The development of artificial intelligence industry is not as good as you think.

On April 26th, the GMIC Global Artificial Intelligence Leadership Summit with the theme of “AI Life” was held in Beijing. Yan Yan LeCun, Dean of Facebook Research Institute, Michael Jordan, Academician of the American Academy of Sciences, American Academy of Engineering, American Academy of Arts and Sciences, Kai-Fu Lee, Chairman and CEO of Innovation Works, Zhang Yaqin, President of Baidu, He Xiaopeng, Chairman of Xiaopeng Automobile, Zhao Ming, President of Huawei Glory The senior vice president of Keda Xunfei Company and Hu Yu, the dean of Xunfei Research Institute, debated the same stage and made the whole meeting climax, bringing a wonderful technology feast to the audience.

Mystery 1: The development of the AI ​​industry is not as good as imagined?

Like in the past, Kai-Fu Lee's opening is still the "wave theory" he is good at. He divides the current status and future of artificial intelligence development into four waves:

The first wave, Internet + AI. Every click of Taobao and every praise of a circle of friends is one of the processes by which the Internet giant collects data. Therefore, in the current data role is increasingly prominent, the Internet giant with data is the AI ​​giant;

The second wave is also aimed at companies with large amounts of data, such as banks, investment institutions, insurance companies, etc. This is a "lower-lying fruit" in the field of artificial intelligence applications. Any field with data can be commercialized. For example, the bank user's data reduces the fraud rate of the credit card, etc., which is a TO B commercialization process;

The third wave is based on visual, auditory sensors to collect new data to create a new user experience. For example, smart speakers, cameras in various fields, etc. In this regard, there are already many products and applications that have landed;

The fourth wave is an autonomous, automated AI wave, such as robots, drones, drones, unmanned stores, unmanned factories, and so on. This wave will completely disrupt the industry. At present, there are still some gaps between China and the international community.

Figure | Chairman and CEO of Innovation Works, Kai-Fu Lee

"We have a huge amount of data, and the development in the field of sensors is also particularly fast, and even in some areas has been a global leader. These four waves will come very fierce and will bring many opportunities for China." Kai-fu Lee Say.

However, a dramatic scene appeared. Just after Li Kaifu just finished, Michael Jordan directly dismissed Li Kaifu at the scene.

"We can't exaggerate the artificial intelligence industry because we haven't built a complete intelligence system at all," Michael Jordan said.

As an academician of the Third Academy, the industry called Michael Jordan "Artificial Intelligence." As an academic, he is not satisfied with the current development of the industry.

"For us, our principle is to build a system. This system is not just about 'no one', it can be automated, but the machine can be truly human. Now everyone's research on artificial intelligence, Research in the field of artificial intelligence has fundamental structural problems."

Figure | American Academy of Sciences, American Academy of Engineering, American Academy of Arts and Sciences, Academician Michael Jordan

Michael Jordan said that the current artificial intelligence system construction is mostly based on individual considerations, that is, too many local conditions are considered, but the overall consideration is not enough, and what we need is a connected whole system. In other words, it is not just "no one", but a machine that can be judged and made from a global perspective. It takes a long time to do this.

In this regard, Yann LeCun also stated that the machine should obtain all the data from all over the world, learn enough background knowledge from the environment under supervision and unsupervised, and establish a system based on principles to obtain the same predictions as people. Decision ability.

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