How a young gamer defeated an academician and won the Nobel Prize

Source: Shihan

Today I want to tell an extremely inspirational story in the scientific field, an incredible feat: the story of a young gamer defeating an academician and winning the Nobel Prize.

Yes, I have previously talked about how gaming graphics cards have sparked a Computing Power revolution and incubated the AI industry, but today’s story is even more incredible and full of unexpected twists.

There is such a young man, who has been praised as a genius since childhood and has loved games since childhood. At the age of 4, he showed a strong interest in chess, and at the age of 8, he was already able to win championships in official chess events. He used the prize money to buy himself an important gift, a computer~ and quickly fell in love with computer games.

Familiar operations, familiar plot~

At the age of 17, he chose to join a game company and become a game designer.

After all, since you love games so much, why not try making one yourself? He joined the famous Bullfrog company at that time.

After entering the company for one year, he led the design of a popular game, which is the famous “Theme Park”.

Simply put, this game from 1994 is the forerunner of many modern theme park and simulation management games, and I even believe that it should also have influenced the Island Tycoon series.

A few years later, he founded his own game company and successively developed two games, Republic and Evil Genius, both of which are simulation business games.

Obviously, he really enjoys this type of simulation management game.

Civilization 5, start!

Here, this story seems similar to the stories of chess genius computer prodigies mentioned in the past,

From a young age, I have had a passion for gaming. I have a talent for chess and Go, and I am able to self-learn computer programming. Eventually, I joined a gaming company and became a top-notch programmer, creating blockbuster products that made waves in the industry.

But this little brother’s outrageousness is just getting started.

After creating a popular game, he quickly started thinking about the role of computers in gaming and began experimenting with adding AI functions to games.

Few media outlets mention this, but as a veteran gamer, I think this is likely the influence brought about by the previous few games.

Because those who often play simulation business games can feel that in the late game, when there are a large number of NPCs, the computer’s Computing Power will have obvious shortcomings,

In the late stage of Civilization 5, one round often freezes the computer.

In theme parks, skylines, and tycoon games, not only are the graphics laggy, but also the citizens’ commuting routes are very unreasonable. Even if you provide them with buses and subways, and even put residential and work areas together, they will still run around and block the roads.

It is possible that these phenomena have sparked his thinking about AI. Can AI be used to optimize these game-like problems?

In 2010, he founded a new company with the goal of “solving intelligent problems” and tried to master games with learning Algorithm.

In 2013, they created an Algorithm called Deep Q-Network (DQN) that can play computer games at a level beyond human capability.

The test results show that DQN has become the best player in the game Space Invaders within 30 minutes of playing.

In 2016, the company released another game AI and defeated the original world champion of the game.

• This AI, called AlphaGo, this time.

Yes, strictly speaking, you can understand the sport of Go as a game, and understand AlphaGo as a game AI,

Just Go, this game is quite special because of its almost infinite calculation variables. It was once considered impossible to crack. AlphaGo is also much more intelligent than those simple computers and crazy computers~

Many people are shocked by the wave of artificial intelligence development in the past two years, often viewing it as a singular, sudden occurrence.

Actually no, over the years the birth of countless electronic games has created a huge demand for game AI, many players hope to have more intelligent AI to battle in the game, or to fight alongside more intelligent NPCs, these demands force programmers to constantly strengthen their exploration of AIAlgorithm.

There has never been a programmer who has fancifully said, 'I will spare no effort to study a more intelligent AI, no, that’s not the case.

The reality is that if you design a good Algorithm, your game will be more fun, and you will earn a billion, while his game will be more intelligent and sell two billion. It is a substantial bonus that motivates everyone to invest endlessly in AI development.

Gunpowder was not designed from the beginning. There was never a scientist who said, ‘Today I am going to invent gunpowder.’ It doesn’t exist. It was a bunch of alchemists hoping for immortality who, in order to fulfill their desire for eternal youth, tinkered with alchemy every day. They added a bit of this today, tried a bit of that tomorrow, and eventually discovered that sulfur, saltpeter, and charcoal mixed together would explode.

At first, Leeuwenhoek didn’t even intend to explore the world of microorganisms. He was just a lens maker, polishing lenses every day. But one day, he suddenly discovered that after polishing the lenses to perfection, he could see things that were invisible to the naked eye.

Like the protagonist of our story, he wanted to make games at the beginning, then he wanted to study smarter games, and finally he developed an incredibly intelligent game AI.

And then they suddenly began to consider a question,

Since AI has self-learning ability and can quickly grasp the rules of Go and electronic games, it has become a champion player.

What if we also understand research in a certain field as a ‘game’, can AI master it?

