Under the third wave of AI, how do humans meet the opportunities and challenges?

21st Century Business Herald reporter Luo Yiqi reported from Guangzhou

The possible negative impacts of the rapid explosion of artificial intelligence are being taken seriously.

Recently, the AI ​​field has once again triggered a round of open letters led by industry leaders. It contains only one sentence: Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war. Like pandemics and nuclear war, becoming a global priority.)

(Screenshot of part of the open letter)

On the one hand, this drives the need for relevant regulations to be implemented quickly, and this action may need to be jointly promoted more broadly; on the other hand, it also shows that this round of AI industry development has reached a particularly rapid turning point.

During the 2023 Xiaomanyao Technology Conference and AIGC Artificial Intelligence Summit held recently, Meng Meiling, professor and director of the Department of Systems Engineering and Engineering Management at the Chinese University of Hong Kong, also told the 21st Century Business Herald reporter that is clearly generated While formal AI will bring great impetus to the digital economy, there are also many risks that must be taken into consideration. In terms of AI ethics, fake news, infringement, etc., it is necessary to clarify how to protect personal rights and interests from the legal and regulatory level. At the same time, individuals must also be more vigilant in the process of using large AI models.

Looking back at history, Zhu Jiaming, an economist and chairman of the Academic Technology Committee of the Digital Finance Research Institute of the Hengqin Guangdong-Macao Deep Cooperation Zone, said that the AI industry has developed for at least 70 years today and can be divided into three stages. : First, it is based on "Machines and Intelligence" published by Turing in 1950 as the starting point; second, it is an artificial intelligence conference held in 1956. Until 2012, deep learning entered a new stage, which lasted for more than 50 years. ; The third is the full arrival of the large model era starting in 2022.

Zhu Jiaming pointed out in an interview that the basic feature of the big model era is to integrate artificial intelligence more closely with human life, economy, learning and education models. This forced change on humanity will be unprecedentedly intense. Therefore, human beings' worries are quite reasonable. What is important now is to popularize education to ensure that the public will not panic or reject it. First, they should learn to understand and apply it. ”

AI Development Wave

During the aforementioned summit, Zhu Jiaming said in his speech, “In this era of large models, there are several basic characteristics: a large model is based on artificial neural networks; Legoization, all models will be combined in different ways to form Large model cluster; pre-training promotes parameter scale, and large models cause the data storage scale to transform to the EP, ZP and even YP stages; more importantly, it has the ability and pattern to understand natural language, and has formed a thinking chain, and then moves towards a thinking tree (ToT); In particular, a huge corpus is required; artificial feedback and reinforcement learning mechanisms are implanted in cybernetics; it provides a great platform for hybrid quantum-classical computing."

The core value of AI is also more diversified: first, it accelerates the trend of artificial intelligence Internet or Internet artificial intelligence; second, it triggers a revolution in knowledge, learning and education, because it changes the knowledge graph; other The third is to change the paradigm of scientific research, that is, human beings have entered a historical stage in which basic scientific research relies heavily on artificial intelligence; the fourth is to accelerate the formation of a cross-over group of mixed intelligence. Human beings are no longer the only component of intelligence, but will enter the human and The era of thinking subject that combines artificial intelligence and machine intelligence; the fifth is to trigger profound changes in the economic structure and economic system; the sixth is to reconstruct the model of human society, physical space and information space.

"Personally, the era of large models is promoting the generalization of artificial intelligence, that is, general artificial intelligence (AGI). This pace is accelerating. " Zhu Jiaming believes that in the next three years, it will be The fourth wave of artificial intelligence development is mainly manifested in the combination of artificial intelligence and industrial applications. In particular, everyone's life style will change, and it will quickly penetrate into all stages of education from preschool to high school.

In an interview with a reporter from the 21st Century Business Herald, he said that when everyone talked about digitalization, their understanding of it was relatively shallow. Today, the profound foundation of digitalization has become artificial intelligence. In this case, the policy level needs to play an important role in giving new connotations to the original technology, which is to promote the full entry into the intelligent era.

As AIGC continues to move forward, everyone will have their own digital avatar in the future, and the artificial intelligence Internet will also be here. "This is equivalent to a large-scale immigration of human thinking patterns and behaviors, which requires a leap to the intelligent era. This will affect the world's population of 8 billion and will require a long process." Zhu Jiaming said.

In the future, the intelligent form of digital people will form the Internet, similar to the WeChat group that transcends existing people. But the most important thing is to bring about great changes in the way people learn. "He continued that from this point of view, the profession that faces the greatest challenge should be teachers, because the speed and effect of students' learning at that time may be much higher than the speed of teachers' teaching.

How big models affect society

At the specific implementation level, how will AI large models penetrate into vertical fields and even personal professional roles layer by layer?

Chen Shi, investment partner of Fengrui Capital, pointed out when sharing that from the perspective of generative AI entering vertical industries, it must be predicted from the perspective of the next ten years.

"Personally, ten years from now will be the era of building neural intelligence models. The top layer is a full-stack large-scale language model, which is a model similar to GPT4. This model aggregates all human knowledge and capabilities. It can even surpass human intelligence and can empower all walks of life. But this opportunity will be rare." He continued that for the next level of industry, it may be necessary to establish an industry vertical model and use existing knowledge, laws, Unstructured text is used as training data and instilled into the language model to produce an intelligent model. This is like a large tool library that can empower industry process reengineering and empower every link.

Further down, "Enterprises must have their own models in the intelligent era, and the enterprise model must have depth, otherwise it may be penetrated. The so-called depth refers to whether it has the ability to understand the upper-level general model. Irreplaceable uniqueness, otherwise the ability will be easily replaced by the upper-level model." Chen Shi pointed out that to the employee's personal model will be divided into two parts, one is based on the capabilities required by the position model Quality is built using thinking data and cognition; the other type is a model that can be tooled, such as co-pilots, intelligent assistants, etc.

"I think ten years from now, it will be an era of extensive model construction. The software layer will become very thin, and most of them will be models. " He continued that before entering the vertical industry, there are still There is basic work to be completed, namely digitization and onlineization.

Dataization solves the problem of data sources. Without data composed of knowledge, rules, etc., it is impossible to establish a model and train it; onlineization can truly embed intelligent capabilities into the scene. In the future, the competitive advantage of industries or enterprises may be reflected in the models built using these data. ”

Meng Meiling analyzed to the 21st Century Business Herald reporter that in the field of education that has attracted much attention, AIGC can already help teachers quickly solve some teaching tasks, such as giving preliminary suggestions when setting questions, and then teachers make targeted adjustments based on the suggestions. . This process will significantly improve the overall efficiency of teaching and learning. AI can provide some correction comments when revising students' articles, helping teachers save time and focus their energy on motivating students.

I think ordinary people should also increase their understanding of AIGC technology, not just people who study science and technology. She also holds the view that humans should actively use large-scale modeling tools to continuously improve productivity and efficiency.

"Although GPT4 is very powerful, the more applications it has, the more deficiencies can still be seen. This means that the current GPT4 is still far from human intelligence. However, it has a large-scale knowledge base and powerful computing power behind it. In contrast, the human brain It is not fair to compare with the limited memory of artificial intelligence. As for how far we are from general artificial intelligence, it is still difficult to predict, but I estimate that the compatibility between humans and AI will be stronger in the future, because AI Where humans are weak is where humans are strong. " Meng Meiling concluded.

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