Shulou(Shulou.com)06/03 Report--

Today, more and more people have begun to believe that the third rise of AI, marked by deep learning technology, will trigger a global productivity iteration. As a technology engine, AI will play an important role in the process of human history, such as fire, electricity and internal combustion engine.

In this great change in productivity, there is a feature that has never appeared before: the development of AI will rely heavily on the creativity of professional scientific and technological personnel and developers as never before. In other words, only when there are sufficient talents and huge resources have been invested by the state and society, can AI have a future.

Respecting talent and attaching importance to education is a tradition engraved in bone and blood by Chinese people. Education has been a major event since ancient times. At the turning point of the integration of AI and social economy, we must answer a question: where do Chinese AI talents come from?

It is not difficult to find from a lot of data that it is not so easy to supply AI from the source of talent today.

95% of the war

Today, the international community has basically reached such a consensus: artificial intelligence will trigger the next round of general technology revolution, bring huge industrial capacity improvement for various economies, and even change the social pattern and the status quo of human production and survival.

With the combination of artificial intelligence and various industries, this change is happening rapidly. Last September, McCarthy comprehensively analyzed the use of AI by 400 multinational enterprises and predicted that by 2030, the total number of GDP brought by AI in the world will exceed that of China and India combined, and proportionally will be greater than the impact of steam engines on the human economy. AI is likely to become the world's largest "economy".

However, the bright future and prospects depend heavily on a scarce resource: not oil, but talent.

Today, all kinds of industries need to understand AI and new talents in the industry. AI entering the industrial economic space needs talents as a driving force, countless scientific and technological innovation needs talents to support and complete, and many industry-university-research integration projects need university talents as a bridge.

Although at present, many talents can meet the demand standards through the service industry, MOOC learning and other ways. The significance of providing AI education in colleges and universities is not only to meet the current needs. The technological breakthroughs brought by pure academic innovation and the continuous transfer of knowledge and experience under the educational mechanism all determine the speed and quality of the follow-up AI industry development.

However, on the side of the bright future, the current situation of China's AI talents is worrying. According to the relevant statistics released by the Ministry of Industry and Information Technology in 2018, the AI talent gap is more than 5 million, and continues to expand, and the AI talent supply rate is less than 5%. According to a forecast made by LinkedIn, it is difficult for China to compare with the United States in the field of AI today, and the biggest reason lies in the different rate of talent output. In the face of such a relatively new discipline as AI, it is obvious that China's higher education is not completely ready. It was not until 2017 that AI undergraduate education began to enter the field of vision of Chinese education.

95% of China's AI is undone, which may have become the deepest bottleneck in the national economy in the tide of intelligence.

How many mountains do we need to cross from desert to fertile soil?

Since the gap of AI talents is so huge, and colleges and universities play such a profound role in the development of AI, why don't colleges and universities train AI talents as soon as possible and transfer them to social practice? There is no doubt that this matter is not as simple as a few words. For example, when we enter the real space of today's colleges and universities, we will find that the "three mountains" have become a great obstacle for colleges and universities to develop AI majors and train AI talents.

First, there are ideas, but no math power: students have the ability to design algorithms, but do not have the ability to create math power. Today, AI computing is still an expensive and scarce resource. Many colleges and universities, especially where they are just beginning to explore AI, can't even afford or buy a GPU to test-no one would believe that chef schools that can't afford to buy vegetables can produce good cooks.

Second, willing, no ability to cultivate: the sudden arrival of a cutting-edge AI, the teacher has not yet learned, how to educate the students? The new teaching materials and the new training mechanism are all in the missing stage. AI education, which is launched hastily and lacks the ability of technical understanding, obviously does not meet the long-term needs of the development of AI industry.

Third, ambition, no resources: colleges and universities also know that AI is good, but they can't do it without money. In the face of AI, colleges and universities not only lack the real voice from enterprises, but also need more scientific research motivation, such as the direction of scientific research, the opportunity of industry-university-research combination, funding and technical support for major AI projects, and so on. These tasks can not be completed by colleges and universities themselves, and need a high degree of linkage of industry-university-research. Hinton, the father of deep learning, believes that AI will be the most closely linked science and technology between universities and enterprises, which is still in its infancy in today's China.

In the face of such an AI talent desert, it is useless to be in a hurry, and there seems to be only one solution: social enterprises feed back what is lacking in talent training. Fortunately, Chinese scientific and technological circles have begun to explore in this direction.