In 2017, at the Wuzhen Go Summit, AlphaGo cleanly defeated world Go champion Ke Jie with a score of 3-0.

In 2018, DeepMind tried to develop an AI system, AlphaFold, which can predict protein structures, attempting to use AI for scientific research.

You must think this is unreliable, to let an AI originally designed for games study science, this is too fantastic.

Not only you think so, but also a certain academician of the Chinese Academy of Sciences thinks so.

Yes, it’s our old acquaintance, Teacher Yan Ning.

So all the encounters in the world are reunions after a long separation, and we unexpectedly meet again~

For many years, there have been three main methods for predicting protein structures: using X-ray diffraction on protein crystals, nuclear magnetic resonance spectroscopy, and the expensive method of cryo-electron microscopy for imaging and modeling.

The Yan Ning team is known for their skilled operation of cryo-electron microscopy using the third method. While others take a photo once, her team can take five times, which is much more efficient.

And DeepMind’s idea is, can this highly repetitive work be solved by AI?

If we understand the process of taking photos and modeling the cryo-electron microscope as a game, can we try to solve it with AI?

“Instead of making films, they chose AI: Since proteins are composed of amino acids, as long as they use the known protein structures available everywhere to link the distances between each pair of amino acids, the angles, and summarize them into a graph, and then let the neural network process them, AI can make predictions on its own.”

The ultimate result is that AI is far more efficient than human beings. The general team efficiency is 1, the Yan Ning team efficiency is 5, and AI is 100,000, and it is still rising rapidly. Because AI does not need to rest and will continue to evolve. Since they made breakthroughs, more than 2 million people from 190 countries have used AlphaFold. With their help, scientists can not only gain a deeper understanding of the resistance of antibiotics, but also design enzyme proteins that can digest plastics.

With such groundbreaking achievements, you can probably guess the rest of the story: this technology won the Nobel Prize. The young man who loves games and originally worked as a game designer is this year’s Nobel laureate in chemistry, Hassabis.

It turns out that the development of the times will fairly throw off everyone. When you are amazed by the development of AI, top scientists may also be taken aback.

In 2022, when we discuss AI, the impact of AI on Yan Ning and others has been observed by many people. From the comments, although everyone recognizes the development of AI, most people think that it may still take some time to replace top scientists. (A few buddies’ comments are very forward-looking and impressive)

Yan Ning may also think so. Yan Ning’s conclusion in 2022 is that the predictive level of AI can only reach their 2017 level.

The plot is exactly the same as the Go industry.

At first, when AlphaGo came out, everyone thought it was nothing more than defeating the world champion. Humans still had a chance to win back with effort.

But soon everyone realized that this view was absurd because human learning relies on teachers and textbooks, and human combat effectiveness is actually built upon the experience of previous generations and years of learning, while AI has only been exposed to Go for less than a year. It may have become a Go master in just one year of entry-level learning, and there will be no need to look further in the future.

In 2022, Yan Ning felt that AI had only reached the level they were at five years ago, which was not a cause for concern.

The problem is that AlphaFold was born in 2018, and by 2022, it’s only four years old. A four-year-old child is about to catch up with you top human scientists. The development speed will definitely be greatly mistaken if you use common sense to judge.

So what does this story tell us?

Is it technological development, AI innovation, life experience, or should biology be recoded as a farmer?

I think the biggest inspiration is love.

Looking back, in 2007 Yan Ning was already a professor and doctoral supervisor at Tsinghua University, and he was a well-known academic master.

At this time, Demis Hassabis was still a game designer, let alone an academic master, he couldn’t even be regarded as a member of the academic community.

At this point, if you tell him that you will defeat an academician of the Chinese Academy of Sciences and win the Nobel Prize in the future, he will not only not believe you, but also cannot imagine it.

An unknown scientist made a remarkable achievement and won the Nobel Prize, which is incredible but at least understandable.

How could I, a stinky gamer, ever win the Nobel Prize? There is no gaming award in the Nobel Prize, right?

The wonder of the world lies here.

You don’t really love scientific research, maybe it’s for the salary, maybe it’s for stability, maybe it’s for the dazzling lights. You do similar work day after day and deeply feel the difficulty of scientific research.

Although he was only playing a game, he was genuinely passionate about it, and as a result, delved into it to the extreme, unexpectedly unlocking the AI technology tree, which turned out to be the key to the new era.

You say this is his good luck, but if he didn’t have a profound love for the game, if he didn’t fundamentally think about the gameplay, if he just made some skin-changing games for money, could this story happen? Obviously not.

It is a passion and dedication that goes beyond everything to love and explore things, which helped him break through the fog and find a new world.

Never forget to love what you love.