer is wrong.
* The system checks backward step by step to find the error.
* Then it adjusts its internal settings so the next answer will be closer to the correct one.

This is very similar to how a teacher helps students correct mistakes on a test.

Backpropagation became one of the most important foundations of modern deep learning.

Without this technology, many AI tools we use today might not even exist.

3.He Continued When Others Gave Up

However, Hinton’s research journey was not easy.

From the 1990s to the early 2000s, many scientists believed neural networks had “no future.”

At that time, computers were not powerful enough, and there was not enough data available. AI research entered a difficult period known as the “AI Winter.”

Many researchers switched to other fields because they thought neural networks would never succeed.

But Hinton did not give up.

In 2006, he introduced a new method called the “Deep Belief Network (DBN),” which helped solve the problem of training deep neural networks. This achievement officially began the era of “deep learning.”

This teaches us an important lesson:

Great scientific discoveries often come from long-term persistence.

Comment by No Agency 38 minutes ago

4.AlexNet Shocked the World

In 2012, Hinton and his students created a famous AI system called AlexNet. One of his students was Alex Krizhevsky.

That year, there was an international competition called the ImageNet Image Recognition Challenge.

The task was simple:

“Show pictures to a computer and ask it to identify what is inside.”

For example:

* A cat?
* A dog?
* An airplane?
* A car?

Before AlexNet, computers were not very good at image recognition. But AlexNet performed far better than every other team, dramatically reducing the error rate.

Technology companies around the world were shocked.

From that year onward:

It is fair to say that 2012 became a major turning point in the explosion of modern AI.

5.He Was Not Only a Scientist, but Also a Teacher

Hinton also had another important role: educator.

Many of his students later became world-leading AI experts, including:

* Yann LeCun
* Ilya Sutskever

These researchers later helped develop many advanced AI technologies, including the conversational AI systems we know today.

That is why some people say:

“Hinton not only created AI technology — he also trained the people who transformed the AI world.”

6.The Concerns of the “Godfather of AI”

Interestingly, one of the people most responsible for advancing AI has recently begun warning the world about its dangers.

Hinton left Google so that he could speak more freely about AI safety.

He worries that if artificial intelligence becomes too powerful in the future, humans may no longer be able to fully control it.

Therefore, he believes the world must pay attention not only to developing AI, but also to:

* Safety
* Ethics
* Laws
* The future of humanity

This reminds us that truly great scientists do not only create technology — they also think carefully about how it may affect the world.

7. What Can We Learn from Him?

Students, Geoffrey Hinton’s story is not only a story about technology. It is also a lesson about life.

He teaches us three important things.

First, believe in your ideas.

Even when many people doubted neural networks, he continued his research.

Second, failure is not something to fear.

AI went through a difficult “winter,” but he never gave up.

Third, technology brings both power and responsibility.

People who invent new technologies must also think about how those technologies may affect society.

Conclusion

Today’s artificial intelligence may seem like a miracle that appeared suddenly. But behind it are decades of hard work by countless scientists.

And Geoffrey Hinton is one of the most important among them.

From backpropagation, to deep learning, to the success of AlexNet, he changed the direction of world technology step by step.

Perhaps one of you in the future will become the next scientist who changes the world.

And what truly matters is not only how intelligent you are, but whether you are willing to continue believing in your dreams even when others doubt you.

Comment by No Agency yesterday

[ICONADA Research Team] When one person’s voice is too faint, let us gather and speak together;When one person’s strength is too weak, let us gather and work together.

In many contemporary societies, people are taught to admire the myth of the heroic individual. Success is framed as personal achievement; failure is treated as personal weakness. Social media intensifies this logic by rewarding visibility, branding, and self-promotion. Yet beneath the celebration of individuality lies a troubling reality: isolated individuals rarely possess enough power to confront entrenched systems of inequality, exploitation, or cultural alienation. The quotation above challenges this modern obsession with individualism by insisting that meaningful change emerges through collective action.

The line “one person’s voice is too faint” speaks not only to political silence, but also to emotional exhaustion. Many people today experience loneliness despite living in hyperconnected societies. Workers feel disposable within corporate systems; students compete rather than collaborate; marginalized communities struggle to be heard in institutions designed without them in mind. Under these conditions, speaking alone often feels futile. The quotation therefore proposes solidarity not as sentimentality, but as survival. A collective voice transforms private suffering into public discourse.

The second line extends this idea from speech to action. “One person’s strength is too weak” acknowledges the limitations of individual effort in confronting structural problems such as economic inequality, climate crisis, racism, censorship, or labor exploitation. Contemporary culture frequently markets resilience as a personal responsibility: meditate more, work harder, optimize yourself. But systemic crises cannot be solved through self-improvement alone. The quotation rejects this neoliberal fantasy by emphasizing cooperation over competition.

There is also a cultural dimension to the statement. In many Asian traditions, community identity historically carried greater importance than radical individual autonomy. However, globalization and consumer capitalism have increasingly replaced communal bonds with transactional relationships. People are encouraged to see one another as competitors for status, wealth, and attention. Against this backdrop, the quotation becomes quietly radical. It reminds us that community is not weakness; interdependence is not failure. Human societies have always advanced through shared labor, shared memory, and shared resistance.

Importantly, collective action does not erase individuality. Rather, it amplifies it. A choir does not silence individual voices; it creates harmony impossible for a solo singer to achieve alone. Likewise, democratic movements, artistic communities, labor unions, and grassroots organizations derive their strength precisely from diverse individuals choosing to act together toward a common purpose.

Ultimately, the quotation is a rejection of passivity and fragmentation. It calls for a politics of participation and a culture of solidarity. In an age where people are increasingly isolated, commodified, and divided, its message is both simple and urgent: alone, we may struggle to endure; together, we become impossible to ignore.