Huawei, which has made great achievements in AI industrialization in recent years, is the first to take this first step. As an enterprise with massive algorithm resources and application scenarios, Huawei accidentally penetrated its talent training strategy into colleges and universities.

On December 27th, Huawei and the School of Information Science and Technology of Peking University jointly held the AI Summit of 100 faculty at the Yingjie Exchange Center of Peking University. More than 340 teachers from electronic information, computer, control engineering, automobile transportation, robot and other AI related departments from 157universities and research institutions attended the summit. At the meeting, Huawei discussed with its partners the development of AI in various industries and its support plan for higher education. Through the contents of this summit, we can find that Huawei is aiming at solving the three AI education problems that colleges and universities are most concerned about:

Give computing power, then technology: Huawei will help universities and research institutes to use Huawei's full stack of AI technical capabilities and computing resources, Huawei Cloud's AI resources and AI suite support, Ascend Teng series chips and Atlas intelligent computing platform, and full-scene AI infrastructure for end-to-end, edge and cloud open to colleges and universities.

Give methods, set teaching materials: jointly develop AI courses in universities and scientific research institutions, and jointly publish books and teaching materials.

Provide resources and face the future: Huawei continues to build and upgrade fertile soil plan, which provides important help for colleges and universities to enter the frontier field of AI and complete discipline construction and scientific research.

Seeing the practical difficulties and solving the real needs, Huawei's AI education empowerment program is characterized by "down-to-earth". And this leads to the next topic: why, along with the times, is Huawei the fertile soil for AI?

Teach according to the material: why is Huawei the initiator?

Confucius said that teaching students in accordance with their aptitude is the basis of Chinese educational philosophy. However, when measuring students' materials, we should also see such a logic: in the field of education, especially in the cutting-edge educational scenes related to the national economy and the people's livelihood, it must be "teachers" with ability, expertise and overall strategy to provide educational transformation for the industry, otherwise the lack of ability of educators will make education a joke.

This is a logic of "teaching students according to their talents", from which we can also reverse why Huawei's AI education program can quickly fall to the ground and win the attention and support of hundreds of universities. There are three conditions that only Huawei has, which makes it the forerunner or even initiator of China's AI talent training mechanism in today's AI spring tide:

First, Huawei has the technical strength and scene penetration ability of AI, and can provide college teachers and students with the technology to solve the most basic problems. From the introduction of Ascend Teng series chips, Huawei announced the full-stack and full-scene AI strategy. With Atlas intelligent computing platform and a series of development tools, Huawei has become the best solution for AI computing power and development penetration in Chinese technology enterprises. The lack of computing power and the problem of development compatibility are the first shackles that plague Chinese colleges and universities to explore AI, and this is also the answer that Huawei can become the "best friend" of colleges and universities.

Second, open ecology and training talents are the characteristics of Huawei. As the fifth way of Huawei's AI strategy, talent strategy is indispensable in Huawei's AI territory. Training a sufficient number of AI developers and professionals who can go deep into various industries is also the most complementary benefit solution in line with Huawei's AI development strategy. The integration of openness, ecological support and AI business makes Huawei the most sincere and powerful educator.

Third, the investment in technological research and development has become the core of Huawei's enterprise spirit. According to the data just released, in 2018 Huawei became the only Chinese company to enter the top 10 in R & D investment in the world, spending more than BAT combined. Betting on education and betting on the future is Huawei's consistent code of action, and it is also the most anticipated way of landing AI in Chinese education today.

There is no doubt that AI and education are both major events in China. When the two meet, the responsibility bearers of the times have no possibility of flinching.

Wind and rain are also the things of Huaxia.

Combined with the basic education system, to build an omni-directional and deep-seated AI talent training mechanism is a work that most enterprises know is correct but can not try. Because the effect is too slow, the direct effect on the enterprise is limited. However, if every enterprise chooses to protect the interests of the flies in front of the waves of the times, then the productivity innovation brought about by new technology will become empty talk.

Although it is the most complex and long-term investment, it is a necessary investment for China's AI industry today. In this critical node, Huawei chose to move forward bravely and make long-term investment for industrial co-prosperity, opening a bright window for the whole AI symbiosis society in the future. We have reason to believe that the 100-school AI summit is not the final plan for Huawei AI education, but the starting point and source of the huge plan. For the integration of AI, higher education and basic disciplines, there is a mountain of hard work waiting to be cracked, but the foolish man wielding a hoe cannot stop.

AI is good, and AI is hard, but the AI industry needs people who work hard, people who work hard. Promoting AI through education is such a success, and the road lies in the present.

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