Chapter 199 - Chapter 199: Chapter 199: Birth (Part 1) (1/2)

Chapter 199: Chapter 199: Birth (Part 1)

Translator: 549690339

As an IT professional who always keeps up to date with the latest information, Xiang Kun is naturally aware of what the most advanced and cutting-edge AI looks like.

In the AI field, deep learning and neural networks are still dominant, with large factories at home and abroad, such as Doge, Penguin, Du Niang, Ali Niang, and so on, each having their own deep research direction, and they publish their latest progress from time to time.

After all, most of the current AI research directions are difficult to create good results with isolated work. Especially in machine learning, data, computing power, and algorithms are all necessary. Without a sufficient dataset, even if your algorithm is exquisite and your machine’s computing power is advanced, it’s hard to get the results you want and apply them to reality.

In some specific fields, AI has already surpassed, or even outstripped, human abilities.

For example, AlphaGo has defeated the top professional Go players one after another. With further improvements and iterations, human players may find it hard to compete with it in the future, and its opponents will become other AIs.

But can we really say that the players defeated by AlphaGo, such as Ke Jie, were only defeated by the AI, by a machine?

Perhaps it’s not that simple.

For example, Xiao Ming’s fighting capacity is only 5. He wants to meet his girlfriend, Xiao Hong, but on the way, he’s blocked by a dragon with a fighting capacity of 100; he can’t beat it.

So Xiao Ming went back to the village, gathered his dwarf friends, spent several years studying the dragon’s weaknesses and combat methods, conducted various simulated confrontations, and eventually built a flying sword, the “Bai Emperor Sacred Sword”.

The “Bai Emperor Sacred Sword” has a combat power of 200 when fighting dragons!

So, Xiao Ming, shouting “Bai Emperor Sacred Sword, follow me!” easily defeated the dragon and met Xiao Hong.

So, was the dragon defeated by the “Bai Emperor Sacred Sword”, or by Xiao Ming and his dwarf friends?

Without Xiao Ming, the “Bai Emperor Sacred Sword” might be knocked down by a cat with a fighting power of 3 because it had never seen one in its training set~!

Last year, Doge’s BERT model even achieved STOA results in 11 NLP tasks in the top-level machine reading comprehension test SQuAD1.1, surpassing human comprehension. Subsequently, domestic teams like Brother Xunfei, Penguin, and Ali Niang, have all topped the SQuAD test one after another.

In the SQuAD2.0, teams like the Asia Institute of Microsoft and Ali Niang are continuously achieving better results. It looks like humans have already been left far behind by AI in reading comprehension.

But is that really the case? Does AI truly have a stronger reading understanding capacity than humans? Can it understand human thinking and intentions?

After all, the current AI is still just a “high-level tool”.

No matter how human it appears.

When Xiang Kun first started the “AI Assistant Plan”, he had already seen the bottlenecks in current machine learning and neural networks. So in the beginning, he did not have the idea of creating a “super AI” because it was unrealistic. He had always been thinking about integrating and optimizing within the existing frameworks.

However, he later found that such a method would still take a lot of time and energy, and it was not something he could easily accomplish on his own. But since it required so much effort, why not think about taking a step further?

To put it bluntly, after several mutations, he has “expanded” again, holding two cents, he wanted to eat the best wonton in the world.

Because he thinks his two cents are very valuable, buying something worth a normal two cents, or even two dollars or twenty dollars would be a loss.

But how can he do this?

Xiang Kun has had several moments of “flash of inspiration”, and has a vague idea, but can’t yet fully grasp it, it’s still not ready to “co-manifest”.

That’s why he agreed to accept Zhang Qian’s project. He wants to use the process of doing other projects to help him find “that light”.

Unfortunately, the help had not been significant. The framework of that project was already set up and the core was completed, but Xiang Kun’s “AI Assistant Plan” still hadn’t even found a good angle to dig from.

Looking at the diagram on the screen, which he drew to help himself think, Xiang Kun pinched his chin with one hand, and played with his Carved Alsace with the other hand.

Xiang Kun now understands:

To make something worth two million with two cents, there must be highly innovative creation. It has to be something completely new, starting from the underlying level, a “lever” that can move the earth.

In the existing framework, there’s no way he could achieve that, even though his brain is much stronger than the average person, or even an ordinary genius, due to mutation. All the institutions, factories, talents, and teams in the world are studying every day, with so many devices and data for them to use, he can never catch up on his own. Since they can’t find the breakthrough from the old framework, it’s unlikely that he could do it on his own.

But how deep would this underlying level need to be?

If you look at it, innovations in software can never be separated from hardware.

Just like when the computer was first born, artificial intelligence was divided into “symbolism”, “connectionism”, and later “behaviorism”.

“Connectionism,” also known as the bionic school, advocates imitating human neurons, using the connection mechanism of neural networks to achieve artificial intelligence. The currently popular machine learning is carried out in the name of “connectionism”.

However, in the 1970s, due to the level of hardware development and lack of computing power, “connectionism” fell into a low point.

Until now, with the rapid development of computer computing power and the advent of massive big data brought about by the development of the Internet and mobile networks, machine learning, under the name of “connectionism,” has found the best growth environment and begun to flourish. It has spawned a variety of platforms, algorithms, and models and has seen a lot of applications in various industries and environments. There is even talk that “AI will replace human work”.