【Editor’s Note】On October 27, 2019, the “Future Has Arrived: The Fourth Industrial Revolution and China’s Future Studies Seminar” was held in Room 302 of the School of Public Management, hosted by Tsinghua University’s National Conditions Research Institute and co-organized by the editorial department of “Cultural Horizons”. Scholars from different disciplines and industry practitioners engaged in cross-disciplinary discussions on how to understand the Fourth Industrial Revolution and its impacts, as well as the possibilities of future studies.
Li Qinglong, president of Wisdom Star, delivered a keynote speech titled “Understanding the Fourth Industrial Revolution from the Perspective of Wisdom Star’s Data Applications”. The following is a整理 based on Mr. Li Qinglong’s speech, which has been approved by him.
◢ Focus｜The Fourth Industrial Revolution and China’s Future Studies Seminar Held
Good day to all the teachers and industry experts. Thank you to the previous two speakers for their insights. Compared to the previous two, Wisdom Star is relatively small, focusing on B2B business. Here, I will share my humble understanding of the Fourth Industrial Revolution based on Wisdom Star’s practical work. Please feel free to criticize and correct any inaccuracies.
The Core Tenets of the Fourth Industrial RevolutionFirst is digitalization, second is intelligence.The foundation of the Fourth Industrial Revolution is to fully digitize the entire society, development, and processes, thus allowing some intelligent factors to be integrated into societal development. The digitalization process includes the integration of technologies and applications such as artificial intelligence, Internet of Things, cloud computing, big data, and smart manufacturing. Ultimately, these integrations aim to achieve comprehensive digitization of all societal processes. Digitalization is also a prerequisite for intelligence.
Let’s discuss the current aspects of society that can be digitized, which can be categorized into four areas.
The first aspect is the digitization of the machinery production process.
The second is the digitization of typical Internet public data, which is the area Wisdom Star is engaged in.
The third includes the inherent internal data stored in various government and enterprise sectors.
The fourth is behavioral data, which is primarily generated by operators and various platforms.
Data types can be categorized into structured, semi-structured, and unstructured. Structured data is easy to understand, but currently, there is a large volume of non-structured data, such as videos on Kuaishou, which are typical representatives of non-structured data. In fact, over 80% of data is unstructured. The single piece of information we view daily, be it an article, an image, a voice clip, or a video, may seem to convey certain information, but it actually contains a wealth of data value that can be mined.
As Mr. He mentioned earlier, short videos may be the core of future artificial intelligence. We have different understandings; I believe that non-structured data has more application scenarios within it. In practical scenarios, video analysis is important, but from a long-term perspective, we believe that NLP technology will play a very important role in the future transformation from digitalization to intelligence.
There is a general understanding of the digitalization process, which includes both shallow and deep aspects. On a shallow level, it refers to the process of digitizing people, objects, and production relationships. Much of the work we are currently doing, such as automating enterprise OA systems and various office systems, has already reached a relatively high degree of informatization.
However, the problem with these systems is that they essentially only achieve the systematization of office processes, which cannot be considered true digitization. Moreover, in a sufficiently large enterprise or organization, one will find significant information asymmetry between multiple systems. The systems cannot achieve digital interoperability, and there is a need for a tool or method to facilitate digital communication. In fact, most B2B enterprises we see in the market are still in this field, working to bridge the digital divide by consolidating data into a wide table for joint querying and application.
In the future, it may be necessary to advance deeper digitalization, including intelligent infrastructure, intelligent production lines, intelligent logistics, and intelligent applications, ultimately leading to the intelligentization of production and lifestyle, thereby improving people’s satisfaction with life.
The First Case is from early 2007 when we collaborated with CCTV’s Economic Channel on the theme program “Even the Smallest Voice Can Be Heard”, which was essentially a large-scale public opinion survey. One particularly important topic was the social analysis of the “Two-Child Policy”.
We know that once a policy is released, it will have a significant impact on society, but what exactly is the social feedback and manifestation of this policy? In many situations, it is challenging to measure accurately. The traditional approach often involves designing a complete set of survey questionnaires, distributing them through various online and offline channels, and finally deriving conclusions through extensive manual statistical analysis. This process often takes more than half a month to a month. Furthermore, the sample size for data collection is very limited; for offline surveys, it is generally challenging to exceed 2000 samples, while online surveys might reach 100,000 or 200,000 at most.
Through Internet big data, we found that the evaluation data regarding the Two-Child Policy on the Internet exceeded 100 million. We can conduct statistical analysis on nearly 100 million comments regarding the Two-Child Policy in real-time. This is why we emphasize that Internet public data is a crucial element in the Fourth Industrial Revolution, as it embodies a virtual society that largely reflects our real society on the Internet—what we prefer to call social-perceived data.
Through in-depth analysis of social-perceived data, one can evaluate and understand the actual response of a policy or event in society.
The Second Case involves our work on the construction of the media integration center in Yanqing District, under the broader context of national county-level media integration. We proposed the concept of “Yanqing in the Eyes of the World”. Why did we mention this concept? Because Yanqing has to establish its image in the eyes of the world, especially with the past World Expo and the upcoming Winter Olympics. However,it has been difficult to scientifically and fairly evaluate such image establishment in the past. Based on real-time monitoring of relevant Internet big data, we constructed models to evaluate it, comparing it with Sochi and Pyeongchang. We also assisted them in better communicating Yanqing as a world-class event host. Of course, our concept of “In the Eyes of the World” also includes the image in the eyes of domestic citizens and Beijing residents, all of which can be visually represented through real-time digitization.
The Third Case is about recruitment websites. We know that if someone posts a question on a platform but there aren’t enough people online at that time, the question may go unanswered, leading to a lack of engagement. Therefore, an intelligent recommendation system is needed to provide timely answers to users’ inquiries, enhancing user retention and engagement. Recently, at the Wuzhen Internet Conference, Li Yanhong proposed the concept of “All Questions Will Have an Intelligent Answer”, which we also endorse.
The Fourth Case concerns the application of the 12345 platform. Traditionally, work order handling has been linear; upon receiving a request, a work order is created and assigned to the relevant functional unit, which is a single chain. Comprehensive digitalization can help obtain a good demographic profile and demand handling map, improving work order processing efficiency.
Wisdom Star’s contributions include real-time digitization of all publicly available text, voice, and video content on the Internet, extracting digital resources from what seems to be incalculable text content. Currently, the total amount has exceeded 200 billion entries, with an addition of 400 million daily, providing a good source of social-perceived data.
Secondly, we have built a text superbrain middle platform that can correspond to all data, including real-time structured processing of internal organizational data, while establishing a knowledge graph engine for data relationship mapping. In the future, we hope to leverage Wisdom Star’s data and computational capabilities to create basic supply capabilities for all those who wish to create value in this area.Thank you all!
Text整理｜Liu Haoyan English Editing｜Wang Qizhen Wang Hongshu
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